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A New Unified Frame and System of Bionic Variable Structure robots: Design and applications 17th

A New Unified Frame and System of Bionic Variable Structure ...

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17th international conference on Intelligent robotics and applications

作者： Wang, Hai Lou, Huanhuan Men, Song Wang, Baoliang Xu, Bocheng Wu, Qingxiang Su, Yuanhao Liu, Huawang Sun, Ning Nankai Univ Coll Artificial Intelligence Inst Robot & Automat Informat Syst Tianjin 300350 Peoples R China Nankai Univ Shenzhen Res Inst Inst Intelligence Technol & Robot Syst Shenzhen 518083 Peoples R China Inspur Yunzhou Ind Internet Co Ltd Jinan 250101 Peoples R China Shandong Special Equipment Inspect & Res Inst Co Jinan 250000 Peoples R China

ISBN: (纸本)9789819607976;9789819607983

robots have been applied in various industries. Nonetheless, conventional robots have difficulties coping with challenges from complex environments and limited spaces. In this paper, a new unified frame and system are designed to provide effective solutions for the technology and system development of bionic variable structure robots (BVSRs). Specifically, we design a complete communication architecture to measure data, feedback information, and send and receive commands between various hardware. Additionally, BVSRs are controlled by the commands from Raspberry Pi, Arduino, and a flight controller based on measured data. Finally, the designed frame and system are applied to two types of BVSRs, including terrestrial-aerial amphibious robots (TAARs) and bionic variable structure UAVs (BVS-UAVs). Experimental results demonstrate that the designed BVSRs achieve stable control in variable modes.

关键词： System frame Variable structure Bionic robots

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Enhancing Haemorrhage Detection in Head CT Scans Using Deep Learning 3

Enhancing Haemorrhage Detection in Head CT Scans Using Deep ...

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3rd international conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Kumar, Aditya Nelson, Leema Kumar, Sudhakar Chitkara University Institute of Engineering & Technology Chitkara University Punjab Rajpur India Chandigarh College of Engineering and Technology Cse Department Chandigarh India

ISBN: (纸本)9798350319125

This work investigates the application of deep learning for haemorrhage detection in head CT scans. The aim of this work is to develop a robust model for accurate detection, even with limited data. The Sequntional CNN model is utilised to detect the haemorrhage CT scans, consisting of convolutional layers to extract features, dense layers for classification, pooling layers for dimensionality reduction, and dropout layers for regularisation. This model uses the data augmentation technique to enhance the training data through transformations like rescaling, shearing, and rotation. This model mitigates overfitting and enhances the overall robustness of the model. Moreover, this model provides significant improvement in accuracy, reaching 94.99%. This performance highlights data augmentation, enhancing the generalisation capacity of the model. The developed model outperforms other deep learning models used in similar applications. This work highlights the adaptability of deep learning in medical image analysis and its potential to enhance healthcare applications, with implications for improved patient outcomes. © 2023 IEEE.

关键词： Artificial intelligence deep learning head CT scans head haemorrhage Sequentional CNN model

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Research and trend of key technology of mining mobile robot mapping 3

Research and trend of key technology of mining mobile robot ...

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3rd international conference on Mechatronics and Mechanical Engineering, ICMME 2024

作者： Wang, Junlin Sun, Shanshan Hu, Lianxin Wang, Zefeng Lin, Minghai Qi, Xiaoyu Ji, Wenjie Wang, Huajun Chu, Yan Huzhou University ZheJiang Huzhou313000 China Huzhou Key Laboratory of Waters Robotics Technology ZheJiang Huzhou313000 China

