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9th International electrical engineering Congress, iEECON 2021

作者： Thunyakaset, N. Ratanacharoen, S. Namsang, A. Lerdwanittip, R. Chomtong, P. Akkaraekthalin, P. Civil Aviation Training Center Aeronautical Engineering Division Thailand Faculty of Technical Education Department of Teacher Training in Electrical Engineering Bangkok Thailand King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok Thailand

ISBN: (纸本)9781728195841

A design of S-band planar monopole antenna suited for CubeSat communication system is presented. The antenna design uses two-layer printed circuit board based on the patch antenna. The patch is cut at the corners to make the surface currents circularly flow and is designed to have a maximum gain suitable for CubeSat configuration. The patch antenna is also designed by using CST software, which simulation results shows that the antenna provides great impedance matching in the S-band at 2.36-2.48 GHz, a bandwidth of 120 MHz, and a directional radiation pattern with maximum gain of 8.17 dBi. © 2021 IEEE.

关键词： Microstrip antennas

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Speed Profile Optimization for Autonomous Electric Bus in Urban Area: Based on Service Route Parameter in Thailand

Speed Profile Optimization for Autonomous Electric Bus in Ur...

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Conference on Power, Energy and Innovations (ICPEI)

作者： Guntinan Sakulphaisan Sirirat Son-In Nitikorn Junhuathon Theerapol Muankhaw Industrial technology and innovation management Faculty of science and technology Pathumwan institute of technology Bangkok Thailand Electrical Engineering and Automation Control Systems Faculty of engineering and industrial technology Bansomdejchaopraya Rajabhat University Bangkok Thailand Department of Electrical Engineering Faculty of Engineering Rajamangala University of Technology Thanyaburi Pathumthani Thailand

This study conducts a comprehensive analysis of optimizing the speed profile of an AE-bus, a critical step in enhancing its operational efficiency. It encompasses three distinct case studies, each targeting specific objectives. The first case emphasizes energy consumption reduction, contributing to overall resource efficiency. The second focuses on eco-conscious speed profiles within predefined travel durations, balancing environmental sustainability and timeliness. The third case prioritizes travel time minimization for streamlined efficiency. Detailed insights into speed adjustments, bus positions, and energy consumption patterns are provided for each case. The findings reveal tailored approaches for energy conservation, speed, and travel time optimization. Additionally, emissions analysis demonstrates that electric buses significantly reduce CO 2 emissions compared to conventional NGV buses, showcasing their potential for environmental benefits.

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Stereotype-Based QOS Awareness for Learning to Use Multimedia in Rural Networks

Stereotype-Based QOS Awareness for Learning to Use Multimedi...

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International Conference on Wireless and Telematics (ICWT)

作者： Adi Sucipto Jupriyadi Arief Budiman Syaiful Ahdan Eki Ahmad Zaki Hamidi Faculty of Engineering & Computer Science Universitas Teknokrat Indonesia Lampung Indonesia Department of Electrical Engineering UIN Sunan Gunung Djati Bandung Indonesia

The use of technology in supporting the education sector can improve the quality of education and human resources. The dissemination of learning content and the use of video conferencing technology in the distance learning process via the network will automatically make the learning process run well. A significant amount of network resources, such as a solid infrastructure and available bandwidth, are required to provide multimedia communication-based services. Most of Indonesia is rural, there are some constraints on network infrastructure in rural areas. Limited resources, difficult access, and high costs to access are the main problems for sending content. In this research, research is conducted on how to build rural network infrastructure, and how to deliver multimedia-based learning content. The results from this study can also be applied anywhere, not just in rural networks. On networks with constrained bandwidth, this is accomplished by paying attention to Quality of Service (QoS), which involves minimizing delays and lost packets. In this study, multimedia streams are categorized and resource allocation in a network with a limited capacity is done using a stereotype-based model. After testing, the test bed shows that using the recommended method on a network with limited bandwidth produces better results than not using the mechanism, as well as from previous studies. The video delay time can be reduced by 8-59%, and the audio delay time can be reduced by around 32-653%. Loss of audio and video packets is decreased by 0-0.05% and 0-0.06%, respectively. Although delays and lost packages are tolerable, but Vanet, medical and other technologies are very concerned about this.

