2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)最新文献

SLAM Algorithm for Omni-Directional Robots based on ANN and EKF 基于神经网络和EKF的全向机器人SLAM算法

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185708

Ahmad M. Derbas, T. Tutunji

引用次数: 0

Dynamical Modeling and Control of Motion System of the Gantry Crane to Minimize Swing Angle of the Payload 最小载荷摆角龙门起重机运动系统动力学建模与控制

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185684

Jihad S. Radaideh, Musa K. AlAjlouni

引用次数: 0

Impact of Grid-Connected Photovoltaic Systems on Low Voltage Distribution Network 光伏并网系统对低压配电网的影响

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185797

Dareen Habash, Ahmad Azzam, Reda Issa, Emad Abdelsalam, H. Qandil

{"title":"Impact of Grid-Connected Photovoltaic Systems on Low Voltage Distribution Network","authors":"Dareen Habash, Ahmad Azzam, Reda Issa, Emad Abdelsalam, H. Qandil","doi":"10.1109/JEEIT58638.2023.10185797","DOIUrl":"https://doi.org/10.1109/JEEIT58638.2023.10185797","url":null,"abstract":"This work presents and analyzes the penetration impact of grid-connected photovoltaic systems on the voltage, power factor, and current harmonics of low-voltage distribution feeders. A typical low-voltage distribution feeder is simulated with installed solar photovoltaics. The electrical parameters data of the feeder are obtained from the Jordanian Electric Power Company, responsible for distributing electrical energy to nearly 66% of the total consumers in Jordan. The analysis was carried out via power system analysis software on a distributed system model using recorded data for consumer load and photovoltaic system generation. The simulation was focused on the change in the levels of voltage, current harmonics, and power factor on the feeder related to integrating photovoltaic panels into the distribution system. Results showed that the integration of solar photovoltaic panels reduces the power factor and increases the current harmonics of the low-voltage distribution feeder. Although some minor overvoltage problems can be expected, particularly in urban areas, in most cases, the overvoltage did not go above the statutory limit of 1.1 p.u.","PeriodicalId":177556,"journal":{"name":"2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126212197","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

Explainable machine learning-based cybersecurity detection using LIME and Secml 使用LIME和Secml进行可解释的基于机器学习的网络安全检测

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185893

Sawsan Alodibat, Ashraf Ahmad, Mohammad Azzeh

{"title":"Explainable machine learning-based cybersecurity detection using LIME and Secml","authors":"Sawsan Alodibat, Ashraf Ahmad, Mohammad Azzeh","doi":"10.1109/JEEIT58638.2023.10185893","DOIUrl":"https://doi.org/10.1109/JEEIT58638.2023.10185893","url":null,"abstract":"The field of Explainable Artificial Intelligence (XAI) has gained significant momentum in recent years. This discipline is focused on developing novel approaches to explain and interpret the functioning of machine learning algorithms. As machine learning techniques increasingly adopt “black box” methods, there is growing confusion about how these algorithms work and make decisions. This uncertainty has made it challenging to implement machine learning in sensitive and critical fields. To address this issue, research in machine learning interpretability has become crucial. One particular area that requires attention is the detection process and classification of malware. Handling and preparing data for malware detection poses significant difficulties for machine learning algorithms. Thus, explainability is a critical requirement in current research. Our research leverages XAI, a novel design of explainable artificial intelligence that uses cybersecurity data to gain knowledge about the composition of malware from the Microsoft large benchmark dataset-Microsoft Malware Classification Challenge (BIG 2015). We use the LIME explainability technique and the Secml python library to develop explainable prediction results about the class of malware. We achieved 94% accuracy using Decision Tree classifier.","PeriodicalId":177556,"journal":{"name":"2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)","volume":"79 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131105431","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

Applying Smart Contract in Blockchain Technology to Manage the Ticketing Issuance and Ticketing Traceability 应用区块链技术中的智能合约管理票务发行和票务可追溯性

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185771

H. Nguyen, H. Nguyen, Thi-Thiet Pham

{"title":"Applying Smart Contract in Blockchain Technology to Manage the Ticketing Issuance and Ticketing Traceability","authors":"H. Nguyen, H. Nguyen, Thi-Thiet Pham","doi":"10.1109/JEEIT58638.2023.10185771","DOIUrl":"https://doi.org/10.1109/JEEIT58638.2023.10185771","url":null,"abstract":"Every year, the Industrial University of Ho Chi Minh City presents a cultural program in conjunction with the start of the academic year. Students from the school are given free tickets to attend this event. However, there has been an occurrence problem with fake tickets or ticket sales appearing throughout the years. To assure the validity of the ticket issued, we suggest a ticketing issuance and ticketing traceability management system by applying smart contract technology on the blockchain platform to store, manage, and trace the origin of tickets. The system is designed on the Ethereum platform to implement smart contracts and blockchain technologies using the Solidity language. A blockchain is a decentralized database that holds data in encrypted chunks that grow over time. These information blocks function independently. The benefit of block chain is that it offers great security by preventing information theft and manipulation. To evaluate the performance of the suggested system, it was carried out with real student data at the Faculty of Information Technology at the Industrial University of Ho Chi Minh City. The experimental results show that the proposed system carries out all functions well.","PeriodicalId":177556,"journal":{"name":"2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132259692","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

Study of Power Factor Corrector Operating at Multiple Switching Frequencies 多开关频率下功率因数校正器的研究

