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1 ISSN X Volume No. 36 Issue No. 6 September 2012 ` 50/- Technical Trends Applications of Digital Image Watermarking in Industries 5 Article Social Media - Marketers New Playing Field 15 Technical Trends A Conspectus of Soft Data Mining in Bioinformatics 8 Article GSM - R (Global System for Mobile Communication - Railway) 18 Technical Trends Medical Tourism - a Business & Technology Perspective 11 Article The Evolution of COBIT 21 CSI Communications September 2012 A

2 ReaderSpeak() Prof. DVR Vithal (Fellow CSI) writes - Dear Mr President: Compliments on the Golden Jubilee initiative - History of CSI. We take pride in that History of computing in India is largely History of CSI. Do launch Hall of Fame and Prajna Awards (prestigious like Turing awards). Suggest an update in each issue of the Communications on history articles/material received with appeal to do more and enthuse others too to send. It is but apt that first tranche is from Kolkata. Congratulations to the Editorial Team. With warm regards Prof Vithal Mr. MD Agrawal (Past President) writes - I was in Delhi, met Dr Subramanium, Ex Dy Director General of NIC. He was appreciating our CSIC. md Prof. R T Goswami (Director, Birla Institute of Technology Mesra, Kolkata Campus) writes - design and arranging order is really very good. Tamal Prof. Phalguni Mukherjee (CSI Region II Student Coordinator) writes Dear All, Received the August issue of Communication yesterday. An excellent piece of work is done by Debasish. Thanks to DP Sinha also. Many unknown things can be known from this issue. In fact, it is a rare collection for CSI lovers. Once again congratulation to Debasish and his team for bringing out this novel idea. Best wishes, Phalguni Mukherjee Prof. Punam Kumar Saha (Associate Professor, University of Iowa, USA) writes: Great! Fantastic. Punam Mr. Ramanuj Bhattacharya, Chicago, USA (Contributor in Computing in Kolkata - Strolling Down Memory Lane in CSIC August 2012 issue) writes: Great job. I have received the printed copy as well. Best wishes, Ramanuj Prof. Sarmistha Neogy (Chairperson, IEEE Computer Society Chapter of IEEE Kolkata Section) writes: great job!! CSI Communications - Call for Articles for forthcoming issues The cover themes for forthcoming issues of CSI Communications are: October Cyber Music November Embedded Systems December Intelligent Systems January Enterprise 2.0 February Programming Language Paradigms March e-libraries (Future topics will be announced on an ongoing basis) The Editorial Board of CSI Communications is looking for high-quality technical articles for different columns pertaining to the above themes or emerging and current interests. The articles should cover all aspects of computing, information, and communication technologies that should be of interest to readers at large and member fraternity of CSI and around. The articles may be long ( words) or short ( words) authored in as the original text (plagiarism is strictly prohibited). The articles shall be peer reviewed by experts decided by the Editorial board and the selected ones shall be published. Both theoretical- and practice-based articles are welcome. The articles and contributions may be submitted in the following categories: Cover Story, Research Front, Technical Trends, and Article. CIOs/Senior IT/IS personnel/consultants of the companies managing technologies/projects related to the cover themes are welcome to contribute under the CIO (Managing Technology) section. Similarly, HR Senior Managers/Personnel/Consultants are invited to contribute under HR section. Also, Letters to the Editors, questions to be answered in Ask an Expert, your experience to share some Programming Tips under the Practitioner Workbench: Programming.Tips() are welcome. How to submit the contributions: The articles may be sent to the CSI Editorial Board via csic@csi-india.org. Article Submission guidelines: All manuscripts should be written at the level of the general audience of varied level of members. Equations and mathematical expressions within articles are not recommended, however, if absolutely necessary, should be minimum. List of references is preferred. List not more than 10 references at the end of your manuscript. Please don t include any embedded reference numbers within the text of your article. If you would to like to refer, you may state names in the text and provide full reference at the end. The reference must state the names of the authors, title, publisher s name, complete publication reference with month and year. Web URLs should be there for website references with accessed date. Figures and Images used should be limited to maximum of three (only high-resolution images need to be sent, and the image needs to be sent separately as well). Only MS-Word and PDF submissions are allowed. Include a brief biography of four to six lines for each author with author picture (high resolution). Editors will edit the contents as felt necessary. Authors of selected articles will be notified by the editorial board and copyright transfer form needs to be filled up by the authors. Only original contributions are requested and no plagiarism is allowed. Please note that months for various cover themes are tentative and may change depending on prevailing circumstances. (Issued on behalf of the Editors of CSI Communications)

