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8th International Conference on Information Technology, Information Systems and electrical engineering, ICITISEE 2024

作者： Darabkh, Khalid A. Al-Mistarihi, Mamoun F. Al-Maaitah, Mera Ismail School of Engineering The University of Jordan Computer Engineering Department Amman11942 Jordan Jordan University of Science and Technology Faculty of Engineering Electrical Engineering Department Irbid22110 Jordan

ISBN: (纸本)9798350368970

In this article, we propose a novel protocol that employs different technologies together, such as Software Defined Network (SDN) for the purpose of offering scalability, programmability, and global network information, and Fog computing for the reason of providing location services that meet V ANET standards. Additionally, we propose a novel cluster head selection algorithm for the purpose of enhancing the efficiency of the protocol by considering three different dimensions, namely, lifetime, average distance, and signal-to-interference noise ratio. The novelty of this proposed algorithm comes from reducing the number of control overheads, reducing long-distance communications, and reducing packet loss due to collisions and contentions inside each cluster, respectively. The proposed protocol has been assessed using N s3 simulator whereas its results are so promising and worth publishing. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Sizing electrolyzer capacity in conjunction with an off-grid photovoltaic system for the highest hydrogen production

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Energy Harvesting and Systems 2023年第2期10卷 331-348页

作者： Hassan, Qusay Abbas, Majid K Tabar, Vahid Sohrabi Tohidi, Sajjad Abdulrahman, Imad Saeed Salman, Hayder M. Department of Mechanical Engineering University of Diyala Baqubah Iraq Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran College of Technical Engineering Al-Farahidi University Baghdad Iraq Department of Computer Science Al-Turath University College Baghdad Iraq

The electrolysis of renewable energy to produce hydrogen has become a strategy for supporting a decarbonized economy. However, it is typically not cost-effective compared to conventional carbon-emitting methods. Due to the predicted intermediate of low-and zero-marginal-cost renewable energy sources, the ability of electrolysis to connect with electricity pricing offers a novel way to cost reduction. Moreover, renewables, particularly photovoltaics, have a deflationary effect on the value of the grid when they are deployed. This study investigates solar electrolysis configurations employing photovoltaic cells to feed a proton exchange membrane water electrolyzer for hydrogen production. Using experimental meteorological data at 1-min precision, the system has been evaluated in Baghdad, the capital of Iraq. Positioned at the yearly optimum tilt angle for the selected site, the solar array is rated at 12 kWp. Temperature effects on solar module energy loss are taken into account. Several electrolyzers with capacities ranging from 2 to 14 kW in terms of hydrogen production were examined to determine the efficacy and efficiency of renewable sources. MATLAB was utilized for the simulation procedure, with a 2021-2035 project lifespan in mind. The results suggest that a variety of potentially cost-competitive options exist for systems with market configurations that closely approximate wholesale renewable hydrogen. At 4313 h of operation per year, the planned photovoltaic array generated 18,892 kWh of energy. The achieved hydrogen production cost ranges between & amp;dollar;5.39/kg and & amp;dollar;3.23/kg, with an ideal electrolyzer capacity of 8 kW matching a 12 kWp photovoltaic array capable of producing 450 kg/year of hydrogen at a cost of & amp;dollar;3.23/kg. & amp;copy;2022 Walter de Gruyter GmbH, Berlin/Boston. © 2023 Walter de Gruyter GmbH. All rights reserved.

关键词： Electrolysis

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Biological age estimation from ECG using Artificial Intelligence approaches 2

Biological age estimation from ECG using Artificial Intellig...

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2nd Jordanian International Biomedical engineering Conference, JIBEC 2024

作者： Sleiman, Jana Daher, Mohamad Khalil, Mohamad Diab, Ahmad Kassem, Abdallah Lebanese University Computer and Communications Engineering Tripoli Lebanon Faculty of Science Faculty of Applied Sciences & Technology Dep. of Computer Science Dep. of Computer Science & Information Technology Tripoli Lebanon Lebanese University Electrical Engineering Tripoli Lebanon Lebanese International University Biomedical Engineering Beirut Lebanon Notre Dame University Faculty Of Engineering ECCE Dept. Zouk Mosbeh Lebanon

