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arXiv 2023年

作者： Wei, Zhiwei Xiao, Yi Tong, Ying Xu, Wenjia Wang, Yang Key Laboratory of Network Information System Technology Institute of Electronic Chinese Academy of Sciences Beijing 100830 The Aerospace Information Research Institute Chinese Academic of Sciences Beijing 100830 School of Resources and Environment Science Wuhan University Wuhan 430079 School of Software Engineering Shenzhen Institute of Information Technology Guangdong Shenzhen 518172 School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876

Building patterns are important urban structures that reflect the effect of the urban material and social-economic on a region. Previous researches are mostly based on the graph isomorphism method and use rules to recognize building patterns, which are not efficient. The knowledge graph uses the graph to model the relationship between entities, and specific subgraph patterns can be efficiently obtained by using relevant reasoning tools. Thus, we try to apply the knowledge graph to recognize linear building patterns. First, we use the property graph to express the spatial relations in proximity, similar and linear arrangement between buildings;secondly, the rules of linear pattern recognition are expressed as the rules of knowledge graph reasoning;finally, the linear building patterns are recognized by using the rule-based reasoning in the built knowledge graph. The experimental results on a dataset containing 1289 buildings show that the method in this paper can achieve the same precision and recall as the existing methods;meanwhile, the recognition efficiency is improved by 5.98 times. © 2023, CC BY.

关键词： Buildings

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A Parallel and Pipelined Hardware Architecture for Fractional-Pixel Motion Estimation in AVS3

A Parallel and Pipelined Hardware Architecture for Fractiona...

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Zeng, Yuning Zhu, Xizhong Xiang, Guoqing Hao, Zhijian Zhang, Peng Huang, Xiaofeng Yan, Wei Peking University School of Software and Microelectronics Beijing China Advanced Institute of Information Technology Peking University Beijing China Peking University Shenzhen Guraduate School School of Electronic and Computer Engineering Shenzhen China Fudan University State Key Laboratory of ASIC System Shanghai China Hangzhou Dianzi University School of Communication Engineering Hangzhou China

ISBN: (纸本)9781665441544

The latest generation of video coding standards has significantly improved video coding performance. The third generation of audio video coding standards (AVS3) is one of these latest standards. However, due to the more flexible block partition mechanism in AVS3, the computational overhead brought by fractional-pixel motion estimation (FME) increases significantly, making it more difficult to implement a real-time FME hardware. In this paper, a parallel and pipelined hardware architecture supporting block sizes from 4x4 to 64x64 is proposed for FME in AVS3, and it is specially designed for coding tree unit (CTU)-level pipelined architecture of AVS3 encoder. Three necessary modules are developed in this architecture. The first module concerns derivation of motion vector predictors (MVPs). The second module is used to derive fractional-pixel motion vectors (FMVs) of coding units (CUs) partitioned by Binary-tree (BT) and Quad-Tree (QT) mechanisms. And a motion vector substitution (MVS) module is proposed to substitute the FMVs of the remaining CUs with the FMVs derived in the second module. Experimental results show that the proposed methods suffer only 0.62% performance degradation in BD-Rate. Furthermore, the architecture is implemented on XILINX ALVEO U250 FPGA at 400 MHz and the presented FME hardware design can support the real-time encoding of 4K@30fps. © 2022 IEEE.

关键词： Pipelines

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TransOff: Towards Fast Transferable Computation Offloading in MEC via Embedded Reinforcement Learning

TransOff: Towards Fast Transferable Computation Offloading i...

