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Annual North-American Power Symposium

作者： Demy Alexander Sarangan Rajendran Nirasha Bataduvaarachchi Visvakumar Aravinthan Al Tamimi Electrical and Computer Engineering Wichita State University Wichita KS USA Transmission Planning & Policy Sunflower Electric Corporation Wichita KS USA

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

In a multi-area network Distributed Energy Resources(DERs) of one area can significantly impact the transmission line flows of other area. The change in transmission line flows over a longer period will lead to transmission revenue loss for a transmission owner. In this study the feasibility of battery energy storage system providing ancillary service to mitigate the line flow impacts of the non-DER area due to the DERs in a neighboring area is studied. Firstly, the line flow difference of the lines in a non-DER area for the DER and non-DER scenario is captured. The most significant lines of the non-DER area are identified based on the number of hours a line experiences a line flow difference exceeding a predefined threshold. Optimization is conducted to determine the additional battery capacity needed at each DER bus to limit the line flows of the identified significant lines. The results demonstrate that utilizing battery energy storage as ancillary services is an effective strategy for mitigating line flow impacts which in turn reduces the revenue loss for the transmission owner.

关键词： Power transmission lines Battery energy storage system Propagation losses Distributed power generation Batteries North America Optimization

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DER Impacts and Equity Considerations for Transmission Assets in a Multi Area Network

DER Impacts and Equity Considerations for Transmission Asset...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Demy Alexander Nirasha Bataduvaarachchi Arun Manoharan Aravinthan Visvakumar Al Tamimi Electrical and Computer engineering Wichita State University Wichita KS USA Transmission Planning & Policy Sunflower Electric Coorporation Wichita KS USA

Due to the rising trend in Distributed Energy Resource (DER) integration it is important to understand the impacts of DER in a multi area network. Transmission line utilization can be altered due to the DER penetration in adjacent areas. These impacts are not considered in traditional transmission planning studies. This paper investigates adjacent area DER impacts on transmission lines from a transmission owner perspective. In order to quantify the transmission line impacts a metric named Performance Index (PI) is developed. Due to the adjacent area DER penetration; over-utilization, under-utilization and no change in utilization of transmission lines were captured using this metric along with their probability of occurrence. The results showed that there can be significant impact on transmission lines in a non-DER area due to the adjacent area DERs. Economic analysis is carried out to capture the loss or benefit in line revenues due to the change in line utilization. The results from the economic analysis also showed that there can be significant impacts in line revenue recovery due to the adjacent area DERs.

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PAIR: Prompt-Aware margIn Ranking for Counselor Reflection Scoring in Motivational Interviewing

PAIR: Prompt-Aware margIn Ranking for Counselor Reflection S...

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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022

作者： Min, Do June Pérez-Rosas, Verónica Resnicow, Kenneth Mihalcea, Rada Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI United States School of Public Health University of Michigan Ann ArborMI United States

Reflections are a core verbal skill used by mental health counselors to express understanding and acknowledgement of the client's experience and concerns. In this paper, we propose a system for the automatic evaluation of counselor reflections. Specifically, our system takes as input one dialog turn containing a client prompt likely leading to a reflection and a counselor response to it, and outputs a numeric score indicating the quality of the reflection made by the counselor. We compile a dataset consisting of reflections portraying different levels of reflective listening skills, and propose Prompt-Aware margIn Ranking (PAIR), a novel framework for reflection scoring that contrasts positive and negative prompt and response pairs using adhoc multi-gap and prompt-aware margin ranking losses. Through empirical evaluations and deployment of our system in a real-life educational environment, we show that our scoring model outperforms several baselines on different metrics, and can be used to provide useful feedback to counseling trainees. © 2022 Association for Computational Linguistics.

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Wavelet and modified VGG-16 deep learning to identify COVID-19 based on X-ray images

Wavelet and modified VGG-16 deep learning to identify COVID-...

