检索结果-内蒙古大学图书馆

Developing new Mg alloy as potential bone repair material via constructing weak anode nano-lamellar structure

Journal of Magnesium and Alloys 2023年第1期11卷 154-175页

作者： Jinshu Xie Lele Wang Jinghuai Zhang Liwei Lu Zhi Zhang Yuying He Ruizhi Wu Key Laboratory of Superlight Material and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin150001China School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan411201China

The mechanics-corrosion and strength-ductility tradeoffs of magnesium(Mg)alloys have limited their applications in fields such as orthopedic ***,a fine-grain structure consisting of weak anodic nano-lamellar solute-enriched stacking faults(SESFs)with the average thickness of 8 nm and spacing of 16 nm is constructed in an as-extruded Mg96.9Y1.2Ho1.2Zn0.6Zr0.1(at.%)alloy,obtaining a high yield strength(YS)of 370 MPa,an excellent elongation(EL)of 17%,and a low corrosion rate of 0.30 mm y−1(close to that of high-pure Mg)in a uniform corrosion *** scanning Kelvin probe force microscopy(SKPFM),one-dimensional nanostructured SESFs are identified as the weak anode(∼24 mV)for the first *** excellent corrosion resistance is mainly related to the weak anodic nature of SESFs and their nano-lamellar structure,leading to the more uniform potential distribution to weaken galvanic corrosion and the release of abundant Y^(3+)/Ho^(3+)from SESFs to form a more protective film with an outer Ca_(10)(PO_(4))_(6)(OH)_(2)/Y_(2)O_(3)/Ho_(2)O_(3) layer(thickness percentage of this layer:72.45%).For comparison,the as-cast alloy containing block 18R long period stacking ordered(LPSO)phase and the heat-treated alloy with fine lamellar 18R-LPSO phase(thickness:80 nm,spacing:120 nm)are also studied,and the characteristics of SESFs and 18R-LPSO phase,such as the weak anode nature of the former and the cathode nature of the latter(37-90 mV),are distinguished under the same alloy ***,we put forward the idea of designing Mg alloys with high mechanical and anti-corrosion properties by constructing"homogeneous potential strengthening microstructure",such as the weak anode nano-lamellar SESFs structure.

关键词： Mg alloys Corrosion Solute-enriched stacking faults LPSO structure SKPFM Hydroxyapatite

来源：评论

学校读者我要写书评

暂无评论

ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with Mamba 16

ColorMamba: Towards High-quality NIR-to-RGB Spectral Transla...

引用

16th Asian Conference on Machine Learning, ACML 2024

作者： Zhai, Huiyu Jin, Guang Yang, Xingxing Kang, Guosheng School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China Department of Computer Science Hong Kong Baptist University Hong Kong

Translating NIR to the visible spectrum is challenging due to cross-domain complexities. Current models struggle to balance a broad receptive field with computational efficiency, limiting practical use. Although the Selective Structured State Space Model, especially the improved version, Mamba, excels in generative tasks by capturing long-range dependencies with linear complexity, its default approach of converting 2D images into 1D sequences neglects local context. In this work, we propose a simple but effective backbone, dubbed ColorMamba, which first introduces Mamba into spectral translation tasks. To explore global long-range dependencies and local context for efficient spectral translation, we introduce learnable padding tokens to enhance the distinction of image boundaries and prevent potential confusion within the sequence model. Furthermore, local convolutional enhancement and agent attention are designed to improve the vanilla Mamba. Moreover, we exploit the HSV color to provide multi-scale guidance in the reconstruction process for more accurate spectral translation. Extensive experiments show that our ColorMamba achieves a 1.02 improvement in terms of PSNR compared with the state-of-the-art method. Our code is available at https://***/AlexYangxx/ColorMamba/. © 2024 H. Zhai1, G. Jin1, X. Yang2 & G. Kang1.