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International Conference on Distributed Computing systems

作者： Zheyuan Hu Jianwei Niu Tao Ren State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou University Zhengzhou China Laboratory for Internet Software Technologies Institute of Software Chinese Academy of Sciences Beijing China

Mobile edge computing (MEC) has been proposed as a promising paradigm to provide mobile devices with both satisfactory computing capacity and task latency. One key issue in MEC is computation offloading (CompOff), which has attracted numerous research interests. Most existing CompOff approaches are developed based on iterative programming (IterProg), that calculates a CompOff action based on system dynamics each time mobile tasks arrive. Due to the heavy dependency of IterProg on reliable system dynamics, as well as the online computational burden, recent years have seen a popular trend to develop CompOff approaches based on deep reinforcement learning (DRL), which could generate real-time model-free CompOff actions. However, due to the intrinsic poor generalization of DRL, it is hard to directly apply DRL-based policies in new MEC environments, and long-time fine-tuning is often required. To address the challenge, this paper proposes a fast transferable CompOff framework (named TransOff), based on the idea of embedded reinforcement learning. Specifically, TransOff is composed of multiple primitive CompOff policies (pCOPs) and a multiplicative composition function (MCF). The pCOPs and MCF are pre-trained in a diverse variety of MEC environments. When encountering new MEC environments, pCOPs are kept fixed to prevent catastrophic forgetting of pre-trained CompOff skills, while only MCF is fine-tuned to produce new compositions of pCOPs to achieve fast transfer. We conduct extensive experiments via both numerical simulation and real testbed, indicating the fast transfer ability of TransOff compared to the state-of-the-art DRL-based and meta learning-based CompOff approaches.

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Motion Vector Search Algorithm for Motion Compensation in Video Encoding 8

Motion Vector Search Algorithm for Motion Compensation in Vi...

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8th IEEE International Conference on Problems of Infocommunications, Science and Technology, PIC S and T 2021

作者： Bondarchuk, Andriy Dibrivniy, Oles Grebenyk, Viktor Onyshchenko, Viktoriia State University of Telecommunications Software Engineering Department Kyiv Ukraine National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of Information Systems And Technologies Kyiv Ukraine

ISBN: (纸本)9781665406826

As a result of a combination of template comparison for estimating block similarity, edge selection algorithms and an improved block search method, two versions of a generalized method for finding motion vectors, called TFEMVFAS (Three by Frame Edge Map Motion Vector Field Adaptive Search), were proposed. Both modifications of the method were tested according to the comprehensive testing recommendations of the international commission MPEG for the evaluation of complex video tools, on the example of 13 video sequences, with different bitrates. The effect of increasing the size of the blocks on which the image is divided on the PSNR value and the maximum acceleration was also investigated. © 2021 IEEE.

关键词： Video streaming

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Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack Tree and Fuzzy Logic 3

Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack T...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Naik, Nitin Jenkins, Paul Grace, Paul Naik, Dishita Song, Jingping Prajapat, Shaligram Mishra, Durgesh Yang, Longzhi Boongoen, Tossapon Iam-On, Natthakan School of Informatics and Digital Engineering Aston University United Kingdom Cardiff School of Technologies Cardiff Metropolitan University United Kingdom Birmingham City University United Kingdom Software College Northeastern University China International Institute of Professional Studies Devi Ahilya University India School of Computer Science & Information Technology Symbiosis University of Applied Sciences India Northumbria University Department of Computer and Information Sciences United Kingdom Aberystwyth University Department of Computer Science United Kingdom

ISBN: (纸本)9798350343274

Organisations and users have been experiencing significant rises in cyberattacks and their severity, which means that they require a greater awareness and understanding of the anatomy of cyberattacks, to prevent and mitigate their effects. In analysing cyberattacks, there are a number of different approaches that may be used to assess their potential risks and effects. However, these are utilised in specific types of cyberattacks and their analysis, which means they cannot be applied in every situation or cyberattack. Moreover, several other factors may influence the decision to use these approaches, such as cost, complexity, skills and adaptability. As a result, continuous research to design and enhance these approaches is undertaken to produce a generic, cost-effective, easy and adaptable approach. This paper presents one such approach to assess the risk of cyberattacks utilising an attack tree and fuzzy logic. An attack tree is a systematic and illustrative method for describing an attack on a system and analysing its taxonomy and other aspects. Subsequently, the probability and risk of each leaf node in the attack tree are calculated using the proposed formulas. Finally, fuzzy logic enables decision making based on imprecise data and heuristics to obtain the overall risk of attack. This proposed approach comprises systematic steps to accomplish an assessment of any cyberattack and its associated risks in an uncomplicated and effective manner, enabling its prevention and mitigation to be determined. The paper illustrates an application of the proposed approach to assess the risk of an information theft attack on an organisation, which can then be utilised to assess the risk of other cyberattacks. © 2023 IEEE.

