Bulletin of Electrical Engineering and Informatics最新文献

Enhancing Arabic offensive language detection with BERT-BiGRU model 利用 BERT-BiGRU 模型加强阿拉伯语攻击性语言检测

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6530

Rajae Bensoltane, Taher Zaki

{"title":"Enhancing Arabic offensive language detection with BERT-BiGRU model","authors":"Rajae Bensoltane, Taher Zaki","doi":"10.11591/eei.v13i2.6530","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6530","url":null,"abstract":"With the advent of Web 2.0, various platforms and tools have been developed to allow internet users to express their opinions and thoughts on diverse topics and occurrences. Nevertheless, certain users misuse these platforms by sharing hateful and offensive speeches, which has a negative impact on the mental health of internet society. Thus, the detection of offensive language has become an active area of research in the field of natural language processing. Rapidly detecting offensive language on the internet and preventing it from spreading is of great practical significance in reducing cyberbullying and self-harm behaviors. Despite the crucial importance of this task, limited work has been done in this field for nonEnglish languages such as Arabic. Therefore, in this paper, we aim to improve the results of Arabic offensive language detection without the need for laborious preprocessing or feature engineering work. To achieve this, we combine the bidirectional encoder representations from transformers (BERT) model model with a bidirectional gated recurrent unit (BiGRU) layer to further enhance the extracted context and semantic features. The experiments were conducted on the Arabic dataset provided by the SemEval 2020 Task 12. The evaluation results show the effectiveness of our model compared to the baseline and related work models by achieving a macro F1- score of 93.16%.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A study on the solution of interval linear fractional programming problem 关于区间线性分数程序设计问题解决方案的研究

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5978

Yamini Murugan, Nirmala Thamaraiselvan

引用次数: 0

Harmonics mitigation technique for asymmetrical multilevel inverter fed by photovoltaic sources 光伏源馈电的非对称多电平逆变器谐波缓解技术

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6607

Ali Riyadh Ali, R. Antar, Abdul Ghani Abdulrazzaq Abdulghafoor

{"title":"Harmonics mitigation technique for asymmetrical multilevel inverter fed by photovoltaic sources","authors":"Ali Riyadh Ali, R. Antar, Abdul Ghani Abdulrazzaq Abdulghafoor","doi":"10.11591/eei.v13i2.6607","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6607","url":null,"abstract":"A multilevel inverter is an electrical device that converts a DC voltage into a higher AC voltage by generating a stepped waveform with several voltage levels. Unlike traditional inverters that produce a square wave or a pulse-width modulated (PWM) waveform with only two voltage levels, multilevel inverters can generate waveforms with three or more levels, resulting in reduced harmonic distortion, improved efficiency, and decreased electromagnetic interference. The design and control of multilevel inverters are active research areas that aim to enhance their performance, reliability, and scalability. In this research, a 31-level asymmetric cascaded multilevel inverter is suggested. The proposed multilevel inverter (MLI) system employs four photovoltaic cells as dc sources with structure of (1:2:4:8) Vdc. The system is modeled by MATLAB/Simulink and total harmonic distortion (THD) values of the output voltage and current are 1.106% for resistive load, and 1.35% and 0.403% for inductive load. These outcomes demonstrate the recommended circuit's efficacy and demonstrate its suitability for medium- and high-power applications.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design of passive voltage balancer system for lead acid battery 铅酸电池无源电压平衡器系统的设计

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5806

B. S. Aprillia, D. K. Silalahi, K. B. Adam, Putu Krishna Bhaskara Perteka Yuda

{"title":"Design of passive voltage balancer system for lead acid battery","authors":"B. S. Aprillia, D. K. Silalahi, K. B. Adam, Putu Krishna Bhaskara Perteka Yuda","doi":"10.11591/eei.v13i2.5806","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5806","url":null,"abstract":"The use of rechargeable batteries for electrical energy storage requires a voltage balancing system. The voltage balancing system requires monitoring in the use of rechargeable batteries so that they can be utilized properly and can improve the electrical energy storage system. In this research, a monitored lead acid battery voltage balancing system was designed so that the management of the battery voltage balance level and the storage of electrical energy in rechargeable batteries can be stored and used optimally. In this research a series of lead acid battery voltage detection and power dissipation circuits were designed. The power dissipation circuit uses the controlled shunt resistor method which is used when the voltage of the lead acid battery being charged exceeds the maximum voltage. This method is easy to implement and can display the value of the lead acid battery voltage and other parameters, so that it can be monitored by the user. The results obtained show that the average voltage error for batteries 1 and 2 is 0.09% and 0.3% respectively. The power dissipation circuit can dissipate lead acid battery power above the reference voltage VREF=±7 V, with a balanced voltage of 6.8 V at 140 minutes and 160 minutes.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Convolution neural network hyperparameter optimization using modified particle swarm optimization 利用改进的粒子群优化技术优化卷积神经网络超参数

