i-eeg: a software tool for eeg feature extraction, feature selection and classification
TRANSCRIPT
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Dear ISAIA 2013 Participant;
We would like to welcome you to Girne American University.
GAU’s goal is to become a University with and without walls, a University located in time and place but unhampered by constraints of either in the fulfillment of its mission. To do this, GAU maintains constant awareness of the impact of technology and how it changes knowledge and learning. GAU evaluates its courses, and programs to be sure that the curriculum and learning strategies reflect these changes.
Faculty of Engineering and Architecture, which was established in1992,was separated into two faculties in 2009. Faculty of Engineering started to function from 2009-2010 academic year on. Faculty of Engineering aims to educate fully qualified engineers in all aspects. In today’s competitive environment, the engineers who are the graduates of GAU Faculty of Engineering, are aimed to be fully equipped with technological, language and engineering skills. The vision of Faculty of Engineering is to become comprehensive, distinct faculty that is recognized both nationally and internationally in engineering teaching, research and development. The mission is to create and disseminate knowledge through creative inquiry, to provide the high standards in engineering education and to serve our students by teaching them how to become contemporary engineers who are culturally informed and well equipped with technological skills. In carrying out its mission, Faculty of Engineering commits to continually evaluating, improving and evolving its programs and stimulates meaningful research and service to community by which they belong to. As a result of the continous quality improvement studies, Faculty of Engineering was awarded ASIIN Accreditation in December 2012 for Computer, Electrical and Electronics and Industrial Engineering Departments.
Within this context The First International Symposium on Engineering, Artificial Intelligence and Applications (ISEAIA 2013)is devoted to play a unique role in providing a platform for researchers, practitioners, developers and educators to share their experiences in the fields of engineering, artificial intelligence and their applications in a friendly environment. We will find the opportunity to provide communication among researchers and to encourage multi-disciplinary and inter-disciplinary researches by ISEAIA 2013.
We are proud to inform you that this conference has exceeded all our expectations. As part of the symposium, you will be able to attend 14 presentation sessions and 3 keynote addresses. This symposium attracted almost 108 attendees from 12 different countries.
We sincerely hope you have an outstanding stay in Kyrenia.
With warm regards,
Assoc. Prof. Dr. Zafer Ağdelen
Symposium Chairman
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Chairman
Assoc. Prof. Dr. Zafer Ağdelen, Girne American University
Organizing Committee Members
Prof. Dr. Sadık Ülker, Girne American University
Prof. Dr. Adalet Abiyev, Girne American University
Assoc. Prof. Dr. Ali Haydar, Girne American University
Assoc. Prof. Dr. Kamil Dimililer, Girne American University
Assoc. Prof. Dr. Kabir Sadeghi, Girne American University
Asst. Prof. Dr. Burcu Toker, Girne American University
Asst. Prof. Dr. İbrahim Erşan, Girne American University
Prof. Dr. Olgun Çiçek, Girne American University
Asst. Prof. Dr. Asım Vehbi, Girne American University
Asst. Prof. Dr. Sualp Davut, Girne American University
Ülkü Taşseven, Girne American University
Elvira, Sabirova, Girne American University
Executive Committee Members
Prof. Dr. Ali Zeki, Girne American University
Assoc. Prof. Dr. Bülent Bilgehan, Girne American University
Asst. Prof. Dr. Tamer Tulgar, Girne American University
Asst. Prof. Dr. Ali Özyapıcı, Girne American University
Asst. Prof. Dr. Mehmet Okaygün, Girne American University
Dr. Serkan Sancak, Girne American University
Dr. Ezgi Deniz, Girne American University
Buğçe Eminağa, Girne American University
Sabriye Topal Karanfiller, Girne American University
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Scientific Committee
Adalet Abiyev, Girne American University, North Cyprus
Adnan Khashman, Near East University, North Cyprus
Akın Cellatoğlu, European University of Lefke, North Cyprus
Amir Karshenas, North Carolina, Raleigh, USA
Alexander Kostin, Girne American University, North Cyprus
Ali Akbar Aghacoochack, Tarbiat Modares University , Iran
Ali Akbar Ramezanianpour, Amir Kabir University of Technology, Iran
Ali Erhan Öztemir, Girne American University, North Cyprus
Ali Haydar, Girne American University, North Cyprus
Ali Okatan, KTO Karatay University, Turkey
Ali Uzer, Fatih University, Turkey
Nusret Tan, Inönü University, Turkey
Hasan Demirel, Eastern Mediterrenean University, Turkey
Mehmetali Salahli, Çanakkale Üniversity, Turkey
Bekir Karlık, Selçuk Üniversity, Turkey
Ali Özyapıcı, Girne American University, North Cyprus
Ali Zeki, Girne American University, North Cyprus
Alireza Sadeghi, FMC Technologies, Norway
Atanas Lazarov, Technical University of Sofia, Bulgaria
Audrius Senulis, Klaipeda University, Lithuania
Behrooz Asgarian, K.N. Toosi University of Technology, Iran
Buğçe Eminağa, Girne American University, North Cyprus
Bülent Bilgehan, Girne American University, North Cyprus
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Burcu Toker, Girne American University, North Cyprus
Cem Ergün, Eastern Mediterrenean University, North Cyprus
Cengiz Kahraman, Istanbul Technical University, Turkey
Ekrem Varoğlu, Eastern Mediterrenean University, North Cyprus
Eleonora Guseinoviene, Klaipeda University, Lithuania
Emine Mısırlı, Ege University, Turkey
Ethem Tolga, Galatasaray University, Rector, Turkey
Ezgi Deniz Ülker, Girne American University, North Cyprus
Fayaz Rahimzadeh Rofooei, Sharif University of Technology, Iran
Farman N. Mammadov, Azerbaijan International Operating Company, Azerbaijan.
Gökhan Gökmen, Marmara University, Turkey
Güneş Gençyılmaz, Aydin University, Turkey
Hakan Altınçay, Eastern Mediterrenean University, North Cyprus
Hamid Torpi, Yıldız Technical University, Turkey
Hüseyin Ademgil, Eurepean University of Lefke, North Cyprus
İbrahim Bay, Cyprus International University, North Cyprus
İbrahim Erşan, Girne American University, North Cyprus
Kabir Sadeqhi, Girne American University, North Cyprus
Kamil Dimililer, Girne American University, North Cyprus
Karuppanan Balasubramanian, Eurepean University of Lefke, North Cyprus
Kemal Leblebicioğlu, Middle East Technical University, Turkey
Manafaddin Namaz, Baku Higher Oil School, Baku, Azerbaijan.
Mario Gatchev, Technical Director of Skygate, Bulgaria
Mehdi Elmi, Best West Engineers Ltd., Canada
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Mohammad Hassan Baziar, Iran University of Science & Technology , Iran
Muhammed Salamah, Eastern Mediterranean University, North Cyprus
Murat Akkaya, Girne American University, North Cyprus
Murat Başkak, Istanbul Technical University, Turkey
Mustafa Babagil, Girne American University, North Cyprus
Mustafa Güneş, Gediz University, Turkey
Naila Allakhverdiyeva, Baku Higher Oil School, Baku, Azerbaijan.
Novruz Alahverdi, Konya University, Turkey
Aghamirza Bashirov, Eastern Mediterrenean University, North Cyprus
Nureddin Kırkavak, Çankaya University, Turkey
Oliver Francis, University of Luxembourg, Luxembourg
Özgür C. Özerdem, Near East University, North Cyprus
Özlem Ünverdi, Yildiz Technical University, Turkey
Kaya Menteşoğlu, UCLA International Institute, USA
Pınar Özbeşer, Girne American University, Canterbury Campus, England
Rafik Aliyev, Azerbaijan National Academy of Sciencies, Azerbaijan
Rahib H.Abiyev, Near East University, North Cyprus
Doğan İbrahim, Near East University, North Cyprus
Asaf Varol, Fırat University, Turkey
Ömer Faruk Bay, Gazi University, Turkey
Ramiz Humbatov, Baku Higher Oil School, Baku, Azerbaijan.
Rehim Memmedov, Azerbaijan State Oil Academy, Baku, Azerbaijan.
Reza Abbasnia, Iran University of Science & Technology , Iran
Ron French, Girne American University, Canterbury Campus, England
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Sabriye Topal, Girne American University, North Cyprus
Serdar Ethem Hamamcı, İnönü University, Turkey
Serhat Şeker, İstanbul Technical University, Turkey
Serkan Sancak, Girne American University, North Cyprus
Sofiane Amziane, Université Blaise Pascal, France
Soydan Redif, European University of Lefke, North Cyprus
Tahir Çetin Akıncı, Kirklareli University, Turkey
Tamer Tulgar, Girne American University, North Cyprus
Tayfun Turgay, Girne American University, North Cyprus
Tolgay Karanfiller, Girne American University, North Cyprus
Urfat Nuriyev, Ege University, Turkey
Vahid Chegini, Iranian National Institute for Oceanography, Iran
Vali Bashiry, Cyprus International University, North Cyprus
Yasemin Fanaeian, Girne American University, North Cyprus
Yassir Osman, Shinas College of Technology , Sultanate of Oman
Zafer Ağdelen, Girne American University, North Cyprus
Zakir Hasanov, Azerbaijan State Oil Academy, Baku, Azerbaijan
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Keynote Speakers
Prof. Dr. Kemal Leblebicioğlu Prof. Dr. Kemal Leblebicioğlu is a full professor of Electrical and Electronics Engineering Department of METU since 1999. He has a background in optimization, optimal control theory, computer vision, intelligent systems, flight control, walking robots and unmanned vehicles. He got a Ph.D. from the Mathematics Department of Middle East Technical University, on 1988, His Ph.D. thesis is “An Optimal Control Problem with Nonlinear Elliptic State Equations”. He has authored many journal papers, book chapters and numerous conference papers. He is in several IFAC technical committees. He was the editor of the Journal “ELEKTRIK” published by TUBITAK (Turkish Scientific
and Technical Research Council) from 1996 to 2009. He is in the editorial board of several Turkish technical journals. He conducted several R&D projects as project leader and researcher. Nowadays he is studying on unmanned vehicles, in particular, unmanned air and underwater vehicles. He has completed a project (supported by TUBITAK) on the construction of a special unmanned undersea vehicle, called ULISAR, which is a mixture of a ROV and a fully automated system. His current projects, also supported by TUBITAK, is on the coordinated guidance of multiple unmanned air vehicles and on the design of a small intelligent ROV. Presently, he is also working as an advisor for YEGAM, a Bahcesehir University Foundation, about matters related to education, developing educational systems to help students and teachers, intelligent testing and student evaluation systems. Hierarchical Decision Making Systems The common practice in multi-level Decision-Making (DM) systems is to achieve the final decision by going through a finite number of DM levels. In this study, a new multi-level DM model is proposed. This model is called as Hierarchical Decision Making (HDM) model and it is supposed to provide a flexible way of interaction and information flow between the consecutive levels that allows policy changes in DM procedures if necessary. In the model, in the early levels there are primary agents that perform DM tasks. As levels increase the information associated with these agents are combined through suitable processes and agents with higher complexity are formed to carry out the DM tasks more elegantly. HDM model is applied to the case study “fault degree classification in a four-tank water circulation system”. For the case study, the processes that connect the lower levels to the higher levels are agent development processes where a special decision fusion technique is its integral part. This decision fusion technique combines previous level decisions and their performance indicator suitably to contribute to the improvement of new agents in higher levels. Additionally, the proposed agent development process provides flexibility both in the training and validation phases and less computational effort is required in the training stage compared to a single (similar capacity) agent development simulation carried out for the same DM task in similar circumstances. Hence HDM model puts forward an enhanced performance compared to single agent with more sophisticated structure. Finally model validation and efficiency in the presence of noise are also simulated. The adaptability of the agent development process due to the flexible structure of the model also accounts for improved performance as seen in the results.
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Another application where hierarchical decision making is the critical issue is the famous “Weapon Target Assignment” problem which is the problem of assigning weapons to threats with the objective of minimizing the expected survival value of threats. Here, a novel approach called “Hierarchical Fuzzy Decision Maker” is considered as an alternative decision-aid system for the Weapon Target Assignment. The idea is to increase approximation performance through cascaded stages. The proposed procedure is applied to implement a Hierarchical Fuzzy Decision Maker for a number of randomly sampled Weapon Target Assignment instances on a realistic scenario. The simulation results show that identified systems have satisfactory performance and serviceable on the battlefield. Finally, as an alternative to hierarchical decision making system, the concepts of “local” and “global” decision making will be introduced. These ideas will be discussed on case studies similar to the ones discussed above.
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Prof. Dr. Derviş Karaboğa Prof. Dr. Derviş Karaboğa received the Master degree in Electronics and Communication Engineering from the Technical University of Istanbul in Turkey and PhD degree in Systems Engineering from School of Engineering, Cardiff University in UK in 1989 and 1994, respectively. He is a Full Professor in Computer Science at the Department of Computer Engineering, University of Erciyes, Turkey and also the head of the intelligent systems research group in the department. He is one of the authors of the book “ Intelligent Optimisation Techniques” published in 2000 by Springer-Verlag and also the author of the book “Artificial Intelligence Optimization Algorithms” published in 2004
and second version in 2012 by Nobel, in Turkish. His research interests include evolutionary computation, neural networks, fuzzy systems and their applications. He began to be interested in the intelligent behaviours of honey bee swarms in 2001 and then introduced “Artificial Bee Colony (ABC) algorithm”, which simulates their intelligent foraging behaviour, into the literature in 2005. Now, ABC (http://mf.erciyes.edu.tr/abc/) is one of the most widely used swarm intelligence based optimisation algorithms to solve real-world optimisation problems. Swarm Intelligence and Artificial Bee Colony (ABC) Approach for Optimization Problems Swarm intelligence (SI) is briefly defined as the collective behaviour of decentralized and self-organized swarms. The well known examples of this type swarms are bird flocks, fish schools and the colony of social insects such as termites, ants, bees etc. Two SI based optimization approaches introduced in 1990s, which are based on the behaviour of ant colony (Ant Colony Optimization-ACO) and fish schooling/bird flocking (Particle Swarm Optimization-PSO), have highly attracted the interest of researchers. Although the swarm intelligence features are clearly seen in honey bee colonies, unfortunately the researchers have recently, especially from the beginning of 2000s, started to be interested in the behaviour of these swarm systems. During a decade, several algorithms have been developed depending on different intelligent behaviours of honey bee swarms. Among those, artificial bee colony (ABC) is the one which has been most widely studied on and applied to solve the real world problems, so far (http://www.scholarpedia.org/article/Artificial_bee_colony_algorithm). Day by day the number of researchers being interested in ABC algorithm increases rapidly. The purpose of this speech is to provide an overview of SI and SI models, and then to focus on the principles of Artificial Bee Colony. The simple actions executed by the individual agents in ABC and the effect of control parameters on the performance of the algorithm will be discussed in detail. The presentation also includes the advances with ABC and its applications.
