检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Hamza, Ali Uneeb, Muhammad Saleem, Komal Ali, Zunaib School of Engineering LondonSE1 0AA United Kingdom School of Electrical Engineering and Computer Science Department of Electrical Engineering Islamabad Pakistan

ISBN: (纸本)9781665471640

The current study presents real-time modeling and non-linear controllers-based energy management system (EMS) for multi-energy hybrid Electric Vehicle (EV), where a detailed physics-based dynamic vehicle model has been considered. The main objective of the paper is to regulate the power flow, stabilize DC voltage for an EV driven by a brushless DC motor, and ensure effective power sharing in a hybrid electric system under complex driving circumstances. The approach is based on tracking the reference battery current by backstepping sliding mode control for optimal power distribution. Subsequently, Integral Sliding Mode Control based on barrier function (NBS-ISMC), and Fractional Order Terminal Sliding Mode Control (FOTSMC) are implemented to control the switching operation of converters for Photovoltaic (PV) and Ultra-capacitor (UC), respectively. User-defined and practical standard drive cycles are selected to test the effectiveness of proposed reference current controllers. Real-time experimental validation of the proposed framework using the Speedgoat Performance Real-Time Target Machine will be included in the final paper. © 2023 IEEE.

关键词： Drive cycles Energy management system Hybrid Electric vehicle Nonlinear Control algorithms Vehicle dynamics

来源：评论

学校读者我要写书评

暂无评论

Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

引用

Intelligent Automation & Soft Computing 2023年第8期37卷 1531-1551页

作者： Hang Yang Xunbo Li Witold Pedrycz School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengduSichuan611731China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6G 1H9Canada

Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply *** study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of *** hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN *** model improves the power supply to a more considerable extent with the least number of power bank *** main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic *** overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or ***’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment ***,the cellular automata(CA)is utilized to enhance the convergence *** case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization *** experiments are conducted on four benchmark functions to validate the effectiveness of the proposed *** experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)*** results show that the proposed energy coverage optimization method based on

关键词： Industrial wireless sensor network hybrid power bank deployment model:energy supply coverage optimization artificial bee colony algorithm radio frequency numerical function optimization

来源：评论

学校读者我要写书评

暂无评论

Enhancing supply chain security through laser-fabricated marks on stainless steel 19

Enhancing supply chain security through laser-fabricated mar...

引用

Laser-based Micro- and Nanoprocessing XIX 2025

作者： Tselios, Christos Mazzucato, Simone Politi, Christina Alexandropoulos, Dimitris Department of Electrical and Computer Engineering University of Patras Achaia Patras26504 Greece Department of Electrical and Computer Engineering University of Peloponnese Achaia Patras22100 Greece SISMA S.p.A. via dell’Industria 1 Piovene Rocchette VI36013 Italy Department of Materials Science University of Patras Achaia Patras26504 Greece

ISBN: (纸本)9781510684508

We present a novel method for generating cryptographic keys from laser-engraved holograms on stainless steel, designed to enhance supply chain security with a focus on industrial scalability, ease of verification, and compliance with National Institute of Standards and Technology (NIST) standards. Using laser-writing technology and off-the-shelf components for key extraction, our approach provides a straightforward, cost-effective, and reliable authentication mechanism between manufacturers and end users. By applying image processing and randomness extraction algorithms, we generate 16-kbit cryptographic keys from each engraving. To validate the effectiveness of these laser-fabricated marks, we analyze correlation coefficient maps and Hamming distance distributions between key sequences from different engravings, demonstrating minimal similarity and enhanced security. Furthermore, the generated 160-kbit key sequences successfully passed all statistical tests of the NIST SP 800-22 test suite. This method offers a practical and scalable solution for anti-counterfeiting and security in real-world applications. © 2025 SPIE.

