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arXiv 2022年

作者： Iftikhar, Sundas Gill, Sukhpal Singh Song, Chenghao Xu, Minxian Aslanpour, Mohammad Sadegh Toosi, Adel N. Du, Junhui Wu, Huaming Ghosh, Shreya Chowdhury, Deepraj Golec, Muhammed Kumar, Mohit Abdelmoniem, Ahmed M. Cuadrado, Felix Varghese, Blesson Rana, Omer Dustdar, Schahram Uhlig, Steve School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom University of Kotli Azad Jammu & Kashmir Azad Kashmir Kotli Pakistan Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Software Systems and Cybersecurity Faculty of Information Technology Monash University Australia Csiro DATA61 Australia Center for Applied Mathematics Tianjin University Tianjin China The Pennsylvania State University PA United States Naya Raipur India Abdullah Gül University Kayseri Turkey Department of Information Technology National Institute of Technology Jalandhar India Spain School of Computer Science University of St Andrews United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria

Resource management in computing is a very challenging problem that involves making sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse nature of workload, and the unpredictability of fog/edge computing environments have made resource management even more challenging to be considered in the fog landscape. Recently Artificial Intelligence (AI) and Machine Learning (ML) based solutions are adopted to solve this problem. AI/ML methods with the capability to make sequential decisions like reinforcement learning seem most promising for these type of problems. But these algorithms come with their own challenges such as high variance, explainability, and online training. The continuously changing fog/edge environment dynamics require solutions that learn online, adopting changing computing environment. In this paper, we used standard review methodology to conduct this Systematic Literature Review (SLR) to analyze the role of AI/ML algorithms and the challenges in the applicability of these algorithms for resource management in fog/edge computing environments. Further, various machine learning, deep learning and reinforcement learning techniques for edge AI management have been discussed. Furthermore, we have presented the background and current status of AI/ML-based Fog/Edge Computing. Moreover, a taxonomy of AI/ML-based resource management techniques for fog/edge computing has been proposed and compared the existing techniques based on the proposed taxonomy. Finally, open challenges and promising future research directions have been identified and discussed in the area of AI/ML-based fog/edge computing. Copyright © 2022, The Authors. All rights reserved.

关键词： Edge computing

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Influencing Factors on Li-ion Conductivity and Interfacial Stability of Solid Polymer Electrolytes, Exampled by Polycarbonates, Polyoxalates and Polymalonates

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Angewandte Chemie 2023年第13期135卷

作者： Dr. Xiaoxin Xie Prof. Zhaoxu Wang Dr. Shuang He Kejun Chen Qiu Huang Peng Zhang Prof. Shu-Meng Hao Dr. Jiantao Wang Prof. Weidong Zhou Beijing Advanced Innovation Center for Soft Matter Science and Engineering State Key Laboratory of Organic-Inorganic Composites Beijing University of Chemical Technology Beijing 100029 China Contribution: Data curation (lead) Investigation (lead) Writing - original draft (lead) Key Laboratory of Theoretical Organic Chemistry and Functional Molecule of Ministry of Education Hunan University of Science and Technology Hunan 411201 China Contribution: Data curation (equal) Investigation (supporting) Software (equal) Contribution: Investigation (supporting) Software (supporting) Contribution: Investigation (supporting) Contribution: Supervision (supporting) China Automotive Battery Research Institute Co. Ltd. Beijing 101407 China

