检索结果-内蒙古大学图书馆

Multi-phase-field simulation of austenite peritectic solidification based on a ferrite grain

Chinese Physics B 2021年第1期30卷 572-577页

作者： Chao Yang Jing Wang Junsheng Wang Yu Liu Guomin Han Haifeng Song Houbing Huang School of Materials Science and Engineering Beijing Institute of TechnologyBeijing 100081China Advanced Research Institute of Multidisciplinary Science Beijing Institute of TechnologyBeijing 100081China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China Software Center for High Performance Numerical Simulation China Academy of Engineering PhysicsBeijing 100088China

A multi-phase-field model is implemented to investigate the peritectic solidification of Fe-C alloy. The nucleation mode of austenite is based on the local driving force, and two different thicknesses of the primary austenite on the surface of the ferrite equiaxed crystal grain are used as the initial conditions. The simulation shows the multiple interactions of ferrite, austenite, and liquid phases, and the effects of carbon diffusion, which presents the non-equilibrium dynamic process during Fe-C peritectic solidification at the mesoscopic scale. This work not only reveals the influence of the austenite nucleation position, but also clarifies the formation mechanism of liquid phase channels and molten pools. Therefore, the present study contributes to the understanding of the micro-morphology and micro-segregation evolution mechanisms of Fe-C alloy during peritectic solidification.

关键词： multi-phase-field simulation morphology evolution peritectic solidification carbon diffusion Fe-C alloy

来源：评论

学校读者我要写书评

暂无评论

Social Distance Monitoring Using Object Detection and Tracking Techniques In the Era of COVID-19

Social Distance Monitoring Using Object Detection and Tracki...

引用

International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Bingshu Wang Ruofan Chang Ze Wang Shuang Feng Chuanbin Zhang School of Software Northwestern Polytechnical University Xi'an China School of Applied Mathematics Beijing Normal University Zhuhai China Faculty of Science and Technology University of Macau Macau China

The COVID-19 has been posing threats to peoples health around the world due to its simple transmission route, strong mutation ability, and high infection. Currently, the superb vaccine breakthrough ability of mutant strains puts people's lives and health further at risk. Many measures are taken to fight against the epidemic. Keeping a safe social distance to prevent the spread of COVID-19 in public places. In this paper, we propose a method to monitor social distancing from a bird's-eye view. It mainly includes three parts. Firstly, an objector based on YOLOv5m is trained to detect human beings. It shows good performance compared with other models such as Faster R-CNN and YOLOv3. Secondly, we propose to use SORT algorithm to track each human by assigning it an ID. It also ensures the accuracy of multiple-object tracking. More importantly, it makes for tracking those who violate social distance. Thirdly, the Euclidean distance between detected people is used to judge whether human beings keep social distance or not. It is implemented by computing the pairwise distances of the detected bounding box centroids. Experiments conducted on birds view dataset show that our method can monitor social distance well. Hopefully the proposed method and dataset can provide some help in the fighting against COVID-19.

关键词：

来源：评论

学校读者我要写书评

暂无评论

An End-to-End Conformer-Based Speech Recognition Model for Mandarin Radiotelephony Communications in Civil Aviation 16th

An End-to-End Conformer-Based Speech Recognition Model for M...

引用

16th Chinese Conference on Biometric Recognition, CCBR 2022

作者： Shi, Yihua Ma, Guanglin Ren, Jin Zhang, Haigang Yang, Jinfeng Institute of Applied Artificial Intelligence of the Guangdong-Hong Kong-Macao Greater Bay Area Shenzhen Polytechnic Shenzhen518055 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9783031202322

