检索结果-内蒙古大学图书馆

Loop Subgraph-Level Greedy Mapping Algorithm for Grid Coarse-Grained Reconfigurable Array

Tsinghua science and Technology 2023年第2期28卷 330-343页

作者： Naijin Chen Fei Cheng Chenghao Han Jianhui Jiang Xiaoqing Wen School of Computer and Information Science Anhui Polytechnic UniversityWuhu 241000China School of Software Engineering Tongji UniversityShanghai 201804China Department of Computer Science and Networks Kyushu Institute of TechnologyFukuoka 820-8502Japan

To solve the problem of grid coarse-grained reconfigurable array task mapping under multiple constraints,we propose a Loop Subgraph-Level Greedy Mapping(LSLGM)algorithm using parallelism and processing element *** the constraint of a reconfigurable array,the LSLGM algorithm schedules node from a ready queue to the current reconfigurable cell array *** mapping a node,its successor’s indegree value will be dynamically *** its successor’s indegree is zero,it will be directly scheduled to the ready queue;otherwise,the predecessor must be dynamically *** the predecessor cannot be mapped,it will be scheduled to a blocking *** dynamically adjust the ready node scheduling order,the scheduling function is constructed by exploiting factors,such as node number,node level,and node *** with the loop subgraph-level mapping algorithm,experimental results show that the total cycles of the LSLGM algorithm decreases by an average of 33.0%(PEA44)and 33.9%(PEA_(7×7)).Compared with the epimorphism map algorithm,the total cycles of the LSLGM algorithm decrease by an average of 38.1%(PEA_(4×4))and 39.0%(PEA_(7×7)).The feasibility of LSLGM is verified.

关键词： Grid Coarse-Grained Reconfigurable Array(GCGRA) mapping loop subgraph scheduling

来源：评论

学校读者我要写书评

暂无评论

A Multimodal Multiobjective Evolutionary Algorithm for Filter Feature Selection in Multilabel Classification

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4428-4442页

作者： Hancer, Emrah Xue, Bing Zhang, Mengjie Victoria University of Wellington Center for Data Science and Artificial Intelligence School of Engineering and Computer Science Wellington6140 New Zealand Mehmet Akif Ersoy University Department of Software Engineering Burdur15039 Turkey

Multilabel learning is an emergent topic that addresses the challenge of associating multiple labels with a single instance simultaneously. Multilabel datasets often exhibit high dimensionality with noisy, irrelevant, and redundant features. In recent years, multilabel feature selection (MLFS) has gained prominence as a crucial and emerging machine learning task due to its ability to handle such data effectively. However, existing approaches for MLFS often prioritize top-ranked features based on intrinsic data criteria, disregarding relationships within the feature subset. Additionally, compared with conventional feature selection, multiobjective evolutionary algorithms (MOEAs) have not been widely explored in the context of MLFS. This study aims to address these gaps by proposing a multimodal multiobjective evolutionary algorithm (MMOEA) called MMDE_SICD which incorporates a preelimination scheme, an improved initialization scheme, an exploration scheme inspired by genetic operations and a statistically inspired crowding distance scheme. The results show that the proposed MMDE_SICD algorithm can outperform a variety of MOEAs and MMOEAs as well as conventional MLFS algorithms. Notably, this study is the first of its kind to consider MLFS as a multimodal multiobjective problem. © 2020 IEEE.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

BMLP:behavior-aware MLP for heterogeneous sequential recommendation

引用

Frontiers of computer science 2024年第3期18卷 235-237页

作者： Weixin LI Yuhao WU Yang LIU Weike PAN Zhong MING College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518123China

1 Introduction Recommender systems can effectively alleviate the problem of information ***,traditional recommendation methods cannot capture users’dynamic *** recommendation methods model user sequences to obtain more accurate and dynamic user ***,deep learning-based sequential recommendation methods have achieved great *** is proposed to capture the sequential information[1,2].Attention-based methods[3]use attention mechanisms to learn relationships between ***-based methods[4−6]transform sequences into graph structures to capture relationships of ***,they have the following two limitations.