The application of solid polymer electrolytes (SPEs) in all-solid-state(ASS) batteries is hindered by lower Li + -conductivity and narrower electrochemical window. Here, three families of ester-based F-modified SPEs of poly-carbonate (PCE), poly-oxalate (POE) and poly-malonate (PME) were investigated. The Li + -conductivity of these SPEs prepared from pentanediol are all higher than the counterparts made of butanediol, owing to the enhanced asymmetry and flexibility. Because of stronger chelating coordination with Li + , the Li + -conductivity of PME and POE is around 10 and 5 times of PCE. The trifluoroacetyl-units are observed more effective than −O−CH 2 −CF 2 −CF 2 −CH 2 −O− during the in situ passivation of Li-metal. Using trifluoroacetyl terminated POE and PCE as SPE, the interfaces with Li-metal and high-voltage-cathode are stabilized simultaneously, endowing stable cycling of ASS Li/LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) cells. Owing to an enol isomerization of malonate, the cycling stability of Li/PME/NCM622 is deteriorated, which is recovered with the introduce of dimethyl-group in malonate and the suppression of enol isomerization. The coordinating capability with Li + , molecular asymmetry and existing modes of elemental F, are all critical for the molecular design of SPEs.

关键词： All-Solid-State Battery High Voltage Cathode Interfacial Stability Lithium Metal Anode Solid Polymer Electrolyte

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Goal-Aware RSS for Complex Scenarios via Program Logic

arXiv

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arXiv 2022年

作者： Hasuo, Ichiro Eberhart, Clovis Haydon, James Dubut, Jérémy Bohrer, Rose Kobayashi, Tsutomu Pruekprasert, Sasinee Zhang, Xiao-Yi Pallas, Erik André Yamada, Akihisa Suenaga, Kohei Ishikawa, Fuyuki Kamijo, Kenji Shinya, Yoshiyuki Suetomi, Takamasa Tokyo101-8430 Japan Dept. Computer Science Worcester Polytechnic Institute 100 Institute Road WorcesterMA01609-2280 United States Inst. Software & Systems Engineering University of Augsburg Universitätstraße 6a AugsburgD-86135 Germany Cyber Physical Security Research Center AIST Aomi 2-4-7 Tokyo135-0064 Japan Graduate School of Informatics Kyoto University Kyoto606-8501 Japan Mazda Motor Corporation Fuchu730-8670 Japan SOKENDAI The Graduate University for Advanced Studies Japan Tokyo Japan

We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement—in addition to collision avoidance as in the original RSS—requires complex planning over long sequences of manoeuvres. To deal with the complexity, we introduce a compositional reasoning framework based on program logic, in which one can systematically develop RSS rules for smaller subscenarios and combine them to obtain RSS rules for bigger scenarios. As the basis of the framework, we introduce a program logic dFHL that accommodates continuous dynamics and safety conditions. Our framework presents a dFHL-based workflow for deriving goal-aware RSS rules;we discuss its software support, too. We conducted experimental evaluation using RSS rules in a safety architecture. Its results show that goal-aware RSS is indeed effective in realising both collision avoidance and goal achievement. © 2022, CC BY-NC-ND.

关键词： Computer circuits

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Transferring knowledge distillation for multilingual social event detection

arXiv

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arXiv 2021年

作者： Ren, Jiaqian Peng, Hao Jiang, Lei Wu, Jia Tong, Yongxin Wang, Lihong Bai, Xu Wang, Bo Yang, Qiang Institute of Information Engineering Chinese Academy of Sciences The School of Cyber Security University of Chinese Academy of Sciences Beijing100041 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The School of Cyber Science and Technology Beihang University Beijing100083 China Institute of Information Engineering Chinese Academy of Sciences Beijing100041 China The Department of Computing Macquarie University Sydney Australia The State Key Laboratory of Software Development Environment The School of Computer Science and Engineering Beihang University Beijing100083 China The National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100029 China The Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong AI Group WeBank Co. Ltd. China