In civil aviation radiotelephony communications, misunderstandings between air traffic controllers and flight crews can result in serious aviation accidents. Automatic semantic verification is a promising assistant solution to decrease miscommunication, thanks to advancements in speech and language processing. Unfortunately, existing general speech recognition models are ineffective when it comes to capturing contextual long-distance dependent local similarity features in radiotelephony communications. To address these problems, this paper proposes an end-to-end Conformer-based multi-task learning speech recognition model for Mandarin radiotelephony communications in civil aviation. The Conformer model improves local information capture while retaining the global information modeling capabilities of contextual long-distance dependencies, owing to the introduction of the convolution module to the Transformer model. Meanwhile, multi-task learning is used to further improve performance by combining connectionist temporal classification (CTC) and attention-based encoder-decoder (AED) models. The experimental results show that the proposed model can perform global and local acoustic modeling effectively, making it particularly suitable for extracting acoustic features of Mandarin civil aviation radiotelephony communications. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Radio telephone

来源：评论

学校读者我要写书评

暂无评论

Target Detection Models Based on deep Learning

Target Detection Models Based on deep Learning

引用

2022 International Conference on Cloud Computing, Performance Computing, and Deep Learning, CCPCDL 2022

作者： Fu, Haoluo Li, Yuming Wang, Weining Xu, Xuanbo P.C. Rossin College of Engineering and Applied Science Lehigh University BethlehemPA18015 United States College of Computer Science Guangdong University of Technology Guangdong Guangzhou510006 China College of software Xinjiang University Xinjiang830046 China School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China

ISBN: (纸本)9781510655867

Object detection is one of the most basic and important tasks in the field of computer vision, and it is the foundation of high-level vision tasks such as behaviour recognition and human-computer interaction. With the development of deep learning technology, the accuracy and efficiency of target detection models have been greatly improved. Compared with traditional target detection algorithms, deep learning uses powerful hierarchical feature extraction and learning capabilities to make a breakthrough in the performance of target detection algorithms. At the same time, the emergence of large-scale data sets and the greatly improved computing power of graphics cards have also contributed to the vigorous development of this field. This article reviews the existing research results of target detection based on deep learning. This article first reviews the traditional target detection algorithm and its existing problems, then introduces the two-stage detection model and single-stage detection model under deep learning, and finally briefly summarizes the application scenarios of the target detection algorithm and summarizes the full text. © 2022 SPIE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Experimental Research of the Radiator Thermal Performance Test Equipment and Its Application in Heating System

引用

Energy Engineering 2021年第2期118卷 399-410页

作者： Lian Zhang Linjun Fan Xin Xu Baowen Cao Heng Zhang Lihong Song Basic Experimental and Training Center Tianjin Sino-German University of Applied SciencesTianjin300350China College of Mechanical Engineering Tianjin University of Science and TechnologyTianjin300222China Tianjin Qicheng Science and Technology Co. Ltd.Tianjin300193China Software and Communication School Tianjin Sino-German University of Applied SciencesTianjin300350China School of Energy Engineering Tianjin Sino-German University of Applied SciencesTianjin300350China

Radiator thermal performance test equipment plays a key role in the processing of developing a new type of heat radiator and its application *** precise of temperature controlling,temperature measuring andflow measuring are the vital factors for a radiator thermal performance test *** on the above back-ground,this paper improves the measurement and control system of radiator thermal performance test equip-ment,which improves the accuracy of the radiator thermal performance test *** paper also optimizes the software and hardware system simultaneously so as to improve the precision of the auto-test system of test *** rate ranges from 175 kg/h to 178 kg/h under different *** average is 176.5 kg/h and the deviation rates are from 1.62%to 1.97%.The heat produced under various conditions is *** maximum is 4.3 kW and the minimum is 4.2 kW for condition 1,the maximum is 3.3 kW and the minimum is 3.2 kW for condition 2 and the maximum is 1.95 kW and the minimum is 1.89 kW for condition ***,the deviation rate is about 2.9%,which shows that the device has high stability and high *** paper studies a new electronic heat cost allocate meter test method by radiator thermal performance test equipment at the same *** paper tests temperature changes through four measures points and gets a result appeared as a heat backup which should be avoided when using in the test of electronic heat cost allocate *** experiences and references could be gained for further research in the heating system from this test and research.