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Design, techno-economic evaluation, and experimental testing of grid connected rooftop solar photovoltaic systems for commercial buildings

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Frontiers in Energy Research 2024年 12卷

作者： Habib, Salman Tamoor, Muhammad Gulzar, Muhammad Majid Chauhdary, Sohaib Tahir Ahmad, Hasnain Alqahtani, Mohammed Khalid, Muhammad Control and Instrumentation Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical Engineering and Technology Government College University Faisalabad Faisalabad Pakistan King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical and Computer Engineering College of Engineering Dhofar University Salalah Oman Department of Electrical Engineering Pakistan Institute of Engineering and Applied Sciences PIEAS Islamabad Pakistan Department of Industrial Engineering and Center for Engineering and Technology Innovations King Khalid University Abha Saudi Arabia Dhahran Saudi Arabia

This study aims to investigate the potential of rooftop solar photovoltaic systems for commercial buildings. Helio-Scope software is utilized to perform simulations to determine the ideal rooftop area for photovoltaic panels. The efficiency of photovoltaic systems is impacted by the shading effects of photovoltaic modules installed in parallel rows. To enhance energy output, the optimal distance between rows is determined, and it is found that 5-feet inter-row spacing provides the best results. The simulation results indicate that with 5-feet inter-row spacing, photovoltaic system has an energy generation of 371.6 MWh, specific yield of 1508.0 kWh/kWp, performance ratio of 82.1%, solar access rate of 98.9%, total solar resource fraction of 96.3% and a total irradiance of 1655.9 kWh/m2. The annual nameplate energy is 425.1 MWh, output energy at irradiance levels is 423.1 MWh, optimal DC output is 378.5 MWh, inverter output is 373.5 MWh, and total energy delivered to the national power grid is 371.6 MWh. The average daily DC inverter input power is 158881.5110 W and the average daily AC inverter output power is 152231.6311 W, showing an inverter efficiency of approximately 95.93%. Moreover, detailed testing of the installed PV system is performed on-site to make sure that equipment’s performance guarantees are achieved, the system is properly installed and its configuration is suitable for commercial operations. The maximum daily output energy generation of an installed photovoltaic (PV) system is 1.33 MWh, and its average energy generation is 1.09 MWh. The voltage of all strings is within the rated range of the inverter, with a maximum voltage of 835 V and a minimum of 698 V, as tested by PV string open-circuit voltage. The inverter efficiency test is also performed, with a maximum efficiency of 98.83% and fill factors ranging from 81.37% to 82.34%. The payback period of a photovoltaic system is 4.22 years and LCOE is 0.0229$/kWh. PV system saved 215569.818 metric to

关键词： Solar power generation

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OPSD: an Offensive Persian Social media Dataset and its baseline evaluations

arXiv

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arXiv 2024年

作者： Safayani, Mehran Sartipi, Amir Ahmadi, Amir Hossein Jalali, Parniyan Mansouri, Amir Hossein Bisheh-Niasar, Mohammadamir Pourbahman, Zahra Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan84156-83111 Iran Faculty of Computer Engineering University of Isfahan Isfahan Iran Department of Industrial Engineering Sharif University of Technology Tehran Iran No. 350 Hafez Ave Tehran*** Iran

Warning This paper includes a sample of comments extracted from the dataset, some of which may contain offensive or obscene content. The proliferation of hate speech and offensive comments on social media has become increasingly prevalent due to user activities. Such comments can have detrimental effects on individuals’ psychological well-being and social behavior. While numerous datasets in the English language exist in this domain, few equivalent resources are available for Persian language. To address this gap, this paper introduces two offensive datasets. The first dataset comprises annotations provided by domain experts, while the second consists of a large collection of unlabeled data obtained through web crawling for unsupervised learning purposes. To ensure the quality of the former dataset, a meticulous three-stage labeling process was conducted, and kappa measures were computed to assess inter-annotator agreement. Furthermore, experiments were performed on the dataset using state-of-the-art language models, both with and without employing masked language modeling techniques, as well as machine learning algorithms, in order to establish the baselines for the dataset using contemporary cutting-edge approaches. The obtained F1-scores for the three-class and two-class versions of the dataset were 76.9% and 89.9% for XLM-RoBERTa, respectively. Copyright © 2024, The Authors. All rights reserved.

