2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)最新文献_第2页

Characterization of Insulator Faults in the Dhofar Power Transmission Network 佐法尔输电网绝缘子故障特征分析

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193366

Mohammed Kashoob, Haitham Al-Habsi, Mohammed Al-Mahri, Salim Al-Zubaidi

{"title":"Characterization of Insulator Faults in the Dhofar Power Transmission Network","authors":"Mohammed Kashoob, Haitham Al-Habsi, Mohammed Al-Mahri, Salim Al-Zubaidi","doi":"10.1109/I2CACIS57635.2023.10193366","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193366","url":null,"abstract":"In power transmission systems, polymer composite insulators are widely used to provide electrical insulation. The safe operation of a power system relies heavily on the detection and replacement of defective insulators on power transmission lines. Most transmission line companies detect faulty insulators by measuring the voltage across them, performing thermal inspections or by examining insulator cracks. However, as transmission lines are long, identifying degraded insulators may be difficult. This paper examines reports of previous incidents that are related to insulator faults or flashovers in the Dhofar transmission network. This network is located in the southern part of the Sultanate of Oman. It extends to coastal areas, an industrial area, desert environment, and a mountainous terrain. Based on collected incident reports, it is evident that the majority of insulation faults are due to factors that are specific to the area where the transmission lines were installed. These factors include low atmospheric pressure, high humidity, salt deposits, temperature, wind, high levels of pollution and bird activity combined with insulator accelerated degradation. As part of this study, different areas and related factors are examined in order to be able to understand future insulator faults on the Dhofar transmission network.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116670840","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 Adaptive Decision Weighted Fusion-based Strategy in Multibiometric System for Face Recognition 基于自适应决策加权融合的多生物特征人脸识别策略

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193678

F. N. M. Ariff, H. Jaafar

{"title":"An Adaptive Decision Weighted Fusion-based Strategy in Multibiometric System for Face Recognition","authors":"F. N. M. Ariff, H. Jaafar","doi":"10.1109/I2CACIS57635.2023.10193678","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193678","url":null,"abstract":"Face recognition system has been foremost since the advent of computers as it involves low-cost installation, non-invasive equipment, and the ease of data collection process. However, the development of face recognition system is not straightforward due to the changes of facial expression, face feature and pose. These changes lead to the performance degradation. Therefore, a multibiometric system is explored and an adaptive decision weighted fusion-based strategy is proposed to tackle the poor performance of single biometric system. The proposed strategy is divided into two parts. In part one, the adaptive weighted is considered where the weighted value is determine based on distance metric of Euclidean Distance (ED). In part two, the decision of fusion process is employed to select the optimum weightage based on distance that obtained in part one. Two feature extractions which are Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been employed to investigate the effectiveness of proposed fusion technique in face identification process. In order to evaluate the effectiveness of the proposed strategy, the face image of benchmark database and collected database are used for the performance evaluations. The results show an adaptive decision weighted fusion-based strategy comes out as an outstanding fusion technique compared to other tested rules with the performances of 95.33% is achieved from the benchmark database and collected database, respectively.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116709177","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

Synchronization of Velocity and Position using PI, PID and DOB controllers 采用PI, PID和DOB控制器同步速度和位置

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193136

Amel Ramdedović, Sejla Dzakmic, Nađa Viteškić

引用次数: 0

Analysis of Free Fatty Acids (FFA) in Palm Oils Based on the Raman Spectra 棕榈油中游离脂肪酸(FFA)的拉曼光谱分析

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193495

Siti Nurshaheera Shaharuzzaman, F. H. Hashim, Mohd Shaiful Sajab, A. B. Huddin

{"title":"Analysis of Free Fatty Acids (FFA) in Palm Oils Based on the Raman Spectra","authors":"Siti Nurshaheera Shaharuzzaman, F. H. Hashim, Mohd Shaiful Sajab, A. B. Huddin","doi":"10.1109/I2CACIS57635.2023.10193495","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193495","url":null,"abstract":"Palm oil is a stable vegetable oil with various uses in both the food and non-food industries. The quality of edible palm oil is measured by its content of free fatty acids (FFA), which should be below 5% to be safely consumed and used, according to The Palm Oil Refiners Association of Malaysia (PORAM). Current titration methods require that the oil sample be dissolved in neutralized ethanol/diethyl, which is a long process that can damage the sample and cause delays and losses in the process. The focus of this study is to analyze the FFA in palm oils based on the Raman spectra of palm oil samples and oil palm fruitlets. Four samples of commercially available palm oils of different qualities, as well as 47 samples of oil palm fruitlets, were used in this study. The Raman spectra of all samples were collected via point scanning using a confocal microRaman imaging spectrometer with a 532 nm laser source. Manual spectrum pre-processing was performed with baseline correction and data filtering using Savitzky-Golay filters. Possible FFA peaks characteristics on the Raman spectrum were then identified through signal interpolation, signal deconvolution, and curve fitting. Statistical analysis was conducted on the extracted features to remove those with low statistical values, thus helping the machine learning algorithms to train the classifier models more efficiently. From this study, it was found that peaks at 1155 cm−1, 1525 cm−1, 1440 cm−1, and 1655 cm−1 from the Raman spectrum were highly correlated with the FFA levels of palm oils obtained through titration. The peak ratios of 1525 cm−1/1655 cm−1 and 1155 cm−1/1655cm−1 also showed a good and fast relationship for analyzing the FFA content of palm oil.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132768861","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

YOLOv5 Models Comparison of Under Extrusion Failure Detection in FDM 3D Printing FDM 3D打印中YOLOv5模型挤压下故障检测的比较

