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31,456 Article Results

IQ level prediction and cross-relational analysis with perceptual ability using EEG-based SVM classification model

10.11591/ijai.v8.i4.pp436-442
Noor Hidayah Ros Azamin , Mohd Nasir Taib , Aisyah Hartini Jahidin , Dyg Suzana Awang , Megat Syahirul Amin Megat Ali
This paper presents IQ level prediction and cross-relational analysis with perceptual ability using EEG-based SVM classification model. The study hypothesized that measure of perceptual ability and intelligence is strongly connected through the brain’s attention regulatory mechanism. Therefore, an intelligent classification model should be able to predict and map IQ levels from a dataset associated with varying levels of perception. 115 samples of resting EEG is acquired from the left prefrontal cortex. Sixty-five is used for perceptual ability analysis via CTMT, while another fifty is used in the development of IQ level classification model using SVM. The mean pattern of theta, alpha and beta bands show positive correlation between perceptual ability and IQ level datasets. Meanwhile, the developed SVM model outperforms the previous ANN method; yielding 100% accuracy for training and testing. Subsequently, the classification model successfully predicts and mapped samples from the perceptual ability dataset to its corresponding IQ levels with 98.5% accuracy. Therefore, validity of the study is confirmed through positive correlation demonstrated by both traits of cognition using the pattern of mean power ratio features, and successful prediction of IQ level for perceptual ability dataset via SVM classification model.
Volume: 8
Issue: 4
Page: 436-442
Publish at: 2019-12-01

Efficient Multi-task offloading with energy and computational resources optimization in a mobile edge computing node

10.11591/ijece.v9i6.pp4908-4919
Mohamed El Ghmary , Tarik Chanyour , Youssef Hmimz , Mohammed Ouçamah Cherkaoui Malki
With the fifth-generation (5G) networks, Mobile edge computing (MEC) is a promising paradigm to provide near computing and storage capabilities to smart mobile devices. In addition, mobile devices are most of the time battery dependent and energy constrained while they are characterized by their limited processing and storage capacities. Accordingly, these devices must offload a part of their heavy tasks that require a lot of computation and are energy consuming. This choice remains the only option in some circumstances, especially when the battery drains off. Besides, the local CPU frequency allocated to processing has a huge impact on devices energy consumption. Additionally, when mobile devices handle many tasks, the decision of the part to offload becomes critical. Actually, we must consider the wireless network state, the available processing resources at both sides, and particularly the local available battery power. In this paper, we consider a single mobile device that is energy constrained and that retains a list of heavy offloadable tasks that are delay constrained. Therefore, we formulated the corresponding optimization problem, and proposed a Simulated Annealing based heuristic solution scheme. In order to evaluate our solution, we carried out a set of simulation experiments. Finally, the obtained results in terms of energy are very encouraging. Moreover, our solution performs the offloading decisions within an acceptable and feasible timeframes.
Volume: 9
Issue: 6
Page: 4908-4919
Publish at: 2019-12-01

Intelligent credit scoring system using knowledge management

10.11591/ijai.v8.i4.pp391-398
Bazzi Mehdi , Chamlal Hasna , El Kharroubi Ahmed , Ouaderhman Tayeb
Promoting entrepreneurship among Moroccan young people has been challenged by a plethora of economic and social problems in the aftermath of the Arab Spring. Several government programs have been set up for young entrepreneurs. Thus, faced with the large number of credit applications solicited by these young entrepreneurs, banks resorted to artificial intelligence techniques. In this respect, this article aims at proposing a decision-making system enabling the bank to automate its credit granting process. It is a tool that allows the bank, in the first instance, to select promising projects through a scoring approach adapted to this segment of entrepreneurs. In the second step, the tool allows the setting of the maximum credit amount to be allocated to the selected project. Finally, based on the knowledge of the bank’s experts, the tool proposes a breakdown of the amount granted by the bank into several products adapted to the needs of the entrepreneur.
Volume: 8
Issue: 4
Page: 391-398
Publish at: 2019-12-01

Design of a discrete PID controller based on identification data for a simscape buck boost converter model

