检索结果-内蒙古大学图书馆

Achieving high strength-ductility synergy in a Mg_(97)Y_(1)Zn_(1)Ho_(1) alloy via a nano-spaced long-period stacking-ordered phase

引用

Journal of Magnesium and Alloys 2023年第4期11卷 1321-1331页

作者： Mingyu Fan Ye Cui Yang Zhang Xinghao Wei Xue Cao Peter K.Liaw Yuansheng Yang Zhongwu Zhang Key Laboratory of Superlight Materials and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001PR China College of Computer Science and Technology Harbin Engineering UniversityHarbin 150001PR China Department of Materials Science and Engineering The University of TennesseeKnoxvilleTN 37996-2100USA Institute of Metal Research Chinese Academy of SciencesShenyang 110016PR China

Achieving high strength in Mg alloys is usually accompanied by ductility ***,a novel Mg97Y1Zn1Ho1 at.%alloy with a yield strength of 403 MPa and an elongation of 10%is *** strength-ductility synergy is obtained by a comprehensive strategy,including a lamella bimodal microstructure design and the introduction of nano-spaced solute-segregated 14H long-period stacking-ordered phase(14H LPSO phase)through rare-earth Ho *** lamella bimodal microstructure consists of elongated un-recrystallized(un-DRXed)coarse grains and fine dynamically-recrystallized grains(DRXed regions).The nano-spaced solute-segregated 14H LPSO phase is distributed in DRXed *** outstanding yield strength is mainly contributed by grain-boundary strengthening,18R LPSO strengthening,and fiberlike reinforcement strengthening from the nano-spaced 14H LPSO *** high elongation is due primarily to the combined effects of the bimodal and lamellar microstructures through enhancing the work-hardening capability.

关键词： Mg wrought alloy Mechanical properties Long-period stacking-ordered(LPSO)phase Age-strengthening behavior Strengthening mechanism

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Enabled Communication Approach for the Internet of Medical Things

引用

computers, Materials & Continua 2023年第8期76卷 1569-1584页

作者： Rahim Khan Abdullah Ghani Samia Allaoua Chelloug Mohammed Amin Aamir Saeed Jason Teo Faculty of Computing and Informatics University Malaysia SabahKota KinabaluSabah88400Malaysia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box84428Riyadh11671Saudi Arabia Department of Computer Science Abdul Wali Khan UniversityMardan23200Pakistan College of Computer Sciences and Information Technology King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Computer Science and IT UET PeshawarJalozai CampusJalozai24240Pakistan

The Internet ofMedical Things(IoMT)is mainly concernedwith the efficient utilisation of wearable devices in the healthcare domain to manage various processes automatically,whereas machine learning approaches enable these smart systems to make informed ***,broadcasting is used for the transmission of frames,whereas congestion,energy efficiency,and excessive load are among the common issues associated with existing *** this paper,a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames,especially with the minimum possible communication overheads in the IoMT *** this purpose,the proposed scheme utilises a well-known technique,i.e.,Kruskal’s algorithm,to find an optimal path from source to destination wearable ***,other evaluation metrics are used to find a reliable and shortest possible communication path between the two interested *** from that,every device is bound to hold a supplementary path,preferably a second optimised path,for situations where the current communication path is no longer available,either due to device failure or heavy ***,the machine learning approach helps enable these devices to update their routing tables simultaneously,and an optimal path could be replaced if a better one is *** proposed mechanism has been tested using a smart environment developed for the healthcare domain using IoMT *** results show that the proposed machine learning-oriented approach performs better than existing approaches where the proposed scheme has achieved the minimum possible ratios,i.e.,17%and 23%,in terms of end to end delay and packet losses,***,the proposed scheme has achieved an approximately 21%improvement in the average throughput compared to the existing schemes.

关键词： Machine learning Internet of Medical Things healthcare load balancing communication

来源：评论

学校读者我要写书评

暂无评论

Overlapping Community Detection Algorithm Based on Local Information

Overlapping Community Detection Algorithm Based on Local Inf...

