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检索条件"任意字段=International Conference on Pattern Analysis and Intelligence Robotics"

共 15862 条记录，以下是4821-4830 订阅

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Multi-Welfare-Robot Cooperation Framework for Multi-Task Assignment in Healthcare Facilities Based on Multi-Agent System

Multi-Welfare-Robot Cooperation Framework for Multi-Task Ass...

引用

IEEE international conference on intelligence and Safety for robotics (ISR)

作者： Yong. Li Xuan-Yu. Jiao Bai-Qing. Sun Qiu-Hao. Zhang Jun-You. Yang Shenyang University of Technology Shenyang China Rehabilitation Robotic Laboratory of Shenyang University of Technology Shenyang China

With the large-scale application of intelligent service robots in health care facilities, the scheduling and planning problem of multiple heterogeneous robots is focused. Therefore, multi-welfare-robot cooperation framework for multi-task assignment in healthcare facilities based on multi-agent system is proposed. This framework adopts the structure of distributed and centralized multi-agent system to realize task assignment and robot scheduling in healthcare facilities. Heterogeneous multi-agent systems allocate tasks through contract network based on market mechanism. Agents' situation awareness when task appears, the individual situation of the elderly and task characteristics are the essential information for agents to calculate bid value. The framework can get an optimal task assignment by distributed consensus between agents.

关键词： Service robots conferences Senior citizens Medical services Safety Planning Task analysis

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Design of Maximum Stopping Deceleration of Mobile Manipulator Considering the Protective Separation Distance without Tip-over

Design of Maximum Stopping Deceleration of Mobile Manipulato...

引用

IEEE international conference on intelligence and Safety for robotics (ISR)

作者： Chang Joo Lee Jihyun Lee Sungsoo Rhim Kyung Hee University Yongin-si Republic of Korea

To increase the efficiency and flexibility of production operations, mobile manipulator has been developed and introduced in collaborative workspaces where robot shares the workspace with a operator. Therefore, the importance of robot safety is also increasing because of the rising possibility of the physical collision between the mobile manipulator and the operator. Keeping distance from robot and operator can be a way to prevent the collision recommended by a protective separation distance, ISO/TS 15066:2016. However, case for tip-over of mobile manipulator had not been considered although collision by tip-over could be danger to the operator. Therefore, a stability of tip-over should be considered when we apply the protective separation distance to guarantee the operator's safety. In this paper, a design method for stopping deceleration with consideration of tip-over and relationship between tip-over moment and the protective separation were presented, and simulation has been conducted to prove this method.

关键词： Design methodology conferences Collaboration Production Manipulators Stability analysis Safety

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Active Disturbance Rejection Control Algorithm of Permanent Magnetic Suspension System **Research supported by ABC Foundation

Active Disturbance Rejection Control Algorithm of Permanent ...

引用

IEEE international conference on intelligence and Safety for robotics (ISR)

作者： Feng Sun Jiacun Liu Junjie Jin Fangchao Xu Qiang Li Haining Zhao Ling Tong Ming Zhang Chuan Zhao Xiaoyou Zhang Shenyang University of Technology Shenyang China

The linear active disturbance rejection control of a permanent magnetic suspension system with a controllable magnetic circuit is studied. The permanent magnet suspension system is a high-order, strongly nonlinear, open-loop unstable system, which is easy to be disturbed by the internal or external complex environment of the system. This paper makes use of the advantages of ADRC, such as strong anti-jamming ability and excellent tracking performance. The cascade control is used to reduce the order of the system, and the linear active disturbance rejection controller is used to control the permanent magnet suspension system. Under the simulation conditions of 0.2mm step and 0.6N step, the linear ADRC and PID controllers are compared and analyzed. The simulation results show that the linear ADRC controller has strong tracking ability and anti-interference ability.

关键词： Robust control Simulation Interference Control systems Permanent magnets Stability analysis Safety

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32nd international conference on Database and Expert Systems Applications, DEXA 2021

32nd International Conference on Database and Expert Systems...

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32nd international conference on Database and Expert Systems Applications, DEXA 2021