Recently published graph neural networks (GNNs) show promising performance at social event detection tasks. However, most studies are oriented toward monolingual data in languages with abundant training samples. This has left the more common multilingual settings and lesser-spoken languages relatively unexplored. Thus, we present a GNN that incorporates cross-lingual word embeddings for detecting events in multilingual data streams. The first exploit is to make the GNN work with multilingual data. For this, we outline a construction strategy that aligns messages in different languages at both the node and semantic levels. Relationships between messages are established by merging entities that are the same but are referred to in different languages. Non-English message representations are converted into English semantic space via the cross-lingual word embeddings. The resulting message graph is then uniformly encoded by a GNN model. In special cases where a lesser-spoken language needs to be detected, a novel cross-lingual knowledge distillation framework, called CLKD, exploits prior knowledge learned from similar threads in English to make up for the paucity of annotated data. Experiments on both synthetic and real-world datasets show the framework to be highly effective at detection in both multilingual data and in languages where training samples are scarce. © 2021, CC BY.

关键词： Embeddings

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Finding action tubes with a sparse-to-dense framework

arXiv

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arXiv 2020年

作者： Li, Yuxi Lin, Weiyao Wang, Tao See, John Qian, Rui Xu, Ning Wang, Limin Xu, Shugong School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China Shanghai Institute for Advanced Communication and Data Science Shanghai University China Multimedia University Malaysia Adobe Research United States State Key Laboratory for Novel Software Technology Nanjing University China

The task of spatial-temporal action detection has attracted increasing attention among researchers. Existing dominant methods solve this problem by relying on short-term information and dense serial-wise detection on each individual frames or clips. Despite their effectiveness, these methods showed inadequate use of long-term information and are prone to inefficiency. In this paper, we propose for the first time, an efficient framework that generates action tube proposals from video streams with a single forward pass in a sparse-to-dense manner. There are two key characteristics in this framework: (1) Both long-term and short-term sampled information are explicitly utilized in our spatiotemporal network, (2) A new dynamic feature sampling module (DTS) is designed to effectively approximate the tube output while keeping the system tractable. We evaluate the efficacy of our model on the UCF101-24, JHMDB-21 and UCFSports benchmark datasets, achieving promising results that are competitive to state-of-the-art methods. The proposed sparse-to-dense strategy rendered our framework about 7.6 times more efficient than the nearest competitor. Copyright © 2020, The Authors. All rights reserved.

关键词： Machine learning

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Non-equilibrium time-relaxation kinetic model for compressible turbulence modeling

arXiv

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arXiv 2021年

作者： Cao, Guiyu Pan, Liang Xu, Kun Wan, Minping Chen, Shiyi Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology Guangdong Shenzhen518055 China Department of Mathematics Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Laboratory of Mathematics and Complex Systems School of Mathematical Sciences Beijing Normal University Beijing100875 China Shenzhen Research Institute Hong Kong University of Science and Technology Guangdong Shenzhen518057 China Department of Mechanics and Aerospace Engineering Southern University of Science and Technology Guangdong Shenzhen518055 China Guangdong-Hong Kong-Macao Jt. Lab. for Data-Driven Fluid Mechanics and Engineering Applications Southern University of Science and Technology Guangdong Shenzhen518055 China

For the first time, the non-equilibrium time-relaxation kinetic model (NTRKM) is proposed for compressible turbulence modeling on unresolved grids. Within the nonequilibrium time-relaxation framework, NTRKM is extended in the form of modified Bhatnagar-Gross-Krook model. Based on the first-order Chapman-Enskog expansion, NTRKM connects with the six-variable macroscopic governing equations. The first five governing equations correspond to the conservative laws in mass, momentum and total energy, while the sixth equation governs the evolution of unresolved turbulence kinetic energy Kutke. The unknowns in NTRKM, including turbulent relaxation time and source term, are determined by essential gradient-type assumption and standard dynamic modeling approach. Current generalized kinetic model on unresolved grids consequently offers a profound mesoscopic understanding for one-equation subgrid-scale turbulence kinetic energy Ksgs model in compressible large eddy simulation. To solve NTRKM accurately and robustly, a non-equilibrium gas-kinetic scheme is developed, which succeeds the well-established gas-kinetic scheme for simulating Navier-Stokes equations. Three-dimensional decaying compressible isotropic turbulence and temporal compressible plane mixing layer on unresolved grids are simulated to evaluate the generalized kinetic model and non-equilibrium gas-kinetic scheme. The performance of key turbulent quantities up to second-order statistics confirms that NTRKM is comparable with the widely-used eddy-viscosity Smagorinsky model (SM) and dynamic Smagorinsky model (DSM). Specifically, compared with the DNS solution in temporal compressible plane mixing layer, the performance of NTRKM is much closer with DSM and better than SM. This study provides a workable approach for compressible turbulence modeling on unresolved grids, enriching the understanding of turbulence modeling within the non-equilibrium time-relaxation framework. © 2021, CC BY.

