检索结果-内蒙古大学图书馆

IEEE International Conference on automation Science and engineering (CASE)

作者： Boyuan Zhang Rui Lai Guanghong Gong Haitao Yuan Jinhong Yang Jia Zhang MengChu Zhou School of Automation Science and Electrical Engineering Beihang University Beijing China CSSC Systems Engineering Research Institute in Beijing China Department of Computer Science Lyle School of Engineering at Southern Methodist University Dallas TX USA Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Wireless Sensor Networks (WSNs) have been widely deployed, and it is crucial to enhance their network longevity and transmission efficiency. This work comprehensively considers communication interference, transmission rate constraints, and motion constraints of Unmanned Aerial Vehicles (UAVs). We propose an energy-efficient UAV-assisted WSN framework with big data transmission. To minimize the weighted sum of UAV’s and WSNs’ energy consumption, we jointly optimize sensor clustering, path planning, and time window allocation by an improved intelligent optimization algorithm assisted by deep learning named Variational Multidimensional Optimization (VMO) with co-evolved Multiple Subpopulations, noted as VMOMS for short. The effectiveness of the proposed VMOMS algorithm for solving high-dimensional problems is demonstrated through numerical analysis and simulation results. These findings highlight the efficiency and practicality of the designed UAV-assisted hierarchical architecture of WSNs, thereby showcasing its potential to enable reliable data transmission from remote WSNs to a centralized cloud server.

关键词： Wireless sensor networks Clustering algorithms Big Data Autonomous aerial vehicles Path planning Energy efficiency Peer-to-peer computing Resource management Optimization Convergence

来源：评论

学校读者我要写书评

暂无评论

3D Modeling for a Flexible Detector in VR Radiography Simulator

3D Modeling for a Flexible Detector in VR Radiography Simula...

引用

International Conference on Information Technologies in engineering Education (Inforino)

作者： Vladimir Kuvshinnikov Evgeny Kovshov Valery Korchagin Research Laboratory of Digital Computer Systems and Automation JSC “Research and Development Institute of Construction Technology - Atomstroy” Moscow Russian Federation Disruptive Engineering School of Chemical Engineering and Machinery Dmitry Mendeleev University of Chemical Technology of Russia Moscow Russian Federation

ISBN: (数字)9798350371369

ISBN: (纸本)9798350371376

Digital simulators based on virtual reality expand the range of educational opportunities and improve the quality of learning in various areas of knowledge through deeper “immersion” in the learning process. Attention to the details of the modeled process plays an important role. One of the tasks of interactive simulators is to provide an opportunity to see the relationship between the user’s actions and the obtained qualitative and quantitative parameters and quality attributes of the simulated process result. Considered the issue of curved shape detectors application relevance in the practice of penetrating radiation evaluation in general and in industrial radiography in particular. The prerequisites for the creation of flexible (bendable) form of digital radiographic detectors and the features of two generations of practically implemented devices are analyzed. Development of a flexible detector digital twin is considered, models and algorithms for its realization in a virtual reality environment are proposed, and the main results of computational and laboratory experiments as well as the obtained radiographic images are presented. The main task of virtual reality technologies within the qualified technical specialists training programs is the development of their professional skills and the formation of stable behavior patterns that ensure strict compliance with the rules and requirements of industrial safety, thereby ensuring the high quality of the end product.

关键词： Radiography Training Solid modeling Ionizing radiation Computational modeling Detectors Virtual reality

来源：评论

学校读者我要写书评

暂无评论

Digital Educational Resources in Industrial Radiography

Digital Educational Resources in Industrial Radiography

引用

International Conference on Information Technologies in engineering Education (Inforino)

ISBN: (数字)9798350371369

ISBN: (纸本)9798350371376

Nowadays, the technological level of production is an important factor for all areas of modern economic development and life quality improvement. Neither in the informational, nor in the industrial sphere it is possible to produce in-demand, modern, and therefore high-tech and complex products without the establishment of an appropriate system of quality examination at multiple stages of production. This article deals with the problem of forming a comprehensive educational environment with the use of heterogeneous educational resources in the training of specialists in the radiation type of nondestructive testing. The purpose of the research and development is to address the shortcomings of classroom, remote digital learning, and laboratory practice listed in the article by developing a solution based on virtual reality technologies. The purpose stated lies in the pursuit of intensive solutions to the existing problems. Extensive development paths are not effective in improving the efficiency of training and checking students’ knowledge in the context of the rapidly growing demand for nondestructive testing specialists. The concept of a digital twin as an educational resource is considered. The structural approach to the formation of complex educational resources both at the level of organization and at the level of digital product is presented. The structure of interrelationships between data in the formation of a digital twin of a radiographic image is presented. The results of the radiographic image simulation and its quality verification are shown.