3 CSI Communications Contents Volume No. 36 Issue No. 6 September 2012 Editorial Board Chief Editor Dr. R M Sonar Editors Dr. Debasish Jana Dr. Achuthsankar Nair Resident Editor Mrs. Jayshree Dhere Advisors Dr. T V Gopal Mr. H R Mohan Technical Trends Applications of Digital Image Watermarking in Industries Baisa L Gunjal and Dr. Suresh N Mali A Conspectus of Soft Data Mining in Bioinformatics Satya Ranjan Dash and Satchidananda Dehuri Medical Tourism - a Business & Technology Perspective Radha M De and Diptiman Dasgupta Practitioner Workbench Programming.Tips()» Fun with Diophantine Equations in C Wallace Jacob Programming.Learn ( Python )» CGI Python Umesh P CIO Perspective Managing Technology» Business Information Systems: Changing Roles of CIOs Dr. R M Sonar Published by Executive Secretary Mr. Suchit Gogwekar For Computer Society of India Design, Print and Dispatch by CyberMedia Services Limited Articles Social Media - Marketers New Playing Field Dr. Anil Vaidya GSM - R (Global System for Mobile Communication - Railway) Prof. (Dr.) V Purnachandra Rao The Evolution of COBIT Avinash W Kadam HR Shared Services Organization Dr. Manish Godse Security Corner Information Security» Electronic Evidence & Cyber Law Adv. Prashant Mali IT Act 2000» Prof. IT Law in Conversation with Mr. IT Executive: Issue No. 6 Mr. Subramaniam Vutha Please note: CSI Communications is published by Computer Society of India, a non-profit organization. Views and opinions expressed in the CSI Communications are those of individual authors, contributors and advertisers and they may differ from policies and official statements of CSI. These should not be construed as legal or professional advice. The CSI, the publisher, the editors and the contributors are not responsible for any decisions taken by readers on the basis of these views and opinions. Although every care is being taken to ensure genuineness of the writings in this publication, CSI Communications does not attest to the originality of the respective authors content CSI. All rights reserved. Instructors are permitted to photocopy isolated articles for non-commercial classroom use without fee. For any other copying, reprint or republication, permission must be obtained in writing from the Society. Copying for other than personal use or internal reference, or of articles or columns not owned by the Society without explicit permission of the Society or the copyright owner is strictly prohibited. PLUS IT.Yesterday(): Ferranti (ICT) SIRIUS Computer at NAL, Bangalore ( ) Dr. R Srinivasan 33 Brain Teaser Dr. Debasish Jana 35 Ask an Expert Dr. Debasish Jana 36 Happenings@ICT: ICT News Briefs in August 2012 H R Mohan 37 On the Shelf! Book Review Dr. Suneeta Sane 38 CSI Report Anirban Basu 39 CSI News 44 Published by Suchit Gogwekar for Computer Society of India at Unit No. 3, 4th Floor, Samruddhi Venture Park, MIDC, Andheri (E), Mumbai Tel. : Fax : hq@csi-india.org Printed at GP Offset Pvt. Ltd., Mumbai CSI Communications September

4 Know Your CSI Executive Committee ( /14)» President Vice-President Hon. Secretary Mr. Satish Babu Prof. S V Raghavan Mr. S Ramanathan president@csi-india.org vp@csi-india.org secretary@csi-india.org Hon. Treasurer Immd. Past President Mr. V L Mehta Mr. M D Agrawal treasurer@csi-india.org ipp@csi-india.org Nomination Committee ( ) Dr. D D Sarma Mr. Bipin V Mehta Mr. Subimal Kundu Regional Vice-Presidents Region - I Region - II Region - III Region - IV Mr. R K Vyas Prof. Dipti Prasad Mukherjee Mr. Anil Srivastava Mr. Sanjeev Kumar Delhi, Punjab, Haryana, Himachal Assam, Bihar, West Bengal, Gujarat, Madhya Pradesh, Jharkhand, Chattisgarh, Pradesh, Jammu & Kashmir, North Eastern States Rajasthan and other areas Orissa and other areas in Uttar Pradesh, Uttaranchal and and other areas in in Western India Central & South other areas in Northern India. East & North East India rvp3@csi-india.org Eastern India rvp1@csi-india.org rvp2@csi-india.org rvp4@csi-india.org Region - V Region - VI Region - VII Region - VIII Prof. D B V Sarma Mr. C G Sahasrabudhe Mr. Ramasamy S Mr. Pramit Makoday Karnataka and Andhra Pradesh Maharashtra and Goa Tamil Nadu, Pondicherry, International Members rvp5@csi-india.org rvp6@csi-india.org Andaman and Nicobar, rvp8@csi-india.org Kerala, Lakshadweep rvp7@csi-india.org Division Chairpersons, National Student Coordinator & Publication Committee Chairman Division-I : Hardware ( ) Division-II : Software ( ) Division-III : Applications ( ) National Student Coordinator Dr. C R Chakravarthy Dr. T V Gopal Dr. Debesh Das Mr. Ranga Raj Gopal div1@csi-india.org div2@csi-india.org div3@csi-india.org Division-IV : Communications Division-V : Education and Research Publication Committee ( ) ( ) Chairman Mr. Sanjay Mohapatra Chairman Division V Prof. R K Shyamsundar div4@csi-india.org To be announced div5@csi-india.org Important links on CSI website» Structure & Organisation National, Regional & State Students Coordinators Statutory Committees Collaborations Join Now - Renew Membership Member Eligibility Member Benefits Subscription Fees Forms Download BABA Scheme Publications CSI Communications* Adhyayan* R & D Projects Technical Papers Tutorials Course Curriculum Training Program (CSI Education Products) Travel support for International Conference enewsletter* Current Issue Archives Policy Guidelines Events President s Desk * Access is for CSI members only. Important Contact Details» For queries, correspondence regarding Membership, contact helpdesk@csi-india.org ExecCom Transacts News & Announcements archive CSI Divisions and their respective web links Division-Hardware Division Software Division Application Division Communications Division Education and Research List of SIGs and their respective web links SIG-Artificial Intelligence SIG-eGovernance SIG-FOSS SIG-Software Engineering SIG-DATA SIG-Distributed Systems SIG-Humane Computing SIG-Information Security SIG-Web 2.0 and SNS SIG-BVIT SIG-WNs SIG-Green IT SIG-HPC SIG-TSSR Other Links - Forums Blogs Communities* CSI Chapters Calendar of Events CSI Communications September

