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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,174 Documents
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Model of intention and actual use mobile learning in higher education institutions in Iraq Ayad Shihan Izkair; Muhammad Modi Lakulu
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1250-1258

Abstract

Mobile learning (ML) is now involved in the creation of teaching and learning methods for higher education. However, this involvement is varied among countries. The objective of this research was to examine the factors that impact students' intentions to use ML in Iraqi higher education institutions (HEIs). Building on unified theory of acceptance and use of technology (UTAUT) and information system success model (ISSM), a conceptual model was developed. The population of this study are users in Iraqi univeristies. Using a stratified random sampling, a total of 323 responses were collected to examine the proposed hypotheses. The findings showed that variables of UTAUT such as effort expectancy (EE), social influence (SI), performance expectancy (PE), facilitating conditions (FC) as well as variables of ISSM such as satisfaction along with perceived enjoyment and self efficacy affected positively the intention to use ML (ITUML) which in turn affected actual use (AU). Gender and experience moderated the effect of PE, EE, and SI on ITUML. A model of ITUML among users in Iraqi HEI was developed. Decision makers are advised to focus on certain variables to enhance the usage of ML in HEI.
Energy aware optimized dynamic routing mechanism in wireless sensor networks Geeta Patil; Arvind Mallikarjun Bhavikatti
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp944-955

Abstract

A trade-off between energy efficiency and optimized routing is massively recommended for transmission efficiency enhancement in wireless sensor networks (WSNs). Therefore, in this paper, graph-based energy optimized dynamic routing (GEODR) mechanism is introduced to set up a balance between energy consumption minimization and throughput enhancement using a dynamic and optimized routing mechanism in WSNs. A clustering scheme is employed based on graph theory, and cluster boundaries are formed using distance vectors. Cluster head (CH) selection is performed based on residual energy, the distance between CHs, and the mobility of the sink node. Each cluster is scattered with multiple tiny nodes, and event monitoring is performed. A model for graph-based dynamic routing to transmit data packets, cluster and cluster boundary formation, and optimization of routing problems is discussed. The performance efficiency of the proposed GEODR mechanism is determined by taking 100 sensor nodes, and 20 nodes are selected as CHs in a sensor network, and several other network parameters are also considered. A massive improvement in energy is observed by using sink node mobility. Experimental results are obtained using the proposed GEODR mechanism in terms of data packet transmission, alive nodes, dead nodes, and residual energy and compared against classical routing mechanisms such as low energy adaptive clustering hierarchy (LEACH) and stable election protocol (SEP).
Low-cost portable throttle curve manipulator for smooth initial movement of an electric vehicle Dimas Adiputra; Pangestu Widodo; Aldo Juan Widodo; Yosefan Alfeus Bayuaji; Nadia Dinda Pratama Putri
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp681-689

Abstract

This research aims to develop a low-cost portable throttle curve manipulator for a smooth initial movement of an electric vehicle. The hardware is mostly made up of an Arduino and a pulse width modulation (PWM)-to- direct current (DC) converter, which can be easily installed in electric vehicle. The manipulator produces a throttle output curve based on the current throttle input. The suitable throttle output curve is investigated in two stages. First, the four throttle curve types are compared based on motor vibration change and total energy usage during initial movement. They are none, linear, exponential, and polynomial curve types with a delay of 1 s. Then, in the second stage, the delay is varied from 0.5 to 2.5 s. The result shows that the linear throttle curve output with a delay of 1 s produces is appropriate to refine the initial movement of an electric vehicle compared to the polynomial and exponential curve types. The brushless DC electric (BLDC) motor vibration change decreases from 148.75 Hz to 107.45 Hz and total energy usage decreases from 90.64 joules to 87.23 joules. Therefore, the research concludes that the low-cost portable throttle curve manipulator can be developed using a linear throttle output curve with a delay of 1 s.
Implementation of a secure wireless communication system using true random number generator for internet of things Huirem Bharat Meitei; Manoj Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp982-992

Abstract

This paper describes the design and implementation of an internet of thing (IoT)-based application that uses a true random number generator (TRNG) with an all digital phase locked loop (ADPLL) for secure wireless communication. Field programmable gate array (FPGA) boards were used on the transmitter and receiver sides and were interfaced with Esp8266 chips to wirelessly send and receive encrypted sensor data. The MQ-2 gas sensor and tracking sensor were connected to the FPGA board on the transmitter side, where data from the sensors was encrypted using the exclusive-OR (XOR) function and the TRNG architecture. The system can be controlled by users through a web browser served by the ThingSpeak cloud. The Artix-7 FPGA device is used to implement the proposed wireless communication system, for which design and synthesis were done using the Xilinx Vivado 2015.2 tool. The proposed system uses a low amount of power and is suitable for a standalone, highly secure TRNG-based IoT application. The National Institute of Standard and Testing (NIST SP 800-22) test showed that ADPLL with finite impulse response (FIR) filter-based TRNGs are better for encrypting IoT devices for secure wireless communication.
An optimization of multiple gateway location selection in long range wide area network networks Chutchai Kaewta; Charuay Savithi; Ekkachai Naenudorn
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1011-1020