关键词： Electronic heat cost allocate meter radiator precise control heating

来源：评论

学校读者我要写书评

暂无评论

Entirety of Quantum Uncertainty and Its Experimental Verification

引用

Chinese Physics Letters 2021年第7期38卷 11-16页

作者： Jie Xie Li Zhou Aonan Zhang Huichao Xu Man-Hong Yung Ping Xu Nengkun Yu Lijian Zhang National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences and School of PhysicsNanjing UniversityNanjing 210093China Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Quantum Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Institute for Quantum Information&State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha 410073China Centre for Quantum Software and Information School of SoftwareFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNSWAustralia

As a foundation of quantum physics,uncertainty relations describe ultimate limit for the measurement uncertainty of incompatible ***,uncertainty relations are formulated by mathematical bounds for a specific *** we present a method for geometrically characterizing uncertainty relations as an entire area of variances of the observables,ranging over all possible input *** find that for the pair of position and momentum operators,Heisenberg's uncertainty principle points exactly to the attainable area of the variances of position and ***,for finite-dimensional systems,we prove that the corresponding area is necessarily semialgebraic;in other words,this set can be represented via finite polynomial equations and inequalities,or any finite union of such *** particular,we give the analytical characterization of the areas of variances of(a)a pair of one-qubit observables and(b)a pair of projective observables for arbitrary dimension,and give the first experimental observation of such areas in a photonic system.

关键词： observable union operators

来源：评论

学校读者我要写书评

暂无评论

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

引用

Computers, Materials & Continua 2023年第2期74卷 3263-3278页

作者： Sagheer Abbas Syed Ali Raza MAKhan Muhammad Adnan Khan Atta-ur-Rahman Kiran Sultan Amir Mosavi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science GC University LahorePakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Pattern Recognition and Machine Learning LabGachon UniversitySeongnam13120Korea Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah31261Saudi Arabia John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

File labeling techniques have a long history in analyzing the anthological trends in computational *** situation becomes worse in the case of files downloaded into systems from the ***,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user ***,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic ***,one major drawback of current topic modeling approaches is better *** rely on specific language types and domain similarity of the *** this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the *** results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

关键词： Automated file labeling file organization machine learning topic modeling

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack Tree and Fuzzy Logic 3

Fuzzy Attack Tree: Assessing Cyberattack Risk Using Attack T...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Naik, Nitin Jenkins, Paul Grace, Paul Naik, Dishita Song, Jingping Prajapat, Shaligram Mishra, Durgesh Yang, Longzhi Boongoen, Tossapon Iam-On, Natthakan School of Informatics and Digital Engineering Aston University United Kingdom Cardiff School of Technologies Cardiff Metropolitan University United Kingdom Birmingham City University United Kingdom Software College Northeastern University China International Institute of Professional Studies Devi Ahilya University India School of Computer Science & Information Technology Symbiosis University of Applied Sciences India Northumbria University Department of Computer and Information Sciences United Kingdom Aberystwyth University Department of Computer Science United Kingdom

ISBN: (纸本)9798350343274

Organisations and users have been experiencing significant rises in cyberattacks and their severity, which means that they require a greater awareness and understanding of the anatomy of cyberattacks, to prevent and mitigate their effects. In analysing cyberattacks, there are a number of different approaches that may be used to assess their potential risks and effects. However, these are utilised in specific types of cyberattacks and their analysis, which means they cannot be applied in every situation or cyberattack. Moreover, several other factors may influence the decision to use these approaches, such as cost, complexity, skills and adaptability. As a result, continuous research to design and enhance these approaches is undertaken to produce a generic, cost-effective, easy and adaptable approach. This paper presents one such approach to assess the risk of cyberattacks utilising an attack tree and fuzzy logic. An attack tree is a systematic and illustrative method for describing an attack on a system and analysing its taxonomy and other aspects. Subsequently, the probability and risk of each leaf node in the attack tree are calculated using the proposed formulas. Finally, fuzzy logic enables decision making based on imprecise data and heuristics to obtain the overall risk of attack. This proposed approach comprises systematic steps to accomplish an assessment of any cyberattack and its associated risks in an uncomplicated and effective manner, enabling its prevention and mitigation to be determined. The paper illustrates an application of the proposed approach to assess the risk of an information theft attack on an organisation, which can then be utilised to assess the risk of other cyberattacks. © 2023 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Explainable-AI-based two-stage solution for WSN object localization using zero-touch mobile transceivers

