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A Multi-Hyperparameter Prediction Framework for Distributed Energy Trading on Photovoltaic Network

Tsinghua Science and Technology 2025年第2期30卷 864-874页

作者： Chun Chen Yong Zhang Boon Han Lim Li Ning Shengzhong Feng Peng Xie School of Intelligent Manufacturing and Equipment Shenzhen Institute of Information TechnologyShenzhen 518172China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen518055China Lee Kong Chian Faculty of Engineering and Science Universiti Tunku Abdul RahmanKajang 43000Malaysia Shenzhen Institute for Advanced Study Shenzhen 518028China Shenzhen Institute of Advanced Technology Chinese Academy of SciencesBeijing 100864China High-performance Intelligent Computing Research Group Guangdong Institute of Intelligent Science and TechnologyZhuhai 519031China

The rapid evolution of distributed energy resources,particularly photovoltaic systems,poses a formidable challenge in maintaining a delicate balance between energy supply and demand while minimizing *** integrated nature of distributed markets,blending centralized and decentralized elements,holds the promise of maximizing social welfare and significantly reducing overall costs,including computational and communication ***,achieving this balance requires careful consideration of various hyperparameter sets,encompassing factors such as the number of communities,community detection methods,and trading mechanisms employed among *** address this challenge,we introduce a groundbreaking neural network-based framework,the Energy Trading-based Artificial Neural Network(ET-ANN),which excels in performance compared to existing *** experiments underscore the superiority of ET-ANN in minimizing total energy transaction costs while maximizing social welfare within the realm of photovoltaic networks.

关键词： photovoltaic energy trading hyperparameter prediction

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Hybrid Signal Integrity Modeling and Analysis of Heterogeneous Integrated System With Neuromorphic Darwin Chip

IEEE Transactions on Signal and Power Integrity

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IEEE Transactions on Signal and Power Integrity 2024年 3卷 37-46页

作者： Chen, Quankun Ma, Hanzhi Li, Da Tao, Tuomin Tan, Shurun Liu, En-Xiao Schutt-Aine, Jose Li, Er-Ping Zhejiang University Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems and Applications College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang University University of Illinois at Urbana-Champaign Institute Haining314400 China A∗star Institute of High Performance Computing Singapore138632 Singapore University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61820 United States

This article introduces a comprehensive approach for designing and analyzing signal integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips. The proposed integrated system architecture includes a neuromorphic Darwin chip, digital signal processing unit, microcontroller unit, field programmable gate arrays, and coding and decoding modules to encode and reconstruct analog spiking signals. The study evaluates the encoding module and the heterogeneous integration structure and conducts signal integrity analysis. To achieve optimal signal integrity performance, the article proposes a novel binocular eye diagram analysis technique. This innovative approach guides the encoding algorithm modification and improves the overall system performance. This research is the first to combine joint field-circuit simulation, heterogeneous integration modeling, and signal integrity analysis of the Darwin neuromorphic chip, and it is expected to serve as a valuable reference for future studies on similar systems. © 2022 IEEE.

关键词： Neural networks

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DEMon: Decentralized Monitoring for highly Volatile Edge Environments

DEMon: Decentralized Monitoring for Highly Volatile Edge Env...

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IEEE International Conference on Utility and Cloud computing (UCC)

作者： Shashikant Ilager Jakob Fahringer Samuel Carlos de Lima Dias Ivona Brandic High Performance Computing Systems Research Group Vienna University of Technology Austria

Monitoring systems play an essential role in efficiently managing resources and application workloads by collecting, storing, and providing requisite information about the state of the resources. However, traditional monitoring systems that collect and store the data in centralized remote servers are infeasible for Edge environments. The centralized architecture increases the communication latency for information storage and retrieval and creates a failure bottleneck. In addition, the Edge resources are arbitrarily (de)provisioned, which creates further challenges for providing quick and trustworthy data. Thus, it is crucial to design and build a monitoring system that is fast, reliable, and trustworthy for such volatile Edge computing systems. Therefore, we propose a Decentralised Edge Monitoring (DEMon) framework, a decentralized, self-adaptive monitoring for highly volatile Edge environments. DEMon, at the core, leverages the stochastic Gossip communication protocol and develops techniques for efficient information dissemination, communication, and retrieval, avoiding a single point of failure and ensuring fast and trustworthy data access. We implement it as a lightweight and portable container-based monitoring system and evaluate it through empirical experiments. The results show that DEMon efficiently decimates and retrieves the monitoring information, addressing the abovementioned challenges.

关键词： Cloud computing Protocols Prototypes Computer architecture Reliability engineering Servers Monitoring

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Medical image registration and its application in retinal images:a review

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Visual computing for Industry,Biomedicine,and Art 2024年第1期7卷 142-164页

作者： Qiushi Nie Xiaoqing Zhang Yan Hu Mingdao Gong Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Singapore Eye Research Institute Singapore 169856Singapore State Key Laboratory of Ophthalmology Optometry and Visual ScienceEye HospitalWenzhou Medical UniversityWenzhou 325027China

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.