关键词： Holograms

来源：评论

学校读者我要写书评

暂无评论

Real-time Fall Prediction Using Kinect Sensor with Random Sample Consensus Algorithm

引用

Sensors and Materials 2024年第1-3期36卷 291-303页

作者： Wang, Po-Tong Chen, Yu-Jen Sheu, Jia-Shing Department of Electrical Engineering Lunghwa University of Science and Technology No. 300 Sec. 1 Wanshou Rd. Guishan District Taoyuan333326 Taiwan Department of Computer Science National Taipei University of Education No. 134 Sec. 2 He-Ping East Road Da-an District Taipei106 Taiwan

Falls are a leading cause of unintentional injury and death and pose a significant risk to individuals living alone, particularly older adults. The World Health Organization reports that approximately 684000 fatal falls occur annually, and that timely fall detection is essential to enable prompt treatment and mitigate harm. To address this challenge, we propose a novel in-home fall detection system that uses the Kinect V2 sensor instead of a wearable device. The system can promptly alert a person’s caregivers or family members when it detects a fall, enabling timely assistance. The Kinect V2 sensor captures depth frames and performs skeleton tracking, and body parts in single-depth image pixels are identified using a random forest classifier. v-disparity images, the Hough transform, and the random sample consensus algorithm are used to identify the floor in depth images, and falls are predicted by analyzing the vertical accelerations of 10 joints in the human skeleton. The system can issue an alarm up to 0.5 s before a fall, enabling preventive measures to be taken. In experiments, the proposed system was effective in accurately predicting falls and hence, has potential to improve fall risk management in caregiving environments. © 2024 M Y U Scientific Publishing Division. All rights reserved.

关键词： Fall detection

来源：评论

学校读者我要写书评

暂无评论

Stock Monitoring and Localization Systems for FIFO Method Using RFID Based Pressure Sensing Tag and AI

IEEJ Transactions on Electronics, Information and Systems

引用

IEEJ Transactions on Electronics, Information and Systems 2024年第9期144卷 894-900页

作者： Hadi, Danang Kumara Song, Zequn Rahmadya, Budi Sun, Ran Takeda, Shigeki Graduate School of Science and Engineering Ibaraki University 4-12-1 Nakanarusawa Ibaraki Hitachi316-8511 Japan Department of Agroindustrial Technology Universitas Muhammadiyah Jember Jember68124 Indonesia Computer System Department Faculty of Information Technology Andalas University Padang25175 Indonesia

This research introduces real-time monitoring and localizing product stock using the First-In-First-Out (FIFO) method with radio frequency identification (RFID) pressure sensing tags. The proposed FIFO system has RFID pressure sensing tags that detect pressure changes, generate sensor codes, and estimate a stock location. Integrating artificial intelligence (AI) improves location estimation accuracy of up-to-date stock visibility. The ability of RFID pressure sensing tags and AI to detect stock from sensor code data enables more effective asset management, optimizes stock management, reduces product waste, and contributes to better efficiency in product inventory management. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Inventory control

来源：评论

学校读者我要写书评

暂无评论

Insurance Plan for Service Assurance in Cloud Computing Market with Incomplete Information

引用

Journal of Communications and Information Networks 2022年第1期7卷 11-22页

作者： Yanru Zhang Chunxiao Jiang Nguyen H.Tran Shengrong Bu FeiRichard Yu Zhu Han College of Computer Science and Engineering the University of Electronic Science and Technology of ChinaChengdu 611731China Shenzhen Institute for Advanced Study UESTCLonghuaShenzhen 518110China Tsinghua Space Center Tsinghua UniversityBeijing 10084China School of Computer Science the University of SydneySydneyNew South WalesAustralia Department of Engineering Brock UniversityONCanada School of Information Technology Depart.of Systems and Computer EngineeringCarleton UniversityOttawa K1S 5B6ONCanada Department of Electrical and Computer Engineering the University of HoustonHouston 77004TXUSA

