International Journal of Soft Computing and EngineeringInternational Journal of Soft Computing and EngineeringInternational Journal of Soft Computing and Engineering

n E d n g i na e g e n i r t i n u g p m o C t f o S I n f t eo l r n a a n r t i u o o n J a l

IJSCEIJSCE

Exploring Innovation

www.ijsce.org

EXPLORING INNOVA

TION

ISSN : 2231 - 2307Website: www.ijsce.org

Volume-7 Issue-6, JANUARY 2018Volume-7 Issue-6, JANUARY 2018

Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. Ltd.

Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. Ltd.

Editor-In-Chief Dr. Shiv Kumar

Ph.D.(CSE), M.Tech.(IT, Honors), B.Tech.(IT)

Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India

Professor & Head, Department of Computer Science & Engineering, Lakshmi Narain College of Technology-Excellence (LNCTE),

Bhopal (M.P.), India

Associated Editor-In-Chief Dr. Pradeep Kumar Gupta

PDF, Ph.D(CSE), ME(CSE), BE(CSE), MACM, MIEEE, LMCSI, SMIACSIT

Assistant Professor(Sr. Grade), Department of Computer Science & Engineering, Jaypee University of Information Technology,

Shimla (H.P.), India

Dr. Mayank Singh

PDF (Purs), Ph.D (CSE), ME (Software Engineering), BE(CSE), SMACM, MIEEE, LMCSI, SMIACSIT

Department of Electrical, Electronic and Computer Engineering, School of Engineering, Howard College, University of KwaZulu-

Natal, Durban-4041, South Africa.

Dr. Shachi Sahu

Ph.D. (Chemistry), M.Sc. (Organic Chemistry)

Additional Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal(M.P.), India

Scientific Editors Dr. Venkat K. Krishnan

Post-Doctoral Research Associate, Electrical and Computer Engineering, 1121 Coover Hall, Iowa State University, Ames, Iowa, USA

50011

Dr. CheeFai Tan

Faculty of Mechanical Engineering, University Technical, Malaysia Melaka, Malaysia

Dr. Moinuddin Sarker

Vice President of Research & Development, Head of Science Team, Natural State Research, Inc., 37 Brown House Road (2nd Floor)

Stamford, CT-06902, USA.

Dr. Shanmugha Priya. Pon

Principal, Department of Commerce and Management, St. Joseph College of Management and Finance, P.O.Box.920, Makambako,

Njombe Region, Tanzania, East Africa, Tanzania

Dr. Guoxiang Liu

Member of IEEE, University of North Dakota, Grand Froks, N.D., USA

Executive Editors Dr. T.C. Manjunath

Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India

Dr. Kosta Yogeshwar Prasad

Director, Technical Campus, Marwadi Education Foundation’s Group of Institutions, Rajkot-Morbi Highway, Gauridad, Rajkot,

Gujarat, India

Dr. P. Dananjayan

Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry, India

Dr. Sunandan Bhunia

Associate Professor & Head,, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West

Bengal, India

Dr. Rajiv Srivastava

Director, Department of Computer Science & Engineering, Sagar Institute of Research & Technology, Bhopal (M.P.), India

Dr. Chakunta Venkata Guru Rao

Professor, Department of Computer Science & Engineering, SR Engineering College, Ananthasagar, Warangal, Andhra Pradesh, India

Dr. Anuranjan Misra

Professor, Department of Computer Science & Engineering, Bhagwant Institute of Technology, NH-24, Jindal Nagar, Ghaziabad,

India.

Dr. Ebrahim Nohani

Associate Professor, Department of Hydraulic Structures, Dezful Branch, Islamic Azad University, Dezful, Iran

Advisory Chair Dr. Uma Shanker

Professor & Head, Department of Mathematics, CEC, Bilaspur(C.G.), India

Dr. Rama Shanker

Professor & Head, Department of Statistics, Eritrea Institute of Technology, Asmara, Eritrea

Dr. Vinita Kumari

Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., India

Dr. Sadhana Vishwakarma

Associate Professor, Department of Engineering Chemistry, Technocrat Institute of Technology, Bhopal(M.P.), India

Dr. Kamal Mehta

Associate Professor, Deptment of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India

Dr. Suresh Babu Perli

Professor & Head, Department of Electrical and Electronic Engineering, Narasaraopeta Engineering College, Guntur, A.P., INDIA

Dr. Binod Kumar

Associate Professor, Schhool of Engineering and Computer Technology, Faculty of Integrative Sciences and Technology, Quest

International University, Ipoh, Perak, Malaysia

Dr. Chiladze George

Professor, Faculty of Law, Akhaltsikhe State University, Tbilisi University, Georgia

Dr. Kavita Khare

Professor, Department of Electronics & Communication Engineering, MANIT, Bhopal (M.P.), INDIA

Dr. C. Saravanan

Associate Professor (System Manager) & Head, Computer Center, NIT, Durgapur, W.B. India.

