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arXiv 2024年

作者： Li, Lei Wang, Mingxin College of Science Henan University of Technology Zhengzhou450001 China School of Mathematics and Information Science Henan Polytechnic University Jiaozuo454003 China

An epidemic model, where the dispersal is approximated by nonlocal diffusion operator and spatial domain has one fixed boundary and one free boundary, is considered in this paper. Firstly, using some elementary analysis instead of variational characterization, we show the existence and asymptotic behaviors of the principal eigenvalue of a cooperative system which can be used to characterize more epidemic models, not just ours. Then we study the existence, uniqueness and stability of a related steady state problem. Finally, we obtain a rather complete understanding for long time behaviors, spreading-vanishing dichotomy, criteria for spreading and vanishing, and spreading speed. Particularly, we prove that the asymptotic spreading speed of solution component (u, v) is equal to the spreading speed of free boundary which is finite if and only if a threshold condition holds for kernel functions. Copyright © 2024, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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BloSecR: A Conceptual Framework of Identity Documents' Security on Blockchain in Refugee Issues and Conserving Fundamental Rights 2

BloSecR: A Conceptual Framework of Identity Documents' Secur...

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2nd IEEE International Conference on Intelligent Technologies, CONIT 2022

作者： Arafat, N.H.M. Pramanik, Md Ileas Jahan, Sumaiya Uddin, Md Nazim Islam, Md Shamimul Akter, Kanij Fatema Henan Polytechnic University Computer Science & Technology Henan Jiaozuo454003 China Begum Rokeya University Computer Science & Engineering Rangpur5404 Bangladesh Manarat International University Dept. of Cse Dhaka Bangladesh World University of Bangladesh Computer Science & Engineering Dhaka1230 Bangladesh

ISBN: (数字)9781665484077

ISBN: (纸本)9781665484077

Identity documents are vital credentials to the people, which assists to fulfil their demands and conserve their rights. Besides the benefits of the amplification of modern technologies, the tendency of forging IDs is becoming a profitable business for criminals. They utilise the technology to make counterfeit ID cards for non-native people (refugees) by taking advantage of their physical or cultural similarities. The aim of this paper is to propose a blockchain-based security model which will ensure the authenticity of identity documents and conserve fundamental rights for refugees. In the construction of the model, a secure environment for identification is demonstrated, where the authorized controller, the third party's data request, reviewing and assisting refugees functions. The detailed proposal of the aid request and donation on the Aid Management (AM) System is presented to complete peer-to-peer transactions between the hosting country (HC) and the refugee upon the request of the refugee and donation of a third party (TP). This model will certainly have a major impact as a wider cyber-defense framework for refugees' identification and basic rights, preventing forged IDs and criminal activities. © 2022 IEEE.

关键词： Cybersecurity

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Spreading Dynamics of a Nonlocal Diffusive Model with a Free Boundary

SSRN

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SSRN 2024年

作者： Li, Lei Wang, Mingxin College of Science Henan University of Technology Zhengzhou450001 China School of Mathematics and Information Science Henan Polytechnic University Jiaozuo454000 China

This paper concerns the spreading speed and asymptotical behaviors, which was left as an open problem in [J. Differential Equations 330 (2022), 110-149], of a nonlocal diffusive Fisher-KPP model with a free boundary. Using a new lower solution, we get the exact finite spreading speed of free boundary that is proved to be the asymptotical spreading speed of solution component $u$. Moreover, for the algebraic decay kernels, we derive the rates of accelerated spreading and the corresponding asymptotical behaviors of solution component $u$. Especially, for the level set $E^{\lambda}(t)$ with $\lambda\in(0,u^*)$, we find an interesting propagation phenomenon different from the double free boundary problem. © 2024, The Authors. All rights reserved.

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FractureNet: A Fusion Approach for Automated Hand Fracture Detection and Classification

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Procedia computer science 2025年 258卷 1131-1146页

作者： Priyanka M Chethan L Reddy Umme Aymon Tian Jipeng Department of Computer Science School of Computing Mysuru Campus Amrita Vishwa Vidyapeetham India Computer Science college Zhongyuan University of Technology Zhengzhou Henan Province China

Bone fractures are a prevalent health concern, and their precise and appropriate recognition is crucial for effective diagnosis and patient recovery. While conventional methods rely on radiologists’ interpretations of imaging studies, computer vision-based analysis offers enhanced fracture detection and classification. The current literature faces a lack of model generalization due imbalanced dataset and restrictions in several classes. The proposed study was undertaken to address these issues and classify hand fractures, with a specific emphasis on transverse and compound types. The proposed FractureNet model divides into two phases: Phase 1 utilizes the YOLOv5 model for fracture detection with CLAHE to enhance image quality, and Phase 2 classifies the fracture type by fusion approach using a HOG, LBP, and VGG16 model to improve the model performance. These combined features advance the model’s capability to distinguish, and the features are fed into various classifiers, among which SVM achieves 95.4% accuracy, 95.3% precision, 96.1% recall, and 95.6% f1-score for the collected fracture x-ray dataset.

