ARPN journal of engineering and applied sciences 

About: ARPN journal of engineering and applied sciences is an academic journal. The journal publishes majorly in the area(s): Computer science & Engineering. It has an ISSN identifier of 1819-6608. Over the lifetime, 859 publications have been published receiving 2713 citations. The journal is also known as: Journal of engineering and applied sciences (ARPN) & ARPN Journal of engineering and applied sciences.

Modeling and simulation based approach of photovoltaic system in simulink model

Abstract: This paper presents the modeling and simulation of photovoltaic model using MATLAB/Simulink software package. The proposed model is design with a user-friendly icon using Simpower of Simulink block libraries. Taking the effect of irradiance and temperature into consideration, the output current and power characteristic of PV model are simulated using the proposed model. Detailed modeling procedure for the circuit model with numerical values is presented. The simulator is verified by applying the model to 36 W PV modules. The proposed model was found to be better and accurate for any irradiance and temperature variations. The proposed model can be very useful for PV Engineers and expert who require a simple, fast and accurate PV simulator to design their systems.

Gamification in online collaborative learning for programming courses: A literature review

Abstract: The popularity of computer science education triggered a dramatic rise in the number of tertiary institutions offering computer science courses. Nevertheless, many employers complain that graduates do not have the required skills. Lately, the higher education sector has faced a continuous decrease in the number of students choosing to study computer science courses, and some of the reasons for this rejection are related to the difficulties in mastering computer science skills. As core subjects in a computer science major, programming language subjects play an important role in successful tertiary computer science education. The embedding of gamification in programming courses has been identified as a potential technique that could maximize student participation and have a positive impact on learning. This research aims to provide an overview of how the embedding of gamification in online collaborative learning can enhance participation among novice programming students. The main findings from this review include the identification of the important participation elements for programming students in the online collaborative learning environment, a list of game elements embedded in online collaborative learning to facilitate participation among programming students, and suggestions regarding suitable gamification approaches for programming courses.

Feature extraction of EEG signal using wavelet transform for autism classification

Abstract: Feature extraction is a process to extract information from the electroencephalogram (EEG) signal to represent the large dataset before performing classification. This paper is intended to study the use of discrete wavelet transform (DWT) in extracting feature from EEG signal obtained by sensory response from autism children. In this study, DWT is used to decompose a filtered EEG signal into its frequency components and the statistical feature of the DWT coefficient are computed in time domain. The features are used to train a multilayer perceptron (MLP) neural network to classify the signals into three classes of autism severity (mild, moderate and severe). The training results in classification accuracy achieved up to 92.3% with MSE of 0.0362. Testing on the trained neural network shows that all samples used for testing is being classified correctlyARPN Journal of Engineering and Applied Sciences

Angle Modulated Simulated Kalman Filter Algorithm for Combinatorial Optimization Problems

Abstract: Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF). Every agent in SKF is regarded as a Kalman filter. Based on the mechanism of Kalman filtering and measurement process, every agent estimates the global minimum/maximum. Measurement, which is required in Kalman filtering, is mathematically modelled and simulated. Agents communicate among them to update and improve the solution during the search process. However, the SKF is only capable to solve continuous numerical optimization problem. In order to solve discrete optimization problems, the SKF algorithm is combined with an angle modulated approach. The performance of the proposed angle modulated SKF (AMSKF) is compared against two other discrete population-based optimization algorithms, namely, binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA). A set of traveling salesman problems are used to evaluate the performance of the proposed AMSKF. Based on the analysis of experimental results, we found that the proposed AMSKF is as competitive as BGSA but the BPSO is superior to the both AMSKF and BGSA.

Papr reduction using scs-slm technique in stfbc mimo-ofdm

Abstract: The combination of MIMO and OFDM gives a very attractive option for high data rate communication in wireless communication system over frequency selective fading. However, MIMO-OFDM also inherent the PAPR problem from OFDM system. We proposed our SCS technique and modified SLM technique to be applied in diversity MIMO-OFDM system for PAPR and BER performance improvement. The utilization of circulant shift codeword from SCS technique with multiplication of phase factor of SLM technique in preparing several candidates for interleaving technique is proposed in MIMO-OFDM system. This approach gave a new solution of reducing high PAPR in MIMO-OFDM system. Moreover, by using diversity MIMO-OFDM which is STFBC, the improvement of BER performance also can be improved until 55%.