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Correction to: Machine Learning-Based Analysis of Surface Hardening in Shot-Peened Superalloys (Journal of Materials engineering and Performance, (2024), 10.1007/s11665-024-09918-1)

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Journal of Materials engineering and Performance 2024年 1-1页

作者： Rodrigues, Paul Kerwad, Mokhtar Massoud Askar, Shavan Pallathadka, Harikumar Abduvalieva, Dilsora Zearah, Sajad Ali Department of Computer Engineering College of Computer Science King Khalid University Al-Faraa Asir-Abha Saudi Arabia Faculty of Information Technology Misurata University Misurata Libya Erbil Technical Engineering College Erbil Polytechnic University Erbil Iraq Manipur International University Manipur Imphal India Department of Mathematics and Information Technologies Tashkent State Pedagogical University Tashkent Uzbekistan Scientific Research Center Al-Ayen University Thi-Qar Iraq

There was an error in the grant number given the Acknowledgment section of this article as originally published. The correct Acknowledgment reads as follows: The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through large group Research Project under grant number RPG2/403/45. The original article has been corrected. © ASM International 2024.

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Fluid Antenna Systems Enabling 6G:Principles, Applications, and Research Directions

arXiv

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arXiv 2024年

作者： Wu, Tuo Zhi, Kangda Yao, Junteng Lai, Xiazhi Zheng, Jianchao Niu, Hong Elkashlan, Maged Wong, Kai-Kit Chae, Chan-Byoung Ding, Zhiguo Karagiannidis, George K. Debbah, Mérouane Yuen, Chau The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The School of Electrical Engineering and Computer Science Technical University of Berlin Berlin10623 Germany The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Computer Science Guangdong University of Education Guangdong Guangzhou China The School of Computer Science and Engineering Huizhou University Huizhou516000 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom The Yonsei Frontier Laboratory Yonsei University Seoul03722 Korea Republic of The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of The Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates The Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece Lebanon Lebanon The Center for 6G Technology Khalifa University of Science and Technology P. O. Box 127788 Abu Dhabi United Arab Emirates

Fluid antenna system (FAS), a novel advancement in reconfigurable antenna technologies, offers unprecedented shape and position flexibility. This innovative approach is emerging as an exciting and potentially transformative technology for wireless communication systems. FAS encompasses any software-controlled fluidic, conductive, or dielectric structure capable of dynamically altering an antenna’s shape and position to modify critical parameters such as gain, radiation pattern, operating frequency, and other key characteristics. Given its unique capabilities, FAS is highly anticipated to play a significant role in shaping the upcoming sixth-generation (6G) wireless networks. This article explores this potential by addressing four major questions: 1) Is FAS crucial to 6G? 2) How can FAS be characterized? 3) What are the applications of FAS? 4) What challenges and future research directions are associated with FAS? In particular, five promising research directions that highlight FAS’s potential are examined. Finally, we conclude by demonstrating the impressive performance of FAS, reinforcing its relevance and promise in future networks. © 2024, CC BY.

关键词： Liquefied gases

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A Framework of FAS-RIS Systems: Performance Analysis and Throughput Optimization

arXiv

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arXiv 2024年

作者： Yao, Junteng Lai, Xiazhi Zhi, Kangda Wu, Tuo Jin, Ming Pan, Cunhua Elkashlan, Maged Yuen, Chau Wong, Kai-Kit The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Computer Science Guangdong University of Education Guangdong Guangzhou China The School of Electrical Engineering and Computer Science Technical University of Berlin Berlin10623 Germany The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom The Yonsei Frontier Laboratory the School of Integrated Technology Yonsei University Seoul03722 Korea Republic of