引用

2023 International Conference on Cyber Security, Artificial Intelligence, and Digital Economy, CSAIDE 2023

作者： Zhang, Binchi Li, Zhiqiang Chongqing University of Posts and Telecommunications College of Computer Science and Technology Chongqing400065 China

ISBN: (纸本)9781510666597

There are many excellent community detection algorithms in the field of overlapping community detection, which can respond well to the needs of various scenarios, traditional community partition method due to excessive ignored the high computational cost brought by the use of global information, in the face of increasingly large scale appear struggling, this article hopes to local information using traditional community partition algorithm, combined with seed development principle, and experiment with human networks and real network data to get better community resultst. © 2023 SPIE.

关键词： Signal detection

来源：评论

学校读者我要写书评

暂无评论

Integrated Sliding Mode Fault- Tolerant Control for Dynamic Positioning T-S Fuzzy Models of Unmanned Marine Vehicles with Thruster Saturation 14

Integrated Sliding Mode Fault- Tolerant Control for Dynamic ...

引用

14th Asian Control Conference, ASCC 2024

作者： Wang, Yang Hao, Li-Ying Li, Tieshan Philip Chen, C.L. College of Navigation Dalian Maritime University Dalian China Marine Electrical Engineering College Dalian Maritime University Dalian China College of Automation Engineering University of Electronic Science and Technology of China Chengdu China College of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9789887581598

This research focuses on addressing the fault-tolerant control (FTC) issue in the context of Takagi-Sugeno (T-S) fuzzy models applied to unmanned marine vehicles (UMVs) with saturation phenomenon. Firstly, considering the saturation and faults of the thrusters, the corresponding T-S fuzzy models for UMV s are established. a novel strategy for integral sliding mode control (ISM C) is developed to address the impact of thruster faults, saturation and ocean disturbances. In contrast to conventional integral sliding mode approaches, this study simultaneously integrates thruster saturation and fault estimation information to construct the sliding surface, thereby reducing conservatism. Ultimately, the comparative simulations have show-cased the effectiveness of the proposed scheme. © 2024 Asian Control Association.

关键词： Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Bidirectional Identity-Based Inner-Product Functional Re-Encryption in Vaccine Data Sharing

引用

IEEE Transactions on Cloud Computing 2025年第2期13卷 617-628页

作者： Wang, Jing Zhou, Yanwei Zhu, Yasi Liu, Zhiquan Yang, Bo Zhang, Mingwu Shaanxi Normal University School of Computer Science Xi’an710119 China Sichuan University Key Laboratory of Data Protection and Intelligent Management Ministry of Education Chengdu610017 China Jinan University College of Cyber Security Guangzhou510632 China Hubei University of Technology School of Computer Wuhan430068 China

With the development of cloud computing, more and more data is stored in cloud servers, which leads to an increasing degree of privacy of data stored in cloud servers. For example, in the critical domain of medical vaccine trials, where public health outcomes hinge on the analysis of sensitive patient data, the imperative to safeguard privacy has never been more pronounced. Traditional encryption methods, though effective at protecting data, often expose vulnerabilities during decryption and lack the ability to support granular data access and computation. One-way re-encryption schemes further impede the agility of data sharing, which is indispensable for the collaborative efforts of research institutions. To address these limitations, we propose a novel bidirectional re-encryption scheme for inner-product functional encryption (IPFE). Our scheme secures data while allowing computation and sharing in an encrypted state, preserving patient privacy without hindering research. By harnessing inner-product functional encryption, our approach allows authorized researchers to extract valuable insights from encrypted data, significantly enhancing privacy protections. Our scheme’s security is predicated on the l-ABDHE (augmented bilinear Diffie-Hellman exponent) assumption, ensuring robustness against chosen plaintext attacks within the standard model. This foundation not only secures the data but also yields compact ciphertext length, minimizing storage demands. We introduce a protocol specifically designed for medical vaccine trials, which leverages our bidirectional IB-IPFRE (Identity-Based Inner-Product Functional Re-Encryption) scheme. This protocol enhances data security, supports collaborative research, and maintains patient privacy. Its application in vaccine trials demonstrates the scheme’s effectiveness in protecting sensitive information while enabling critical research insights. © 2013 IEEE.