关键词： Training Radiography Nondestructive testing Training data Production Organizations Throughput

来源：评论

学校读者我要写书评

暂无评论

Realizing Global Citizen Solutions for Sustainable Development Goals: A Collaborative engineering Course Between Thai and Japanese Students 23

Realizing Global Citizen Solutions for Sustainable Developme...

引用

23rd International Symposium on Communications and Information Technologies, ISCIT 2024

作者： Sae-Jia, Thanachot Leelawat, Natt Tang, Jing Murakami, Rie Taoka, Yuki Ota, Eri Punyabukkana, Proadpran Chulalonkorn University Faculty of Engineering Department of Environmental Engineering Bangkok Thailand Chulalongkorn University Faculty of Engineering Department of Industrial Engineering Bangkok Thailand Chulalongkorn University Disaster and Risk Management Information Systems Research Unit Bangkok Thailand Graduate School of System Design and Management Keio University Yokohama Japan International School of Engineering Chulakongkorn University Faculty of Engineering Bangkok Thailand Global Education Section Center for Entrepreneurship Education Tokyo Institute of Technology Tokyo Japan School of Environment and Society Tokyo Institute of Technology Tokyo Japan Chulalongkorn University Faculty of Engineering Department of Computer Engineering Bangkok Thailand

ISBN: (纸本)9798350353952

One of the problems faced by engineering and science students is focusing solely on technical knowledge while needing more cultural context. In today's interconnected world, addressing global challenges necessitates collaborative efforts from individuals across nations. Accordingly, a joint course between Chulalongkorn University in Thailand and the Tokyo institute of Technology in Japan has been established. The recent theme of the course, 'Gamification towards Sustainable Development Goals (SDGs),' aimed to foster global citizenship and address SDGs through multicultural collaboration. This study examines the similarities and differences in problem identification between Thai and Japanese student groups participating in the course. Data was collected from discussions, presentations, and group assignments throughout the course. The findings indicate that while both groups share common concerns, such as waste management, language barriers, and transportation issues, their perspectives and proposed solutions are influenced by cultural characteristics. Thai students emphasized infrastructural inadequacies and local traditions, whereas Japanese students focused on efficiency and the impacts of tourism. The study highlights the importance of understanding cultural nuances in collaborative international projects to achieve effective and innovative solutions to global challenges. © 2024 IEEE.

关键词： Sustainable development goals

来源：评论

学校读者我要写书评

暂无评论

Enhancing Sentiment Analysis on SEED-IV Dataset with Vision Transformers: A Comparative Study 23

Enhancing Sentiment Analysis on SEED-IV Dataset with Vision ...

引用

Proceedings of the 2023 11th International Conference on Information Technology: IoT and Smart City

作者： Imad Eddine Tibermacine Ahmed Tibermacine Walid Guettala Christian NAPOLI Samuele Russo Department of Computer Automation and Management Engineering Sapienza Unviersity of Rome Italy Department of Computer Science University of Biskra Algeria Department of Computer Automation and Management Engineering Sapienza Unviersity of Rome Italy and Institute for Systems Analysis and computer Science Italian National Research Council Italy and Department of Computational Intelligence Czestochowa University of Technology Poland Department of Psychology Sapienza Unviersity of Rome Italy

ISBN: (纸本)9798400709043

This paper introduces a new approach to emotion classification utilising deep learning models, specifically the Vision Transformer (ViT) model, in the analysis of electroencephalogram (EEG) signals. A dual-feature extraction approach was implemented in our study, utilising Power Spectral Density and Differential Entropy, to analyse the SEED IV dataset. This methodology resulted in the detailed classification of four distinct emotional states. The ViT model, which was originally designed for image processing, has been successfully applied to EEG signal analysis. It demonstrated remarkable performance by attaining a test accuracy of 99.02% with little variance. Notably, it outperformed conventional models like GRUs, LSTMs, and CNNs in this context. The findings of our study indicate that the ViT model has a high level of effectiveness in accurately identifying complex patterns present in EEG data. Specifically, the precision and recall rates achieved by the model surpass 98%, while the F1 score is estimated to be about 98.9%. The results of this study not only demonstrate the efficacy of transformer-based models in analysing cognitive states, but also indicate their considerable potential in improving systems for sympathetic human-computer interaction.

