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Knowledge Graph Representation Learning based on Entity Semantic Distance Classification

computer-Aided Design and Applications 2024年第S7期21卷 256-269页

作者： Zhang, Yi Cao, Wanhua Liu, Juntao Wang, Yuanbin Rao, Ziyun College of Computer Science and Technology Harbin Engineering University Harbin China Wuhan Digital Engineering Research Institute Wuhan China

In recent years, significant progress has been made in knowledge graph representation learning, which has shown promising results in knowledge computing applications such as relation extraction and knowledge reasoning. However, the unbalanced distribution of relations and entities in knowledge graphs leads to low training efficiency. To address this issue, this paper proposes a novel knowledge representation learning method based on entity distance classification. This method classifies entities based on their semantic distance on a specific relational plane, and employs different training strategies to increase the training opportunities for entities with low semantic distance differentiation. Moreover, the loss function is adjusted by introducing different residual weights, which allows for the allocation of different training opportunities to negative samples. The effectiveness of our approach is demonstrated by comparing it with mainstream knowledge representation models on various benchmark datasets. © 2024 U-turn Press LLC,.

关键词： Knowledge graph

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Performance issue monitoring, identification and diagnosis of SaaS software:a survey

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Frontiers of computer science 2025年第1期19卷 71-95页

作者： Rui WANG Xiangbo TIAN Shi YING College of Mining and Safety Engineering Shandong University of Science and TechnologyQingdao 266590China School of Computer Science Wuhan UniversityWuhan 430072China

SaaS (Software-as-a-Service) is a service model provided by cloud computing. It has a high requirement for QoS (Quality of Software) due to its method of providing software service. However, manual identification and diagnosis for performance issues is typically expensive and laborious because of the complexity of the application software and the dynamic nature of the deployment environment. Recently, substantial research efforts have been devoted to automatically identifying and diagnosing performance issues of SaaS software. In this survey, we comprehensively review the different methods about automatically identifying and diagnosing performance issues of SaaS software. We divide them into three steps according to their function: performance log generation, performance issue identification and performance issue diagnosis. We then comprehensively review these methods by their development history. Meanwhile, we give our proposed solution for each step. Finally, the effectiveness of our proposed methods is shown by experiments.

关键词： SaaS software performance log generation performance issue identification performance issue diagnosis

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DAUNet: Detail-Aware U-Shaped Network for 2D Human Pose Estimation

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computers, Materials & Continua 2024年第11期81卷 3325-3349页

作者： Xi Li Yuxin Li Zhenhua Xiao Zhenghua Huang Lianying Zou College of Information and Artificial Intelligence Nanchang Institute of Science and TechnologyNanchang330108China School of Electrical and Information Engineering Wuhan Institute of TechnologyWuhan430205China School of Computer Science and Technology Hubei Business CollegeWuhan430079China

Human pose estimation is a critical research area in the field of computer vision,playing a significant role in applications such as human-computer interaction,behavior analysis,and action *** this paper,we propose a U-shaped keypoint detection network(DAUNet)based on an improved ResNet subsampling structure and spatial grouping *** network addresses key challenges in traditional methods,such as information loss,large network redundancy,and insufficient sensitivity to low-resolution *** is composed of three main ***,we introduce an improved BottleNeck block that employs partial convolution and strip pooling to reduce computational load and mitigate feature ***,after upsampling,the network eliminates redundant features,improving the overall ***,a lightweight spatial grouping attention mechanism is applied to enhance low-resolution semantic features within the feature map,allowing for better restoration of the original image size and higher *** results demonstrate that DAUNet achieves superior accuracy compared to most existing keypoint detection models,with a mean PCKh@0.5 score of 91.6%on the MPII dataset and an AP of 76.1%on the COCO ***,real-world experiments further validate the robustness and generalizability of DAUNet for detecting human bodies in unknown environments,highlighting its potential for broader applications.

关键词： Human pose estimation keypoint detection U-shaped network architecture spatial grouping mechanism

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Hybrid IT? Algorithm for Large-Scale Colored Traveling Salesman Problem

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Chinese Journal of Electronics 2024年第6期33卷 1337-1345页

作者： Xueshi DONG College of Computer Science and Technology Qingdao University Beijing Key Laboratory of Urban Spatial Information Engineering School of Computer Science Wuhan University

In the fields of intelligent transportation and multi-task cooperation, many practical problems can be modeled by colored traveling salesman problem(CTSP). When solving large-scale CTSP with a scale of more than 1000dimensions, their convergence speed and the quality of their solutions are limited. This paper proposes a new hybrid IT?(HIT?) algorithm, which integrates two new strategies, crossover operator and mutation strategy, into the standard IT?. In the iteration process of HIT?, the feasible solution of CTSP is represented by the double chromosome coding, and the random drift and wave operators are used to explore and develop new unknown regions. In this process, the drift operator is executed by the improved crossover operator, and the wave operator is performed by the optimized mutation strategy. Experiments show that HIT? is superior to the known comparison algorithms in terms of the quality solution.