关键词： Decision making

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CA-Edit: Causality-Aware Condition Adapter for High-Fidelity Local Facial Attribute Editing 39

CA-Edit: Causality-Aware Condition Adapter for High-Fidelity...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Xian, Xiaole He, Xilin Niu, Zenghao Zhang, Junliang Xie, Weicheng Song, Siyang Yu, Zitong Shen, Linlin Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China University of Exeter United Kingdom Great Bay University China

ISBN: (纸本)157735897X

For efficient and high-fidelity local facial attribute editing, most existing editing methods either require additional finetuning for different editing effects or tend to affect beyond the editing regions. Alternatively, inpainting methods can edit the target image region while preserving external areas. However, current inpainting methods still suffer from the generation misalignment with facial attributes description and the loss of facial skin details. To address these challenges, (i) a novel data utilization strategy is introduced to construct datasets consisting of attribute-text-image triples from a data-driven perspective, (ii) a Causality-Aware Condition Adapter is proposed to enhance the contextual causality modeling of specific details, which encodes the skin details from the original image while preventing conflicts between these cues and textual conditions. In addition, a Skin Transition Frequency Guidance technique is introduced for the local modeling of contextual causality via sampling guidance driven by low-frequency alignment. Extensive quantitative and qualitative experiments demonstrate the effectiveness of our method in boosting both fidelity and editability for localized attribute editing. Our codes will be made publicly available. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Overview and Assessment Approaches of Energy Consumption and GHG Emissions Through the Development and Application of Artificial Intelligence - An Example from the Agricultural Sector

Overview and Assessment Approaches of Energy Consumption and...

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IEEE International Workshop on Metrology for Agriculture and Forestry (MetroAgriFor)

作者： Stefan Rilling Jens Henningsen Katharina Milde Daniel Martini Lorenz Wickert Patricia Kelbert Adaptive Reflective Teams Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS Sankt Augustin Germany Data Science Fraunhofer Institute for Experimental Software Engineering IESE Kaiserslautern Germany Team Digital Technologies Advisory Board for Technology and Construction in Agriculture KTBL Darmstadt Germany

ISBN: (数字)9798350355444

ISBN: (纸本)9798350355451

This article looks at the sustainability of various artificial intelligence (AI) methods. In recent months, AI methods have received a great deal of public attention and the benefits for sustainability have been emphasised. However, the ecological impacts of AI methods must also be considered in this debate. This article presents an overview of various approaches to sustainability assessment and addresses issues relating to energy consumption and the associated Carbon dioxide (CO2) emissions, and a Life Cycle Assessment (LCA) calculation for a concrete agricultural AI-use case.

关键词： Life cycle assessment Energy consumption Conferences Forestry Carbon dioxide Metrology Agriculture Artificial intelligence Sustainable development Carbon emissions

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Algorithm for Recognition of Network Traffic Anomalies Based on Artificial Intelligence 5

Algorithm for Recognition of Network Traffic Anomalies Based...

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5th International Congress on Human-Computer Interaction, Optimization and Robotic Applications, HORA 2023

作者： Laptiev, Oleksandr Musienko, Andrii Nakonechnyi, Volodymyr Sobchuk, Andrii Gakhov, Sergii Kopytko, Serhii Shevchenko National University Doctor of Technical Sciences Faculty of Information Tehnology Department of Cyber Security and Information Protection Taras Kyiv Ukraine National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Doctor of Technical Sciences Docent Department of Software Engineering in Energy Kyiv Ukraine State University of Telecommunication Doctor of Philosophy Department of Information and Cyber Security Kyiv Ukraine State University of Telecommunication Candidate of Military Sciences Docent Department of Information and Cyber Security Kyiv Ukraine State University of Intellectual Technologies and Communication Candidate of Economic Sciences Department of Cyber Security and Technical Information Protection Odesa Ukraine

