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A Review on Active Customers'Participation in Smart Grids

Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 3-16页

作者： Konrad Schmitt Rabindra Bhatta Manohar Chamana Mahtab Murshed Ilham Osman Stephen Bayne Luciane Canha Electrical and Computer Engineering Department Texas Tech UniversityLubbockTX79409USA Wind Energy Program Texas Tech UniversityLubbockTX79409USA Electromechanical and Power Systems Department Federal University of Santa MariaSanta MariaRS97105-900Brazil Design Release Engineer at Electrification and Power conversion General MotorsGM Tech Center RoadWarrenMI48092USAl IEEE

Industrial,commercial,and residential facilities are progressively adopting automation and generation *** having flexible demand and renewable energy generation,traditional passive customers are becoming active participants in electric power system *** profound coordination among grid operators and active customers,the facilities’capability for demand response(DR)and distributed energy resource(DER)management will be valuable asset for ancillary services(ASs).To comply with the increasing demand and flexible energy,utilities urgently require standards,regulations,and programs to efficiently handle load-side resources without trading off stability and *** study reviews different types of customers’flexibilities for DR,highlighting their capabilities and limitations in performing local ancillary services(LASs),which should benefit the power grid by profiting from it through incentive *** financial incentives and techniques employed around the world are presented and *** potential barriers in technical and regulatory aspects are successfully identified and potential solutions along with future guidance are discussed.

关键词： Active distribution network(ADN) ancillary services energy management flexible demand resiliency

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Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers (vol 2, pg 1, 2022)

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INFECTION CONTROL & HOSPITAL EPIDEMIOLOGY 2023年第10期44卷 1705-1705页

作者： Kamineni, Meghana Otles, Erkin Oh, Jeeheh Rao, Krishna Young, Vincent B. Li, Benjamin Y. West, Lauren R. Hooper, David C. Shenoy, Erica S. Guttag, John G. Wiens, Jenna Makar, Maggie Electrical Engineering and Computer Science Department Massachusetts Institute of Technology Cambridge Massachusetts Medical Scientist Training Program University of Michigan Medical School Ann Arbor Michigan Department of Industrial and Operations Engineering University of Michigan College of Engineering Ann Arbor Michigan Division of Computer Science and Engineering University of Michigan College of Engineering Ann Arbor Michigan Department of Internal Medicine Division of Infectious Diseases University of Michigan Medical School Ann Arbor Michigan Infection Control Unit Massachusetts General Hospital Boston Massachusetts Division of Infectious Diseases Massachusetts General Hospital Boston Massachusetts Harvard Medical School Boston Massachusetts

Many data-driven patient risk stratification models have not been evaluated prospectively. We performed and compared the prospective and retrospective evaluations of 2 Clostridioides difficile infection (CDI) risk-prediction models at 2 large academic health centers, and we discuss the models’ robustness to data-set shifts.

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Integrating Physical Wheelchairs and Virtual Basketball for Enhanced Access and Enjoyment in Wheelchair Basketball 6

Integrating Physical Wheelchairs and Virtual Basketball for ...

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6th IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality, AIxVR 2024

作者： Hsu, Yu-Hung Fang, Iuan-Kai Wang, Chun Chen, Jui-Chien Hu, Min-Chun National Tsing Hua University Department of Computer Science Hsinchu Taiwan National Tsing Hua University International Intercollegiate Ph.D. Program Hsinchu Taiwan National Taiwan University Department of Electrical Engineering Taipei Taiwan University of Texas at Austin School of Information United States

ISBN: (纸本)9798350372021

Wheelchair basketball for people with disabilities is a niche market with limited attention and resources due to its smaller scale. We utilize the characteristics of VR technology, combining wearable devices with physical wheelchair seating, to create a virtual and real interactive game of wheelchair basketball. This enables people with disabilities to exercise at home and allows the general public to experience the challenges of disability sports, fostering empathy and emphasizing the importance of social justice. © 2024 IEEE.

关键词： Virtual reality

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Optimization of the 5G VANET Routing Protocol on AODV Communication with Static Intersection Node 3

Optimization of the 5G VANET Routing Protocol on AODV Commun...

