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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Li, Qinyun Jin, Jin Xu, Yuanping Kong, Chao Wang, Weiye Xu, Zhijie Zhang, Chaolong Guo, Benjun School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

To achieve high precision reconstruction of complex point cloud data, this paper presents a novel method based on an adaptive threshold. Firstly, a pre trained neural network is used to initially segment the point cloud, and an adaptive threshold is introduced into the discrete optimal transport to effectively detect feature regions such as edges and corners based on local geometric information. Subsequently, a zero level set smoothing loss function and a normal alignment loss function are introduced into the implicit neural network to optimize the feature region and the smooth region respectively. Finally, the optimized point cloud is reconstructed through the Marching Cubes algorithm. Experimental results show that compared with DeepSDF and Occupancy Networks, the accuracy of the proposed method on the corresponding data sets is improved by 3.33% and 1.2% respectively. © 2024 IEEE.

关键词： Cloud platforms

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Intelligent Recognition of Geometric Tolerance Symbol Annotation Blocks 4

Intelligent Recognition of Geometric Tolerance Symbol Annota...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Li, Congxin Xu, Yuanping Zhang, Chaolong Kong, Chao Jin, Jin Wang, Weiye Xu, Zhijie Guo, Benjun Tang, Dan School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

In previous mechanical design drawings, the geometric tolerance symbol annotation block was directly annotated on the mechanical design drawing by engineers, resulting in the symbol annotation block being non-editable and non-shareable. To achieve digitization, this study proposes an improved Swin_YOLOv5_GE model based on YOLOv5 to realize the positioning of the symbol annotation block. Compared with the original YOLOv5, the accuracy is increased by 4%. Then, image processing is performed on the located and cropped symbol annotation block to achieve denoising and tilt correction of the symbol annotation block. Finally, it is input into CRNN for the recognition of the symbol annotation block. The final experimental results prove that the method in this paper can obtain an overall recognition accuracy of 94%, proving the feasibility of this method. © 2024 IEEE.

关键词： Machine design

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MSEs Credit Risk Assessment Model Based on Federated Learning and Feature Selection

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Computers, Materials & Continua 2023年第6期75卷 5573-5595页

作者： Zhanyang Xu Jianchun Cheng Luofei Cheng Xiaolong Xu Muhammad Bilal School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China State Key Laboratory Novel Software Technology Nanjing UniversityNanjing210023China Department of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siGyeonggi-do17035Korea

Federated learning has been used extensively in business inno-vation scenarios in various *** research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment ***,this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises(MSEs)using multi-dimensional enterprise data and multi-perspective enterprise *** proposed model includes four main processes:namely encrypted entity alignment,hybrid feature selection,secure multi-party computation,and global model ***,a two-step feature selection algorithm based on wrapper and filter is designed to construct the optimal feature set in multi-source heterogeneous data,which can provide excellent accuracy and *** addition,a local update screening strategy is proposed to select trustworthy model parameters for aggregation each time to ensure the quality of the global *** results of the study show that the model error rate is reduced by 6.22%and the recall rate is improved by 11.03%compared to the algorithms commonly used in credit risk research,significantly improving the ability to identify ***,the business operations of commercial banks are used to confirm the potential of the proposed model for real-world implementation.

关键词： Federated learning feature selection credit risk assessment MSEs

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A Metamodel for a DSL to Design Decision Support systems in Smart Tourism

A Metamodel for a DSL to Design Decision Support Systems in ...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ouaddi, Charaf Benaddi, Lamya Souha, Adnane Naimi, Lahbib Bouziane, El Mahi Jakimi, Abdeslam Moulay Ismail University Software Engineering and Information Systems Engineering Team Faculty of Science and Technology Errachidia Department of Computer Sciences Morocco

ISBN: (纸本)9798350369106

The development of Decision Support systems (DSS) for several companies operating in sectors such as tourism, healthcare, or others, presents significant challenges due to the nature of their multi-component architecture. A typical DSS consists of a data component, a model component incorporating machine learning and deep learning techniques, and a user interface component, each one requires diverse technologies. This complexity increases development time and effort, hindering the efficient design of DSS tailored to specific domains like tourism, where real-time decision-making is essential. One promising approach to overcome these challenges is the use of Domain-Specific Languages (DSLs). DSLs allow developers to model and generate code more efficiently by providing high-level abstractions suited to the domain. By leveraging DSLs, it is possible to simplify the design process and automate the generation of code or parts of the DSS, thereby reducing the overall complexity and time required for development. This paper proposes a metamodel for designing DSS, specifically for the Smart Tourism sector. The metamodel serves as a foundation for the creation of DSL. The goal is to provide a solution to facilitate the development of DSS for the demands of tourism. The paper outlines the key concepts, approach, and results, presenting the first element of the proposed DSL which is the metamodel capturing the essential components and relationships for DSS in Smart Tourism. © 2024 IEEE.

