Journal of computer technology & applications (vol5, issue3) by STM Journals Publication

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Dr. Gunamani Jena ME CSE, PhD, FIE, MIEEE, LMISTE, MCSI, India.

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I take the privilege to present the hard copy compilation for the [Volume 5 Issue (3)] Journal of Computer Technology & Applications (JoCTA). The intension of JoCTA is to create an atmosphere that stimulates creativeness, research and growth in the area of Computer Technology & Applications. The development and growth of the mankind is the consequence of brilliant Research done by eminent Scientists and Engineers in every field. JoCTA provides an outlet for Research findings and reviews in areas of Computer Technology & Applications found to be relevant for National and International recent developments & research initiative. The aim and scope of the Journal is to provide an academic medium and an important reference for the advancement and dissemination of Research results that support high level learning, teaching and research in the domain of Computer Science and Technology. Finally, I express my sincere gratitude and thanks to our Editorial/ Reviewer board and Authors for their continued support and invaluable contributions and suggestions in the form of authoring writeups/ reviewing and providing constructive comments for the advancement of the journals. With regards to their due continuous support and co-operation, we have been able to publish quality Research/Review findings for our customers base. I hope you will enjoy reading this issue and we welcome your feedback on any aspect of the Journal.

Dr. Archana Mehrotra Director STM Journals

Journal of Computer Technology & Applications

Contents

1. Clustering the Data in Search Engines Hamid Behrangi, Hossein Ahmadi

2. Periodic Turing Machines Mark Burgin

3. Customization of GIS Tools through Web-based Open Source GRASS Interface Suman Sinha, Laxmi Kant Sharma, Saurabh Sharma

4. A Practical Iterative Side Channel Cube Attack on AES-128/256 Erfan Aghaee, Shahram Jamali, Majid Rahimi, Hamed Yusefi

5. An Exploration on Data Mining for Face Detection based on Real-time Face Tracking V. Murugananthan, B.L. Shivakumar

Journal of Computer Technology & Applications ISSN: 2229-6964 (online), ISSN: 2347-7229 (print) Volume 5, Issue 3 www.stmjournals.com

Clustering the Data in Search Engines Hamid Behrangi 1*, Hossein Ahmadi 2 1

Young Researches Club, Zanjan Branch, Islamic Azad University, Zanjan, Iran Young Researches Club, Tehran Branch, Islamic Azad University, Tehran, Iran

Abstract Contents of the internet is rapidly growing day by day. To reach the information we search on the internet, we're using internet search engines, which can return millions of search results depends on the query. Finding the information needed on the search results can be a massive problem. Search result clustering is a useful operation to solve this problem. In this paper, results taken from search engines divided into a number of clusters, thus users quickly are able to find their favorite results. In the read more, Naming the clusters and how the clusters are split results in other subjects are discussed.

Keywords: Information retrieval, Clustering Strategies, Web Mining

Journal of Computer Technology & Applications ISSN: 2229-6964 (online), ISSN: 2347-7229 (print) Volume 5, Issue 3 www.stmjournals.com

Periodic Turing Machines Mark Burgin* University of California, Los Angeles, 405 Hilgard Ave., Los Angeles, CA, USA Abstract It is proved that in comparison with Turing machines, inductive Turing machines represent the next step in the development of computer science providing better models for contemporary computers and computer networks. In particular, it is proved that simple inductive Turing machines can solve the Halting Problem for Turing machines, while inductive Turing machines of higher orders can generate and decide the whole arithmetical hierarchy. It means that inductive Turing machines are super-recursive algorithms, which model and perform unconventional computations. Inductive Turing machines are a particular case of periodic Turing machines. Thus, periodic Turing machines are super-recursive algorithms, which are more powerful than Turing machines. At the same time, periodic Turing machines reflect pivotal traits of periodic computational processes. In this paper, we study relations between periodic and inductive Turing machines.