ISBN: (纸本)9798331539542

This paper explores the application of Artificial Intelligence (AI) techniques in healthcare, specifically focusing on electrocardiogram (ECG) data analysis and biological age estimation. The study begins with an overview of ECG as a diagnostic tool and discusses the integration of Deep Learning (DL) models, particularly Convolutional Neural Networks (CNNs), in healthcare for various applications. Previous studies reviewed in this context consistently identify CNNs as the superior model for ECG analysis and prediction tasks. The primary research investigates the use of Machine Learning (ML) algorithms to estimate biological age from ECG data, employing metrics such as Mean Absolute Error (MAE) and variance to evaluate model performance. Subsequently, DL models are implemented and compared, demonstrating superior accuracy in estimating the biological age of new patients. While both ML and DL approaches were initially explored, this paper primarily focuses on deep learning methodologies due to their demonstrated superiority in healthcare applications. The findings highlight the efficacy of deep learning over traditional ML methods, underscoring its potential for enhancing diagnostic accuracy and personalized patient care. For instance, the most accurate deep learning model, the Convolutional Neural Network (CNN), achieved a Mean Absolute Error (MAE) of 1.49 and an R2 score of 0.53, whereas the best-performing traditional ML model, Random Forest, achieved an MAE of 1.54 and an R2 score of 0.55. These results clearly indicate the advantage of deep learning models in capturing complex patterns in ECG data, leading to more precise and reliable estimations of biological age. © 2024 IEEE.

关键词： Convolutional neural networks

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Studying Physical Properties of Gas-To-Liquid Compared with Mineral Oil under Accelerated Thermal Aging 25

Studying Physical Properties of Gas-To-Liquid Compared with ...

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25th International Middle East Power System Conference, MEPCON 2024

作者： Badawi, Mohamed Ibrahim, Shimaa A. Mansour, Diaa-Eldin A. El-Faraskoury, Adel Ward, Sayed A. Benha University Faculty of Engineering at Shoubra Department of Electrical Engineering Egypt Egypt-Japan University of Science and Technology School of Electronics Communications and Computer Engineering Electrical Power Engineering Department Alexandria Egypt Tanta University Faculty of Engineering Electrical Power and Machines Engineering Department Tanta Egypt Egyptian Electricity Holding Company Extra High Voltage Research Centre Egypt Delta University for Science and Technology Faculty of Engineering Department of Electrical Engineering Egypt

ISBN: (纸本)9798350379648

Mineral oil (MO) has long been utilized in high-voltage power transformers, as a cooling and dielectric medium;because of it is availability as it is extracted from fossil oil. Recently, Gas-To-Liquid (GTL) has a significant increase in use due to its superior performance, its purity and chemical consistency over conventional mineral oils. This paper presents examination of the temperature effects on mineral (Diala S2) and gas to liquid (Diala S4) oil physical properties. Fresh oil and aged oil samples, of the two oil types, have been tested in this paper. Accelerated thermal aging test have been conducted in laboratory to simulate the heat stress experienced by transformers during operation. Three aged oil samples, of the two types of oil, have been prepared in laboratory (3, 6, and 10 days). Density and viscosity measurements were performed on these fresh and aged oil samples. The results concluded that during the initial years, chemical changes cause a minor drop in the density of the mineral oil. Conversely, GTL oil has superior qualities since it stays more stable over time. Over time, the density of both oils exhibits comparable stability, however GTL oil is favored over mineral oil due to its consistency and stability. Diala S4 and Diala S2 oils have higher viscosity, suggesting superior cooling performance before aging. However, Diala S2 dropped to 10.649 mm2/s after three years, indicating its long-term consequences. Diala S4 oil had higher flow efficiency, enhancing transformer cooling and insulating performance within thermal aging. This is due to GTL oil, derived from natural gas, has higher resistance to chemical deterioration, allowing it to sustain its viscosity stability over extended periods. These results emphasize the importance of choosing oils, especially GTL oil type based on their apparent and physical stability over time. © 2024 IEEE.