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Prof. Dr. Sadık Ülker Prof. Dr. Sadık Ülker received the M.E.E. degree in Electrical Engineering and the Ph.D. degree in Electrical Engineering from the University of Virginia in May 1999 and January 2002, respectively. He has a B.S. degree in Electrical Engineering from University of Virginia (1996). He has worked in the research labs of University of Virginia during his graduate studies. He received Louis T. Rader graduate research award in June 2001 from the university for his research on sampled-line network analyzers. Later he worked as a post-doc in University of Virginia Millimeter Wave Laboratory for 6 months. In September 2002 he joined to the Girne American University faculty of Engineering and
Architecture, Electrical Engineering Department. From September 2003 till October 2005, he was appointed as Vice Dean of Engineering and Architecture Faculty. From November 2005 till July 2007 he was appointed as Vice Rector to the University responsible from the academic affairs. In April 2009 he was promoted to the Associate Professor Status. Starting April 2009 he has been Vice Rector responsible from Academic Affairs. He is a member of IEEE since 1992, IEEE-MTTS and IEEE-APS since 1996, and a member of Eta Kappa Nu since 1995. Particle Swarm Optimization in Microwave Circuits Metaheuristic algorithms have been widely used in the optimization of engineering design problems. Because of this rising interest in electrical engineering optimization problems, a special issue for electromagnetic and microwave circuit design using these metaheuristic algorithms was done in March 2007. One of the most popular metaheuristic algorithm is Particle Swarm Optimization. Although the particle swarm optimization was introduced in 1995, the application to electromagnetics was not until 2004 and to microwave circuits was not until 2005. Since then, many papers were published which simply suggested the use of PSO in the optimization of microwave circuits. Some examples for optimization problems are; design of microwave filters, microwave microstrip antennas, microwave matching circuits, microwave couplers, microwave power dividers, and microwave amplifiers. In this speech emphasis will be given on how Particle Swarm Optimization can be applied to solve some of these microwave circuits.
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List of Abstracts An Overview on Design, Construction and Installation of Offshore Template Platforms Suitable for Persian Gulf Oil/Gas Fields .............................................. Assessment of ICZM Application and Requirements of Master Plan for Construction of Harbors in North Cyprus.............................................................. Advantages of the Walsh Functions in the Measurement of Reactive Power in the Electric Power Systems.................................................................................... Seasonal Artificial Neural Network Models for Predicting Hourly PM10 Concentrations Using Lagged Inputs Revealed by PCA....................................... New Integral Transform for Solving Differential Equations in Engineering Applications .......................................................................................................... ANN Based Prediction of Flow And Heat Transfer Between Two Tandem Square Cylinders Near The Wall........................................................................... ANALYSIS OF THE HARMONIC PROBLEMS IN THREE PHASE TRANSFORMERS AND SOLUTION BY A PROPOSED FILTER................... Deutsch Algorithm In Two Valued Logic............................................................. UAV Route Planning For Maximum Target Coverage......................................... A Local Optimization Technique for Assigning New Targets to the Planned Routes of Unmanned Aerial Vehicles.................................................................... Model-based Test Case Prioritization Using Neural Network Classification........ Earthquake Data Modeling Using Artificial Neural Networks and Time Series Analysis ................................................................................................................. Simulated Annealing Approach for Timetabling Problem.................................... A Tabu Search Algorithm for Green Capacitated Vehicle Routing Problem........ A modified ant colony optimization algorithm for asymmetric traveling salesman problem................................................................................................... An improved artificial bee colony algorithm for attractive traveling salesman problem ................................................................................................................. Detection and Localization of Abnormality of Crowd.......................................... Modelling of Driver Lane Choice Behaviour with Artificial Neural Network (ANN) and Lineer Regression (RL) Analysis on Deformed Roads......................
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Geothermal Energy Potential of Turkey by Utilising the Airborne Magnetic Data ....................................................................................................................... QUALITY FUNCTION DEPLOYMENT AND ITS APPLICATION ON A SMARTPHONE DESIGN..................................................................................... TRIZ: Theory of Inventive Problem Solving and Comparison With Other Problem Solving Techniques................................................................................. A predictive model for compressive strength of the concretes incorporating volcanic ash............................................................................................................ A New Approach for Improving the Performance of Support Vector Machines for Maximal Oxygen Uptake Prediction................................................................ Prediction of Maximal Oxygen Uptake Using Multilayer Perceptron and Multiple Linear Regression Combined with Feature Selection............................. Prediction of Upper Body Power of Cross-Country Skiiers Using Artificial Neural Networks.................................................................................................... Performance Evaluation of Nonparametric Adaptive Techniques for MIMO Radar Target Detection.......................................................................................... Measurement of OSPF-MPLS-TE-FRR Line Transitions and Data Losses.......... Analysis of Incident-Level Crime Data Using Clustering with Hybrid Metrics.. BREAST CANCER DIAGNOSIS VIA DATA MINING: PERFORMANCE ANALYSIS OF SEVEN DIFFERENT ALGORITHMS..................................... Investigating the Effect of Questionnaire Variables on the Prediction of Maximal Oxygen Uptake Using Multilayer Perceptron and Multiple Linear Regression ............................................................................................................. i-EEG: A Software Tool for EEG Feature Extraction, Feature Selection and Classification ......................................................................................................... Ultimate Strength of Composite Beam with Web Openings Subjected to Combined Interaction of Positive Bending and Axial Tension............................. Application of Petri nets to decrease the path dependent loss and the switch cross talk in optical network.................................................................................. Fuzzy Quantities and Interpretative Processing in Decision Making for Expert Systems ................................................................................................................. WIRED AND WIRELESS COMMUNICATION TECHNIQUES AND APPLICATIONS IN RAILWAY SYSTEMS.......................................................
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THE USE OF ARTIFICIAL NEURAL NETWORKS IN ANALYZING THE IMPACT OF HRM ON FIRM PERFORMANCE................................................ DESIGN AND IMPLEMENTATION OF A METEOROLOGY STATION AND WEATHER QUALITY OBSERVATION INSTRUMENT........................ GENERALIZED EVOLUTIONARY ALGORITHM: A NEW OPTIMIZATION ALGORITHM.......................................................................... Application of Particle Swarm Optimization to Microwave Tapered Microstrip Lines ..................................................................................................................... Synthesis of SiC-MoSi2-Al2O3 electrical heating elements by combustion method ................................................................................................................... Creating Surveys Using Artificial Agents............................................................. Resource throughput improvement on the cell-edge in LTE cellular systems...... Statisitical Analysis of Overall Satisfaction and Demographic Factors in State-Owned Emergency Services of North Cyprus....................................................... Perceptional Analysis of Patient Satisfaction from Health Services Provided in North Cyprus: A Case Study of Government Hospitals........................................ Behavior of Reinforced Concrete Corbels Strengthened with Ferrocement Sheets .................................................................................................................... Design and Construction of an Autonomous Unmanned Ground Vehicle (UGV) and Basic Waypoint Trajectory Tracking.............................................................. Counting Passengers in an Elevator Cabin Using Real-Time Image Processing.. Developing Virtual Driving Simulator for Educational Purposes........................ Real Time Virtual Mirror Using Kinect................................................................. Using Gravitational Force in Terrain Optimization Problems............................... An Analog CMOS Tunable Current-Mode Classifier Core Circuit with Reduced Power Consumption................................................................................ DLF Recovery WDM Optical Network Using Edge Disjoint Path with Shortest Path Method........................................................................................................... Design Patterns as First Class Citizens in Software Development........................ ISOLATED WORD RECOGNITION................................................................... Estimation of Concrete Compressive Strength with Artificial Neural Network...
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The Effects of Cure Conditions on Mechanical Properties of Polymer Modified Cement Mortars...................................................................................................... Finite Product Representation via Multiplicative Calculus in Signal Processing.. Automatic control system of discrete dosing process............................................ PROCESSING OF GEOPHYSICAL EXPLORATION DATA CONDUCTED BY SEISMOACOUSTIC WAY ON THE BASIS OF “FUZZY LOGIC” METHOD ..............................................................................................................
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An Overview on Design, Construction and Installation of Offshore Template Platforms Suitable for Persian Gulf Oil/Gas Fields
Assoc.Prof.Dr. Kabir Sadeghi Girne American University, Civil Engineering, Cyprus
Keywords: Jacket, Template, Platforms, Offshore Structure, Design, Construction, Installation.
Offshore template (Jacket) type platforms are used widely in Persian Gulf for a variety of functions and in different water depths up to 100 m. Since right planning, design, fabrication, transportation, installation and commissioning of petroleum platforms, considering the water depth and environment conditions are very important, this paper reviews the technical fundamentals and covers applications of the technical principles for the case of fixed template platforms. The overall objective is to provide a general understanding of different stages of design, construction, load-out, transportation and installation of offshore platforms in Persian Gulf considering the governing environmental condition and water depths.
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Assessment of ICZM Application and Requirements of Master Plan for Construction of Harbors in North Cyprus
Ms. Fatemeh Nouban Girne American University, Construction Management, Cyprus
Assoc.Prof.Dr. Kabir Sadeghi Girne American University, Civil Engineering, Cyprus
Keywords: ICZM, Master Plan, Construction of Harbor, North Cyprus
1. Introduction The coastal zone, where the land meets the sea, contains many of the earth’s most complex, diverse and productive ecological systems. Coastal zones are often placed under multiple and intense pressures. This can result in short-term and long-term time and changes in environmental quality leading to deterioration of the environmental, socio-economic and cultural resources. Therefore, special attention should be directed to the planning and management of coastal zones. The use of techniques which attempt to assist in managing the resulting conflicts in a sustainable way is becoming increasingly important. Well organizing and considering all parameters of planning, design, construction and operational aspects to minimize the energy, time, fuel consumption, usage of equipment and transportation is essential for construction of new harbors. In coastal zone management, studies should examine how coastal managers might apply all parameters in the framework of an Integrated Coastal Zone Management (ICZM) context. 2. ICZM ICZM is a new concept, having first been proposed over thirty years ago. It is a process for the management of the coast using an integrated approach, regarding all aspects of the coastal zone, including geographical and political boundaries, in an attempt to achieve sustainability. The purpose of ICZM is to achieve cooperative management of coastal zones, providing a means of balancing social and economic demands with the sustainable use of coastal ecosystems ensuring their use for present and future generations. ICZM implies between different levels of administration (national, regional and local), between different economic bodies that have a stake in the coast, between administration and public, and between the research community and coastal managers. Although the detailed responsibilities and powers of local government vary from State to State, in general, local authorities mange, regulate and facilitate a wide range of coastal activities. They also have various resource development and management roles. 3. Harbor Master Plan Considering all parameters related to import/export demands and the TRNC policies to develop marine and offshore industries, a recommendation to prepare a harbor master plan are proposed.
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Different types of infrastructures related to harbors that are reviewed in the harbor master planning are as follows: - Jetties and marine terminals, - Ship building and repair facilities, - Logistics facilities, - Dredging and reclamation, - Coastal, marine and offshore structures, - Loading and off-loading facilities. Study are included the following aspects: - Economics, - Environment, - Planning, - Design, - Construction, - Operations, - Maintenance. Factors to be considered when selecting the type of structures: - Layout, - Environmental conditions, - Operational conditions, - Navigation requirements, - Construction conditions and period, - Construction cost, - Availability of construction material, - Maintenance. 4. Summary of formulation to evaluate the best location of harbors To find the best location of a new harbor by implementation of the data, a computer application entitled HaLoFin (Harbor Location Finder) is developed by the authors. In this regard, the following method is applied: - The spherical coordinates system is used to find the distances between, harbor, cities and the harbors in other countries. - The coordinates of the location of any point on the earth is found from the Google Earth. - The coordinates of the departure points of ships from the other countries for import and the destination points of ships for export are selected as (Rf, Өf, ϕf). - The coordinates of different points examined as locations of the harbor are taken as (Rh, Өh, ϕh). - The coordinates of the center of cities inside the country or the center of gravity of distribution of population in a city or a consumption center is chosen as (Rc, Өc, ϕc). - The distance between cities and harbor and also the distance of the harbor and the harbors in other countries are calculated by using the coordinates extracted from the Google Earth and Google Maps. Latitudes (π/2 – θ) and longitudes (ϕ) for harbor coordinates (Rh, Өh, ϕh) and city coordinates (Rc, Өc, ϕc) or departure points of ships from the other countries for import and the destination points of ships for export (Rf, Өf, ϕf) are applied by using in the spherical coordinates. Since for transportation in the country in addition to waterways, the roads and railways are
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used and the tariff of transportation for unit of cargos are different Proad , Prail , Pwater and Pair are used for road, railway, water way, airplane tariff per ton (USD/ton). The transportation total price function is minimized for finding the best location of harbor (Ri, Өi, ϕi): To find new demand for a new harbor, the total demand for the country minus the amounts transported from the airports, land gates and other harbors are considered. Minimum value of TTP indicates the best location for construction of the harbor. Since the distance between the harbor and the cities should be calculated from the trajectory of the roads, railways or waterway, for the sake of more accuracy, several coordinates of points on the trajectories may be selected and the summation of distances gives the distance between a city and the harbor or between local harbor and overseas harbor.
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Advantages of the Walsh Functions in the Measurement of Reactive Power in the Electric Power Systems
Prof.Dr. Adalet Abiyev GAU, Energy Systems Engineering, Turkey
Keywords: reactive power measurement, instantaneous power signal, Walsh function, phase shift
Reactive power is an integral part of the total electric power in power systems. In spite of the negative effect of the reactive power on the normal operating of the power systems, reactive power is the inherent phenomena of the most of power system components, such as electric machinery, energy transmission and distribution systems, power transformers, etc. All these power systems components have behavior to store an electromagnetic energy, because they include the reactive components, mainly, inductance in the wide range power systems applications. That’s just the main cause for the existence of the reactive power in power systems. The higher the reactive power the larger the current required for transmission the same amount of energy from source to the user. This problem significantly reduces efficiency of the energy transmission in transmission and distribution lines. Different type of compensation circuits have been developed and applied for the increasing an efficiency of the energy transmission process through compensation of reactive power. The level of reactance to be imposed by the compensation system depends on the value of the reactive power in existing power system, that is why, proper measurement of reactive power in power systems is the one of the extremely important scientific research area. In the field of measurement of reactive power the various methods and the algorithms have been developed and published in the scientific journals and international conference proceedings during last decade. The most of the known methods for measuring reactive power are based on the digital measuring approach, although analog measurement methods are the most suitable for the application where the low-cost and simplicity are of the prime importance. Among the existing methods the reactive power measurement methods using different type of transforms such as Fourier, FFT, DFT, Wavelet, Walsh, etc form class of measurement methods designed for application as the imbedded part of complex power measurement and analysis systems. Fourier and Wavelet transforms based measurement methods require generation set of orthogonal waveforms (discrete or analog). Since these transforms require multiplication of the signals and summation them in the complex domain, application of Fourier as well as the Wavelet transform approaches are accompanied with the increase of the volume of required operations resulting to the high cost and less speed. In this aspect use of Walsh functions for reactive power measurement reduces the volume of operations required for multiplication of the input signal by the Walsh function. Since Walsh functions have only two values, +1 and -1, over the normalized period, it becomes significantly simple to perform multiplication operation. Really, the multiplication of the signal by +1 is equivalent to the original signal. In other words, signal remains unchanged. Multiplication of the given signal by -1, actually, is the same operation as the inverting of the original signal. This is main advantage of the Walsh transform based method of reactive power measurement. By use of this approach the series of instruments have been developed, investigated, and simulated for single- as well as the three-phase power systems.