Managing Chair Mr. Jitendra Kumar Sen

International Journal of Soft Computing and Engineering (IJSCE)

Reviewer Chair Dr. Giriraj Kumar Prajapati

Associate Professor, Department of Electronics and Communication Engineering, Sree Chaitanya Institute of Technological Sciences,

Timmapur, Karimnagar (Telangana)-505527, India.

Dr. Prasenjit Chatterjee

Associate Professor & Head, Department of Mechanical Engineering, MCKV Institute of Engineering, Howrah (West Bengal)-

711204, India.

Dr. Mallavolu Malleswararao

Associate Professor & Head, Department of Electrical & Electronics Engineering, RISE Krishna Sai Prakasam Group of Institutions

Ongole, (Andhra Pradesh)-523272, India.

Dr. Deepali Sharma

Assistant Professor, Department of Radiation Oncology, School of Medicine, Tulane University, LA, USA.

Dr. Sadu Venkatesu

Associate Professor, Department of Mechanical Engineering, Sree Vidyanikethan Engineering College (Autonomous) A. Rangampet,

Tirupati (Andhra Pradesh), India.

Dr. B. Krishna Kumar

Professor, Department of Electronics and Communication Engineering, Methodist College of Engineering and Technology,

Hyderabad (Telangana)-500001, India.

Dr. M. Vasim Babu

Associate Professor, Department of Electronics and Communication Engineering, KKR & KSR Institute of Technology and Sciences

(KITS) Vinjanampadu, Guntur, (Andhra Pradesh), India.

Dr. Froilan D. Mobo

Assistant Professor, Department of Computer and Social Sciences, Philippine Merchant Marine Academy, San Narciso, Zambales,

Philippines.

S.

No

Volume-7 Issue-6, January 2018, ISSN: 2231-2307 (Online)

Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.

Page

No.

1.

Authors: Muhammad Awais Umar, Mujtaba Hussain, Basharat Rehman Ali, Muhammad Numan

Paper Title: Super (a,1)-Tree-Antimagicness of Sun Graphs

Abstract: Let ),(= EVG be a finite simple graph with |)(| GV vertices and |)(| GE edges. An edge-covering

of G is a family of subgraphs tHHH ,,, 21 such that each edge of )(GE belongs to at least one of the

subgraphs iH , ti ,1,2,= . If every subgraph iH is isomorphic to a given graph H , then the graph G admits

an H -covering. A graph G admitting H covering is called an ),( da - H -antimagic if there is a bijection

|})(||)(|,{1,2,: GEGVEVf such that for each subgraph H of G isomorphic to H , the sum of

labels of all the edges and vertices belonged to H constitutes an arithmetic progression with the initial term a and

the common difference d . For |})(|,{1,2,3,=)( GVVf , the graph G is said to be super ),( da - H -

antimagic and for 0=d it is called H -supermagic. In this paper, we investigate the existence of super ,1)(a - 3S

-antimagic labeling of Sun graphs nSG , its uniform subdivision )(rSGn , disjoint union of sun graphs and its

uniform subdivision denoted by mSGn and mSGn(r) respectively, where r, m ≥ 1.

Keywords: Sun graph nSG , uniform subdivided Sun graph )(rSGn , su- per (a, 1)-S3-antimagic, super (a, 1)-

S3(r)-antimagic, disjoint union of Sun graph mSGn and its uniform subdivision mSGn(r). MR (2010) Subject

Classification: 05C78, 05C70

References:

1. Ba c

a, M., Kimáková, Z., A. Semani c

ová-Fe n

ov c

íková and Umar, M.A., Tree-Antimagicness of Disconnected Graphs, Mathematical

Problems in Engineering, Vol. 2015, Article ID 504251, 4 pages, http://dx.doi.org/10.1155/2015/504251.