Nowadays,cloud computing has been identified as new opportunities for migrating to the expected agility,reuse,and adaptive capabilities that can support the ever changing IT trends and ***,the rapid evolution of those technologies also comes with open issues such as security,privacy,integrity,quality of services,and their possible detrimental *** this work,the concept of insurance is introduced to compensate the cloud computing customers when encountering those failures if service providers(SPs)have insurance ***,we consider the situation when the insurer is unable to see the system failure risk levels of the SPs,which is usually seen as an incomplete information market,in contrast with the optimal situation in a complete information ***,an insurance-based cloud computing architecture is proposed to build a monetary credit system in which the cloud computing SP pays a premium for a certain coverage to the ***,problem is formulated to solve the optimal insurance plan in complete and incomplete information markets,together with detail analysis of insurance policies in both cases are ***,simulation results show the properties of the two insurance plans and parameters that affect the design of the insurance plan.

关键词： service assurance cloud computing market incomplete information game theory insurance plan

来源：评论

学校读者我要写书评

暂无评论

A Stable Task Assignment Mechanism for Multi-Platform Mobile Crowdsensing

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 8079-8094页

作者： Peng, Shuo Zhang, Guo Zhang, Baoxian Yao, Zheng Liu, Chen Li, Cheng University of Chinese Academy of Sciences Research Center of Ubiquitous Sensor Networks Beijing100049 China University of British Department of Electrical and Computer Engineering BCV6T 1Z4 Canada Simon Fraser University School of Engineering Science BurnabyBCV5A 1S6 Canada

Mobile crowdsensing (MCS) is a new paradigm for Internet of Things. It can fully utilize the smart devices carried by mobile users for accomplishing various sensing tasks. Most existing task assignment mechanisms have assumed the availability of just a single service platform and without considering the preference of users and platforms. In this paper, we focus on studying how to design efficient task assignment mechanism when there are multiple service platforms in the MCS system and further the preferences of both users and platforms are considered while the sensing quality of each user is unknown in advance. The design objective is to maximize the overall sensing qualities of all completed tasks while respecting the budget constraint of each platform. We build a multi-platform oriented task assignment framework and formulate the problem under study as a 0-1 integer linear programming (ILP) problem. We propose a Multi-platform Stable Task Assignment mechanism (MSTA). MSTA works in a round by round manner. In each round, MSTA first performs budget splitting among different task locations for each platform, then makes stable matching between users and platforms and performs online learning of users' sensing qualities by using the multi-armed bandit (MAB) model. We deduce the time complexity of MSTA and prove that MSTA has the properties of stability, individual rationality, budget feasibility, and truthfulness. Simulation results demonstrate the high performance of the proposed MSTA mechanism. © 1967-2012 IEEE.

关键词： Budget control

来源：评论

学校读者我要写书评

暂无评论

Improved Demonstration-Knowledge Utilization in Reinforcement Learning

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2139-2150页

作者： Liu, Yanyu Zeng, Yifeng Ma, Biyang Pan, Yinghui Gao, Huifan Zhang, Yuting Xiamen University Xiamen Key Laboratory of Big Data Intelligent Analysis and Decision Department of Automation Xiamen361102 China Northumbria University Department of Computer and Information Sciences NewcastleNE1 8ST United Kingdom Minnan Normal University Department of Computer Science Zhangzhou363000 China Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China

Reinforcement learning (RL) has made great success in recent years. Generally, the learning process requires a huge amount of interaction with the environment before an agent can achieve acceptable performance. This motivates many techniques, such as incorporating prior knowledge which is usually presented as experts' demonstration, and using a probability distribution to represent state-and-action values, to accelerate the learning process. The methods perform well when the prior knowledge is genuinely correct and no much change occurs to the learning environment. However, the requirement is not perfectly realistic in many complex applications. The demonstration knowledge may not reflect the true environment and even be full of noise. In this article, we introduce a dynamic distribution merging method to improve knowledge utilization in a general RL algorithm, namely Q-learning. The new method adapts a normal distribution to represent state-action values and merges the prior and learned knowledge in a discriminative way. We theoretically analyze the new learning method and demonstrate its empirical performance over multiple problem domains. © 2020 IEEE.