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185763

D. Stepins, J. Zakis, A. Subbarao, A. Suzdaļenko, J. Zarembo, K. Khandakji

引用次数: 0

Features Selection for Force Myography Based Hand Gesture Recognition 基于力肌图的手势识别特征选择

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185697

Malak Fora, Manar Jaradat, B. B. Atitallah, Congyu Wu, O. Kanoun

{"title":"Features Selection for Force Myography Based Hand Gesture Recognition","authors":"Malak Fora, Manar Jaradat, B. B. Atitallah, Congyu Wu, O. Kanoun","doi":"10.1109/JEEIT58638.2023.10185697","DOIUrl":"https://doi.org/10.1109/JEEIT58638.2023.10185697","url":null,"abstract":"Hand gesture recognition has a wide range of applications in robotics, game control, and in communication with the deaf and people with trouble hearing. Recognition of American sign language (ASL) hand gestures has been extensively studied in the literature. Multiple data sources and different features extracted from these data were used to classify ASL gestures. In this study, we examined the features used in previous research to determine the minimum number of features that can give an accurate classification of ASL hand gestures. Force myography (FMG) signals captured for ASL gestures of digits 0–9 were used in this analysis of the selected features. Extracted features from the raw FMG signals were applied to K-nearest neighbors (KNN) and Extreme Learning Machine (ELM) to evaluate their efficiency in identifying the corresponding hand gesture. Results show that using only the mean value as input to classification algorithms yields the highest classification accuracy. The classification accuracy was 90% and 96.9% for KNN and ELM, respectively.","PeriodicalId":177556,"journal":{"name":"2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129265287","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

Sentiment Analysis of Tweets: A Machine Learning Approach 推文情感分析:一种机器学习方法

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185898

Ammar S. Badarneh, Suhaib Al-Darwesh, Omar A. Alzubi, Wael Qassas, Mohammad ElBasheer

{"title":"Sentiment Analysis of Tweets: A Machine Learning Approach","authors":"Ammar S. Badarneh, Suhaib Al-Darwesh, Omar A. Alzubi, Wael Qassas, Mohammad ElBasheer","doi":"10.1109/JEEIT58638.2023.10185898","DOIUrl":"https://doi.org/10.1109/JEEIT58638.2023.10185898","url":null,"abstract":"The growth and advancement in social network platforms increase the number of users noticeably. Social network platforms, like Twitter, grant users the ability to interact and express their emotions about events. Since Twitter platform involves all ages with a fair representation of gender, the sentiment analysis of Twitter data reflects the general feelings of people about a particular event. The sentiment analysis is a natural language processing (NLP) method that mainly focuses on deciding whether the sentiment is positive, negative, or neutral. Additionally, it is referred to as material polarity or mining of opinions. In the context of sentiment analysis, various approaches can be applied such as the Lexicon and machine learning (ML) approaches. Compared with lexicon approach, ML approach is considered simple and more efficient. In this study aims at Performing sentiment analysis of Twitter data related to COVID19 using the ML approach. Four ML models are used in this study namely, linear support vector classification (Linear SVC), logistic regression (LR), decision tree (DT), and random forest (RF). The performance of the above-mentioned models is tested using various metrics such as accuracy, recall, precision, and F1 score. The results released that the Linear SVC model has superior performance among the other models.","PeriodicalId":177556,"journal":{"name":"2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121495667","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 Photovoltaic Forecasting Using ANN Network for Central and Southern Regions of Jordan 利用人工神经网络对约旦中南部地区的太阳能光伏预测

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185900

Rafi Al-Rawashdeh, Mohammad Alsarayreh, Abdallah Al-Odienat

{"title":"Solar Photovoltaic Forecasting Using ANN Network for Central and Southern Regions of Jordan","authors":"Rafi Al-Rawashdeh, Mohammad Alsarayreh, Abdallah Al-Odienat","doi":"10.1109/JEEIT58638.2023.10185900","DOIUrl":"https://doi.org/10.1109/JEEIT58638.2023.10185900","url":null,"abstract":"The use of renewable energy has increased during the last several decades. The most popular renewable energy source is photovoltaic (PV) technology, which uses solar radiation to create electricity. However, a number of variables, such as position, weather, etc., have an impact on the production of PV electricity. It is crucial to control the inherent changeability of PV plants as they expand and contribute significantly to the production of grid power. Predicting solar PV is therefore essential for ensuring efficient and dependable grid functioning. The forecasting model's inputs were historic PV power output data from two solar power installations in Jordan's central and southern regions. The prediction of PV power production in this research takes into account a stacked long short-term memory network (LSTM), a crucial part of the deep recurrent neural network. This model and Nonlinear Autoregressive NARX have been contrasted (Dynamic Neural Network). The outcomes demonstrated equivalent, admirable performance for both the dynamic NARX ANN and the LSTM, with NARX being better. The dynamic ANN can be claimed to be superior to the deep neural network (DNN) for time-based performance modeling of PV systems with varying data.","PeriodicalId":177556,"journal":{"name":"2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134080874","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

Single-Axis Solar Tracker System for Maintaining Southward Orientation of Solar Cells in Solar Cars 保持太阳能汽车太阳能电池向南方向的单轴跟踪系统

2023 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT) Pub Date : 2023-05-22 DOI: 10.1109/JEEIT58638.2023.10185858

Z. Almajali, Sana A. Aldmour

引用次数: 1