Volume-04 , Special Issue-01 , Feb - 2016 Go Back

The Command Based System (CBS) is one of the fields of Human Computer Interaction (HCI). In the modern era the Command Based System is enormously explored by many scientists and it is used in many fields. This study proposes to develop a new approach to build up a Command Based System which will accept a Text as an input and take the corresponding action. In this paper the String and Synonym Matching Algorithm (SSMA) is made to develop a String Command Based System (SCBS). The String and Synonym Matching Algorithm (SSMA) Algorithm focuses on the comparison between the users given string with the preloaded strings in the system database. The comparison is made in two ways i.e. a straight string comparison and the comparison between all the synonyms of the input string with the preloaded strings from the system database. The trick of matching the synonyms of the user given string reduces the space in the system database and increases the flexibility of the user to give more input with same meaning.

Human Computer Interaction (HCI), Command Based System (CBS), String Command Based System (SCBS), Unimodal System, String and Synonym Matching Algorithm (SSMA), Space Complexity

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Papri Ghosh, Tejbanta Singh Chingtham, Mrinal Kanti Ghose, "Space Reduction using String and Synonym Matching Algorithm (SSMA)", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.1-8, 2016.

This paper proposed a new spectral graph clustering model by casting the non-categorical spatial data sets into an undirected graph. Decomposition of the graph to Delaunay graph has been done for computational efficiency. All pair shortest path based model has been adapted for the creation of the underlying Laplacian matrix of the graph. The similarity among the nodes of the graph is measured by a random selection based correlation coefficients. The effectiveness as well as the efficiency of the proposed model has beentasted and measuredwith standard data and the performances are compared with that of existing standard models.

Graph Clustering;Delaunay Triangulation;All-pair Shortest Path Distance; Similarity Matrix; Spectral Clustering

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Parthajit Roy, Swati Adhikari, J. K. Mandal, "A Shortest Path Similarity Matrix based Spectral Clustering", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.9-15, 2016.

Medical imaging is a process of creating images of interior body organs or parts which is very useful for diagnose, clinical analysis and treatment of specific disease. Magnetic Resonance Imaging (MRI) is amedical imaging technique used primarily in medical settings to produce high quality images of the inside of the human body or parts. MRI has become effective way to study brain tumors.Threshold based image segmentation is a common technique often used to detect the tumor object. The literature survey depicts that most of the existing methods have ignored the poor quality images. In this paper a method has been proposed based on histogram segmentation to detect the brain tumor from T1 weighted MRI images. T1 weighted MRI images of brain has been takenas input. This system includes image filtering, image segmentation, and object extraction for the purpose. The whole procedure has been implemented in MATLAB.

Magnetic Resonance Image (MRI), Histogram segmentation, Brain tumor, Histogram peak difference

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Kanishka Sarkar, ArdhenduMandal, Rakesh Kumar Mandal, "Histogram Peak Normalization Based Threshold to Detect Brain Tumor from T1 Weighted MRI", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.16-24, 2016.

Fire is one of the major problems that are causing great loss to property and ecosystem in today’s world. Fires not only affect the characteristics of forests but it also affects human lives and livelihood. Due to the lack of specific techniques for calculation of burnt regions of forests, researchers use different methods. In this research, an automated approach is developed to determine the significant burnt area of forest using different image processing techniques. The proposed method is compared with other existing methods and is found to be capable in more precise measurement of the burnt area.

Thresholding, Erosion, Dilation, Region leveling

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Bibek Ranjan Ghosh, Siddhartha Banerjee, Attyuttam Saha, "Automated System for Computationof Burnt Forest Region using Image Processing", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.25-31, 2016.

Image compression plays an important role in digital image processing, it is also very crucial for efficient transmission and storage of images. In image compression, does not only concentrate on reducing size but also concentrate on doing it without losing quality and information of image. This paper summarizes the image compression techniques that may be lossy and lossless and research possibilities.

Image Compression; Lossy Techniques; Lossless Techniques

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Sumanta Lal Ghosh, Dilip Roy Chowdhury, "Conceptual Framework Strategies for Image Compression: A Review", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.32-37, 2016.

Today the importance of going green have been realized both in terms of environmental issues and cost minimization by implementing different strategies and policies by the ICT industry. Going green suggest the environmentally responsible practice of computers and related resources of ICT. For a sustainable environment, today Green Computing is an emerging topic, because of efficient power usage, minimal or no emission of carbon footprint, also proper disposal of electronic waste (e-waste) and many more, thus to take less participation in the global warming phenomenon. In this study, emphasis has given ondiminishing the energy and carbon footprint of computer and its related resources like- monitors, printers using green computing.

Carbon Footprint; E-waste; Green Computing; ICT

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Deepanjan Sen, Dilip Roy Chowdhury, "Green Computing : Efficient Practices And Applications", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.38-47, 2016.

