检索结果-内蒙古大学图书馆

16th International Conference on Social Robotics, ICSR + InnoBiz 2024

作者： Yan, Shuya Li, Xiaocong Qian, Huaming Ma, Jun Al Mamun, Abdullah College of Intelligent Systems Science and Engineering Harbin Engineering University Harbin150001 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore Guangzhou China Information Science and Technology Eastern Institute of Technology Ningbo China

ISBN: (纸本)9789819611508

In robotics applications, ensuring reliable performance in the presence of actuator faults is essential for maintaining system safety and reliability. This paper presents a tolerant tracking control method for permanent magnet synchronous motors (PMSMs) based on adaptive dynamic programming and fault compensation. The method simultaneously considers tracking accuracy and energy consumption through a policy iteration algorithm. In the optimality analysis of the algorithm, more relaxed conditions are provided to demonstrate that the performance function can converge to a near-optimal value within a finite number of iterations. In practical implementation, an actor-critic network is used to approximate the performance function and control protocol, alongside a fault detection mechanism based on an expanded time horizon, which achieves fault detection from arbitrary initial values. The effectiveness of the proposed algorithm is verified using a high-fidelity PMSM model in Simulink. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Permanent magnets

来源：评论

学校读者我要写书评

暂无评论

A Secure and Efficient Framework for Multi-Round Data Trading Over the Internet of Artificially Intelligent Things

引用

IEEE Internet of Things Magazine 2022年第1期5卷 119-124页

作者： Zheng, Xu Zhang, Lizong Hui, Bei Tian, Ling Cai, Zhipeng School of Computer Science and Engineering University of Electronic Science and Technology of China China School of Information and Software Engineering University of Electronic Science and Technology of China China Georgia State University Department of Computer Science United States

IoT data trading has greatly benefited the popularization of both the Internet of Things (IoT) and Artificial Intelligence of Things (AIoT). Current solutions mainly treat the dataset owned by each device as a commodity and focus on maintaining a data market. Meanwhile, inspired by recent achievements in distributed machine learning and federated learning, AIoT can actually realize its services by retaining the data locally on devices and only exchanging model parameters. However, existing IoT data trading methods fail to meet this secure and efficient process. Therefore, this article proposes a novel framework for data trading over AIoT. It allows the service provider to trade on deep learning model training instead of purchasing the full datasets. Key factors for the security issues and data pricing are addressed for the framework, including the design of the learning parameters and the comprehensive privacy concerns. Then a novel data trading strategy is proposed for the service provider to jointly maintain the model performance and the budget consumption. Evaluation results reveal the improvements on the model performance. Finally, some open problems in the design of data trading in AIoTs are discussed. © 2018 IEEE.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Open-Source Simulators for Drone-Assisted Vehicular Ad Hoc Networks

Open-Source Simulators for Drone-Assisted Vehicular Ad Hoc N...

引用

International Conference on Data Analytics and Management, ICDAM 2022

作者： Kumar, Santosh Vasudeva, Amol Sood, Manu Department of Computer Science Himachal Pradesh University Shimla India Department of Computer Science and Engineering Jaypee University of Information Technology Himachal Pradesh Solan Waknaghat India

ISBN: (纸本)9789811976148

Intelligent transportation systems (ITS) are a collection of cutting-edge technologies that are intended to offer a variety of road traffic management and safety services. The number of automobiles on the road and flying in three-dimensional (3D) space has increased dramatically, increasing the risk of accidents and other security issues. A new technology based on the network composed of flying drones, mobile vehicles, and ad hoc infrastructure known as UAV-assisted vehicular ad hoc network (VANET), a subtype of mobile ad hoc network (MANET), is designed to deal with security issues observed in VANETs. The applications or protocols designed for vehicular safety in such a network should be thoroughly tested before deployment. In many scenarios, simulations with the help of readily available tools play a significant role within the limited scope of testing in research at various levels. Therefore, such simulation tools and their appropriate selection for specific purposes are essential for validating any research concept before being implemented in various real-world network scenarios. This paper explores available open-source simulators that can be used to simulate UAV-assisted VANETs. Additionally, a comparison based on various features of simulators has also been presented aimed at helping in the selection of a particular tool for specific problems. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Vehicular ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Optimizing accuracy and efficiency in real-time people counting with cascaded object detection