10.11591/ijpeds.v10.i4.pp1797-1805
Mohammed Almaged , Salam Ibrahim Khather , Abdulla I. Abdulla
This work shows the design and tuning procedure of a discrete PID controller for regulating buck boost converter circuits. The buck boost converter model is implemented using Simscape Matlab library without having to derive a complex mathematical model. A new tuning process of digital PID controllers based on identification data has been proposed. Simulation results are introduced to examine the potentials of the designed controller in power electronic applications and validate the capability and stability of the controller under supply and load perturbations. Despite controller linearity, the new approach has proved to be successful even with highly nonlinear systems. The proposed controller has succeeded in rejecting all the disturbances effectively and maintaining a constant output voltage from the regulator.
Volume: 10
Issue: 4
Page: 1797-1805
Publish at: 2019-12-01

Bivariate modified hotelling’s T2 charts using bootstrap data

10.11591/ijece.v9i6.pp4721-4727
Firas Haddad , Mutasem K. Alsmadi , Usama Badawi , Tamer Farag , Raed Alkhasawneh , Ibrahim Almarashdeh , Walaa Hassan
The conventional Hotelling’s  charts are evidently inefficient as it has resulted in disorganized data with outliers, and therefore, this study proposed the application of a novel alternative robust Hotelling’s  charts approach. For the robust scale estimator , this approach encompasses the use of the Hodges-Lehmann vector and the covariance matrix in place of the arithmetic mean vector and the covariance matrix, respectively.  The proposed chart was examined performance wise. For the purpose, simulated bivariate bootstrap datasets were used in two conditions, namely independent variables and dependent variables. Then, assessment was made to the modified chart in terms of its robustness. For the purpose, the likelihood of outliers’ detection and false alarms were computed. From the outcomes from the computations made, the proposed charts demonstrated superiority over the conventional ones for all the cases tested.
Volume: 9
Issue: 6
Page: 4721-4727
Publish at: 2019-12-01

Enhancing active radial distribution networks by optimal sizing and placement of DGs using modified crow search algorithm

10.11591/ijeecs.v16.i3.pp1179-1188
Mohamed Abdelbadea , Tarek A. Boghdady , Doaa Khalil Ibrahim
Incorporating many Distributed Generators (DGs) technologies in power system networks has grown rapidly in recent years. Distributed generation (DG) plays a key role in reducing power loss and enhancing the voltage profile in radial distribution networks. However, inappropriate DGs site or size may cut network efficiency; moreover, injecting harmonics is one of the integration concerns of inverter-based DGs. Two-procedure based approach is introduced in this paper. The first procedure solves the DGs siting and sizing problem, as a multi-objective one by improving the voltage profile of the whole distribution network and also reducing its power loss. A weighted sum method is presented to create the Pareto optimal front in this procedure and get the compromised solution by applying a novel metaheuristic optimizer, named Crow Search Algorithm (CSA). A modification on CSA is also proposed and applied to improve its performance. The achieved solution for inverter-based DGs placement and size is checked in the second procedure to make sure the accepted voltage THD at all buses by implementing detailed simulation for the tested system using Matlab/Simulink. The proposed approach has been tested on IEEE 33-bus radial distribution system with photovoltaic DGs. To confirm the superiority of the modified CSA algorithm in terms of quality of solution, its achieved results are compared with the results offered by the original CSA algorithm and published results of some other nature-inspired algorithms.
Volume: 16
Issue: 3
Page: 1179-1188
Publish at: 2019-12-01

Intelligent control of DC-DC converter based on PID-neural network

10.11591/ijpeds.v10.i4.pp2254-2262
Hussain K. khleaf , Ali kareem Nahar , Ansam Subhi Jabbar
This paper introduced a “PID-NN” based on Particle Swarm Optimization control that was applied to a boost converter operating in large-signal domains. Simulation results have shown that the proposed “PID-NN controller” could enhance the (boost converter) startup response with the use of fewer on-off switch operations compared to the Conventional “PID controllers”. This result is of high importance in practice since reducing the number of on-off switches can effectively decrease the transient disturbances and losses due to switching. Simulations also prove that the proposed “PID-NN controller” is capable of efficiently improving rejecting potential disturbances that could happen in the input voltage. Moreover, it has been noticed that the output voltage is more efficiently controlled when applying “PID-NN controller”. The results of the simulation show the efficiency of the suggested algorithm compared with other well-known learning methods.
Volume: 10
Issue: 4
Page: 2254-2262
Publish at: 2019-12-01