关键词： FractureNet YOLOv5 Feature fusion SVM

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Spreading dynamics of a Fisher-KPP nonlocal diffusion model with a free boundary

arXiv

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arXiv 2024年

作者： Li, Lei Wang, Mingxin College of Science Henan University of Technology Zhengzhou450001 China School of Mathematics and Information Science Henan Polytechnic University Jiaozuo454000 China

This paper concerns the spreading speed and asymptotical behaviors, which was left as an open problem in [7], of a Fisher-KPP nonlocal diffusion model with a free boundary. Using a new lower solution, we get the exact finite spreading speed of free boundary that is proved to be the asymptotical spreading speed of solution component u. Moreover, for the algebraic decay kernels, we derive the rates of accelerated spreading and the corresponding asymptotical behaviors of solution component u. Especially, for the level set Eλ(t) with λ ∈ (0, u∗), we find an interesting propagation phenomenon different from the double free boundary problem. Copyright © 2024, The Authors. All rights reserved.

关键词： Diffusion

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Ontology-Based Knowledge Graph Construction and Application for Large Workpiece Forging 8

Ontology-Based Knowledge Graph Construction and Application ...

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8th IEEE International Conference on computer and Communications, ICCC 2022

作者： Duan, YiYan Liu, Yong Information Engineering School Henan University of Science and Technology Luoyang China Automobile and Rail Transit School Luoyang Polytechnic Luoyang China

ISBN: (纸本)9781665450515

Due to the advent of the big data era and the redundancy of industrial data, people use a series of information technologies to continuously promote the transformation of traditional industry, and the development of industry is bound to move into the era of intelligence. The article carries out the construction of process knowledge mapping on the existing industrial process design scheme, constructs a process ontology model through industrial specifications, starts from acquiring data from industrial archives, identification of industrial entities, extraction of relationships between industrial entities and fusion of process knowledge, and constructs a process assembly knowledge mapping in the forging field by storing the acquired process data into the graph database, and finally The visualization display of data storage based on database Neo4j is realized. The experimental results have verified the feasibility of the designed diagram. © 2022 IEEE.

关键词： Ontology

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Unifying Demonstration Selection and Compression for In-Context Learning

arXiv

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arXiv 2024年

作者： Gao, Jun Cao, Ziqiang Li, Wenjie School of Computer Science and Technology Department of Computer Science Hong Kong Polytechnic University Hong Kong

In-context learning (ICL) enables LLMs to exhibit spectacular emergent capabilities in various scenarios. Unfortunately, introducing demonstrations easily makes the prompt length explode, bringing a significant burden to hardware. In addition, random demonstrations usually achieve limited improvements in ICL, necessitating demonstration selection among accessible candidates. Previous studies introduce extra modules to perform demonstration compression or selection independently. In this paper, we propose an ICL framework UniICL, which Unifies demonstration selection and compression, and final response generation via a single frozen LLM. UniICL leverages the understanding ability of well-trained LLMs to independently compress different demonstrations into compressed features, and then a learnable projection layer converts features to LLM-acceptable compressed virtual tokens. Apart from substituting original demonstrations to reduce input length, virtual tokens are again used to select potential demonstrations. Finally, current queries together with selected compressed virtual tokens are fed into the same frozen LLM for response generation. UniICL is a parameter-efficient framework that only contains 17M trainable parameters originating from the projection layer and a learnable embedding. We build UniICL upon two backbones and conduct experiments over in- and out-domain datasets of both generative and understanding tasks, encompassing ICL scenarios with plentiful and limited demonstration candidates. Results show that UniICL effectively unifies 12× compression, demonstration selection, and response generation, efficiently scaling up the baseline from 4-shot to 64-shot ICL with 24 GB CUDA allocation1 Copyright © 2024, The Authors. All rights reserved.

关键词： Demonstrations

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Research on coking diagnosis based on semi-supervised Bayesian T-distribution mixed model 4

Research on coking diagnosis based on semi-supervised Bayesi...

