Computer Science & I.T

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APPLYING DATA ANALYTICS IN INCREASING EFFICIENCY OF PUBLIC DISTRIBUTION SYSTEMS

Author(s):SHEETAL MAHAJAN
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 99-104
Public Distribution System (or PDS) is system operated by government of India to distribute subsidized food items to poor. Due to massive scale of system and involvement of large number of entities and departments, frauds and theft are common in system. This paper analyses use of tools and principles of Data analytics to increase the efficiency of PDS. This paper explores possibilities detecting fraud by analysing withdrawal trends at State, district and shop level. The paper further analyse using data analytics to predicting demand at various times of year at state, district and shop level; so adequate supply could be ensured.

DATA HIDING FOR BINARY IMAGE BY CONNECTIVITY-PRESERVING

Author(s):A. R. CHANDEKAR
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 105-112
Digital watermarking and data hiding techniques are used in many applications such as ownership protection, copy control, annotation, and authentication. In this method of blind data hiding for binary image by preserving the connectivity among pixels in a local neighborhood. Embedding the data in binary image is possible by flipping the pixels. The flippability decision of a pixel depends on three transitions from the pixels to its eight neighbors in a 3X3 block. Flipping a pixel does not destroy the connectivity among pixel, to ensure the good visual quality of an image. Fixed Block method of partitioning an image is discussed here. Security issue, visual quality, various methods of data hiding are discussed.

THE BPO COUNTRY COMPETENCY MODEL (CCM): A MODEL ESTABLISHING THE RELATIONSHIP AND THE DEGREE OF SIGNIFICANCE OF FACTORS THAT DRIVE COMPETENCE IN THE BUSINESS PROCESS OUTSOURCING (BPO)

Author(s):BEN OCRA, BENJAMIN AGGREY NTIM
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 113-120
The Business Process Outsourcing (BPO) sector is one of the fastest growing and important business sectors in the world. The sector provides a balance for the management and development of businesses. This paper aimed at examining factors that impact competence in the BPO sector. The study involved a survey and quantitative research designs in which snowball sampling was applied in selecting 320 respondents across 5 countries. The Multiple Linear Regression was used for data analysis in the context of SPSS. Findings indicated a significant positive relationship between competence and human resource attractiveness, financial attractiveness, BPO company characteristics and political environment. The model developed by the author explained 66% of variance in competence. Therefore, competence can be expedited in the BPO sector by enhancing human resource attractiveness, financial attractiveness, BPO company characteristics and political environment.

OPINION MINING FROM TEXT IN MOVIE DOMAIN

Author(s):NIDHI MISHRA, C. K. JHA
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 121-128
With emergence of web 2.0, there is a burst of movie domain opinion rich resources in the form of review sites like IMDB, yahoo movies etc. These resources contain public opinion on the movies which could help others in their decision making processes. These opinions could be expressed on different aspects of movie such as cast crew, story line etc. in number of sentences. Unlike product review sites, in which one or more bad features makes it bad overall, movie review sites do not follow the same presumption. Hence feature based review mining of movies are required so that people get opinions on the basis of individual feature. In this paper, we compute opinion of the feature of movie such as story, star cast, direction etc. and present the related text fragment to the user.

FACE RECOGNITION USING INCREMENTAL PRINCIPAL COMPONENTS ANALYSISINDEPENDENT COMPONENT ANALYSIS (IPCA-ICA) ALGORITHM

Author(s):P P REWAGAD, P S DESAI
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 129-136
The objective of this paper is to put working, mathematical model and result of Incremental Principal Component Analysis and Independent Component Analysis (IPCA-ICA) algorithm in face recognition which has the capabilities of recognition the face with different poses and under different conditions. This algorithm computes the principal components of a sequence of image vectors incrementally without estimating the covariance matrix (so covariance-free) and at the same time transforming these principal components to the independent directions that maximize the non-Gaussianity of the source. This procedure is done by merging the runs of two algorithms based on Incremental principal component analysis (IPCA) and independent component analysis (ICA) running sequentially.