关键词： Transportation Traveling salesman problems Multitasking Encoding Standards Biological cells Convergence

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Existence and uniqueness of mean field equilibrium in continuous bandit game

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science China(Information sciences) 2025年第3期68卷 395-396页

作者： Xiong WANG Yuqing LI Riheng JIA School of Computer Science and Technology Huazhong University of Science and Technology School of Cyber Science and Engineering Wuhan University Wuhan University Shenzhen Research Institute School of Computer Science and Technology Zhejiang Normal University

Multiarmed bandit(MAB) models are widely used for sequential decision-making in uncertain environments, such as resource allocation in computer communication systems.A critical challenge in interactive multiagent systems with bandit feedback is to explore and understand the equilibrium state to ensure stable and tractable system performance.

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Constructal design of a rectangular parallel phase change microchannel in a three-dimensional electronic device

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science China(Technological sciences) 2024年第5期67卷 1381-1390页

作者： ZHANG JiWen FENG HuiJun CHEN LinGen GE YanLin Institute of Thermal Science and Power Engineering Wuhan Institute of TechnologyWuhan430205China College of Power Engineering Naval University of EngineeringWuhan430033China Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment Wuhan430205China School of Mechanical&Electrical Engineering Wuhan Institute of TechnologyWuhan430205China

Based on constructal theory,a rectangular parallel phase change microchannel model in a three-dimensional electronic device(TDED)is established with R134a as the cooling *** on the minimization of a complex function(CF)composed of linear weighting sum of maximum temperature difference and pumping power consumption,constructal design of the TDED is conducted first;and then,maximum temperature difference and pumping power consumption are minimized by non-dominated sorting genetic algorithm-II *** results reveal that there exist an optimal mass flow rate(0.0012 kg/s)and a quadratic optimal aspect ratio(AR)(0.39)of the microchannel which lead to quadratic minimum CF(0.817).Compared with the original value,the CF after optimization is reduced by 18.34%.Reducing the inlet temperature of cooling fluid and microchannel number appropriately can help to enhance the overall performance of *** using the artificial neural network and genetic algorithms in the toolboxes of Matlab software,the optimal AR gained in the Pareto solution set is located between 0.2–*** smallest deviation index among three discussed strategies is 0.346,and the corresponding optimal AR is 0.413,which is selected as the optimal design strategy of the microchannel in the TDED under multiple *** findings in this study can serve as theoretical guides for thermal designs of electronic devices.

关键词： constructal theory parallel microchannel evaporation phase change three-dimensional electronic device multi-objective optimization artificial neural network

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Constructal design of a rectangular porous fin considering minimization of maximum temperature difference and pumping power consumption

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science China(Technological sciences) 2024年第3期67卷 919-929页

作者： LIU XiaoYe FENG HuiJun CHEN LinGen GE YanLin Institute of Thermal Science and Power Engineering Wuhan Institute of TechnologyWuhan 430205China College of Power Engineering Naval University of EngineeringWuhan 430033China Hubei Provincial Engineering Technology Research Center of Green Chemical Equipment Wuhan 430205China School of Mechanical&Electrical Engineering Wuhan Institute of TechnologyWuhan 430205China

A heat dissipation model of a rectangular porous fin is established based on constructal theory. First, the constructal design of rectangular porous fin is conducted by selecting a complex function minimization, which composed of linear weighting sum of maximum temperature difference and pumping power consumption, as optimization objective. Effects of gap height, air inlet velocity, total porous fin volume and porosity on the optimal constructs are investigated, respectively. The findings show that the complex function can attain its double minimum at a value of 0.802 when the fin length and number are optimized, and the corresponding optimal fin length and number are 8.01 mm and 10, respectively. In comparison to original design, the complex function and maximum temperature difference after twice optimization are decreased by 19.80% and 66.31%, ***, the comprehensive performance of porous fin is improved by simultaneously optimizing the fin length and number. The artificial neural network is applied to predict the fin performances, which is used to conduct multi-objective optimization based on NSGA-II algorithm. Optimal structure of porous fin for multiple requirements is gained by LINMAP and TOPSIS decisionmaking strategies. The findings in this study can serve as theoretical guides for fin thermal designs of electronic devices.