引用

International Journal of information technology (Singapore) 2024年 1-14页

作者： Holla, M. Raviraja Suma, D. Holla, M. Darshan Department of Information and Communication Technology Manipal Institute of Technology Manipal Academy of Higher Education (MAHE) Karnataka Manipal 576104 India Department of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education (MAHE) Karnataka Manipal 576104 India

Growing concerns about public safety have driven the demand for real-time surveillance, particularly in monitoring systems like people counters. Traditional methods heavily reliant on facial detection face challenges due to the complex nature of facial features. This paper presents an innovative people counting system known for its robustness, utilizing holistic bodily characteristics for improved detection and tallying. This system achieves exceptional performance through advanced computer vision techniques, with a flawless accuracy and precision rate of 100% under ideal conditions. Even in challenging visual conditions, it maintains an impressive overall accuracy of 98.42% and a precision of 97.51%. Comprehensive analyses, including violin plot and heatmaps, support this outstanding performance. Additionally, by assessing accuracy and execution time concerning the number of cascading stages, we highlight the significant advantages of our approach. Experimentation with the TUD-Pedestrian dataset demonstrates an accuracy of 94.2%. Evaluation using the UCFCC dataset further proves the effectiveness of our approach in handling diverse scenarios, showcasing its robustness in real-world crowd counting applications. Compared to benchmark approaches, our proposed system demonstrates real-time precision and efficiency. © The Author(s) 2024.

关键词： Cascaded detector computer vision Object detection People counting Real-time

来源：评论

学校读者我要写书评

暂无评论

Integrating Deep Q-Networks and YOLO with Autonomous Robots for Efficient Warehouse Management 5

Integrating Deep Q-Networks and YOLO with Autonomous Robots ...

引用

5th IEEE International Conference on Recent Trends in computer Science and technology, ICRTCST 2024

作者： Vivek, N. Suriya, A. Kamala, V. Chinnasamy, N.V. Akshya, J. Sundarrajan, M. Choudhry, Mani Deepak SRM Institute of Science and Technology Department of Computational Intelligence Chennai India KGiSL Institute of Technology Department of Computer Science and Engineering Coimbatore India Karpagam Academy of Higher Education Department of Computer Science Coimbatore India SRM Institute of Science and Technology Department of Networking and Communications Chennai India KGiSL Institute of Technology Department of Information Technology Coimbatore India

ISBN: (纸本)9798350351378

Autonomous robotic cars' rapid, accurate, and efficient product handling and navigation are changing warehouse inventory management. These 24/7 smart vehicles save labor costs, human error, and operational inefficiencies. Time-consuming and incorrect manual scanning and recording is used for inventory management. Traditional autonomous car Q-learning algorithms may suffer in dynamic inventory circumstances and lack the complexity needed for real-time decision-making. Our research creates novel algorithms for autonomous robotic cars. The Deep Q-Network (DQN) we utilize for navigation adapts better to changing circumstances than ordinary Q-learning. YOLO object detection replaces slower QR code recognition for inventory monitoring. We use Decision Trees to find QR code data insights for decision-making. Our research results are promising. A greater cumulative reward curve over 100 simulated episodes gives DQN a 40% learning efficiency advantage over Q-learning. With 95% accuracy, YOLO outperformed Haar Cascade classifiers in QR code detection by 40% speed and 15% accuracy. Decision Trees identified QR code data 5.9% better than Rule-Based Systems, indicating inventory dependability. Autonomous robots can simplify inventory management in warehouses. Algorithmic technology allows these ambulances to drive intelligently, detect warehouse things faster and more accurately, and make decisions based on complicated data. These advanced artificial intelligence algorithms may make robotic systems more responsive and customized, changing inventory management subfields. These algorithms must be updated so autonomous cars can drive to meet logistical needs. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Flying Ad Hoc Network (FANET): Opportunities, Trending Applications and Simulators

Flying Ad Hoc Network (FANET): Opportunities, Trending Appli...

