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Frontiers in Optics + Laser science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser science 2023

作者： Zhu, Chen Huang, Jie Research Center for Optical Fiber Sensing Zhejiang Laboratory Hangzhou311100 China Department of Electrical and Computer Engineering Missouri University of Science and Technology RollaMO65409 United States

An optical fiber curvature sensor based on a no-core fiber (NCF) cascaded with a hollow-core fiber (HCF), realizing simultaneously high sensitivity and a broad dynamic range with the assistance of machine learning ana... 详细信息

ISBN: (纸本)9781957171296

关键词： Curvature sensors Fiber Bragg gratings Fiber optic sensors Long period fiber gratings Machine learning Optical fibers

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Fabry-Perot Interferometer in a Coreless Fiber Fabricated by aFsLaser for High-Temperature Applications

Fabry-Perot Interferometer in a Coreless Fiber Fabricated by...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

An optical fiber in-line Fabry-Perot interferometer (FPI) fabricated in a no-core fiber using the direct femtosecond laser writing technique for high-temperature sensing applications is reported. © Optica Publish... 详细信息

ISBN: (纸本)9781957171258

关键词： Fabry-Perot interferometers

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Fiber Ring Resonator Based on Microwave Photonics and Sensitivity-Enhanced Sensing

Fiber Ring Resonator Based on Microwave Photonics and Sensit...

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Optica Sensing Congress 2023, AIS, FTS, HISE, Sensors, ES 2023 - Part of Optical Sensors and Sensing Congress 2023

A new concept of microwave-photonic (MWP) fiber ring resonator is introduced and a method for sensitivity-enhanced sensing based on the system is proposed and experimentally demonstrated. © 2023 The Author (s).

ISBN: (纸本)9781957171241

关键词： Microwave photonics

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An Overview of Artificial Intelligence Ethics

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第4期4卷 799-819页

作者： Huang, Changwu Zhang, Zeqi Mao, Bifei Yao, Xin Southern University of Science and Technology Research Institute of Trustworthy Autonomous Systems Shenzhen518055 China Southern University of Science and Technology Department of Computer Science and Engineering Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Shenzhen518055 China Huawei Technologies Company Ltd. Trustworthiness Theory Research Center Shenzhen518055 China University of Birmingham School of Computer Science BirminghamB15 2TT United Kingdom

Artificial intelligence (AI) has profoundly changed and will continue to change our lives. AI is being applied in more and more fields and scenarios such as autonomous driving, medical care, media, finance, industrial robots, and internet services. The widespread application of AI and its deep integration with the economy and society have improved efficiency and produced benefits. At the same time, it will inevitably impact the existing social order and raise ethical concerns. Ethical issues, such as privacy leakage, discrimination, unemployment, and security risks, brought about by AI systems have caused great trouble to people. Therefore, AI ethics, which is a field related to the study of ethical issues in AI, has become not only an important research topic in academia, but also an important topic of common concern for individuals, organizations, countries, and society. This article will give a comprehensive overview of this field by summarizing and analyzing the ethical risks and issues raised by AI, ethical guidelines and principles issued by different organizations, approaches for addressing ethical issues in AI, and methods for evaluating the ethics of AI. Additionally, challenges in implementing ethics in AI and some future perspectives are pointed out. We hope our work will provide a systematic and comprehensive overview of AI ethics for researchers and practitioners in this field, especially the beginners of this research discipline. © 2020 IEEE.

关键词： Industrial robots

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Assessing the Robustness of nnU-Net in the Detection of Prostate Lesions via Bi-Parametric MRI

Assessing the Robustness of nnU-Net in the Detection of Pros...

