International Journal of Information Science and Computing
Category - Research Article
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Title:
Neural Optimized Autotuning Fuzzy Logic Controller for Spherical Tank Process
Abstract:

In any real time control application, the controller is expected to give optimal results irrespective of plant non-linearity, operating point change, component non-linearity and saturation. Fuzzy Logic Control (FLC) meets the control objective as it crafts the human experience in the form of If-Then rules. As the gain factors or scaling factors are constant in conventional FLC, Autotuning FLC with tuned scaling factors take over the charge. Further, in real time controllers, the memory constraint is dominant. As a solution, reduction of existing fuzzy rule base by subtractive clustering and optimization of the reduced rule set via neural network is proposed. Autotuning of input scale factors clubbed with reduction and optimization of a controller rule set is proposed to meet out the dynamic control of real time spherical tank process. The efficacy of the proposed approach is compared with real time servo and regulatory results of conventional FLC and AFLC of the spherical tank process

Category - Research Article
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Title:
MTech-Information Science and Technology (IST): Possibilities and challenges with proposed Five Year Integrated model for building Technology vis-à-vis Society
Abstract:

Information Science as a subject is an important interdisciplinary knowledge cluster and is very much close to Information Technology and Computer Science. But Information Science also deals with some other knowledge gradients such as Information Studies, Knowledge Management and hence Management Science. Still, MTech or BTech programme is mainly popular in India, it’s neighbouring countries and some UK Asian countries. As far as Information Science with MTech is concerned, not a single programme available on this nomenclature; but huge possibilities are there to introduce such programme with mixing up Engineering faculties with existing Information Science schools. Thus, this paper discusses about Information Science, it’s changing nature, and also about need and potentiality of five years integrated MTech- Information Science programme

Category - Research Article
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Title:
Cooperative Communication For 5G Networks: A Green Communication Based Survey
Abstract:

This paper provides an in-depth review on the technologies being considered for recent and future wireless cellular networks based on cooperative communication with reduction in energy. Initially, the evolution from fourth generation (4G) to fifth generation (5G) is described in terms of performance characteristics and major requirements. The technology developed by the 3GPP community, which supports the integration of current and future services. The fifth generation (5G) cellular networks will require a major paradigm shift to satisfy the increasing demand for higher data rates, reduced latencies, better energy efficiency, and reliable connectivity through femto-cell based relays. These relay nodes are equipped with energy harvesting technique in cooperative networks for the improvement in energy efficiency. Unlike conventional energy source, the fluctuation in energy flow causes performance degradation. To overcome the above drawbacks, energy harvesting technique and other methodologies are explained together with possible improvements, challenges and few approaches that have been considered in this paper.

Category - Research Article
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Title:
Comparative Study on LCMS, LMS and CMS
Abstract:

A Learning Content Management System (LCMS) is an integrated multi-user administrative, authoring, and delivery platform. It allows administrators to host, schedule, manage registrations, assess, test, and track online training activities. These systems also allow Instructional Designers to create and house course materials, and learners to access course schedules, register for training, take assessments, and manage transcripts. The tools may base on content management or learning content management. Presently a composition of Learning Management System (LMS) and Content Management System (CMS) is used in eLearning. This paper helps you to understand the basic functionality of LMS, CMS and LCMS and how these are helpful in eLearning.

Category - Research Article
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Title:
Some Common Fixed Point Theorems in 2-Metric Spaces
Abstract:

In this paper, we obtain some results of fixed point theorems in 2-metric spaces which are inspired by the works of V. Gupta et al.[3 ]. The results are proved using some binary relation and conditions on the mappings. Existence and uniqueness of fixed points of self maps satisfying certain conditions are investigated in a complete 2-metric space.

Category - Research Article
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Title:
Cyber Security Analysis of E-Commerce in Madhya Pradesh
Abstract:

This paper presents Cyber Security analysis of E-commerce for reliance products in Madhya Pradesh. We evaluate Division and district wise accuracy of transactions and business growth percentages. Generally we take four divisions Indore, Bhopal, Jabalpur and Gwalior. Each division we select four districts. We take districts in Indore Alirajpur, Dhar, Barwani, Khandwa. In Bhopal Raisen, Rajgarh, Sehore, Vidisha. In Jabalpur Katni, Seoni Mandla, Balaghat. In Gwalior Datia, Guna, Shivpuri, Ashoknagar. We used three different types of data sets Bag of Words, Twenty News Group data sets, Legal Case Reports Datasets in the Experiments. For experimental results analysis evaluated using the analytical MATLAB 7.14 software is used. The experimental results show the proposed approach best performs.

Category - Research Article
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Title:
Ensemble Classifier based on Optimized Feature Matrix for Healthcare Dataset
Abstract:

The mining of health care data is important aspect for the forecast of critical disease like cancer. In health care data mining various tools and techniques are available and applicable from machine learning. Machine Learning offers popular effective technique of classification for the purpose of mining voluminous dataset of health care. This paper implements the different traditional classifiers decision tree, k-nearest neighbor, support vector machine and modified ensemble classifier random forest for classification of health/diseased entities from the UCI data set for Cancer. The paper proposes the feature matrix extracted from majority voting ensemble classifier random forest mapped to SVM. Then it is implemented on three variations of cancer data set. Random forest shows the great results in terms of reduction in features, overfitting by averaging several tree, and also algorithm show less variance by using multiple tree, reduce the chance of stumbling across a classifier that doesn’t perform well because of the relationship between train and test data. In Random Forest, randomness is introduced by identifying the best split feature from a random subset of available features. These available important features further classified by powerful supervised machine learning algorithm named support vector machine. The main purpose of feature selection approach is to select a minimal and relevant feature subset for the given dataset and maintaining its original representation. This approach enhances the performance of SVM classifier and give rise to modified the majority vote ensemble classifier. The proposed hybrid mechanism of random forest feature matrix and SVM classification has shown 1.3% increment in accuracy for reduced cancer data set and this is verified from three reduced cancer data sets. This paper also demonstrates better accuracy of proposed ensemble classifier by comparative analysis with existing classifiers mechanism.