引用

2022 IEEE Pune Section International Conference, PuneCon 2022

作者： Parihar, Ashish Singh Chakraborty, Swarnendu Kumar National Institute of Technology Nit Department of Computer Science and Engineering Arunachal Pradesh Jote India Jaypee Institute of Information Technology Department of Computer Science & Engineering and Information Technology Uttar Pradesh India

ISBN: (纸本)9781665498975

Flying objects have always been an exciting and attractive world to feel and watch. It ranges from a fly-enabled playing toy to commercial planes. When it comes to the wireless networking domain, flying ad hoc network plays a vital role in managing and handling unmanned aerial vehicles (or drones) to serve a variety of real-time applications like inagriculture, remote sensing, terrorist location tracking, good delivery, weather prediction, forest fire monitoring and many more. Since these drones have flying capacity without any assistance from human personnel, their applicability regions are growing day by day. Now a days, this field is a center point of attraction for the researcher community due to its highly dynamic attributes and hence through this work, we present various research opportunities in this domain of drone-based networks along with a discussion to its trending applications. We have also discussed various existing simulators that are capable of modeling this kind of ad hoc domain in their platforms and are quite helpful for future investigators to understand the best-suited environment for their art-of-works in regard to this field. © 2022 IEEE.

关键词： Routing protocols

来源：评论

学校读者我要写书评

暂无评论

QUALYST: Data Quality Assessment System for Thailand Open Government Data 20

QUALYST: Data Quality Assessment System for Thailand Open Go...

引用

20th International Joint Conference on computer Science and Software engineering, JCSSE 2023

作者： Samakit, Tanapat Anutariya, Chutiporn Buranarach, Marut School of Engineering and Technology Asian Institute of Technology Computer Science & Information Management Ict Department Thailand National Electronics and Computer Technology Center Data Science and Analytics Research Group Thailand

ISBN: (纸本)9798350300505

Open Government Data (OGD) refers to the provision of data produced by the government to the general public, in a format that is readily readable and can be used by machines with ease. It can also promote transparency, improve decision-making, enhance accountability, create economic opportunities, and encourage civic engagement. The OGD can help citizens understand the government and its legitimacy and transparency. Thus, when the government shares its data with people, it helps to create trust by being transparent, accountable, and promoting innovative solutions that benefit everyone. However, each published dataset has no indication of its quality assessment at all;thus, making it difficult for citizens to assess the reliability of the data from the OGD. Therefore, a data quality assessment for OGD should be developed. This will help create effective datasets which in turn help users understand the data. This study proposes QUALYST, a system that assesses Thailand's OGD dataset and validates it for analytic and visualization purposes. The study focuses on designing the data storage and implementing the assessment system. Furthermore, the proposed data quality dimensions, the developed data pipeline, and the assessment process are elaborated. Finally, the prototype system is demonstrated using Thailand's OGD datasets with examples in a visualized format. © 2023 IEEE.

关键词： Transparency

来源：评论

学校读者我要写书评

暂无评论

Utilizing Cutting-Edge Machine Vision Techniques for Swift Anomaly Detection in Suboptimal Surveillance Environments 3

Utilizing Cutting-Edge Machine Vision Techniques for Swift A...