关键词： Classification Deep Learning EEG Signal Analysis Vision Transformer

来源：评论

学校读者我要写书评

暂无评论

High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

引用

Journal of Bionic engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

来源：评论

学校读者我要写书评

暂无评论

Motion Planning Integrated with Vehicle-Terrain Interactions for Off-Road Autonomous Ground Vehicles 27

Motion Planning Integrated with Vehicle-Terrain Interactions...

引用

27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Yin, Jianhua Zhan, Xianyuan Ji, Tianying Xu, Bingrong He, Yi Zhang, Daqing Li, Lingxi Wuhan University of Technology Intelligent Transportation Systems Research Center Wuhan430063 China Engineering Research Center of Transportation Information and Safety Ministry of Education Wuhan430063 China Chongqing Research Institute Wuhan University of Technology Chongqing China Institute for Ai Industry Research Tsinghua University Beijing100084 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Tsinghua University Department of Computer Science and Technology Beijing100084 China School of Automation Wuhan University of Technology Wuhan430070 China College of Mechanical and Electrical Engineering Hunan Agricultural University Changsha410128 China Sunward Intelligent Equipment Co. Ltd. Changsha410100 China Elmore Family School of Electrical and Computer Engineering College of Engineering Purdue University IN46202 United States

ISBN: (纸本)9798331505929

Off-road autonomous ground vehicles (AGVs) work in unstructured environments with varied elevation and deformable ground, where vehicle-terrain interactions are more complex resulting in unpredictable dynamics behavior. Current sensor-based hazards/obstacle identification methods mainly focus on geometric hazards/obstacles with explicit geometry, which might be adequate for vehicles in on-road conditions. However, in the off-road environment, vehicle-terrain interactions could introduce non-geometric hazards that cannot be detected by current geometric hazards-oriented sensing techniques, e.g. vehicle stuck in mud. To enable AGVs to traverse the target terrain and meet the goal while avoiding non-geometric hazards, this work proposes a motion planning method integrated with coupled vehicle-terrain dynamics response. Specifically, terramechanics-based modeling and simulation (M&S) is utilized to characterize vehicle-terrain interactions. Based on the dynamics response, a reinforcement learning (RL) algorithm with a specialized reward function is used to navigate the AGV to find the goal with high mobility and safety. We demonstrate the proposed method with two case studies, 1) high mobility is the foremost concern with less safety requirement, and 2) both high mobility and safety are required. The results show that the proposed motion planning method is effective for navigating the AGV in off-road terrains. © 2024 IEEE.

关键词： Off road vehicles

来源：评论

学校读者我要写书评

暂无评论

Pothole Detection in Asphalt Roads: A Comprehensive Approach for Enhanced Road Maintenance and Safety with AlexNet Model

Pothole Detection in Asphalt Roads: A Comprehensive Approach...

引用

2024 International Telecommunications Conference, ITC-Egypt 2024

作者： Abdelmalak, Mark Emad Sobhi Khodadadi, Nima Zaki, Ahmed Mohamed Eid, Marwa M. Rizk, Faris H. Ibrahim, Abdelhameed Abdelhamid, Abdelaziz A. Abualigah, Laith El-Kenawy, El-Sayed M. Delta Higher Institute of Engineering and Technology Department of Communications and Electronics Mansoura35111 Egypt University of Miami Department of Civil and Architectural Engineering Coral GablesFL United States Computer Science and Intelligent Systems Research Center BlacksburgVA24060 United States Delta University for Science and Technology Faculty of Artificial Intelligence Mansoura35111 Egypt Bahrain Polytechnic Faculty of Engineering Isa Town Bahrain Ain Shams University Faculty of Computer and Information Sciences Department of Computer Science Cairo11566 Egypt Al al-Bayt University Computer Science Department Mafraq25113 Jordan Middle East University MEU Research Unit Amman11831 Jordan Jadara University Jadara Research Center Irbid Jordan

ISBN: (纸本)9798350351408

The research article described in this paper puts forward a novel method of using an integrated software approach and high-end hardware devices for adaptive and intelligent detection of potholes on asphalt roads. The Pothole Detection Dataset is used for the dataset analysis, and we put VGG19Net, ResNet-50, GoogLeNet, and AlexNet among the computer vision models to analyze the applicability of these models. Different types of networks were compared, and AlexNet showed the best results as it achieved 92.15% accuracy, 91.38 % sensitivity (TPR), and a surprisingly high F-score, which reached 96.52%. Furthermore, by using its time of 279.35 seconds, which might be considered very fast, AlexNet shows many strengths in helping to do this, as well as identifying road anomalies, making it a perfect candidate for real-world utilization. This research demonstrates the emergence of sophisticated integrated pothole repair solutions, emphasizing the importance of both software and hardware in developing sophisticated pothole detection. Practices and this research could be an example for further surveying road inspection technologies. © 2024 IEEE.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