2. Ba c

a, M., Brankovic, L., Semani c

ová-Fe n

ov c

íková, A., Labelings of plane graphs containing Hamilton path, Acta Math. Sinica -

English Series, 2011, 27(4), 701–714.

3. Ba c

a, M., Miller, M., Phanalasy, O., Semani c

ová-Fe n

ov c

íková, A., Super d-antimagic labelings of disconnected plane graphs, Acta

Math. Sinica - English Series, 2010, 26(12), 2283–2294.

4. Ba c

a, M., Lin, Y., Muntaner-Batle, F.A., Rius-Font, M., Strong labelings of linear forests, Acta Math. Sinica - English Series, 2009,

25(12), 1951–1964.

5. Ba c

a, M., Miller, M., Super edge-antimagic graphs: A wealth of problems and some solutions, Brown Walker Press, Boca Raton, Florida,

2008.

6. Ba c

a, M., Numan, M., Shabbir, A., Labelings of type (1,1,1) for toroidal fullerenes, Turkish Journal of Mathematics, 2013 37, 899–907.

7. Figueroa-Centeno, R.M., Ichishima, R., Muntaner-Batle, F.A., The place of super edge-magic labelings among other classes of labelings,

Discrete Math., 2001, 231, 153–168.

8. Gutiérrez, A., Lladó, A., Magic coverings, J. Combin. Math. Combin. Comput., 2005, 55, 43–56.

9. Inayah, N., Salman, A.N.M., Simanjuntak, R., On ),( da - H -antimagic coverings of graphs, J. Combin. Math. Combin. Comput., 2009,

71, 273–281.

10. Inayah, N., Simanjuntak, R., Salman, A.N.M., Syuhada, K.I.A., On ),( da - H -antimagic total labelings for shackles of a connected

graph H , Australasian J. Combin., 2013, 57, 127–138.

11. Jeyanthi, P., Selvagopal, P., More classes of H -supermagic graphs, Internat. J. Algor. Comput. Math., 2010, 3, 93–108.

12. Lih, K.W., On magic and consecutive labelings of plane graphs, Utilitas Math., 1983, 24, 165–197.

13. Lladó, A., Moragas, J., Cycle-magic graphs, Discrete Math., 2007, 307, 2925–2933. 14. Marr, A.M., Wallis, W.D., Magic Graphs, Birkhäuser, New York, 2013.

15. Maryati, T.K., Baskoro, E.T., Salman, A.N.M., hP -(super)magic labelings of some trees, J. Combin. Math. Combin. Comput., 2008, 65,

198–204.

16. Maryati, T.K., Salman, A.N.M., Baskoro, E.T., Supermagic coverings of the disjoint union of graphs and amalgamations, Discrete Math.,

2013, 313, 397–405.

17. Ngurah, A.A.G., Salman, A.N.M., Susilowati, L., H -supermagic labelings of graphs, Discrete Math., 2010, 310, 1293–1300.

1-4

2.

Authors: Mahmoud Al-Zyood

Paper Title: The Impact of using GIS on the Selection of ATM Sites and Their Effect on Profitability

Abstract: This paper focuses on the factors that influence the locations of automated teller machines (ATMs) and

their impact on profitability using Geographic Information System (GIS). ATM services represent relatively

expensive operations for banks, who seek to meet consumer demands with optimum cost efficiency. The increasing

availability of computer technologies to study and monitor user behaviors have opened many new areas for banks to

streamline their operations, and one novel application is the use of GIS to determine the optimum location of ATMs

to meet consumer demand and maintain market competitiveness related to strategic decisions. GIS can help banks to

analyze competitors in order to maintain current market share and try to expand in the future for continuity and

improve the quality of services provided. This paper undertakes a review of literature related to this topic,

concluding that it is important to locate ATMs using the best strategies to achieve bank objectives in the short and

long term, and that GIS can greatly assist in this by enabling banks to identify the optimum location for ATMs to

meet consumer demand, achieving the strategic aim of maintaining and increasing market share and competition to

5-8

attract and keep customers and increase profitability. Furthermore, it is recommended that future studies explore the

incorporation of social media analytics in banking strategy relative to GIS and the placement of ATMs.

Keywords: ATM, GIS, Profitability, Location

References: 1. Fernandes, L. (2007). The location intelligent enterprise: Enhancing business intelligence with location [online]. DM Insights on Location.

