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MBSE Approach to Early Naval Ship design Exploration with Power Electronic Power Distribution System in Power and Energy Corridors

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IEEE Transactions on Transportation Electrification 2025年

作者： Cuzner, Robert Chalfant, Julie Gross, David Shabani, Hamed Ali, Naqash Steurer, Mischa University of Wisconsin-Milwaukee Department of Electrical Engineering MilwaukeeWI53211 United States Design Laboratory of the MIT Sea Grant College Program Massachusetts Institute of Technology CambridgeMA02139 United States Florida State University Center for Advanced Power Systems TallahasseeFL32310 United States

The concept development of any system includes the definition of various parameters of interest and determination of the threshold (satisfactory) and goal (desired) value for each. These are classically organized into Measures of Effectiveness, Measures of Performance (MOPs), & Technical Performance Measures (TPMs). These form the basis of performance requirements, the means for evaluating design, and the measure by which systems are validated. A cross-cutting sub-set of MOPs and TPMs, Key Performance Parameters (KPPs) can define the trade space within which to optimize the emerging solution. Applying this systematic approach is substantially complicated when the system of interest aims for unprecedented capabilities from emerging technologies, which is the situation for electric ship research. This paper presents an Integration Framework that effectively maps out a process leading to defined parameter objectives, which is being developed and used in the U.S. Department of Navy sponsored Power Electronic Power Distribution System (PEPDS) research initiative. The method then integrates the Model-Based systems engineering (MBSE) system model with genetic algorithm trade space exploration tools. © 2025 IEEE. All rights reserved.

关键词： Warships

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Enhanced optical imaging and fluorescent labeling for visualizing drug molecules within living organisms

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Acta Pharmaceutica Sinica B 2024年第6期14卷 2428-2446页

作者： Ting Sun Huanxin Zhao Luyao Hu Xintian Shao Zhiyuan Lu Yuli Wang Peixue Ling Yubo Li Kewu Zeng Qixin Chen School of Pharmaceutical Sciences National Key Laboratory of Advanced Drug Delivery SystemMedical Science and Technology Innovation CenterShandong First Medical University&Shandong Academy of Medical SciencesJinan 250062China Departments of Diagnostic Radiology SurgeryChemical and Biomolecular Engineeringand Biomedical EngineeringYong Loo Lin School of Medicine and College of Design and EngineeringNational University of SingaporeSingapore 119074Singapore Institute of Biochemical and Biotechnological Drugs School of Pharmaceutical SciencesCheeloo College of MedicineShandong UniversityJinan 250012China Key Laboratory of Biopharmaceuticals Postdoctoral Scientific Research WorkstationShandong Academy of Pharmaceutical ScienceJinan 250098China State Key Laboratory of Natural and Biomimetic Drugs School of Pharmaceutical SciencesPeking UniversityBeijing 100191China School of Life Sciences Science and Technology Innovation CenterShandong First Medical University&Shandong Academy of Medical SciencesJinan 250062China School of Chinese Materia Medica Tianjin University of Traditional Chinese MedicineTianjin 301617China Tianjin Pharmaceutical DA REN TANG Group Corporation Limited Traditional Chinese Pharmacy Research Institute Tianjin 300457China Key Laboratory of Systems Bioengineering(Ministry of Education) School of Chemistry Engineering and TechnologyTianjin UniversityTianjin 300072China

The visualization of drugs in living systems has become key techniques in modern *** advancements in optical imaging technologies and molecular design strategies have revolutionized drug *** the subcellular level,super-resolution microscopy has allowed exploration of the molecular landscape within individual cells and the cellular response to *** beyond subcellular imaging,researchers have integrated multiple modes,like optical near-infrared II imaging,to study the complex spatiotemporal interactions between drugs and their *** combining these visualization approaches,researchers gain supplementary information on physiological parameters,metabolic activity,and tissue composition,leading to a comprehensive understanding of drug *** review focuses on cutting-edge technologies in drug visualization,particularly fluorescence imaging,and the main types of fluorescent molecules ***,we discuss current challenges and prospects in targeted drug research,emphasizing the importance of multidisciplinary cooperation in advancing drug *** the integration of advanced imaging technology and molecular design,drug visualization has the potential to redefine our understanding of pharmacology,enabling the analysis of drug micro-dynamics in subcellular environments from new perspectives and deepening pharmacological research to the levels of the cell and organelles.