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2023 IEEE EMBS Special Topic Conference on Data science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Zaridis, Dimitrios I. Mylona, Eugenia Tachos, Nikolaos Kalantzopoulos, Charalampos Pezoulas, Vasileios C. Koutsouris, Dimitrios D. Matsopoulos, George K. Marias, Kostas Tsiknakis, Manolis Fotiadis, Dimitrios I. National Technical University of Athens School of Electrical and Computer Engineering Biomedical Engineering Laboratory AthensGR15773 Greece Forth Biomedical Research Institute Ioannina Greece University of Ioannina Ioannina Greece Forth Institute of Computer Science Heraklion Greece Hellenic Mediterranean University Department of Electrical and Computer Engineering Crete Heraklion Greece FORTH-IMBB Ioannina Greece University of Ioannina Unit of Medical Technology and Intelligent Information Systems Materials Science and Engineering Department IoanninaGR 45110 Greece

ISBN: (纸本)9798350383386

Within the scope of prostate cancer diagnostic imaging, distinguishing lesions is challenging due to their subtle appearance and the prostate gland's complexity. This study employed the nnU-Net, a state-of-the-art medical image segmentation model, on a dataset of 301 patients from 2 openly available datasets to identify whether lesion sizes are affecting the model's performance. By applying t-SNE dimensionality reduction algorithm among dice score and respective lesion sizes, we found that nnU-Net behaves differently for lesions smaller than 9mm compared to lesions larger than 15mm. These insights can inform specialized training approaches for future deep learning models in prostate lesion *** Relevance: The main contributions of this study is, to investigate whether lesion sizes affects nnU-Net's deficiency leading to the development of more specialized models in respect to these factors. © 2023 IEEE.

关键词： Urology

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Peripheral octamethyl-substituted nickel(Ⅱ)-phthalocyanine-decorated carbon-nanotube electrodes for high-performance all-solid-state flexible symmetric supercapacitors

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Journal of Energy Chemistry 2023年第1期76卷 214-225,I0006页

作者： Yu Wang Minzhang Li Rajendran Ramachandran Haiquan Shan Qian Chen Anxin Luo Fei Wang Zong-Xiang Xu Department of Chemistry Southern University of Science and TechnologyShenzhen 518055GuangdongChina Guangdong-Hong Kong-Macao Joint Laboratory for Photonic-Thermal-Electrical Energy Materials and Devices Southern University of Science and TechnologyShenzhen 518055GuangdongChina School of Microelectronics Southern University of Science and TechnologyShenzhen 518055GuangdongChina SUSTech Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055GuangdongChina Engineering Research Center of Integrated Circuits for Next-Generation Communications Ministry of EducationShenzhen 518055GuangdongChina

Construction of advanced electrode materials with unique performance for supercapacitors(SCs)is essential to achieving high implementation in the commercial ***,we report a novel peripheral octamethyl-substituted nickel(Ⅱ)phthalocyanine(Ni Me_(2)Pc)-based nanocomposite as the electrode material of all-solid-state *** highly redox-active NiMe_(2)Pc/carboxylated carbon nanotube(CNTCOOH)dendritic nanocomposite provides rapid electron/electrolyte ion-transport pathways and exhibits excellent structural stability,resulting in high-capacity activity and impressive cycling *** composite prepared with the optimized weight ratio of Ni Me_(2)Pc:CNT-COOH(6:10)showed the highest specific capacitance of 330.5 F g^(-1)at 0.25 A g^(-1).The constructed NiMe_(2)Pc/CNT-COOH-based all-solid-state symmetric SC device showed excellent performance with a maximum energy density of 22.8 Wh kg^(-1)and outstanding cycling stability(111.6%retained after 35,000 cycles).Moreover,flexible carbon cloth significantly enhanced the energy density of the NiMe_(2)Pc/CNT-COOH all-solid-state symmetric device to 52.1 Wh kg^(-1)with 95.4%capacitance retention after 35,000 cycles,and it could be applied to highperformance flexible electronics *** findings provide a novel strategy to design phthalocyanine-based electrode materials for next-generation flexible SC devices.

关键词： Nickel phthalocyanine Carbon nanotubes Nanocomposites Flexible supercapacitors Cycling stability

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Container-based Platform for Edge-Computing in Energy System Applications

Container-based Platform for Edge-Computing in Energy System...

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IEEE General Meeting Power& Energy Society

作者： Mahmoud S. Abdelrahman Hossam Hussein Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami Fl USA

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The design of power systems is growing more complex due to the large-scale building of microgrids and the ongoing advancement of renewable energy technologies. Several management approaches are applied to overcome these issues using cloud computing and the Internet of Things (IoT). However, the security and time delay for long-distance transferring to cloud communication are crucial concerns. Edge computing is a promising technology to address these challenges. Emerging smart energy systems are frequently deployed at the Edge of the power grid to meet the needs of smart grid users and achieve secure, efficient, and low-latency data processing. This paper proposes a container-based platform for Edge computing emulation based on a co-simulation model to implement, test, and validate Edge computing-based energy system applications. In addition, the feasibility of the proposed model is demonstrated by a case study of a consensus control technique based on an Edge computing framework for multi-microgrids.