引用

3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Yadav, Rakesh Kumar Veena, C.S. Sudhamsu, Gadug Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh India Presidency University Department of Electronics and Communication Engineering Karnataka Bangalore India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India

ISBN: (纸本)9798350343274

In the realm of surveillance and anomaly detection, the proposed Adaptive Multimodal Anomaly Detection (AMAD) method stands as an innovative and potent approach. The objective of this method is to detect anomalies swiftly and accurately in suboptimal surveillance environments by amalgamating state-of-the-art machine vision techniques with multimodal data fusion. The core idea revolves around leveraging advanced deep learning architectures and statistical models, thereby enhancing the performance of anomaly detection systems. The AMAD method initiates with Algorithm 1: Multimodal Data Fusion, a process that involves integrating multimodal data streams, such as visual, thermal, and infrared information, into a unified feature space. This integration is accomplished using a weighted sum approach, allowing varying importance levels to be assigned to each modality based on weights (α, β, γ). This fusion strategy proves pivotal in capturing a holistic representation of the environment. Convolutional Neural Network (CNN) for Feature Learning follows, where a CNN architecture is employed to learn robust and discriminative features from the fused data. This study showcases that AMAD, with its multimodal integration, deep learning-based feature extraction, and efficient scoring mechanism, triumphs over traditional anomaly detection techniques. It significantly contributes to enhanced anomaly detection capabilities, emphasizing its potential for bolstering public safety and security in dynamic and challenging technological landscapes. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Ethical Implications of Gen-AI and LLMs in Computing Education 2024

Ethical Implications of Gen-AI and LLMs in Computing Educati...

引用

1st ACM Virtual Global Computing Education Conference V. 2, SIGCSE Virtual 2024

作者： Zarb, Mark Brown, John N.A. Goodfellow, Martin Liaskos, Konstantinos Young, Tiffany School of Computing Engineering and Technology Robert Gordon University Aberdeen United Kingdom Department of Computer and Information Sciences University of Strathclyde Glasgow United Kingdom

ISBN: (纸本)9798400706042

The panel convenes five educators to discuss the ethical implications of utilising Generative AI (Gen-AI) and Large Language Models (LLMs) in computing education. Their expertise spans various domains, including organising national workshops on the implications of generative AI tools, conducting surveys on their use within curricula, implementing institutional policies related to technology use, and engaging with students directly in the classroom. They reflect on the evolution of Gen-AI and LLMs from challenging-to-use technologies to indispensable tools for users of all levels. Furthermore, they examine the ethical dilemmas arising from the widespread adoption of these technologies in educational contexts, particularly regarding issues of originality, integrity, and responsible use. In addition, they explore practical strategies for integrating ethics education into computing curriculum design and classroom practices. This includes discussions on the role of educators in guiding students towards ethical technology usage, addressing uncertainties surrounding Gen-AI tools, and fostering a culture of responsible innovation within educational institutions. Through their collective insights and experiences, the panel aims to provide recommendations for navigating the ethical complexities inherent in the integration of Gen-AI technologies into computing education curricula. © 2024 Copyright held by the owner/author(s).

关键词： Ethical technology

来源：评论

学校读者我要写书评

暂无评论

Augmenting Content Retrieval Through Machine Learning 3

Augmenting Content Retrieval Through Machine Learning

引用

3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Pavan, P.S. Sripriya, T. Vikas, B. Shivank Parmar, Yuvraj Acharjya, Kalyan Faculty of Engineering and Technology Department of Civil Engineering Karnataka Ramnagar562112 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350319125

gadget getting to know is a subset of synthetic intelligence that focuses on making predictions via reading and getting to know patterns from records. In current years, machine studying has been increasingly more carried out to numerous fields consisting of natural language processing, laptop vision, and records analytics. in the field of content material retrieval, system gaining knowledge of strategies are used to enhance the effectiveness and efficiency of search algorithms, making it less complicated for customers to discover the information they ***, content retrieval structures depend on indexing and key-word-based totally strategies to retrieve applicable information. even as these strategies have been powerful, they have barriers in dealing with complicated queries and information the context of the facts being searched for. this is where machine learning is available in, providing the functionality to research and learn from big amounts of facts to enhance the accuracy and relevance of search consequences. through the usage of machine getting to know, content retrieval systems can better recognize the purpose at the back of a person's query and generate more correct outcomes. that is accomplished through strategies such as natural language processing, which allows the system to recognize and extract which means from text and speech. moreover, gadget gaining knowledge of can be carried out to study from past person interactions and feedback to continuously enhance the search enjoy. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：