5 President s Message Satish Babu From : president@csi-india.org Subject : President s Desk Date : 1st September, 2012 Dear Members I compose this issue of the President's Message from Kuala Lumpur, where I'm representing CSI and SEARCC at the Global Conference on Computing Ethics (GCCE 2012), organized by the Malaysian National Computer Confederation (MNCC). As I reflect upon the relevance of Computing Ethics in India as well as around the world, I see several emerging areas, some of which I will share with you. Computing Ethics today has gone beyond its original definition, which was largely restricted to the computational role in areas such as scientific or business computing. Today, ICTs have become the most widely, diversely, and flexibly used technologies in the history of humankind. Networks whether computer, human, or social now span the world, posing a number of challenges to the established ways of communicating, learning, working, playing, or living. In many countries, including our own, the IT Industry has become not only a large employer of the best talent, but also the most prolific innovator of all time. On the flip side, issues of inappropriate use of ICTs ranging from unsafe content, cyber crime, cyber terrorism or cyber war, also threaten established structures of the economy, society, and polity. Computing Ethics have to be seen through this prism of what ICT/IT represents today. When examined this way, computing ethics covers a fairly large area of intellectual content, including the traditional ethics and morality, law, politics, and business & social use of technology. One of the most important roles of CSI's mandate as a national computer society is in inculcating ethics amongst computing professionals. An important concept in this regard is that of a voluntary Code of Ethics (CoE) for members, which CSI did have from its early days. However, the explosive growth of the IT Industry in the last two decades may perhaps necessitate taking a new look at our CoE, and if necessary, enhancing its contemporary relevance. We also need to actively disseminate the CoE to our members, especially students, so that we bring up the next generations of IT professionals with a firm ethical base from which to operate as professionals. This will have lasting strategic benefits, and would be one of the most effective ways how CSI can contribute to our nation. Another role that CSI can play at the social level is in developing and maintaining a set of guidelines for the use of computers in society. In India, there is some amount of confusion within different stakeholders particularly amongst parents and teachers on the one hand, and youth and students on the other on matters such as use of technology, online content monitoring, and child safety. CSI, as a users' organization, certainly can and should play a role developing such guidelines. At another level, there is also currently a national and international debate between different top-level stakeholders such as Governments, Content Providers, Business, and Civil Society on matters relating to content control vis-à-vis concerns such as national security and internal harmony. This is a matter that perhaps is difficult to settle for all times, and may need an ongoing negotiating mechanism at the national level. If such a mechanism is created, CSI, as a neutral, multistakeholder entity, can certainly play a role in it. In some countries, new national bodies are being proposed to play the role of the maintainer and disseminator of a national Voluntary Code of Conduct, but we have to choose our own model as appropriate. Some of the conflict that we see today in this debate on contentious areas such as censorship has an ethical dimension as well. We do have examples of ethically superior models such as Free and Open Source Software (FOSS) in the purely technological realms of software creation, distribution, and ownership. It is interesting to observe that FOSS has been developed by practitioners engineers, technologists, and programmers themselves. However, no similar models exist for the national-level governance of technology. Given that these are technologies of the 21st Century, and that the traditional systems are trying to govern them using laws of the 20th and 19th centuries, and given further that there is a trans-generational disparity between the users (mostly the youth) and the administrators (typically the older generation), some of this conflict is inevitable. It is time for the international community to consider framing of an entirely new legal framework for the governance of technology, perhaps modeled after the 1948 landmark legal instrument, the Universal Declaration of Human Rights (UDHR), which boldly proclaimed a new and unprecedented vision and philosophy for humankind. A similar bold, innovative, coherent, and forwardlooking techno-legal framework may be necessary to govern ICTs, given their unique nature. The development of such a framework must be through an inclusive process with wide consultations between all relevant stakeholders. CSI, as a Civil Society organization representing several communities such as students, academia, researchers, and users, must gear itself up to participate in these processes and help achieve this vision. With best wishes, Satish Babu President CSI Communications September

6 Editorial Rajendra M Sonar, Achuthsankar S Nair, Debasish Jana and Jayshree Dhere Editors Dear Fellow CSI Members, We welcome our readers to this September 2012 issue. In this issue we were supposed to cover a theme called Multimedia Mining. However, we did not receive enough contributions on the suggested topic and so decided to go for a general topic of IT applications to give justice to the type of articles received by contributors. We are also skipping some of the sections like research front. The technical trend section has three articles: first one by Prof. Gunjal and Dr. Suresh N Mali on Applications of Digital Image Watermarking in Industries. The article focuses on applications in IP protection, health care, Criminal photograph authentication and transmission, Secured e-voting systems required for elections, Remote Education and Insurance. Many firms are increasingly looking towards social media as one of the channels to reach to large number of customers. The second article is on Soft Data Mining in Bioinformatics by Satya Ranjan Dash and Satchidananda Dehuri of School of Computer Application, KIIT University, Bhubaneswar; while third article under technology management