Low-Latency and Energy-Efficient Task Scheduling for End-Edge-Cloud Collaborative Computing

Low-Latency and Energy-Efficient Task Scheduling for End-Edg...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Jingyao Li Haitao Yuan Yaofei Ma Jing Bi Jinhong Yang Jia Zhang School of Automation Science and Electrical Engineering Beihang University Beijing China College of Computer Beijing University of Technology Beijing China CSSC Systems Engineering Research Institute Beijing China Dept. of Computer Science Southern Methodist University Dallas TX USA

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Mobile edge computing (MEC) is a new paradigm that improves the quality of service compared with traditional cloud computing. In MEC, computational tasks are submitted by numerous end users and are partially offloaded to edge servers or a central cloud. However, the characteristics of tasks are different from each other, and the limited resources of computational nodes are also heterogeneous, which brings great challenges to computation offloading and resource allocation for MEC. This work establishes an end-edge-cloud collaborative computing network, which consists of end devices, edge servers, and a central cloud. Task execution location and CPU running frequency determine the execution time and energy consumption to finish the tasks. Considering the aforementioned factors, a multi-objective constrained optimization problem is formulated. To solve the problem, an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II) with self-adaptive crossover and mutation rates is proposed, which is called Improved NSGA-II with _Self-adaptive Crossover and Mutation (INSCM). The total execution time and energy consumption can be jointly minimized with our proposed INSCM. Numerous experiments are carried out to test the performance of INSCM. Simulation results show that INSCM effectively improves the performance of NSGA-II and surpasses random offloading and NSGA-III, which shows practical use in real-life scenarios.

关键词： Energy consumption Cloud computing Time-frequency analysis Multi-access edge computing Simulation Collaboration Servers Optimization Sorting Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Prediction of Stroke Risk Within 7-Years Follow Up Using Machine Learning Models

Prediction of Stroke Risk Within 7-Years Follow Up Using Mac...

引用

2023 IEEE EMBS Special Topic Conference on Data Science and engineering in Healthcare, Medicine and Biology, IEEECONF 2023

作者： Tsarapatsani, Konstantina-Helen Sakellarios, Antonis Tsakanikas, Vasilis D. Rudolf, Henrik Trampisch, Hans J. Pezoulas, Vasileios C. Matsopoulos, George K. Fotiadis, Dimitrios I. University of Ioannina Unit of Medical Technology and Intelligent Information Systems Dept. of Materials Science and Engineering IoanninaGR 45110 Greece Biomedical Research Institute Greece Institute for Biostatistics and Informatics in Medicine and Ageing Research University Medical Center Rostock Germany Ruhr University Bochum Department of Medical Informatics Biometry and Epidemiology Bochum Germany National Technical University of Athens School of Electrical and Computer Engineering Athens Greece

ISBN: (纸本)9798350383386

A stroke, also known as brain attack, occurs when blood supply to your brain is interrupted. Primary prevention relies on prompt prediction of a stroke. While currently there are several clinical risk scores, machine learning (ML) models seems to be more suitable tools for accurate prediction of stroke events. Therefore, this work focuses on the prediction of stroke within 7 years follow-up in patients who have not suffered from a stroke or TIA event at baseline. LightGBM (LGBM), Extreme Grading Boosting (XGBoost), Support Vector Machine (SVM) and Decision Tree were employed in the getABI dataset, which includes 5,897 participants. The performance of models was calculated by Accuracy (ACC), Sensitivity (SENS), Specificity (SPE) and area under the receiver operating characteristic curve (AUC) of each model. According to the comparison analysis's results, LGBM has been shown to be the most trustworthy algorithm, with accuracy 68 %. Moreover, sex, age, status of peripheral artery disease (PAD), history of myocardial infarction, angina pectoris, amputation and diabetes and pulse status of different arteries can be used as a simple and cost-effective way to predict *** Relevance: A fatal medical emergency, stroke may be anticipated using artificial intelligence, and the sooner it is predicted, the more cerebrovascular disease occurrences can be avoided. © 2023 IEEE.

关键词： Forecasting

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：