ISBN: (纸本)9781510681651

The change in maps after accidents poses significant inconvenience for personnel and rescue teams. Focused on surface and underground mining exploration maps, and considering the rapid emergency response of mining exploration robots, efforts are directed at determining optimal technical combinations by Analysising encompasses navigation positioning, wireless communication, data processing, and real-time mapping. Specially, in surface mining environments, inertial navigation combined with LiDAR(LIght Detection And Ranging) technology excels, considering factors like error accuracy, application scenarios, data processing capability, detection range, reliability, and cost. Wi-Fi technology is commonly used for data transmission. In underground mining environments, a combination of inertial navigation and visual technology, typically employing Zigbee wireless communication, is more suitable. Detailed analysis of real-time mapping techniques, emphasizing the comparison between laser SLAM (Simultaneous Localization and Mapping) and visual SLAM, as well as improvements in ORB-SLAM1-3(a Versatile and Accurate Monocular SLAM System), is presented. Finally, the prospects and trends of artificial intelligence in mobile robot map exploration are discussed, aiming to provide more accurate, reliable, and efficient solutions for mining exploration. These research findings contribute to optimizing the performance of intelligent mining exploration robots, enhancing their application capabilities in mining exploration and emergency rescue. © 2024 SPIE.

关键词： Zigbee

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Intelligent Computing for Healthcare: A Survey 3

Intelligent Computing for Healthcare: A Survey

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3rd international conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Vijeta Singh, K.M. Singh, Ashish Kalinga Institute of Industrial Technology School of Computer Engineering Odisha Bhubaneswar751024 India

ISBN: (纸本)9798331523893

The healthcare sector is increasingly adopting intelligent systems to address the growing demand of medical services. The system transforms medical services by leveraging advanced computational techniques and healthcare innovation. The advanced technologies of computing models include Artificial intelligence (AI), Machine Learning (ML), Edge Computing (EC), Quantum Computing, Cloud Computing, Neuromorphic Computing, and many more. It significantly improves resource utilization, patient outcomes, efficiency, diagnostic accuracy, and real-time decision-making. This survey systematically reviews the latest IC models, analyzing their architectures, operational mechanisms, and performance metrics. This survey includes the strengths and weaknesses of different IC models. A comparative analysis of existing approaches is provided to identify their strengths, limitations, and applicability to various healthcare scenarios. A generic IC framework will help to understand the development of new computing models. In addition, this survey paper discussed the features and applications of IC in healthcare. The insights presented in this paper aim to bridge existing gaps and provide a foundation to advance IC-driven healthcare solutions. © 2025 IEEE.

关键词： Supervised learning

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Design of Mixed Reality Assembly System Based on Improved ORB Algorithm 3

Design of Mixed Reality Assembly System Based on Improved OR...

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3rd international conference on Computer Vision, Image and Deep Learning and international conference on Computer Engineering and applications, CVIDL and ICCEA 2022

作者： Lu, Na Xiao, YongFei Zhao, Jie Shandong Provincial Key Laboratory of Robot and Manufacturing Automation Technology ShanDong China Harbin Institute of Technology Institute of Automation Shandong State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9781665459112

This paper studies the natural feature point detection algorithm in a virtual assembly system. To address the problems of unsatisfactory detection effect and poor matching accuracy of the ORB algorithm, a feature uniform distribution algorithm based on pyramidal grid division is proposed, and a strategy of retaining feature points according to Harris response values is formulated to solve the problem of feature point aggregation while ensuring extraction speed. Hamming distance and the RANSAC algorithm are used to constrain the matching results. The robot assembly system based on this algorithm overlays the 3D model of the spraying robot and virtual information in the mobile device to improve the assembly efficiency of the staff. The experimental results show that the mixed reality(MR) assembly system based on the algorithm of this paper performs well, and the real-time performance and alignment accuracy are improved. © 2022 IEEE.

关键词： Assembly

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Business intelligence Model for Customer Targeting Using Fuzzy-C-Means and FP-Growth 3

Business Intelligence Model for Customer Targeting Using Fuz...