引用

science China(Information sciences) 2024年第7期67卷 27-45页

作者： Kai FANG Junxin CHEN Han ZHU Thippa Reddy GADEKALLU Xiaoping WU Wei WANG School of Mathematics and Computer Science Zhejiang A&F University School of Software Dalian University of Technology Faculty of Applied Sciences Macao Polytechnic University Department of Electrical and Computer Engineering Lebanese American University School of Information Engineering Huzhou University Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University

Artificial intelligence technology is widely used in the field of wireless sensor networks(WSN).Due to its inexplicability, the interference factors in the process of WSN object localization cannot be effectively eliminated. In this paper, an explainable-AI-based two-stage solution is proposed for WSN object localization. In this solution, mobile transceivers are used to enlarge the positioning range and eliminate the blind area for object localization. The motion parameters of transceivers are considered to be unavailable,and the localization problem is highly nonlinear with respect to the unknown parameters. To address this,an explainable AI model is proposed to solve the localization problem. Since the relationship among the variables is difficult to fully include in the first-stage traditional model, we develop a two-stage explainable AI solution for this localization problem. The two-stage solution is actually a comprehensive consideration of the relationship between variables. The solution can continue to use the constraints unused in the firststage during the second-stage, thereby improving the performance of the solution. Therefore, the two-stage solution has stronger robustness compared to the closed-form solution. Experimental results show that the performance of both the two-stage solution and the traditional solution will be affected by numerical changes in unknown parameters. However, the two-stage solution performs better than the traditional solution, especially with a small number of mobile transceivers and sensors or in the presence of high noise. Furthermore,we have also verified the feasibility of the proposed explainable-AI-based two-stage solution.

关键词： explainable AI object localization semidefinite relaxation mobile transceiver two-stage solution closed-form solution

来源：评论

学校读者我要写书评

暂无评论

HOTS3D: Hyper-Spherical Optimal Transport for Semantic Alignment of Text-to-3D Generation

arXiv

引用

arXiv 2024年

作者： Li, Zezeng Wang, Weimin Li, Wenhai Lei, Na Gu, Xianfeng International Information and Software Institute Dalian University of Technology Dalian116620 China School of Software Dalian University of Technology Dalian116620 China Department of Computer Science and Applied Mathematics State University of New York at Stony Brook Stony BrookNY11794-2424 United States

Recent CLIP-guided 3D generation methods have achieved promising results but struggle with generating faithful 3D shapes that conform with input text due to the gap between text and image embeddings. To this end, this paper proposes HOTS3D which makes the first attempt to effectively bridge this gap by aligning text features to the image features with spherical optimal transport (SOT). However, in high-dimensional situations, solving the SOT remains a challenge. To obtain the SOT map for high-dimensional features obtained from CLIP encoding of two modalities, we mathematically formulate and derive the solution based on Villani's theorem, which can directly align two hyper-sphere distributions without manifold exponential maps. Furthermore, we implement it by leveraging input convex neural networks (ICNNs) for the optimal Kantorovich potential. With the optimally mapped features, a diffusion-based generator and a Nerf-based decoder are subsequently utilized to transform them into 3D shapes. Extensive qualitative and qualitative comparisons with state-of-the-arts demonstrate the superiority of the proposed HOTS3D for 3D shape generation, especially on the consistency with text semantics. The code will be publicly available. Copyright © 2024, The Authors. All rights reserved.

关键词： Spheres

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：