Available at: https://www.directionsmag.com/article/2629 [last accessed 26 Oct. 2017].

2. Ismail, W. M. (2001). Geographic information system, demographic spatial analysis and modeling. MSc thesis, School of Housing, Building and Planning, University Science Malaysia. Available at: http://www.hbp.usm.my/thesis/HeritageGIS/thesis.htm [last accessed 26 Oct.

2017].

3. Jafrullah, M., Uppuluri, S., Rajopadhaye, N., and Srinatha Reddy, V. (2003). An integrated approach for banking GIS. Business GIS, Map India Conference, March 2003.

4. Lee, H. Y. and Kim, E. M. (1997). The study of bank branch location through GIS techniques: The case of Kang Nam Gu, Seoul.

Geographic Information System Association of Korea Publication, 5(1), Serial Number 8, 11-26. 5. Miliotis, P., Dimopoulou, M. and Giannikos, I. (2002). A hierarchical location model for locating bank branches in competitive

environment. International Transactions in Operational Research, 9(5), 549-565.

6. Min, H. (1989). A model-based decision support system for locating banks. Information and Management, 17(4), 207-215. 7. Mylonakis, J., Malliaris, P. and Siomkos, G. (1998). Marketing-driven factors influencing savers in the Hellenic bank market. Journal of

Applied Business Research, 14(2), 109-16.

8. Olsen, L. M. and Lord, J. D. (1979). Market area characteristics and branch bank performance. Journal of Bank Research, 10(2), 102-110. 9. Zhang, L. and Rushton, G. (2008). Optimizing the size and locations of facilities in competitive multi site service systems. Computers &

Operations Research, 35(2), 327-338.

10. Butt, A. I., & Al-Ramadan, B. (2005). Usefulness of Geodemographics & GIS for Banking Sector in Pakistan. Term Paper. pdf. 11. Basar, A., Kabak, Ö., & Ilker Topcu, Y. (2017). A Decision Support Methodology for Locating Bank Branches: A Case Study in Turkey.

International Journal of Information Technology & Decision Making, 16(01), 59-86. 12. Genevois, M. E., Celik, D., & Ulukan, H. Z. ATM Location Problem and Cash Management in ATM’s. Murphy, R. E. (2017). The central

business district: a study in urban geography. Routledge.

13. Endro, T., Taher, A., Zainul, A., & Nayati, U. H. (2017). The Influence of Business Location On Competitive Environment, Competitive Strategy, And Rural Banks Performance On The Example Of Bank Perkreditan Rakyat. Russian Journal of Agricultural and Socio-

Economic Sciences, 65(5) (2017)

14. Paradi, J. C., & Zhu, H. (2013). A survey on bank branch efficiency and performance research with data envelopment analysis. Omega, 41(1), 61-79.

15. Paradi, J. C., & Zhu, H. (2013). A survey on bank branch efficiency and performance research with data envelopment analysis. Omega,

41(1), 61-79. 16. Farahani, R. Z., Rezapour, S., Drezner, T., & Fallah, S. (2014). Competitive supply chain network design: An overview of classifications,

models, solution techniques and applications. Omega, 45, 92-118.

17. Sher, F. A. I. S. A. L., TARIQ, M., & JAN, F. A. (2015). Financial performance of banks in Pakistan: a comparative analysis of public and private sectors. VFAST Transactions on Education and Social Sciences, 6(2).

18. Franco Halpert, D. (2012). Assessment of the centre of gravity technique for the solution of the facility location problem (Bachelor's thesis,

Universidad de La Sabana).

3.

Authors: P. Manimegalai, U. S. Ragupathy

Paper Title: Medical Evaluation of Improved Label Fusion Based Haematoma Segmentation In Traumatic Brain

Injury Images

Abstract: Atlas based segmentation is a well-known method of automatically computing the segmentation. When

multiple atlases are available, then each atlas can be used to compute a ‘label’, which is an estimation of the ground

truth segmentation of a target image. By combining these labels, a more accurate approximation of the ground truth

segmentation can be made. In the proposed work, the axial view of brain CT image for target and prelabelled images

are taken for haematoma segmentation. The canny edge detection is performed to detect the wide range of edges in

the images. The edge detected images are registered by using the rigid transformation method to spatially align one

image to fit into another. The atlas images are selected based on the fixed threshold value and all the selected atlases

are combined by using Selective and Iterative Method of Performance Level Estimation (SIMPLE) algorithm in

label fusion process for the accurate segmentation of haematoma. The label fusion process is performed for a set of 6

labelled images and 10 target images and from the results it is observed that the error is reduced by 3% and

similarity coefficient is increased by 16%, which indicates that the proposed method performs better when compared

to the existing method.