series is by Radha M Dey and Diptiman Dasgupta of IBM, wherein they discuss Medical Tourism: its lifecycle, Business Opportunities and Ecosystem, Role of Information Technology and also cover information about Electronic Medical Records. Many firms are increasingly looking towards social media as one of the channels to reach to large number of customers. Dr. Anil Vaidya, who has been a regular contributor to CSI-C covers this subject and discusses how social Media has become New Playing Field for marketing people. Prof. (Dr.) V Purnachandra Rao of Institute of Signal Engineering & Telecommunications (IRISET), Secunderabad writes about what is GSM-R: Global System for Mobile Communication- Railway and illustrates its architecture. Avinash W Kadam, Advisor, ISACA s India Task Force has contributed an article about The Evolution of COBIT (Control Objectives for Information and Related Technologies) Framework, which is helping organizations worldwide to implement IT Governance. He talks about various versions of COBIT and COBIT 5 in more details and will be contributing more articles in future on this subject. The Evolution of COBIT (Control Objectives for Information and Related Technologies) Framework, which is helping organizations worldwide to implement IT Governance. Prof. Wallace Jacob has been contributing in Practitioner Workbench column under section Programming.Tips(), and in this issue his contribution is about fun with Diophantine Equations in C. Diophantine Equation is indeterminate polynomial equation that allows the variables to be integers only. The other section called Programming. Learn("Python") under Practitioner Workbench covers guidelines on CGI (common gateway interface) using Python. In his series of articles on business information systems, Dr. R M Sonar this time focuses on how roles, functions and responsibilities of CIOs are changing with evolution in technology. In the Information Security section of the Security Corner column, Adv. Prashant Mali writes about Electronic Evidence & Cyber Law. Another section called IT Act 2000 under Security Corner is enriched with a writeup byadv. Subramaniam Vutha, where he focuses on electronic signatures and explains how they are used in e-commerce to authenticate the parties involved through a Q&A style. Dr. Manish Godse, in HR column introduces the readers to shared services: how they are implemented, driving factors, role of ICT and outsourcing of such services. As suggested by Dr DVR Vithal, we have started a new column called IT.Yesterday() in this issue... You all are welcome to contribute your experiences of yesteryears of computing and of CSI for this column. As suggested by Dr DVR Vithal, we have started a new column called IT.Yesterday() in this issue. This time Dr. R Srinivasan takes the readers to 1960s by explaining elements, features, working and architecture of Ferranti (ICT) SIRIUS Computer at National Aerospace Laboratories. You all are welcome to contribute your experiences of yesteryears of computing and of CSI for this column. As usual there are other regular features such as Brain Teaser, Ask an Expert, On the Shelf and Happenings@ICT. CSI Reports and CSI News section provide event details of various regions, SIGs, chapters and student branches. There are many different announcements of various types of CSI awards. We have also compiled some of the feedback received from distinguished readers for your information under ReaderSpeak() on backside of front cover. Please note that we welcome your feedback, contributions and suggestions at csic@csi-india.org. With warm regards, Rajendra M Sonar, Achuthsankar S Nair, Debasish Jana and Jayshree Dhere Editors CSI Communications September

7 Technical Trends Digital watermarking has been a popular topic for both researches and applications in the last decade. With rapid development in multimedia technology and vast Internet use, it has become a common practice to create copy, transmit, and distribute digital data. Obviously, it leads to unauthorized replication problem. The digital watermarking system is an effective technique for protecting the copyright of the digital production and the data safety maintenance. Fig. 1 shows generalized concept of image watermarking. Image watermarking can assure the integrality and the reliability of the digital information by examining and analyzing the watermarking [4]. Consequently, it becomes an available method for intellectual property protection and digital multimedia anticounterfeiting techniques. This article focuses on fundamentals of digital image watermarking and its applications in industry. Fig. 1: Generalized concept of image watermarking Image Watermarking Classification As shown in Fig. 2, Watermarking algorithms can be classified on several criteria [1,7]. According to Embedding Domain: i) Spatial domain, ii) Frequency/transform domain, and iii) Temporal domain According to Extractor: i) Blind and ii) Nonblind According to Human Perception: i) Visible and ii) Nonvisible - a) Robust and b) Fragile According to Application: i) Source-based and ii) Application-based Fig. 2: General classification of watermarking In spatial domain, watermark is embedded by directly modifying pixel values of cover Baisa L Gunjal* and Dr. Suresh N Mali** * Assistant professor, Amrutvahini College of Engineering Sangamner, A nagar, MS ** Principal, Singhgad Institute of Technology and Science, Narhe, Pune, India Applications of Digital Image Watermarking in Industries image as shown in Fig. 2. Least Significant Bit (LSB) insertion is example of spatial domain watermarking. These algorithms are simple in implementation [8,13]. But problems with such algorithms are: low watermark information hiding capacity, less security; hence anybody can detect such algorithms. Original Image Watermarked_Image Watermark Extracted_Watermark Fig. 3: Spatial domain watermarking In frequency domain, the watermark is inserted into transformed coefficients of image giving more informationhiding