International Journal of Electrical and Computer Engineering (IJECE)

Journal Information
ISSN / EISSN : 20888708 / 20888708
Current Publisher: Institute of Advanced Engineering and Science (10.11591)
Total articles ≅ 2,508
Current Coverage
Archived in

Latest articles in this journal

Mustafa Ayesh Al-Dhaheri, Nasr-Eddine Mekkakia-Maaza, Hassan Mouhadjer, Abdelghani Lakhdari
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1736-1746; doi:10.11591/ijece.v10i2.pp1736-1746

Diabetes is considered one of the life-threatening diseases in the world which need continuous monitoring to avoid the complication of diabetes. There is a need to develop a non-invasive monitoring system that avoids the risk of infection problems and pain caused by invasive monitoring techniques. This paper presents a method for developing a noninvasive technique to predict the blood glucose concentration (BCG) based on the Near-infrared (NIR) light sensor. A prototype is developed using a finger sensor based on LED of 940 nm wavelength to collect photoplethysmography (PPG) signal which is variable depending on the glucose concentration variance, a module circuit to preprocess PPG signals is realized, which includes an amplifier and analog filter circuits, an Arduino UNO is used to analog-to-digital conversion. A digital Butterworth filterer is used to remove PPG signal trends, then detect the PPG data peaks to determine the relationship between the PPG signal and (BCG) and use it as input parameters to build the calibration model based on linear regression. Experiments show that the Root Mean Squares Error (RMSE) of the prediction is between 8.264mg/dL and 13.166 mg/dL, the average of RMSE is about 10.44mg/dL with a correlation coefficient (R^2) of 0.839, it is observed that the prediction of glucose concentration is in the clinically acceptable region of the standard Clark Error Grid (CEG).
Prathviraj N., Santosh L Deshpande
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1915-1923; doi:10.11591/ijece.v10i2.pp1915-1923

The single constrained Quality of Service (QoS) routing in Mobile Ad-hoc NETwork (MANET) is disastrous in consideration of MANET characteristics, inference, collision and link failure as it maintains a single path. The QoS enabled routing yields better packet delivery and maintains consistency among nodes in the network by incorporating multi-constrained and multipath routing. The Dynamic Source Routing (DSR) is best suited source routing algorithm to maintain multipath information at the source node, but performance degrades with larger number of mobile nodes. Multi-layer mechanism should be incorporated to maintain QoS metric information spreads across multiple layers of TCP/IP protocol stack. The proposed multipath QoS enabled source routing provides balanced routing by making use of all these features. The imprecise decision making strategy called Rough Set Theory (RST) is used at destination node for decision making. The Route REQuest (RREQ) messages coming from different routes are filtered by considering the QoS metrics of each and every route by making use of RST. The Route REPly (RREP) messages are generated and delivered to the source node for filtered RREQ messages. The proposed routing algorithm will reduce load on the network by reducing number of control messages exchanged for route establishment. This will evenly distribute load among all the nodes and it also avoid the scenarios like few nodes starved for resources. Finally, multipath routing always provides alternate routing option in case of route failure.
Halima Ikaouassen, Abderraouf Raddaoui, Miloud Rezkallah, Hussein Ibrahim
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1905-1914; doi:10.11591/ijece.v10i2.pp1905-1914

This paper investigates an improved current predictive model control (PCMC) strategy with a prediction horizon of one sampling time for voltage regulation in standalone system based on diesel engine driven fixed speed of a synchronous generator. An adaptive PR controller with anti-windup scheme is employed to achieve high performance regulation without saturation issues. In addition, new method to obtain the optimal parameters of the adaptive PR controller to achieve high performance during the transition and in steady state is provided. To balance the power at the point of common coupling (PCC) as well as to feed a clean power to the connected loads, a three-phase voltage source inverter (VSI) with LRC filter is controlled using the developed improved PCMC strategy, where the output filter current is controlled using the predicting of the system behaviour model in the future step, at each sampling prediction time. The performances of the proposed configuration and the improved control strategy are verified using Matlab/Simulink interface.
Ida Nurhaida, Vina Ayumi, Devi Fitrianah, Remmy A. M. Zen, Handrie Noprisson, Hong Wei
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 2045-2053; doi:10.11591/ijece.v10i2.pp2045-2053