Keywords: Multi Atlas based segmentation, Registration, Edge Detection, label fusion, Brain Images, SIMPLE

References: 1. Chengwen Chu and Masahiro Oda (2017), ‘Multi-Atlas Pancreas Segmentation: Atlas Selection based on Vessel Structure’, Medical Image

Analysis, ELSEVIER, vol. 39, pp.18-28.

2. Christian Ledig , Rolf A. Heckemann , Alexander Hammers , Juan Carlos Lopez and F.J .Virginia (2015), ‘Robust Whole-Brain

Segmentation: Application to Traumatic Brain Injury’, Medical Image Analysis, ELSEVIER, vol. 21, pp.40-58. 3. Eva M. van Rikxoort and Yulia Arzhaeva (2010), ‘Adaptive Local Multi-Atlas Segmentation: Application to the Heart and the Caudate

Nucleus’, Medical Image Analysis, vol. 14, Issue 1, pp.39–49.

4. Heckemann and Hejnal (2006), ‘Automatic Anatomical Brain MRI Segmentation Using Combining Label propagation and Label Fusion’, NeuroImage, vol. 33, no.1, pp.115-126.

5. Irimia A and Toga G (2011), ‘Comparison of Acute and Chronic Traumatic Brain Injury Using Semi-Automatic Multimodal Segmentation

of MR Volumes’, Journal of Neurotrauma, vol. 28, pp.2287– 2306. 6. Isgum I and Staring M (2009), ‘Multi-Atlas-Based Segmentation with Local Decision Fusion Application to Cardiac and Aortic

Segmentation in CT Scans’, IEEE Transactions on Medical Imaging’, vol. 28, no. 7, pp. 1000–1010.

7. Klein S, Staring M and Pluim S (2008), ‘Automatic Segmentation of the Prostate in 3D MR images by Atlas Matching Using Localized Mutual Information’, Journal of Medical Physics, vol. 35, no. 4, pp.1407-1417.

8. Langerak T.R. and van der Heide U.A. (2015), ‘Improving Label Fusion in Multi-Atlas Based Segmentation by Locally Combining Atlas

Selection and Performance Estimation’, Computer Vision and Image Understanding, ELSEVIER, vol.130, pp.71-79. 9. Langerak T.R. and Kotte T.J (2010), ‘Label Fusion in Atlas-Based Segmentation Using a Selective and Iterative Method for Performance

Level Estimation(SIMPLE)’, IEEE Transactions on Medical Imaging, vol 29, no.12, pp.2000-2008.

10. Meritxell Bach Cuadra and Jean-Philippe (2004), ‘Atlas-Based Segmentation of Pathological MR Brain Images Using a Model of Lesion Growth’, IEEE Transactions on Medical Imaging, vol.23, no.10, pp.1301-1314.

11. Rohlfing, Brandt T, Menzel R and Maurer R (2004), ‘Evaluation of Atlas Selection Strategies for Atlas-Based Image Segmentation with

9-13

Application to Confocal Microscopy Image of Bee Brains’, Neuroimage, vol. 21, pp. 1428-1442.

12. Sabuncu and Golland (2010), ‘A Generative Model for Image Segmentation Based on Label Fusion’, IEEE Transactions on Medical

Imaging, vol. 29,no.10, pp.1714–1720. 13. Wachinger and Karl Fritscher (2010), ‘Contour Driven Atlas Based Segmentation’, IEEE Transactions on Medical Imaging’, vol. 34, no. 12,

pp.2492-2502.

14. Warfield and William M. Wells (2004), ‘Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image Segmentation’, IEEE Transactions on Medical Imaging, vol. 23, no.7, pp.903-901.

15. Xabier and Solorzano (2009), ‘Combination Strategies in Multi-Atlas Image Segmentation: Application to Brain MR Data’, IEEE

Transactions on Medical Imaging, vol. 28, no. 8, pp.1266-1277.