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3rd international conference on Emerging Smart Technologies and applications, eSmarTA 2023

作者： Ahmed Mohammed, Sam Abdulilah Saeed, Mogeeb A. Software Engineering Taiz University Taiz Yemen Computer Networks and Distributed Systems Taiz University Taiz Yemen

ISBN: (纸本)9798350305333

In the era of business, business intelligence (BI) technology can inform the decision-maker of the right data and insight. In this study, a business intelligence model is built to help the marketing department build an efficient promotion strategy. This paper aims to understand the impact of segmenting customers using the soft clustering technique (fuzz-c-means) based on their spending behavior or Recency, Frequency, and Monetary Model (RFM model) on product affiliation or market basket analysis to develop more efficient promotions to target customers. This aim is approached first by, downloading a dataset called online retail from Kaggle, exploring data to remove the missing value and detect and remove outliers, and constructing an RFM model (Recency, frequency, and monetary). Second, the clustering algorithm is performed fuzzy-c-means, to segment customers into clusters with similar characteristics. Third, product affiliation or association rules are obtained as per cluster using the FP-growth algorithm. Eventually, spending behavior is concluded to show a significant impact on product affiliation which means that clustering based on spending behavior increases the efficiency of market basket analysis (MBA). © 2023 IEEE.

关键词： Decision making

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Conflict Between Artificial intelligence and Traditional Designers: How Artificial intelligence Transforms the Design Process 3rd

Conflict Between Artificial Intelligence and Traditional Des...

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3rd international conference on Emerging Trends in Expert applications and Security, ICE-TEAS 2024

作者： Gupta, Keshav Dev Pandey, Rishi Pathak, Devendra Nath Ranjan, Rakesh Gupta, Vijay Department of Computer Science Engineering Poornima College of Engineering Rajsthan Jaipur India Department of Animation & Multimedia Birla Institute of Technology Ranchi Mesra India Department of Computer Science & Engineering Poornima College of Engineering ISI-6 RIICO Institutional Area Sitapura Rajasthan Jaipur India Department of Computer Science & Engineering Babu Banarasi Das University Lucknow India Department of Computer Science International School of Informatics and Management Sector 12 Mahaveer Marg Jaipur Mansarovar India

ISBN: (纸本)9789819739905

The development of technology, especially the use of resources provided by artificial intelligence (AI), has advanced in areas where business is gaining importance and is an important fear of economic growth. The use of technical skills in the creation of products and services is not unique to design. In today's world, artificial intelligence (AI) has become an industry in many countries, and design is no exception. However, the lines of work performed by humans and machines are changing rapidly, and as a result, the global market is also changing a lot. This is the result of very rapidly developing technology. This raises the question of how this progress has and will continue to influence the future work of designers. What skills do designers need to enter or stay in this industry? The purpose of this article is to provide a summary of research findings on the impact of intelligence on the performance of designers, as well as an analysis that includes an evaluation of the potential and benefits of intelligent design solutions. Case studies and other scientific studies are used to analyze the applications and benefits of AI-based solutions. Studies can be theoretical or empirical. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： international trade

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Research and application of key technologies of power grid model data management based on blockchain 3

Research and application of key technologies of power grid m...

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3rd IEEE international conference on Information technology, Big Data and Artificial intelligence, ICIBA 2023

作者： Yibo, Wang Tianxun, Zhang Yong, Zhang Jinwei, Zhang Yue, Zhang North China Branch of State Grid Corporation of China Xicheng District Beijing100032 China Beijing Business University School of Artificial Intelligence 10048 China Beijing Electric Chain Technology Co. Ltd CHAOyang District Beijing100020 China

ISBN: (纸本)9781665490788

At present, the operation and management of the power grid is complex and changeable, and the information islands between each link are obvious. In the process of promoting the transformation of the power grid, the blockchain technology meets the needs of multi-level collaborative management of power grid dispatching. Using the tamper proof and traceable characteristics of the blockchain technology, it can effectively solve the security and reliability problems of the interaction of regulatory data. Firstly, based on the characteristics of blockchain technology, this paper deeply analyzes the feasibility of integration of smart grid regulation business and deep application of blockchain. Secondly, according to the characteristics of smart grid dispatching application, the dispatching blockchain application architecture is designed, and the research on key technologies of the integration of blockchain technology and power dispatching application is carried out. Finally, with the tamper-proof and traceable characteristics of blockchain technology, the dispatching metadata management applications are deployed. Blockchain encryption technology and consensus mechanism are used to provide unified and traceable on-chain metadata which achieves effective control of the dispatching business system data. © 2023 IEEE.

