检索结果-内蒙古大学图书馆

22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Liang, Jiale Ma, Xiaowei Ding, Houjian He, Zhenli Co. Ltd China Yunnan University Yunnan Key Laboratory of Software Engineering Kunming China Yunnan University School of Software Kunming650504 China

ISBN: (纸本)9798331509712

This paper investigates the performance of Mobile Edge Computing (MEC) systems using the M/M/m queuing model, focusing on how server configurations and queuing rules affect task response times on edge servers. The study considers two types of tasks with different processing requirements: special tasks and general tasks. The study analyzes the response time under two queuing rules: first-come-first-served (FCFS) and head-of-line (HOL) priority. By evaluating the impact of server execution speed and the number of cores, this work provides insights for optimizing task scheduling and resource management in MEC environments, which ultimately improves system performance and reduces latency. © 2024 IEEE.

关键词： Queueing theory

来源：评论

学校读者我要写书评

暂无评论

Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP 39

Text and Image Are Mutually Beneficial: Enhancing Training-F...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Li, Yayuan Guo, Jintao Qi, Lei Li, Wenbin Shi, Yinghuan National Key Laboratory for Novel Software Technology Nanjing University China School of Computer Science and Engineering Southeast University China

ISBN: (纸本)157735897X

Contrastive Language-Image Pretraining (CLIP) has been widely used in vision tasks. Notably, CLIP has demonstrated promising performance in few-shot learning (FSL). However, existing CLIP-based methods in training-free FSL (i.e., without the requirement of additional training) mainly learn different modalities independently, leading to two essential issues: 1) severe anomalous match in image modality;2) varying quality of generated text prompts. To address these issues, we build a mutual guidance mechanism, that introduces an Image-Guided-Text (IGT) component to rectify varying quality of text prompts through image representations, and a Text-Guided-Image (TGI) component to mitigate the anomalous match of image modality through text representations. By integrating IGT and TGI, we adopt a perspective of Text-Image Mutual guidance Optimization, proposing TIMO. Extensive experiments show that TIMO significantly outperforms the state-of-the-art (SOTA) training-free method. Additionally, by exploring the extent of mutual guidance, we propose an enhanced variant, TIMO-S, which even surpasses the best training-required methods by 0.33% with approximately ×100 less time cost. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

EF-IMR: Embedded Flash with Interlaced Magnetic Recording Technology

EF-IMR: Embedded Flash with Interlaced Magnetic Recording Te...

引用

2025 Design, Automation and Test in Europe Conference, DATE 2025

作者： Ma, Chenlin Zheng, Xiaochuan Sun, Kaoyi Wang, Tianyu Wang, Yi College of Computer Science and Software Engineering Shenzhen University China State Key Laboratory of Radio Frequency Heterogeneous Integration China

ISBN: (纸本)9783982674100

Interlaced Magnetic Recording (IMR), a technology that improves storage density through track overlap, introduces significant latency due to Read-Modify-Write (RMW) operations. Writing to overlapped tracks affects underlying tracks, requiring additional I/O operations to read, back up, and rewrite them, resulting in significant head movement latency. We propose EF-IMR, a new architecture that ensures crash consistency in IMR while minimizing RMW latency and head movement. EF-IMR reduces head movement during RMW operations and decreases redundant RMW operations. Evaluations under real-world, intensive I/O workloads show that EF-IMR reduces RMW latency by 20.11 % and head movement latency by 89.37% compared to existing methods. © 2025 EDAA.

关键词： Magnetic tape storage

来源：评论

学校读者我要写书评

暂无评论

UKF‐MOT:An unscented Kalman filter‐based 3D multi‐object tracker

引用

CAAI Transactions on Intelligence Technology 2024年第4期9卷 1031-1041页

作者： Meng Liu Jianwei Niu Yu Liu Collective Intelligence&Collaboration Laboratory China North Artificial Intelligence and Innovation Research InstituteBeijingChina China North Vehicle Research Institute BeijingChina State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijingChina State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijingChina School of Computer Science and Engineering Beihang UniversityBeijingChina

Multi‐object tracking in autonomous driving is a non‐linear *** better address the tracking problem,this paper leveraged an unscented Kalman filter to predict the object's *** the association stage,the Mahalanobis distance was employed as an affinity metric,and a Non‐minimum Suppression method was designed for *** the detections fed into the tracker and continuous‘predicting‐matching’steps,the states of each object at different time steps were described as their own continuous *** conducted extensive experiments to evaluate tracking accuracy on three challenging datasets(KITTI,nuScenes and Waymo).The experimental results demon-strated that our method effectively achieved multi‐object tracking with satisfactory ac-curacy and real‐time efficiency.