ISBN: (纸本)9783030864743

The proceedings contain 68 papers. The special focus in this conference is on Database and Expert Systems Applications. The topics include: Sarcasm Detection for Japanese Text Using BERT and Emoji;Sigmalaw PBSA - A Deep Learning Model for Aspect-Based Sentiment analysis for the Legal Domain;BERT-Based Sentiment analysis: A Software Engineering Perspective;a Stochastic Block Model Based Approach to Detect Outliers in Networks;Medical-Based Text Classification Using FastText Features and CNN-LSTM Model;diversified pattern Mining on Large Graphs;EHUCM: An Efficient Algorithm for Mining High Utility Co-location patterns from Spatial Datasets with Feature-specific Utilities;BERT-Based Multi-Task Learning for Aspect-Based Opinion Mining;GPU-Accelerated Vertex Orbit Counting for 5-Vertex Subgraphs;subgroup Discovery with Consecutive Erosion on Discontinuous Intervals;efficient Discovery of Partial Periodic-Frequent patterns in Temporal Databases;database Framework for Supporting Retention Policies;internal Data Imputation in Data Warehouse Dimensions;purging Data from Backups by Encryption;improving Quality of Ensemble Technique for Categorical Data Clustering Using Granule Computing;Online Optimized Product Quantization for Dynamic Database Using SVD-Updating;querying Collections of Tree-Structured Records in the Presence of Within-Record Referential Constraints;Dealing with Plethoric Answers of SPARQL Queries;feature Selection and Software Defect Prediction by Different Ensemble Classifiers;traffic Flow Prediction Through the Fusion of Spatial-Temporal Data and Points of Interest;Fast SQL/Row pattern Recognition Query Processing Using Parallel Primitives on GPUs;predicting Student Performance in Experiential Education;log-Based Anomaly Detection with Multi-Head Scaled Dot-Product Attention Mechanism;enhancing Scan Matching Algorithms via Genetic Programming for Supporting Big Moving Objects Tracking and analysis in Emerging Environments.

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Semantic analysis of Cultural Heritage Data: Aligning Paintings and Descriptions in Art-Historic Collections 25th

Semantic Analysis of Cultural Heritage Data: Aligning Painti...

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25th international conference on pattern Recognition Workshops, ICPR 2020

作者： Jain, Nitisha Bartz, Christian Bredow, Tobias Metzenthin, Emanuel Otholt, Jona Krestel, Ralf Hasso Plattner Institute University of Potsdam Potsdam14482 Germany

ISBN: (纸本)9783030687953

Art-historic documents often contain multimodal data in terms of images of artworks and metadata, descriptions, or interpretations thereof. Most research efforts have focused either on image analysis or text analysis independently since the associations between the two modes are usually lost during digitization. In this work, we focus on the task of alignment of images and textual descriptions in art-historic digital collections. To this end, we reproduce an existing approach that learns alignments in a semi-supervised fashion. We identify several challenges while automatically aligning images and texts, specifically for the cultural heritage domain, which limit the scalability of previous works. To improve the performance of alignment, we introduce various enhancements to extend the existing approach that show promising results. © 2021, Springer Nature Switzerland AG.

关键词： Alignment

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Advancements and Challenges in Artificial intelligence for Lewy Body Disease Research: A Brief Survey 27th

Advancements and Challenges in Artificial Intelligence for...

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27th international conference on pattern Recognition, ICPR 2024

作者： D’Alessandro, Tiziana De Stefano, Claudio Fontanella, Francesco Pustovalova, Olga University of Cassino and Southern Lazio Via G. Di Biasio 43 FR Cassino03043 Italy

ISBN: (纸本)9783031876592

Lewy Body Disease (LBD) encompasses a spectrum of neurodegenerative disorders, including Parkinson’s Disease Dementia (PDD) and Dementia with Lewy Bodies (DLB), characterized by abnormal protein aggregates known as Lewy bodies. This survey reviews the existing approaches, advancements, and open issues in using artificial intelligence for LBD research. We begin by outlining relevant data types, including clinical records, digital biomarkers, and neuroimaging data. These datasets can be used for training the machine learning (ML) and deep learning (DL) algorithms that may enhance diagnostic accuracy, predict disease progression, and identify potential therapeutic targets. The survey then delves into various ML and DL methodologies applied in LBD research. Supervised learning techniques, such as decision trees and support vector machines, have shown promise in classifying LBD subtypes and predicting patient outcomes. Unsupervised learning methods, including clustering and principal component analysis, help identify novel patterns in complex datasets. Additionally, DL approaches, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are increasingly utilized for their capability to analyze high-dimensional neuroimaging and time-series data. Despite these technological advancements, the survey highlights several persistent challenges. Data heterogeneity, quality, explainability, and privacy concerns remain significant obstacles. Integrating multi-modal data sources and the potential use of transfer learning to improve model robustness are discussed as promising future directions. This survey aims to provide a comprehensive overview of the intersection between data science and LBD research, offering insights into how ML and DL can be exploited to advance our understanding and treatment of this complex group of diseases. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Support vector machines

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NPABT: Naming pattern analysis Of Bengali Text To Detect Various Community Using Machine Learning Approach 12

NPABT: Naming Pattern Analysis Of Bengali Text To Detect Var...

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12th international conference on Computing Communication and Networking Technologies, ICCCNT 2021

作者： Ria, Nushrat Jahan Ani, Jannatul Ferdous Islam, Mirajul Masum, Abu Kaisar Mohammad Choudhury, Tanupriya Abujar, Sheikh Dept. of CSE Daffodil International University Dhaka Bangladesh Dept of Informatics University of Petroleum and Energy Studies Dehradun India Dept. of CSE Independent University Bangladesh Dhaka Bangladesh

ISBN: (纸本)9781728185958

Natural Language processing is an important part of Artificial intelligence which enriches languages. It creates a bridge between humans and machines to communicate. In this paper, we have proposed a method that can automatically predict a person's community where he may belong by using their name. Based on the research available on online literature, we are the first to do research on it. We have collected more than 8,000 names of the four major communities of Bangladesh, including both males and females. Then data has been preprocessed to clean those texts by following the natural language processing approach. The six most popular machine learning classifiers have been used to train and test this data. Usually, human names have some prefix or suffix of their community. From that prefix or suffix, this method determines the community of that person's or their predecessors' community. The used approaches worked really well for these data and give higher accuracy for the models. The total performance of those classifiers is up to 65.12%-78.25%. Random Forest (RF) classifiers achieved the highest accuracy which is 78.25%. © 2021 IEEE.