One of the most famous cultural heritages in Indonesia is batik. Batik is a specially made drawing cloth by writing Malam (wax) on the cloth, then processed in a certain way. The diversity of motifs both in Indonesia and the allied countries raises new research topics in the field of information technology, both for conservation, storage, publication and the creation of new batik motifs. In computer science research area, studies about Batik pattern have been done by researchers and some algorithms have been successfully applied in Batik pattern recognition. This study was focused on Batik motif recognition using texture fusion feature which is Gabor, Log-Gabor, and GLCM; and using PCA feature reduction to improve the classification accuracy and reduce the computational time. To improve the accuracy, we proposed a Deep Neural Network model to recognise batik pattern and used batch normalisation as a regularises to generalise the model and to reduce time complexity. From the experiments, the feature extraction, selection, and reduction gave better accuracy than the raw dataset. The feature selection and reduction also reduce time complexity. The DNN+BN significantly improve the accuracy of the classification model from 65.36% to 83.15%. BN as a regularization has successfully made the model more general, hence improve the accuracy of the model. The parameters tuning also improved accuracy from 83.15% to 85.57%.
Basheer Al-Duwairi, Wafaa Al-Kahla, Mhd Ammar Alrefai, Yazid Abedalqader, Abdullah Rawash, Rana Fahmawi
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 2182-2191; doi:10.11591/ijece.v10i2.pp2182-2191

The Internet of Things (IoT) is becoming an integral part of our daily life including health, environment, homes, military, etc. The enormous growth of IoT in recent years has attracted hackers to take advantage of their computation and communication capabilities to perform different types of attacks. The major concern is that IoT devices have several vulnerabilities that can be easily exploited to form IoT botnets consisting of millions of IoT devices and posing significant threats to Internet security. In this context, DDoS attacks originating from IoT botnets is a major problem in today’s Internet that requires immediate attention. In this paper, we propose a Security Information and Event Management-based IoT botnet DDoS attack detection and mitigation system. This system detects and blocks DDoS attack traffic from compromised IoT devices by monitoring specific packet types including TCP SYN, ICMP and DNS packets originating from these devices. We discuss a prototype implementation of the proposed system and we demonstrate that SIEM based solutions can be configured to accurately identify and block malicious traffic originating from compromised IoT devices.
Chethan B. K., M. Siddappa, Jayanna H. S.
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1561-1569; doi:10.11591/ijece.v10i2.pp1561-1569

A mobile agent offers discrete advantage both in facilitating better transmission as well as controlling the traffic load in Mobile Adhoc Network (MANET). Hence, such forms of network offers maximized dependencies on mobile agents in terms of its trust worthiness. At present, there are various work being carried out towards resisting security breach in MANET; however approaches using mobile agent based mechanism is few to found. Therefore, the proposed system introduces a novel mathematical model where an extensive decision making system has been constructed for identifying the malicious intention of mobile agents in case they go rogues. By adopting multi-tier communication policy and fairness concept, the proposed system offers the capability to resist any form of malicious activity of mobile agent without even presence of any apriori information of adversary. The outcome shows proposed system outshines existing security scheme in MANET.
El Ghouch Nihad, Kouissi Mohamed, En-Naimi El Mokhtar
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1980-1992; doi:10.11591/ijece.v10i2.pp1980-1992