关键词： Large datasets

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Real-time Efficacy of Features Extraction using Machine Learning and Deep Learning for Frontal Alpha Asymmetry. 5

Real-time Efficacy of Features Extraction using Machine Lear...

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5th IEEE International Symposium in Robotics and Manufacturing Automation, ROMA 2022

作者： Hafeez, Yasir Ali, Syed Saad Azhar Amin, Hafeez Ullah Naqvi, Syed Faraz Adil, Syed Hasan Boon, Tang Tong University of Nottingham Malaysia School of Computer Science Faculty of Science and Engineering Semenyih43500 Malaysia Universiti Teknologi Petronas Centre for Intelligent Signal and Imaging Research Electrical and Electronics Engineering Department Perak Seri Iskandar32610 Malaysia University of Nottingham Malaysia Faculty of Science and Engineering School of Computer Science Semenyih43500 Malaysia Iqra University Software Engineering Department Karachi Pakistan

ISBN: (数字)9781665459327

ISBN: (纸本)9781665459327

The frontal alpha asymmetry represents as the neuromarker for stress. Stress is the psycho-physiological state of brain in response to some event or a demand. The continuous monitoring of mental stress is necessary to avoid chronic health issues. The real-time monitoring of frontal alpha asymmetry is necessary in daily life and to help in the therapy for example neurofeedback. In this paper, different approaches of machine learning and deep learning were adopted to extract the frontal alpha asymmetry features. The results analysis was based on the efficacy and the comparison of techniques for feature extraction has also been presented. © 2022 IEEE.

关键词： Feature extraction

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Kalman Filter for tracking a noisy cosinusoidal signal with constant amplitude

Kalman Filter for tracking a noisy cosinusoidal signal with ...

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International Conference on computer and Communication engineering, ICCCE

作者： Prima Wijaya Kusuma Mohamed Hadi Habaebi Galang P. N. Hakim Rachmat Muwardi Md. Rafiqul Islam Department of Electrical Engineering Faculty of Engineering Universitas Mercu Buana Jakarta Indonesia Department of Electrical and Computer Engineering Kulliyyah of Engineering (KOE) International Islamic University Malaysia (IIUM) Selangor Malaysia School of Optics and Photonics Beijing Institute of Technology Beijing China

This paper presents a Kalman filter based approach in order to solve the problem of tracking a noisy cosinusoidal signal with constant amplitude in the presence of noise. The objective is to estimate the state of the signal accurately, considering the inherent challenges posed by noise corruption. The Kalman filter is utilized as the core algorithm for state estimation, leveraging its ability to combine noisy measurements and a dynamic model to provide optimal estimates. The filter is initialized with zero states and covariance, and the state and covariance estimates are iteratively updated using time updates and measurement update equations. Through extensive simulations, the performance of the proposed Kalman filter-based algorithm is evaluated. The results demonstrate its effectiveness in accurately tracking cosinusoidal signals and mitigating the impact of noise. the Kalman Filter algorithm in this system produces low MSE at about 0.021 and MAE at about 0.111. The metrics results signify the algorithm’s ability to filter noise and estimate the actual state of the system, reflecting its robust tracking performance. The simulation results validate the effectiveness of the proposed approach and highlight its potential to enhance signal tracking accuracy in the presence of noise. Further research can explore the algorithm’s performance in various scenarios and investigate additional modifications to increase its robustness in challenging environments.

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Design & Business Modelling of An Innovative Energy Storage Unit combined with Supercapacitor & Capacitor Bank for MagLev Piezoelectric Wind Turbine 7

Design & Business Modelling of An Innovative Energy Storage ...