RB-Bayes algorithm for the prediction of diabetic in Pima Indian dataset

10.11591/ijece.v9i6.pp4866-4872
Rajni Rajni , Amandeep Amandeep
Diabetes is a major concern all over the world. It is increasing at a fast pace. People can avoid diabetes at an early stage without any test. The goal of this paper is to predict the probability of whether the person has a risk of diabetes or not at an early stage. This would lead to having a great impact on their quality of human life. The datasets are Pima Indians diabetes and Cleveland coronary illness and consist of 768 records. Though there are a number of solutions available for information extraction from a huge datasets and to predict the possibility of having diabetes, but the accuracy of their mining process is far from accurate. For achieving highest accuracy, the issue of zero probability which is generally faced by naïve bayes analysis needs to be addressed suitably. The proposed framework RB-Bayes aims to extract the required information with high accuracy that could survive the problem of zero probability and also configure accuracy with other methods like Support Vector Machine, Naive Bayes, and K Nearest Neighbor. We calculated mean to handle missing data and calculated probability for yes (positive) and no (negative). The highest value between yes and no decide the value for the tuple. It is mostly used in text classification. The outcomes on Pima Indian diabetes dataset demonstrate that the proposed methodology enhances the precision as a contrast with other regulated procedures. The accuracy of the proposed methodology large dataset is 72.9%.
Volume: 9
Issue: 6
Page: 4866-4872
Publish at: 2019-12-01

The use of Least Significant Bit (LSB) and Knight Tour Algorithm for image steganography of cover image

10.11591/ijece.v9i6.pp5218-5226
Soo Ann Nie , Ghazali Sulong , Rozniza Ali , Andrew Abel
Steganography is one of the method to communicate in a hidden way. In another word, steganography literally means the practice of hiding messages or information within another data. Previous studies have proposed various steganography techniques using different approaches including Least Significant Bit (LSB), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT). However, different approaches still have its own weaknesses. Therefore image stenography using Knight Tour Algorithm with Least Significant Bit (LSB) technique is presented. The main objective is to improve the security factor in the stego image. Basically, the proposed technique is divided into two parts which are the sender and receiver side. Then, steganalysis which is a type of attack on stenography algorithm is used to detect the secret message in the cover image by the statistical analysis of pixel values. Chi Square Statistical Attach which is one of the type of steganalysis is used to detect these near-equal Po Vs in images and bases the probability of embedding on how close to equal the even pixel values and their corresponding odd pixel values are in the test image. The Knight Tour Algorithm is applied due to the common Least Significant Bit technique that is weak in security and easily decoded by outsider.
Volume: 9
Issue: 6
Page: 5218-5226
Publish at: 2019-12-01

Research methods of V/F control for matrix converter use direct space vector modulation

10.11591/ijece.v9i6.pp5115-5124
Bogdan Vasilev , Le Van Tung
Matrix converter (MC) is direct AC to AC converter built on bidirectional switches with more outstanding advantages compared to the indirect AC - DC-AC converter such as power exchange in two directions, allowing regenerative braking performance amount returned grid. However, the modulation method for Matrix converter has the disadvantage of low voltage transmission ratio, current at the input and output current, the voltage of converter has many high-order harmonic components. The paper presents the technique of directly modulating the space vector which will improve the quality of matrix converter such as input and output currents with sine form, power factor input is nearly 1 and can be adjusted. Also, build V/F control method for matrix converter to control three-phase alternating current induction motors. Research results are tested by Matlab & Simulink software.
Volume: 9
Issue: 6
Page: 5115-5124
Publish at: 2019-12-01

Assessing the intelligence of a student through TIC-TAC-TOE game for career guidance

10.11591/ijece.v9i6.pp5545-5551
Sastry Kodanda Rama Jammalamadaka , Chandra Prakash Vudatha
In order to provide Career Guidance by an expert system to a student, apart from his/her academic record, it is necessary to assess various psychological factors of the student like Intelligence, patience and perseverance, Learning ability and Speed of solving problem, etc. The outcome of this research work is an expert system called Tic-Tac-Toe Game Playing Career Guidance System (TTT-GP-CGS) that is useful to assess the psychological factors of the student through Tic-Tac-Toe Game Playing, build the cognitive model of the student and predict the appropriate career(s) for the student. The system plays Tic-Tac-Toe game with the student several times. The average score obtained by the student reflects his/her intelligence. The average time taken by the student for playing the game reflects student's speed of solving problem. The number of attempts the student makes reflects the students patience and perseverance. When the student plays the game with the spaystem every day, if the student's  score increases day by day, it reflects that the student has good learning ability. In this way the system will assess the psychological factors of the student and builds the cognitive model of the student. Internally the system converts the quantitative scores into qualitative scores. The system maintains a table of careers and the expected levels of psychological factors that are required from student's side to carry out the career successfully. The system invokes a matching process  by considering the cognitive model of the student and the table of careers, and predicts the career(s) suitable  to the student.
Volume: 9
Issue: 6
Page: 5545-5551
Publish at: 2019-12-01