关键词： Optical imaging Drug visualization Fluorophore labeling Therapeutics

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Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models

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IEEE Transactions on Vehicular Technology 2025年

作者： Liu, Chuanhong Guo, Caili Yang, Yang Chen, Mingzhe Quek, Tony Q. S. Beijing University of Posts and Telecommunications Beijing Key Laboratory of Network System Architecture and Convergence School of Information and Communication Engineering Beijing100876 China Beijing University of Posts and Telecommunications Beijing Laboratory of Advanced Information Networks School of Information and Communication Engineering Beijing100876 China University of Miami Department of Electrical and Computer Engineering Institute for Data Science and Computing Coral GablesFL United States Singapore University of Technology and Design Dept. of Information Systems Technology and Design 487372 Singapore

Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial computational demands of LAI models pose significant challenges for real-time communication scenarios. To address this, this paper proposes utilizing knowledge distillation (KD) techniques to extract and condense knowledge from LAI models, effectively reducing model complexity and computation latency. Nevertheless, the inherent complexity of LAI models leads to prolonged inference times during distillation, while their lack of channel awareness compromises the distillation performance. These limitations make standard KD methods unsuitable for task-oriented semantic communication scenarios. To address these issues, we propose a fast distillation method featuring a pre-stored compression mechanism that eliminates the need for repetitive inference, significantly improving efficiency. Furthermore, a channel adaptive module is incorporated to dynamically adjust the transmitted semantic information based on varying channel conditions, enhancing communication reliability and adaptability. In addition, an information bottleneck-based loss function is derived to guide the fast distillation process. Simulation results verify that the proposed scheme outperform baselines in term of task accuracy, model size, computation latency, and training data requirements. © 1967-2012 IEEE.

关键词： NP-hard

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A Facile Superlithiophilic 3d Host with Transition Metal Oxides Heterostructure for Ultrastable Zero-Volume-Expansion Lithium Metal Anodes

SSRN

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SSRN 2024年

作者： Wang, Guohong Peng, Gangqiang Zhang, Wenhan Akbar, Abdul Rehman Peng, Zefan Zheng, Qianfeng Luo, Haimei Liu, Fude Institute for Advanced Study Shenzhen University Guangdong Shenzhen518060 China Department of Advanced Design and Systems Engineering City University of Hong Kong Kowloon852 Hong Kong Department of Mechanical and Energy Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Micro/Nano Engineering Laboratory Research Institute of Tsinghua University in Shenzhen Guangdong Shenzhen518057 China

Lithium metal batteries (LMBs) have garnered immense attention as the frontrunners for next-generation energy devices due to their unprecedented capacity and the lowest electrochemical potential in nature. Nonetheless, their practical implementation has been hindered by critical challenges, including dendrite formation and the instability of the solid electrolyte interface (SEI). In this study, we present a pioneering in-situ growth of a ZnO-CuO heterostructure in a crack shield construction on a three-dimensional (3D) copper foam host. Computational COMSOL simulations reveal marked improvements in electron transfer processes post-decoration. In galvanostatic measurements, the Li@ZnO-CuO-CF electrode demonstrates exceptional stability, exhibiting only a 0.2 V hysteresis and no volume expansion in a symmetric cell under a 50 mA cm-2 current density. Moreover, the electrode retains a remarkable 95.4% of its initial capacity after 600 cycles at 0.5 C and an impressive 85.5% capacity after 220 cycles at 1 C when paired with a high-loading LiFePO₄ (LFP) cathode. These findings underscore the substantial potential of our well-designed electrode as a significant advancement in LMB development. © 2024, The Authors. All rights reserved.

关键词： Zinc oxide

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A Facile Superlithiophilic 3d Host with Transition Metal Oxides Heterostructure for Ultrastable Zero-Volume-Expansion Lithium Metal Anodes

SSRN

引用

SSRN 2024年

作者： Wang, Guohong Peng, Gangqiang Zhang, Wenhan Akbar, Abdul Rehman Peng, Zefan Zheng, Qianfeng Luo, Haimei Liu, Fude Institute for Advanced Study Shenzhen University Guangdong Shenzhen518060 China Department of Advanced Design and Systems Engineering City University of Hong Kong Kowloon 852 Hong Kong Department of Mechanical and Energy Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Micro/Nano Engineering Laboratory Research Institute of Tsinghua University in Shenzhen Guangdong Shenzhen518057 China

Lithium metal batteries (LMBs) have garnered immense attention as the frontrunners for next-generation energy devices due to their unprecedented capacity and the lowest electrochemical potential in nature. Nonetheless, their practical implementation has been hindered by critical challenges, including dendrite formation and the instability of the solid electrolyte interface (SEI). In this study, we present a pioneering in-situ growth of a ZnO-CuO heterostructure in a crack shield construction on a three-dimensional (3D) copper foam host. Computational COMSOL simulations reveal marked improvements in electron transfer processes post-decoration. In galvanostatic measurements, the Li@ZnO-CuO-CF electrode demonstrates exceptional stability, exhibiting only a 0.2 V hysteresis and no volume expansion in a symmetric cell under a 50 mA cm-2 current density. Moreover, the electrode retains a remarkable 95.4% of its initial capacity after 600 cycles at 0.5 C and an impressive 85.5% capacity after 220 cycles at 1 C when paired with a high-loading LiFePO4 (LFP) cathode. These findings underscore the substantial potential of our well-designed electrode as a significant advancement in LMB development. © 2024, The Authors. All rights reserved.