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7th International Conference on Electronics, Materials engineering and Nano-Technology, IEMENTech 2023

作者： Khan, Md Shahrukh Adnan Chew, Kristin Kabir, Md. Ashraful Islam, Muhammad Jahirul Aziz, Abid Vaithilingam, Chockalingam Aravind Khatun, Sufia Chua, Kein Huat Kamal, Ainun Uttara University Electrical & Electronic Engineering Dhaka Bangladesh Senior Custom Switchboard Estimator Schneider Electric Sydeny Australia Canadian University of Bangladesh Computer Science and Engineering Dhaka Bangladesh Matribhumi Real Estate Matribhumi Group Dhaka Bangladesh Uttara University Fintech Research Group Dhaka Bangladesh Taylor's University School of Engineering Subang Jaya Malaysia Canadian University of Bangladesh Electrical & Electronic Engineering Dhaka Bangladesh Universiti Tunku Abdul Rahman Faculty of Engineering and Sciene Kajang Malaysia Canadian University of Bangladesh Department of Business Administration Dhaka Bangladesh

ISBN: (纸本)9798350305517

This research provides a thorough description of the original research on developing, evaluating, and putting into practice an energy harvesting system that operates under ambient settings using a Charging bank combined of Supercapacitor, Capacitor and batteries adopted to piezoelectric transducer integrated Vertical Axis Wing Turbine. This research intends to investigate alternate energy-generating techniques in order to satisfy the rising need for power sources brought on by the quick development of electronic gadgets. The actual results of this study definitely show that using a capacitor bank significantly increases the output of piezoelectric transducers, leading to a noticeably more effective supercapacitor bank charging process. © 2023 IEEE.

关键词： Piezoelectricity

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Fast Simple Image Encryption Technique Based on Chaos Based System

Fast Simple Image Encryption Technique Based on Chaos Based ...

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Telecommunications Conference (ITC-Egypt), International

作者： Tamer O.Diab Wageda I.Al Sobky Salwa M. SeragEldin Ahmed Khairy Mahmoud Hany Nasry Zaky Mofreh A. Hogo Electrical Engineering Department Benha Faculty of Engineering Banha University Banha Egypt Basic Engineering Sciences Department Faculty of Engineering Banha University Banha Egypt Department of Computer Engineering College of Computers and Information Technology Taif University Department of Electronics and electrical communications Engineering Faculty of Engineering Tanta University Air Defense College Alexandria University Alexandria Egypt Department of Mathematics Military Technical College Egypt

In this paper, a novel image encryption technique based on chaotic maps is described. Encrypting an image with chaotic maps ensures that the safe cipher characteristics of confusion and diffusion are met. Moreover, chaos-based image cryptosystems have many features compared to the classical cryptographic techniques such as fast, effective security, minimum computing overheads, extremely sensitive to the control parameters and initial settings. These all features make effective encryption techniques with the best performance. Four chaotic maps are used in the proposed scheme to generate the encryption key, initial vector, and ciphering encryption S-Boxes. The maps used are the Chebyshev map, 1D improved quadratic map, 1D Improved Logistic Map and Altered Sine-Logistic based Tent map ASLT.

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When medical images meet generative adversarial network: recent development and research opportunities

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Discover Artificial Intelligence 2021年第1期1卷 1-20页

作者： Li, Xiang Jiang, Yuchen Rodriguez-Andina, Juan J. Luo, Hao Yin, Shen Kaynak, Okyay Department of Control Science and Engineering Harbin Institute of Technology Harbin150001 China Department of Electronic Technology University of Vigo Vigo36310 Spain Department of Mechanical and Industrial Engineering Faculty of Engineering Norwegian University of Science and Technology Trondheim7033 Norway Department of Electrical and Electronics Engineering Bogazici University Istanbul34342 Turkey

Deep learning techniques have promoted the rise of artificial intelligence (AI) and performed well in computer vision. Medical image analysis is an important application of deep learning, which is expected to greatly reduce the workload of doctors, contributing to more sustainable health systems. However, most current AI methods for medical image analysis are based on supervised learning, which requires a lot of annotated data. The number of medical images available is usually small and the acquisition of medical image annotations is an expensive process. Generative adversarial network (GAN), an unsupervised method that has become very popular in recent years, can simulate the distribution of real data and reconstruct approximate real data. GAN opens some exciting new ways for medical image generation, expanding the number of medical images available for deep learning methods. Generated data can solve the problem of insufficient data or imbalanced data categories. Adversarial training is another contribution of GAN to medical imaging that has been applied to many tasks, such as classification, segmentation, or detection. This paper investigates the research status of GAN in medical images and analyzes several GAN methods commonly applied in this area. The study addresses GAN application for both medical image synthesis and adversarial learning for other medical image tasks. The open challenges and future research directions are also discussed. © The Author(s) 2021.

关键词： Generative adversarial networks

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