capacity and more robustness against watermarking attacks because information can be spread out to entire image [1]. Watermarking using Discrete Wavelet Transform, Discrete Cosine Transform, and CDMA-based Spread Spectrum Watermarking are examples of Transform Domain Watermarking. Any digital image watermarking method has two main counterparts: embedding algorithm and extraction algorithm [5]. Embedding algorithm is step-by-step process of inserting watermark logo into original cover image to form watermarked image. Extraction algorithm is just reverse process to extract embedded watermark from watermarked image. Cover Image Watermark N Level DWT/2D DCT N Level DWT/2D DCT E M B E D D I N G Inverse DWT (IDWT)/Inverse 2D DCT Watermarked Image Fig. 4: Transform domain image watermark embedding Fig. 4 shows sample schematic embedding algorithm in transform domain. Here, frequency domain like Discrete Wavelet Transform (DWT) or Discrete Cosine Transform (DCT) etc. are used as embedding domain [2,12]. In the following section various applications of digital image watermarking in industry are discussed. Image Watermarking Applications Media Requirements There are requirements for watermarking system for different media types [10]. a) Image watermarking; b) Document watermarking; c) Graphics watermarking; d) Audio watermarking; and e) Video watermarking. In the following section example applications where digital image watermarking well fits to provide security protection. Image copyright communication for right management and protection Providing copyright to digital images by hiding rightful information is main aim of digital image watermarking. Microsoft is one of the many content owners to embed digital watermarks in images as a means to communicate and protect image copyrights [10]. This ensures that image users or licensees are acting in compliance with guidelines and allows legal departments to effectively communicate and enforce image copyrights. Image watermarking applications in health care Telemedicine combines Medical Information System with Information Technology that includes use of computers to receive, store, and distribute medical information over long distances. Telemedicine can be divided into number of medical-related technologies using computers for health care like teleradiology, telepathy, telecare, telesurgery, teleneurology etc. [8] In number of medical applications, medical images require special safety and confidentiality, because critical judgment is done on the information provided by medical images. Critically ill or injured patients can be treated locally by effective and secured communication between CSI Communications September

8 remote hospitals and distant specialists. Exchange of medical images between hospitals located in different geographical locations is a common practice nowadays as shown in Fig. 5. Hence, healthcare industry demands secure, robust, and more information-hiding techniques promising strict secured authentication and communication through Internet or mobile phones. Conventional watermarking systems embed the hidden information in the entire image. This is not acceptable for sensitive imagery like medical images. PHYSICIAN Diagnosis Based Image Hospital Logo or Patients Record Medical Image Through Internet Mobile Phones Fig. 5: Need for security in telemedicine A medical image contains Region of Interest (ROI) and Non Region of Interest (RONI). ROI is sensitive region of medical image using which doctors do exact diagnosis and decide treatment accordingly [8]. Fig. 6: Selecting ROI for image under diagnosis: selecting ROI directly and selecting using tool Use of classical watermarking techniques may create the distortion in ROI and consequently the diagnosis value of image may be lost. Hence, only RONI should be used for watermark embedding. The ROI of image can be selected interactively from medical image. Excluding such selected region, the watermark is embedded. Fig. 6 shows separation of ROI in Matlab from given image under diagnosis. The physician can use different options to select ROI interactively. Fig. 7 shows some of the options including: rectangular, ellipse-shaped, polygon with n number of vertices, or selection with free hand. Thus, ROI and RONI of image needs to be separated before watermark embedding. The watermark is embedded with pixels of RONI and watermarked image is constructed. Fig. 7: Selecting ROI for medical image Criminal photograph authentication and transmission Most of the crime investigations are based on database submitted to crime branches from remote locations via Internet or mobile phones. When some unwanted crime happens, the criminal(s) photograph is constructed according to preliminary information collected from eyewitnesses where actual incident happens. This sensitive criminal image data needs to be transmitted across network through the Internet or mobile phone. Transmission of such image data demands high and guaranteed security. Secured e-voting systems required for elections With rapid growth of computer network, Internet has reached to common villagers of country and worldwide as well. Due to widespread use of the Internet with information and communication technologies in order to get their inevitable benefits like accuracy, speed, cost saving etc. more secure transactions such as shopping, banking, submitting tax returns are done online. Obviously, electronic voting is a possible alternative for conducting elections by maintaining security in election process [6,9]. Several institutions and companies have proposed Internet as a medium for remote electronic voting, either as an alternative or replacement for traditional poll and paper ballot systems [9]. Though recently electronic voting machines (EVMs) has replaced traditional ballot papers and boxes of conventional voting system, fraud voting and other illegal practices on polling booth like violence, voting by poll workers for absent voters etc. are challenges for