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

共 15864 条记录，以下是391-400 订阅

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Design and Kinematic Simulation analysis of Spherical Modular Robots 17th

Design and Kinematic Simulation Analysis of Spherical Modula...

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17th international conference on Intelligent robotics and Applications

作者： Zhu, Boshi Peng, Jun An, Ningli Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Peoples R China Xian Univ Technol Fac Printing Packaging Engn & Digital Media Techn Xian 710048 Peoples R China

ISBN: (纸本)9789819607976;9789819607983

Traditional robots are developed to achieve specific goals or functions. They are mostly tracked, footed, rod-type and other structures. They are suitable for structured scenes such as flat ground, slopes, walls, etc. They are obviously restricted by the terrain. At the same time, the functions are relatively simple. After the whole machine is designed and manufactured, the functions cannot be easily expanded. Compared with traditional robots, modular robots have the advantages of diversity, reliability and scalability, and are more suitable for unstructured scenes. This paper summarizes the common chain-type, crystal-type and hybrid modular robots from the perspective of structural morphology. On this basis, this paper proposes a spherical robot unit as the base unit of the modular robot and completes the body construction of the base unit through structural and circuit design. The modified D-H parameter method and Newtoon-Euler method are used to complete the kinematic and dynamic modeling respectively, and the motion simulation of "BaseUnit" is realized in the Simscape Multibody simulation environment, which preliminarily verifies the feasibility of BaseUnit to realize the self-reconfigurable modular robot system.

关键词： Modular Robots Spherical Unit Structural Design Kinematic analysis

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Ontology population using CNN model: Application to COVID-19 diagnosis 6

Ontology population using CNN model: Application to COVID-19...

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6th international conference on pattern analysis and Intelligent Systems, PAIS 2024

作者： Mellal, Nacima Saighi, Asma Institute of Applied Science & Technology University of Oum Research Laboratory of Artificial Intelligence And Autonomous Objects Dept. Networks And Telecommunication El Bouaghi Algeria University of Oum Research Laboratory of Artificial Intelligence And Autonomous Objects Dept. Computer Science El Bouaghi Algeria

ISBN: (纸本)9798350350265

AI models and especially deep learning models have found applications across various medical domains. While many studies focus on using electronic health records (EHRs) data to train AI models, implementing the reverse process poses several challenges. Also, the heterogeneous nature of the used data in EHRs, such as diagnoses, clinical reports, test results, prescriptions, and medical images, makes their interpretation difficult for the practitioners which require a unified understanding. Medical ontologies are useful to improve data interpretability and semantics. In this paper, we aim to create a synergy between ontologies and deep learning techniques to enhance efficiency, data understanding, and provide healthcare quality. We propose a system in which our developed ontology is populated automatically using the predictions of an AI model. We have developed and trained a CNN model to aid in the COVID-19 diagnosis. The initial obtained results are promising with an accuracy of 98%. © 2024 IEEE.

关键词： COVID-19

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Time-Varying Volatility Among Bahrain Stock Exchange with Disruptive Technology and Sustainable Asset Class- Insights for Portfolio Diversification

Time-Varying Volatility Among Bahrain Stock Exchange with Di...

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2024 ASU international conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

作者： Sharma, Sudhi Aswal, Neeraj Aggarwal, Vaibhav Reepu Tiwari, Vivek New Delhi India Grd Higher Education Rajpur Road Dehradun India Jindal Global Business School Op Jindal Global University India Chandigarh University Department of Management Chandigarh India

ISBN: (纸本)9798350372229

With the backdrop of an evolving nexus between technology and sustainability, this research underscores the changing investment patterns, with portfolio managers integrating disruptive technologies and identifying sustainable opportunities. The necessity of diversification becomes vital during crises, exemplified by the recent pandemic and financial vulnerabilities. The Bahrain stock exchange, a vital contributor to technology- driven enterprises and sustainable finance, emerges as a strategic focal point. The study aims to analyze the dynamic landscape of the Bahrain stock exchange, by investigating the diversification with the transformative forces of disruptive technology and the burgeoning sustainable asset class. The study applied Time-varying volatility models TVP- VAR and Network analysis. The results show that non-conventional funds are providing robust diversification with the Bahrain index. Notably, iShares robotics and Artificial intelligence Multisector ETF (IRBO) and First Trust NASDAQ AI and robotics ETF (ROBT) emerge as superior diversifier. The results are useful for investors and portfolio managers. © 2024 IEEE.