关键词： Kinetic theory

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Revisiting Co-occurring directions: Sharper analysis and efficient algorithm for sparse matrices

arXiv

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arXiv 2020年

作者： Luo, Luo Chen, Cheng Xie, Guangzeng Ye, Haishan Department of Mathematics Hong Kong University of Science and Technology Hong Kong Department of Computer Science and Engineering Shanghai Jiao Tong University China Academy for Advanced Interdisciplinary Studies Peking University China Shenzhen Research Institute of Big Data Chinese University of Hong Kong Shenzhen Hong Kong

We study the streaming model for approximate matrix multiplication (AMM). We are interested in the scenario that the algorithm can only take one pass over the data with limited memory. The state-of-the-art deterministic sketching algorithm for streaming AMM is the co-occurring directions (COD), which has much smaller approximation errors than randomized algorithms and outperforms other deterministic sketching methods empirically. In this paper, we provide a tighter error bound for COD whose leading term considers the potential approximate low-rank structure and the correlation of input matrices. We prove COD is space optimal with respect to our improved error bound. We also propose a variant of COD for sparse matrices with theoretical guarantees. The experiments on real-world sparse datasets show that the proposed algorithm is more efficient than baseline methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Approximation algorithms

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Periodically Interrupting Bonding Behavior to Reformat Delocalized Electronic States of Graphdiyne for Improved Electrocatalytic Hydrogen Evolution

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Angewandte Chemie 2022年第42期134卷

作者： Kaikai Ma Jing Wu Xin Wang Yu Sun Zhaozhao Xiong Fulong Dai Haokun Bai Yong Xie Zhuo Kang Yue Zhang Academy for Advanced Interdisciplinary Science and Technology Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing 100083 P. R. China Beijing Key Laboratory for Advanced Energy Materials and Technologies School of Materials Science and Engineering University of Science and Technology Beijing Beijing 100083 P. R. China Contribution: Conceptualization (lead) Data curation (lead) Formal analysis (lead) Funding acquisition (lead) Investigation (lead) Methodology (lead) Project administration (lead) Contribution: Conceptualization (lead) Data curation (lead) Funding acquisition (lead) Investigation (lead) Methodology (lead) Project administration (lead) Resources (lead) Software (lead) Supervision (lead)

π electron configuration plays a pivotal role in metal-free carbon catalysts, and its delocalization degree overwhelmingly dominates catalytic activity. However, precise and targeted regulation of inherent π electrons still remain challenging. Here, one chemical-bond-targeted physical clipping strategy is proposed and effectively adopted in the cutting-edge carbon material system of graphdiyne (GDY) as a concept-of-proof. The delocalized electrons are expected to be periodically reformatted for substantially enhancing π electron delocalization. Via theoretical screening and well-designed experiments, periodical interruption of Csp−Csp 2 bonds in GDY can render sp−C sites with decent activity, ultimately yielding top-ranking electrocatalytic performance without intentionally introducing external decoration. The as-proposed concept endows a universal prescription to push the limit of delocalization degree, thus shedding novel light on the rational design of decent metal-free catalysts.