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4rth International Conference on Applied Mathematics, Modelling, and Intelligent Computing, CAMMIC 2024

作者： Yang, Hanmei Cui, Delong Li, Qirui Peng, Zhiping Zuo, Jinglong School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Electronic and Information Engineering Guangdong University of Petrochemical Technology Maoming525000 China School of Computer Science Guangdong University of Petrochemical Technology Maoming525000 China Jiangmen Polytechnic College Jiangmen529090 China

ISBN: (纸本)9781510681637

In the process of ethylene production, the operating data of ethylene cracking furnace not only has the problems of time variability, non-gauss, strong noise, and outlier influence but also the collected data is incomplete, presenting the problem of scarce data with labels and abundant data without labels. To solve the above problems, this paper proposes a soft measurement model based on a semi-supervised Bayesian T-distribution mixture for the coking diagnosis of ethylene cracking furnaces. The model adopts a semi-supervised structure to solve the problem of the small number of data labels, adopts a T-distribution model to ensure the robustness of the model to strong noise and outliers under the Bayesian framework, and solves the solid variation of process data through the mixed model—complexity, non-Gaussian, and nonlinear problems. Finally, the experiment was carried out on the coking data of an ethylene cracking furnace in a petrochemical plant to verify the feasibility and prediction accuracy of the model under the condition of limited label data, and also to verify the robustness of the model to outliers. © 2024 SPIE.

关键词： Statistics

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A Hierarchical Graph Convolutional Network with Infomax-Guided Graph Embedding for Population-Based ASD Detection

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IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4349-4361页

作者： Hao, Xiaoke Ma, Mingming Tao, Jiaqing Cao, Jiahui Qin, Jing Liu, Feng Zhang, Daoqiang Ming, Dong Hebei University of Technology School of Artificial Intelligence Tianjin300401 China Tianjin University Academy of Medical Engineering and Translational Medicine Tianjin300072 China The Hong Kong Polytechnic University Centre for Smart Health School of Nursing 999077 Hong Kong Tianjin Medical University General Hospital Department of Radiology Tianjin Key Laboratory of Functional Imaging Tianjin300052 China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing211106 China

Recently, functional magnetic resonance imaging (fMRI)-based brain networks have been shown to be an effective diagnostic tool with great potential for accurately detecting autism spectrum disorders (ASD). Meanwhile, the successful use of graph convolution networks (GCNs) methods based on fMRI information has improved the classification accuracy of ASD. However, many graph convolution-based methods do not fully utilize the topological information of the brain functional connectivity network (BFCN) or ignore the effect of non-imaging information. Therefore, we propose a hierarchical graph embedding model that leverage both the topological information of the BFCN and the non-imaging information of the subjects to improve the classification accuracy. Specifically, our model first use the Infomax Module to automatically identify embedded features in regions of interests (ROIs) in the brain. Then, these features, along with non-imaging information, is used to construct a population graph model. Finally, we design a graph convolution framework to propagate and aggregate the node features and obtain the results for ASD detection. Our model takes into account both the significance of the BFCN to individual subjects and relationships between subjects in the population graph. The model performed autism detection using the Autism Brain Imaging Data Exchange (ABIDE) dataset and obtained an average accuracy of 77.2% and an AUC of 87.2%. These results exceed those of the baseline approach. Through extensive experiments, we demonstrate the competitiveness, robustness and effectiveness of our model in aiding ASD diagnosis. © 2013 IEEE.

关键词： Graph embeddings

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Research on gravity compensation control of BPNN upper limb rehabilitation robot based on particle swarm optimization

Research on gravity compensation control of BPNN upper limb ...

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International Symposium, Seminar, and Exhibition, Display Week 2024

作者： Pang, Zaixiang Deng, Xiaomeng Gong, Linan Guo, Danqiu Wang, Nan Li, Ye School of Computer Science and Engineering Changchun University of Technology Changchun China School of Mechanical and Electrical Engineering Changchun Polytechnic Changchun China School of Artificial Intelligence The Tourism College of Changchun University Changchun China Jilin Weimiao Medical Technology Co. Ltd Changchun China School of Mechatronic Engineering Changchun University of Technology Changchun China

A four-degree-of-freedom upper limb exoskeleton rehabilitation robot system with a gravity compensation device is constructed. The objective is to address the rehabilitation training needs of patients with upper limb motor dysfunction. A BP neural network adaptive control method based on particle swarm optimization is proposed. First, the degrees of freedom of the human body are analyzed, and a Lagrange method is employed to construct a dynamic model. Second, a particle swarm optimization back propagation neural network adaptive control algorithm based on particle swarm optimization is presented. Subsequently, the range of motion of the upper limbs is analyzed with reference to muscle anatomy and a three-dimensional motion capture system. And the robot structure design is analyzed in detail. Finally, simulation experiments were conducted, and the results demonstrated that the proposed method exhibited high effectiveness and accuracy. © 2024 The Author(s).

关键词： Particle swarm optimization (PSO)

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