关键词： Cloud computing Computational modeling Emulation Microgrids Containers Consensus control Smart grids Internet of Things Security Edge computing

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Communication Networks-Based Control of Cyber-Physical Microgrids

Communication Networks-Based Control of Cyber-Physical Micro...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

This paper surveys the communication networksbased control of cyber-physical microgrids (MGs), including the different architectures of MGs, the control system, and the communication networks within the MGs. The proposed work introduces an overview of the AC, DC, and hybrid AC/DC architectures, highlighting the challenges in the control systems used for each architecture. Focusing on the hierarchical control structure of MGs, we demonstrate the vital role of communication infrastructure in the resilient control of MGs to coordinate between the primary, secondary, and tertiary layers for achieving the control objective. The requirements for communication networks and their influence on MGs' reliable and secure operation are also presented. We have investigated the impact of communication delays, failures, and packet loss on the control system's performance. This survey offers insights into the effects of communication infrastructure on efficient and robust control of cyber-physical MGs in dynamic energy environments.

关键词： Surveys Robust control System performance Packet loss Microgrids Control systems Delays Communication networks Reliability Resilience

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Cyber-HIL Autonomous Inverter-Based Microgrid Framework: Control System Performance and Communication Network Quality of Service

Cyber-HIL Autonomous Inverter-Based Microgrid Framework: Con...

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IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798350372717

ISBN: (纸本)9798350372724

The integration of communication networks within modern power systems enhances the control of modern power systems; however, it increases the system's complexity. This interdependence raises the need to analyze power systems as cyber-physical systems (CPS). Microgrids (MGs) play a vital role in modern power systems, facilitating sustainable operation while decreasing the reliance on the main grid. Different distributed energy resources can be integrated by utilizing power electronics inverters working under grid-forming mode; this configuration forms the inverter-based autonomous AC microgrids. Droop control as a primary control layer is a wellknown technique that enables power-sharing among the various resources within the inverter-based MG. However, it has a limitation in keeping the system voltage and frequency constant. Thus, a secondary control layer is introduced to compensate for the droop limitations. This paper presents an innovative study that considers the communication network performance while studying the control of MGs through a cyber hardware-in-theloop (Cyber-HIL) autonomous inverter-based MG framework that integrates Opal-rt, network simulator ns-3, and docker containers. The effectiveness of the designed MG system equipped with its primary and the developed centralized secondary control system, in addition to the quality of service (QoS) of the designed communication network emulation, are presented in the experimental results.

关键词： Emulation Microgrids Quality of service Containers Control systems Power systems Communication networks Voltage control Frequency control Load modeling

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Learning good state and action representations for Markov decision process via tensor decomposition

The Journal of Machine Learning Research

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The Journal of Machine Learning research 2023年第1期24卷 5157-5209页

作者： Chengzhuo Ni Yaqi Duan Munther Dahleh Mengdi Wang Anru R. Zhang Department of Electrical & Computer Engineering Princeton University Laboratory for Information & Decision Systems Massachusetts Institute of Technology Electrical Engineering & Computer Science Department Massachusetts Institute of Technology Department of Biostatistics & Bioinformatics Duke University

The transition kernel of a continuous-state-action Markov decision process (MDP) admits a natural tensor structure. This paper proposes a tensor-inspired unsupervised learning method to identify meaningful low-dimensional state and action representations from empirical trajectories. The method exploits the MDP's tensor structure by kernelization, importance sampling and low-Tucker-rank approximation. This method can be further used to cluster states and actions respectively and find the best discrete MDP abstraction. We provide sharp statistical error bounds for tensor concentration and the preservation of diffusion distance after embedding. We further prove that the learned state/action abstractions provide accurate approximations to latent block structures if they exist, enabling function approximation in downstream tasks such as policy evaluation.

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