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arXiv 2024年

作者： Xu, Luo Lin, Ning Poor, H. Vincent Xi, Dazhi Perera, A.T.D. Department of Civil and Environmental Engineering Princeton University PrincetonNJ United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ United States Andlinger Center for Energy and the Environment Princeton University PrincetonNJ United States Center for Policy Research on Energy and the Environment Princeton University PrincetonNJ United States

Climate extremes, such as hurricanes, combined with large-scale integration of environment-sensitive renewables, could exacerbate the risk of widespread power outages. We introduce a coupled climate-energy model for cascading power outages, which comprehensively captures the impacts of evolving climate extremes on renewable generation, and transmission and distribution networks. The model is validated by the 2022 Puerto Rico catastrophic blackout during Hurricane Fiona - the first-ever system-wide blackout event with complete weather-induced outage records. The model presents a novel resilience pattern that was not captured by the present state-of-the-art models and reveals that early failure of certain critical components surprisingly enhances overall system resilience. Sensitivity analysis of various behind-the-meter solar integration scenarios demonstrates that lower integration levels (below 45%, including the current level) exhibit minimal impact on system resilience in this event. However, surpassing this critical level without additional flexibility resources can exacerbate the failure probability due to substantially enlarged energy imbalances. Copyright © 2024, The Authors. All rights reserved.

关键词： Outages

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Surface tension measurement of normal human blood samples by pendant drop method

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Journal of Medical engineering and Technology 2020年第5期44卷 227-236页

作者： Yadav, Siddharth Singh Sikarwar, Basant Singh Ranjan, Priya Janardhanan, Rajiv Goyal, Ayush Department of Mechanical Engineering Amity University Noida India Department of Electrical and Electronic Engineering Amity University Noida India Amity Institute of Public Health Amity University Noida India Department of Electrical Engineering and Computer Science Texas A&M University KingsvilleTX United States

The surface tension of blood plays an important role not only in the birth and decompression sickness but also in other functionality of the organism. It also provides capillary action during blood flow process. In this article, a simple and low-cost device is designed and fabricated for measuring the surface tension of blood by pendant drop method. In this device, a droplet of blood is formed in a closed chamber on tip of an 18-gauge blunt needle and it is photographed by a camera in very humid conditions (RH = 99%) to minimise the evaporation. A wetted wick is provided at the bottom of the chamber for maintaining constant relative humidity in chamber. Surface tension of blood is inferred using drop shape factor method and image analysis technique at various experimental conditions. This device is validated and calibrated with surface tension measurements of water and silicone oil. Its measurements are in good agreement against data reported in literature. Post-validation, surface tensions of blood samples with and without anticoagulant of healthy persons at various temperatures (range from 20 to 40 °C) was measured. It was found that the surface tension of normal blood samples strongly correlates with blood temperature. The surface tension of female blood was remarkably different from same of male blood. However, the effect of age (21–60 year) on the surface tension was negligible for all practical purposes. Increased percentage of anticoagulant in blood increases its surface tension. This research specifies a baseline for surface tension of normal blood samples at various conditions which in turn provides new insights to pathologists in identifying various disease conditions. © 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Surface tension

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Colorectal Polyp Localization: From Image Restoration to Real-time Detection with Deep Learning

Colorectal Polyp Localization: From Image Restoration to Rea...

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International Symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Mahsa Dehghan Manshadi Milad Mousavi Arian Golzarian Madjid Soltani Amir Mosavi Department of Mechanical Engineering K.N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering University of Waterloo Ontario Canada John von Neumann Faculty of Informatics Obuda University Budapest Hungary University of Public Service Budapest Hungary

Increasing demands for artificial intelligence tools in the medical sector show the huge interest of physicians. In recent years, one of the most effective assistant systems in this field is the real-time detection of early-stage colorectal polyps during colonoscopy. Since even experienced physicians may miss polyps during colonoscopy, the real-time assistance system is designed to prevent this and hence contributes to diminish the number of missed critical cases. One challenge in this field is the detection of false positives. These systems are prone to mistake artifacts for colorectal polyps. This review provides an overview over current quality assessment and restoration techniques to make a high-quality training dataset for training deep neural network algorithms. Furthermore, four of the latest, fastest, and most accurate methods are introduced and analyzed in the rest of the review. Our main contribution is to provide an analysis of current methods used to detect colorectal polyps. We present a list of available datasets and present a range of challenges colorectal cancer detection systems face.