In this paper, we investigate reconfigurable intelligent surface (RIS)-assisted communication systems which involve a fixed-antenna base station (BS) and a mobile user (MU) that is equipped with fluid antenna system (FAS). Specifically, the RIS is utilized to enable communication for the user whose direct link from the base station is blocked by obstacles. We propose a comprehensive framework that provides transmission design for both static scenarios with the knowledge of channel state information (CSI) and harsh environments where CSI is hard to acquire. It leads to two approaches: a CSI-based scheme where CSI is available, and a CSI-free scheme when CSI is inaccessible. Given the complex spatial correlations in FAS, we employ block-diagonal matrix approximation and independent antenna equivalent models to simplify the derivation of outage probabilities in both cases. Based on the derived outage probabilities, we then optimize the throughput of the FAS-RIS system. For the CSI-based scheme, we first propose a gradient ascent-based algorithm to obtain a near-optimal solution. Then, to address the possible high computational complexity in the gradient algorithm, we approximate the objective function and confirm a unique optimal solution accessible through a bisection search method. For the CSI-free scheme, we apply the partial gradient ascent algorithm, reducing complexity further than full gradient algorithms. We also approximate the objective function and derive a locally optimal closed-form solution to maximize throughput. Simulation results validate the effectiveness of the proposed framework for the transmission design in FAS-RIS systems. © 2024, CC BY.

关键词： Antennas

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Metagenomic Characterization of Biomethane Transformation by Lipid-Catalyzed Anaerobic Fermentation of Lignite

SSRN

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SSRN 2023年

作者： Chen, Zhenhong Song, Bo Guo, Hongyu Xia, Dapin Cai, Yidong Wang, Yongjun Zhao, Weizhong Research Institute of Petroleum Exploration & Development Beijing100083 China School of Energy Science and Engineering Henan Polytechnic University Jiaozuo454000 China Mining Research Institute of Henan Polytechnic University Jiaozuo454000 China School of Energy Resources China University of Geosciences Beijing100083 China College of Computer Science and Technology Henan Polytechnic University Jiaozuo454000 China Department of Environmental Engineering Technical University of Denmark LyngbyDK-2800 Denmark

The present study aims at using lipid in a novel way to improve the efficiency of methane production from lignite anaerobic digestion. The obtained results showed an increase by 3.13 times of the cumulative biomethane content of lignite anaerobic fermentation, when 1.8 g lipid was added. The gene expression of functional metabolic enzymes was also found to be enhanced during the anaerobic fermentation. Moreover, the enzymes related to fatty acid degradation such as long-chain Acyl-CoA synthetase and Acyl-CoA dehydrogenase were increased by 1.72 and 10.48 times, respectively, which consequently, accelerated the conversion of fatty acid. Furthermore, the addition of lipid enhanced the carbon dioxide trophic and acetic acid trophic metabolic pathways. Hence, the addition of lipids was argued to promote the production of methane from lignite anaerobic fermentation, which provided a new insight for the conversion and utilization of lipid waste. © 2023, The Authors. All rights reserved.

关键词： Fatty acids

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A Critical Investigation in Analysing the Main Factors Influencing the Network Security Strategies By Applying the Big Data Context Using Multivariate Analysis of Variance (MANOVA) 2

A Critical Investigation in Analysing the Main Factors Influ...

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2nd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2022

作者： Khanna, M.Rajesh Arun, M. Othman, Bestoon Abdulmaged Johar, Siti Sarawati Bhattacharya, Sumanta Suribabu, Potnuri Veltech Multitech Dr.Rangarajan Dr.Sakunthala Engineering College Department of Information Technology India School of Computing Kalasalingam Academy of Research and Education Krishnankoil India Knowledge University-kurdistan Region- Iraq. Business Administration Koya Technical Institute Erbil Polytechnic University College of Administration & Financial Sciences Accounting Department Erbil Iraq Universiti Tun Hussein Onn Malaysia Centre for General Studies and Co-curricular Department of Social Science Johor Darul Takzim Batu Pahat86400 Malaysia Department of Science and Technology and Biotechnology MAKAUT India Department of Computer Science and Engineering Jntu Hyderabad India

ISBN: (纸本)9781665437899

Organizations may use big data to analyze enormous and complicated information in order to uncover hidden trends and correlations, as well as to distribute information across a network. Information that travels via an organization's network is frequently delicate, necessitating the use of a platform that is both efficient and safe. As a result, network security has indeed been elevated to the beginning stages of consideration in the big data world. Consequently, network security systems must handle with a large amount of data that is both complicated and varied in order to detect and prevent possible threats in actual time. Unfortunately, since these systems are frequently built on old methodologies, they are problematic when it comes to protecting large amounts of information. In this article, we will primarily discuss network security and information protection solutions for large amounts of information. First and foremost, we discuss the elements that influence network security architecture in the Big Data world. Following that, we will discuss several big data solutions that allow for the protection of data throughout networks, as well as new study findings. © 2022 IEEE.