关键词： Bonding Behavior Delocalization Degree Graphdiyne Hydrogen Evolution π Electron State

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Antisymmetry rules of response properties in certain chemical spaces

arXiv

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arXiv 2025年

作者： Shiraogawa, Takafumi Krug, Simon León Ehara, Masahiro von Lilienfeld, O. Anatole Institute for Molecular Science National Institutes of Natural Sciences 38 Nishigonaka Myodaiji Okazaki444-8585 Japan Research Center for Computational Science National Institutes of Natural Sciences 38 Nishigonaka Myodaiji Okazaki444-8585 Japan The Graduate University for Advanced Studies 38 Nishigonaka Myodaiji Okazaki444-8585 Japan Machine Learning Group Technische Universität Berlin Berlin10587 Germany Chemical Physics Theory Group Department of Chemistry University of Toronto St. George Campus TorontoM5S3H6 Ontario Canada Department of Materials Science and Engineering University of Toronto St. George Campus TorontoM5S 3E4 Ontario Canada Vector Institute for Artificial Intelligence TorontoM5S 1M1 Ontario Canada Berlin Institute for the Foundations of Learning and Data Berlin10587 Germany Department of Physics University of Toronto St. George Campus TorontoM5S 1A7 Ontario Canada Acceleration Consortium University of Toronto TorontoM5R 0A3 Ontario Canada

Understanding chemical compound space (CCS), a set of molecules and materials, is crucial for the rational discovery of molecules and materials. Concepts of symmetry have recently been introduced into CCS to account for near degeneracies and differences in electronic energies between iso-electronic materials. In this work, we present approximate relationships of response properties based on a first-principles view of CCS. They have been derived from perturbation theory and antisymmetry considerations involving nuclear charges. These rules allow approximate predictions of relative response properties of pairs of distinct compounds with opposite nuclear charge variations from a highly symmetric reference material, without the need for experiments or quantum chemical calculations of each compound. We numerically and statistically verified these rules for electric and magnetic response properties (electric dipole moment, polarizabilities, hyperpolarizabilities, and magnetizabilities) among charge-neutral and iso-electronic BN-doped polycyclic aromatic hydrocarbon derivatives of naphthalene, anthracene, and pyrene. Our analysis indicates that, despite their simplicity, antisymmetry rule-based predictions are remarkably accurate, enabling dimensionality reduction of CCS. Response properties in alchemical perturbation density functional theory were investigated to clarify the origin of this predictive power. © 2025, CC BY.

关键词： Naphthalene

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Rely-Guarantee Reasoning about Messaging System for Autonomous Vehicles

Rely-Guarantee Reasoning about Messaging System for Autonomo...

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Theoretical Aspects of software engineering (TASE)

作者： Wenjing Xu Yongwang Zhao Dianfu Ma YuXin Zhang Qian Xiao State Key Laboratory of Software Development Environment School of Computer Science and Engineering Beihang Univerisity Beijing China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China State Key Laboratory of Automotive Simulation and Control College of Automotive Engineering Jilin University Jilin China School of Computer Science and Technology Guizhou University Guiyang China

Messaging system as a communicating infrastructure is a safety-critical component of autonomous vehicles. For the purpose of safety certification of Level 4 autonomous driving systems, its necessary to provide a formally verified specification of messaging systems. This paper presents a realistic case study using the PiCore rely-guarantee framework to formally verify the DGPS (Differential Global Positioning System) of UISEE autonomous driving systems. We first create an axiom model of messaging systems by extending PiCore, which is reusable for concrete applications. The model supports dynamic configuration of message buffers as well as the automatic generation of the rely and guarantee conditions for compositional reasoning. It is instantiated when developing the formal specification of DGPS. Then, we use the rely-guarantee proof system of PiCore to verify the functional correctness and invariant of DGPS. The specification and its proof provide a strong evidence for the ongoing safety certification of DGPS.

关键词： Cognition Safety Formal specifications Vehicle dynamics Autonomous vehicles Certification Global Positioning System

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