关键词： RGB color model

来源：评论

学校读者我要写书评

暂无评论

Predicting circRNA-Disease Associations by Using Multi-Biomolecular Networks Based on Variational Graph Auto-Encoder with Attention Mechanism

引用

Chinese Journal of Electronics 2024年第6期33卷 1526-1537页

作者： Jing YANG Xiujuan LEI Yi PAN School of Computer Science Shaanxi Normal University Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology

CircRNA-disease association(CDA) can provide a new direction for the treatment of diseases. However,traditional biological experiment is time-consuming and expensive, this urges us to propose the reliable computational model to predict the associations between circRNAs and diseases. And there is existing more and more evidence indicates that the combination of multi-biomolecular information can improve the prediction accuracy. We propose a novel computational model for CDA prediction named MBCDA, we collect the multi-biomolecular information including circRNA, disease, miRNA and lncRNA based on 6 databases, and construct three heterogeneous network among them, then the multi-heads graph attention networks are applied to these three networks to extract the features of circRNAs and diseases from different views, the obtained features are put into variational graph auto-encoder(VGAE) network to learn the latent distributions of the nodes, a fully connected neural network is adopted to further process the output of VGAE and uses sigmoid function to obtain the predicted probabilities of circRNA-disease *** a result, MBCDA achieved the values of AUC and AUPR under 5-fold cross-validation of 0.893 and 0.887. MBCDA was applied to the analysis of the top-25 predicted associations between circRNAs and diseases, these experimental results show that our proposed MBCDA is a powerful computational model for CDA prediction.

关键词： Knowledge engineering Attention mechanisms Computational modeling Biological system modeling Predictive models Feature extraction Heterogeneous networks Topology Data mining Diseases

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale HSV Color Feature Embedding for High-Fidelity NIR-to-RGB Spectrum Translation

Multi-Scale HSV Color Feature Embedding for High-Fidelity NI...

引用

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

作者： Zhai, Huiyu Chen, Mo Yang, Xingxing Kang, Guosheng School of Computer Science and Engineering Hunan University of Science and Technology Xiangtan China Hong Kong Baptist University Department of Computer Science Hong Kong

ISBN: (纸本)9781665410205

This study investigates the actual impact of ChatGPT on human resource management (HRM) occupations and compares it with assessments from large language models (LLMs). Using data from the Occupational Information Network (O*NET), we developed a novel methodology combining real-world evidence from Google search results with evaluations from GPT-4, GPT-3.5, and Claude 3 Opus. Our findings reveal significant variations in the degree of exposure among HRM occupations. Training and Development Managers were the most exposed, with 86.52% of their tasks potentially automated by ChatGPT, while Labor Relations Specialists were the least exposed at 11.08%. Notably, LLM assessments consistently overestimated the exposure levels by an average of 30% compared to real-world evidence. This discrepancy highlights the importance of critically evaluating LLM capabilities in task automation. Our research contributes to understanding AI's impact on HRM practices and provides valuable insights for professionals adapting to the AI era. It also underscores the need for caution when relying solely on LLM assessments for workforce planning and development. © 2024 IEEE.

关键词： Human resource management

来源：评论

学校读者我要写书评

暂无评论

Image Fuzzy Enhancement Based on Membrane Computing Particle Swarm Optimization Algorithm

Journal of Network Intelligence

引用

Journal of Network Intelligence 2024年第2期9卷 658-672页

作者： Hou, Xiao-Mao Cai, Liu-Ping Wang, Yan-Hui Automation and Information Engineering College Hunan Chernical Vocational Technology College Zhuzhou412000 China Graduate School Department Saint Paul University Tuguegarao3500 Philippines School of Computer Science and Engineering Hunan University of Information Technology Changsha410151 China