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Seasonal Artificial Neural Network Models for Predicting Daily PM10 Concentrations Using Lagged Inputs Revealed by PCA
Mr. Fatih Taşpınar The University of Duzce, Environmental Engineering, Turkey
Mr. Resul Kara The University of Duzce, Computer Engineering, Turkey
Mr. Ertan Durmuşoğlu The University of Kocaeli, Environmental Engineering, Turkey
Mr. Aykan Karademir The University of Kocaeli, Environmental Engineering, Turkey
Keywords: Particulate matter, air pollution prediction, artificial neural networks, Principal Component Analysis
The health impact of particulate matter (PM) has become very important due to fossil fuels, vehicle traffic and industrial emissions for public over the past years. In the environmental sciences a lot of study managed the understanding of the PM phenomenon with forecasting ambient PM with aerodynamic diameter up to 10 µm (PM10). Vehicle emissions, forestry products industries and extended fossil fuel consumption in heating seasons cause PM air pollution considering local meteorology and hilly topography in Duzce, Turkey. In this paper we introduce a neural network (ANN) tool with lagged input scheme which is supported by Principal Component Analysis (PCA) method to forecast hourly PM10 concentrations one hour ahead in Duzce. The lagged inputs over 24-h include all hourly based meteorological parameters and PM concentrations in 2007-2013 period. Statistical analysis methods are investigated and applied to provide with an operational air quality forecasting module for PM10. The most relevant inputs of lagged variables over 24-h period revealed by PCA are used to feed the multilayer perceptron ANN (MLPANN) to forecast next hour’s PM10 concentration. Due to reasonably high seasonal variations in PM10 levels two ANN model reflecting winter and summer seasons are constructed. Use of these two seasonal and PCA optimized ANN models showed an increased the prediction performance compared to a single ANN model. Hourly fluctuations of PM10 levels reflected fairly well with the proposed approach using the ANN model, and it can be extended to take precautions for public health by an online service. Furthermore, the levels of other common air pollutants such as SO2 and NOx can be predicted using the proposed method for public and local authorities in terms of health concerns.
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New Integral Transform for Solving Differential Equations in Engineering Applications
Asst.Prof.Dr. Ali Ozyapici GAU, Engineering, Turkey
Dr. Tolgay Karanfiller GAU, Education, Turkey
Keywords: Integral Transform, Laplace Transform.
This work is aimed to define new integral transform for solving differential equations arised in different fields of engineering. The introduced integral transform includes well known integral transform method Laplace Transform as well as some of other well known integral transforms. Therefore, the given theory will be a general approach to other integral transforms. Moreover, some of examples will be considered to demonstrate the applicability of introduced integral transform.
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ANN Based Prediction of Flow And Heat Transfer Between Two Tandem Square Cylinders Near The Wall
Ms. Özge YETİK Eskişehir Osmangazi Üniversitesi, Makine Mühendisliği, Turkey
Assoc.Prof.Dr. Necati MAHİR Eskişehir Osmangazi Üniversitesi, Makine Mühendisliği, Turkey
Keywords: ANN, Tandem square cylinders, Wall Effect
The design of the flow and heat transfer between two tandem square cylinders near the wall requires more proficiency and longer times within complex calculations. Artificial neural network (ANN) is a powerful way and works rapidly to make a decisions and modeling of the processes within the expertise. The prediction were made using ANN model based on the location of cylinder, the ratio of the distance between the cylinders to cylinder size (L/D) and the ratio of the distance between cylinder and the wall to cylinder size (G/D). Consequently, the Nusselt number value is found. In this study, the back-propagation learning algorithm with three different variants; namely Levenberg-Marguardt (LM), Polak-Ribiere Conjugate (CGP) and Scaled Conjugate Gradient (SCG) were used in the network so that the best approach could be found. The most suitable algorithm was found as LM with 8 neurons in single hidden layer and R2 is 0.972. The reynolds numbers is kept low (Re=150) for this study in order to restrict the study to the 2D flow. For the two cylinders, the orientations with the existence of a wall were examined. Nonuniform grid structure was formed in x and y axes directions, and denser grid structure was used near the cylinder and the wall. The flow between the two tandem cylinders were analyzed separately for cases with a plate. When there is a plate in the vicinity of the cylinders, very different results were reached due to lack of symmetric flow.
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ANALYSIS OF THE HARMONIC PROBLEMS IN THREE PHASE TRANSFORMERS AND SOLUTION BY A PROPOSED FILTER
Assoc.Prof.Dr. Özgür Cemal Özerdem Near East University, Electrical and Electronic Engineering, Northern Cyprus
Mr. Ibrahim Rashid Balani Near East University, Electrical and Electronic Engineering, Iraq
Keywords: Three Phase Transformers, Non-linear loads, Harmonic reduction
In recent years, there has been an increased concern about the effects of nonlinear loads on the electric power system. Nonlinear loads are any loads which draw current which is not sinusoidal and include such equipment as fluorescent lamp, gas discharge lighting, solid state motor drives, diodes, transistors and the increasingly common electronic power supply causes generation of harmonics. Harmonic voltage and currents affect normal operating of a three-phase transformer. As iron and copper losses increase depending on the level of harmonic and distortion, the transformer is not loaded with nominal power, thus its efficiency decreases significantly. As the efficiency of the transformer working under nominal power, operational expenses will increase, which is bad for the economy. In general transformers are designed to supply sinusoidal loads in their nominal frequencies. However, mostly transformers supply non-linear loads and these non-sinusoidal currents lead to excessive heating of the transformer, which in turn distortion its power quality. This procedure is presented in IEEE-C57-110 document by supposing that eddy current losses change with harmonic level and the square of the current. The current industry practice is to combine filters of different topologies to achieve a certain harmonic filtering goal. In this paper a combination of three tuned harmonic filters have been designed and used to mitigation harmonic distortions in three phase transformer which generated by nonlinear load (three phase full wave bridge rectifier used as nonlinear load). Two type of filter are used, C-type filters to eliminate or to reduce the effects of 5^th and 7^th harmonics, and one double-tuned filter to eliminate or to reduce the effects of 〖11〗^th and 〖13〗^th harmonics. Analytical study of combination of three tuned harmonic filters technique for proposed filters circuit shows a drastic minimization of 5^th, 7^th, 〖11〗^th, and 〖13〗^th harmonic components of the input current, with total harmonic distortion (THD) of the input current reduced from 18.51% to ~2% and power factor improved nearly to unity. Tuned harmonic filters are designed to reduce harmonic distortions to locate within the IEEE 519 harmonic voltage and current limits. The results of the proposed filters are analyzed to evaluate the effectiveness of the filter design. The aim of this study is to reduce current harmonics in a Three-phase transformer under linear and nonlinear load based on harmonic tuned filters technique in order to get current waveform near to sinusoidal waveform. For this purpose combination of two types of filters (double tuned filter and c-type filter) have been used and proposed. Therefore the broad objectives of this paper are: Studying three phase transformer under linear and nonlinear load. Analyzing the tuned harmonic filter technique for the system under nonlinear load in order to minimize harmonic distortion. Mathematical analysis of the passive harmonic filter network in order to get the equations of
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elements to design passive filters circuit. Simulating the circuit configuration with and without tuned harmonic filter, using (Mat lab Simulink) program, and comparing the waveforms results. The system is composed of two C-type filters to eliminate or to reduce the effects of 5th and 7th harmonics, and one double-tuned filter to eliminate or to reduce the effects of 11th and 13th harmonics is shown. The reactive power of each filters are 1KVAr, and the nominal voltage of capacitance are 220V which is connected in parallel with the system. It is installed in parallel with a harmonic-producing load, that is, a three-phase bridge rectifier of rating 20 kVA. The filtering performance of the ‘C’ type filter lies in between the second and third order types. The main advantage in the ‘C’ type filter is a considerable reduction in fundamental frequency losses, the double tuned filter can eliminate two harmonics and its equivalent impedance is the same as two parallel single tuned filters. This filter has the advantage of reducing the power losses at fundamental frequency as compared with two single tuned filters. In this study the passive filter technique is used to reduce harmonic distortion of the input current in three phase full wave bridge rectifier which used as nonlinear load and it’s simulated by computer using (Matlab Simulink) program. A proposed passive filter which is consist of combination of three tuned filters, two C-type filters to eliminate or to reduce the effects of 5th and7th harmonics, and one double-tuned filter to eliminate or to reduce the effects of 11th and 13th harmonics are analyzed, designed and their results are compared. Based on the theoretical analyzed and simulation results, the following points are observed: The double tuned filter can eliminate two harmonics and its equivalent impedance is the same as two parallel single tuned filters. This filter has the advantage of reducing the power losses at fundamental frequency as compared with two single tuned filters. The main advantage in the ‘C’ type filter is a considerable reduction in fundamental frequency losses When three phase transformers loaded by pure resistive load the voltage and current waveforms are in phase and there is no waveforms distortion. Total harmonic distortion THD=0.02%. When three phase transformers loaded by pure inductive load the voltage and current waveforms will be out of phase from one another. However, no waveform distortion will take place and total harmonic distortion (THD) =0.02%. When three phase transformers loaded by pure capacitive load the voltage and current waveforms will be out of phase from one another. However, no waveform distortion will take place and total harmonic distortion (THD) = 0.02%. When three phase transformers loaded by nonlinear load (three phase bridge full wave rectifier in our case) without using filter the voltage and current waveforms are distorted and total harmonic distortion (THD) = 18.51% . When three phase transformers loaded by nonlinear load (three phase bridge full wave rectifier in our case) with filter, we notice that the near sinusoidal wave shape of the input current and a drastic reduction in current harmonic is therefore obtained. The THD in this case is reduced significantly to ~2%. The power factor is significantly improved from 0.71 to 0.976.
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Deutsch Algorithm In Two Valued Logic
Ms. Buğçe Eminağa Girne American University, Industrial Engineering, Cyprus
Asst.Prof.Dr. Mustafa Riza Eastern Mediterranean University, Mathematics, Cyprus
Keywords: Deutsch , Logic , Quantum Computing
The Deutsch algorithm is the first and one of the most important examples for the illustration of the efficiency and superiority of quantum algorithms. It is exponentially faster than any possible deterministic classical algorithm. The important part is that a reversible circuit is given for computing an unknown function. In this study, we review the properties of Deutsch Algorithm in two-valued logic explain how the generalization to three valued logic is conducted. The corresponding NOT and Hadamard gates that are needed for the extension to three valued logic are introduced and discussed.
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UAV Route Planning For Maximum Target Coverage
Asst.Prof.Dr. Murat Karakaya Atılım University, Computer Engineering, Turkey
Keywords: UAV, Route Planning, Optimization, Ant Colony Optimization, Simulation
The importance and the impact of using Unmanned Aerial Vehicles (UAVs) in military and civil operations are increasing. One of the challenges in effectively tasking these expensive vehicles is planning the flight routes to monitor the targets. This problem is related with the Multiple Travelling Salesman Problem (mTSP) and the Vehicle Routing Problem (VRP). In these well-defined problems, it is mostly assumed that travelling salesmen or vehicles should visit all the targets and the target function is defined as to find a minimum-distant route. Even, in the constraint versions of the mTSP and VRP, some other restrictions (visiting time windows, number of depots, etc.) are included; it is still assumed that there exists enough number of travelling salesmen or vehicles to cover all the given locations. However, in reality the number and flight range of UAVs might be insufficient to cover all the targets. As a result, the maximization of the number of targets covered by the limited number of UAVs can be defined as a new problem. Thus, this article presents a solution for this practical optimization problem by modifying the Max-Min Ant System (MMAS) algorithm along with the local optimization technique accordingly. In the proposed solution, each ant constructs routes for the given number of UAVs using pheromone and heuristic information. These routes are locally optimized using a modified 2-opt technique. After each iteration, the solution which covers more targets with less route distance is selected as the iteration-best solution and the pheromone values of the edges on that route are increased. According to the termination condition, the algorithm stops and outputs the best route found so far as the result. To evaluate the success of the proposed method, another approach, based on the Nearest Neighbor (NN) heuristic, is developed as well. Both solutions are implemented using MASON simulation library and compared by extensive experiments with different parameters and standard TSP data files. The results showed the success of the proposed MMAS method by increasing the number of covered targets up to %18 compared to the solution based on the NN heuristic.
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A Local Optimization Technique for Assigning New Targets to the Planned Routes of Unmanned Aerial Vehicles
Asst.Prof.Dr. Murat Karakaya Atılım University, Computer Engineering, Turkey
Keywords: Heuristic searching methods, local search, UAV, dynamic route planning
Using Unmanned Aerial Vehicles (UAVs) are one of the reconnaissance methods gaining popularity recently. Since UAVs are very expensive and scare resources, UAV route planning is vital for increasing their effectiveness in monitoring targets. Route planning can be static or dynamic. In static route planning, routes are constructed according to given UAVs and targets and do not change during the mission. However, in dynamic route planning, number of routes or UAVs can alter which requires the update of existing routes to adopt these changes. For example, some of the UAVs can be lost during the mission or new targets might pop up after the take-off. This article proposes an iterative local optimization for the distribution of new targets to the existing routes in dynamic route planning. In the proposed solution, it is supposed that all UAVs have the same flight ranges, their initial routes are planned, and they have already visited some of the targets according to these routes. Furthermore, for each UAV, the slack range which is the difference between the flight range and initial route distance is calculated. Whenever some new targets appear, the proposed iterative insertion algorithm executes as follows. In the first phase of the algorithm, an UAV with the highest slack range is picked and its route is modified by inserting a new target at a time. Adding a new target to an existing route causes an increase in the route distance, which is called update cost. If the update cost is not greater than the slack range, the new target is inserted to the route. After finishing attempts with all new targets, if any of them is left over, insertion process is executed with the UAV having the next highest slack range as described above until either all UAVs or new targets are finished. If there are still uncovered new targets after trying all UAVs, the algorithm proceeds the second phase in which a 2-opt technique is applied to the modified UAV routes for increasing the slack ranges. Then, the first phase of the algorithm is re-run for the remaining uncovered targets. Algorithm will terminate either all the new targets are covered or 2-opt technique does not produce any better slack ranges. This local optimization technique is implemented using Mason simulation library and tested with various experiments for different parameter settings and TSP data files. The results showed the effectiveness and the success of the proposed iterative insertion algorithm.
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Model-based Test Case Prioritization Using Neural Network Classification
Dr. Nida Gökçe Muğla Sıtkı Koçman Üniversitesi, Fen Fakültesi, İstatistik Bölümü, Turkey
Prof.Dr. Mübariz Eminli Haliç Üniversitesi, Mühendislik Fakütesi, Bilgisayar Mühendisliği, Turkey
Keywords: Test case prioritization, event, clustering, neural network classification
Model-based testing for real-life software systems often require a large number of tests, all of which cannot exhaustively be run due to time and cost constraints. Thus, it is necessary to prioritize the test cases in accordance with their importance the tester perceives. In our previous study, in order to reduce these constraints, event- oriented graph model based and with using clustering approach has been presented. This approach aims to determining indirectly preference degree of test cases which are usually given by several attributes of relevant events through clustering all events entailed and frequency of occurrence of events, and then ranking them in accounting to degrees obtained. It is obvious that such as a way prioritization has high computational cost and it is capable to ranking the existing test cases only whereas there may be needed updating or extending test suite .In this paper, this problem is solved by improving our given previous study. Namely, there for each test case, previously obtained important index and mentioned frequency for all events belonging to given test case as inputs and corresponding classification label of this one as output are used in presenting a data for classification. A data set obtained in such a way for all existing test cases as training data are classified by Feedforward backpropagation neural network (NN). The structure of NN-classifier in terms of the number of nodes in input, hidden and output layers have been determined. The classification results for commercial application show that by suggested approach, the high classification accuracies %98 and the acceptable test prioritization performance especially, for testing data set are achieved.