关键词： Encryption Vaccines Data Privacy Iron Security Protection Vectors Protocols Cloud Computing Access Control Inner Product Function Encryption Identity Based Encryption CPA Security Bidirectional Re Encryption Data Sharing Research Institute Privacy Of Data Collaborative Research Data Security Sensitive Data Privacy Protection Patient Privacy Encrypted Data Chosen Plaintext Computational Cost Medical Data Vector Of Length Access Control Vector Production Original Information Secret Key Public Key Security Requirements Bilinear Map Decryption Process Key Generation Information Encryption Round Of Experiments Decryption Algorithm Encryption And Decryption Vaccine Information Evaluation Of Drug Efficacy Public Parameters Cryptographic Primitives

来源：评论

学校读者我要写书评

暂无评论

Deep Closest Point registration based on Hybrid Features 2

Deep Closest Point registration based on Hybrid Features

引用

2nd International Symposium on computer Applications and Information Systems, ISCAIS 2023

作者： An, Hongyan Li, Zhuo College of Computer Science and Cyber Security Chengdu University of Technology Chengdu610065 China

ISBN: (纸本)9781510666665

The core problem of point cloud registration can be explained as computing rigid transformations to align two point clouds, which is a key technology used in popular fields such as three-dimensional reconstruction, robotics, and autonomous driving. We come up with a hybrid feature-based model inspired by Deep Closest Point (DCP) and Robust Point Matching using Learned Features (RPMNET). The main innovation of this model is to combine abstract features extracted by Dynamic Graph CNN (DGCNN) with Point Pair Features (PPF) as hybrid features for point cloud registration, after that, soft matching is performed between two point clouds, and then singular value decomposition (SVD) is applied to compute the rigid transformations. Besides, we adopt the ModelNet40 dataset for training and compare the trained model with DCPV2, Iterative Closest Point (ICP) and some other ICP variants, the comparison of results indicates our model performs better than the above methods in predicting the angle of rotation when rigid transformations occur. We also test our model on clean and noise-added test sets respectively to verify the robustness of it. © 2023 SPIE.

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Sketch Less Face Image Retrieval: A New Challenge 48

Sketch Less Face Image Retrieval: A New Challenge

引用

48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023

作者： Dai, Dawei Li, Yutang Wang, Liang Fu, Shiyu Xia, Shuyin Wang, Guoyin Chongqing University of Posts and Telecommunications College of Computer Science and Technology Chongqing400065 China

ISBN: (纸本)9781728163277

In some specific scenarios, face sketch was used to identify a person. However, drawing a complete face sketch often needs skills and takes time, which hinder its widespread applicability in the practice. In this study, we proposed a new task named sketch less face image retrieval (SLFIR), in which the retrieval was carried out at each stroke and aim to retrieve the target face photo using a partial sketch with as few strokes as possible (see Fig. 1). Firstly, we developed a method to generate the data of sketch with drawing process, and opened such dataset;Secondly, we proposed a two-stage method as the baseline for SLFIR that (1) a triplet network, was first adopt to learn the joint embedding space shared between the complete sketch and its target face photo;(2) regarding the sketch drawing episode as a sequence, we designed a LSTM module to optimize the representation of the incomplete face sketch. Experiments indicate that the new framework can finish the retrieval using a partial or poor drawing sketch. (https://***/ddw2AIGROUP2CQUPT/SLFIR) © 2023 IEEE.

关键词： Face Sketch Partial Sketch Sequence Learning Sketch-Based Image Retrieval

来源：评论

学校读者我要写书评

暂无评论

Integrating Users’ Global and Local Interest for Session-based Recommendation

Integrating Users’ Global and Local Interest for Session-ba...

引用

2022 International Conference on computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2022

作者： Fang, Yiqiu Wu, Ning Ge, Junwei College of Computer Science & Technology Chongqing University of Posts and Telecommunications Chongqing400000 China

ISBN: (纸本)9781510663350

Conventional recommendation systems mostly recommend based on users’ global stable interest, while SR focuses on learning local active interest from the current session. Relevant research points out that integrating users’ global and local interest can improve model accuracy. However, most SR models are deficient in interest mining and fusion, and do not fully utilize the time interval content between sessions, result in inaccurate recommendations. In the paper, we propose a new session-based recommendation method called Global and Local Interest Integration Model (GLI-GNN). GLI-GNN introduces the concept of session time and attention mechanism to obtain global preferences from users’ previous sessions;it uses GNN to obtain local interest from current sessions;it uses attention mechanism to integrate both. The results indicate that GLI-GNN realizes new optimal performance in next-shot interactive recommendation. Experimental results show that GLI-GNN is superior to the existing SR models. © 2023 SPIE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Investigation of the Internet of Things to Track the Distribution Temperature of Transformers with Accounting Residential Loads

Investigation of the Internet of Things to Track the Distrib...