Several researches in the field of adaptive learning systems has developed systems and techniques to guide the learner and reduce cognitive overload, making learning adaptation essential to better understand preferences, the constraints and learning habits of the learner. Thus, it is particularly advisable to propose online learning systems that are able to collect and detect information describing the learning process in an automatic and deductive way, and to rely on this information to follow the learner in real time and offer him training according to his dynamic learning pace. This article proposes a multi-agent adaptive learning system to make a real decision based on a current learning situation. This decision will be made by performing a hypride cycle of the Case-Based Reasonning approach in order to follow the learner and provide him with an individualized learning path according to Felder Silverman learning style model and his learning traces to predict his future learning status. To ensure this decision, we assign at each stage of the Incremental Hybrid Case-Based Reasoning at least one active agent performing a particular task and a broker agent that collaborates between the different agents in the system.
Rekha V., Natarajan K., Innila Rose J.
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1849-1858; doi:10.11591/ijece.v10i2.pp1849-1858

Background Subtraction of a foreground object in multimedia is one of the major preprocessing steps involved in many vision-based applications. The main logic for detecting moving objects from the video is difference of the current frame and a reference frame which is called “background image” and this method is known as frame differencing method. Background Subtraction is widely used for real-time motion gesture recognition to be used in gesture enabled items like vehicles or automated gadgets. It is also used in content-based video coding, traffic monitoring, object tracking, digital forensics and human-computer interaction. Now-a-days due to advent in technology it is noticed that most of the conferences, meetings and interviews are done on video calls. It’s quite obvious that a conference room like atmosphere is not always readily available at any point of time. To eradicate this issue, an efficient algorithm for foreground extraction in a multimedia on video calls is very much needed. This paper is not to just build Background Subtraction application for Mobile Platform but to optimize the existing OpenCV algorithm to work on limited resources on mobile platform without reducing the performance. In this paper, comparison of various foreground detection, extraction and feature detection algorithms are done on mobile platform using OpenCV. The set of experiments were conducted to appraise the efficiency of each algorithm over the other. The overall performances of these algorithms were compared on the basis of execution time, resolution and resources required.
Fredy Martinez, Edwar Jacinto, Fernando Martinez
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 2164-2172; doi:10.11591/ijece.v10i2.pp2164-2172

This paper presents a low cost strategy for real-time estimation of the position of obstacles in an unknown environment for autonomous robots. The strategy was intended for use in autonomous service robots, which navigate in unknown and dynamic indoor environments. In addition to human interaction, these environments are characterized by a design created for the human being, which is why our developments seek morphological and functional similarity equivalent to the human model. We use a pair of cameras on our robot to achieve a stereoscopic vision of the environment, and we analyze this information to determine the distance to obstacles using an algorithm that mimics bacterial behavior. The algorithm was evaluated on our robotic platform demonstrating high performance in the location of obstacles and real-time operation.
Manoj Chavan, Ravish R. Singh, Vinayak Bharadi
International Journal of Electrical and Computer Engineering (IJECE), Volume 10, pp 1823-1832; doi:10.11591/ijece.v10i2.pp1823-1832

Online signature verification is a prominent behavioral biometric trait. It offers many dynamic features along with static two dimensional signature image. In this paper, the Hybrid Wavelet Transform (HWT) was generated using Kronecker product of two orthogonal transform such as DCT, DHT, Haar, Hadamard and Kekre. HWT has the ability to analyze the signal at global as well as local level like wavelet transform. HWT-1 and -2 was applied on the first 128 samples of the pressure parameter and first 16 samples of the output were used as feature vector for signature verification. This feature vector is given to Left to Right HMM classifier to identify the genuine and forged signature. For HWT-1, DCT HAAR offers best FAR and FRR. . For HWT-2, KEKRE 128 offers best FAR and FRR. HWT-1 offers better performance than HWT- 2 in terms of FAR and FRR. As the number of states increase, the performance of the system improves. For HWT - 1, KEKRE 128 offers best performance at 275 symbols whereas for HWT - 2, best performance is at 475 symbols by KEKRE 128.
Back to Top Top