Modular multilevel converter (MMC) based STATCOM with vector control and virtual impedance voltage compensations

10.11591/ijpeds.v10.i4.pp1833-1851
Abdurrahman Umar Lawan , Haider A.F. Almurib , Jeen G. Khor
This paper presents modular multilevel converter (MMC) with circulating current control which provides an improved balanced capacitors voltages. The control is achieved by employing compensation techniques in the external and internal controls of the MMC based static compensator (STATCOM). Performance variations arise during STATCOM non-ideal operation with grid externally and during capacitors voltage transients due to charging and discharging within the MMC that result in the emergence of a voltage disturbance. The proportional integral (PI) controller is usually employed in the external and internal controls for a fast response and reactive current control. In this paper, the performance of the PI controller is improved using voltage compensation in the external control and virtual impedance in the capacitor voltage control within a five-level MMC. The proposed control minimizes the variations in the STATCOM operations with the grid and within the MMC to provide an enhanced overall system response.
Volume: 10
Issue: 4
Page: 1833-1851
Publish at: 2019-12-01

A new approach for enhancing LSB steganography using bidirectional coding scheme

10.11591/ijece.v9i6.pp5286-5294
Mohammed M. Saeed Abdullah Al-Momin , Issa Ahmed Abed , Hussein A. Leftah
This paper proposes a new algorithm for embedding private information within a cover image. Unlike all other already existing algorithms, this one tends to employ the data of the carrier image more efficiently such that the image looks less distorted. As a consequence, the private data is maintained unperceived and the sent information stays unsuspicious.  This task is achieved by dividing the least significant bit plane of the cover image into fixed size blocks, and then embedding the required top-secret message within each block using one of two opposite ways depending on the extent of similarity of each block with the private information needed to be hidden. This technique will contribute to lessen the number of bits needed to be changed in the cover image to accommodate the private data, and hence will substantially reduce the   amount of distortion in the stego-image when compared to the classic LSB image steganography algorithms.
Volume: 9
Issue: 6
Page: 5286-5294
Publish at: 2019-12-01

Product recommendation system based user purchase criteria and product reviews

10.11591/ijece.v9i6.pp5454-5462
Jinyoung Kim , Doyeun Hwang , Hoekyung Jung
In this paper, we propose a system that provides customized product recommendation information after crawling product review data of internet shopping mall with unstructured data, morphological analysis using Python. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. User searches for a proudct to be purchased and select the most important purchase criteria when purchasing the product. And extracts and analyzes only the review including the purchase criterion selected by the user among the product reviews left by other users. The positive and negative evaluations contained in the extracted product review data are quantified and using the average value, we extract the top 10 products with good product evaluation, sort and recommend to users. And provides user-customized information that reflects the user's preference by arranging and providing a center around the criteria that the user occupies the largest portion of the product purchase. This allows users to reduce the time it takes to purchase a product and make more efficient purchasing decisions.
Volume: 9
Issue: 6
Page: 5454-5462
Publish at: 2019-12-01

Solar energy density estimation using ANFIS based on daily maximum and minimum temperature

10.11591/ijpeds.v10.i4.pp2206-2213
M. Irwanto , H. Alam , M. Masri , B. Ismail , W. Z. Leow , Y. M. Irwan
The data of solar energy density in one area is very important when the area will constructed photovoltaic (PV) system. The data is as preliminary study to decide what the area is suitable or not to be constructed the PV application system. But, sometime the available data is missing because the limitation of weather equipment.  An alternative technique for the available data of solar energy density should be done for the continuity of PV application system decision. An estimation technique of solar energy density is one part of good alternative to solve this problem. This paper presents the estimation of solar energy density using Adaptive Neuron Fuzzy Inference System (ANFIS). The ANFIS system has two input data of the measured daily minimum, maximum temperature and difference between maximum and minimum temperature. The measured solar energy density is as target data of ANFIS system. The data is recorded from Medan meteorological station through the web site of world weather online for the year of 2018. The result shows that the average estimated solar energy density is classified in the very high solar energy density and based on the percentage error shows that the estimated solar energy density is acceptable.
Volume: 10
Issue: 4
Page: 2206-2213
Publish at: 2019-12-01
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