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Bulletin of Electrical Engineering and Informatics
Published by Universitas Ahmad Dahlan
ISSN : -     EISSN : -     DOI : -
Core Subject : Engineering,
Electrical & Electronics Engineering
Bulletin of Electrical Engineering and Informatics (Buletin Teknik Elektro dan Informatika) ISSN: 2089-3191, e-ISSN: 2302-9285 is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world. The journal publishes original papers in the field of electrical, computer and informatics engineering.
Arjuna Subject : -
Articles 2,901 Documents
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Acceptance of augmented reality in video conference based learning during COVID-19 pandemic in higher education Sunardi Sunardi; Arief Ramadhan; Edi Abdurachman; Agung Trisetyarso; Muhammad Zarlis
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.4035

Abstract

Three years after the COVID-19 pandemic emerged, we have adapted to the new normal, especially in the education field. Learning with video conferences has become our daily activity, and learning tools have gotten more prominent attention to gain student engagement, especially in emergency remote teaching (ERT). Since the trends of metaverse campaigns by meta, augmented reality (AR) has increased recognition in education contexts. However, very little research about the acceptance of augmented reality in video conferences, especially among university students. This paper aims to measure acceptance of AR in video conferences to motivate and inspire students to gain benefits and get impactful technology in the learning process. The research gathered data from a survey of 170 university students (from 5 majors in the study program and 17 different demographic areas) using unified theory of acceptance of technology 2 (UTAUT2). The result reveals that variables significantly impact acceptance: performance expectancy, hedonic motivation, and habit. The least significant but still positive effects are effort expectancy, social influence, and facilitating conditions. The study will provide helpful information on AR technology in video conferences and help top-level management in the university that provides online/distance learning in the early diffusion stage for metaverse in education.
Reduction of false negatives in multi-class sentiment analysis Chris Aloysius; P. Tamil Selvan
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4682

Abstract

Sentiment analysis classifications are done as positive, negative, as well as neutral ones. The increased usage of social media and its effects on society call for a more thorough, fine-grained explanation than that. In this study, classification is done in five classes-strongly positive, weakly positive, neutral, weakly negative, and strongly negative-in a more precise manner. Instead of using the typical ways of measuring accuracy alone, a novel method to eliminate false negatives (FN) is focused together with a fine-grained categorization. A bigger risk in sentiment analysis is a false negative. FN classification occurs when the context's polarity is identified as True when it is actually false. A complex dataset is used in this research for the experimental study, and the entire dataset is separated into five classes. Each class's FN are assessed using the suggested methodology. Comparing the proposed strategy to other, it was found to achieve about 53% more reduction in FN cases than rule based models and better predictions than compared machine learning models.
Enhanced backstepping control for disturbances rejection in quadrotors Ali Saibi; Hadjira Belaidi; Razika Boushaki; Recham Zine Eddine; Amrouche Hafid
Bulletin of Electrical Engineering and Informatics Vol 11, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i6.3997

Abstract

This work studies the issue of quadrotor trajectory tracking control in presence of disturbances and model uncertainties. The paper starts by extracting the kinematics and dynamics models of the quadrotor. This results in the motion equations, which eventually serve as a blueprint for creating the suggested smart flight control scheme. Secondly, an enhanced backstepping controller (BSC) is developed and tested to keep the quadrotor tracking the desired trajectory both in steady state and in presence of disturbances. Finally, BSC beside two other controllers: sliding mode controller (SMC) and proportional derivative controller (PDC) are implemented in MATLAB/Simulink and the obtained results are compared and conclusions are extracted. Therefore, it is established that PDC is not robust to disturbances as noise will be amplified due to the derivative term. Whereas, although SMC is robust to parameter variations and disturbances; however, it is not continuous which may affect the actuators due to the increased gains which may saturate them. In contrast, BSC requires too many tuning parameters; however, it ensures Lyapunov Stability and does not depend on the system as it does not involve cancelling system nonlinearity. Moreover, BSC results are 1017 better than the results of the two other controllers.
Simulation of 3D-space vector modulation for neutral point clamped inverters Palanisamy Ramasamy; Ramkumar Ravindran; Neetu Gupta; Gunjan Sardana; Indumathi Sekar; Venugopala Aparna Marthanda; Selvakumar Kuppusamy
Bulletin of Electrical Engineering and Informatics Vol 12, No 2: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i2.4502

