Academy & Industry Research Collaboration Center (AIRCC)


  • 1. Efficiency of Decision Trees in Predicting Students Academic Performance

    S. Anupama Kumar and Vijayalakshmi M.N , R.V.College of Engineering, India
    July 2011 | Cited by 39

    Educational data mining is used to study the data available in the educational field and bring out the hidden knowledge from it. Classification methods like decision trees, rule mining, Bayesian network etc can be applied on the educational data for predicting the students behavior, performance in examination etc. This prediction will help the tutors to identify the weak students and help them to score better marks. The C4.5 decision tree algorithm is applied on student's internal assessment data to predict their performance in the final exam. The outcome of the decision tree predicted the number of students who are likely to fail or pass. The result is given to the tutor and steps were taken to improve the performance of the students who were predicted to fail. After the declaration of the results in the final examination the marks obtained by the students are fed into the system and the results were analyzed. The comparative analysis of the results states that the prediction has helped the weaker students to improve and brought out betterment in the result. To analyse the accuracy of the algorithm, it is compared with ID3 algorithm and found to be more efficient in terms of the accurately predicting the outcome of the student and time taken to derive the tree.
  • 2. Knowledge Based Analysis of Various Statistical Tools in Detecting Breast Cancer

    S. Aruna, S.P. Rajagopalan and L.V. Nandakishore, Dr M.G.R University, India
    July 2011 | Cited by 25

    In this paper, we study the performance criterion of machine learning tools in classifying breast cancer. We compare the data mining tools such as Naive Bayes, Support vector machines, Radial basis neural networks, Decision trees J48 and simple CART. We used both binary and multi class data sets namely WBC, WDBC and Breast tissue from UCI machine learning depositary. The experiments are conducted in WEKA. The aim of this research is to find out the best classifier with respect to accuracy, precision, sensitivity and specificity in detecting breast cancer.
  • 3. Chaos Image Encryption using Pixel shuffling

    Manjunath Prasad and K.L.Sudha, Dayananda Sagar College of Engineering, India
    July 2011 | Cited by 22

    The advent of wireless communications, both inside and outside the home-office environment has led to an increased demand for effective encryption systems. The beauty of encryption technology comes out in more pronounced way when there is no absolute relation between cipher and original data and it is possible to rebuild the original image in much easier way. As chaotic systems are known to be more random and non-predictable, they can be made utilized in achieving the encryption. The transposition technology of encryption systems requires scrambleness behaviour in order to achieve the encryption of the data. This scrambleness behaviour can be derived from the randomness property of chaos which can be better utilized in the techniques like transposition system. In wireless communication systems, bandwidth utilization is an important criterion. In order to use encryption system in wireless communication; key space plays an important role for the efficient utilization of the bandwidth. In this paper we present a chaosbased encryption algorithm for images. This algorithm is based on pixel scrambling where in the randomness of the chaos is made utilized to scramble the position of the data. The position of the data is scrambled in the order of randomness of the elements obtained from the chaotic map and again rearranged back to their original position in decryption process. The same algoritm is tested with two different maps and performance analysis is done to select best suited map for encription.
  • 4. Backpropagation Learning Algorithm Based on Levenberg Marquardt Algorithm

    S.Sapna1, A.Tamilarasi2 and M.Pravin Kumar1
    1K.S.R College of Engineering, India and 2Kongu Engineering College, India
    Oct 2012 | Cited by 20

    Data Mining aims at discovering knowledge out of data and presenting it in a form that is easily compressible to humans. Data Mining represents a process developed to examine large amounts of data routinely collected. The term also refers to a collection of tools used to perform the process. One of the useful applications in the field of medicine is the incurable chronic disease diabetes. Data Mining algorithm is used for testing the accuracy in predicting diabetic status. Fuzzy Systems are been used for solving a wide range of problems in different application domain and Genetic Algorithm for designing. Fuzzy systems allows in introducing the learning and adaptation capabilities. Neural Networks are efficiently used for learning membership functions. Diabetes occurs throughout the world, but Type 2 is more common in the most developed countries. The greater increase in prevalence is however expected in Asia and Africa where most patients will likely be found by 2030. This paper is proposed on the Levenberg - mMarquardt algorithm which is specifically designed to minimize sum-of-square error functions. Levernberg-Marquardt algorithm gives the best performance in the prediction of diabetes compared to any other backpropogation algorithm.
  • 5. Comparative Study of Hand Gesture Recognition System

    Rafiqul Zaman Khan and Noor Adnan Ibraheem, Aligarh Muslim University, India
    July 2012 | Cited by 16

    Human imitation for his surrounding environment makes him interfere in every details of this great environment, hear impaired people are gesturing with each other for delivering a specific message, this method of communication also attracts human imitation attention to cast it on human-computer interaction. The faculty of vision based gesture recognition to be a natural, powerful, and friendly tool for supporting efficient interaction between human and machine. In this paper a review of recent hand gesture recognition systems is presented with description of hand gestures modelling, analysis and recognition. A comparative study included in this paper with focusing on different segmentation, features extraction and recognition tools, research advantages and drawbacks are provided as well.
  • 6. SVD Based Robust Digital Watermarking For Still Images Using Wavelet Transform

