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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 64 Documents
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Search results for , issue "Vol 26, No 2: May 2022" : 64 Documents clear
Design of proportional integral and derivative controller using particle swarm optimization technique for gimbal system Mohd Hafiez Ahmad; Khairuddin Osman; Sharatul Izah Samsudin
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp714-722

Abstract

This paper presents the development of an optimal proportional, integral and derivative (PID) controller for controlling camera gimbal on unmanned aerial systems (UAV). Three optimal controller improvements are obtained using the suggested particle swarm optimization (PSO) technique. The PSO algorithm is initially built and integrated with the PID controller to control the DC motor gimbal. Before comparing the performance of a DC motor with PSO-PID with a DC motor with Zeigler-Nichols controller, the impacts of iteration numbers are explored. Finally, bode analysis was conducted to validate the stability of the proposed PSO-PID controller. Simulation is conducted within the MATLAB environment to verify the system's performance in terms of settling time, steady-state error and overshoot. The simulation results show has a longer settling time (0.91656 sec) than the Ziegler-Nichols controller (0.14316 sec) but a shorter rising time (0.091686 sec) than the Ziegler-Nichols controller (0.00094 sec). Furthermore, the overshoot was lowered from 12.941% to 0.959% as a result. As a result, the suggested PSO-PID controller technique outperforms the Ziegler-Nichols controller in terms of overshoot and rise time. Further study will investigate the integration of other optimisation methodologies such as fuzzy logic for better performance.
Flow incorporated neural network based lightweight video compression architecture Sangeeta Sangeeta; Preeti Gulia; Nasib Singh Gill
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp939-946

Abstract

The sudden surge in the video transmission over internet motivated the exploration of more promising and potent video compression architectures. Though the frame prediction based hand designed techniques are performing well and widely used but the recent deep learning based researches in this domain provided further directions of pure deep learning based next generation codecs. As the bandwidth over the internet is varying, adaptive bit rate representation is more suitable for video quality adjustment in tune with bandwidth variation. The proposed architecture comprises of end to end trainable video compression network consisting of majorly three modules namely-motion extension network, flow autoencoder and frame autoencoder. Frame autoencoder generates the individual compressed frames, flow autoencoder is used for optical flow based motion compensation chore and next frame is predicted by the motion extension network. The network is designed and evaluated in incremental manner. The analysis of the outcomes demonstrates the promising performance of the network quantitatively and qualitatively. Moreover, the results reveal that inclusion of optical flow based motion compensation network to the MotionNet architecture has enhanced the performance.
Thermal model developed of high electron mobility transistor AlGaN-GaN Azzeddine Farti; Abdelkader Touhami
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp689-698

Abstract

The performance of AlGaN-GaN HEMTs is influenced by the self-heating phenomenon, which leads to the power dissipation that is related to the increase of the local temperature of the device. The study of this increasing of the temperature is executed under different parameters, namely, low field mobility, velocity saturation, thermal conductivity of the substrate. A thermal model is developed to study the effect of this phenomenon on the current-voltage characteristics. Among the techniques to minimize the increase in the local temperature, we based on the good choice of the substrate used in the transistor. To highlight this proposal model, we have made a comparable study between the substrates of silicon and sapphire. Our analytical results are in a good agreement with published experimental data.
An internet of things-based medication validity monitoring system Yasmin Makki Mohialden; Nadia Mahmood Hussien; Qabas Abdal Zahraa Jabbar; Mostafa Abduhgafoor Mohammed; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp932-938

Abstract

Medicine is critical to our everyday lives and to the well-being of individuals of all ages and backgrounds. With the beginning of the Corona pandemic and a rise in Corona virus infection cases, the use of medications to prevent and recover from infection has increased, as well as to treat illness consequences, has grown. The effectiveness of medicines is greatly influenced by the expiration date. In this paper, a system for pharmacy or medical store's information storage system was developed and enhanced by automatically monitoring the validity of medications on a periodic basis and sending expiry reports to medicine authorities through e-mail to warn them that a medicine is approaching expiration. The system was also enhanced with internet of thing (IoT) for fast and secure delivery of the medicine validity report.
Convolution neural network model for fundus photograph quality assessment Sinan S. Mohammed Sheet; Tian-Swee Tan; Muhammad Amir Bin As'ari; Wan Hazabbah Wan Hitam; Qi Zhe Ngoo; Joyce S.Y. Sia; Kelvin Ling Chia Hiik
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp915-923

Abstract

The excellent quality of color fundus photograph is crucial for the ophthalmologist to process the correct diagnosis and for convolutional neural network (CNN) models to optimize output classification. As a result of main causes as acquire devises efficiency and experience of a physician most fundus photographs can have uneven illuminance, blur, and bad contrast, in addition to micro-features of retinal diseases, which need to force their contrast. Fundus photograph quality assessment method is proposed to find out the perfect enhanced color fundus Technique in fundoscopy photographs-based CNN model. Five photograph quality measurements, in addition to five CNN metrics, were used as standard in this study. In this research innovative approach combining photograph quality measurement and CNN metrics analysis is proposed to find out the best enhance method that is set for the multiclass CNN model. The contrast enhancement techniques are evaluated using 267 color fundus photographs divided into three retina diseases cases were downloaded from the open-source database “FIGSHARE”. The study outcome showed that the presented system (single-CNN) can determine well the contrast enhancement method, as well as the low-quality fundus photograph then it can boost CNN metrics to achieve superior.
The main pillars of Agile consolidation in newly Agile teams in Agile software development Gahroee, Tayebe Mohamadi; Javdani Gandomani, Taghi; Aghaei, Mohammadreza Soltan
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1216-1226