Keywords: Computation, stability, turing machine, inductive Turing machine, periodic turing machine

Journal of Computer Technology & Applications ISSN: 2229-6964 (online), ISSN: 2347-7229 (print) Volume 5, Issue 3 www.stmjournals.com

Customization of GIS Tools through Web-based Open Source GRASS Interface Suman Sinha1*, Laxmi Kant Sharma2, Saurabh Sharma3 1

Department of Remote Sensing, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India 2 Centre for Land Resource Management, Central University of Jharkhand, Jharkhand, India 3 TATA Consultancy Services, Gurgaon, Haryana, India

Abstract The expertise on certain details relating to certain locations could only be provided through the expenditure of valuable time, money and effort with the expert having to survey the land manually or obtain the information about the place through complicated procedure. A simple decision support system where the expert selects any combination of unions of maps provided from a remote location and provides his suggestion based on the data retrieved from the unioned map. The user then locally accesses the system and selects the appropriate unioned map. The combined map is displayed in a window and using a cursor, he selects the location of interest. Thus, our application helps in the simplification of procedures and an economical way of obtaining expert advice on problems being faced by the common man without the need for either the expert or the customer to know the complex inner operations of the system.

Keywords: GIS, GRASS, SQL, PHP, mapserver, apache webserver

Journal of Computer Technology & Applications ISSN: 2229-6964 (online), ISSN: 2347-7229 (print) Volume 5, Issue 3 www.stmjournals.com

A Practical Iterative Side Channel Cube Attack on AES-128/256 Erfan Aghaee*, Shahram Jamali, Majid Rahimi, Hamed Yusefi University of Mohaghegh Ardabili, Ardabil, Iran

Abstract The Side Channel Cube Attack (SCCA) is a kind of Algebraic Side Channel Attack (ASCA) consisting of theoretical and practical aspects. This paper presents a general framework for the SCCA (called an Iterative SCCA (ISCCA)) on block ciphers in which theoretical and practical aspects are explained and the requirements are listed. On the theoretical side, we use extraction of quadratic equations, recognition of iterated chosen plaintexts, and cube iteration to improve the SCCA on block ciphers. On the experimental side, we define a feasible scenario in which the ISCCA can be applied on block ciphers. Then, we implement the ISCCA on AES and verify the results on an ARM microcontroller. Finally, we compare the proposed SCCA (ISCCA) with the Simple Power Analysis, the previous SCCAs, and the previous attacks on AES. This comparison is based on template building and data, time, and memory complexity. We show that the SCCA can recover 128 and 256 key bits of the AES-128/256 only with data complexity 27.3, time complexity 215.74 and memory complexity 27.89 on AES-128, and data complexity 27.75, time complexity 216.2 and memory complexity 28.21 on AES-256. We show that only nine interesting points are needed for template matching phase. This is the most efficient SCCA on AES-128/256.

Keywords: Side channel, cube attack, AES-128/256, Hamming weight, 路ARM microcontroller

Journal of Computer Technology & Applications ISSN: 2229-6964 (online), ISSN: 2347-7229 (print) Volume 5, Issue 3 www.stmjournals.com

An Exploration on Data Mining for Face Detection based on Real-time Face Tracking V. Murugananthan1*, B.L. Shivakumar2 1

Research Scholar, Research and Development Centre , Bharathiar University, Coimbatore, Tamilnadu, India 2 Director, Department of Computer Applications, Sri Ramakrishna Engineering College, Coimbatore, Tamilnadu, India

Abstract Data mining has been extensively used to gather meaningful information and to improve the significant relationship for the variables warehoused in large data stores. Machine learning provides the technical basis of data mining. Automatic face recognition research which try to give the computer ability to recognize face to distinguish characters. As a key technology of biometrics face recognition technologies, in public security, information security, financial, and other fields has potential application prospect. This paper studies a system of face detection and recognition system based on real-time video. In the face detection part, proposed the Adaboost-ASM face detection algorithm, this algorithm is Adaboost face detection algorithm combined with the Active Shape Model, mainly to solve the problem of the Adaboost face detection algorithm is easy to false drop face in complex region and a similar face region, implement face real-time detection and eliminate non-face region. In the part of face recognition, this paper using 2D-Gabor wavelet feature extraction, and analyzes the advantage and disadvantages of PCA method and Fisher linear discriminant method, and decide using Fisherface method combined with the PCA and Fisher linear discriminant analysis method to reduce the face feature, and then do the projection of the best classification for facial feature. In the end, calculate the projection value of face and projection value of the training sample by cosine distance formula, identifying face. The aim of this research is to implement a face recognition system that will be incorporated to build a system with enhanced properties of the detection algorithm and comparison algorithm for real-time tracking with the basis of logical analysis of data.

Keywords: Data mining, Adaboost, ASM face detection, Gabor feature extraction, PCA, Fisherface, face recognition, Camshift