Abstract

The adoption of smart agricultural technology in rural areas is still limited in terms of network infrastructure supported. As a result, farmers continue to practice traditional farming that mainly focuses on human labor and requires experience in planning the production of agricultural products in unstable weather conditions, which makes the farmers highly risky. Currently, long range (LoRa) technology is a smart agriculture support tool that will enable the Internet of Things devices to a large number of end nodes distributed over a wide geographical area. They could access cloud computing from a long distance, kilometers, for processing via long range wide area network (LoRaWAN) communication protocol. When choosing a multiple gateway location for LoRaWAN networks, big networks must consider the spatial distribution of clients, radio signal propagation, and the cap on the number of devices served access. In this study, a mathematical model is developed to optimize coverage. The LINGO modeling program, an exact software method, was used to test the model. The findings indicated that the best six gateways at the optimal LoRaWAN gateway location. The gateways can provide signal coverage for all end nodes and can manage the capacity of the LoRaWAN gateway to support the proper number of end nodes.
Machine learning algorithms for privacy preserving in vehicular ad hoc network Shazia Sulthana; Byppanahalli Narayana Reddy Manjunatha Reddy
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1021-1028

Abstract

Machine learning (ML) will improve the outcomes through the use of methods that categorize the information into the predetermined set. This work is to present an estimation and assessment of machine learning techniques for achieving privacy preservation in vehicular ad hoc networks (VANETs). This method generates two distinct group keys for prime and secondary users. Road side units (RSUs) are deployed to broadcast one group key from the trusted authority (TA) to the primary users, and secondary users are utilized to transmit the other group key. The main aim of this network is developed to avoid vulnerable attacks and to enhance the privacy of this network, Naïve Bayesian classifier (BC), support vector machine (SVM), K-nearest neighbor (KNN), artificial neural networks (ANN), Bayesian network (BN) methods are utilized in correlation with the proposed deep neural networks (DNN) with the black widow optimization (BWO) for protection preserving. These learning characterization procedures are assessed concerning delay, network lifetime, throughput, delivery ratio, and drop and this proposed calculation (DNN-BWO) shows improved results than the current methodologies.
Analysis of SSVEP component acquisition from EEG signals for efficient target identification Kalenahally R. Swetha; Ravikumar G. Krishnegowda; Shashikala S. Venkataramu
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp838-845

Abstract

The application of the brain-computer interface (BCI) is massively helpful and advantageous for disabled people. Moreover, BCI is an arrangement of software and hardware interface that provides a direct interaction between the human brain and computer devices. Therefore, in this article, A steady state visual evoked potential (SSVEP)-based BCI system is presented to identify SSVEP components from multi-channel electroencephalogram (EEG) data by minimizing background noise using an adaptive spatial filtering method. Here, the proposed adaptive spatial filtering-based SSVEP component extraction (ASFSCE) model improves reproducibility among multiple trails and identifies targets efficiently by optimizing the Eigenvalue problem. Along with that, the proposed ASFSCE model minimizes computational complexity from O(G2) to to get high target identification accuracy with faster execution. Performance results are measured using the SSVEP dataset. In this dataset, 11 subjects are used to perform experiments and 256-channel EEG data is taken. The efficiency of the proposed ASFSCE model is measured in terms of mean target detection accuracy and mean information transfer rate (ITR) in bits per minute. The average detection accuracy and ITR are evaluated by considering 23 trials for each subject. The obtained detection accuracy is 93.47% and ITR is 308.23 bpm.
Analysis study of the bee algorithms as a mechanism for solving combinatorial problems Hafedh Ali Shabat; Khamael Raqim Raheem
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp1091-1098

Abstract

Combinatorial optimization problems are problems that have a large number of discrete solutions and a cost function for evaluating those solutions in comparison to one another. With the vital need of solving the combinatorial problem, several research efforts have been concentrated on the biological entities behaviors to utilize such behaviors in population-based metaheuristic. This paper presents bee colony algorithms which is one of the sophisticated biological nature life. A brief detail of the nature of bee life has been presented with further classification of its behaviors. Furthermore, an illustration of the algorithms that have been derived from bee colony which are bee colony optimization, and artificial bee colony. Finally, a comparative analysis has been conducted between these algorithms according to the results of the traveling salesman problem solution. Where the bee colony optimization (BCO) rendered the best performance in terms of computing time and results.
Speech scrambling based on multiwavelet and Arnold transformations Zahraa Abdulmuhsin Hasan; Suha Mohammed Hadi; Waleed Ameen Mahmoud Al-Jawher
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp927-935

Abstract

For communication applications where secure speech signal transmissions are a key requirement, speech scrambler is taken into consideration. To prevent someone from listening in on private conversations without their knowledge, it can transform clear speech into a signal that is unintelligible. The proposed speech scrambling system involves using two types of frequency transformation techniques: multiwavelet transform and Arnold transform. The effectiveness of the scrambling algorithm was evaluated with the help of three different measurements: the peak signal to noise ratio (PSNR), the estimated time (ET), and the mean square error (MSE). According to the final findings, the outcome of the scrambled speech signal does not have any residual intelligibility, while the quality of the descrambled speech is extremely satisfactory and has a low MSE level.
Neural network based novel controller for hybrid energy storage system for electric vehicles Sagar Sharma; Shakuntla Boora
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 2: May 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i2.pp670-680

Abstract

This manuscript deals with the various control strategies of storage system for an electrical vehicle. High demands in the electrical systems in the field of transportations leads to various challenges and more precise control and regulations techniques. Apart from the conventional grid system now a days the integration of renewable energy systems like solar, wind and fuel cell system leads to more complex system but these system shares the load from conventional generating system. This paper deals with the study and control aspects of the electrical vehicles associated with hybrid energy storage (HES) systems. In general, when systems are integrated with the main grid there are more distortions and ripples in the system. To reduce these distortions various control techniques are used. This paper proposes a neural network-based PI (NNPI) controller for HES system for electric vehicles for better distortion less outputs.

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