Abstract

Many software companies and teams use Agile methods as their main development approach. These methods promise higher team productivity, faster product delivery, a more flexible development process, and greater customer satisfaction. Nevertheless, a review of the literature shows that adapting to these methods, known as Agile transition, is not as easy as expected. However, several frameworks and models have been proposed to facilitate the Agile transition process. The challenging issue after the transition to agility is the behavior of companies and teams after the Agile transition and how to maintain agility in the long run. Very little research has been done on this issue, which has largely expressed concern. The present study tries to explore the hidden aspects of the transition to agility and provide a solution for Agile consolidation in newly Agile software teams. In this regard, using the grounded theory approach, the basic theory of Agile consolidation in these teams has been presented. Preliminary findings of the study indicate important factors that play an important role in Agile consolidation. Identification of challenges, facilitators, organizational culture structure, and human roles in Agile consolidation is the most important initial findings of this study.
Improving the quality of service in wireless sensor networks using an enhanced routing genetic protocol for four objectives Mahmoud Moshref; Rizik Al-Sayyed; Saleh Al-Sharaeh
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1182-1196

Abstract

Multi-objective algorithms are used to achieve high performance for quality of service (QoS) in wireless sensor networks (WSNs) is an important field for researchers because these algorithms improve two or more conflicting objectives and present the best trade-off between the conflicting objectives to solve multi-objective problems (MOPs). Previous research proposed an algorithm that relies on non-dominated sorting genetic algorithm 3 (NSGA-III), namely enhanced non-dominated sorting genetic routing algorithm (ENSGRA). This algorithm is used to optimise three objectives, which include number of worked sensors, energy consuming and node covering area. The fourth objective, which is node load balancing, is added in the current research. Such an addition aims to improve node distribution around cluster heads and decrease network congestion, thus decreasing energy consumption and increasing network lifetime. The ENSGRA algorithm is compared with multi-objective multi-step particle swarm optimisation (MOMSPSO), non-dominated sorting genetic algorithm 2 (NSGA-II), and NSGA-III. The proposed algorithm ENSGRA exceed to MOMSPSO, NSGA-II, and NSGA-III in the proposed QoS model in the final outcomes, as the proposed approach achieved (38%) average combination (optimisation) percentage. Which is the highest percentage over other methods.
Medicine prediction based on doctor’s degree: a data mining approach Md Shohel Arman; Kaushik Sarker; Asif Khan Shakir; Shah Fahad Hossain; Afia Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1125-1134

Abstract

The effective use of information mining in profoundly unmistakable fields like e-business, promoting and retail has prompted its application in different enterprises. There is an absence of powerful investigation devices to find concealed connections and patterns in information. This examination paper expects to give a review of ebb and flow systems of learning revelation in databases utilizing information mining strategies that are being used in today’s therapeutic research especially in medicine prediction. Correlation, Chi-square and Euclidean distance feature selections are used to select features and showing the comparison of the result between K-Nearest neighbors, Naïve Bayes, decision tree, artificial neural network. The result uncovers that decision tree beats and sometime Bayesian grouping is having comparative precision as of choice tree. The analysis of performance can be done in such as doctor’s degrees may vary the diseases medicine.
Investigations on spectral efficiency of muticellnetworks using hybrid beamforming S. Deepa; J. Jeneetha Jebanazer; S. Rajakumar; J. Mercy Sheeba; J. Rryan
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp826-835

Abstract

Millimeter wave communication systems with antenna beamforming facilitates practical solutions to the capacity crunch issues in the upcoming 5G wireless networks. Multi-cell dense networks are prone to three major interferences-inter-cell, intra-cell and Inter layer interference-the most dominating being the inter-cell interference. This paper focuses to alleviate inter-cell interference using hybrid beamforming (HBF) approach, leveraging coordinated multipoint (CoMP) technique, thereby improving the SE of 5G networks. Simulation results show HBFpeforms in par with optimal weights, making it a suitable candidate for 5G networks. As the number of data streams is increased from Ns=1 to 4 for 0 dB signal to noise ratio (SNR) with Nt=64 and Nr=16, the SE increases from 9.5557 bits/s/Hz to 26.423 bits/s/Hz for optimal weights and from 9.1885 bits/s/Hz to 19.763 bits/s/Hz and hybrid weights, respectively. The second set of experiments are conducted to study the effect of number of transmit antennas on spectral efficiency (SE). The results show that as the number of transmit antennas is increased from Nt=16 to 64 for 0 dB SNR, with Nr=16 and Ns=4, the SE increases from 17.735 bits/s/Hz to 26.423 bits/s/Hz and 13.750 bits/s/Hz to 19.763 bits/s/Hz for optimal weights and hybrid weights, respectively.
Model based adaptive controller with grasshopper optimization algorithm for upper-limb rehabilitation robot Aliaa Adnan; Ekhlas H. Karam; Muaayed F. Al-Rawi
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp723-731

Abstract

Model based adaptive controllers (MBACs) are considered one of the most common adaptive controllers that are used with robotic systems due to their ensuring nonlinear robust scheme with global asymptotic stability for controlling nonlinear systems. However, this controller requires precise mathematical models of the controlled systems. In this paper, an optimal model-based adaptive controller (OMBAC) is suggested for controlling a two-link upper limb rehabilitation robot. This controller, in the presence of model uncertainties, can guarantee the robustness of the rehabilitation robot. Although the OMBAC is an adaptive and model-based controller, some of its parameters need to be determined precisely. In this paper, these parameters are determined by the grasshopper optimization algorithm (GOA). The Lyapunov method is used to analyze the stability assurance of controlled rehabilitation. The results of the simulation for two tested trajectories (linear and nonlinear trajectories) demonstrate the efficiency of the suggested OMBAC with fast settling time, minimum error steady state, and very small overshoot.

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