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6112

Muhammad Munsarif, Muhammad Sam'an, Andrian Fahrezi

{"title":"Convolution neural network hyperparameter optimization using modified particle swarm optimization","authors":"Muhammad Munsarif, Muhammad Sam'an, Andrian Fahrezi","doi":"10.11591/eei.v13i2.6112","DOIUrl":"https://doi.org/10.11591/eei.v13i2.6112","url":null,"abstract":"Based on the literature review, a convolutional neural network (CNN) is one of the deep learning techniques most often used for classification problems, especially image classification. Various approaches have been proposed to improve accuracy performance. In CNN architecture, parameter determination is very influential on accuracy performance. Particle swarm optimization (PSO) is a type of metaheuristic algorithm widely used for hyperparameter optimization. PSO convergence is faster than genetic algorithm (GA) and attracts many researchers for further studies such as genetic algorithms and ant colony. In PSO, determining the value of the weight parameter is very influential on accuracy. Therefore, this paper proposes CNN hyperparameter optimization using modified PSO with linearly decreasing randomized weight. The experiments use the modified National Institute of Standards and Technology (MNIST) dataset. The accuracy of the proposed method is superior, and the execution time is slower to random search. In epoch 1, epoch 3, and epoch 5, the proposed method is superior to baseline CNN, linearly decreasing weight PSO (LDWPSO), and RL-based optimization algorithm (ROA). Meanwhile, the accuracy performance of the proposed method is superior to previous studies, namely LeNet-1, LeNet-2, LeNet-3, PCANet-2, RANDNet-2, CAE1, CAE-2, and bee colony. Otherwise, lost to PSO-CNN, distributed PSO (DPSO), recurrent CNN, and CNN-PSO. However, the four methods have a complex architecture and wasteful execution time.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The development and usability test of an automated fish counting system based on CNN and contrast limited histogram equalization 基于 CNN 和对比度受限直方图均衡化的自动鱼类计数系统的开发和可用性测试

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5840

Jing Mei Leong, Mohd Hanafi Ahmad Hijazi, A. Saudi, Chin Kim On, Ching Fui Fui, H. Haviluddin

{"title":"The development and usability test of an automated fish counting system based on CNN and contrast limited histogram equalization","authors":"Jing Mei Leong, Mohd Hanafi Ahmad Hijazi, A. Saudi, Chin Kim On, Ching Fui Fui, H. Haviluddin","doi":"10.11591/eei.v13i2.5840","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5840","url":null,"abstract":"The aquaculture industry has rapidly grown over the year. One pertinent aspect is the ability of the aquaculture farm management to accurately count the fish populations to provide effective feeding and the control of breeding density. The current practice of counting the fish manually increased the hatchery workers workload and led to inefficiency. The presented work proposed an intelligent, web-based fish counting system to assist hatchery workers in counting fish from images. The methodology consists of two phases. First, an intelligent fish counting engine is developed. The captured image was first enhanced using the contrast limited adaptive histogram equalization. A deep learning architecture in the form of you only look once (YOLO)v5 is used to generate a model to identify and count fish on the image. Second, a web-based application is developed to implement the developed fish counting engine. When applied to the test data, the developed engine recorded a precision of 98.7% and a recall of 65.5%. The system is also evaluated by hatchery workers in the University Malaysia Sabah fish hatchery. The results of the usability and functionality evaluations indicate that the system is acceptable, with some future work suggested based on the feedback received.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Solar power forecasting model as a renewable generation source on virtual power plants 作为虚拟发电厂可再生能源的太阳能发电预测模型

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5870

Suwarno Suwarno, Doni Pinayungan

{"title":"Solar power forecasting model as a renewable generation source on virtual power plants","authors":"Suwarno Suwarno, Doni Pinayungan","doi":"10.11591/eei.v13i2.5870","DOIUrl":"https://doi.org/10.11591/eei.v13i2.5870","url":null,"abstract":"This paper describes modeling solar power generation as a renewable energy generator by simulating the analytical approach mean absolute error and root mean square error (MAE and RMSE). This research estimates the error referring to long short-term memory (LSTM) network learning. Related to this, the Indonesian government is currently actively developing solar power plants without ignoring the surrounding environment. The integration of solar power sources without accurate power prediction can hinder the work of the grid and the use of new and renewable generation sources. To overcome this, virtual power plant modeling can be a solution to minimize prediction errors. This study proposes a method for on-site virtual solar power plant efficiency with a research approach using two models, namely RMSE and MAE to account for prediction uncertainty from additional information on power plants using virtual solar power plants. A prediction strategy verified against the output power of photovoltaic (PV) modules and a set based on data from meteorological stations used to simulate the virtual power plants (VPP) model. This forecast prediction refers to the LSTM network and provides forecast errors with other learning methods, where the approach simulated with 12.36% and 11.85% accuracy for MAE and RMSE, respectively.","PeriodicalId":37619,"journal":{"name":"Bulletin of Electrical Engineering and Informatics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140353815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An enhanced control scheme for multifunctional grid connected PV system using fuzzy and predictive direct power control 使用模糊和预测直接功率控制的多功能并网光伏系统增强型控制方案

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5660

B. Boukezata, A. Chaoui, J. Gaubert, O. Boutalbi

引用次数: 0

Performance evaluation of feature selections on some ML approaches for diagnosing the narcissistic personality disorder 对用于诊断自恋型人格障碍的一些多语言方法的特征选择进行性能评估

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.6717

H. Sulistiani, A. Syarif, K. Muludi, Warsito Warsito

引用次数: 0

The fog computing for internet of things: review, characteristics and challenges, and open issues 面向物联网的雾计算：回顾、特点和挑战以及开放性问题

Bulletin of Electrical Engineering and Informatics Pub Date : 2024-04-01 DOI: 10.11591/eei.v13i2.5555

Mahmood A. Al-Shareeda, A. Alsadhan, Hamzah H. Qasim, S. Manickam

引用次数: 2