关键词： Bahrain Stock Market Diversification Network analysis TVP-VAR

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Robot Arm Design and Application Case analysis Combining Artificial intelligence and Bionics

Robot Arm Design and Application Case Analysis Combining Art...

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robotics and Technologies for Industrial Automation (ROBOTHIA), IEEE international conference on

作者： Nuo Pang Mustaffa Halabi Azahari School of design Dalian University of Science and Technology Dalian China City Graduate School City University Malaysia Kuala Lumpur Malaysia

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

With the application of artificial intelligence (AI) technology in medical diagnosis, treatment, and rehabilitation, combining AI with bionics to design more intelligent and adaptable robotic arms can improve the effectiveness of rehabilitation training. However, there are still many challenges in accurately identifying and simulating the movement patterns of the human arm. In this article, we investigated the application of bionics in the design of artificial joints and motion-assistive devices, as well as the role of machine learning and deep learning in motion pattern recognition and electromyography signal processing. In addition, combining AI with bionic technology, we designed and developed a bionic rehabilitation arm with highly intelligent and personalized features. The arm excels in motion pattern recognition and electromyography signal processing and can effectively enhance the effectiveness of rehabilitation training.

关键词： Training Service robots Biomimetics Arms Signal processing Manipulators Solids Electromyography pattern recognition Artificial intelligence

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Identification of Potential Biomarkers Using Integrative Approach: An Application of ESCC 1

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9th international conference on pattern Recognition and Machine intelligence (PReMI)

作者： Saikia, Manaswita Bhattacharyya, Dhruba K. Kalita, Jugal K. Manipal Acad Higher Educ Manipal Inst Technol Bengaluru Dept Comp Sci & Engn Manipal India Tezpur Univ Tezpur 784028 Assam India Univ Colorado Coll Engn & Appl Sci Colorado Springs CO 80918 USA

ISBN: (数字)9783031127007

ISBN: (纸本)9783031126994;9783031127007

This paper presents a consensus-based approach that incorporates three microarray and three RNA-Seq methods for an unbiased and integrative identification of Differentially Expressed Genes (DEGs) as potential biomarkers for critical disease(s). The proposed method has been found to perform satisfactorily on two microarrays and one RNA-Seq datasets for Esophageal Squamous Cell Carcinoma (ESCC). It has been able to identify 9 crucial genes for ESCC.

关键词： Differential Expression analysis Biomarkers ESCC Differentially Expressed Gene RNA-Seq Microarray

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Disturbance Rejection for Markovian Jump Systems Based on Equivalent Input Disturbance Approach 5

Disturbance Rejection for Markovian Jump Systems Based on Eq...

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5th international conference on robotics, Intelligent Control and Artificial intelligence, RICAI 2023

作者： Wang, Xinming Li, Bo Du, Youwu Zhao, Junjie School of Electrical and Information Engineering Jiangsu University of Technology Changzhou China

ISBN: (纸本)9798350357950

Equivalent Input Disturbance (EID) is an approach to equate the effect of external disturbances on the system output to the effect of virtual disturbances on the system output, which mainly consists of two parts: state observer and disturbance estimator. In this paper, the EID approach is proposed to solve the problem of disturbance rejection for Markovian jump systems. Firstly, the state observer and the disturbance estimator are designed to achieve a certain disturbance rejection performance for a class of Markovian jump systems. Secondly, the sufficient condition for the stability of the closed-loop system and the method of designing controller are given in the form of Linear Matrix Inequality (LMI). Finally, the feasibility of this approach is confirmed by simulation example. © 2023 IEEE.

关键词： disturbance rejection EID LMI Markovian jump systems stability analysis

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Simplification Process in Supply Chain Management Through Artificial intelligence 4

Simplification Process in Supply Chain Management Through Ar...

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4th international conference on Sentiment analysis and Deep Learning, ICSADL 2025

作者： Sharma, Ayushi Kumar, Rakesh Kumar, Deepak Pandey, Purnendu Shekhar Awasthi, Shashank Uttaranchal Institute of Management Uttaranchal University Uttarakhand Dehradun India Graphic Era Deemed to Be University Department of Management Studies Dehradun India Army Institute of Technology Pune India G.L. Bajaj Institute of Technology and Management India