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Earthquake Data Modeling Using Artificial Neural Networks and Time Series Analysis
Dr. Nida Gökçe Muğla Sıtkı Koçman Üniversitesi, İstatistik, Turkey
Asst.Prof.Dr. Hatice Özkoç Muğla Sıtkı Koçman Üniversitesi, İktisat, Turkey
Keywords: ANN, Time Series, ARIMA, Earthquake Data Modeling
Artificial Neural Network (ANN) is a computing technology that was developed to model the learning process of the human brain. ANNs are mathematical systems include many nerve cells are weighted linked together. Applications areas of ANNs involve nonlinear system identification and decision making, control, times series etc. due to non-linear processing capabilities and feature of learning from the data. Traditionally, time series analysis approach is used for modeling of time-dependent data. ANN may be prefered for autoregressive moving average models owing to time series modeling of curvilinear structure instead of time series analysis. In this study, ANN Nonlinear Autoregressive (NAR) time series model and Autoregressive Integrated Moving Average (ARIMA) model applied to the modeling of seismic data. Analysis were performed using the values of between the years 1900-2013 on the basis of the highest magnitude earthquakes in Turkey. Models were compared in terms of goodness of fit.
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Simulated Annealing Approach for Timetabling Problem
Mr. ilker küçükoğlu uludag university, industrial engineering, Turkey
Mr. Alkın Yurtkuran uludag university, industrial engineering, Turkey
Ms. Özlem Kanga uludag university, industrial engineering, Turkey
Keywords: Simulated annealing, timetabling
Timetabling problem, which is one of the large and complex problems, deals with the allocation of exam tasks to specific time periods so that some specific constraints are satisfied and the created timetable is feasible and effective. Thus, finding a good university timetabling program is not a simple work for an organization in practice. As a result, many approaches to producing sufficiently good solution have been introduced in literature. This paper presents a Simulated Annealing (SA) approach to solve timetabling problem for combinable tasks distinctly from the existing studies. To combine a set of tasks, each pair of tasks must be crosschecked to prevent conflict. The objective is to find best task-period assignment that minimize total period usage and also satisfy all the constraints. In order to demonstrate the efficiency of the proposed SA algorithm, experiments with real life input data have been conducted. Computational results show that proposed SA exhibits superior performance to find effective solutions.
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A Tabu Search Algorithm for Green Capacitated Vehicle Routing Problem
Mr. ilker küçükoğlu uludag university, industrial engineering, Turkey
Ms. Seval Ene uludag university, industrial engineering, Turkey
Dr. Aslı Aksoy uludag university, industrial engineering, Turkey
Prof.Dr. Nursel Öztürk uludag university, industrial engineering, Turkey
Keywords: Green vehicle routing, tabu search algorithm
Global climate change is one of the most challenging environmental problems facing society. Therefore, reducing the greenhouse gases, especially carbon dioxide, has become a critical environmental issue worldwide and has attracted attentions in all economic sectors and industries. In high competitive environment, industrial organizations have to investigate logistics strategies and adopt green supply chain applications to consider accurate use of natural resources as a social responsibility. Green logistics is concerned with producing and distributing products in a sustainable way, taking into account of environmental and social factors. Thus the objectives are not only concerned with the economic impact of logistics policies on the enterprises carrying them out, but also wider effects on daily life, such as the effects of pollution on the environment. This paper presents the Green Capacitaed Vehicle Routing Problem (G-CVRP) which considers CO2 emissions and fuel consumptions on the constrary of clasical Capaciated Vehicle Routing Problem (CVRP). The objective is to find best route plans that minimize total CO2 emission amount and reduce fuel consumption at the same time. The G-CVRP is formulated using mixed integer programming and solved using Tabu Search (TS) meta-heuristic algorithm. A fuel consumption and CO2 emission calculation model is constructed considering vehicle technical specifications, vehicle load and transportation distance. The proposed algorithm is performed with various examples and computational results show that TS provides effective solutions to G-CVRP for reducing total energy consumption and CO2 emissions.
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A modified ant colony optimization algorithm for asymmetric traveling salesman problem
Ms. Ozlem Kanga Uludag University, Industrial Engineering, Turkey
Mr. Ilker Kucukoglu Uludag University, Industrial Engineering, Turkey
Mr. Alkin Yurtkuran Uludag University, Industrial Engineering, Turkey
Keywords: Asymmetric traveling salesman problem, Ant colony optimization, Meta-heuristics
In asymmetric traveling salesman problem (ATSP) the path between two cities may not exist in both directions or the bi-directional distances between a pair of cities are not necessarily identical, forming a directed graph. The objective is to obtain the shortest possible route visiting every city by means of the asymmetrical distance matrix and returning to the origin at the end of the tour. Problems of this type arise in various areas, such as logistics planning and circuit board design. To solve the well-known ATSP, an ant colony optimization (ACO) algorithm with local search technique is proposed. Ant colony optimization (ACO) algorithm is a tool, generally used for solving complex combinatorial optimization problems, with promising results. ACO is one of the swarm intelligence methods based on behavior of ants trying the find the optimum path between a food source and the colony. A comparative computational study using optimization software shows that the proposed ACO algorithm is a viable option for ATSPs.
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An improved artificial bee colony algorithm for attractive traveling salesman problem
Mr. ALKIN YURTKURAN ULUDAG UNIVERSITY, INDUSTRIAL ENGINEERING, Turkey
Ms. OZLEM KANGA ULUDAG UNIVERSITY, INDUSTRIAL ENGINEERING, Turkey
Mr. ILKER KUCUKOGLU ULUDAG UNIVERSITY, INDUSTRIAL ENGINEERING, Turkey
Keywords: Attractive traveling salesman problem, Artificial bee colony algorithm, Random key
Artificial bee colony algorithm (ABC) mimics the foraging behavior of honey bee swarms. ABC has been justified to be competitive to other novel population based meta-heuristics on both combinatorial and continuous optimization problems. Attractive traveling salesman problem (AtTSP) is a relatively new variant of TSP problem where customer and facility nodes are disjoint. The objective of AtTSP is to find the maximal profit tour using the subset of facilities. Every tour should starts and ends at the depot and the length of the tour should not exceed the given maximum tour length limit. In AtTSP, every visited facility attains profit, which depends on the attractiveness of that facility and its distance to customer. Total tour profit is the sum of all profits from visited facilities. In this study, a modified ABC (MABC) algorithm to solve AtTSP is proposed. MABC utilizes different move strategies during the same search process to balance the exploration and exploitation. Computational experiments on selected benchmarks show that, MABC outperforms other meta-heuristics.
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Detection and Localization of Abnormality of Crowd
Asst.Prof.Dr. Md. Haidar Sharif Gediz University, Computer Engineering, Turkey
Asst.Prof.Dr. Sahin Uyaver Istanbul T. University, Computer Eng., Turkey
Keywords: Abnormality, Mahalanobis metric, Optical flow
Abnormality detection and localization in video surveillance is a key task for public security and safety. Numerous methods have been directed to detect abnormalities in videos. Among them holistic category is widely recalled. This category treats the crowd flow as a single entity, so that the tracking issue is not challenge for dense crowded scenes. Information of main crowd flows is a key issue for this category to understand crowd behaviour. Several abnormal crowd behavior detection methods based on holistic idea have been proposed by considering both optical flow method and a combination of few other methods, e.g., hidden Markov models [2], Lagrangian particle dynamics [1], covariance matrices [10], direction map [3], normalized continuous rank-increase measure [7], social force model [5], Bhattacharyya metric [11], Mahalanobis metric [8], and entropy [9]. Some of these methods have been tested with either simulated data [2] or both simulated and real data [9]. A few of those methods detect and localize abnormal behaviors in crowd videos (e.g., Mehran et al. [5]). Our primary goal is to introduce a holistic method free from segmentation orindividual subject tracking to detect and locate anomalies in video sequences. In this paper, we have addressed an approach which detects and locates abnormalities in videos based on the statistical treatments of spatiotemporal information of a set of interest points within a region of interest over time. Clustering algorithm clusters the points of interest to provide potential location of abnormality on the frame and normalized Mahalanobis distances provide the knowledge of the state of anomalousness. This paper is considered as an extended version of the work presented by Sharif et al. [8], which detects anomalies in videos. Key advantage of the current method concerns that it can both detect and locate anomalies in video sequences. Rest of this paper: section 2 outlines proposed framework; section 3 reports detection abilities of the approach; and section 4 makes conclusion. References [1] S. Ali and M. Shah. A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis. In Conference on Computer Vision and Pattern Recognition (CVPR), pages 1–6, 2007. [2] E. L. Andrade, S. Blunsden, and F. R. B. Modelling crowd scenes for event detection. In International Conference on Pattern Recognition (ICPR), pages 175–178, 2006. [3] N. Ihaddadene and C. Djeraba. Real-time crowd motion analysis. ICPR, pages 1–4, 2008. [4] B. D. Lucas and T. Kanade. An iterative image registration technique with an application to stereo vision. In IJCAI ’81, pages 674–679, 1981. [5] R. Mehran, A. Oyama, and M. Shah. Abnormal crowd behavior detection using social
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force model. In Computer Vision and Pattern Recognition (CVPR), pages 935–942, 2009. [6] U. of Minnesota. Unusual crowd activity dataset of university of minnesota. available from http://mha.cs.umn.edu/movies/crowdactivity-all.avi, 2009. [7] M. H. Sharif and C. Djeraba. Exceptional motion frames detection by means of spatiotemporal region of interest features. In International Conference on Image Processing (ICIP), pages 981–984, 2009. [8] M. H. Sharif and C. Djeraba. A simple method for eccentric event espial using Mahalanobis metric. In Iberoamerican Conference on Pattern Recognition (CIARP), pages 417–424, 2009. [9] M. H. Sharif and C. Djeraba. An entropy approach for abnormal activities detection in video streams. Pattern Recognition, 45(7):2543–2561, 2012. [10] M. H. Sharif, N. Ihaddadene, and C. Djeraba. Covariance matrices for crowd behaviour monitoring on the escalator exits. In Advances in Visual Computing, pages 470–481, 2008. [11] M. H. Sharif, S. Uyaver, and C. Djeraba. Crowd behavior surveillance using Bhattacharyya distance metric. In Computational Modeling of Objects Represented in Images (CompIMAGE), pages 311–323, 2010. [12] J. Shi and C. Tomasi. Good features to track. In CVPR’94, pages 593–600, 1994.
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Modelling of Driver Lane Choice Behaviour with Artificial Neural Network (ANN) and Lineer Regression (RL) Analysis on Deformed Roads
Mr. Metin Mutlu Aydın Gümüşhane Üniversitesi, İnşaat Mühendisliği, Turkey
Mr. Mehmet Sinan Yıldırım Gediz Üniversitesi, İnşaat Mühendisliği, Turkey
Asst.Prof.Dr. Orhan Karpuz Gümüşhane Üniversitesi, İnşaat Mühendisliği, Turkey
Keywords: lane Changing Behaviour, Artificial Neural Network (ANN) Model, Linear Regression (LR) Model, Road Surface Deformations
In parallel to the economic developments, the importance of road transportation was significantly increased in Turkey. As a result of this, long-distance freight transportation gains more importance and hence numbers of the heavy vehicle were significatly increased. Consequently, road surface deformations are observed on the roads as the incresing freight transportion and climatic conditions influence the road surface. Therefore, loss of functionality of the road surface is observed and drivers are much prone to accident due to their driving characteristics as they can have more tendency to change their lanes not to pass through the deformation area. In this study, the lane changing behaviours of the drivers are investigated and both Artificial Neural Network (ANN) and Linear Regression (LR) models are proposed to simulate the driver behaviour of lane changing who approach to a specific road deformation area. The potential of ANN model for simulating the driver behavior is evaluated with successive comparison of the model performances with LR model. While there is a slight performance increment for the ANN model with respect to LR model, it is quite evident that, ANN models can play an important role for providing the driver behavior approaching a road surface deformation. It can be said that, approaching speed plays an important factor on the lane changing behavior of a driver. This can be criticized by the fact that, drivers with high approaching speeds are tend to pass through the deformation to avoid the accidents while changing their lanes with a high speed.
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Geothermal Energy Potential of Turkey by Utilising the Airborne Magnetic Data
Prof.Dr. Abdullah Ateş Ankara University, Geophysical Engineering, Turkey
Keywords: Geothermal, Airborne, Magnetic, Turkey
Magnetic anomalies can be used to explore the geothermal energy potential. Magnetic surveys can be done on land, sea surface as well as from the air. Airborne magnetic surveys are fast and efficient ways of exploring the magnetisation of the ground. If there are upper crustal or crustal magnetised substances these can be seen on the airborne magnetic anomaly maps. Airborne magnetic anomalies of Turkey were surveyed by the General Directorate of the Mineral Research and Exploration and show many intense amplitude of anomalies. It is important knowing the non-magnetic bottom depths of bodies causing anomalies. That means the heat is 580 ºC and thus the magnetisation cannot be exist. This temperature is known as the Curie temperature. It is possible to exploit the heat dependency of the magnetic mineral. If the heat increases, magnetisation of the substance decreases. Eventually, it looses all of its magnetisation at the aforementioned temperature. The Curie Point Depths (CPDs) of the airborne magnetic anomalies of Turkey were determined to investigate source bottom depths. In western Turkey, there are two shallow high heat regions and that the high-heat is as close as 9 km to the ground surface. In central Anatolia high heat (580 ºC) is as close as 8 km to the ground surface. If we assume that at 3km depth the heat is 200 ºC, this depth could be reached by drilling boreholes. In east Anatolia, unfortunately, high heat regions are not shallow. The shallowest depth is about 16 km from the surface. This depth cannot easily be reached. I suggest that the geothermal fields of east Anatolia should be explored individually. Furthermore, resent research indicated that the geothermal regions of east Anatolia is fault controlled.
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QUALITY FUNCTION DEPLOYMENT AND ITS APPLICATION ON A SMARTPHONE DESIGN
Dr. Bülent Cerit İstanbul Teknik Üniversitesi, Endüstri Mühendisliği, Turkey
Mr. Gökhan Kalem İstanbul Teknik Üniversitesi, Endüstri Mühendisliği, Turkey
Ms. Güneş Küçükyazıcı İstanbul Teknik Üniversitesi, Endüstri Mühendisliği, Turkey
Keywords: Quality Function Deployment, the Kano Model, Telecommunication, Smartphones
In recent years, the capability of new product development has been gaining more importantance for all customer oriented companies in order to increase customer satisfaction. Therefore, various quality management techniques have arised in order to decrease product life cycle, respond completely to the customer demands and dominate the market efficiently. One of the most significant methods in this direction is the Quality Function Deployment (QFD). QFD is a quality management technique which aims to listen to the voice of customer (VoC) and design the product as per customer demands and expectations. In the first step, customer requirements are defined as the beginning of the QFD process and then technical requirements are determined according to the features of product or service. House of Quality (HoQ) is created as the second step. The interpretation of HoQ is important so as to determine the customer satisfaction strategies. QFD is an effective way to keep the design quality of a product or service under control. The aim of this paper is exploring the application of the QFD method on a new product development in accordance with customer expectations. The design of new Turkcell smartphone has been selected as the research case. QFD researches have been examined and literature scanning has been performed for the telecommunication industry. However, it was not easy to find so many QFD sample projects in the sector due to fact that product life cycle is completed very fast. It is required to grab competitive advantage by means of continuous review of new product development techniques because mobile communication technologies are so dynamic in many aspects. In addition, updated information and short history related to the telecommunication sector and mobile phone market including smartphones have been examined. It is aimed to understand QFD application well by explaning characteristics of smartphones and their development stages in the research. At the beginning of the research case, customer and technical questionnaires have been prepared with the focus group studies and literature review, after the determination of customer and technical requirements. The Customer Questionnaire is applied amongst
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Turkcell employees modelling the target segment in the smartphone market and then the Technical Questionnaire is applied on concerned technical departments. Afterwards, HoQ has been built implementing QFD steps after collecting VoC. The application of QFD on the new smartphone design has been supported by the Kano Model to be able to categorize and prioritize customer requirements. The model is also preferred in order to acquire more sensitive results. According to the results of HoQ, it is initially decided to act for the operating system and the software design to improve the factors affecting user experience in an inferior direction. At the end of the research case, detailed results have been interpreted by taking prior customer requirements into consideration.