OBJECT TRACKING SYSTEM USING IMAGE PROCESSING

Author(s):S. P. RASAL, HARSHA INGALE, V. S. SHELAR
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 137-142
Now a day, video surveillance is a part of our day to day life. In every private institute, company, government hospitals, offices, school, colleges, everywhere we need object tracking system for security purpose. Visual monitoring of activities using cameras automatically without human intervention is a challenging problem. Moving object detection is very important in intelligent surveillance. In this paper, an improved algorithm based on frame difference is presented for moving object detection. The method of motion detection and tracking is background subtraction. This paper presents a new object tracking model that systematically combines region and shape features. We design a new object detector for accurate and robust tracking in low-contrast, in noisy environment and complex scenes, which usually appear in the commonly used surveillance systems.

CLUSTER ANALYSIS – AN OVERVIEW

Author(s):ANURADHA BHATIA, GAURAV VASWANI
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 143-150
Clustering analysis, also called segmentation analysis or taxonomy analysis, aims to identify homogeneous objects into a set of groups, named clusters, by given criteria. Clustering is a very important technique of knowledge discovery for human beings. It has a long history and can be traced back to the times of Aristotle .These days; cluster analysis is mainly conducted on computers to deal with very large-scale and complex datasets. With the development of computer-based techniques, clustering has been widely used in data mining, ranging from web mining, image processing, machine learning, artificial intelligence, pattern recognition, social network analysis, bio-informatics, geography, geology, biology, psychology, sociology, customers behaviour analysis, marketing to e-business and other fields.

SELECTION OF MASTER STATION AND SYNCHRONIZATION OF TRANSMISSION IN QUANTUM CRYPTOGRAPHY: A NOVEL APPROACH

Author(s):MOLOY DHAR, SANDIP TIGGA, SOURISH MITRA, SAYANI CHANDRA
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 151-158
Two parties can communicate in secret if they already share a sufficient quantity of secret information. The problem then is how to distribute this secret information or key. Quantum cryptography provides the potential to ensure the security of the process of key distribution and hence to guarantee the covert nature of the communication. Quantum key distribution (QKD) uses quantum mechanics to guarantee secure communication. It enables two parties to produce a shared random secret key known only to them, which can then be used to encrypt and decrypt messages. Classical Cryptographic communication system is a secret communication that can only take place after a key is communicated in secret over a totally secure communication channel. Most widely used is the BB84 Protocol which was developed by IBM. In this paper takes advantage of Heisenberg’s principle in which measuring a quantum system disturbs it and yields incomplete information i.e. quantum key distribution which takes advantage of certain phenomena that occur at the subatomic level, so that any attempt by an enemy to obtain the bits in a key not only fails, but gets detected as well. In this paper, the intention was to propose the idea of an algorithm that can realize a quantum transmission between two computers. This algorithm, based on the result of the Secret Key conciliation process proposed by Bennett and Brassard on 1984 (BB84), can assure a high security communication between two users. The master station selection and its synchronized transmission oriented approach intend to be a quantum network algorithm that can realize a quantum connection between two computers.

CLASSIFICATION OF DEFORESTATION FACTORS USING DATA MINING TECHNIQUES

Author(s):S. JYOTHI, K. SARITHA, K. R. MANJULA
Journal: International Journal of Computer Science Engineering and Information Technology Research
Publisher:TJPRC Pvt Ltd.
Abstract
| Pages: 159-172
Data mining techniques have been widely used for extracting knowledge from large amounts of data. Monitoring deforestation is utmost important for the developing countries. Classification of deforestation is one of the primary objectives in the analysis of remotely sensed data. The present study focuses on monitoring accurate results of deforestation and forest degradation using classification techniques. In this paper, an experiment has been set up on different classification algorithms to compare the results. To evaluate the results, we used the WEKA open source tool, which is a collection of machine learning algorithms consisting of different processing tasks such as classification, association and clustering. The main aim of our study in this paper is comparative study of the classification algorithms to find the best algorithm of our data set.
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