ISBN: (纸本)9798331523923

The aim of this study is to examine Artificial intelligence(AI) applications in the supply Chain process. According to recent research on Supply Chain Management (SCM) in AI technology and various other technologies (machine learning, deep learning, neural network, expert vision, artificial neural network). Supply Chain Management (SCM) is transforming to artificial intelligence (AI), which improves sustainability, accuracy, and efficiency. This study explores AI in inventory management, warehouse management, customer satisfaction etc. AI Transportation, inventory control, and demand forecasting are all made easier by technologies like computer vision, robotics, and machine learning. Global sustainability goals are in line with AI, but adoption is hampered by issues like labour skill gaps, algorithmic biases, cybersecurity threats, and data quality. Training for the workforce, effective data management, and sustainable procedures are among the recommendations. AI is a key component of SCM's future since it can promote innovation, operational excellence, and sustainable development. The study contributes the objectives to analysis about AI reduced overall cost in supply chain management and also to study and analysis about AI enhanced quality and quantity of product in supply chain management. The study also discussed the SCM through the demand and supply concept economically. There are many challenges like biasness in the algorithm, skill person, and compromise with accuracy which need to be addressed. Finally, the study recommends suggestions and discusses the limitations of AI in supply chain management including sustainable future scope. © 2025 IEEE.

关键词： Customer satisfaction

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Spot the Difference: A Novel Task for Embodied Agents in Changing Environments 26

Spot the Difference: A Novel Task for Embodied Agents in Cha...

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26th international conference on pattern Recognition / 8th international Workshop on Image Mining - Theory and Applications (IMTA)

作者： Landi, Federico Bigazzi, Roberto Cornia, Marcella Cascianelli, Silvia Baraldi, Lorenzo Cucchiara, Rita Univ Modena & Reggio Emilia Modena Italy

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Embodied AI is a recent research area that aims at creating intelligent agents that can move and operate inside an environment. Existing approaches in this field demand the agents to act in completely new and unexplored scenes. However, this setting is far from realistic use cases that instead require executing multiple tasks in the same environment. Even if the environment changes over time, the agent could still count on its global knowledge about the scene while trying to adapt its internal representation to the current state of the environment. To make a step towards this setting, we propose Spot the Difference: a novel task for Embodied AI where the agent has access to an outdated map of the environment and needs to recover the correct layout in a fixed time budget. To this end, we collect a new dataset of occupancy maps starting from existing datasets of 3D spaces and generating a number of possible layouts for a single environment. This dataset can be employed in the popular Habitat simulator and is fully compliant with existing methods that employ reconstructed occupancy maps during navigation. Furthermore, we propose an exploration policy that can take advantage of previous knowledge of the environment and identify changes in the scene faster and more effectively than existing agents. Experimental results show that the proposed architecture outperforms existing state-of-the-art models for exploration on this new setting.

关键词： Three-dimensional displays Navigation Layout pattern recognition Intelligent agents Task analysis Artificial intelligence

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Synchronization analysis of stochastic Cohen-Grossberg neural networks driven by G-Brownian motion with inertial terms 2

Synchronization analysis of stochastic Cohen-Grossberg neura...

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2nd international conference on robotics, Artificial intelligence and Intelligent Control, RAIIC 2023

作者： Wang, Yaqian Yang, Jun Gou, Jinhao Xu, Shiqiang Southwest Minzu University College of Electrical Engineering Chengdu China

ISBN: (纸本)9798350328004

In this paper, the exponential synchronization (ES) of stochastic Cohen-Grossberg neural networks driven by G-Brownian motion with inertial terms (G-SCGNNIs) is studied. The original system is transformed into another system by variable substitution. Through establishing an appropriate Lyapunov function and using G-Itô formula, the exponential synchronization criterion of the system is discovered. Ultimately, a numerical simulation example is provided to validate the theoretical result. © 2023 IEEE.

关键词： Lyapunov functions

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Determining traffic node reliability by fuzzy fault tree analysis and small scaled model 22

Determining traffic node reliability by fuzzy fault tree ana...

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IEEE Joint 22nd international Symposium on Computational intelligence and Informatics / 8th IEEE international conference on Recent Achievements in Mechatronics, Automation, Computer Science and robotics (CINTI-MACRo)

作者： Tompa, Ilona Bakucz, Peter Gabor, Kiss Obuda Univ Banki Donat Fac Mech & Safety Engn Budapest Hungary

ISBN: (纸本)9798350398823

In this paper, we outline the analysis of a traffic node's safety using a fuzzy fault tree method and a small-scaled model to gain information on the reliability of the node. The reliability of the dynamics of the node is determined by using the fuzzy FTA optimized minimal cut set procedure in a planned, small-scaled real environment, which requires testing the procedure in real-time and in an embedded environment. The optimization is based on percolation theory.

关键词： fuzzy fault tree minimum cut set percolation theory autonomous vehicles scaled model

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