关键词： Zinc oxide

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Multi-Uncertainty Aware Autonomous Cooperative Planning

Multi-Uncertainty Aware Autonomous Cooperative Planning

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Shiyao Zhang He Li Shengyu Zhang Shuai Wang Derrick Wing Kwan Ng Chengzhong Xu Research Institute for Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC) University of Macau Macau China Information Systems Technology and Design Pillar at Singapore University of Technology and Design Singapore Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Electrical Engineering and Telecommunications the University of New South Wales Australia

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Autonomous cooperative planning (ACP) is a promising technique to improve the efficiency and safety of multi-vehicle interactions for future intelligent transportation systems. However, realizing robust ACP is a challenge due to the aggregation of perception, motion, and communication uncertainties. This paper proposes a novel multi-uncertainty aware ACP (MUACP) framework that simultaneously accounts for multiple types of uncertainties via regularized cooperative model predictive control (RC-MPC). The regularizers and constraints for perception, motion, and communication are constructed according to the confidence levels, weather conditions, and outage probabilities, respectively. The effectiveness of the proposed method is evaluated in the Car Learning to Act (CARLA) simulation platform. Results demonstrate that the proposed MUACP efficiently performs cooperative formation in real time and outperforms other benchmark approaches in various scenarios under imperfect knowledge of the environment.

关键词： Solid modeling Uncertainty Three-dimensional displays Real-time systems Planning Safety Power system reliability Intelligent transportation systems Meteorology Predictive control

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Research on Robust Measurement Method of Heart Rate Using Remote Photoplethysmography Based on Adversarial Learning Network with High and Low Frequency Features

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IEEE Transactions on Circuits and systems for Video Technology 2025年第6期35卷 5208-5222页

作者： Zhai, Dezhao Chen, Wei Ding, Yinghao Yu, Ming Li, Qinwei Wu, Hang Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China People's Liberation Army Systems Engineering Institute Academy of Military Sciences Tianjin300161 China Civil Aviation University of China Tianjin Key Laboratory for Advanced Signal Processing Tianjin300300 China Nankai University School of Artificial Intelligence Tianjin300381 China

Remote Photoplethysmography (rPPG) is a non-contact method for measuring heart rate (HR) through facial video, breaking the constraints of contact measurements and offering broad application prospects. However, in real monitoring scenarios, the distance of subjects and facial illumination often vary. This leads to degradation of rPPG signals due to changes in facial resolution and light intensity. This paper presents the High and Low Frequency Feature Adversarial Learning Network (HLFF-AL), which utilizes feature space interpolation and composite feature capture to perform multi-band global and local signal extraction. By adopting an adversarial learning strategy, it enhances the capability to capture semantic information of rPPG under varying resolutions and lighting, bridging the differences in rPPG signal generation due to resolution changes. While maintaining accuracy in HR measuring, the robustness of the network is improved to achieve robust measurement of HR via rPPG. Even under high-resolution conditions, the Mean Absolute Error (MAE) for the three public datasets - unchanging lighting (COHFACE, UBFC-rPPG) and varying lighting (BUAA-MIHR) - reached 1.10 bpm, 1.64 bpm, and 4.41 bpm, respectively, with a mere 0.29 bpm difference in MAE between high and low resolutions on the BUAA-MIHR dataset. This demonstrates that HLFF-AL can predict more robust rPPG signals in various resolutions and lighting scenarios, achieving competitive results compared to state-of-the-art methods. © 1991-2012 IEEE.

关键词： Heart

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Distributed Model Predictive Control of Vehicle Platoons with Random Packet Loss

Distributed Model Predictive Control of Vehicle Platoons wit...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Tan, Yan Bian, Yougang Li, Chongkang Hu, Manjiang Du, Changkun Xu, Biao College of Mechanical and Vehicle Engineering Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha China Beijing Advanced Innovation Center for Intelligent Robots and Systems School of Mechatronical Engineering Beijing Institute of Technology Beijing China

ISBN: (纸本)9780738146577

In order to make up for the deficiencies of previous studies that ignore the impact of packet loss in vehicle platoon control, an innovative distributed model predictive control approach is proposed to address the internal stability issues under Bernoulli random packet loss in this paper. Under the mean communication topology which contains spanning trees, the impact of random packet loss probability on platoon asymptotic stability is explored, and the upper limit of the packet loss probability to maintain asymptotic stability is found. Finally, a sufficient condition for the consensus of vehicle platoons with random packet loss is proposed. In order to verify the proposed sufficient condition, a large number of simulations are executed to expose the repercussion of random packet loss on the platoon tracking performance. © 2021 IEEE.