关键词： Machine learning

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A Novel Method for Detecting the Width of Tobacco Filaments Based on Coordinate Point Fitting 23

A Novel Method for Detecting the Width of Tobacco Filaments ...

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Proceedings of the 2023 international Joint conference on robotics and Artificial intelligence

作者： Jinxin Tie Yuefeng Wang Weizheng Zhang Meng Li Daojian Yang Jinhua Song Maosong Li Junhui Wang Mingfang Zheng Chunbo Yuan Yue Long Yujie Wu Jie Li Ningbo Cigarette Factory China Tobacco Zhejiang Industrial Co. Ltd. China School of Computer and Communication Engineering Zhengzhou University of Light Industry China College of tobacco science and engineering Zhengzhou University of Light Industry China

ISBN: (纸本)9798400707704

Abstract. The width of the tobacco filament (WTF) is a significant process parameter in cigarette production as it has a crucial impact on both the physical quality and sensory experience of the product. The detection methods currently employed for WTF mainly involve manual visual inspection or low-frequency offline inspection, which lack representation, accuracy, and efficiency. To enhance the detection efficiency and accuracy, a method for detecting WTF images utilizing the coordinate point fitting method (CPFM) is proposed. We compare the performance of CPFM with the conventional Hough transform method (HTM) and the circle with different radii method (CDRM). Based on experimental results, CPFM has a relative error of 5.3%, an absolute error of 0.085 mm, and a maximum relative standard deviation of 1% in six repetitive experiments. This suggests that the suggested CPFM technique is dependable and dependable and fulfills the statistical demands of metrology. By implementing the WTF image detection method, which relies on the coordinate point fitting methodology, detection efficiency and accuracy are substantially increased. The technique necessitates rapid and exact WTF detection and surpasses prior approaches significantly. Compared to traditional methods, the CPFM method exhibits distinct benefits in detecting WTF. It is probable that the method will become widely used in cigarette production to improve both product quality and production efficiency.

关键词： Coordinate point fitting Detection efficiency Morphological analysis Tobacco filaments Width detection

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A New Boundary Optimal Control of Multi Joint Flexible Manipulator Based on LaSalle analysis Method

A New Boundary Optimal Control of Multi Joint Flexible Manip...

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international conference on robotics and Automation Engineering (ICRAE)

作者： Huiqing Liang Dehua Zhang School of Miami college Henan University Henan China School of Artificial Intelligence Henan University Henan China

ISBN: (纸本)9781665406987

This paper presents a new boundary control method for flexible manipulator based on LaSalle analysis method, which is a nonlinear system with unknown parameters, external disturbances and integrity constraints. Through theoretical analysis and dynamic modeling using LaSalle analysis method, using appropriate parameters enables us to obtain higher practicability than using the exponential convergence method in the traditional distributed parameter control method, without applying the traditional Lyapunov stability analysis. In addition, the dependence of each parameter is also given. And the theoretical analysis and practical simulation are carried out, which show the effectiveness of the proposed algorithm.

关键词： Vibrations Analytical models Simulation Heuristic algorithms Optimal control Nonlinear dynamical systems Impedance

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Genetic Algorithm Based Optimization in Solving Multi Robot Task Allocation Problems

Genetic Algorithm Based Optimization in Solving Multi Robot ...

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international conference on Computing, Communication, and Intelligent Systems (ICCCIS)

作者： M Rohini. B Manohari. S Adhithyan. Sri Krishna College of Engineering and Technology Coimbatore Tamilnadu India

ISBN: (纸本)9781665462013

As the world moves on in the direction of automated production lines and advanced robotics, there is a need to solve the problems of task allocation to robots to maximize efficiency based on parameters that change from situation to situation. This paper imparted knowledge on basic-intermediate problem-solving techniques to solve problems in the MRTA category. Problems we need to solve are decisions to make or tasks to complete. The Framework of making decisions based on existing data falls under Artificial intelligence. While the second part of doing tasks comes under the Framework of Robot Process Automation, for which machines already know what to do (Programmed), But need user input as to where to go to do the tasks in question. The purpose of this work is to learn about the different types of problems and how to solve them in the best possible way. This work implemented mixed linear programming with saving matrix methodology that minimized the total distance and path of robots in coordinating the robot environment, thus minimizing the idleness of the robot.

关键词： Automation Robot kinematics Production Linear programming Resource management Problem-solving Task analysis

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