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Decarbonizing Regional Multi-Modal Transportation System with Shared Electric Charging Hub

SSRN

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SSRN 2022年

作者： Ye, Zuzhao Yu, Nanpeng Wei, Ran Liu, Xiaoyue Cathy Department of Electrical and Computer Engineering University of California Riverside RiversideCA United States School of Public Policy University of California Riverside RiversideCA United States Department of Civil and Environmental Engineering University of Utah Salt Lake CityUT United States

In light of the growing concerns of global climate change, the pace of transportation electrification has greatly accelerated in recent years as an effort towards net-zero greenhouse gas (GHG) emissions. However, it remains unclear how to effectively deploy and operate public charging infrastructure to best serve an electrified transportation system within a multi-modal context while maximizing the benefits of decarbonization. To address this question, we propose a mechanism of shared charging hubs that can provide holistic energy management for both electric buses (EBs) and passenger electric vehicles (EVs).The deployment and operation of shared charging hubs is determined by a new spatio-temporal optimization model which aims to minimize GHG emission given a budget limit while avoiding the occurrence of massive spikes in peak power demand. This is achieved by coherently accommodating the charging demand of EBs and EVs, and explicitly integrating the time-varying electricity carbon intensity and vehicle-to-grid (V2G) technology. To demonstrate its effectiveness, the model is applied to the bus fleets operated by seven transit agencies and the park-and-ride facilities (for EVs) near twelve rail transit stations in Contra Costa County, California, USA. The results show that the shared charging hubs can lead to significant GHG emission reduction while mitigating the peak electricity demand. This research will help policymakers and transportation agencies make more informed decisions regarding the planning and design of charging infrastructure. © 2022, The Authors. All rights reserved.

关键词： Climate change

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Role of Wireless Communications in Digital Economy in the Present Context 6

Role of Wireless Communications in Digital Economy in the Pr...

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6th International Conference on Trends in Electronics and Informatics, ICOEI 2022

作者： Revathi, S. Shrivastava, Arpan Yussupova, Ardak Hidayatulloh, A. Nururrochman Saltanat, Daurbekova Mishra, Arpana Sri Ramakrishna Institute of Technology Department of Computer Science and Engineering Coimbatore India Management Devi Ahilya Vishva Vidyalaya Madhya Pradesh India Kazakh National University of Arts Department of Art Studies Nur-Sultan Kazakhstan Universitas Gadjah Mada Leadership and Policy Innovation Program Indonesia International Education Corporation Department of Construction Almaty050042 Kazakhstan Sharda University Electrical Electronics and Communication Engineering Greater Noida India

ISBN: (纸本)9781665483285

Wireless communication has connected millions of people across the world to internet to enable them to reap benefits of digital economy in present scenario. Almost all the sectors of economy including healthcare, agriculture and transportation nowadays rely largely upon wireless communications. In the present context, the sudden outbreak of Covid-19 has caused governments to impose restrictions on various activities and employees have been directed to work from their homes to ensure safety. In such a situation, wireless communication has made it possible to connect with each other via the internet. Apart from this, Smart healthcare-system has been developed through utilisation of wireless communication systems. During this pandemic situation, delivery of healthcare services in remote areas has gained huge momentum and wireless communication plays a vital role in this regard. Aim of current critical assessment is to provide an in-depth analysis of the role played by wireless communication in establishment of a well-structured digital economy in present scenario. In literature-review, different applications of wireless technology via ICT in various sectors and aspects of life have been discussed through a conceptual and a theoretical framework. The Method section of current study has provided an in-depth insight into the ways required information have been collected in this study. As found in the results and discussion section, a positive relation exists between wireless-communication and establishment of digital economy in current situation. This study has concluded that there are certain challenges associated with wireless communication;however, it has significant influence in making processes smarter and faster as compared to earlier. © 2022 IEEE.

关键词： Internet of things

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The impact of different ethical frameworks underlying a robot’s advice on charitable donations

The impact of different ethical frameworks underlying a robo...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Boyoung Kim Ruchen Wen Qin Zhu Tom Williams Elizabeth Phillips Center for Security Policy Studies-Korea George Mason University Korea Incheon South Korea Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Maryland USA Department of Engineering Education Virginia Tech Virginia USA Department of Computer Science Colorado School of Mines Colorado USA Department of Psychology George Mason University Virginia USA

The current work explored to what extent a robot could persuade people to participate in charitable giving by offering moral advice grounded in different ethical theories. In a laboratory, participants, who are students at a university, first performed a task to acquire lottery tickets and then received from a robot information about a charity event organized for students at their university. The robot also offered them moral advice of which the underlying framework was grounded in either deontological or Confucian role ethics to encourage donating their lottery tickets to the event. We found advice grounded in Confucian role ethics to be more effective in inducing donations than advice grounded in deontological ethics. We also found that the more strongly participants felt close to other students at their university, the less donations they would make after receiving advice grounded in deontological ethics. These findings suggest the benefits of framing moral messages of robots based upon theories of Confucian role ethics in promoting prosocial behavior. We discuss potential explanations for the negative relationship between participants’ sense of closeness with other students and their donation behavior when the robot’s advice focuses on theories of deontological ethics.