关键词： Big data

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Integrated Optimization of Charging Infrastructure, Renewable Energy and Battery Electric Bus Scheduling Subject to Power Distribution Network Constraints

SSRN

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SSRN 2024年

作者： Najafi, Arsalan Gao, Kun Parishwad, Omkar Tsaousoglou, Georgios Jin, Sheng Yi, Wen Department of Architecture and Civil Engineering Chalmers University of Technology GothenburgSE-412 96 Sweden Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Institute of Intelligent Transportation Systems College of Civil Engineering and Architecture Zhejiang University Hangzhou310058 China Department of Building and Real Estate The Hong Kong Polytechnic University Hung Hom Hong Kong

The adoption of Battery Electric Buses (BEBs) in electric public transit systems presents a significant opportunity for advancing sustainable transportation. However, it also poses challenges to the coupled electric transport and energy systems, particularly concerning the safety and efficiency of Power Distribution Networks (PDN). This study introduces a comprehensive BEB-PDN framework designed for the joint optimization of charging infrastructure, charging scheduling, and integration of renewable energy resources, with a specific focus on their impacts on PDN. The complexity of the proposed model is primarily due to its extensive decision variables and nonlinear constraints. To address this, a decomposition approach is employed, linearizing the problem and dividing it into master and subproblems for efficient resolution. A case study in Skövde, Sweden demonstrates that without renewable energy integration, high charging demands from BEBs can lead to PDN safety violations, such as significant voltage drops at certain nodes. The incorporation of renewable energy sources with battery energy storage in the BEB transit system is shown to enhance the PDN's stability and safety while catering to the system's spatiotemporal charging demands. This study offers an optimization framework for the integrated planning of charging infrastructure, BEB systems, and renewable energy, providing empirical insights into their potential benefits. © 2024, The Authors. All rights reserved.

关键词： Electric buses

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FaceBench: A Multi-View Multi-Level Facial Attribute VQA Dataset for Benchmarking Face Perception MLLMs

arXiv

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arXiv 2025年

作者： Wang, Xiaoqin Ma, Xusen Hou, Xianxu Ding, Meidan Li, Yudong Chen, Junliang Chen, Wenting Peng, Xiaoyang Shen, Linlin Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China AIAC Xi’an Jiaotong-Liverpool University China Tsinghua University China The Hong Kong Polytechnic University Hong Kong City University of Hong Kong Hong Kong Sun Yat-sen University China

Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in various tasks. However, effectively evaluating these MLLMs on face perception remains largely unexplored. To address this gap, we introduce FaceBench, a dataset featuring hierarchical multi-view and multi-level attributes specifically designed to assess the comprehensive face perception abilities of MLLMs. Initially, we construct a hierarchical facial attribute structure, which encompasses five views with up to three levels of attributes, totaling over 210 attributes and 700 attribute values. Based on the structure, the proposed FaceBench consists of 49,919 visual question-answering (VQA) pairs for evaluation and 23,841 pairs for fine-tuning. Moreover, we further develop a robust face perception MLLM baseline, Face-LLaVA, by training with our proposed face VQA data. Extensive experiments on various mainstream MLLMs and Face-LLaVA are conducted to test their face perception ability, with results also compared against human performance. The results reveal that, the existing MLLMs are far from satisfactory in understanding the fine-grained facial attributes, while our Face-LLaVA significantly outperforms existing open-source models with a small amount of training data and is comparable to commercial ones like GPT-4o and Gemini. The dataset will be released at https://***/CVI-SZU/FaceBench. Copyright © 2025, The Authors. All rights reserved.

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technology Roadmap for Flexible Sensors

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ACS NANO 2023年第6期17卷 5211-5295页

