International Journal of Modern Education and Computer Science (IJMECS)

IJMECS Vol. 10, No. 8, Aug. 2018

Cover page and Table of Contents: PDF (size: 227KB)

Table Of Contents


Numerical Simulation Methods of Electromagnetic Field in Higher Education: Didactic Application with Graphical Interface for FDTD Method

By Mihaela Osaci

DOI:, Pub. Date: 8 Aug. 2018

In general, the act of teaching in universities of the numerical methods of electromagnetic field simulation is a rather difficult action. In order to facilitate this act, it is necessary to use modern didactic means that complement the classical ones, so that the students understand in an interactive manner the method, the algorithm and its implementation into a programming language. This paper proposes a didactic method able to facilitate the understanding of numerical methods in electromagnetism. It's about of a didactic application with graphical interface, programmed using the Guide Matlab to simulate the electromagnetic waves propagation through various environments and applying the finite-difference time-domain method (FDTD).

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Modified Integral Sliding Mode Controller Design based Neural Network and Optimization Algorithms for Two Wheeled Self Balancing Robot

By Ekhlaskaram Noor Mjeed

DOI:, Pub. Date: 8 Aug. 2018

Two-wheeled Self-balancing (TWSB) mobile robot is considered to be highly nonlinear and unstable dynamic system. Unstable means that the robot is free to advance forward or backward without any forces applied. It must, therefore, be controlled. The purpose of this work is to design an intelligent nonlinear Modified Integral Sliding Mode Controller (MISMC) based on simple Adaline neural network for balancing a two-wheeled self-balancing mobile robot, in addition to improve the performance of this robot in tracking the desired trajectory.
The simple Adaline neural network is used to enhance the performance of the conventional Integral Sliding Mode Controller (ISMC) which is an effective and powerful technique because it has a high performance. Also, in this work, a Modified Particle Swarm Optimization (MPSO) and Modified Cuckoo Search (MCS) algorithms have been proposed to find and tune the best MISMC parameters and hence enhance the performance characteristics of the robot system by reducing the processing time as well as improving the response accuracy through minimizing the tracking error of the mobile robot. The Integral Square Error (ISE) method has been used as a performance index for the two algorithms (MPSO, MCS) to measure the performance of the proposed controller. Numerical simulations show the efficiency of the suggested controller by handling the balance and tracking problems of the two-wheeled self-balancing mobile robot.

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An Informal Approach to Identify Bright Graduate Students by Evaluating their Classroom Behavioral Patterns by Using Kohonen Self Organizing Feature Map

By C.Bhanuprakash Y.S. Nijagunarya M.A. Jayaram

DOI:, Pub. Date: 8 Aug. 2018

The intention of this paper is to analyze how a behavior of a student will influence us in gauging their performance level rather than considering their traditional examination scores. This approach is considered to be one of the informal approaches which guide many school managements to identify good, average and poor category of students. The main criteria used here is behavioral science which explores activities and interactions among the student community when they are inside the school campus.
School-Wide Positive Behavior Support can assist in addressing the issues related to the prevention, educational identification and effective intervention implementation through its systemic logic, data-based decision making, and capacity building within and across schools.
Clustering is the process of grouping a set of data objects into multiple groups or clusters with high similarities and dissimilarities. Dissimilarities and Similarities are assessed on the attribute values describing the objects and often involve distance measures. Clustering acts as a data mining tool by having its roots in many application areas such as biology, security, business intelligence, web search etc.
In this survey, we have involved 200 + students who are currently studying engineering streams in various classes that includes first semester to final semester. Their age group was in the range of 18 to 22 years. Their behavioral survey has been conducted over a span of 4 to 6 months by closely observing their activities, mannerisms and then evaluated by entering in to this system by using the evaluation interface. This evaluation interface consists of 15 features with 4 optional choices. Each choice is rated with a specific numeric value. By taking one of the choices among all the 15 features for each of the student, at the end, he/she will get some score which will be stored in a database. With the help of this score, a manual grouping was done. Later, for the same dataset, a soft computing technique has been applied by working with self organizing feature map algorithm for grouping the students.

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Clustering based Architecture for Software Component Selection

By Jagdeep Kaur Pradeep Tomar

DOI:, Pub. Date: 8 Aug. 2018

The component-based software engineering (CBSE) consists of component selection, qualification, adaptation, assembly and updating of components according to the requirements. The focus of this paper is software component selection only. Now-a-days many selection processes, techniques and algorithms are proposed for this task. This paper presents generalized software component selection architecture using clustering. The architecture is divided into four tiers namely Component Requirements and Component Selection Tier, Query and Decision Tier, Application logic tier with Clustering and Component Cluster Tier. The architecture offers manifold advantages like i) presenting a generalized architecture where the existing techniques can be applied, reducing the search space for the component selection. ii) It also illustrates the usage of clustering in the software component selection without the need for pre- specification of number of clusters and considering more than two features while clustering. iii)The cluster validation is performed to check the correctness of the clusters. This complete selection process is validated on a representative instance of set of components.

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A Case Analysis on Different Registration Methods on Multi-modal Brain Images

By Deepti Nathawat Manju Mandot Neelam Sharma

DOI:, Pub. Date: 8 Aug. 2018

Many applications of artificial vision need to compare or integrate images of the same object but obtained at different moments of time with different devices (cameras), from different positions, under different conditions, etc. These differences in capture give rise to images with important relative geometric differences that prevent these "Fit" with precision over each other.
The registry eliminates these geometric differences so that located pixels in the same coordinates correspond to the same point of the object and, therefore, both images can easily be compared or integrated. The registration of images is essential in disciplines such as remote sensing, radiology, robotic vision, etc. ; Fields, all of them, that overlap images to study environmental phenomena, monitor tumours carcinogenic or to reconstruct the observed scene. This paper also study different measures of similarity used to measure their consistency and a novel procedure is proposed to improve the accuracy of the linear record by pieces. Specifically the elements that influence the estimation are analysed experimentally of probability distributions of the intensity levels of the images. These distributions are the basis for calculating measures of similarity based on entropy as mutual information (MI) or the Entropy correlation coefficient (ECC). Therefore, the effectiveness of these measures depends critically on their correct estimation.

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Voltage Quality Evaluation of Distribution Network based on Probabilistic Load Flow

By Guowei Dong Hengrui Ma

DOI:, Pub. Date: 8 Aug. 2018

Voltage quality for residents of 10kV and below is affected by some factors: voltages of substation 10kV buses, power supply topologies, line types, and power supply distances of 10kV lines, reactive power compensation and loads of distribution transformers. As loads of distribution transformers vary randomly in space and time, voltages of distribution transformers fluctuate randomly as well as distribution network power flows, even network structures and parameters are invariable when voltages of 10kV buses. According to the definition of voltage eligibility rate, a random fluctuation model of distribution transformer loads was built through long term statistical analysis of distribution transformer loads on actual distribution network. By calculating the probabilistic load flows and considering correlation of random fluctuations, static voltages of distribution transformers were analyzed with probability method and power supply voltage eligibility rates of all 10kV lines could be calculated. The simulations show that the power supply voltage eligibility rates can be analyzed and evaluated more comprehensively by probabilistic load flow calculation, such a calculation provides the theoretical calculation basis for both reasonably controlling the bus voltages and improving the power supply voltage eligibility rates.

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