关键词： autonomous vehicle transportation

来源：评论

学校读者我要写书评

暂无评论

keyword extraction method based on complex network

引用

International Journal of Information and Communication Technology 2024年第4期25卷 323-335页

作者： Yang, Zhen Gong, Huajian Ma, Weiyun Yin, Chunlin Li, Jie Liu, Siyang Zhu, Hua Zhao, Na Electric Power Research Institute of Yunnan Power Grid Kunming650217 China School of Computer Science and Technology Xidian University Xian710000 China Key Laboratory in Software Engineering of Yunnan Province School of Software Yunnan University Kunming650091 China

keyword extraction has a wide range of applications in the field of natural language processing. Many research results on keyword extraction at present. Among them, keyword extraction methods are based on complex networks do not require a lot of data training in advance and are simple to implement. This paper analyses and realises the application of complex network theory in the Chinese news keyword extraction task. We collected and analysed 2,061 news texts from Sina website as experimental data, and found that the number of keywords extracted affected the performance of keyword extraction method. We also compared the performance of our algorithm with other keyword extraction algorithms. The experiments verify the accuracy and effectiveness of complex networks in keyword extraction of Chinese news texts. Based on PyQt and TextRank, a news text keyword analysis platform is constructed to realise the visualisation of text network and the extraction of Chinese news keywords Copyright © 2024 Inderscience Enterprises Ltd.

关键词： complex network keyword extraction text network TextRank

来源：评论

学校读者我要写书评

暂无评论

Numerical simulation of formaldehyde distribution characteristics in the high-speed train cabin

引用

Building Simulation 2024年第2期17卷 285-300页

作者： Fan Wu Hang Dong Chao Yu Hengkui Li Qingmin Cui Renze Xu Key Laboratory of Traffic Safety on Track Ministry of EducationSchool of Traffic&Transportation EngineeringCentral South UniversityChangshaHunan410075China Joint International Research Laboratory of Key Technologies for Rail Traffic Safety ChangshaHunan410075China National&Local Joint Engineering Research Center of Safety Technology for Rail Vehicle ChangshaHunan410075China School of Software Henan University of EngineeringZhengzhouHenan451191China

The global concern over indoor air pollution in public vehicles has grown *** a focus on enhancing passengers’comfort and health,this study endeavors to investigate the distribution characteristics of formaldehyde within a high-speed train cabin by employing a computational fluid dynamics(CFD)model which is experimentally validated in a real cabin *** research focuses on analyzing the impact of air supply modes,temperature,relative humidity,and fresh air change rate on the distribution and concentration of *** results demonstrate that the difference in average formaldehyde concentration between the two air supply modes is below 1.3%,but the top air supply mode leads to a higher accumulation of formaldehyde near the sidewalls,while the bottom air supply mode promotes a more uniform distribution of ***,the temperature,relative humidity,and fresh air change rate are the primary factors affecting formaldehyde concentration levels,but they have modest effects on formaldehyde’s distribution pattern within the *** the temperature and relative humidity increase,the changes in formaldehyde concentrations in response to variations in these factors become more ***,the formaldehyde concentration may surpass the standard limit of 0.10 mg/m^(3)if the fresh air change rate falls below 212 m^(3)/*** research provides a systematic approach and referenceable results for exploring formaldehyde pollution in high-speed train cabins.

关键词： indoor air pollution formaldehyde CFD simulation high-speed train ventilation

来源：评论

学校读者我要写书评

暂无评论

Neighborhood Subgraph-based Illicit Transaction Detection in Cryptocurrency Networks 12

Neighborhood Subgraph-based Illicit Transaction Detection in...

引用

12th IEEE International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2024

作者： Jin, Shenghao Yang, Qiwen Chen, Shengyu Zhang, Hui Beihang University State Key Laboratory of Complex & Critical Software Environment School of Computer Science & Engineering Beijing China