    S.Ramakrishnan, T.Gopalakrishnan, K.Balasamy, Dr.Mahalingam College of Engineering and Technology, India
    July 2011 | Cited by 15

    This paper aims at developing a hybrid image watermarking algorithm which satisfies both imperceptibility and robustness requirements. In order to achieve our objectives we have used singular values of Wavelet Transformation's HL and LH sub bands to embed watermark. Further to increase and control the strength of the watermark, we use a scale factor. An optimal watermark embedding method is developed to achieve minimum watermarking distortion. A secret embedding key is designed to securely embed the fragile watermarks so that the new method is robust to counterfeiting, even when the malicious attackers are fully aware of the watermark embedding algorithm. Experimental results are provided in terms of Peak signal to noise ratio (PSNR), Normalized cross correlation (NCC) and gain factor to demonstrate the effectiveness of the proposed algorithm. Image operations such as JPEG compression from malicious image attacks and, thus, can be used for semi-fragile watermarking.
  • 7. An Uncompressed Image Encryption Algorithm Based on DNA Sequences

    Shima Ramesh Maniyath and Supriya M, Amrita Vishwa Vidyapeetham ,School of Engineering, India
    July 2011 | Cited by 12

    The rapid growth of the Internet and digitized content made image and video distribution simpler. Hence the need for image and video data protection is on the rise. In this paper, we propose a secure and computationally feasible image and video encryption/decryption algorithm based on DNA sequences. The main purpose of this algorithm is to reduce the big image encryption time. This algorithm is implemented by using the natural DNA sequences as main keys. The first part is the process of pixel scrambling. The original image is confused in the light of the scrambling sequence which is generated by the DNA sequence. The second part is the process of pixel replacement. The pixel gray values of the new image and the one of the three encryption templates generated by the other DNA sequence are XORed bit-by-bit in turn. The main scope of this paper is to propose an extension of this algorithm to videos and making it secure using modern Biological technology. A security analysis for the proposed system is performed and presented.
  • 8. Variable Range Energy Efficient Location Aided Routing For MANET

    Nivedita N. Joshi and Radhika D. Joshi, College of Engineering - Pune, India
    July 2011 | Cited by 11

    A Mobile Ad-Hoc Network (MANET) is a temporary, infrastructure-less and distributed network having mobile nodes. MANET has limited resources like bandwidth and energy. Due to limited battery power nodes die out early and affect the network lifetime. To make network energy efficient, we have modified position based Location Aided Routing (LAR1) for energy conservation in MANET. The proposed protocol is known as Variable Range Energy aware Location Aided Routing (ELAR1-VAR). The proposed scheme controls the transmission power of a node according to the distance between the nodes. It also includes energy information on route request packet and selects the energy efficient path to route data packets. The comparative analysis of proposed scheme and LAR1 is done by using the QualNet simulator. ELAR1-VAR protocol improves the network lifetime by reducing energy consumption by 20% for dense and mobile network while maintaining the packet delivery ratio above 90%.
  • 9. HMM Based POS Tagger for Hindi

    Nisheeth Joshi1, Hemant Darbari2 and Iti Mathur1, 1Banasthali University, India and 2Center for Development of Advanced Computing, India
    Feb 2013 | Cited by 11

    Part of Speech tagging in Indian Languages is still an open problem. We still lack a clear approach in implementing a POS tagger for Indian Languages. In this paper we describe our efforts to build a Hidden Markov Model based Part of Speech Tagger. We have used IL POS tag set for the development of this tagger. We have achieved the accuracy of 92%.
  • 10. Frequent Subgraph Mining Algorithms - A Survey and Framework for Classification

    K.Lakshmi1 and T. Meyyappan2, 1M.Visvesvaraya Institute of Technology, India and 2AlagappaUniversity, India
    Jan 2012 | Cited by 09

    Data mining algorithms are facing the challenge to deal with an increasing number of complex objects. Graph is a natural data structure used for modeling complex objects. Frequent subgraph mining is another active research topic in data mining . A graph is a general model to represent data and has been used in many domains like cheminformatics and bioinformatics. Mining patterns from graph databases is challenging since graph related operations, such as subgraph testing, generally have higher time complexity than the corresponding operations on itemsets, sequences, and trees. Many frequent subgraph Mining algorithms have been proposed. SPIN, SUBDUE, g_Span, FFSM, GREW are a few to mention. In this paper we present a detailed survey on frequent subgraph mining algorithms, which are used for knowledge discovery in complex objects and also propose a frame work for classification of these algorithms. The purpose is to help user to apply the techniques in a task specific manner in various application domains and to pave wave for further research.