关键词： sequences behavior sequential

来源：评论

学校读者我要写书评

暂无评论

Early Detection of Cyber-Physical Attacks on Electric Vehicles Fast Charging Stations Using Wavelets and Deep Learning

IEEE Transactions on Industrial Cyber-Physical Systems

引用

IEEE Transactions on Industrial Cyber-Physical Systems 2024年 2卷 220-231页

作者： Abu-Nassar, Ahmad M. Morsi, Walid G. Electrical Computer and Software Engineering Department Faculty of Engineering and Applied Science OshawaONL1G 0C5 Canada

Transportation electrification plays an important role in the operation of the smart grid through the integration of the electric vehicle fast charging stations (EVFCSs), which allows the electric vehicles to provide regulation services to the grid through the vehicle-to-grid (V2G) concept. However, such an integration makes smart grid assets prone to cyber vulnerability threats. In this paper, a cyber-physical attack detection approach is developed to early detect such attacks. The proposed approach combines the continuous wavelet transform (CWT) and the convolution neural network (CNN) to provide an effective detection technique. The proposed detection approach has undergone rigorous testing that considered 420 realistic operational scenarios. Unlike in previous work, the proposed detection approach was found to be effective in automatically learning the salient features from the data as well as identifying the frequency bands that hold such features and using them in the classification process. Furthermore, this work investigated the cyber-attack detection accuracy using different time resolutions of smart meters. The results have shown that the proposed approach effectively detects cyber-physical attacks with an accuracy of 99.76% and a low computational time of 1.8 seconds. © 2024 IEEE.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Dynamic Routing of Multiple QoS-Required Flows in Cloud-Edge Autonomous Multi-Domain Data Center Networks

引用

computers, Materials & Continua 2024年第2期78卷 2287-2308页

作者： Shiyan Zhang Ruohan Xu Zhangbo Xu Cenhua Yu Yuyang Jiang Yuting Zhao School of Computer Science(National Pilot Software Engineering School) Beijing University of Posts and TelecommunicationsBeijing100876China College of Computer Science and Technology Tianjin UniversityTianjin300072China Institute of Artificial Intelligence Nankai UniversityTianjin300071China College of Information Science and Engineering East China University of Science and TechnologyShanghai200237China

The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and *** this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain *** to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward *** the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the *** addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+*** a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network *** LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.

关键词： Multi-Domain data center networks autonomous routing

来源：评论

学校读者我要写书评

暂无评论

Understanding Blockchain Trilemma, Causes and Solutions 17

Understanding Blockchain Trilemma, Causes and Solutions

引用

IEEE Congress on Cybermatics: 17th IEEE International Conference on Internet of Things, iThings 2024, 20th IEEE International Conference on Green Computing and Communications, GreenCom 2024, 17th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2024, 10th IEEE International Conference on Smart Data, SmartData 2024

作者： Chaudhary, Monu Bhunia, Suman Miami University Department of Computer Science and Software Engineering OxfordOH United States

ISBN: (纸本)9798350351637

With extensive research and development in blockchain technology, the concern about scalability, security, and decentralization is still evident. Blockchain trilemma describes that it is realistically impossible to simultaneously achieve a high level of decentralization, security, and scalability. However, new developments in the sector of blockchain are making progress in simultaneous achievement of these three aspects. Layer 1 blockchain is the base level of blockchain network architecture. It includes blockchain networks like Bitcoin, Ethereum, etc. However, the Layer 1 blockchain network faces scalability issues. Layer 2 blockchain is a network built on top of Layer 1 blockchain to help eliminate scalability issues. This paper presents a comparative analysis of Layer 1 and Layer 2 blockchain networks and different approaches to solving the blockchain trilemma in Layer 1 and Layer 2 blockchain networks. From the study, we found that Layer 2 blockchain networks are easier and faster to implement. © 2024 IEEE.

关键词： Blockchain Blockchain Trilemma Decentralization Scalability Security

来源：评论

学校读者我要写书评

暂无评论

Detection of Conspiracy vs. Critical Narratives and Their Elements using NLP 25

Detection of Conspiracy vs. Critical Narratives and Their El...

引用

25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024

作者： Albladi, Aish Seals, Cheryl D. Department of Computer Science and Software Engineering Auburn University AuburnAL United States

The growing use of digital media or social media has given a platform to the people to deliver their ideas and viewpoints openly. It is facilitating the rapid spread of contrasting opinions openly. Ultimately, this has developed echo chambers or polarized platforms. These platforms either encourage conspiracy theories or critical narratives. So, nowadays, it has become crucial for people to be aware of being part of such narratives. Moreover, it is also necessary for the organisations to identify the conspiracy creators or the ones who do not possess a conspiracy mentality. This can be made possible by the use of natural language processing techniques to do this task automatically. This study presents the solutions to the two most pressing challenges in today's era. The subtask one of this study provides a solution for the identification of conspiracy narratives and critical narratives using the BERT model. Our model achieved an MCC score of 0.80. Secondly, the other subtask helps to recognize the span of the topic relevant to the important constituents of both categories of oppositional narratives, i.e., agent, facilitator, victim, campaigner, objective, negative effect. The overall accuracy of the model is 95%. These models can be used for the development of an algorithm that can automatically classify the conspiracy theories and critical narratives. © 2024 Copyright for this paper by its authors.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Ethical Aspects of ChatGPT in software engineering Research