作者： Luo, Yifei Abidian, Mohammad Reza Ahn, Jong-Hyun Akinwande, Deji Andrews, Anne M. Antonietti, Markus Bao, Zhenan Berggren, Magnus Berkey, Christopher A. Bettinger, Christopher John Chen, Jun Chen, Peng Cheng, Wenlong Cheng, Xu Choi, Seon-Jin Chortos, Alex Dagdeviren, Canan Dauskardt, Reinhold H. Di, Chong-an Dickey, Michael D. Duan, Xiangfeng Facchetti, Antonio Fan, Zhiyong Fang, Yin Feng, Jianyou Feng, Xue Gao, Huajian Gao, Wei Gong, Xiwen Guo, Chuan Fei Guo, Xiaojun Hartel, Martin C. He, Zihan Ho, John S. Hu, Youfan Huang, Qiyao Huang, Yu Huo, Fengwei Hussain, Muhammad M. Javey, Ali Jeong, Unyong Jiang, Chen Jiang, Xingyu Kang, Jiheong Karnaushenko, Daniil Khademhosseini, Ali Kim, Dae-Hyeong Kim, Il-Doo Kireev, Dmitry Kong, Lingxuan Lee, Chengkuo Lee, Nae-Eung Lee, Pooi See Lee, Tae-Woo Li, Fengyu Li, Jinxing Liang, Cuiyuan Lim, Chwee Teck Lin, Yuanjing Lipomi, Darren J. Liu, Jia Liu, Kai Liu, Nan Liu, Ren Liu, Yuxin Liu, Yuxuan Liu, Zhiyuan Liu, Zhuangjian Loh, Xian Jun Lu, Nanshu Lv, Zhisheng Magdassi, Shlomo Malliaras, George G. Matsuhisa, Naoji Nathan, Arokia Niu, Simiao Pan, Jieming Pang, Changhyun Pei, Qibing Peng, Huisheng Qi, Dianpeng Ren, Huaying Rogers, John A. Rowe, Aaron Schmidt, Oliver G. Sekitani, Tsuyoshi Seo, Dae-Gyo Shen, Guozhen Sheng, Xing Shi, Qiongfeng Someya, Takao Song, Yanlin Stavrinidou, Eleni Su, Meng Sun, Xuemei Takei, Kuniharu Tao, Xiao-Ming Tee, Benjamin C. K. Thean, Aaron Voon-Yew Trung, Tran Quang Wan, Changjin Wang, Huiliang Wang, Joseph Wang, Ming Wang, Sihong Wang, Ting Wang, Zhong Lin Weiss, Paul S. Wen, Hanqi Xu, Sheng Xu, Tailin Yan, Hongping Yan, Xuzhou Yang, Hui Yang, Le Yang, Shuaijian Yin, Lan Yu, Cunjiang Yu, Guihua Yu, Jing Yu, Shu-Hong Yu, Xinge Zamburg, Evgeny Zhang, Haixia Zhang, Xiangyu Zhang, Xiaosheng Zhang, Xueji Zhang, Yihui Zhang, Yu Zhao, Siyuan Zhao, Xuanhe Zheng, Yuanjin Zheng, Yu-Qing Zheng, Zijian Zhou, Tao Zhu, Bowen Zhu, Ming Zhu, Rong Zhu, Yangzhi Zhu, Yong Zou, Guijin Chen, Xiaodong 08-03 Innovis Singapore 138634 Republic of Singapore Innovative Centre for Flexible Devices (iFLEX) School of Materials Science and Engineering Nanyang Technological University Singapore 639798 Singapore Department of Biomedical Engineering University of Houston Houston Texas 77024 United States School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 United States Microelectronics Research Center The University of Texas at Austin Austin Texas 78758 United States Department of Chemistry and Biochemistry California NanoSystems Institute and Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior and Hatos Center for Neuropharmacology University of California Los Angeles Los Angeles California 90095 United States Colloid Chemistry Department Max Planck Institute of Colloids and Interfaces 14476 Potsdam Germany Department of Chemical Engineering Stanford University Stanford California 94305 United States Laboratory of Organic Electronics Department of Science and Technology Campus Norrköping Linköping University 83 Linköping Sweden Wallenberg Initiative Materials Science for Sustainability (WISE) and Wallenberg Wood Science Center (WWSC) SE-100 44 Stockholm Sweden Department of Materials Science and Engineering Stanford University Stanford California 94301 United States Department of Biomedical Engineering and Department of Materials Science and Engineering Carnegie Mellon University Pittsburgh Pennsylvania 15213 United States Department of Bioengineering University of California Los Angeles Los Angeles California 90095 United States School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University Singapore 637457 Singapore Nanobionics Group Department of Chemical and Biological Engineering Monash University Clayton Australia 3800 Monash