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3rd East Indonesia Conference on computer and Information Technology, EIConCIT 2021

作者： Sahabuddin Achmad, Andani Syarif, Syafruddin Stmik Profesional Computer Engineering Study Program Makassar Indonesia Hasanuddin University Electrical Engineering Department Makassar Indonesia

ISBN: (纸本)9781665405140

The integration of 5G and VANET will result in an intelligent transportation system. Relay of 5G data from mobile networks to VANET which is greatly underutilized can reduce the burden on mobile networks. Wireless technology has been used in vehicles or better known as the Vehicular Ad hoc Network (VANET). One of the keys to the success of sending data on VANET is the Path Selection Algorithm which is the task of the routing protocol the routing protocol that is widely used in research in the VANET environment is AODV (Adhoc On-Demand Distance Vector), because among other protocols, AODV is the most suitable and suitable for implementation in the VANET environment, and AODV is also one of the reactive routing protocols. This study includes an increase in the performance of a routing protocol, so in this study, the SIN (Static Intersection Node) is added to the RSU (Road-Side Unit) which is located at an intersection. Which functions as a repeater that helps send data packets to other vehicles around it so that it can increase the Packet Delivery Ratio and minimize Packet Loss and End to End Delay the focus of this research is to determine the most ideal Static Intersection Node position as well as the most effective number of Static Intersection Nodes. © 2021 IEEE.

关键词： Vehicular ad hoc networks

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Natural Language Processing Meets Hardware Trojan Detection: Automating Security of FPGAs

Natural Language Processing Meets Hardware Trojan Detection:...

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IEEE computer Society Annual Symposium on VLSI

作者： Vaishnavi More Aaditya Chaudhari Barnaboss Puli Vasavi Vuppala Jaya Dofe Wafi Danesh Department of Electrical and Computer Engineering California State University Fullerton CA USA Division of Engineering Program The State University of New York New Paltz NY USA

ISBN: (数字)9798350354119

ISBN: (纸本)9798350354126

The inherent runtime reconfiguration capability of field programmable gate array (FPGA) has been a key feature for deployment in various application scenarios, such as data centers, cloud computing, and edge computing, among others. In such applications, reconfiguration is achieved via remote access, which allows multiple users to utilize FPGA resources concurrently and modify the configuration bitstream. An adversary can exploit the accessibility of the configuration bitstream to insert a hardware Trojan (HT) into the FPGA, thereby creating a critical security vulnerability. Since the HT is designed to remain dormant to avoid detection, it can bypass conventional verification and vali-dation techniques. However, any HT inserted in a configuration bitstream must leave a trace even if it is dormant. This paper proposes a supervised learning method using a deep, recurrent neural network (RNN) algorithm to identify such malicious configuration bitstreams in FPGAs. By analysing the patterns present in the bitstream, the proposed method is able to identify any anomalies present in the implemented design. Our method is applied to three ISCAS 85 benchmark circuits of various sizes and topology, implemented on a Xilinx Artix-7 FPGA. Our experimental results showed a maximum accuracy of 93% in detecting HT in bitstreams.

关键词： Recurrent neural networks Accuracy Benchmark testing Very large scale integration Hardware Topology Trojan horses

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Daily Peak Load Forecast of Banda Aceh City Using Adaptive Neuro Fuzzy Inference System (ANFIS) Method

Daily Peak Load Forecast of Banda Aceh City Using Adaptive N...

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computer System, Information Technology, and electrical engineering (COSITE), International Conference on

作者： Heldi Tindra Ira Devi Sara Ramzi Adriman Graduate program of Electrical Engineering Universitas Syiah Kuala Banda Aceh Aceh Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Aceh

electrical energy has become a fundamental need for society to achieve economic and technical efficiency. To meet the demand for electrical energy, the thing that is done is Electric Load Forecast. In this study, we developed a daily peak load forecast model for Banda Aceh City by considering data on temperature, humidity, and today’s electricity load data at peak hours. Forecasts are made using artificial intelligence, namely, the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. Software used Matlab R2015a to create a daily peak load forecast model based on the neuro-fuzzy designer toolbox. The ANFIS model developed is a variation of triangular, trapezium, and Gaussian membership function types, with each membership function equipped with 3 and 4 variable fuzzy sets. This study uses the MAPE instrument to measure the accuracy of the developed ANFIS model. The results obtained through simulations that have been carried out, all ANFIS Models produce MAPE values below 10%. This indicates that the developed ANFIS Model is very appropriate to be used for Daily Peak Load Forecast in Banda Aceh.