Artificial Neural Network plays an important role in medical diagnostics field and used by medical practitioners and domain specialists for diagnosis and treatment with ultimate accuracy. In this paper, a medical diagnosis system is proposed for predicting Generalized Anxiety Disorder (GAD). In today’s world of computational Intelligence, Swarm Intelligence technique is one of the successive ways to solve hard medical problems. Particle Swarm Optimization (PSO) imitates the behavior of a swarm of insects or a group of fish or birds. In this paper the relative advantages of genetic algorithm, Particle Swarm Optimization and Artificial Neural Network (ANN) are combined to achieve the desired accuracy. ANN’s are often used as a powerful discriminating classifier for tasks in medical diagnosis for early detection of diseases. The data set on this study is composed of 200 patients with various sign symptoms. The objective of this paper is to determine the weights of the neural network using genetic algorithm in less number of iterations and PSO algorithm for feature Reduction. For training the network Quasi-newtonalgorithm is used in this study using various training algorithm parameters. The accuracy obtained using this approach is 98.56%.

Artificial Neural Network (ANN); Genetic Algorithm (GA); Particle Swarm Optimization (PSO); Generalized Anxiety Disorder (GAD)

[1] Anxiety Dsorders Association of America Available: http://www.adaa.org
[2] ”Generalized Anxiety Disorder: When Worry Gets Out of Control”-national institute of mental Health U.S. Department of Health and Human Services national institutes of Health
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Dilip Roy Chowdhury, Arpita Das, "Generalized Anxiety Disorder : Prediction using ANN", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.48-56, 2016.

This beautiful world is a collection of variety of people. They have different sort of mind. Some people always speak the truth. Some hardly have the habits to tell the truth. If a person is guilty then he or she must try to save him or herself and conceal his or her sin. If a system can be designed to detect lie then a genuine and trusty counseling can be done for the establishment of the truth. This paper contains an algorithm PVMANN which makes a gateway to detect a person’s truthfulness.

Lie detection, Artificial Neural Network (ANN), Pattern, Perceptron, Segmentation

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[2]. Mic Hanlon, Mathematician at Manchestar Metropolitan University, Polygraphic Lie Detecting Technique.
(www.gizmag.com/go/1735/)
[3]. Patrick Kennedy, School of Professional Development
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Shantanu Chakraborty, Rakesh Kumar Mandal, "Pattern Variation Method to Detect Lie Using Artificial Neural Network (PVMANN)", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.57-60, 2016.

Steganography is an ancient approach of fusing data into innocence medium to hide data secretly in such a way no one can have knowledge of it. This paper presents a technique of Image steganography on frequency domain through Daubechies Transformation. This transformation converts image from spatial domain to frequency domain and allowed embedding with a payload of 2.0 bpb without visual degradation. A gray level image considered as innocent medium of size NxN, where N = 2p, p is an positive integer & is divided into 4x4 non-overlapping blocks in a row major order and a 2D Daubechies Transformation is applied to each of (NxN)/16 blocks to generate frequency components. Three layer of adjustment in terms of security enhancement are applied to improve the quality of stego image. The number of bits embedded per pixel or block is a variable and based on hash function which is used to find the position of each bit. After embedding 4 bits from LSB are grouped into two pairs and XORed, bitwise results are shuffled and stored on last four bits from LSB

Daubechies Transform,Cover Image,Stego Image

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[3] J.K. Mandal,MadhumitaSengupta, ”Authentication/Secret Message Transformation through Wavelet Transform Based Subband Image Coding (WTSIC)”,2010
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[5] MadhumitaSengupta,J. K. Mandal, N. Ghoshal ,”An Authentication Technique in Frequency Domain through Wavelet Transform (ATFDWT)”,2012
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Jyotsna Kumar Mandal, Sujit Das,, Madhumita Sengupta , "A novel technique to hide information using Daubechies Transformation", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.61-68, 2016.

CPU is a primary computer resource, so its scheduling is central to operating system design. When multiple runnable processes exist in the ready queue, OS has the onus of responsibility to decide which one is to run fast. The part of the OS that takes this decision is called scheduler and the algorithm based on which it works, is called the scheduling algorithm. Different kinds of scheduling algorithms exist in the literature. Among them First-Come-First-Served (FCFS), Shortest-job-first (SJF), Priority Scheduling and Round-robin, are mention-worthy. This paper proposes a weight-based starvation-free improvised scheduling algorithm that allocates CPU to processes in round-robin manner while the time quantum is calculated based on the burst time of the processes waiting in the ready queue.

Anuradha Banerjee, Nabajit Mondal, Naznin, Poulomi Basu, Prateeksha Singh

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CPU, Processes, Ready Queue, Round-Robin, Scheduling, Weight, "Weight-based Starvation-free Improvised Round-Robin (WSIRR) CPU Scheduling Algorithm", International Journal of Computer Sciences and Engineering, Vol.04, Issue.01, pp.69-77, 2016.