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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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Tidal energy assessment with hydrodynamic modelling Imran Ali; Andrew Ragai Henry Rigit; Omar bin Yaakob; Jane Labadin; Altaf Hussain Rajpar
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1201-1212

Abstract

The increasing demand for sustainable energy generation brings a need for tidal current energy resource exploration around the globe. Hydrodynamic modelling is an essential aspect to explore macro tidal sites. In the current research paper, a 2D hydrodynamic model is set up by utilizing the numerical application of Delft3D. The model is validated against the database results and the two macro tidal sites are identified along the coastline of Sarawak, Malaysia. The maximum available kinetic energy flux at the identified location is 0.6 kW/m2, during peak neap tide hours. This stands as a sound justification to have a detailed tidal energy assessment study in this area in future research.
Smart technologies of the risk-management and decision-making systems in a fuzzy data environment Yesmagambetova Marzhan; Keribayeva Talshyn; Koshekov Kairat; Belginova Saule; Alibekkyzy Karlygash; Ospanov Yerbol
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1463-1474

Abstract

The purpose of this article is to provide a methodology for calculating and predicting the quality of solution implementation in complicated multi-parametric organizational and technological challenges with control agent uncertainty. The article's study findings are centered on the practical application of formal methods in predicting the outcomes of control and decision-making risks under the uncertainty of model agents. The proposed mathematics and simulation applications use a multi-agent strategy to handle the general problem of assessing quality control based on "producer risk (project customer)" and "user risk." Computer experiments with simultaneous graphical visualization of the results improve the accuracy of mathematical modeling, increasing the study's effectiveness. Under the uncertainty of system agents, a simulation model has been designed to analyze and anticipate the dependability of control and the hazards of decision-making. The suggested model is unique in that it takes into account the statistical nature of normative values as well as the rules of equal probability. To handle a frequent problem, the proposed system technique employs a dual approach. It accomplishes this by assessing the quality of the control process based on the magnitude of the risks in the decision-making system.
Development of data encryption standard algorithm based on magic square Suhad Muhajer Kareem; Abdul Monem S. Rahma
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp297-305

Abstract

Data encryption standard is one of the famous algorithms that used in many fields for security purpose but it s susceptible for many attacks. This paper+ proposes a new modification of data encryption standard (DES) algorithm called magic square data encryption standard (MSDES) algorithm in order to include a high-level security by increase the mixing between the plaintext (96 bit) and the key (48 bit). This modification is done by using magic square 3×3 and an additional key is created using linear first shift register (LFSR) in each round of the Feistel of DES. A colour image encryption is simulated and presented as the comparison between the original DES and MSDES algorithm. The proposed algorithm gets the best results in complexity, histogram, entropy, peak-signal-to-noise ratio-(PSNR) and coefficient-correlation.
The impacts from Sr4La(PO4)3O: Ce3+, Tb3+, Mn2+ phosphor resulting in luminous flux of WLED devices Huu Phuc Dang; Bui Van Hien; Nguyen Le Thai
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp693-699

Abstract

Using the solid-state technique that involves great temperature, we created multiple phosphors Sr4La(PO4)3O:Ce3+, Tb3+, Mn2+ (abbreviated as SLPO:Ce, Tb, Mn). We then examined their heat consistency, luminescence, as well as energy shift from Ce3+ to Tb3+ and Mn2+. We can acquire a considerable boost for the faint emission in green generated by Tb3+ as well as the emission in red generated by Mn2+ via adding the sensitizer Ce3+ ions. Through modifying the proportion between Ce3+ and Tb3+ along with the proportion between Ce3+ and Mn2+, it is possible to adjust the chroma of emission. We acquired white illumination which had color coordinates determined as (0.3326, 0.3298) for the testing phosphor Sr4La(PO4)3O: 0.12Ce3+, 0.3Mn2+. Such result displays the promising efficiency of phosphors Sr4La(PO4)3O:Ce3+, Tb3+, Mn2+ for the WLED devices.
Underwater image copyright protection using robust watermarking technique Methaq Talib Gaata; Mustafa Dhiaa Al-Hassani
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1148-1156

Abstract

It became possible to send and reformat underwater images for copyright theft due to the rapid advancement of computer networks and image forgery tools. Acquiring underwater images is dangerous and requires much efforts, expensive imaging equipment, and professional photographers. Therefore, there is an urgent need to develop copyright protection methods to ensure that property rights are not lost. This paper presents a robust watermarking technique that ensures proof of ownership for underwater images, preventing unauthorized individuals from claiming ownership. The suggested watermarking technique's main contribution depends on using the Hough transform in order to find appropriate regions to hide the watermark information within the underwater images. The Hough transform is useful for identifying areas of difficult texture that can be used as a host for watermark information with minimal distortion. Also, the Twofish algorithm has been used to encrypt the watermark information before being hidden in the underwater image. The performance of the suggested watermarking technique is tested by two metrics: quality and robustness. The results show that the suggested method works because of the quality of the images that were made after the watermark was added and because it could withstand the attacks on it.
A new density core graph-cut class decomposition to improve neural network classification performance Eakawat Tantamjarik; Thitipong Tanprasert
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp496-508