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2022 International Conference on Data Science and Intelligent Computing, ICDSIC 2022

作者： Kareem, Omar Sedqi Al-Sulaifanie, Ahmed Khorsheed University of Duhok Dept. of Electrical and Computer Engineering Kurdistan Region Duhok Iraq Duhok Polytechnic University Dept. of Public Health Kurdistan Region Duhok Iraq

ISBN: (纸本)9798350334883

COVID-19 is caused by the SARS coronavirus 2 family (SARS-CoV-2). A quick antibody or antigen test can detect the presence of COVID-19, but further testing is needed to confirm a positive result. Radiologists use chest X-rays to diagnose chest diseases early. The proposed system integrates discrete wavelet transformation and deep learning to help radiologists categorise conditions. Wavelets break down images into multiple spatial resolutions depending on a high pass and low pass frequency components and efficiently extract characteristics from lung X-rays. Here, we use a hybrid wavelet-CNN model to diagnose lung X-rays. The proposed CNN model is trained and verified on different source COVID 19 chest X-ray images for binary and three classes. The proposed studies suggest significant improvement in outcomes, with the best parameters achieving 99.42% accuracy and 96.43% accuracy for binary and three classes. The depiction of feature maps shows that our suggested network collected features from the corona virus-affected lung properly. Results suggest that the proposed model is successful enough for COVID 19 diagnosis. © 2022 IEEE.

关键词： COVID-19

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Smart Happy Device with IoT : For those who suffer anxiety, stress, and depression 12

Smart Happy Device with IoT : For those who suffer anxiety, ...

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12th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2024

作者： Yakub, Fitri Azizan, Azizul Dhamanti, Inge Khudzari, Ahmad Zahran Md. Govindan, Niranjana Muljono, Muljono UTM Malaysia-Japan International Institute of Technology Electronic System Engineering Department Kuala Lumpur Malaysia Universiti Teknologi Malaysia Cyberphysical Research Group Embedded AI & ML Science Lab Faculty of Artificial Intelligence Kuala Lumpur Malaysia Universitas Airlangga Faculty of Public Health Department of Health Policy and Administration Surabaya Indonesia UTM Faculty of Engineering Department of Biosciences & Medical Engineering Johor Bahru Malaysia SRMIST Faculty of Engineering & Technology Department of Computing Technologies Chennai India Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia

ISBN: (纸本)9798350340204

Due to the rising cases of Covid-19 in the world especially in Malaysia, the impact had been hit hard for many people. Due to this all people must be isolated in their home. It has affected the well-being and working life of millions of people across the world. Due to this disease, the mental health among people has increased significantly for the past 2 years. According to MoH, out of 983 Malaysian students, about 20.4%, 6.6%, and 2.8% are experienced minimal to moderate, marked to severe, and most extreme levels of anxiety, respectively. The main stressors are the remote online teaching, and uncertainty about the future regarding study and career which can affect mental health. Thus, the main objective of this project is to develop a product that may provide different medication methods to its users by helping people who suffer anxiety, stress, and depression. We used aromatherapy, positive quotes, and music therapy in order to release stress. The user can also check his or her pulse rate by only touching the fingerprint through the sensor. The microcontrollers used in this project are Arduino Uno and Arduino Mega to build the project circuit. The experimental results can improve body health, mind and spirit which enhances both physical and emotional health. © 2024 IEEE.

关键词： COVID-19

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Electrocoagulation-based AZO DYE (P4R) Removal Rate Prediction Model using Deep Learning

Electrocoagulation-based AZO DYE (P4R) Removal Rate Predicti...

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2023 International Symposium on Green Technologies and Applications, ISGTA 2023

作者： Akoulih, Meryem Tigani, Smail Byoud, Fouzia Rharib, Meryem El Saadane, Rachid Pierre, Samuel Chehri, Abdellah Ghachtouli, Sanae El IME Lab Faculty of Science Hassan 2 University Casablanca20250 Morocco Research and Development Unit Accsellium LLC Fez Morocco Electrical Engineering Department SIRC-LaGeS Hassania School of Public Labors Casablanca20250 Morocco Department of Computer and Software Engineering Polytechnique Montréal MontréalQC Canada Department of Mathematics and Computer Science Royal Military College of Canada KingstonON11 K7K 7B4 Canada

This article presents a study on the effectiveness of electrocoagulation (EC) for the removal of azo dyes from wastewater. The analysis was performed using a combination of statistical methods, including density estimation, correlation analysis, and deep learning for electrocoagulation performance prediction. The results showed that electrocoagulation was able to effectively remove azo dyes from the wastewater, considering the energy consumption and the mass of flocs being important factors in the process. Deep Learning (DL) is used to build our predictive model using the datasets collected during the experimentation stage. Overall, the findings suggest that electrocoagulation is a promising technique for the treatment of wastewater containing azo dyes, and that the use of statistical and machine learning methods can aid in the optimization of the process. © 2024 The Authors. Published by ELSEVIER B.V.