Abstract

This paper gives an idea to simulation of three-dimensional space vector modulation for neutral point clamped multilevel inverter. Three dimensional-space vector modulation (3D-SVM) algorithm is progressed method of two dimensional-space vector modulation (2D-SVM) algorithm; it leads to reduce the complexity in reference vector identification and switching time calculation, also it includes the various advantages of 2D-SVM like minimized total harmonic distortion, reduced EMI issues. A simple system for the assortment of switching state vectors to track the reference voltage vectors without using any redundant switching vectors. This proposed method tracks the reference vector by identifyinglsubcubes and prisms by using mathematicallconditions. Here the cost of the proposedltechnique is independentlof voltagellevels oflinverter. This paper realizes the accomplishment of 3D-SVM using a neutral point clamped inverter. The simulation results of the proposed method are verified using MATLAB/Simulink.
Relay node placement in wireless sensor network for manufacturing industry Safiee, Rabiatul Adawiyah; Apandi, Nur Ilyana Anwar; Muhammad, Nor Aishah; Sheng, Wan Wing; Sarijari, Mohd Adib
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.3978

Abstract

Relay nodes are necessary to maintain scalability and increase longevity as the number of manufacturing industrial sensors grows. In a fixed-budget circumstance, however, the cost of purchasing the bare minimum of relay nodes to connect the network may exceed the budget. Although it is hard to establish a network that connects all sensor nodes, in this case, a network with a high level of connection is still desirable. This paper proposes two metrics for determining the connectedness of a disconnected graph of sensor nodes and determining the optimum deployment method for relay nodes in a network with the highest connectedness while staying within a budget restriction. The metrics are the number of connected graph components and the size of the most significant connected graph component. Prim's algorithm and the approximation minimum spanning tree algorithm are applied to construct a disconnected graph and discover the best relay node placement to solve these two criteria. Compared to the other metrics, simulation findings suggest that prioritizing the most significant connected components in the disconnected graph can yield superior outcomes by deploying the fewest number of relay nodes while retaining the connectedness of the graph.
The impact of training data selection on the software defect prediction performance and data complexity Benyamin Langgu Sinaga; Sabrina Ahmad; Zuraida Abal Abas; Antasena Wahyu Anggarajati
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3698

Abstract

Directly learning a defect prediction model from cross-project datasets results in a model with poor performance. Hence, training data selection becomes a feasible solution to this problem. Limited comparative studies investigating the effect of training data selection on the prediction performance have presented contradictory results. Those studies also did not analyze why a training data selection method underperforms. This study aims to investigate the impact of training data selection on the defect prediction model and data complexity measures. The method is based on an empirical comparison between prediction performance and data complexity measure before and after selection. This study compared 13 training data selection methods on 61 projects using six classification algorithms and measured the data complexity using six complexity measures focusing on overlap class, noise level, and class imbalanced ratio. Experimental results indicate that the best method for each dataset varies depending on the dataset and classifiers. The training data selection most affects noise rate and class imbalance. We concluded that critically selecting the training data method could improve the performance of the prediction model. We recommend dealing with noise and unbalanced classes when designing training data methods.
Performance analysis of CMOS based analog circuit design with PVR variation Prajapati, Pankaj P.; Kshatriya, Anilkumar J.; Bharvad, Sureshbhai L.; Upadhyay, Abhay B.
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.4357