关键词： Merging

来源：评论

学校读者我要写书评

暂无评论

Decisioning-Based Approach for Optimising Control engineering Tools Using Digital Twin Capabilities and Other Cyber-Physical Metaverse Manufacturing System Components

引用

IEEE Transactions on Consumer Electronics 2024年第1期70卷 3212-3221页

作者： Mourad, Nahia Alsattar, Hassan A. Qahtan, Sarah Zaidan, Aws Alaa Deveci, Muhammet Sangaiah, Arun Kumar Pedrycz, Witold British University in Dubai Faculty of Engineering and IT Dubai United Arab Emirates University of Mashreq College of Administrative Science Department of Business Administration Baghdad10067 Iraq Middle Technical University College of Health and Medical Technology-Baghdad Department of Computer Center Baghdad10047 Iraq SP Jain School of Global Management SydneyNSW2141 Australia National Defence University Turkish Naval Academy Department of Industrial Engineering Istanbul34040 Turkey Lebanese American University Department of Electrical and Computer Engineering Byblos Lebanon International Graduate Institute of AI National Yunlin University of Science and Technology Yunlin64002 Taiwan University of Alberta Faculty of Engineering Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Faculty of Engineering and Natural Sciences Department of Computer Engineering Istanbul34010 Turkey

The optimisation of control engineering tools based on digital twin capabilities and other cyber-physical metaverse manufacturing system (CPMMS) components are crucial for the successful performance. This study proposes a model for optimising control engineering tools using digital twin capabilities and other CPMMS components to solve the open issues. The main contributions and novelty aspects of the methodological process are outlined as follows: Formulated and developed is a decision matrix based on a utility procedure for 10 control engineering tools with digital twin capabilities and other three CPMMS components (Programmable-Logic-Controller and Human-Machine-Interface, Internet of Things connectivity and cybersecurity features). This matrix accounts for the uncertainty associated with tool assessment and transformation evaluation issue;formulated and develop an integrating fuzzy weighted with zero-inconsistency-interval-valued spherical fuzzy rough sets (IvSFRS-FWZIC) and combined compromise solution (CoCoSo) methods. The IvSFRS-FWZIC method is utilised to assign importance degrees to the digital twin capabilities and other CPMMS components. The applicability and robustness of the proposed approach are validated and evaluated through conducting sensitivity, correlation, and comparative analyses. The proposed approach can assist managers in analysing and selecting the most suitable tool for developing CPMMS. © 1975-2011 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Machine Learning Techniques Applied to Development of Flexible Electronic Antireflective Film

引用

Sensors and Materials 2024年第1期36卷 17-23页

作者： Lin, Shih-Hung Wang, Yuan-Ting Wang, Yao-Chin Department of Electronics Engineering National Yunlin University of Science and Technology 123 University Road Section 3 Douliou Yunlin64002 Taiwan Bachelor of Science and Technology National Chi Nan University 1 University Road Puli Town Nantou County545 Taiwan Department of Computer Science and Information Engineering Cheng Shiu University 840 Chengcing Road Niaosong District Kaohsiung City83347 Taiwan

In this study, we aim to optimize the process for developing antireflective and refractive-index-matching films on flexible substrates. The development of these films is crucial in light of the increasing demand in the market for flexible electronics, which are poised to be the next emerging technology and application after semiconductors and flat panel displays. Our research involves the production of these films by physical vapor deposition and sputtering techniques, which can also be applied to various optical thin films. The effectiveness of our coating process has been verified and refined on the basis of feedback. The results of this study are applicable to related industrial technologies and will contribute to improving industry competitiveness. © 2024 M Y U Scientific Publishing Division. All rights reserved.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：