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193388

Muhammad Lut, Liwauddin Abd Latib, M. A. Ayob, Nurasyeera Rohaziat

{"title":"YOLOv5 Models Comparison of Under Extrusion Failure Detection in FDM 3D Printing","authors":"Muhammad Lut, Liwauddin Abd Latib, M. A. Ayob, Nurasyeera Rohaziat","doi":"10.1109/I2CACIS57635.2023.10193388","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193388","url":null,"abstract":"The fused deposited material (FDM) 3D printing technique has advanced to the point that it can now be utilised with a variety of materials. However, it still confronts challenges in quality control as flaws in the printed model frequently go undetected throughout the printing process. Consequently, time and materials easily go to waste. By employing an intelligent system that can detect faults throughout the printing process and pauses or halts the printing activity to apply corrective actions can prevent such issues. Hence, this paper presents a study on failure object detection of under extrusion in 3D printing by using YOLOv5 models of size n, s, m, l and xl with three different sets of data consisting of 600, 1200 and 2400 images. Simulation results showed that the YOLOv5 models were able to effectively detect under extrusion failures in 3D printing with varying accuracy based on the model size and data set. Based on the results, the YOLOv5xl model with a dataset of 2400 images achieved the highest detection accuracy among all models and datasets. These findings have potential implications for improving the reliability and efficiency of 3D printing process.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133828701","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

Robust Control of Interleaved Boost Converter for Open-Cathode PEM Fuel Cell Systems 开阴极PEM燃料电池系统交错升压变换器的鲁棒控制

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193075

J. Tan, R. R. Raja Ismail

引用次数: 0

Multi-stage Transfer Learning for Corn Leaf Disease Classification 玉米叶片病害分类的多阶段迁移学习

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193168

Cao Yong, Jonel R. Macalisang, Alexander A. Hernandez

引用次数: 0

Application of Machine Learning In Renewable Energy: A Bibliometric Analysis of a Decade 机器学习在可再生能源中的应用:十年文献计量学分析

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193231

S. Ajibade, D. D. C. Flores, Muhammad Ayaz, Y. Dodo, F. O. Areche, Anthonia O. Adediran, O. J. Oyebode, Johnry Dayupay

{"title":"Application of Machine Learning In Renewable Energy: A Bibliometric Analysis of a Decade","authors":"S. Ajibade, D. D. C. Flores, Muhammad Ayaz, Y. Dodo, F. O. Areche, Anthonia O. Adediran, O. J. Oyebode, Johnry Dayupay","doi":"10.1109/I2CACIS57635.2023.10193231","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193231","url":null,"abstract":"Machine learning studies in the field of renewable energy are analysed here (REML). So, from 2012 to 2021, we looked at the publication tendencies (PT) and bibliometric analysis (BA) of REML research that was indexed by Elsevier Scopus. Key insights into the research landscape, scientific discoveries, and technological advancement were revealed by BA, while PT highlighted REML’s important players, top cited papers, and financing organisations. In total, the PT discovered 1,218 works, 397 of which were conference papers and 106 were reviews. Because it spans the disciplines of science, technology, engineering, and mathematics, REML research is exhaustive, varied, and consequential. The most productive researchers, countries, and sponsors include Ravinesh C. Deo, the United States’ National Renewable Energy Laboratory, and China’s National Natural Science Foundation. Journal prestige and open access are valued by contributors, as seen by the success of Applied Energy and Energies. Productivity among REML’s key stakeholders is boosted by collaborations and research funding. Keyword co-occurrence analysis was used to categorise REML research into four broad topic areas: systems, technologies, tools/technologies, and socio-technical dynamics. According to the results, ML plays a crucial role in the prediction, operation, and optimisation of RET as well as the design and development of RE-related materials.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124271267","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 Hybrid Algorithm Based on Artificial Bee Colony and Artificial Rabbits Optimization for Solving Economic Dispatch Problem 一种基于人工蜂群和人工兔子优化的混合算法求解经济调度问题

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/I2CACIS57635.2023.10193351

W. Lee, Mohd Ruzaini Hashim

{"title":"A Hybrid Algorithm Based on Artificial Bee Colony and Artificial Rabbits Optimization for Solving Economic Dispatch Problem","authors":"W. Lee, Mohd Ruzaini Hashim","doi":"10.1109/I2CACIS57635.2023.10193351","DOIUrl":"https://doi.org/10.1109/I2CACIS57635.2023.10193351","url":null,"abstract":"The Artificial Bee Colony (ABC) algorithm has gained widespread attention and has been applied in various fields due to its ability to achieve excellent global optimization results and ease of implementation. Despite these advantages, the basic ABC algorithm has some drawbacks such as slow convergence, poor exploitation, and difficulty in finding the best solution among all feasible solutions in some cases. Hence, a hybrid optimization algorithm called Artificial Bee Rabbit Optimization (ABRO) is proposed in this paper. This algorithm synergizes the ABC algorithm and Artificial Rabbits Optimization (ARO) algorithm. The original ABC algorithm has a better exploration approach while the ARO algorithm has a better exploitation strategy when approaching the optimum value. The new hybrid algorithm integrates the good features of both standard optimization strategies, thus producing better possible solutions. Four types of benchmark functions are applied to test the performances of the proposed algorithm. Furthermore, the proposed algorithm is applied in the IEEE-26 bus system for tackling the economic dispatch problem. The results show that the ABRO algorithm outperforms the original ABC algorithm and ARO algorithm in all benchmark functions and successfully reduces the cost of the power generation for the IEEE- 26 bus system.","PeriodicalId":244595,"journal":{"name":"2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124975259","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

I2CACIS 2023 Cover Page I2CACIS 2023封面

2023 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) Pub Date : 2023-06-17 DOI: 10.1109/i2cacis57635.2023.10193382

引用次数: 0