关键词： Computer-aided diagnosis Medical image registration Deep learning Generative model Transformer Retina

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Self-Organization Towards 1/f Noise in Deep Neural Networks

arXiv

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arXiv 2023年

作者： Le, Nicholas Chong Jia Feng, Ling Department of Physics National University of Singapore 117551 Singapore Complex Systems Group Systems Science Department Institute of High Performance Computing A*STAR 138632 Singapore

The presence of 1/f noise, also known as pink noise, is a well-established phenomenon in biological neural networks, and is thought to play an important role in information processing in the brain. In this study, we find that such 1/f noise is also found in deep neural networks trained on natural language, resembling that of their biological counterparts. Specifically, we trained Long Short-Term Memory (LSTM) networks on the ‘IMDb’ AI benchmark dataset, then measured the neuron activations. The detrended fluctuation analysis (DFA) on the time series of the different neurons demonstrate clear 1/f patterns, which is absent in the time series of the inputs to the LSTM. Interestingly, when the neural network is at overcapacity, having more than enough neurons to achieve the learning task, the activation patterns deviate from 1/f noise and shifts towards white noise. This is because many of the neurons are not effectively used, showing little fluctuations when fed with input data. We further examine the exponent values in the 1/f noise in "internal" and "external" activations in the LSTM cell, finding some resemblance in the variations of the exponents in fMRI signals of the human brain. Our findings further supports the hypothesis that 1/f noise is a signature of optimal learning. With deep learning models approaching or surpassing humans in certain tasks, and being more "experimentable" than their biological counterparts, our study suggests that they are good candidates to understand the fundamental origins of 1/f noise. © 2023, CC BY.

关键词： Long short-term memory

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Inferring Unable-to-Board Commuters for Overcrowded Buses Using Smart Card Data

SSRN

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SSRN 2022年

作者： Tan, Hong En Ramli, Muhamad Azfar Complex Systems Group Systems Science Department Institute of High Performance Computing A*STAR 1 Fusionopolis Way Singapore138632 Singapore

As public transportation faces increasing ridership demand, metrics such as the number of passengers denied boarding become important for measuring the service quality of transit systems. Many studies in the past have used Automated Fare Collection (AFC) and Automated Vehicle Location (AVL) data to infer the probability distributions for commuters that experience unable-to-board (UTB) events in metro systems, but few have studied UTB events for buses. In this paper, we demonstrate that the probability distribution of UTB commuters inferred from AFC data can be modelled by a truncated binomial distribution under certain assumptions. This model is then validated against synthetic UTB events generated using simulations and against actual UTB events recorded from ground surveys. Finally, we apply our model on real AFC data of commuters in the Singapore bus network to serve as a case study. Our method enables transport planners and operators to identify bus stops and time intervals where overcrowding and UTB events is prevalent, so that appropriate measures can be taken to mitigate such occurrences. © 2022, The Authors. All rights reserved.

关键词： Buses

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Versatility of π-d Conjugated Coordination Nickel Metal-Organic Frameworks as Electrode Materials of Metal-Ion Batteries

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Energy Material Advances 2024年第1期5卷 120-132页

作者： Zaohong Zhang Kaihui Xu Jing Yang Zhuoyu Ji Yunchen Ge Zhicong Shi Yongwei Zhang Kai Zhang Chuan Wu Jia Hong Pan State Key Laboratory of Featured Metal Materials and Life-Cycle Safety for Composite Structures School of ResourcesEnvironments and MaterialsGuangxi UniversityNanning 530004China Low Carbon Energy Process Intensification Research Institute and MOE Key Laboratory of Resources and Environmental Systems Optimization North China Electric Power UniversityBeijing 102206China Institute of High Performance Computing Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore Guangxi Key Laboratory of Manufacturing Systems and Advanced Manufacturing Technology Guilin University of Electronic TechnologyGuilin 541004China School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Key Laboratory of Environmental Science and Engineering School of Materials Science and EngineeringBeijing Institute of TechnologyBeijing 100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing 314019China