Image fuzzy enhancement is a research hotspot in the field of image processing, which aims to recover enhanced beginning clear images from degraded images. Based on the research of traditional particle swarm optimization algorithm and fuzzy enhancement algorithm, an image fuzzy enhancement method based on membrane computing particle swarm algorithm is proposed. Firstly, in order to make full use of the sparse characteristics of the clear image, the coefficient decomposition under wavelet domain and tightly supported wavelet domain is performed on the image respectively. Then, a joint optimisation model is constructed using L1 parametric constraints to achieve pretzel noise cancellation. Next, the MMH-PSO algorithm is designed by improving the particle swarm algorithm using membrane computing and Metropolis-Hastings sampling. Based on the simulated annealing algorithm temperature drop process, Metropolis-Hastings sampling is used to add randomness to the particle swarm algorithm so that it has the ability to jump out of the local optimum. The use of membrane computing enhances the parallelism of the particle swarm algorithm and can reduce the time complexity in solving complex problems. Finally, MMH-PSO is used to simultaneously search out the magnitude of the two fuzzy parameters in the traditional fuzzy enhancement algorithm in order to improve the accuracy of the algorithm. The experimental results show that the proposed algorithm has better SSIM values than the traditional fuzzy enhancement algorithm, which effectively improves the image quality and makes the image edge information more abundant. © 2024, J. Network Intell. All rights reserved.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Network Traffic Anomaly Detection Based on DGBi-SA Model

引用

engineering Letters 2025年第3期33卷 612-619页

作者： Wang, Xin Dai, Hong Huang, Zheng Han, Yue University of Science and Technology Liaoning Liaoning CO Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Liaoning CO Anshan114051 China

Network traffic anomaly detection plays a crucial role in today's network security and performance management. In response to the challenges in current network traffic data processing, such as insufficient structuring and dynamics, the paper proposes a network traffic anomaly detection approach based on DGBi-SA model, which integrates Dynamic Graph Convolutional Networks (DyGCN), Bi-directional Long Short-Term Memory (Bi-LSTM), and the Self-Attention mechanism. To solve the problem of insufficient structuring, the model employs DyGCN to capture network traffic's dynamic graph structural characteristics proficiently. Simultaneously, combining Bi-LSTM and the Self-Attention mechanism enhances the model's ability to capture temporal and spatial dependencies. The main objective of the research in the paper is to improve the accuracy and detection efficiency of network traffic prediction, thereby achieving effective detection and timely response to abnormal behaviors in complex network environments. Through a sequence of experiments conducted on the CICIDS-2017 dataset, the paper verifies that the DGBi-SA model can effectively solve the above problems. The experimental results indicate that the model outperforms existing methods in key performance indicators such as AUC, precision, recall, and F1 score, thereby proving that the DGBi-SA model has important application value and scientific significance in network traffic anomaly detection. © 2025, International Association of Engineers. All rights reserved.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Two-Way Neural Network Performance PredictionModel Based onKnowledge Evolution and Individual Similarity

引用

computer Modeling in engineering & sciences 2024年第2期138卷 1183-1206页

作者： Xinzheng Wang Bing Guo Yan Shen College of Computer Science Sichuan UniversityChengdu610065China School of Information Science and Engineering Guilin University of TechnologyGuilin541004China School of Control Engineering Chengdu University of Information TechnologyChengdu610225China

Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,*** with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is *** makes building models to predict students’performance accurately in such an environment even *** paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course *** experiments on a real dataset show that our model performs better thanthe baselines in many indicators.

关键词： computer education performance prediction deep learning

来源：评论

学校读者我要写书评

暂无评论

An Efficient Virtual Channel Scheme Based on Multi-hop Payment Channel 10

An Efficient Virtual Channel Scheme Based on Multi-hop Payme...