election commissions of a given country. The electronic election allows voters to vote over the Internet without geographical restrictions. The mobility, democracy, and privacy are important criteria in evaluating electronic voting schemes [12]. The system should be capable of handling electronic ballots with multiple scopes at the same time, e.g. presidential, municipal, parliamentary, amongst others [4]. It has been always a challenging task for the election commission to conduct free and fair polls in any country. Crores of rupees or dollars are spent by democratic countries for the secure and smooth conduct of the election process. Current research focuses on designing and building voting protocols that can support the voting process, while implementing the security mechanisms required for preventing fraud and protecting voters privacy [2]. Digital copyright protection system based on mobile agent Mobile agent technology and digital watermark technology compensate each other and play a very important role in the industrial applications. The integration of the mobile agent technology and watermark technology has been intensively investigated in recent years. The detail architecture can be found in Quan and Hong (2008) [11]. Remote education Distance education is gaining popularity in rural areas of developing countries due to the shortage of teachers. In order to support a variety of curriculum for different states in a diverse country like India along with various languages, there is a need for intelligent technologies to create a CSI Communications September

9 deployable remote education solution. The main challenge in the distance education solution is the dissemination of content and teacher-student interaction [3]. The secured transmission of image data is part of distant learning. Image watermarking is solution for providing security in this regard. Health and car insurance companies Health and car insurance companies nowadays use image processing [3]. Health insurance companies usually store the scanned copies of the medical images of their clients. The database may require processing and transmitting to central administrative offices. The car companies image databases are referred for insurance-related decision making in case of damage to vehicles during accidents. The digital image watermarking protection is provided to such image database. Conclusion Thus, digital image watermarking has many applications in industry ranging from copyright protection, telemedicine, criminal photograph authentication, worldwide voting systems, copyright protection system based on mobile agent, remote education, and health and car insurance. In summary, digital image watermarking can be used in any area where there is need to protect image data. Acknowledgments This work is funded by the Board of Colleges and University Development (BCUD), University of Pune with File Ref. No.-BCUD /OSD/390, dated 25/10/2010. We are thankful to BCUD, Pune for providing this research grant. We are also thankful to Amrutvahini College of Engineering, Sangamner, A nagar and Singhgad Institute of Technology and Science, Narhe, Pune for technical support during this work. References [1] Abu-Errub, A, and Al-Haj, A, (2008). Optimi-zed DWT-based image watermarking. First International Conference on Applications of Digital Information and Web Technologies, IEEE, 4-6. [2] Burrus, C S, et al. (1998). Introduction to Wavelets and Wavelet Transformation, Prentice Hall, ISBN: [3] Chattopadhyay, T, et al. (2012). Applications of Image Processing in Industries. Computer Society of India Communications (CSIC), 36(4), [4] Chun-Ta Li, et al. (2009). A Verifiable Electronic Voting Scheme over the Internet. Sixth IEEE International Conference on Information Technology: New Generations, ITNG '09, [5] Kasmani, S A and Naghsh-Nilchi, A (2008). "A New Robust Digital Image Watermarking Technique Based On Joint DWT-DCT Transformation. Convergence and Hybrid Information Technology, 2008, 2, [6] Khasawneh, M, et al. (2008). A biometric-secure e-voting system for election processes. 5th IEEE International Symposium on Mechatronics and Its Applications, ISMA, 1-8. [7] Kougianos, E, et al. (2008). Hardware Assisted Watermarking for Multimedia. Elsevier Journal on Computer and Electrical, 35(7), [8] Kundu, M K and Das, S (2010). Lossless ROI Medical Image Watermarking Technique with Enhanced Security and High Payload Embedding. International conference on Pattern Recognition, [9] Menon, T, et al. (2009). ID Based Signature Schemes for Electronic Voting. Second IEEE International Conference on Computer and Electrical Engineering, ICCEE '09, [10] Podilchuk, C I and Delp, E J (2001). Digital Watermarking algorithms and applications. IEEE Signal Processing Magazine, [11] Quan, L and Hong, L (2008). A new architecture for digital copyright protection system based on mobile agent. 3rd IEEE Conference Industrial Electronics and Applications, [12] Soman, K P and Ramchandran, K I (2008). Insight into Wavelets: From Theory to Practice, 2nd Edition, Prentice Hall of India. [13] Sun, G and Yu, Y (2007). DWT Based Watermarking Algorithm of Color Images. Second IEEE Conference on Industrial Electronics and Application, n About the Authors Baisa L Gunjal has completed M.Tech in I.T. and presently working as assistant Professor in Amrutvahini College of Engineering Sangamner, A nagar, MS. She has 14 years teaching experience and she is coordinator of seven postgraduate courses running in her college. She is also working on research project funded by BCUD, University of Pune and having more than 15 International publications including IEEE Explorer, IET-UK libraries etc. She is also CSI Student branch coordinator at AVCOE Sangamner and CSI Member. Dr. Suresh N Mali is Principal, Singhgad Institute of Technology and Science, Narhe, Pune, India. He has written 3 technical books and published 25 papers in various national and international journals and various conferences. He is Member of expert Committee of AICTE, New Delhi to visit at various newly opened institutes of western region on behalf of AICTE, BOS member for Computer Engineering at University of Pune, MS, India and worked as Member of Local Inquiry Committee on behalf of University of Pune. His research interests are information security, data hiding, signal processing, digital multimedia communications and Steganography. CSI Communications September