ISBN: (纸本)9798331510633

With the widespread adoption of cryptocurrencies, associated illicit activities such as money laundering, fraud, extortion, and Ponzi schemes have garnered significant attention. Traditional studies have extensively employed graph neural network technologies to identify illicit transactions, typically treating the entire transaction network as input to classify its nodes. Although these methods perform well on small-scale networks, they face performance limitations when processing large-scale blockchain transaction data. To address this issue, we propose a neighborhood subgraph-based method for detecting illicit transactions, integrating GCN and LSTM. In this approach, the GCN captures and integrates information from adjacent nodes for each transaction, facilitating a deep understanding of network structures. The LSTM is tasked with capturing the sequence and variations in fund flows, effectively tracking the direction and temporal characteristics of the money flow. Experimental results indicate that when using 3-hop neighborhood subgraphs, our model's performance surpasses other GCN-based methods. Compared to previous models that require considering the entire transaction network, our approach only needs to utilize information from an average of 80 nodes, significantly improving efficiency. © 2024 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

SCaR: Refining Skill Chaining for Long-Horizon Robotic Manipulation via Dual Regularization 38

SCaR: Refining Skill Chaining for Long-Horizon Robotic Manip...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Chen, Zixuan Ji, Ze Huo, Jing Gao, Yang State Key Laboratory for Novel Software Technology Nanjing University China School of Engineering Cardiff University United Kingdom

Long-horizon robotic manipulation tasks typically involve a series of interrelated sub-tasks spanning multiple execution stages. Skill chaining offers a feasible solution for these tasks by pre-training the skills for each sub-task and linking them sequentially. However, imperfections in skill learning or disturbances during execution can lead to the accumulation of errors in skill chaining process, resulting in execution failures. In this paper, we investigate how to achieve stable and smooth skill chaining for long-horizon robotic manipulation tasks. Specifically, we propose a novel skill chaining framework called Skill Chaining via Dual Regularization (SCaR). This framework applies dual regularization to sub-task skill pre-training and fine-tuning, which not only enhances the intra-skill dependencies within each sub-task skill but also reinforces the inter-skill dependencies between sequential sub-task skills, thus ensuring smooth skill chaining and stable long-horizon execution. We evaluate the SCaR framework on two representative long-horizon robotic manipulation simulation benchmarks: IKEA furniture assembly and kitchen organization. Additionally, we conduct a simple real-world validation in tabletop robot pick-and-place tasks. The experimental results show that, with the support of SCaR, the robot achieves a higher success rate in long-horizon tasks compared to relevant baselines and demonstrates greater robustness to perturbations. © 2024 Neural information processing systems foundation. All rights reserved.

关键词：

来源：评论

学校读者我要写书评

暂无评论

FIFAWC:a dataset with detailed annotation and rich semantics for group activity recognition

引用

Frontiers of Computer Science 2024年第6期18卷 271-272页

作者： Duoxuan PEI Di HUANG Yunhong WANG State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Intelligent Recognition and Image Processing Lab. School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

1 *** Activity Recognition(GAR),which aims to identify activities performed collectively in videos,has gained significant attention *** conventional action recognition centered on single individuals,GAR explores the c... 详细信息

关键词： has collective gained

来源：评论

学校读者我要写书评

暂无评论

Coca: Improving and Explaining Graph Neural Network-Based Vulnerability Detection Systems 24

Coca: Improving and Explaining Graph Neural Network-Based Vu...

引用

44th ACM/IEEE International Conference on software engineering, ICSE 2024

作者： Cao, Sicong Sun, Xiaobing Wu, Xiaoxue Lo, David Bo, Lili Li, Bin Liu, Wei Singapore Management University Singapore Yangzhou University Yangzhou China Yunnan Key Laboratory of Software Engineering Yunnan China

ISBN: (纸本)9798400702174

Recently, Graph Neural Network (GNN)-based vulnerability detection systems have achieved remarkable success. However, the lack of explainability poses a critical challenge to deploy black-box models in security-related domains. For this reason, several approaches have been proposed to explain the decision logic of the detection model by providing a set of crucial statements positively contributing to its predictions. Unfortunately, due to the weakly-robust detection models and suboptimal explanation strategy, they have the danger of revealing spurious correlations and redundancy issue. In this paper, we propose Coca, a general framework aiming to 1) enhance the robustness of existing GNN-based vulnerability detection models to avoid spurious explanations;and 2) provide both concise and effective explanations to reason about the detected vulnerabilities. Coca consists of two core parts referred to as Trainer and Explainer. The former aims to train a detection model which is robust to random perturbation based on combina-torial contrastive learning, while the latter builds an explainer to derive crucial code statements that are most decisive to the detected vulnerability via dual-view causal inference as explanations. We apply Coca over three typical GNN-based vulnerability detectors. Experimental results show that Coca can effectively mitigate the spurious correlation issue, and provide more useful high-quality explanations. © 2024 ACM.

关键词： Graph neural networks

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：