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TRIZ: Theory of Inventive Problem Solving and Comparison With Other Problem Solving Techniques
Mr. Bülent Cerit İstanbul Teknik Üniversitesi, Endüstri Mühendisliği, Turkey
Mr. Dirim Şener İstanbul Teknik Üniversitesi, Endüstri Mühendisliği, Turkey
Ms. Güneş Küçükyazıcı İstanbul Teknik Üniversitesi, Endüstri Mühendisliği, Turkey
Keywords: TRIZ, Problem Solving Techniques, Management
In today’s business world, it is obligatory to produce or closely follow and apply the technological and scientific developments in order to survive in a highly competitive environment by establishing productive, efficient and profitable businesses and to keep abreast of the rapid changes of the needs. Products, services and related processes, which have to be developed and differentiated continuously, create technical and non-technical problems, which become gradually more difficult. Inventive and innovative point of view is necessary to solve these problems which cannot be handled by traditional methods. In the beginning of 1946, G. Altshuller wanted to facilitate the resolution of difficult inventive problems and to provide this facilitation to all humanity, and developed TRIZ (Theory of Inventive Problem Solving) so as to provide a tool for this necessity. In this paper, TRIZ’s difference, which occurred with the possession of inventive problem solving philosophy and the provision of the possibility to use extensive knowledge base, is explained. The systematic approach of TRIZ is essentially emphasized in detail. Brief explanations of other problem solving methods are also presented in order to provide a benchmark to reveal the strong and weak characteristics of TRIZ among the other methods. The possibility of using TRIZ together with other problem solving techniques, instead of using the method as a single solution provider, is discussed in the paper. A few case studies are examined by problem descriptions, system analyses, opportunity identifications and solution generations. Inventive Standards, which are a set of abstract solutions condensed from related inventive patents by TRIZ researchers, are represented in the form of a Substance-Field Model, which is the basic structure of what makes a system viable and able to successfully perform a function. Contradiction Matrix and Inventive Principles are given. The contribution of TRIZ to future Industrial Engineering applications is also considered.
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A predictive model for compressive strength of the concretes incorporating volcanic ash
Asst.Prof.Dr. Kasım Mermerdaş Hasan Kalyoncu University, Civil engineering, Turkey
Assoc.Prof.Dr. Erhan Güneyisi Gaziantep University, Civil engineering, Turkey
Assoc.Prof.Dr. Mehmet Gesoğlu Gaziantep University, Civil engineering, Turkey
Mr. Mehmet Sakin Hasan Kalyoncu University, Civil engineering, Turkey
Keywords: Genetic programming, volcanic ash, compressive strength, multiple linear regression
In this paper, genetic programming based an explicit formulation of compressive strength of concretes incorporated with volcanic ash (VA) which is used as a supplementary cementitious material for concrete, was presented. The data used for modeling were collected from the available experimental studies presented in the literature. Total 136 data samples were arranged to form training and testing sub-databases. The input variables were considered as water-to-binder (w/b) ratio, total binder content (B), age of concrete (A), and replacement level of VA. Using these critical input variables the compressive strength of the concretes were predicted through the proposed model. In order to emphasize the effectiveness of this modeling method, another predictive model from multiple linear regression was also presented for the same database. Two prediction performance of the models were evaluated through some statistical parameters such as correlation coefficient, mean absolute percent error, mean square etc. The results indicated that the prediction capability of the proposed GEP model is more accurate and reliable than the MLR model.
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A New Approach for Improving the Performance of Support Vector Machines for Maximal Oxygen Uptake Prediction
Mr. Mustafa Açıkkar Çukurova University, Physical Education and Sports, Turkey
Assoc.Prof.Dr. Mehmet Fatih Akay Çukurova University, Computer Engineering, Turkey
Keywords: Support Vector Machines, Maximal Oxygen Uptake, Performance Evaluation
In this paper, we propose a new approach for improving the performance of Support Vector Machines (SVM) on regression. Our approach is based on the elimination of irrelevant samples from the training data by taking into account the standard error of estimates (SEE’s) of each sample. The samples that have SEE values bigger than a specified threshold have been removed to form a new training data. The performance of our approach is assessed by applying it on a maximum oxygen uptake (VO2max) data set, which has gender, age, body mass index (BMI), exercise time and heart rate as predictor variables and VO2max as target variable. The data set includes data of 185 subjects. Several models have been developed by using combination of the predictor variables. Initially, 80% of the data is used as a training set and the rest of the data is used as a test set. Grid search is used to find the optimal SVM parameters for each model. Optimal SVM parameters have been used to train the reduced training data. The performance of the models has been evaluated by calculating the SEE’s and multiple correlation coefficients (R’s) of the test data. The results show that our approach is able to decrease the SEE of the models by 8.64% and increase the R of the models by 5.42% on the average. Considering the results, we can say that our approach can be used for valid prediction of VO2max.
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Prediction of Maximal Oxygen Uptake Using Multilayer Perceptron and Multiple Linear Regression Combined with Feature Selection
Mr. Erman AKTÜRK Cukurova University, Computer Engineering, Turkey
Assoc.Prof.Dr. Mehmet Fatih Akay Cukurova University, Computer Engineering, Turkey
Keywords: neural networks, multiple linear regression, feature selection, maximal oxygen uptake
Maximal oxygen uptake (VO2max) is the maximum capacity of an individual\\\'s body to transport and use oxygen during incremental exercise, which reflects the physical fitness of the individual. In this paper, multilayer perceptron (MLP) and multiple linear regression (MLR) methods combined with a feature selection algorithm (Relief-F with a ranker search) have been used to develop maximal, submaximal and non-exercise VO2max prediction models for healthy subjects ranging in age from 18 to 65 years. Age, gender, height and weight are the common variables in each prediction model. Maximal models include heart rate, rating of perceived exertion, respiratory exchange ratio and grade; submaximal models include stage, rating of perceived exertion and heart rate and non-exercise models include perceived functional ability (PFA) and physical activity rating (PAR) scores as predictor variables. Dimensionality of data set is reduced by one feature at a time before being passed on to the regression method. By using 10-fold cross-validation on the data set, the performance of the prediction models has been evaluated by calculating their standard error of estimates (SEE’s) and multiple correlation coefficients (R’s). The results indicate that MLR-based models perform better than MLP-based ones. The performance of the MLR-based models is the best when all features are present in each model. The SEE’s of the MLR-based maximal, submaximal and non-exercise models are 4.89, 4.49 and 3.96, respectively.
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Prediction of Upper Body Power of Cross-Country Skiiers Using Artificial Neural Networks
Mr. Shahaboddin Daneshvar Cukurova University, computer engineering department, Turkey
Assoc.Prof.Dr. Mehmet Fatih Akay Cukurova University, Computer Engineering, Turkey
Keywords: neural networks, upper body power
Upper body power (UBP) is an important determinant of cross-country ski race performance. Although numerous studies exist to measure UBP of cross-country skiers, to date, no study has attempted to predict UBP without carrying out any measurements. The purpose of this study is to predict 10-second UBP (UBP10) using a multi-layer feed-forward artificial neural network (MFANN). The data set includes data of 57 subjects. Gender, age, body mass, maximum heart rate, absolute maximum oxygen uptake (AVO2max), relative maximum oxygen uptake (RVO2max) and exercise time are predictor variables and UBP10 is the target variable. Twelve (UBP10) prediction models have been developed by using combination of the predictor variables. The optimal values of the parameters that affect the performance of the MFANN models (i.e. number of neurons in the hidden layer, learning rate and momentum) have been found by trial and error. By using 10-fold cross-validation on the data set, the performance of the models has been evaluated by calculating their standard error of estimates (SEE’s) and multiple correlation coefficients (R’s). The results shows that the model including the predictor variables gender, age, body mass and maximum heart rate yields the lowest SEE (SEE = 24.74) whereas the model including the variables gender, age, body mass and time yields the highest SEE (SEE = 33.06) for prediction of UBP.
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Performance Evaluation of Nonparametric Adaptive Techniques for MIMO Radar Target Detection
Ms. Nefiye ERKAN Gazi Üniversitesi, Elektrik Elektronik Mühendisliği, Turkey
Asst.Prof.Dr. Nursel AKÇAM Gazi Üniversitesi, Elektrik Elektronik Mühendisliği, Turkey
Keywords: MIMO, Radar, Capon, APES, LS
In this study, the performance of target detection in Multiple Input Multiple Output (MIMO) radars has been evaluated by implementing Capon, Amplitude and Phase Estimation (APES), and Least Squares (LS) methods within multiple input and output structures. The impact of changing the number of antennas used in MIMO radars on target detection has been examined. In addition, how the performance of target detection changes based on distance between antennas. The impact of the methods, mentioned above, in MIMO radars has been evaluated in environments having jamming signal, and the performances of MIMO radar systems in detecting multiple targets have been compared.
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Measurement of OSPF-MPLS-TE-FRR Line Transitions and Data Losses
Mr. Murat OĞUL Gazi Üniversitesi, Elektrik Elektronik Mühendisliği, Turkey
Asst.Prof.Dr. Nursel AKÇAM Gazi Üniversitesi, Elektrik Elektronik Mühendisliği, Turkey
Ms. Nefiye ERKAN Gazi Üniversitesi, Elektrik Elektronik Mühendisliği, Turkey
Keywords: OSPF, MPLS, Simena, Hping3
In this paper, when using Open Shortest Path First (OSPF) and Multi Protocol Lable Switching-Traffic Engineering (MPLS-TE) in Internet Protocol (IP) packet switching networks recover time was tested and compared and during that time amount of data lost in case of the link overload and failure. For the accuracy of measurements, two different traffic generators were used and the differences were compared. One of them is Simena device and the other one is a Hping3 program working with Linux platforms. Line transitions and data losses were measured seperately with Simena and Hping3, calculations were performed and results were compared.
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Analysis of Incident-Level Crime Data Using Clustering with Hybrid Metrics
Mr. Mehmet Sait VURAL Mersin Üniversitesi, Bilgisayar Mühendisliği, Turkey
Assoc.Prof.Dr. Mustafa GÖK Çukurova Üniversitesi, Elektrik-Elektronik Mühendisliği, Turkey
Asst.Prof.Dr. Zeki YETGİN Mersin Üniversitesi, Bilgisayar Mühendisliği, Turkey
Keywords: Crime Analysis, GIS, Causal Relation, Decision-Making, Clustering Algorithms
Law enforcement agencies use modern crime analysis software to solve and prevent crimes. The development of crime analysis tools requires access to incident-level crime data (criminals’ IDs, time and place of incidents, etc). However, obtaining such data is very hard in practice, since the crime data is confidential. On the other hand, crime analysis usually processes aggregate-level information, such as frequency of crimes occurring over a particular geography, rather than processing the incident-level data. In this paper, a decision-making method is proposed to infer the closely related incidents using clustering with hybrid similarity metrics. The incident-level crime data is artificially generated by using a parametric GIS model. The motivation for this approach is that in general crime analysis methods do not require fully realistic data set in order to train and test decision making algorithms. The motivation behind using hybrid metrics is that the incident-level crime data includes both numeric and categorical information with unstable feature vector lengths. In order to evaluate the proposed method, a novel performance metric, called Crime Driven Casual Relation Performance (CDCRP), is introduced. The results show that the proposed method has a decision performance of above 92% on the incidents, which well decides the causally related incidents.
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BREAST CANCER DIAGNOSIS VIA DATA MINING: PERFORMANCE ANALYSIS OF SEVEN DIFFERENT ALGORITHMS
Dr. Zehra KARAPINAR SENTURK Duzce University, Computer Engineering, Turkey
Assoc.Prof.Dr. Resul KARA Duzce University, Computer Engineering, Turkey
Keywords: Data mining, breast cancer diagnoses, RapidMiner
According to World Health Organization (WHO), breast cancer is the top cancer in women both in the developed and the developing world. Increased life expectancy, urbanization and adoption of western lifestyles trigger the occurrence of breast cancer in the developing world. Most cancer events are diagnosed in the late phases of the illness and so, early detection in order to improve breast cancer outcome and survival is very crucial. In this study, it is intended to contribute to the early diagnosis of breast cancer. An analysis on breast cancer diagnoses for the patients is given. For the purpose, first of all, data about the patients whose cancers’ have already been diagnosed is gathered and they are arranged, and then whether the other patients are in trouble with breast cancer is tried to be predicted under cover of those data. Predictions of the other patients are realized through seven different algorithms and the accuracies of those are to be given. The data about the patients are taken from UCI Machine Learning Repository thanks to Dr. William H. Wolberg from the University of Wisconsin Hospitals, Madison. During the prediction process, RapidMiner 5.0 data mining tool is used to apply data mining with the desired algorithms.
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Investigating the Effect of Questionnaire Variables on the Prediction of Maximal Oxygen Uptake Using Multilayer Perceptron and Multiple Linear Regression
Mr. Eser Yücel Cukurova University, Computer Engineering, Turkey
Assoc.Prof.Dr. Mehmet Fatih Akay Çukurova University, Computer Engineering, Turkey
Mr. Erman Aktürk Çukurova University, Computer Engineering, Turkey
Keywords: neural networks, multiple linear regrassion, maximal oxygen uptake
Maximal oxygen uptake (VO2max) is defined as the highest rate of oxygen consumption attainable during maximal or exhaustive exercise. VO2max is widely accepted as the standard gauge of cardiorespiratory fitness and is useful as an indicator of a person\\\'s aerobic potential or upper limit. The purpose of this study is to investigate the effect of questionnaire variables on the prediction of VO2max by using multilayer perceptron (MLP) and multiple linear regression (MLR). Two types of questionnaire variables are considered. Perceived functional ability (PFA) questions are designed to determine how fast participants believe they could walk, jog, or run one and a three mile distance without becoming overly breathless or fatigued. The sum of the responses to the two PFA questions is the PFA score (range = 2–26). The physical activity rating (PA-R) question allows participants to self-report their level of physical activity during the past six months. The response to the PA-R question is the PA-R score (range = 0–10). 4 different sets of VO2max prediction models have been developed. Common predictor variables in each set are gender, age and body mass index (BMI). Rest of the predictor variables are ending speed, heart rate and stage of the exercise test. By using 10-fold cross-validation on the data set, the performance of the prediction models has been evaluated by calculating their standard error of estimates (SEE’s) and multiple correlation coefficients (R’s). The results show that inclusion of PFA and PA-R scores in VO2max models yields %18.26 to %28.00 and %17.92 to %26.99 reductions in SEE’s for MLR-based and MLP-based models, respectively.