关键词： Azo dyes

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Joint Planning of Dynamic Wireless Charging Lanes and Power Delivery Infrastructure for Heavy-Duty Drayage Trucks

SSRN

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SSRN 2023年

作者： Ye, Zuzhao Bragin, Mikhail A. Wei, Ran Yu, Nanpeng Department of Electrical and Computer Engineering University of California RiversideCA United States School of Public Policy University of California RiversideCA United States University of Connecticut United States

Heavy-duty drayage trucks pose a considerable emission burden and health risk, primarily due to their operation in densely populated areas around seaports and intermodal terminals. In response to these concerns, governments are setting ambitious targets for zero-emissions drayage truck transition. As such, the widespread adoption of electric drayage trucks is on the horizon. However, one of the main challenges hindering the mass electrification of drayage trucks is the low readiness of charging infrastructure. Traditional charging stations can lead to long waiting times for truck drivers, which can be detrimental to an industry where timely pickup and delivery are crucial. Dynamic wireless charging lanes (DWCLs) have emerged as a promising alternative or supplement to stationary charging stations by enabling charging-on-the-move. Although electric drayage trucks are potentially the most benefited vehicles from DWCLs, the optimal deployment of DWCLs for them is rarely studied. To address this problem, we propose a framework that focuses on the deployment of DWCLs with special attention paid to drayage trucks, while jointly planning the associated power delivery infrastructure. The proposed planning model identifies the optimal locations of DWCLs in a given transportation network and determines how they will be powered by nearby electrical substations. Additionally, the framework also evaluates whether an upgrade of the electrical substation is needed. A large-scale Global Positioning System (GPS) dataset and an electrical substation dataset, which contain more than 7,000 heavy-duty drayage trucks that span over a period of 12 months and over 255 substations, are utilized to provide the necessary input to the proposed framework. We demonstrate the effectiveness of the proposed framework through a case study conducted on a highway network of more than 1,000 miles around the Greater Los Angeles area, home to two of the world's busiest seaports, Port of Los Angeles and P

关键词： Trucks

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Air Quality and Healthy Ageing: Predictive Modelling of Pollutants using CNN Quantum-LSTM

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IEEE Access 2025年 13卷 94212-94223页

作者： Naz, Fareena Fahim, Muhammad Cheema, Adnan Ahmad McNiven, Bradley D. E. Cao, Tuan-Vu Hunter, Ruth Duong, Trung Q. Queen’s University School of Electronics Electrical Engineering and Computer Science BelfastBT7 1NN United Kingdom Ulster University School of Engineering BelfastBT15 1AP United Kingdom Memorial University of Newfoundland Faculty of Engineering and Applied Science St. John’sA1C 5S7 Canada Norwegian Institute for Air Research Oslo Norway Queen’s University Centre for Public Health School of Medicine Dentistry and Biomedical Sciences BelfastBT7 1NN United Kingdom