10 Technical Trends Satya Ranjan Dash* and Satchidananda Dehuri** * School of Computer Application, KIIT University, Patia, Bhubaneswar sdashmca@kiit.ac.in ** Department of Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore , Odisha. satchi.lapa@gmail.com A Conspectus of Soft Data Mining in Bioinformatics Abstract: This article discusses a conspectus of soft data mining and its challenges in bioinformatics. In addition, we are redefining the boundary of soft computing (boundary means components exclusively contributing to soft computing for handling a wider domain of problems) and in the sequel redefining the term soft data mining. Keywords: Soft set, Soft Computing, Data Mining, Bioinformatics Introduction Last few decades witnessed the individual and combined efforts of data mining and soft computing in the realm of bioinformatics [10]. Data mining [5] can be regarded as an algorithmic process that takes sample as an input and yield patterns such as classification rules, association rules, or clustering as an output. The different soft computing methodologies are highlighted along with a newly introduced paradigm such as soft set theory [11]. The definition of soft computing is redefined by including the paradigm of soft set theory. Individually or in integrated mode, soft computing tools are turning out to be an efficient and robust candidate for performing data mining tasks. Soft data mining used in bioinformatics related tasks like protein structure prediction and analysis of DNA, gene sequence analysis, gene mapping, ribonucleic acid and protein, molecular docking with ligand design etc. are highlighted along with their basic features. The basic material of this article is divided into three subsections. The first subsection discusses the idea of soft computing. The underlying idea of data mining and bioinformatics are discussed in the following subsections, respectively. Soft computing Soft computing [19] is a consortium of methodologies (e.g. fuzzy logic, neural networks, and evolutionary algorithms) that works together and provides, in one form or another, flexible information processing capabilities for handling real-life problems. With an aim to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth, soft computing achieves tractability, robustness, low-cost solution, and close similitude with humanlike decision-making. Normally, fuzzy set theory is appropriate for handling the issues related to understandability of patterns in an incomplete/noisy data. Artificial neural networks are nonparametric, adaptive by learning, robust, and exhibit good generalization capabilities in data-rich environments. The exploitation and exploration capabilities of evolutionary algorithms attract researchers to use them for potentially huge search spaces and navigating them, looking for optimal combinations of things. Let us discuss two more paradigms which are enforcing us to redefine the boundary of soft computing. Rough set theory was developed by Zdzislaw Pawlak [15] and used for classificatory analysis of data tables. An important use of rough set theory in data mining has been in generating rules for classification. These rules maps to different important regions of the feature space which ultimately represent clusters [6]. In last decade, rough set theory has been considered as a component of soft computing which in various synergistic combinations with fuzzy system, neural networks, and evolutionary algorithms, provides a robust framework to achieve tractability, robustness, lowcost solution, and closely resembles with human-like decision making [14]. For Rough set Soft set Soft Computing Fig. 1: Soft computing and its basic constituents example, synergistic integration of neural network and rough set helps in extracting rudimentary domain knowledge in the form of rules for describing different concepts/classes, and then encoding them as parameter of neural network; thereby constituting the initial knowledgebase network for efficient learning. Fig. 1 illustrates the constituents of soft computing developed over the years. Soft set theory [11] introduced by Molodtsov in 1999, is a new method for dealing with uncertain data. The advantage of soft set theory is that it is free from the inadequacy of the parameterization tools, unlike in the theories of fuzzy set [19], probability, and interval mathematics [18]. A general mathematical tool - soft set theory offer solutions for dealing with uncertain, fuzzy, not clearly defined objects [8]. In soft set theory, membership is decided by adequate parameters, rough set theory employs equivalence classes, whereas fuzzy set theory depends upon grade of membership. Although three theories are quite distinct yet deal with vagueness. Joint application of these theories may result in a fruitful way [2,7]. With this discussion, we argue that soft set theory may be treated as another constituent of soft computing. Fig. 1 demonstrates its stand in soft computing paradigm. Fuzzy theory Neural network Evolutionary algorithm Redefined by S K Pal et al. Redefined by Dehuri et al. CSI Communications September