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i-EEG: A Software Tool for EEG Feature Extraction, Feature Selection and Classification
Asst.Prof.Dr. Baha ŞEN Yıldırım Beyazıt University, Computer Engineering, Turkey
Mr. Musa PEKER Karabuk University, Computer Engineering, Turkey
Keywords: Computer-aided diagnosis, EEG, Software Tool, Feature Extraction, Feature Selection, Classification
Computer-aided diagnosis of some brain disorders using EEG signals, is an issue of growing concern in recent years. In this study, a software which is developed from EEG data is presented for seizure detections and diagnosis of disease. Developed software offers a different approach for the aspect of combining processes of data cleaning, feature extraction, feature selection and classification together. Software is developed using the C# programming language which is one of .NET programming languages. With the software, 4-stage procedures are performed on the EEG signal. For the first stage, filtering and cleaning of EEG data is ensured. For this stage, filtering algorithms are used. At second stage, attribute extraction process is done for determination of the significant information from EEG data. At this stage, 40 attribute values that widely preferred in literature can be obtained. At third stage (selection stage), attribute selection is carried out to ensure detection of effective attributes among all the attributes. At the selection stage, the user can select any algorithm that she/he wants among five different algorithms. These algorithms are fisher scoring, t-test, gini, fast correlation based filter (FCBF), mRMR and reliefF, respectively. At final stage, effective attributes are presented as input to the classification algorithms. The user can choose five different classification algorithms for the classification stage. These algorithms are feed-forward neural network, radial basis function neural network, C4.5 decision tree, random forest algorithm and support vector machines, respectively. The software which has a visual interface is very easy to use and designed to be user-friendly. An application sample is given with using the software developed in this study. In the application sample, applications were made on EEG data in order to determine depth of anesthesia. Results can be obtained as statistical in this software. It also is possible to follow the performance results graphically. After user testing completed, it is aimed to share the software free of charge as open source software project.
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Ultimate Strength of Composite Beam with Web Openings Subjected to Combined Interaction of Positive Bending and Axial Tension
Mr. Mahesan Bavan National University of Malaysia, Civil and Structural Engineering, Malaysia
Keywords: Composite beam with web openings, combined interaction of axial tension and positive bending, 3D non-linear FEM models, ultimate limit state, failure mode
In past research studies, the load carrying capacity of steel-concrete composite beam with web openings has been designed by monotonic loads. But in many cases, axial tensile loads are existed in the composite beams located in high rise buildings, cable stayed bridges and inclined areas, and those are ignored in the prediction of ultimate limit state of composite beam with web openings in the established design codes, which bring in conservative design. Thus, this paper deals an investigation in the designing process of the composite beams consisted web openings on steel section of the steel-concrete composite beam. A three dimensional finite element model was developed with non-linear material components for composite beam subjected to combined axial tension and positive bending and compared with available experimental data. The ultimate limit state and failure mode were found in close agreement between experiment and finite element model. A parametric study was then performed such as distance and diameter of circle web openings on the steel section of composite beam. The results show that the early failure state exists in the composite beam with web openings steel components subjected to combined axial tension and positive bending. When an optimum composite section is need to establish in the designing process of the composite beams consisted web openings, the investigation proceeded can be a useful implementation to access the system’s ultimate limit state.
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Application of Petri nets to decrease the path dependent loss and the switch cross talk in optical network
Dr. tolgay Karanfiller Uluslararası Kıbrıs Üniversitesi, Bilgisayar Öğretmenliği, Cyprus
Keywords: petri net
This study mainly focused on path dependent loss and switch crosstalk. The aim of this study is to decrease path dependent loss and switch crosstalk in optical networks by using the Petri nets. The approach is to find minimum number of switches which will be sufficient to perform desired communication patterns. Firstly, optical network will be represented by Petri nets. Secondly invariants method will be used to test reachability in Petri nets. This method is easy to applied in extended network topologies. [1] Bashirov, R., Rearrangeability of (2logN uniform connection pattern, Calcolo, Springer Verlag, 38, pp. 85-95, 2001. [2] Bashirov, R., Crespi, V., Analyzing the permutation capability of multistage interconnection networks with colored Petri nets, Information Sciences, 176, pp. 3143-3165, 2006. [3] Bashirov, R., Karanfiller, T., On path dependent loss and switch crosstalk reduction in optical networks, Information Sciences, 180, pp. 1040-1050, 2010. [4] Bashirov, R., Karanfiller, T., Lort, H., An approach to reduce path-dependentloss in optical networks implementing Petri nets, In: Prococeedings of 8th International Conference on Application of Fuzzy Systems and Soft Computing, Quadrat Verlag, Helsinki, 1-3 September, pp. 91-96, 2008. [5] Bashirov, R., Kordon, F., Lort, H., Exploiting colored Petri nets to decide on permutation admissibility, Acta Informatica, 46, pp. 43-55, 2009. [6] T. Murata, Petri nets: properties, analysis and applications, Proc. of IEEE, 77, 541-580 (1989). [7] X. Shen, M. Xu, X. Wang, An optimal algorithm for permutation admissibility to multistage interconnection networks, IEEE Transactions on Computers, 44, 604-608 (1995). [8] X. Shen, An optimal O(NlgN) algorithm for permutation admissibility to extra-stage cube-type networks, IEEE Transactions on Computers, 44, 1144-1149 (1995). [9] X. Shen, F. Yang, Y. Pan, Equivalent permutation capabilities between time-division optical omega networks and non-optical extra-stage omega networks, IEEE Transactions on Networking, 9, 518-524 (2001). [10] Y. Yang, J. Wang, Y. Pan, Permutation capability of optical multistage interconnection networks, Journal of Parallel and Distributed Computing, 60, 72-91 (2000). [11] Y. Pan, Optical multistage interconnection networks: new challenges and approaches, IEEE Communications Magazine, 37, 50-56 (1999). [12] C. Tocci, H. J. Caulfield, Optical interconnection - Foundations and applications, Artech, 1994.
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Fuzzy Quantities and Interpretative Processing in Decision Making for Expert Systems
Asst.Prof.Dr. Shahin Keynoush Girne American University, Architecture, Turkey
Keywords: Fuzzy Logic, Decision Making, Expert Systems
In the classic logic, based on the binary system of 0 and 1, the permanent truth statement is as followed: P -> P 1 -> 1 or 0 -> 0 While in the fuzzy logic there are infinite sets of truth statements coming out of the paradox form of the multi valance system of quantities: P -> 1 - P 0.5 -> 1 - 0.5 (P=0.5) 0.5 -> 0.5 Or two step sets of quantities in between 0 and 1 which the first input would be the same quantity of second output: 0.75 -> 1 - 0.25 0.25 -> 1 - 0.75 ---> (P=0.75) 0.75 -> 0.75 There is a capacity in the dynamism of fuzzy approach in which the same quantities could carry different identities. For instance while 0.5 -> 0.5 is taking place it doesn't mean that necessarily input ID(0.5)=Output ID(0.5). It means while half of a unit (in quantity) is equal to the other half there is still two different IDs: "half" and "other half" as "labels". It shows the concept behind the fuzzy dynamism which is capable to create a context for interpretative processing based on fuzzy quantities as labeling qualities. GIS is a typical expert system to help urban planners have a better vision of urban growth and predict its behavior. But in Fluid Planning, planners are no more looking for certain answers. They do look for more dynamic history of an expert system which can carry on with unpredictable events, to be capable to recall the preset scenarios (in initial plan) and synthesizing it with opposite scenarios. To gain this, the memory of system (even data bases) could do a labeling for each output of certain iteration. So whenever system recalls any of those total or partial information those labels may lead to new generation of scenarios for decision makers.
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WIRED AND WIRELESS COMMUNICATION TECHNIQUES AND APPLICATIONS IN RAILWAY SYSTEMS
Asst.Prof.Dr. N. Özlem Ünverdi Yıldız Technical University, Electrical & Electronics Engineering, Turkey
Asst.Prof.Dr. N. Aydın Ünverdi İstanbul Technical University, Mechanical Engineering, Turkey
Keywords: Wireless Communivation, Railway Transportation,HVAC, WDM, PCM
Railway transportation which has been the preferred choice because of its reliability and speed is spreading rapidly nowadays. Uninterrupted flow of railway traffic which is increasing day by day is guaranteed by traffic control systems. These systems give information in real time about the traffic flow and control, emergencies, speed limits and weather forecast. In this study, wired and wireless communication techniques of railway transportation systems are examined. High data transfer speeds of reliable, small loss and broad band optical fibers and communication structure of railway transportation systems with high communication speeds are evaluated. The system which operates the illumination, alarm, pressure and door sensors, emergency switch, and controls the route and heating-ventilation-air-conditioning, HVAC, performance by observing their state is investigated. The inverters in the Wavelength Division Multiplexing, WDM, system, the elements where Pulse Code Modulation, PCM, is used, and central control unit of the optical communication system are analyzed. The system is modeled by using OptiSystem 7.0 simulator program. It is observed that the signal gets weaker in the optical fiber, the power at the gates of the optical circulator which distributes the signal received from the optical fiber is decreased because of the path difference, and the signal is filtered at the exit of the optical filter. Wireless communication mechanism of the railway systems where antennas are used is assessed. The parameters of the dipole antenna of the system are evaluated. It is found that the power of the dipole antenna reaches its maximum value at teta=pi/2 and that the power decreases as the distance from the source increases due to the physical mechanism involved.
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THE USE OF ARTIFICIAL NEURAL NETWORKS IN ANALYZING THE IMPACT OF HRM ON FIRM PERFORMANCE
Assoc.Prof.Dr. Kamil Dimililer Girne American University, Electrical & Electronics Engineering, Turkey
Assoc.Prof.Dr. Zafer Agdelen Girne American University, Industrial Engineering, Turkey
Assoc.Prof.Dr. Ali Haydar Girne American University, Computer Engineering, Turkey
Keywords: RBF networks, HRM, Firm performance
The importance of Human Resource Management (HRM) as a tool of sustainable competitive advantage and the relationship between human resource management and firm performance has been analyzed extensively by many researchers for the last two decades. Many of these studies are based on the statistical approaches aiming at finding whether there is a relationship between the HRM practices and firm performance or not. In this study, the authors report the findings emerging from a study that explores the relationship between the input variables (HRM measures and control variables) and the firm performance measures through the use of Radial Basis Function (RBF) networks which establish a nonlinear relation between input and output data. From the experimental results, it is observed that the relationship can be constructed using RBF networks.
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DESIGN AND IMPLEMENTATION OF A METEOROLOGY STATION AND WEATHER QUALITY OBSERVATION INSTRUMENT
Mr. Adnan Cora Karadeniz Teknik Üniversitesi, Electrical & Electronics Engineering, Turkey
Mr. Onur Can Yardibi Karadeniz Teknik Üniversitesi, Electrical & Electronics Engineering, Turkey
Mr. Safa Mert Keleş Karadeniz Teknik Üniversitesi, Electrical & Electronics Engineering, Turkey
Mr. Recep Sultan Karadeniz Teknik Üniversitesi, Electrical & Electronics Engineering, Turkey
Keywords: Meteorology, Weather Quality
Thesystemconsist of a weathermeterwhichmeasureswindspeed, winddirectionandrainfall. Second blockincludestemperature, humidityandpressuresensors, thethirdblock is theweatherqualityobservationcircuitand is composed of LPG, CO, CH4, Hydrogensensors. Theinstrument can be suppliedviatheserial port orbattery.Thisoptionplays an important role tosupplyenergyfromdifferentsources. Thesystem can be used as fixedor mobile. Inthe Project batteriesareused. Solar cellpanels can be addedtomeetownenergyneed. Weather board has moreports on foradditionalsensors. Thesystemtakesdatafromsensorsandtransfersthe data viatheserialport BluSMIRFbluetooth modem orXBee modüle to Data Storage Unit(PC). TheXBee modüle Works at 2.4 GHz Bandand has a power of 63 µW, can be usedupto 1 mile(1.6 km) in openair. Alltheprocessesaremadeby anATmega328 8-bit in 28 pinprocessor, reads data in everytwoseconds. Asoftware program writtenwithArduino. Data takenfromthesensors can be transferredfaster. Theunitsof measuredquantities can be convertedfromonetoanotherachievedbytherelatedintruction. Under badweatherconditionsifmeasuredvaluesarebeyondthe normal valuesthesystemgives an alertsignal on thescreen.Thesystem is suitabletodevelop, sothankstothewirelesscontrolsystem can be used in agricalturalactivities. Inorderto be eligibleall of the data andseen on PC screen is achievedby Microsoft Visual Studio program, an interface a databasesystem is achieved. As an option, data can be storedinstantlyor on theotherinterface can be showngraphicallyforthepast. Dateand time arealsogivenbytheNotePad. Theinstrument is portable, light, easytoinstallanduse.
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GENERALIZED EVOLUTIONARY ALGORITHM: A NEW OPTIMIZATION ALGORITHM
Assoc.Prof.Dr. Ali Haydar Girne American University, Computer Engineering, Turkey
Assoc.Prof.Dr. Kamil Dimililer Girne American University, Electrical & Electronics Engineering, Turkey
Keywords: Evolutionary Algorithms, Optimization
This study introduces a new meta-heuristic optimization algorithm, which is called as Generalized Evolutionary Algorithm(GEA), for the solution of real-valued multi-modal optimization problems. The algorithm is designed in order to construct a better balance on the exploitation and exploration of a given problem which is the main deficiency for some known optimization algorithms. We evaluate the performance of the proposed algorithm on fourteen benchmark functions. The experimental results demonstrate a high efficiency and robustness of this algorithm to the selected benchmark functions. Moreover, it has few control parameters which makes it easy to use and it has a good convergence speed.
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Application of Particle Swarm Optimization to Microwave Tapered Microstrip Lines
Dr. Ezgi Deniz Ülker Girne American University, Computer Engineering, Turkey
Prof.Dr. Sadık Ülker Girne American University, Electrical & Electronic Engineering, Turkey
Keywords: Evolutionary Algorithm (EA), Particle Swarm Optimization (PSO), Tapered Microstrip Lines
Application of metaheuristic algorithms has been of continued interest in the field of electrical engineering because of their powerful features. In this work special design is done for a tapered transmission line used for matching an arbitrary real load to 50 line. The problem at hand is to match this arbitray load to a using three section tapered transmission line with impedances in decreasing order from the load. So the problem becomes optimizing an equation with three unknowns with various conditions. The optimized values are obtained using Particle Swarm Optimization. It can easily be shown that PSO is very strong in solving this multiobjective optimization problem.
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Synthesis of SiC-MoSi2-Al2O3 electrical heating elements by combustion method
Dr. N. Suat Canarslan Girne American University, Electrical & Electronics Engineering, Turkey
Keywords: Combustion Synthesis Method, Heating Elements, Porosity, Resistivity
Combustion synthesis of SiC-MoSi2-Al2O3 electrical heating elements by using highly exothermic reactive system of MoO3-Al-Si was investigated. SiC functioned as a filler material to control the combustion reaction and alsoconstituted part of the element. The amount of SiC additive varied in the range from 45% to 65% wt. and was optimized with respect to porosity level, resistivity range and net-shape quality of the heating elements. The element containing about 60% wt. SiC reveals low porosity level, full conversion for the reaction and superior net-shape quality. It has been shown that, by using combustion synthesis method, it is feasible to prepare an electrical heating element with room temperature resistivity and maximum watt loading of 12cm and 25 W/cm2 respectively. However, relatively high level of porosity present in the final synthesized product, the electrical heating element in accordance with the investigation can be used at temperatures up to 1500 C.
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Creating Surveys Using Artificial Agents
Asst.Prof.Dr. İbrahim Erşan Girne American University, Computer Engineering, Turkey
Asst.Prof.Dr. Tamer Tulgar Girne American University, Computer Engineering, Turkey
Keywords: Information Retrieval, Data Mining, Survey, Artificial Intelligence
Survey plays an important role in keeping track of attitudes for especially production phase of engineering. Without having a good prepared and assessed survey it may not be possible to figure out current state of needs. Using today’s computer technology, it is possible to find thousands of completed survey projects. Main idea is, using this whole experience in an effective way to reach excellence in survey creation. Any questionnaire can be divided into three main sections as subject, query and result. Using Information Retrieval, from a database of completed and evaluated surveys, related ones, for a desired subject, are collected and analyzed with Data Mining techniques to obtain a new query. In that case, it will be possible to determine weight of each question more precisely. After completing and evaluating new survey, it can be located in database, with modified weights, as a new feedback for future queries, so a kind of learning process for excellence will be aimed. Explained system may help us to obtain very efficient questionnaires but time factor must be taken into consideration. Needs and view points of participants are always in tendency to change. This case will change the answers of questions and also will need to replace some questions with new ones or with very old ones.
