Journal of Computer Sciences and Applications

This article addresses an interesting comparative analytical study. The presented study considers two concepts of diverse algorithmic biological behavioral learning approach. Those concepts for computational intelligence are tightly related to neural and non-neural Systems. Respectively, the first algorithmic intelligent approach concerned with observed obtained practical results after three neural animal systems’ activities. Namely, they are Pavlov’s, and Thorndike’s experimental work. Furthermore, a mouse’s trials during its movement inside figure of eight (8) maze, those aiming to reach optimal solution for reconstruction problem. However, second algorithmic intelligent approach conversely originated from observed activities’ results for non-neural Ant Colony System (ACS). Those results have been obtained after reaching optimal solution solving Traveling Sales-man Problem (TSP). Interestingly, the effect of increasing number of agents (either neurons or ants) on learning performance shown to be similar for both introduced neural and non-neural systems. Considering observed two systems' performances, it has shown both to be in agreement with learning convergence process searching for Least Mean Square (LMS) error algorithm. Accordingly, adopted ANN modeling is realistically relevant tool systematic observations' investigation and performance analysis for both selected computational intelligence (biological behavioral learning) systems.

Journal of Computer Sciences and Applications. 2015, 3(3), 79-89. DOI: 10.12691/jcsa-3-3-4
Pub. Date: July 03, 2015

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DecenCrypto Cloud: Decentralized Cryptography Technique for Secure Communication over the Clouds

by Shyam Nandan Kumar

Original Research

With the advent of the World Wide Web and the emergence of e-commerce applications and social networks, organizations across the Cloud, share a large amount of data day by day. Secure Data sharing is an important issue over the cloud environment. In order to enhance the security services, the paper proposes Decentralized Cryptography Technique for Secure Communication over the Clouds. In this paper, Cryptography Model for Secure Data Sharing over Cloud is presented first. Cryptography Management Approach is given to access the secure resource over cloud and then Algorithm Design Methodology is provided in decentralized manner. The paper also provides a concise but all-round analysis on data security and privacy protection issues associated with cloud computing.

Journal of Computer Sciences and Applications. 2015, 3(3), 73-78. DOI: 10.12691/jcsa-3-3-3
Pub. Date: June 10, 2015

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Three Dimensional Face Surfaces Analysis using Geodesic Distance

by Rachid AHDID, Said SAFI and Bouzid MANAUT

Original Research

In this paper, we present an automatic 3D face recognition system based on the computation of the geodesic distance between the reference point and the other points in the 3D face surface. To compute a geodesic distance, we use the Fast Marching algorithm for solving the Eikonal equation. For space reduction, we apply Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (LDA). Quantitative measures of similarity are obtained and then used as inputs to several classification methods. In the classifying step, we use: Neural Networks (NN), k-Nearest Neighbor (KNN) and Support Vector Machines (SVM). To test this method and evaluate its performance, a simulation series of experiments were performed on 3D Shape REtrieval Contest 2008 database (SHREC2008).

Journal of Computer Sciences and Applications. 2015, 3(3), 67-72. DOI: 10.12691/jcsa-3-3-2
Pub. Date: May 13, 2015

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Transplanting Binary Decision Trees

by Eli M. Dow and Tim Penderghest

Original Research

In this paper, we describe a means of compiling binary decision trees as generated by the C4.5 binary decision tree classifier into high-performance, reusable, stand-alone, run-time classifiers. We demonstrate the memory savings and run time characteristics of a compiled tree as compared to the traditional use of a C4.5 runtime. We demonstrate 100% correctness over every input we have available for testing as compared to our own enhanced version of the classic C4.5 run-time classification routine, consultr. In addition, this work provides a framework for comparing decision tree classifiers to more in vogue classifiers such as support vector machines as demonstrated within.

Journal of Computer Sciences and Applications. 2015, 3(3), 61-66. DOI: 10.12691/jcsa-3-3-1
Pub. Date: May 11, 2015

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11258 Views3042 Downloads6 Likes1 Citations