关键词： Digital subscriber lines

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An Improved SlowFast Model for Violence Detection 4

An Improved SlowFast Model for Violence Detection

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Huang, Qinxue Zhang, Chaolong Xu, Yuanping Wang, Weiye Xu, Zhijie Guo, Benjun Jin, Jin Kong, Chao School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

As social safety concerns become increasingly prominent, the importance of violence detection has become increasingly significant. Accurately identifying violent behavior helps facilitate timely interventions, reducing harm and losses, thereby enhancing public safety. To minimize the interference from irrelevant actions (e.g., those from spectators and uninvolved individuals) during violence detection, this study proposes an improved SlowFast method that enhances the robustness of the model by modifying the network structure of the Slow Pathway and lateral connections. In the Slow Pathway, the original residual block is replaced with an SE-Res residual block, which strengthens the weighting of channel importance, making the model more stable in complex scenarios. The lateral connections are improved by integrating a 3D-Convolutional Block Attention Module(3DCBAM), enhancing feature fusion and increasing the model's sensitivity to key features across different temporal scales. Furthermore, to address the class imbalance issue within the dataset, the Focal Loss function has been modified, effectively improving the performance of each class. The improved model demonstrates excellent performance in violence detection tasks, achieving an accuracy of 96.67%, which is a 1.12% improvement over the classical model. © 2024 IEEE.

关键词： Feature extraction

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A Lightweight Convolutional Dual-Channel Transformer Framework for Efficient Part Segmentation of Point Cloud Data 4

A Lightweight Convolutional Dual-Channel Transformer Framewo...

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4th International Symposium on Artificial Intelligence and Intelligent Manufacturing, AIIM 2024

作者： Li, Jianhua Xu, Yuanping Zhang, Chaolong Kong, Chao Jin, Jin Wang, Weiye Xu, Zhijie Guo, Benjun Tang, Dan School of Software Engineering Chengdu University of Information Technology Chengdu China School of Advanced Technology Xi'an Jiaotong-Liverpool University Suzhou China

ISBN: (纸本)9798331541729

In recent years, transformer-based models have made significant breakthroughs in natural language processing and computer vision. However, these models have encountered challenges when dealing with point cloud data because the irregular and disordered structure of point cloud data leads to a huge computational and memory burden. To address this problem, this paper proposes a Multidimensional Convolution-Dual Channel Transformer Network for efficient processing of point cloud data. The MCDTN framework consists of two branches: the main channel enhances the modeling of cross-channel features through dynamic attention to optimize feature representation;the auxiliary channel further improves fine-grained segmentation capabilities through encoders, multi-scale information interaction, and spatial attention. Experimental results show that MCDTN performs excellently in shape classification and part segmentation tasks, effectively reducing computational costs. © 2024 IEEE.

关键词： Natural language processing systems

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Application of fractal theory to study morphology of manganese sulfide inclusion in resulfurized free-cutting steels

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Journal of Iron and Steel Research International 2023年第1期30卷 137-149页

作者： Xiang-yu Xu Zhi-qi Zeng Qian-ren Tian Chen-wei Cao Ping Shen Jian-xun Fu Center for Advanced Solidification Technology(CAST) State Key Laboratory of Advanced Special SteelSchool of Materials Science and EngineeringShanghai UniversityShanghai 200444China Baosight Software Co. Ltd.Information Service HeadquartersShanghai 201203China

The morphology and distribution of manganese sulfide(MnS)inclusions have a significant influence on the comprehensive performance,which is an important research field for resulfurized *** on the experiments of non-aqueous electrolyte and scanning electron microscope observation,the fractal theory was employed to study the three-dimensional morphologies of MnS *** results showed that the edge fractal dimension of MnS inclusions was between 1.59 and *** addition,similar morphology of MnS inclusions had a close fractal *** MnS edge fractal dimension is highly positively correlated with the morphological *** multifractal spectrums of MnS inclusions on two-dimensional plane of as-cast and as-rolled resulfurized free-cutting steels were *** large-size MnS inclusions belong to large probability subset,while the small-size MnS inclusions belong to small probability *** multifractal spectrum can truly and effectively reflect the difference and non-uniformity of distribution of MnS inclusions on 2D *** the premise of similar content of MnS,with the refinement of MnS inclusions,the multifractal spectrum width and the multifractal spectrum symmetry parameter were *** multifractal spectrum provides a new method for studying the second phase in materials.