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Resource throughput improvement on the cell-edge in LTE cellular systems
Asst.Prof.Dr. Tamer Tulgar Girne American University, Computer Engineering, Turkey
Asst.Prof.Dr. İbrahim Erşan Girne American University, Computer Engineering, Turkey
Keywords: Interference Management, Relay Station, Long Term Evolution
In this paper, an intelligent interference mitigation algorithm for resource reuse and coordination efficiency in Long Term Evolution (LTE) cellular systems is presented. Inter-cell interference mitigation is considered to remedy the throughput performance at the cell edge. To further improve the performance, effect of relay stations is also considered. In several studies, either different interference mitigation schemes are proposed to solve the interference problem or relay stations are used to manage power considerations again to coordiante interference sources. In the proposed scheme two methods are used in conjunction to achieve even channel usage performance all over the cell while mitigating inter-cell interference.The proposed scheme’s performance is evaluated through simulaiton and results are compared to similar studies. As a result, comparisons prove that by employing the two approaches together, considerable performance improvement is achieved for data rate and throughput metrics.
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Statisitical Analysis of Overall Satisfaction and Demographic Factors in State-Owned Emergency Services of North Cyprus
Assoc.Prof.Dr. Zafer Ağdelen Girne American University, Industrial Engineering, Turkey
Asst.Prof.Dr. Burcu Toker Girne American University, Industrial Engineering, Turkey
Keywords: health services, emergency services, patient satisfaction, North Cyprus
The health services in North Cyprus are provided by governmental hospitals and a few number of private hospitals. According to the studies regarding preferences of the patients, it is observed that majority of the patients prefer governmental hospital services as they find the services provided trustable. Especially in cases of emergency services, the choice of majority of the patients is towards governmental hospital emergency services. As the Ministry of Health in North Cyprus is continuously working on finding opportunities to improve the existing health system and emergency services, patients are complaining from several problems related to services, especially provided by state-owned emergency services. In this study, we aimed to analyze the relationship of overall satisfaction of the patients from emergency services provided by governmental hospitals and demographic factors. For the analysis, as a result of literature survey, a questionnaire consisting of two main sections is constructed. The first section is composed of demographic questions and the second section is composed of perceptional questions about the quality of services provided by emergency departments. After collection of data, detailed statistical analysis is carried out. T-test and Anova test are applied to analyze the relationship between overall satisfaction and selected demographic factors. Based on the findings, several suggestions are made to provide a valuable scientific contribution to the actions of Ministry of Health in the improvement of emergency services provided by governmental hospitals which would increase patient satisfaction.
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Perceptional Analysis of Patient Satisfaction from Health Services Provided in North Cyprus: A Case Study of Government Hospitals
Asst.Prof.Dr. Burcu Toker Girne American University, Industrial Engineering, Turkey
Assoc.Prof.Dr. Zafer Ağdelen Girne American University, Industrial Engineering, Turkey
Assoc.Prof.Dr. Tülin Bodamyalı Girne American University, Industrial Engineering, Turkey
Keywords: government, health services, perceptional analysis, statistics, North Cyprus
In the recent years, awareness has risen of how patients perceive the quality of their care. In an extremely competitive environment, patient satisfaction has become a tool to gain attention and value amongst the patients as well as providers. Hospitals and other health care centers are increasingly using this information while making important decisions regarding the operational and treatment plans. The health centers can use survey results to design and track quality improvement over time, as well as compare themselves to other health centers. Also, this information is of great use for healthcare accreditations. By conducting their own surveys, the health care organizations are able to recognize and resolve potential patient satisfaction problems and thus improve their strategies. Having satisfaction surveys also helps identify the specific needs of the patients for the health care provider. Recently, in the Turkish Republic of Northern Cyprus (TRNC), the concept of patient satisfaction also gained great importance. Patients are complaining about the health system of TRNC and the Ministry of Health is seeking for changes and solutions which will lead to a strong, satisfactory and sustainable health system. The health system of Turkish Republic of Northern Cyprus is mainly based on governmental hospitals on non-profit basis. The majority of the community prefers to have treatment in those hospitals. In Turkish Republic of Northern Cyprus, there are several problems related with functioning and performance of public hospitals, such as lack of patient satisfaction, long waiting time for treatment and dissatisfaction of doctors. In this paper, it is aimed to focus on the perceptional analysis of patients, which will enlighten the patient component. This will provide a scientific basis by for the operations of the Ministry of Health for the general improvement of the public health system of Turkish Republic of Northern Cyprus. To collect data about the patients’ perceptions, a questionnaire consisting of three main parts is prepared. Based on these facts, a set of suggestions are made on the improvement of health services for the purpose of increasing hospital performance.
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Behavior of Reinforced Concrete Corbels Strengthened with Ferrocement Sheets
Mr. Azad A. Mohammed University of Sulaimani, Civil Engineering, Iraq
Ms. Dunyazad K. Assi University of Sulaimani, Civil Engineering, Iraq
Keywords: Bonding, Corbel, Ferrocement, Sheets, Strengthening
The present research outlines behavior of reinforced concrete corbels strengthened with precast ferrocement sheets made from high strength mortar contain wire meshes. Such type of sheets was tested to be an alternative for those strengthening materials having high costs per unit. For this purpose nine reinforced concrete corbels were cast and tested for ultimate load capacity and deformations. Test results indicate that there is a load enhancement over that of control reinforced concrete corbels as a result of strengthening with HSF sheets regardless of the amount of steel reinforcement provided to the corbel. Percentage of ultimate load in general varies from 132% to 207%. The load enhancement was found to be more for those corbels lightly reinforcement for flexure. Test results also indicate that there is a proportionality between load enhancement of concrete corbels and thickness of HSF sheets provided to the corbel. An equation obtained from regression analysis was proposed to calculate the ultimate load capacity of reinforced concrete corbel strengthened with HSF sheets and can be used for the design of reinforced concrete corbels strengthened with HSF sheets.
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Design and Construction of an Autonomous Unmanned Ground Vehicle (UGV) and Basic Waypoint Trajectory Tracking
Mr. Halit Hülako Hakkari Üniversitesi, Makine Mühendisliği, Turkey
Prof.Dr. Sadettin Kapucu Gaziantep Üniversitesi, Makine Mühendisliği, Turkey
Keywords: Unmanned, Trajectory Tracking, GPS
In recent years, Unmanned Vehicles has been quite popular for the researchers and that vehicles are still being developed by the researchers and engineers. Unmanned Vehicle have to do all operations without aid and have all capabilities. In this study, it was worked on tracking of waypoint trajectory by Autonomous Unmanned Ground Vehicle. It was utilized from microprocessor, GPS and compass module. The operating working principle of Unmanned Ground Vehicle is as follow: At the begining, waypoints or earth coordinates are loaded an eeprom, GPS modul calculates the new position for every 200 ms to find current angle between North and trajectory that is a line between the current possition and destination\waypoint. Compass module also calculates current heading value that it shows angle between North and course. According to this datas microprocessor compares the results and chooses the correct angle of servo that controls the direction of UGV. This platform will be used as a test vehicle to improve capability of tracking waypoint trajectory.
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Counting Passengers in an Elevator Cabin Using Real-Time Image Processing
Ms. Serap Kazan Sakarya University, Computer Engineering, Turkey
Mr. M. Fatih Adak Sakarya University, Computer Engineering, Turkey
Keywords: elevator cabin, image processing, transfer time
The waiting and transfer time of passengers effects the quality of service at elevators. Stopping and waiting on each floor for the people have very big importance when considering transfer time of the elevators. Although the elevator is full, it often stops unnecessarily. The transfer time can be reduced by means of preventing unnecessary stops. In this study, in order to shorten the transfer time and to prevent unnecessary stops, the passengers in the elevator and waiting people at each floor are counted by using real-time image processing technique based on image segmentation.
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Developing Virtual Driving Simulator for Educational Purposes
Mr. İsmail Öztel Sakarya University, Computer Engineering, Turkey
Mr. Cemil Öz Sakarya University, Computer Engineering, Turkey
Keywords: driving simulator, driver education, game programming, virtual reality, traffic accident prevention
Analyzing traffic accidents, human behavior represents the most relevant problem; especially drivers’ behavior. In this regard, driver education becomes essential. In our project, we present a simulator consisting of both software and hardware including, a steering wheel, a pedal system, a shift knob, a seat and a visual display. This system needs a virtual platform modeled using Google Sketchup-3D Modeling Program. We used a Unity Game Engine in order to enable the platform. Thanks to this simulator, prospective drivers will be able to acquire experience in a virtual environment without the risks of the real world. In the simulator, the driver is penalized for every infraction according to the Turkish traffic rules. For instance, if the driver runs a red light, then penalty points are given. If the driver does not follow traffic signalization, again the simulator penalizes the driver with penalty points.
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Real Time Virtual Mirror Using Kinect
Ms. Gözde Yolcu Sakarya University, Computer Engineering, Turkey
Ms. Serap Kazan Sakarya University, Computer Engineering, Turkey
Keywords: Virtual mirror, Virtual try-on, Virtual reality, Image processing, Real time Systems, Kinect for Windows
This paper proposes a real time image processing approach to enable users to try virtual garments on in front of a virtual mirror. The user’s hand motions select the clothes from a list on screen. Afterwards a virtual representation of the user wearing the selected virtual clothes appears in the virtual mirror. To create a more realistic effect, the system takes into account different images of the clothes according to different human poses and movements. Additionally, we developed an algorithm for matching up all motions between the virtual clothes and the human being. In this study, we benefit from the Microsoft Kinect SDK in order to follow the user’s movements, coordinate the suitable clothe try-ons and provide depth sort effect to the human body and the clothes.
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Using Gravitational Force in Terrain Optimization Problems
Ms. Erisa Terolli Epoka University, Computer Engineering, Albania
Mr. Briland Hitaj Epoka University, Computer Engineering, Albania
Dr. Oguz Altun Epoka University, Computer Engineering, Albania
Keywords: optimization problems, gravity variation, physics, agents,minimal point
Optimization problems represent algorithms designed for difficult problems which may require huge amount of space or computational time. Such kind of algorithms bring out solutions which are optimal and at the same time closer to the real life environments where not everything is precise and the possibility of errors is present at every instant. Finding the minimal point in a terrain is a challenge of its own, especially when we are dealing with an unknown area. In order to tackle this problem, we thought of making use of gravitational force, since it is proportionally related to earth center proximity. In an unknown terrain, we spread our agents, that are capable to communicate information to one another at randomly generated positions. Later on, each of these agents calculates the gravity variation with altitude at its respective position. Since, we were looking to find the optimal minimum point in the terrain, after the gravity variation with altitude is computed by each agent, the highest gravity is found. This is communicated to the other agents as well and they start moving toward the agent that is currently found at an area with high gravity variation. The agents move toward the high gravity agent with a certain heuristic coefficient. During their path they may encounter other terrain points where the gravitational force is stronger, which would cause a change in the path of other agents making them move toward the newly found position. This is done until an optimal minimum is found by the agents. Our test results so far have been very promising. We aim to develop the algorithm furthermore in order to increase its efficiency and efficacy. We strongly believe that such an algorithm can be used to reach in the unexplored areas of ocean floor, or searching for minerals by minimizing the area of search in an optimal time.
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An Analog CMOS Tunable Current-Mode Classifier Core Circuit with Reduced Power Consumption
Prof.Dr. Ali Zeki Girne American University, Electrical & Electronics Engineering, Turkey
Keywords: Analog Classifier, Neural Networks
Classification is an essential task in neural networks, pattern recognition and artificial intelligence. One can achieve classification via software or hardware, where the latter can supply much faster responses. Hardware realization of a classifier may be based on digital or analog techniques [1]. In analog realization, activation function of a neuron can be based on Euclidian distance, Gaussian neighborhood, trapezoidal (rectangular) comparison window, etc. The rectangular activation function supplies a binary output and is suitable for rectangular partitioning only. Nevertheless, some techniques, like Fisher's linear discriminant analysis (LDA) can be used for pre-processing so as to widen the application area of such classifiers [2]. An analog classifier can be designed in voltage- or current-mode. Properly designed, current-mode circuits can be superior, in terms of speed, accuracy and other facilites (e.g. Easy addition/subtraction of currents) . Tunability of a classifier is another important feature which avails a more flexible configurable system. In this work, a CMOS tunable current-mode classifier core circuit (1-dimentional core neuron) has been proposed. The circuit was based on trapezoidal activation function and the motivation was to obtain a new topology which consumes less power with respect to its counterparts [3], [4], which also accept one input (Iin), compare it with the trapezoidal (rectangular) region's (window's) upper and lower limits (I1 and I2) and supplies a binary output (Iout=IH or Iout=0) based on this comparison, where I1, I2 and IH are tunable. Tunability enables easy realization and configuration of a multi-dimentional classifier by simply connecting copies of the a single core neuron structure. The structure of the proposed circuit have similarities with the one proposed in [3], but current steering/switching methods and realization of the logic are different or modified. Particularly the following modifications reduced the contributions of I2 and IH currents to the total power consumption: i) Creating I2 from sum of a copy of I1 and the "window width" Iw (Iw=I2-I1), which can be used to indirectly tune I2. ii) Not steering IH to an alternative path when Iin is out of the "window" (The current path is cut off). For the following two ultimate cases, the power consumption of the proposed circuit aproaches to half (50%) of that of [3]: i) I2 and I1 are close (Iw is small) and are dominant over Iin (so, Iin is out of the” window”) and IH, ii) IH is dominant over Iin, I2 and I1, while Iin is out of the ”window” (Example for case (i): I2=500nA, I1=480nA, Iin=15nA, IH=30nA –> Pnew=0.53xPold. Example for case (ii): I2=35nA, I1=15nA, Iin=45nA, IH=500nA –> Pnew=0.55xPold) (Note: Reference paths of currents are included in power calculation). Power consumption approaches to that (100%) of [3] for the following worst conditions: i) Iin is dominant current (IH>>I2,I1,IH), ii) IH dominates others while Iin is within the ”window” (I2>Iin>I1). (Example for case (i): I2=25nA, I1=10nA, Iin=500nA, IH=35nA –> Pnew=0.93xPold. Example for case (ii):
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I2=70nA, I1=25nA, Iin=50nA, IH=500nA –> Pnew=0.98xPold). When compared with the structure in [4], the proposed structure is much better, achieving as low as 20% of the power of [4] for the best cases and approaching to the same value (100%) for the worst cases. As a typical case example, the current parameter values of the 4 core circuits (CCs) of [4] were used (CC1: I1= 70nA, I2=140nA, IH=60nA, CC2: I1= 210nA, I2=280nA, IH=120nA, CC3: I1=60nA, I2=140nA, IH=100nA, CC4: I1= 280nA, I2=360nA, IH=80nA) with ultimate cases for Iin, namely a low (IinIin>I1) and a large (Iin>I2) value. As Iin was varied from 1nA to 500nA, circuit simulations yielded power consumption values for the new circuit ranging roughly from 55% to 90% of that of [3] and from 40% to 55% of that of [4]. The simulation results were in close agreement with the theoretical calculations. During the simulations, device aspects, biasing methods, bias currents and VDD supply values were set to equal values for the compares circuits as far as possible, in order to keep the comparison a fair one. [The details of the proposed structure and the theoretical/simulation results will be supplied in the main paper. Also, the references will be extended] References: [1] Elmasry, M.I. (Editor), "VLSI Artificial Neural Networks Engineering", Springer, 1994. [2] Goknar, I.C., Yildiz, M., Minaei, S, ""Neural CMOS-Integrated Circuit and Its Application to Data Classification", IEEE Tran. Neural Networks and Learning Systems, Vol. 23, No. 5, pp. 717-724, May 2012. [3] Yildiz, M., Minaei, S, Goknar, I.C., "A CMOS classifier circuit using neural networks with novel architecture", IEEE Tran. Neural Networks and Learning Systems, Vol. 18, No. 6, pp. 1845-1849, Nov. 2007. [4] Yildiz, M., Minaei, S, Goknar, C., "A flexible current-mode classifier circuit and its applications", International Journal of Circuit Theory and Applications, Vol. 39, No. 9, pp. 933-945, Sep. 2010.