Metal-organic frameworks have emerged as promising electrode materials for metal-ion batteries due to their superior structural ***,they face challenges such as poor reversibility and easy degradation during electrochemical redox ***,we report the synthesis ofπ-d conjugated coordination polymers through NH_(3)-vapor-assisted self-polymerization of NiCl_(2)·6H_(2)O with 1,2,4,5-benzenetetramine tetrahydrochloride(namely,Ni-BTA).The synthesized Ni-BTA exhibits an open lattice structure that enhances the capacity for metal-ion diffusion,ensuring prolonged electrochemical cycling ***,electrochemical characterizations reveal that Ni-BTA functions as a bifunctional material,serving as both cathode and anode materials for lithium-ion batteries(LIBs).After 1,000 cycles at 1.0 A g^(−1),the cathode and anode show high discharge capacities of 199.7 and 338.4 mAh g^(−1),***,symmetrical all-organic batteries constructed with Ni-BTA exhibit a high specific capacity of 30.6 mAh g-1 and an ultrastable coulombic efficiency of approximately≈100%after 6,000 cycles at 1.0 A g^(−1).Furthermore,Ni-BTA exhibits versatility as a robust cathode for aluminum ion batteries(AIBs),delivering a discharge capacity of 18.7 mAh g^(−1) after 10,000 cycles at 1.0 A g^(−1).These findings highlight the potential of Ni-BTA as a versatile and durable electrode materials for both LIBs and AIBs.

关键词： d conjugation electrochemical stability open lattice stru metal ion batteries electrochemical redox processesherewe lithium ion batteries coordination polymers electrode materials

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Pronounced advance on typhoon track forecast with global convection-permitting model

引用

Science Bulletin 2025年第9期70卷 1424-1428页

作者： Gu, Jun Zhao, Chun Li, Gudongze Feng, Jiawang Xu, Mingyue Du, Qiuyan Xia, Zihan Li, Yubin Chen, Guanghua Hao, Xiaoyu Chen, Junshi An, Hong Deep Space Exploration Laboratory/School of Earth and Space Sciences/CMA-USTC Laboratory of Fengyun Remote Sensing/State Key Laboratory of Fire Science/Institute of Advanced Interdisciplinary Research on High-Performance Computing Systems and Software University of Science and Technology of China Hefei230026 China Laoshan Laboratory Qingdao266237 China CAS Center for Excellence in Comparative Planetology University of Science and Technology of China Hefei230026 China School of Atmospheric Physics Nanjing University of Information Science and Technology Nanjing210044 China Key Laboratory of Cloud-Precipitation Physics and Severe Storms Institute of Atmospheric Physics Chinese Academy of Sciences Beijing100029 China School of Computer Science and Technology University of Science and Technology of China Hefei230026 China

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Fundus Image Quality Assessment and Enhancement: a Systematic Review

arXiv

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arXiv 2025年

作者： Li, Heng Li, Haojin Ou, Mingyang Yu, Xiangyang Zhang, Xiaoqing Niu, Ke Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Autonomous Systems SUSTech Shenzhen China Department of Computer Science and Engineering SUSTech Shenzhen China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Computer School Beijing Information Science and Technology University Beijing China Singapore

As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image degradation is common under intricate imaging environments, impacting following diagnosis and treatment. Consequently, image quality assessment (IQA) and enhancement (IQE) are essential for ensuring the clinical value and reliability of fundus images. While existing reviews offer some overview of this field, a comprehensive analysis of the interplay between IQA and IQE, along with their clinical deployment challenges, is lacking. This paper addresses this gap by providing a thorough review of fundus IQA and IQE algorithms, research advancements, and practical applications. We outline the fundamentals of the fundus photography imaging system and the associated interferences, and then systematically summarize the paradigms in fundus IQA and IQE. Furthermore, we discuss the practical challenges and solutions in deploying IQA and IQE, as well as offer insights into potential future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Photography

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Hardware-Oblivious SIMD Parallelism for In-Memory Column-Stores Template Vector Library - General Approach and Opportunities 10

Hardware-Oblivious SIMD Parallelism for In-Memory Column-Sto...

引用

10th Annual Conference on Innovative Data systems Research, CIDR 2020

作者： Ungethüm, Annett Pietrzyk, Johannes Damme, Patrick Krause, Alexander Habich, Dirk Lehner, Wolfgang Focht, Erich Database Systems Group Technische Universität Dresden Dresden Germany High Performance Computing Europe NEC Deutschland GmbH Stuttgart Germany

Vectorization based on the Single Instruction Multiple Data (SIMD) parallel paradigm is a core technique to improve query processing performance especially in state-of-the-art in-memory column-stores. In mainstream CPUs, vectorization is offered by a large number of powerful SIMD extensions growing not only in vector size but also in terms of complexity of the provided instruction sets. However, programming with vector extensions is a non-trivial task and currently accomplished in a hardware-conscious way. This implementation process is not only error-prone but also connected with quite some effort for embracing new vector extensions or porting to other vector extensions. To overcome that, we present a Template Vector Library (TVL) as a hardware-oblivious concept in this paper. We will show that our single source hardware-oblivious implementation runs efficiently on different SIMD extensions as well as on a pure vector engine. Moreover, we demonstrate that several new optimization opportunities are possible, which are difficult to realize without a hardware-oblivious approach. © 10th Annual Conference on Innovative Data systems Research, CIDR 2020.

关键词： Vectors

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