关键词： MnS inclusion Morphology Fractal dimension Multifractal Resulfurized steel

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Evaluation Methods and Replicability of software Architecture Research Objects

Evaluation Methods and Replicability of Software Architectur...

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2023 Fachtagung des GI-Fachbereichs softwaretechnik, software engineering 2023 - 2023 Conference of the GI software engineering Division, software engineering 2023

作者： Konersmann, Marco Kaplan, Angelika Kühn, Thomas Heinrich, Robert Koziolek, Anne Reussner, Ralf Jürjens, Jan al-Doori, Mahmood Boltz, Nicolas Ehl, Marco Fuchß, Dominik Großer, Katharina Hahner, Sebastian Keim, Jan Lohr, Matthias Sağlam, Timur Schulz, Sophie Töberg, Jan-Philipp Software Engineering RWTH Aachen University Germany Karlsruhe Institute of Technology Germany University of Koblenz-Landau Germany Fraunhofer Institute for Software and Systems Engineering ISST Germany

ISBN: (纸本)9783885797265

Our paper at the 19th IEEE International Conference on software Architecture (ICSA 2022) started by noticing that software Architecture (SA) as research area experienced an increase in empirical research. Empirical research builds a sound foundation for validity and comparability. A current overview of the evaluation and replicability of SA research objects could help to discuss our empirical standards as a community. However, no current overview existed. We assessed the current state of practice of evaluating SA research objects and replication artifact provision in full technical conference papers from ICSA and the European Conference on software Architecture (ECSA) 2017-2021. We first developed a categorization schema for SA research object evaluation and artifact provisioning. In a systematic literature review with 153 papers, we then classified the papers according to that schema. From our findings we derive and describe four proposals for improving the state of practice in evaluating SA research objects. © 2023 Gesellschaft fur Informatik (GI). All rights reserved.

关键词： software architecture

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Deepfake Detection: Emerging Techniques and Evolving Challenges 12

Deepfake Detection: Emerging Techniques and Evolving Challen...

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12th International Conference on Internet of Everything, Microwave, Embedded, Communication and Networks, IEMECON 2024

作者： Natarajan, Krishnaraj Mathur, Abeer Bhargava, Kshitiz Singh, Manvendra Tejpal, Moulik Department of Database Systems School of Computer Science & Engineering Vellore Institute of Technology Vellore India Department of Software Systems School of Computer Science & Engineering Vellore Institute of Technology Vellore India

ISBN: (纸本)9798350387315

Several newly developed techniques and tools for manipulating images, audio, and videos have been introduced as an outcome of the recent and rapid breakthroughs in AI, machine learning, and deep learning. While most applications for these techniques or tools are in the fields of entertainment and education, some individuals with unlawful intent have also been benefited from them. These individuals use such techniques for various purposes, including the spread of misleading information and unnecessary propaganda, the incitement of political instability, hate and unrest, as well as for purposes of torture and blackmail. These high-quality and convincing manipulated images, audio, or videos are commonly referred to as ‘Deepfakes’. Since then, various solutions to the problems raised by Deepfakes have been proposed in academic studies. This literature review contains relevant publications that offered a variety of approaches to give an updated summary of the research activities in different types of Deepfake attacks, their detection, and countermeasures. It also assesses the effectiveness of the detection capabilities of different techniques with various datasets and algorithms applied in Deepfake detection, while also outlining the various benefits and drawbacks of various methodologies. © 2024 IEEE.

关键词： Deep learning

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3D Visualization of Forest Fire Spread Model Based on Cellular Automata 8

3D Visualization of Forest Fire Spread Model Based on Cellul...

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8th International Conference on Computer and Communication systems, ICCCS 2023

作者： Hou, Zeqing Sun, Yu Cai, Mingyu Beijing University of Technology Beijing Engineering Research Center for IOT Software and Systems Beijing China

ISBN: (纸本)9781665456128

Whereas the traditional forest fire spread model cannot clearly and dynamically display the fire spread process, this paper optimizes the cell structure and evolution rules of cellular automata (CA) in the traditional forest fire spread model to improve the simulation accuracy and develops a forest fire spread simulation system using Unity 3D technology, which realizes the dynamically display and 3D visualization of forest fire spread process. It plays an important role in forest fire prevention and extinguishing. © 2023 IEEE.

关键词： Cellular automata

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