引用

Conference of Recent Trends and Applications of Soft Computing in Engineering, RTASCE 2024

作者： Mezaal, Yaqeen S. Abed, Faisal Theyab ALRubeei, Ibtihal R. Niama Alrikabi, Aday R. H. Salim ALRikabi, Haider Th. Mutar, Hussein A. Alaidi, Abdul Hadi M. Farhan, Mansour S. Obod, Ivan College of Engineering University of Information Technology and Communications Baghdad Iraq Electrical Engineering Department College of Engineering Wasit University Wasit Iraq Department of Physics College of Science Wasit University Wasit Iraq College of Computer Science and Information Technology Wasit University Wasit Iraq Kharkiv National University of Radio Electronics Kharkiv Ukraine

ISBN: (纸本)9783031828805

Commercial and industrial loads are relatively lighter than residential loads and have become lighter over the years as distribution transformer loads are affected by the rate of urbanization. When geared to provide distribution infrastructure that will supply electrical power in growing cities, it often struggles to meet the demand for power due to urbanization. This has compounded the issue of distribution transformers and their tendency to overheat. The impact between the residential load and the distribution transformer temperature in monitoring is approaching through the lens of the Internet of Things (IoT), which is the focus of this study. The distribution transformers’ optimum performance is essential for maximizing distribution network function as well as ensuring electric supply to residential areas. Fluctuations in residential loads also have an impact in changing the temperature of the transformers and this may, in the process, pose operational challenges as well as cause equipment failures. When many distribution transformers mounted with IoT temperature sensors are connected to a centralized management platform, temperature information can be captured and processed in real time. Today, it is possible to identify temperature anomalies that can speak about the presence of problems in the form of, for instance, overload or insulation damage in advance. Besides the understanding of the consumer demand profile, the utility can use the temperature data alongside the domestic load profile for the anticipation of the peak demand periods. Some of the outcomes observed when IoT technology is utilized for temperature monitoring include enhanced operating efficiency, reduced downtime, and enhanced product reliability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

Combining Extreme Learning Machine Through Random Projections for Dimensional Information Taxonomy and Assembling 1

Combining Extreme Learning Machine Through Random Projection...

引用

1st IEEE International Conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Altuwairiqi, Majid College of Computers and Information Technology Department of Computer Science Taif University Saudi Arabia

ISBN: (纸本)9798350345957

The Extreme Learning Machine (ELM) is a revolutionary feed-forward neural network learning technique that functions on a single hidden layer. It is based on the idea that the more information a neural network has, the better it can learn (SLFNs). It uses a random process to set the weights of the hidden neurons and uses the Moore-Penrose (MP) generalised inverse to analytically compute the weights of the output neurons. Both of these computations are done in parallel. ELM does not require iteration for the calculation of the SLFN parameters, in contrast to the sluggish gradient descent- based learning techniques that are typically used for SLFN. This is because the parameters for the hidden layer are initialised in a random manner and are maintained throughout the knowledge procedure. In addition, the output burdens are determined systematically. In most cases, this modification makes the input statistics more identifiable in the ELM topographies space, which makes it easier to solve the underlying or connected problems. In addition to its lightning-fast learning, the ELM algorithm also delivers outstanding results in terms of generalisation. This comes as a bonus to its lightning-fast learning. When classifying and clustering the data for this research article, we make use of ELM in conjunction with random projection (RP). It is conceivable that the choices could be cut in half. The first one is intended for use with enormous datasets, whereas the second one works much better with more limited ones. Building a small network with a strong generalization performance, while utilizing a limited neurons count in the secreted level is the goal of this research paper. © 2023 IEEE.

关键词： Lightning

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：