ISBN: (纸本)9798350337525

Abnormalities in network traffic can be caused by malfunctioning network equipment, accidental or intentional actions by users, or the actions of attackers. Thus, for reliable data transmission in the information network, it is necessary to take measures to detect anomalies in a timely manner and take measures to eliminate them. Therefore, in order to ensure reliable data transmission in the network, the development of new methods for detecting anomalies is of urgent importance. This work is devoted to the development of an improved algorithm for recognizing network traffic anomalies based on artificial intelligence. On the basis of the conducted analysis and research, an improved algorithm was developed for the most accurate determination of an abnormal state. The principle component analysis algorithm was taken as a basis and a type of Generative adversarial network algorithm, a machine learning algorithm without a teacher, was added to it, namely BIGAN, which uses an encoder in its activity, namely, thanks to its E encoder, it is able to detect anomalies in input and processed data, which made it possible to detect network traffic anomalies with greater accuracy and in less time. © 2023 IEEE.

关键词： Data transfer

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Equivalent Circuit Analysis of the Multi-Sheet-Beam Folded Waveguide Slow-wave Structure

Equivalent Circuit Analysis of the Multi-Sheet-Beam Folded W...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Yanan Ma Fengying Lu Rui Zhang Yong Wang The Key Laboratory of Science and Technology on High Power Microwave Sources and Technologies Aerospace Information Research Institute Chinese Academy of Sciences China The School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences China Key Laboratory of Avionic Information System Technology Southwest China Institute of Electronics Technology Chengdu China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

An equivalent circuit analysis method for the Folded Waveguide (FW) slow-wave structure based on Multi-Sheet-Beam (MSB) is investigated. Folded waveguide is a periodic slow–wave structure made entirely of metal. It is commonly used in travelling wave tubes (TWT) due to its simple coupling structure, robust mechanical design, and excellent heat dissipation capabilities. The MSB-FW slow-wave structure utilizes multiple sheet beams to increase amplification power, reduce single beam current density, shorten the length of the electron beam channel, and improve efficiency. Thus, the MSB-FW slow-wave structure contributes to the performance of the TWT especially in THz *** basic principle and working mechanism of the MSB-FW slow-wave structure are introduced firstly. Previous studies have been more detailed in the analysis of dual-pencil-beam or multi-pencil-beam. However, the analysis of Multi-Sheet-Beam has not yet been fully developed. Therefore, a method based on equivalent circuits to analyze the MSB-FW slow-wave structure is proposed. Based on microwave transmission line theory, the method has converted the MSB-FW slow-wave structure into equivalent microwave networks. Transmission line theory and microwave network analysis techniques are used for modelling and analysis. The equivalent circuit approach is used to analyze dispersion characteristics of MSB-FW slow-wave structure through rational selections of equivalent component parameters and *** results indicate that the dispersion curves obtained from the theoretical results and the simulation results are consistent. This verifies the accuracy and reliability of the equivalent circuit analysis method and lays a foundation for the design of MSB-FW TWT.

关键词： Electromagnetic heating Simulation Reliability theory Microwave theory and techniques Microwave circuits Microwave amplifiers Transmission line theory

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Overview and Assessment Approaches of Energy Consumption and GHG Emissions Through the Development and Application of Artificial Intelligence - An Example from the Agricultural Sector

Overview and Assessment Approaches of Energy Consumption and...

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2024 IEEE International Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2024

作者： Rilling, Stefan Henningsen, Jens Milde, Katharina Martini, Daniel Wickert, Lorenz Kelbert, Patricia Fraunhofer Institute for Intelligent Analysis and Information Systems Iais Adaptive Reflective Teams Sankt Augustin Germany Fraunhofer Institute for Experimental Software Engineering Iese Data Science Kaiserslautern Germany Advisory Board for Technology and Construction in Agriculture Ktbl Team Digital Technologies Darmstadt Germany

ISBN: (纸本)9798350355444

关键词： Crops

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