关键词： Smart contract

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Transforming Healthcare with Federated Learning-based Artficial intelligence: Concepts, Classifications, and Challenges 3

Transforming Healthcare with Federated Learning-based Artfic...

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3rd international conference on Sentiment Analysis and Deep Learning, ICSADL 2024

作者： Uma Maheswari, G. Gnana Jeslin, J. Rajasuguna, M. Amutha, S. RMK College of Engineering and Technology Tamil Nadu Chennai India RMK College of Engineering and Technology Department of Computer Science and Engineering Tamil Nadu Pudhuvayal Chennai India RandD Institute of Science and Technology Vel Tech Rangarajan Dr.Sagunthala Tamil Nadu Chennai India

ISBN: (纸本)9798350396157

The realm of intelligent healthcare has seen a surge in discussions about transformative technologies, with a focus on federated learning (FL), artificial intelligence (AI), and explainable AI (XAI). Traditionally, healthcare data has been centralized, with a limited number of entities sharing raw data across the industry. However, this approach poses significant risks and challenges. Introducing AI into the healthcare ecosystem opens the door to a multitude of agent collaborators, each capable of working alongside their chosen host. The decentralized nature of FL is a noteworthy aspect, as it ensures that raw data remains within its source while enabling model-based communication within the system. The fusion of FL, AI, and XAI offers the potential to address some of the system's limitations and challenges. This article delves deep into the ways in which FL is revolutionizing healthcare facilities through AI integration. We begin by examining the current landscape of futuristic technologies, including FL, AI, XAI, and their relationship with the healthcare sector. We categorize FL in conjunction with AI, exploring a wide array of applications in healthcare IT. Key issues within the healthcare domain, such as privacy, security, stability, and reliability, are addressed. Furthermore, we showcase practical use cases of FL and AI in medical settings. We conclude by shedding light on the various future directions and avenues of research in the management of healthcare using FL-based AI. In this article, we offer insights into the development and implementation of the Contribution-Aware Federated Learning (CAreFL) system for intelligent healthcare. This system not only optimizes the FL model aggregation process based on evaluation results but also assesses the contributions of FL participants in a fair and transparent manner, ensuring efficiency and confidentiality. © 2024 IEEE.

关键词： Health care

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Improved A* algorithm for path planning in dynamic environments 3

Improved A* algorithm for path planning in dynamic environme...

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3rd international conference on Algorithms, Microchips, and Network applications, AMNA 2024

作者： Hu, Chenhao Zhang, Zhian School of Mechanical Engineering Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9781510680098

To improve the global path planning capabilities of mobile robots and achieve real-time obstacle avoidance, a robot path planning algorithm that improves the traditional A* algorithm is proposed. The A* algorithm is utilized for the design of global path planning, incorporating weight coefficients into the heuristic function to bolster search efficiency. Path smoothing is performed by improving the Floyd algorithm, aiming to reduce inflection points and increase the path smoothness. For local path planning, the artificial potential field method is adopted to address the real-time obstacle avoidance limitations of the A* algorithm. Simultaneously, local corrections are applied to mitigate potential issues associated with local minima in the artificial potential field method. Additionally, attempts are made to navigate around obstacles by fine-tuning the turning angle. Simulation results validate that the improved A* algorithm can effectively construct reasonable paths in the map environment with better search mechanism and flexibility. The improved artificial potential field algorithm successfully achieves real-time obstacle avoidance, surpassing local optimal points. © 2024 SPIE.

关键词： Motion planning

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