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DCGAN-based Medical Image Augmentation to Improve ELM Classification Performance 11

DCGAN-based Medical Image Augmentation to Improve ELM Classi...

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

作者： Rando Setiawan, Noor Akhmad Permanasari, Adhistya Erna Rulaningtyas, Riries Suksmono, Andriyan Bayu Sitanggang, Imas Sukaesih Universitas Gadjah Mada Dept. of Electrical and Information Engineering Yogyakarta Indonesia Biomedical Engineering Program Dept. of Physics Universitas Airlangga Surabaya Indonesia Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia Ipb University Department of Computer Science Bogor Indonesia

ISBN: (纸本)9781665460309

Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%. © 2022 IEEE.

关键词： Generative adversarial networks

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Cascaded multiparameter quantum metrology

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Physical Review A 2025年第1期111卷 012618-012618页

作者： Gregory Krueper Lior Cohen Juliet T. Gopinath Department of Physics University of Colorado Boulder Boulder Colorado 80309 USA Department of Electrical Computer and Energy Engineering University of Colorado Boulder Boulder Colorado 80309 USA Materials Science and Engineering Program University of Colorado Boulder Boulder Colorado 80309 USA

We present an innovative, platform-independent concept for multiparameter sensing where the measurable parameters are in series, or cascaded, enabling measurements as a function of position. With temporally resolved detection, we show that squeezing can give a quantum enhancement in sensitivity over that of classical states by a factor of e2r, where r≈1 is the squeezing parameter. As an example, we have modeled an interferometer that senses multiple phase shifts along the same path, demonstrating a maximal quantum advantage by combining a coherent state with squeezed vacuum. Further classical modeling with up to 100 phases shows linear scaling potential for adding nodes to the sensor. The approach can be applied to remote sensing, geophysical surveying, and infrastructure monitoring.

关键词： Interferometers

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Unleashing Multi-Hop Reasoning Potential in Large Language Models through Repetition of Misordered Context

arXiv

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arXiv 2024年

作者： Yu, Sangwon Kim, Ik-Hwan Song, Jongyoon Lee, Saehyung Park, Junsung Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of

Multi-hop reasoning, which requires multi-step reasoning based on the supporting documents within a given context, remains challenging for large language models (LLMs). LLMs often struggle to filter out irrelevant documents within the context, and their performance is sensitive to the position of supporting documents within that context. In this paper, we identify an additional challenge: LLMs' performance is also sensitive to the order in which the supporting documents are presented. We refer to this as the misordered context problem. To address this issue, we propose a simple yet effective method called context repetition (CoRe), which involves prompting the model by repeatedly presenting the context to ensure the supporting documents are presented in the optimal order for the model. Using CoRe, we improve the F1 score by up to 30%p on multi-hop QA tasks and increase accuracy by up to 70%p on a synthetic task. Additionally, CoRe helps mitigate the well-known "lost-in-the-middle" problem in LLMs and can be effectively combined with retrieval-based approaches utilizing Chainof- Thought (CoT) reasoning. Copyright © 2024, The Authors. All rights reserved.

关键词： Context sensitive languages

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Leveraging IoT and TinyML for Smart Battery Management in Electric Bicycles

Leveraging IoT and TinyML for Smart Battery Management in El...

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International Workshop on Secure Internet of Things (SIoT)

作者： Thommas Flores Matheus Andrade Morsinaldo Medeiros Miguel Amaral Marianne Silva Ivanovitch Silva Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte - Natal Brazil

Ahstract-Urban mobility and environmental sustainability are critical challenges intensified by population growth, urbanization, and increased vehicle presence, leading to issues like congestion, pollution, and climate change. To counter this, the urgency for efficient and eco-friendly transportation solutions is evident. Battery Management Systems (BMS) play a central role, overseeing batteries in electronics, vehicles, and energy storage systems for safety and reliability. Focusing on electric bicycles (e-Bikes), the article highlights BMS's role in enhancing cyclist experiences and delves into techniques utilizing energy-efficient hardware and deep learning, notably TinyML, to predict Lithium-Ion battery State of Health (SoH). It examines diverse architectures and parameters, unveiling relationships to guide machine learning model construction, emphasizing delayed feedback integration based on rigorous statistics. The article navigates through data segregation and model training processes, presenting a comprehensive approach that balances sustainability, efficiency, and technological progress in predicting e-Bike battery SoH.

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