关键词： Viscosity

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Torque estimation for robotic joint with harmonic drive transmission based on system dynamic characteristics

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Journal of Systems engineering and Electronics 2022年第6期33卷 1320-1331页

作者： ZHU Minghong XIAO Shu YU Fei Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Intelligent Systems Science and Engineering Harbin Engineering UniversityHarbin 150001China College of Mathematical Sciences Harbin Engineering UniversityHarbin 150001China

In the applications of joint control and robot movement,the joint torque estimation has been treated as an effective technique and widely *** are made to analyze the kinematic and compliance model of the robot joint with harmonic drive to acquire high precision torque *** analyzing the structures of the harmonic drive and experiment apparatus,a scheme of the proposed joint torque estimation method based on both the dynamic characteristics and unscented Kalman filter(UKF)is designed and *** on research and scheme,torque estimation methods in view of only harmonic drive compliance model and compliance model with the Kalman filter are simulated as guidance and reference to promote the research on the torque estimation ***,a promoted torque estimation method depending on both harmonic drive compliance model and UKF is designed,and simulation results compared with the measurements of a commercial torque sensor,have verified the effectiveness of the proposed method.

关键词： harmonic drive torque estimation compliance model unscented Kalman filter(UKF)

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Improved Bounds on the Size of Permutation Codes Under Kendall τ-Metric

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IEEE Transactions on Information Theory 2025年第6期71卷 4156-4166页

作者： Parvaresh, Farzad Sobhani, Reza Abdollahi, Alireza Bagherian, Javad Jafari, Fatemeh Khatami, Maryam University of Isfahan Faculty of Engineering Department of Electrical Engineering Isfahan81746-73441 Iran School of Mathematics Tehran19395-5746 Iran University of Isfahan Faculty of Mathematics and Statistics Department of Applied Mathematics and Computer Science Isfahan81746-73441 Iran University of Isfahan Faculty of Mathematics and Statistics Department of Pure Mathematics Isfahan81746-73441 Iran

In order to overcome the challenges caused by flash memories and also to protect against errors related to reading information stored in DNA molecules in the shotgun sequencing method, the rank modulation method has been proposed. In the rank modulation framework, codewords are permutations. In this paper, we study the largest size P(n, d) of permutation codes of length n, i.e., subsets of the set Sn of all permutations on {1, . . . , n} with the minimum distance at least d ∈ {1, . . . ,(Formula presented)} under the Kendall τ-metric. By presenting an algorithm and two theorems, we improve the known lower and upper bounds for P(n,d) . In particular, we show that P(n,d)=4 for all n ≥ 6 and (Formula presented) (Formula presented) © 1963-2012 IEEE.

关键词： Flash memory

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Melinjo Chip Dryer Monitoring System Using Fuzzy Logic Method

Melinjo Chip Dryer Monitoring System Using Fuzzy Logic Metho...

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2023 International Conference on Networking, electrical engineering, computer science, and Technology, IConNECT 2023

作者： Pranita, Elka Sembiring, Jaka Persada Jayadi, Akhmad Putri, Novia Utami Jaenul, Ariep Fathurahman, Ananda M Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Lampung Indonesia Universitas Global Jakarta Faculty of Electrical Engineering Jawa Barat Indonesia

ISBN: (纸本)9798350331172

The monitoring system of the emping melinjo dryer is a system made to make it easier for melinjo emping craftsmen to monitor the drying rate of emping melinjo on the emping melinjo dryer based on temperature, humidity, weight, and drying status, in general monitoring is usually done through the human sense of touch only or on the Liquid Crystal Display screen display in the melinjo emping dryer box. With the real-time monitoring system of the melinjo emping dryer, the manual method is replaced with this system, this system is made in the form of an application called SMAPEM IoT, in this application there is Temperature, Humidity, Weight, and Drying Status Data and a graphic display. This system works by utilizing the thingspeak platform database as a storage place for value data sent by temperature, humidity, and weight sensors on the melinjo emping dryer, so that the monitoring system for this melinjo emping dryer can be accessed anywhere and anytime, provided that the device must be connected to an internet connection. The conclusion of the research conducted is that the results of testing on the melinjo emping dryer monitoring system that has been made work quite well with sensor reading errors between the Serial Monitor and the Thingspeak Platform Database, average temperature error of 0.43 Percent, average Humidity error of 1.43 Percent, and average Weight error of 3.15 Percent. © 2023 IEEE.