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2025年第2期6卷 254-267页

作者： Akbar, Muhammad Azeem Khan, Arif Ali Liang, Peng Lappeenranta-Lahti University of Technology Software Engineering Department Lappeenranta15210 Finland University of Oulu M3S Empirical Software Engineering Research Unit Oulu90014 Finland Wuhan University School of Computer Science Wuhan430072 China

ChatGPT can improve software engineering (SE) research practices by offering efficient, accessible information analysis, and synthesis based on natural language interactions. However, ChatGPT could bring ethical challenges, encompassing plagiarism, privacy, data security, and the risk of generating biased or potentially detrimental data. This research aims to fill the given gap by elaborating on the key elements: motivators, demotivators, and ethical principles of using ChatGPT in SE research. To achieve this objective, we conducted a literature survey, identified the mentioned elements, and presented their relationships by developing a taxonomy. Furthermore, the identified literature-based elements (motivators, demotivators, and ethical principles) were empirically evaluated by conducting a comprehensive questionnaire-based survey involving SE researchers. In addition, we employed an interpretive structure modeling approach to analyze the relationships between the ethical principles of using ChatGPT in SE research and develop a level-based decision model. We further conducted a cross-impact matrix multiplication applied to classification analysis to create a cluster-based decision model. These models aim to help SE researchers devise effective strategies for ethically integrating ChatGPT into SE research by following the identified principles by adopting the motivators and addressing the demotivators. The findings of this study will establish a benchmark for incorporating ChatGPT services in SE research with an emphasis on ethical considerations. © 2020 IEEE.

关键词： software engineering

来源：评论

学校读者我要写书评

暂无评论

A Multimodal Method for Semi-Biometric Information Based User Identification in AR and VR Applications

A Multimodal Method for Semi-Biometric Information Based Use...

引用

2024 IEEE International Performance, Computing, and Communications Conference, IPCCC 2024

作者： Li, Han Lyu, Ke Dossett, Owen Feng, Xianglong Miami University Department of Computer Science and Software Engineering Oxford45056 United Kingdom

ISBN: (纸本)9798350367942

Virtual Reality (VR) and Augmented Reality (AR) have witnessed a surge in popularity, revolutionizing various industries and enhancing user experiences. As these technologies continue to evolve, ensuring secure user identification becomes increasingly important. However, existing identification methods often come with vulnerabilities or require costly hardware implementations. To address these challenges, we propose a novel semi-biometric information-based user identification approach leveraging multimodal techniques. By analyzing the user's viewing patterns and gaze behavior in the runtime, we can accurately identify individuals. This approach offers a promising solution for seamless user identification in VR and AR applications, without compromising on user experience or requiring expensive hardware modifications. To verify the efficiency of our proposed algorithm, we test our algorithm using a public dataset, the result of which shows a high classification accuracy. Additionally, beyond traditional evaluation metrics, we perform a transferability test, demonstrating the adaptability of our solution to new scenarios with robust generality. © 2024 IEEE.

关键词： Biometrics

来源：评论

学校读者我要写书评

暂无评论

Neural Operator-Based Framework for Time Efficient Denoising of Displacement Fields in Ultrasound Elastography

Neural Operator-Based Framework for Time Efficient Denoising...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Zhu, Yihong Peng, Bo School of Computer Science and Software Engineering Southwest Petroleum University Chengdu610500 China

ISBN: (纸本)9781665410205

In ultrasound elastography, the noise present in the measured displacement fields has been a critical factor affecting the quality of the strain or elastic distribution reconstruction. Existing partial differential equation (PDE) based denoising algorithms can effectively remove noise to some extent but are limited by slow solving speeds. To address this challenge, we introduce a neural operator-based framework for denoising measured displacement fields in ultrasound elastography. By utilizing neural operators to learn a general solution operator for the denoising equation, the framework aims to achieve fast and accurate denoising of displacement fields. Experiments conducted on simulated data and tissue-mimicking phantom data demonstrate that this method performs comparably to traditional methods across various metrics. In particular, the proposed approach achieves processing speeds approximately 30 to 577 times faster than the finite difference method (FDM) in various data dimensions, making it a highly effective solution for rapid and scalable data processing in ultrasound elastography. © 2024 IEEE.

关键词： Ultrasonic applications

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：