Abstract

Process, supply voltage, and temperature (PVT) are three important factors which contribute to performance variation of the complementary metal–oxide–semiconductor (CMOS) based analog circuits. In this paper, CMOS based analog circuit design with the PVT variation effects are explored. The effects of the PVT variation on the performance of CMOS based analog circuits are introduced. The optimization of CMOS based analog circuits such as differential amplifier (DA) and two-stage operational amplifier (op amp) circuits with PVT variations with different algorithms such as cockoo search (CS), particle swam optimization (PSO), hybrid CSPSO, and differential evaluation (DE) algorithms is presented. Each algorithm is implemented using the C programming language, interfaced with Ngspice circuit simulator, and tested on the Intel®core™ i5, 2.40 GHz processor with 8 GB internal RAM using the Ubuntu operating system (OS). The result shows PVT variation affects the performance of CMOS circuit.
Measurement and assessment of mobile network electromagnetic radiation pollution in Ramadi, Iraq Mohammad S. Zidan; Mohammed Qasim Taha; Linha Abdulhameed Yaseen; Namariq Dawood Hameed; Qais N. Abid
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3938

Abstract

The electromagnetic radiation produced by cellular towers in Ramadi city, west of Iraq, is measured and analyzed in this research. This contains basic nodes, hub repeaters, and feeders for transmitting the carrier throughout the entire Ramadi city as well as the surrounding areas. As a result, this research focused on this area to measure and assess energy to determine if it is safe for people or has over the danger threshold. The study region was split into fifty-five mobile phone tower locations. In general, electric field intensity levels surpass 1.7 V/m, which is dangerous and should be reduced. However, apart from a few sites (2, 3, 35, 36, 45, 51, and 53), the magnetic field intensity and radiation density are acceptable based on the findings. The energy severity criteria are based on LATNEX corporation's guidelines.
Deep learning-based methods for anomaly detection in video surveillance: a review Berroukham, Abdelhafid; Housni, Khalid; Lahraichi, Mohammed; Boulfrifi, Idir
Bulletin of Electrical Engineering and Informatics Vol 12, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i1.3944

Abstract

Detecting anomalous events in videos is one of the most popular computer vision topics. It is considered a challenging task in video analysis due to its definition, which is subjective or context-dependent. Various approaches have been proposed to address the anomaly detection problems. These approaches vary from hand-crafted to deep learning. Many researchers have gone into determining the best approach for effectively detecting anomalies in video streams while maintaining a low false alarm rate. The results proved that approaches based on deep learning offer very interesting results in this field. In this paper, we review a family of video anomaly detection approaches based on deep learning techniques, which are compared in terms of their algorithms and models. Moreover, we have grouped state-of-the-art methods into different categories based on the approach adopted to differentiate between normal and abnormal events, and the underlying assumptions. Furthermore, we also present publicly available datasets and evaluation metrics used in existing works. Finally, we provide a comparison and discussion on the results of various approaches according to different datasets. This paper can be a good starting point for such researchers to understand this field and review existing work related to this topic.
Optimal backstepping controller for controlling DC motor speed Layla H. Abood; Bashra Kadhim Oleiwi; Ekbal Hussain Ali
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.3940

Abstract

In this paper, squirrel search algorithm (SSA) is adapted to tune the optimal parameters of a backstepping controller for controlling speed in DC motor; Lyapunov stability theorem is applied to derive the control low to achieve system stability analysis. M-file and Simulink platform is used to simulate the response of the system, a comparison with conventional controllers is utilized, all gains are tuned using SSA method and integral time absolute error (ITAE) fitness function to test the efficient performance of the proposed controller also a comparison with other tuned different controllers is done. Transient response analysis is used to validating the proposed controller performance. The simulation results showed a stable response and efficint performance for the proposed controller when compared with the two conventional controllers used by 41.6% for PID controller and by 32% for PI controller in rise time while in settling time is superior by 36.97% for PID controller and by 41.82% for PI controlle these values led for achieving the desired speed in fast and stable response.

Page 159 of 291 | Total Record : 2901

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