Humans rely increasingly on sensors to address grand challenges and to improve quality of life in the era of digitalization and big data. For ubiquitous sensing, flexible sensors are developed to overcome the limitations of conventional rigid counterparts. Despite rapid advancement in bench-side research over the last decade, the market adoption of flexible sensors remains limited. To ease and to expedite their deployment, here, we identify bottlenecks hindering the maturation of flexible sensors and propose promising solutions. We first analyze continued...challenges in achieving satisfactory sensing performance for real-world applications and then summarize issues in compatible sensor-biology interfaces, followed by brief discussions on powering and connecting sensor networks. Issues en route to commercialization and for sustainable growth of the sector are also analyzed, highlighting environmental concerns and emphasizing nontechnical issues such as business, regulatory, and ethical considerations. Additionally, we look at future intelligent flexible sensors. In proposing a comprehensive roadmap, we hope to steer research efforts towards common goals and to guide coordinated development strategies from disparate communities. Through such collaborative

关键词： soft materials mechanics engineering flexible electronics conformable sensors bioelectronics human-machine interfaces body area sensor networks technology translation sustainable electronics

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False Data Injection Attack on Atmospheric Electric Field in Thunderstorm Warning

False Data Injection Attack on Atmospheric Electric Field in...

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2022 International Conference on Computing, Communication, Perception and Quantum technology, CCPQT 2022

作者： Li, Xiang Hayawi, Kadhim Chen, Yi Chang, Shih Yu Wen, Hong Ho, Pin-Han Yang, Ling Yin, Qiyuan College of Electronic Engineering Chengdu University of Information Technology Chengdu610225 China College of Technological Innovation Zayed University Abu Dhabi144534 United Arab Emirates School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu611731 China Cma Key Laboratory of Atmospheric Sounding Chengdu610225 China San Jose State University Department of Applied Data Science San JoseCA95192 United States University of Waterloo Department of Electrical and Computer Engineering Waterloo Canada Guangdong Meteorological Public Safety Technical Support Center Guangzhou510640 China

ISBN: (数字)9781665470209

ISBN: (纸本)9781665470209

Thunderstorm warning plays an important role in lightning prevention and disaster mitigation. In practical applications, thunderstorm warning system is also vulnerable to attacks, such as False Data Injection Attack (FDIA). However, there is a lack of research on False Data Injection Attack for thunderstorm warning. Therefore, this paper put forwards a FDIA method based on principal component analysis (PCA) for atmospheric electric field (AEF), which is usually used for thunderstorm warning. In the FDIA scenario, the AEF-based thunderstorm warning algorithm is also introduced with electric field differential index (EFDI). Finally, experiments are conducted based on AEF data collected by an atmospheric electric field meter (AEFM) about the real thunderstorm. The experimental results show that FDIA seriously interferes with the results of the AEF-based thunderstorm warning. © 2022 IEEE.

关键词： Principal component analysis

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Optimized Control of IoT-Monitored Microgrid Systems Using Genetic Algorithm

Optimized Control of IoT-Monitored Microgrid Systems Using G...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： N. Vijayalakshmi Yuvaraj S V. Vijaya Baskar R. Krishnaswamy K. Sasikala C. Srinivasan Department of Electrical and Electronics Engineering Government Polytechnic college Deputed from Annamalai University Coimbatore Tamilnadu India Department of Electronics and Communication Engineering Faculty of Engineering and Technology SRM Institute of Science and Technology Chennai Tamil Nadu India School of Electrical and Electronics Engineering Sathyabama Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering University College of Engineering Ariyalur Tamil Nadu India Department of Electrical and Electronics Engineering Vels Institute of Science Technology & Advanced Studies (VISTAS) Chennai Tamil Nadu India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India

Microgrid (MG) systems have become a good way to make power generation and distribution more efficient, especially when Distributed Energy Resources (DERs) are introduced. The inverter is a critical part of MGs since it regulates the voltage output to the grid. A unique method is proposed to tune the settings of a Proportional-Integral-Derivative (PID) controller for the inverter using Genetic Algorithm (GA). The main aim is to use GAs to improve the inverter control in an MG that is monitored by the Internet of Things (IoT). GA's are very useful for resolving difficult optimization issues. Optimization of voltage regulation, stability, and power transmission to the grid may be achieved by using GA-based tuning of PID controller settings. From the simulation results, the GA-based methodology provides better control performance than conventional tuning approaches, providing exact voltage regulation and improving the MG's stability and dependability.

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