11 Data mining Data mining [5] involves the use of semiautomatic data analysis tool by harnessing the best attribute of soft computing methodologies to discover novel, valid, and interesting patterns, along with a relationship in large data sets. Data mining is an iterative process within which progress is defined by discovery, through either automatic, semiautomatic, or manual methods. Data mining is useful in an explanatory analysis scenario in which there are no predetermined notions about what will constitute an interesting outcome. Data mining is the search for novel, useful, and nontrivial information in large gamut of data. Prediction and description are considered as two primary goals of data mining. Predictive data mining, which produces the model of the system described by the given data set and descriptive data mining, which produces new, nontrivial information based on the available data set. The goal of prediction and description are achieved through data mining tasks: 1. Classification: discovery of a predictive learning function that classifies a data item into one of several predefined classes. 2. Discovering association rules: it aims to extract interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories and describes association relationship among different attributes. 3. Clustering: a common descriptive task in which one seeks to identify a finite set of categories or clusters. Data mining has its origin in various disciplines, like statistics, soft computing [10], multiobjective optimization [3], database management system, pattern recognition [13], machine learning [9] etc. Statistics has its roots in mathematics, and therefore that something is sensible on theoretical grounds before testing it in practice. Data mining from pattern recognition point of view along with a relevance of soft computing is a topic of interest in many researchers in last two decades. In data mining the aforesaid tasks like classification, association rule mining, and clustering may be treated as multiobjective problems rather than a uniobjective, therefore a new paradigm was started by Ghosh et al. [3] i.e., multiobjective optimization for knowledge discovery. Machine learning has willingness to test something out to see how it performs [16]. Bioinformatics Bioinformatics [1] is the science of storing, extracting, organizing, analyzing, and interpreting biological data. Its importance has increased with the technology of Deoxyribonucleic acid (DNA) sequencing, microarrays, as well as the widespread understanding that genes and proteins interactions. This in turn renders high performance data analysis algorithms central to various bioinformatic tasks. There are a lot of patterns in biology which are not understood and data mining helps to discover novel and hopefully useful information. Data mining is used in the prediction of gene relations in a genome, gene expression analysis, protein-ligand docking, and the prediction of protein folding resulting from changes in the DNA [10]. The diverse range of rapidly expanding databases produced by modern molecular biology has ignited a need for more accurate classification and prediction algorithms. The accuracy of classification algorithms can be affected by a large variety of factors, some of which may be considered to be generic to any data mining algorithm and applicable to research in other application domains. Data Mining in Bioinformatics Molecular biology laboratories have gathered a very huge amount of data in sequence and functional genome projects [1]. It is a difficult task to analyze these data manually. Therefore, sophisticated semiautomatic computing techniques are necessary to extract new, meaningful, and useful information from these data. Past few years, data mining techniques have been successfully applied in such analysis. A few examples of these applications are analysis of gene expression data, recognition of genes in DNA sequences, and protein structure prediction. Usually, biological data needs to be preprocessed before they can be used in a data mining algorithm. There are a lot of patterns in biology which are not understood and data mining helps to discover novel and hopefully useful information. Data mining is used in the prediction of gene relations in a genome, understanding of relations for region activation in the brain, and the prediction of protein folding resulting from changes in the DNA. Sequence analysis is a major area in bioinformatics encompassing the techniques for studying the biological sequences, DNA, RNA, and proteins, on the linear structure level. The focus of this area is generally on the identification of intramolecular similarities, which boils down to detecting repeated segments within a given sequence, while identifying intermolecular similarities amounts to spotting common segments among two or multiple sequences. From a data mining point of view, sequence analysis is nothing but string- or pattern-mining specific to biological strings. Gene sequences isolated from diseased and healthy tissues can be compared to identify critical differences between the two classes of genes. Such features can be used for classifying biodata and predicting behaviors. A lot of methods developed for biodata classification [10]. One of the most important search problems in biodata analysis is similarity search and comparison among biosequences and structures. For example, gene sequences isolated from diseased and healthy tissues can be compared to identify critical differences between the two classes of genes. This can be done by first retrieving the gene sequences from the two tissue classes, and then finding and comparing the frequently occurring patterns of each class. Since biodata usually contains noise or nonperfect matches, it is important to develop effective sequential or structural pattern-mining algorithms in the noisy environment, such as that recently reported in Pal (2004) [14]. The amino acid sequence of a protein (primary structure) can be easily determined from the sequence on the gene that codes for it. In most of the cases, this primary structure uniquely determines a structure in its native environment. Knowledge of this structure is vital in understanding the function of the protein. For lack of better terms, structural information is usually classified as secondary, tertiary, and quaternary. CSI Communications September

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