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Analytical inverter-based distributed generator model for power flow analysis

arXiv

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arXiv 2021年

作者： Turner-Bandele, Naeem Pandey, Amritanshu Pileggi, Larry Electrical and Computer Engineering Dept. Carnegie Mellon University Engineering and Public Policy Dept. Carnegie Mellon University

Quantifying the impact of inverter-based distributed generation (DG) sources on power-flow distribution system cases is arduous. Existing distribution system tools predominately model distributed generation sources as either negative PQ loads or as a PV generator and then employed a PV-PQ switching algorithm to mimic Volt/VAR support. These models neglect the unique characteristics of inverter-based distributed generation sources, have scalability and convergence issues, and are ill-suited for increasing solar penetration scenarios. This work proposes an inverter-based DG model accounting for the inverter's topology, sensing position, and control strategies. The model extends recently introduced analytical positive sequence generator models for three-phase studies. The use of circuit-simulation based heuristics help achieve robust convergence. Simulation of the PG&E prototypical feeders using a prototype solver demonstrate the model's accuracy and efficacy. © 2021, CC BY-NC-ND.

关键词： Analytical models

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Poster: Design of a Music Intervention System Using Social Robotics for Cognitive Enhancement 23

Poster: Design of a Music Intervention System Using Social R...

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Proceedings of the 8th ACM/IEEE International Conference on Connected Health: Applications, Systems and engineering Technologies

作者： Tyler Morris Darina V. Petrovsky Sai Swaminathan Xiaopeng Zhao Department of Mechanical Aerospace and Biomedical Engineering The University of Tennessee Knoxville TN USA Rutgers School of Nursing New Brunswick NJ USA Institute for Health Heath Care Policy and Aging Research New Brunswick NJ USA Min H. Kao Department of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA

ISBN: (纸本)9798400701023

To aid in the care of older adults living with Alzheimer's disease and related dementias (ADRD), many forms of therapies and interventions have been created. One such approach, music intervention, uses song and dance to engage users cognitively, physically, and emotionally. This form of intervention has been proven effective for persons living with ADRD, yet it has not been widely implemented due to a low number of professionals (caregivers, music intervention specialists, etc.) performing the interventions. Social robots can provide relief to caregivers by engaging older adults living with ADRD in music. Therefore, we suggest using social robots to use song and dance to interact with older adults living with ADRD through the Music intervention Using Socially Engaging robotics (MUSE) app. This app will have older adults with ADRD participate in a variety of music-based activities that promote positive cognitive, physical, and emotional well-being.

关键词： social robots

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A Lightweight and Enhanced Semantic Segmentation Network for Mapping of Retrogressive Thaw Slumps from Sentinel-2 Images

A Lightweight and Enhanced Semantic Segmentation Network for...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Yi Yuan Guiyun Zhou Zhonghua Su Ziyin Liu Weiwei Sun Xiangchao Meng Jie Wen Zhiqiang Wu School of Resources and Environment University of Electronic Science and Technology of China Chengdu China School of Computer and Software Engineering Xihua University Chengdu China Department of Geography and Spatial Information Techniques Ningbo University Ningbo China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Sichuan Provincial Public 7 Security Department Communications and Information Technology Headquarters Chengdu China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Fine mapping of retrogressive thaw slumps (RTSs) holds paramount significance in the study of permafrost degradation and carbon exchange. We propose a lightweight and enhanced semantic segmentation network (LessNet) for automatically mapping the RTSs from Sentinel-2 images. LessNet is constructed on the encoder-decoder framework with innovative incorporation of attention mechanism and dual-level semantic features fusion. The lightweight architecture of LessNet eliminates the need for pre-training, and the network hyperparameters are automatically updated based on the training dataset, which allows for fast convergence of supervised learning. Experiments conducted in the Beiluhe region of the Tibetan Plateau highlight the robustness and competitive performance of the model.

关键词： Training Semantic segmentation Supervised learning Transfer learning Semantics Robustness Permafrost

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Deep Learning based Currency Trend Classification Trained on Technical Indicators based Generated Dataset

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Procedia computer Science 2023年 225卷 4364-4370页

作者： Smail Tigani Amal Makrane Rachid Saadane Abdellah Chehri AAIR Lab Digital Engineering and Artificial Intelligence Systems High Private School 20100 Casablanca Moroccoo Electrical Engineering Department SIRC-LaGeS Hassania School of Public Labors 20250 Casablanca Morocco Department of Mathematics and Computer Science Royal Military College of Canada Kingston ON 11 K7K 7B4 Canada

This research paper presents a deep learning-based predictive model for classifying currency trends using technical indicators. The model is trained on a dataset generated from three technical indicators: relative strength index (RSI), moving average convergence divergence (MACD), and stochastic. The dataset consists of historical currency data along with the corresponding values of the technical indicators. The deep learning model can accurately classify the trends of a given currency based on the importance of these indicators. The model's performance is evaluated using standard metrics, and the results demonstrate its effectiveness in classifying currency trends. The proposed model provides a valuable tool for traders and investors in the foreign exchange market by helping them make informed decisions about the direction of currency prices.

关键词： Deep Learning Algorithmic Trading Predictive Analytics

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