关键词： Packet loss

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pH-indicative Films Based on Chitosan–PVA/Sepiolite and Anthocyanin from Red Cabbage: Application in Milk Packaging

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Journal of Bionic engineering 2022年第3期19卷 837-851页

作者： Marya Raji Laila El Foujji Mohamed El Mehdi Mekhzoum Mounir El Achaby Hamid Essabir Rachid Bouhfid Abou el kacem Qaiss Moroccan Foundation for Advanced Science Innovation and ResearchComposites and Nanocomposites CenterRabat Design CenterRue Mohamed El JazouliMadinat El IrfaneRabat10100Morocco Faculty of Science Laboratoire de Chimie Organique Et HétérocycliqueUniversity Mohammed V in RabatRabat10100Morocco Materials Science and Nano-Engineering Department Mohammed VI Polytechnic UniversityLot 660–Hay Moulay RachidBen Guerir43150Morocco Mechanic Materialsand Composites(MMC)Laboratory of Energy EngineeringMaterials and SystemsNational School of Applied Sciences of AgadirIbn Zohr UniversityAgadir80000Morocco

Biobased smart packaging is been the most interesting research *** this study,pH-sensitive films based on anthocyanin molecules from red cabbage and sepiolite mineral nano-clay as functional additives were *** films were fabricated by casting method of blend polymer Chitosan/Poly(Vinyl Alcohol)at two fillers loading(5wt.%and 10wt.%).The structural,morphological,thermal,optical,hygroscopic,and mechanical properties as well as the pH sensitivity of films were *** thermal properties confirm that the amount of the anthocyanin in sepiolite was around 6.4%.The tensile strength and the young’s modulus of produced composites at 10wt.%sepiolite–anthocyanin content was increased to 8.90 MPa and 163 MPa,*** maximum water absorption that the films may absorb was 12.3%.pH sensitivity analysis showed that the Smart films change the color by changing the pH level,from pink at pH lower than 6 to yellow at pH higher than ***,the developed pH-sensitive films show band gaps in visible light that make them useful for monitoring milk spoilage.

关键词： Smart packaging Anthocyanin Red cabbage pH-sensitive and milk spoilage

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Mixture Gaussian Distribution-Based Collaborative Reinforcement Learning for 3D UAV Localization Optimization Against Jamming Attacks

Mixture Gaussian Distribution-Based Collaborative Reinforcem...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Yujiao Zhu Mingzhe Chen Sihua Wang Yuchen Liu Gaolei Li Changchuan Yin Tony Q.S. Quek Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing China Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Department of Electrical and Computer Engineering and Institute for Data Science and Computing University of Miami Coral Gables FL USA Department of Computer Science North Carolina State University Raleigh NC USA School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In this paper, the optimization of unmanned aerial vehicle (UAV) localization under jamming attacks is studied. In the considered network, a base station (BS) collaborates with an active UAV to localize a target UAV. During this positioning process, a jamming UAV transmits discontinuous signals to passive UAVs to interfere the distance information measurement. To localize the target UAV under jamming attacks, the BS jointly use two localization methods: 1) generative adversarial network (GAN)-based positioning method and 2) time difference of arrival (TDOA)-based positioning method. Since GAN-based positioning method cannot defense in a strong jamming signal while TDOA-based positioning method may consume more energy and sacrifice localization accuracy, the BS must select an appropriate positioning method (GAN-based or TDOA-based methods) and four distance measurement information of passive UAVs to estimate the position of the target UAV. This problem is formulated as an optimization problem whose goal is to minimize the positioning error between the estimated and the ground truth positions of the target UAV while considering jamming attacks and the trajectory of passive UAVs. To solve this problem, we propose a mixture Gaussian distribution model-based collaborative reinforcement learning (RL) method which enables the active UAV to determine its transmit power and trajectory, and enables the BS to select the most appropriate subsets of distance measurement information and the optimal positioning method according to the movement of passive UAVs and the unknown jamming attack pattern of the jamming UAV. Simulation results show the proposed method can reduce the positioning error of the target UAV by up to 36.5% compared to the method that does not consider the GAN-based positioning method.

关键词： Location awareness Simulation Collaboration Reinforcement learning Gaussian distribution Autonomous aerial vehicles Distance measurement Trajectory Jamming Optimization

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