引用

10th IEEE International Conference on Cyber Security and Cloud Computing and 9th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2023

作者： Li, Feng Liu, Yaqin Liang, Wei Xie, Songyou Yang, Yang Li, Yuhui Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China Hunan University College of Computer Science and Electronic Engineering Changsha China

ISBN: (纸本)9798350312461

The transaction throughput and confirmation time of the current mainstream blockchain cryptocurrency platform are far lower than those of traditional centralized trading platforms, which is difficult to meet the growing needs of users. Therefore, this paper proposes an efficient multi-hop off-chain Virtual Channel (VC) payment scheme to improve the confirmation speed of transactions by performing high-frequency and small transactions off-chain. The proposed scheme constructs a virtual channel scheme with dynamic selection [1], [2] through Hash Time-Lock Contract (HTLC) and constant collateral, and closes the virtual channel through on-chain settlement to ensure the balance security and atomicity of transactions. The proposed VC scheme is suitable for multi-hop Payment Channel (PC) networks, after the VC construction is completed, the transaction initiator and receiver directly conduct transactions through the virtual channel, ensuring the privacy of the transaction. Experimental analysis shows that the proposed scheme can resist a variety of malicious attacks and realize a rapid and safe transaction process. © 2023 IEEE.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

A systematic mapping to investigate the application of machine learning techniques in requirement engineering activities

引用

CAAI Transactions on Intelligence technology 2024年第6期9卷 1412-1434页

作者： Shoaib Hassan Qianmu Li Khursheed Aurangzeb Affan Yasin Javed Ali Khan Muhammad Shahid Anwar School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjingJiangsuChina Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadhSaudi Arabia School of Software Northwestern Polytechnical UniversityXianShaanxiChina Department of Computer Science School of PhysicsEngineering&Computer ScienceUniversity of HertfordshireHatfieldUK Department of AI and Software Gachon University Seongnam-siSeongnamSouth Korea

Over the past few years,the application and usage of Machine Learning(ML)techniques have increased exponentially due to continuously increasing the size of data and computing *** the popularity of ML techniques,only a few research studies have focused on the application of ML especially supervised learning techniques in Requirement engineering(RE)activities to solve the problems that occur in RE *** authors focus on the systematic mapping of past work to investigate those studies that focused on the application of supervised learning techniques in RE activities between the period of 2002–*** authors aim to investigate the research trends,main RE activities,ML algorithms,and data sources that were studied during this ***-five research studies were selected based on our exclusion and inclusion *** results show that the scientific community used 57 *** those algorithms,researchers mostly used the five following ML algorithms in RE activities:Decision Tree,Support Vector Machine,Naïve Bayes,K-nearest neighbour Classifier,and Random *** results show that researchers used these algorithms in eight major RE *** activities are requirements analysis,failure prediction,effort estimation,quality,traceability,business rules identification,content classification,and detection of problems in requirements written in natural *** selected research studies used 32 private and 41 public data *** most popular data sources that were detected in selected studies are the Metric Data Programme from NASA,Predictor Models in Software engineering,and iTrust Electronic Health Care System.

关键词： data sources machine learning requirement engineering supervised learning algorithms

来源：评论

学校读者我要写书评

暂无评论

A Survey of Knowledge Graph Construction Using Machine Learning

引用

computer Modeling in engineering & sciences 2024年第4期139卷 225-257页

作者： Zhigang Zhao Xiong Luo Maojian Chen Ling Ma School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China Shunde Innovation School University of Science and Technology BeijingFoshan528399China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083China

Knowledge graph(KG)serves as a specialized semantic network that encapsulates intricate relationships among real-world entities within a structured *** framework facilitates a transformation in information retrieval,transitioning it from mere string matching to far more sophisticated entity *** this transformative process,the advancement of artificial intelligence and intelligent information services is ***,the role ofmachine learningmethod in the construction of KG is important,and these techniques have already achieved initial *** article embarks on a comprehensive journey through the last strides in the field of KG via machine *** a profound amalgamation of cutting-edge research in machine learning,this article undertakes a systematical exploration of KG construction methods in three distinct phases:entity learning,ontology learning,and knowledge ***,a meticulous dissection of machine learningdriven algorithms is conducted,spotlighting their contributions to critical facets such as entity extraction,relation extraction,entity linking,and link ***,this article also provides an analysis of the unresolved challenges and emerging trajectories that beckon within the expansive application of machine learning-fueled,large-scale KG construction.

关键词： Knowledge graph(KG) semantic network relation extraction entity linking knowledge reasoning

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：