Abstract

This research presents a new pre-processed class decomposition technique called density core graph-cut (DCGC). The method uses supervised clustering instead of a traditional unsupervised one to decompose the class. Supervised clustering requires additional label information to function and with that it gains a better understanding of the distribution. DCGC employs nearest neighbors to form a density core graph for each class. Then, the edges of each graph to be removed or cut is identified utilizing class information. Lastly, it yields final clusters by grouping all connected cores and assigning the remaining samples to a cluster where the nearest core belongs. Training neural network classifiers on complex label data will yield a better accuracy with the modified class representation. Intuitively, the decision boundaries separating classes based on the modified labels are less complex, and classifiers’ chance to reach these hyperplanes is higher. The results present that training neural networks using label representations from DCGC significantly helps improve the classification accuracy of neural networks on syntactic datasets as high as 30%. For real-world problems, the experiment presents a mixed result in which some datasets moderately benefit from DCGC.
Estimation of channel distortion in orthogonal frequency division multiplexing system using pilot technique Nisha Mary Joseph; C. Puttamadappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp106-114

Abstract

Orthogonal frequency-division multiplexing (OFDM) is resistant to frequency selective fading due to the longer symbol duration. However, mobile applications channel timing fluctuations in one OFDM signal cause intercarrier-interference (ICI), which reduces performance. This research presented the support vector regression (SVR) model-based channel estimation technique for coherent optical communication systems. Due to the coherent optical orthogonal frequency-division-multiplexed (COOFDM) system, a channel model is developed that includes linear fibre dispersion effects, noise from optical amplifiers, and inter-carrier interference generated by laser phase noise. As a result, for such a system, an accurate channel estimate is essential. Based on this concept, derivation of channel estimation and phase estimation for the system of CO-OFDM. The proposed method is tested and evaluated using MATLAB software. Computer simulation results for several standard methods such as extreme learning machines (ELM) and artificial neural networks (ANN) validate the feasibility of the suggested methodology. The CO-OFDM system’s transmission experiments and computer simulations prove that the support vector machine-based model following pilot-assisted phase estimation gives the optimal performance. Therefore, results depicted that the channel estimation utilizing the SVR model gives good performance than the other methods, thus the proposed model gives an accurate CE process, respectively.
Intelligent UAV path planning framework using artificial neural network and artificial potential field Meena Thangaraj; Ravi Sankar Sangam
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp1192-1200

Abstract

Unmanned aerial vehicles (UAVs) are utilized extensively in various fields of daily activities in the day to day life and industrial applications. The raises of utilization of UAVs guide the researchers to concentrate on various problems like handling rich and large-scale information and uninterrupted communication. Further, to achieve the above the obstacle free zone is mandatory and the present autonomous drones may fail to handle such situations. To address the mentioned issues, an effective path planning algorithm is needed, to find the optimal path and obstacle free mobility. Hence, UAV path planning needs intelligent and autonomous navigation system by providing high level of optimization in order to attain optimal path with the obstacles avoidance. In this paper, AI employed framework for UAV path planning is proposed by utilizing the salient features of both artificial neural network (ANN) and artificial potential field (APF). ANN is implemented for obtaining optimal path and APF is utilized for evading the obstacles throughout the path. Further, the implementation results show the better performance than the existing works in terms of the collision free optimal path for UAVs.
Earthquake prediction in Iraq using machine learning techniques Nada Badr Jarah; Kadhim Mahdi Hashim; Abbas Hanon Hassin
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp322-329

Abstract

This study deals with addressing the scientific achievements and the history of earthquake prediction in Iraq, in addition to attempting to discuss the possibility of machine learning to predict earthquakes from a theoretical perspective. The idea of predicting earthquakes gives at least a little time to protect people and reduce earthquake damage. In Iraq, we notice an increase in the occurrence of earthquakes, especially in the southern regions, where they form a strange phenomenon because they are plain areas and far from the seismic fault line, due to the errors that accompany excessive oil extraction and in random and unstudied ways, and geological studies raise fears in predicting an increase in earthquakes for the coming years. We have explored the possibility of applying machine learning technology to predict earthquakes in Iraq, and follow-up recording of tremors at different stations in Iraq through three centers of seismic sensor networks. In addition to the earthquake catalog in Iraq (1900-2019). This study may pave the way for more research to develop an integrated and accurate earthquake prediction system using machine-learning technologies.
Experimental investigation of hybrid thermoelectric evaporative air-cooling system for crickets rearing process Peeradapath Parametpisit; Piyapat Panmuang; Amornthep Sonsilphong; Chaiyong Soemphol
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1374-1381

Abstract

Due to the effects of the change in temperature that have resulted in dramatic changes in the livelihoods of crickets. Hence, the implementation of cooling technologies is an important factor for alleviating these negative consequences. This research presents the experimentally investigate the feasibility of employing a thermoelectric cooler in combination with an evaporative air-cooling system for two-spotted cricket (Gryllus bimaculatus) rearing process. The proposed cooling system has been installed to reduce the temperature that appropriate for the cricket rearing. The experimental results show that the product air temperature of cricket rearing pens with thermoelectric evaporative air-cooling system decreases form ambient air. The average temperature of the cricket rearing pens with thermoelectric evaporative air-cooling system is 29.66 °C, with the highest temperature at 31.40 °C. While the average temperature of the cricket rearing pens without thermoelectric evaporative air-cooling system is 33.75 °C, with the highest temperature at 37.10 °C. Furthermore, this research also shows that this proposed system can improve cricket survival rate. The crickets that reared in the prototype system have a survival rate of 88.5%, while survival rate of crickets in an uncontrolled pen is 67.2%. This paper provides a potential of applying thermoelectric evaporative air-cooling for cricket farming.

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