The concept of healthy ageing is emerging and becoming a norm to achieve a high quality of life, reducing healthcare costs and promoting longevity. Rapid growth in global population and urbanisation requires substantial efforts to ensure healthy and supportive environments to improve the quality of life, closely aligned with the principles of healthy ageing. Access to fundamental resources which include quality healthcare services, clean air, green and blue spaces plays a pivotal role in achieving this goal. Air quality, in particular, is a critical factor in achieving healthy ageing targets. However, it necessitates a global effort to develop and implement policies aimed at reducing air pollution, which has severe implications for human health including cognitive impairment and neurodegenerative diseases, while promoting healthier environments such as high quality green and blue spaces for all age groups. Such actions inevitably depend on the current status of air pollution and better predictive models to mitigate the harmful impact of emissions on planetary health and public health. In this work, we proposed a hybrid model referred as AirVCQnet, which combines the variational mode decomposition (VMD) method with a convolutional neural network (CNN) and a quantum long short-term memory (QLSTM) network for the prediction of air pollutants. The performance of the proposed model is analysed on five key pollutants including fine Particulate Matter PM2.5, Nitrogen Dioxide (NO2), Ozone (O3), PM10, and Sulphur Dioxide (SO2), sourced from air quality monitoring station in Northern Ireland, UK. The effectiveness of the proposed model is evaluated by comparing its performance with its equivalent classical counterpart using root mean square error (RMSE), mean absolute error (MAE), and R-squared (R2). The results demonstrate the superiority of the proposed model, achieving a performance gain of up to 14% and validating its robustness, efficiency and reliability by leveraging t

关键词： Air quality

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Exploring the Intent-Behavior Gap in Social Media Advocacy for Gender Equality and Social Inclusion

Exploring the Intent-Behavior Gap in Social Media Advocacy f...

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International Conference on Behavior, Economic and Social Computing (BESC)

作者： Rabab Ali Abumalloh Osama Halabi Asmaa Alfadala Raian Ali Department of Computer Science and Engineering Qatar University Doha Qatar College of Public Policy Hamad Bin Khalifa University Doha Qatar College of Science and Engineering Hamad Bin Khalifa University Doha Qatar

ISBN: (数字)9798331531904

ISBN: (纸本)9798331531911

The concepts of Gender Equality and Social Inclusion (GESI) are crucial for fostering inclusive societies and promoting equal opportunities for all individuals, contributing to social cohesion, economic development, and overall well-being. Social media platforms have offered several benefits for individuals, including information and knowledge sharing, and enhanced connectivity and networking opportunities. On the other hand, social media has enabled several forms of GESI violations, including hate speech, targeted harassment, and discriminatory content. One important solution to face these violations is the challenging behavior of those who violate GESI concepts on social media platforms. While many users may intend to confront and combat such violations, the actual behavior may not always align with these intentions. Accordingly, this study aims to investigate users' challenging intentions and behavior of GESI violations on social media platforms, while focusing on the cultural differences among the UK and Arab. We also investigated the moderating impact of social inclusion on the relationship between intention and behavior regarding challenging violations of GESI. To meet this goal, we deployed a survey among two samples of UK (325) and Arab (312) participants. Our results show that there are intention-behavior disparities in challenging GESI violations on social media platforms for both samples. The results also confirmed the moderating impact of social inclusion on the relationship between intention and behaviors regarding challenging violations of GESI among UK participants and rejected it among Arab participants.

关键词： Surveys Knowledge engineering Social computing Social networking (online) Hate speech Focusing Media Cultural differences Faces Gender issues

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Dynamics of Price-Based Competition between Blue and Green Hydrogen with Net Zero Emissions Targets

SSRN

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SSRN 2024年

作者： Fazeli, Reza Longden, Thomas Beck, Fiona J. Australia Zero-Carbon Energy for the Asia-Pacific Grand Challenge ANU Australia Crawford School of Public Policy ANU Australia College of Engineering and Computer Science

The early development of blue hydrogen is often proposed to ‘kick-start’ a hydrogen economy however, the volatility of the cost of gas, different emission intensities of blue technological options, and projected cost reductions in electrolysers could lead to stranded assets. We develop a model to interrogate the dynamics of hydrogen supply and demand using different cost trajectories for green and blue hydrogen production, and under different carbon pricing scenarios. We find that the window of opportunity for blue hydrogen is mostly determined by how quickly green hydrogen costs reduce. We show that blue hydrogen assets deployed within the next three decades are likely to be significantly underutilised, unless the cost of green hydrogen remains at the high end of projections. This analysis implies that there is a substantial risk that investments in blue hydrogen will lead to stranded assets, which could occur without high-quality information and clear policies. © 2024, The Authors. All rights reserved.

关键词： Investments

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