关键词： Liquid crystal displays

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A taxonomy of common engineering activities and competencies

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Australasian Journal of engineering Education 2023年第2期28卷 181-193页

作者： Crossin, Enda Richards, Jessica I. Dart, Sarah Naswall, Katharina Department of Electrical and Computer Engineering Faculty of Engineering University of Canterbury Christchurch New Zealand School of Psychology Speech and Hearing University of Canterbury Christchurch New Zealand Brisbane Australia Faculty of Science University of Canterbury Christchurch New Zealand

In this paper, we address the lack of a unified approach to understanding engineering practice by developing and presenting a taxonomy of common engineering activities. The taxonomy consists of 86 common engineering activities linked to 17 engineering competencies and the 11 International engineering Alliance graduate attributes. The list of activities was developed using a six-step process, including multiple systematic literature searches and surveying engineers. The taxonomy provides a critical foundation for better understanding what engineers do, particularly in the Australian and New Zealand context. The taxonomy has potential utility in both engineering practice research and engineering education curriculum reform. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Taxonomies

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A survey of artificial intelligence models for wireless capsule endoscopy videos for superior automatic diagnosis: problems and solutions

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Multimedia Tools and Applications 2025年 1-35页

作者： El-Gammal, Eman M. El-Shafai, Walid Taha, Taha E. El-Fishawy, Adel S. Abd El-Samie, Fathi E. Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Center of Advanced Software and Biomedical Clinical Engineering Consultations Faculty of Engineering Cairo University Giza Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia

Wireless Capsule Endoscopy (WCE) emerged as an innovative and patient-centric approach for non-invasive and painless examination of the gastrointestinal (GI) tract. It serves as a pivotal tool in helping medical practitioners in the early detection of anomalies within the intricate domain of the human GI tract. The automated identification of aberrations assumes paramount significance, contributing not only to temporal efficiency but also to timely diagnosis. Within the realm of academic literature, a plethora of Artificial Intelligence (AI) methodologies have been proposed to effectuate the automatic classification, segmentation, and synthesis of anomalies inherent in WCE images. This scholarly endeavor undertakes a comprehensive and meticulous survey, elucidating the spectrum of anomaly classification, summarization, and detection techniques harnessed for computer-Aided Diagnosis (CAD) in the context of WCE images. The survey begins by delineating the methodologies underpinning WCE image classification and video processing. Subsequently, an exhaustive evaluation of techniques for analyzing WCE images is furnished, accompanied by an in-depth exploration of pertinent surveys, in addition to a judicious assessment of their merits and demerits. Furthermore, this study undertakes a rigorous evaluation of prevailing datasets utilized to benchmark the efficacy of various WCE techniques. In summary, this survey serves as a vanguard, delineating promising avenues for future investigations in the realm of WCE image analysis models. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Endoscopy

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Performance Analysis of Real-Time Safety Vest and Helmet Detection Using Yolov8 18

Performance Analysis of Real-Time Safety Vest and Helmet Det...

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18th International Conference on Telecommunication Systems, Services, and Applications, TSSA 2024

作者： Saputra, Mochammad Agung Munastha, Ketut Abimanyu Mulyono, Tanto Trisno Fitriadi, Budi Setiawan, Asep Trisna Lestari, Nina Universitas Sangga Buana Faculty of Engineering Department of Electrical Engineering Bandung Indonesia Universitas Sangga Buana Bandung Indonesia Universitas Bandar Lampung Faculty of Computer Science Lampung Indonesia

ISBN: (纸本)9798331527686

Workplace safety is a critical priority in the industry, particularly in enforcing occupational health and safety (OHS) standards. This study introduces an innovative OHS compliance inspection system integrating access control with object recognition technology. The system captures images of workers using an ESP32Cam as the pre-processing step for safety helmet and vest detection. The ESP32 Cam captures the best image for detection at a maximum distance of 100 cm. The OpenCV library accesses these images, while the YOLOv8 library performs object recognition. The dataset includes 761 images for helmets and 314 images for vests, with the best results achieved using 100 training epochs of the pre-trained *** model. The system demonstrates a confidence level of 0.89 and an accuracy rate 0.75 in identifying safety helmets and vests. Recognition results are monitored in real-time via a web-based dashboard, with data stored in a database for further analysis. This study highlights the potential of integrating object recognition technology to enhance OHS compliance and workplace safety. © 2024 IEEE.

关键词： Inspection equipment

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