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DLF Recovery WDM Optical Network Using Edge Disjoint Path with Shortest Path Method
Dr. Sandeep Joshi Manipal University, India
Keywords: Optical network, wavelength division multiplexing(wdm),disjoint path, Menger’s Theorem, Ford Fulkerson max flow algorithm ,Double link failure(DLF).
In recent years Optical network become a backbone for data transfer. Due to data transfer rate (TB/S) with wavelength division multiplexed (WDM) concepts optical networks become very important. Optical fibers, the connecting media in optical networks, are prone to failures. Hence it becomes important to make the network resilient to link failures. Link and path failure in WDM network become a bottleneck in high data transfer rate. Survivability and Recovery in essential in case of link or path failure[1]. Many researchers have done work for single link as well as partial double link failure. I propose dual link recovery with shortest paths via creating communication network for each node in network.
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Design Patterns as First Class Citizens in Software Development
Asst.Prof.Dr. Birol Aygün Yeditepe University, Turkey
Keywords: Programming Languages, ontology-based intelligence
This paper briefly reviews the notion of patterns as used in some aspects of our society, in particular in communication, computation and genetics. From bit-level programming to current high-level languages, the progression of pattern usage in programming languages is examined.
While the concept of design patterns is not new, for various reasons the actual use of design patterns in software development has been very limited. Results in this area are reported andreasons for this occurence are investigated.
A higher-level programming framework with patterns as “first-class citizens” is proposed. The framework, itself based on patterns, will have a detailed knowledge of syntactic, semantic and pragmatic specifications of design patterns. The framework will assist programmers in developing code using design patterns directly, with the eventual aim of improving efficiency, reliability, standardization and maintainability inproject development.
Finally, the potential application of ontology-based intelligence in the framework to help users select patterns, to diagnose problems and to improve the performance of the framework itself over time will be posted as a future research problems.
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ISOLATED WORD RECOGNITION
Prof.Dr. Rahib H. Abiyev Near East University, Department of Computer Engineering, Turkey
Mr. Hussein Mohammed University of Mosul, Department of Computer Engineering, Iraq
Keywords: LPC, MFCC, NN
The paper presents the design of speech recognition system that uses preprocessing, feature extraction and classification stages. In preprocessing stage a denoising is done to get the speech data without noise. In feature extraction stage Linear Predictive Coding (LPC), Mel Frequency Cepstral Coefficients (MFCC), and Spectrogram methods are used to extract the features of the word. Neural Networks (NN) was used to classify the spoken words to different patterns so the system can recognize unknown spoken words according to these patterns. The set of spoken words are used in simulation of the system. The comparative results of the system have been provided using above mentioned feature extraction methods.
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Estimation of Concrete Compressive Strength with Artificial Neural Network
Mr. Selahattin Albayrak Gumushane University, Civil Eng. Dept, Turkey
Mr. Ahmet Çavdar Gumushane University, Civil Eng. Dept, Turkey
Mr. Sinasi Bingol Gaziosmanpasa University, Civil Eng. Dept, Turkey
Keywords: Artificial Neural Network, Concrete Compressive Strength, Ultrasonic velocity, Schmidt Hummer
Because concrete has inhomogeneous structure, control of its strength and quality in-situ is pretty difficult. Non-destructive test methods can be used for determination of mechanical properties of concrete in-situ. Although, these methods are practical, they can give deceptive results. It is needed to be supported with the destructive methods to obtain more sensitive result and decrease these deceptive results. On the other hand, numerical calculation methods, originated as parallel with the developments on today’s computer technology, provide a great advantage especially in prediction of experimental results. One of them is Artificial Neural Networks (ANN), which is a sub-branch of Artificial Intelligence (AI). In this study, it is investigated estimation of concrete compressive strength with ANN by using non-destructive test methods results. 151 series of experiments that contain results of curing time (day), ultrasonic velocity (m/s) and Schmidt hammer are tested to obtained concrete compressive strength. In addition, compressive strengths are obtained with destructive method. 121 series of examples are used in learning stage and 30 series of examples are used in test stagefor ANN application to investigate approximation of experimental results. It is investigated that the results obtained are quite approximate each other.
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The Effects of Cure Conditions on Mechanical Properties of Polymer Modified Cement Mortars
Mr. Ahmet Çavdar Gumushane University, Civil Eng. Dept, Turkey
Mr. Sedat Sevin Gumushane University, Civil Eng. Dept, Turkey
Mr. Yusuf Kaya Gumushane University, Civil Eng. Dept, Turkey
Mr. Sinasi Bingol Gaziosmanpasa University, Civil Eng. Dept, Turkey
Keywords: StirenButadienRubber,Polycarboxylate modified StirenButadien, Rubber, Modified Acrylic Dispersion, compressive strength, flexural strength, deflection
The uses of polymers for various structural applications are gaining popularity throughout the World. The flexural strength and toughness properties of these composites maybe significantly improved by incorporation of different types of polymers.In this study, three different types of polymers are added to cement mortars, and then these mortarsare cured under three different conditions. Thus, it is aimed to investigate their mechanical contributions to mortars and to determine the most suitable cure condition for polymer modified concrete, comparatively. StirenButadienRubber (SBR), Polycarboxylate modified StirenButadienRubber (PSBR), Modified Acrylic Dispersion (MAD)polymers are chosen as polymers. These polymers are added into the mortars inthree different ratios (0.0%, 5%, 10%) by volume and the polymer modified mortars are cured under three different conditions (one day in the water - one day out, 16 hours in the water - 8 hours out, watering twice a day). The physical propertiesand flexural strengths, deflections and compressive strengths of the cement mortarsare investigated. It is concluded that each polymer contributes the mechanical and physical properties of mortars in different addition ratios and different cure conditions. The mortars modified with MAD polymer show the best performance for chosen polymer addition ratios and also watering twice a day is the most suitable cure condition.When MAD is used, the flexural strengths of the samples increasein important level without compressive strength falls.
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Finite Product Representation via Multiplicative Calculus in Signal Processing
Assoc.Prof.Dr. Bülent Bilgehan Girne American University, Electrical & Electronics Engineering, Turkey
Keywords: Product Representation, Multiplicative Calculus, Signal Processing
This work demonstrade the application of multiplicative calculus in signal processing. Product representation of a function generated in place of series (Fourier, Taylor) representation for typical applications. The product representation reveals the advantages compare with series representation especially when the fitted function is selected to match with the behaviour of the signal in process.
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Automatic control system of discrete dosing process
Assoc.Prof.Dr. S.F. Jafarov Power Engineering, Azerbaijan
Dr. R.E. Mammadova Power Engineering, Azerbaijan
Dr. F.N. Mammadov Power Engineering, Azerbaijan
Keywords: Controllers, Dosing
In the present article the installation details of control system of discrete dosing process have been elaborated. For that, the automatization of technological process via technical means and programs (programmed logic controllers) has been proposed. It is noted that the following and typical to this time problems exist in manufacturing enterprises. They are mainly: 1) in various telemechanical and automatizatization systems that collect and register the initial data, carry out saving of provided parameters of processes and shut at dispatcher control level 2) in energy supply and energy sources counting systems 3) separate local automatized work places and controlling problems in workshop counting networks. The solution of these issues is considered to be an actual problem from data measuring, automatization and control system points of view. Due to authors propositions, structural changes, new type of software for automatic regulation of discrete dosing process have been conducted. The implementation of automatized logic controllers; enabled the realization of industrial tires, real-time interference into technological data, effective Supervisory Control and Data Acquisition systems and increase of employees’ awareness of information technologies. One of these technological processes is dosing process of granular materials. The primary goal in automatization of dosing process is not only a mass measuring but also an automatic control and regulation of technological processes. Modern automatic dosing units are integral parts of complex automatization in different industrial areas. Automatic dosing equipment for granular materials are classified due to installation structure of technological processes: by movement of materials along horizontally placed equipment and flow stream itself, by conveyor transportation of materials. As it is seen, due to conduct of automatized controllers important results have been achieved and here are some examples of these achiements: the working principle of technological process of discrete dosing has been researched, the structural scheme of control system of discrete dosing process has been sketched, the automatized logic controllers software for the control of discrete dosing process has been worked out.
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PROCESSING OF GEOPHYSICAL EXPLORATION DATA CONDUCTED BY SEISMOACOUSTIC WAY ON THE BASIS OF “FUZZY LOGIC” METHOD
Dr. F.N. Mammadov Power Engineering, Azerbaijan
Dr. R.E. Mammadova Power Engineering, Azerbaijan
Keywords: Fuzzy Logic, Seismoacoustic
The present article is devoted to processing and interpretation of data obtained from the geophysical exploration conducted by seismoacoustic way in the Caspian sea on the basis of “Fuzzy logic” method. When using traditional processing methods, algorithms and programs for processing the data and getting a profile image, there was a great need for improving the accuracy and quality of pictures. One of the disadvantages of the methods used in this sphere is that, distinctive depiction of the boundaries of geological structures that form the earth crust on seabed and frontiers of tectonic disorders as well as their detailed study are problematic. There is a great demand for upgrading calculation methods and geological interpretation means of geophysical data. The processing of seismoacoustic data based on the implementation of “Fuzzy logic “ method is of great significance from the point of view of accuracy achievement, mitigation of errors and improvement of the quality of profile images. In fact, the outlines of geological structure levels of the earth crust on seabed are not of homogeneous composition. Outlines of separation of sea water, silt, mud, sand, lime and etc.levels from each other turned to a compound structure and consist of this and other types of homogeneous rocks. Finding out the ratio of mud to sand and others inside the separation outline of mudstones and sandstones by means of “Fuzzy logic” method contributes to the improvement of accuracy. Creation of database, investigation and recognition algorithms as well as establishment of expert systems for the implementation of rock types are the main stages of this method. Depicting seismoacoustic profiles with traces and studying spectral characteristics of these traces are essential while processing the initial data. As it is known, the number of pixels in the points of profile traces and amplitudes are the main characteristic parameters. The assessment and calculation of these parameters with high precision in creation of database via “Fuzzy logic” processing method plays a significant role. Another advantage of using this data processing and interpretation method is that, the distinction of anomalies and tectonic disorders unexplored in the research area is clearly shown, the possibility of defining the structure changes and assessing the rock type is high.
Author Index Abdullah Ateş (Prof.Dr.) 23 Adalet Abiyev (Prof.Dr.) 5 Adnan Cora 42 Ahmet Çavdar 61, 62 Ali Haydar (Assoc.Prof.Dr.) 41, 43 Ali Ozyapici (Asst.Prof.Dr.) 7 Ali Zeki (Prof.Dr.) 56 Alkın Yurtkuran 16, 18, 19 Aslı Aksoy (Dr.) 17 Aykan Karademir 6 Azad A. Mohammed 50 Baha Şen (Asst.Prof.Dr.) 36 Birol Aygün (Asst.Prof.Dr.) 59 Briland Hitaj 55 Buğçe Eminağa 11 Burcu Toker (Asst.Prof.Dr.) 48, 49 Bülent Bilgehan (Assoc.Prof.Dr.) 63 Bülent Cerit (Dr.) 24, 26 Cemil Öz 53 Dirim Şener 26 Dunyazad K. Assi 50 Erhan Güneyisi (Assoc.Prof.Dr.) 27 Erisa Terolli 55 Erman Aktürk 29, 35 Ertan Durmuşoğlu 6 Eser Yücel 35 Ezgi Deniz Ülker (Dr.) 44 F.N. Mammadov (Dr.) 64, 65 Fatemeh Nouban 2 Fatih Taşpınar 6 Gökhan Kalem 24 Gözde Yolcu 54 Güneş Küçükyazıcı 24, 26 Halit Hülako 51 Hatice Özkoç (Asst.Prof.Dr.) 15 Hussein Mohammed 60 İbrahim Erşan (Asst.Prof.Dr.) 46, 47 Ibrahim Rashid Balani 9 İlker Küçükoğlu 16, 17, 18, 19 İsmail Öztel 53 Kabir Sadeghi (Assoc.Prof.Dr.) 1, 2 Kamil Dimililer (Assoc.Prof.Dr.) 41, 43 Kasım Mermerdaş (Asst.Prof.Dr.) 27 M. Fatih Adak 52 Mahesan Bavan 37 Md. Haidar Sharif (Asst.Prof.Dr.) 20 Mehmet Fatih Akay (Assoc.Prof.Dr.) 28, 29, 30, 35 Mehmet Gesoğlu (Assoc.Prof.Dr.) 27
Mehmet Sait VURAL 33 Mehmet Sakin 27 Mehmet Sinan Yıldırım 22 Metin Mutlu Aydın 22 Murat Karakaya (Asst.Prof.Dr.) 12, 13 Murat OĞUL 32 Musa PEKER 36 Mustafa Açıkkar 28 Mustafa GÖK (Assoc.Prof.Dr.) 33 Mustafa Riza (Asst.Prof.Dr.) 11 Mübariz Eminli (Prof.Dr.) 14 N. Aydın Ünverdi (Asst.Prof.Dr.) 40 N. Özlem Ünverdi (Asst.Prof.Dr.) 40 N. Suat Canarslan (Dr.) 45 Necati MAHİR (Assoc.Prof.Dr.) 8 Nefiye ERKAN 31, 32 Nida Gökçe (Dr.) 14, 15 Nursel AKÇAM (Asst.Prof.Dr.) 31, 32 Nursel Öztürk (Prof.Dr.) 17 Oguz Altun (Dr.) 55 Onur Can Yardibi 42 Orhan Karpuz (Asst.Prof.Dr.) 22 Özlem Kanga 16, 18, 19 Özge YETİK 8 Özgür Cemal Özerdem (Assoc.Prof.Dr.) 9 R.E. Mammadova (Dr.) 64, 65 Rahib H. Abiyev (Prof.Dr.) 60 Recep Sultan 42 Resul Kara (Assoc.Prof.Dr.) 6, 34 S.F. Jafarov (Assoc.Prof.Dr.) 64 Sadettin Kapucu (Prof.Dr.) 51 Sadık Ülker (Prof.Dr.) 44 Safa Mert Keleş 42 Sahin Uyaver (Asst.Prof.Dr.) 20 Sandeep Joshi (Dr.) 58 Sedat Sevin 62 Selahattin Albayrak 61 Serap Kazan 52, 54 Seval Ene 17 Shahaboddin Daneshvar 30 Shahin Keynoush (Asst.Prof.Dr.) 39 Sinasi Bingol 61, 62 Tamer Tulgar (Asst.Prof.Dr.) 46, 47 Tolgay Karanfiller (Dr.) 7, 38 Tülin Bodamyalı (Assoc.Prof.Dr.) 49 Yusuf Kaya 62 Zafer Ağdelen (Assoc.Prof.Dr.) 41, 48, 49 Zehra Karapınar Sentürk (Dr.) 34 Zeki Yetgin (Asst.Prof.Dr.) 33