关键词： constructal theory rectangular porous fin pumping power consumption maximum temperature difference complex function multi-objective optimization

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MLRT-UNet:An Efficient Multi-Level Relation Transformer Based U-Net for Thyroid Nodule Segmentation

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computer Modeling in engineering & sciences 2025年第4期143卷 413-448页

作者： Kaku Haribabu Prasath R Praveen Joe IR Department of Computer Science and Engineering RMK College of Engineering and TechnologyTiruvallur601206India School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India

Thyroid nodules,a common disorder in the endocrine system,require accurate segmentation in ultrasound images for effective diagnosis and ***,achieving precise segmentation remains a challenge due to various factors,including scattering noise,low contrast,and limited resolution in ultrasound *** existing segmentation models have made progress,they still suffer from several limitations,such as high error rates,low generalizability,overfitting,limited feature learning capability,*** address these challenges,this paper proposes a Multi-level Relation Transformer-based U-Net(MLRT-UNet)to improve thyroid nodule *** MLRTUNet leverages a novel Relation Transformer,which processes images at multiple scales,overcoming the limitations of traditional encoding *** transformer integrates both local and global features effectively through selfattention and cross-attention units,capturing intricate relationships within the *** approach also introduces a Co-operative Transformer Fusion(CTF)module to combine multi-scale features from different encoding layers,enhancing the model’s ability to capture complex patterns in the ***,the Relation Transformer block enhances long-distance dependencies during the decoding process,improving segmentation *** results showthat the MLRT-UNet achieves high segmentation accuracy,reaching 98.2% on the Digital Database Thyroid Image(DDT)dataset,97.8% on the Thyroid Nodule 3493(TG3K)dataset,and 98.2% on the Thyroid Nodule3K(TN3K)*** findings demonstrate that the proposed method significantly enhances the accuracy of thyroid nodule segmentation,addressing the limitations of existing models.

关键词： Thyroid nodules endocrine system multi-level relation transformer U-Net self-attention external attention co-operative transformer fusion thyroid nodules segmentation

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The ringed residual u-net with non-natural regions feature for image splicing forgery detection and localization

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 7447-7459页

作者： Wang, Qi Lu, Tongwei School of Computer Science and Engineering Wuhan Institute of Technology Wuhan China Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China

Recently, with the emergence of many image editing tools (photoshop, Topaz studio, etc.), the authenticity of images has been severely challenged. However, the performance of some existing traditional feature extraction methods and detection methods based on convolutional neural network (CNN) is poor, and the information provided by the features extracted from the network is limited and single. In this paper, an end-To-end ringed residual U-Net is proposed to detect image splicing forgery by blending features of non-natural regions. Some regions with significant differences from the image background are defined as non-natural regions(such as the irregular border at the splicing of images). In this paper, a feature enhancement module for non-natural regions is constructed, which the image through the pooling of four different scales, and these features are then combined with the original image and input to the backbone network for processing, aiming to highlight regions of the image that differ significantly from the background. Therefore, after adding the feature enhancement module for non-natural regions to the end-To-end ring residual U-Net, more attention will be paid to the tampering regions in the feature extraction stage, image manipulation detection and localization will also become more accurate. Compared with some mainstream methods, this method achieves better performance on the three standard datasets(CASIA2.0, NIST2016, COLUMBIA). In addition, it has excellent robustness under JPEG compression attack and noise corruption attack. © 2024-IOS Press. All rights reserved.

关键词： Topaz

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A Multi-Perspective Recommendation Model Based on Knowledge Graph 7

A Multi-Perspective Recommendation Model Based on Knowledge ...

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7th International Conference on Robotics, Control and Automation engineering, RCAE 2024

作者： Wang, Ziqi Zhang, Jun Wuhan Institute of Technology College of Computer Science and Engineering Wuhan China

ISBN: (纸本)9798350355642

A knowledge graph is a graph structure that represents and organizes knowledge, where nodes represent entities and edges represent the relationship between entities. The model uses the rich information in the knowledge graph, including entity properties, relationships, and semantic similarity, to improve the recommendation effect. However, the traditional knowledge graph is difficult to mine the user intention, so the recommendation effect is limited. In order to solve this problem, the MKGN model proposed in this paper transmits the collaboration signal and knowledge signal through the collaborative knowledge perception module, and then obtains the user and the project embedding through the knowledge attention mechanism;introduces the user interest into the potential vector of the interest module, builds the user-interest-item triplet, obtains the user and combines the user and the project embedding together for the final recommendation score. The model is compared with the baseline algorithm on two public datasets, and the model has better performance than the baseline algorithm model. © 2024 IEEE.

关键词： Knowledge graph

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