检索结果-内蒙古大学图书馆

5th international conference on Smart and Sustainable Technologies, SpliTech 2020

作者： Vukadinovic, Dinko Basic, Mateo Ho Nguyen, Cat Duy Nguyen, Tien Lan Vu, Nhu Bubalo, Matija University of Split Fesb Split Croatia Duy Tan University Institute of Theoretical and Applied Research Viet Nam Tai Nguyen University of Technology Faculty of Electronics Engineering Tai Nguyen Viet Nam Tang Long University Faculty of Mathematics and Informatics Hanoi Viet Nam

ISBN: (纸本)9789532901054

this paper deals with a variable-speed wind energy conversion system (WECS), which is designed for dc load supply and battery charging in stand-alone applications. the PI speed controller, which is typically used in vector control systems with a self-excited induction generator (SEIG), is here replaced with a hedge-algebra controller (HAC). With this type of controller, it is possible to achieve a faster response and reduced overshoot/undershoot in the wind turbine (WT) speed in comparison with the PI controller. Fuzziness parameters and the linguistic rule base of the HAC are obtained by applying a genetic-algorithm-based optimization, which implies minimization of a predefined performance index. In this paper, the integral absolute error of the SEIG rotor speed is selected as the performance index, with the maximum overshoot/undershoot in the rotor speed during transients limited to 5%. the HAC is here for the first time implemented as the speed controller of the WT-driven SEIG. Simulation results show fast rotor speed responses obtained with the optimized HAC, which are superior to the PI controller responses. © 2020 University of Split, FESB.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Hybrid 6D Object Pose Estimation from the RGB Image 16

Hybrid 6D Object Pose Estimation from the RGB Image

引用

16th international conference on informatics in control, automation and robotics (ICINCO)

作者： Staszak, Rafal Belter, Dominik Poznan Univ Tech Inst Control Robot & Informat Engn Poznan Poland

ISBN: (纸本)9789897583803

In this research, we focus on the 6D pose estimation of known objects from the RGB image. In contrast to state of the art methods, which are based on the end-to-end neural network training, we proposed a hybrid approach. We use separate deep neural networks to: detect the object on the image, estimate the center of the object, and estimate the translation and "in-place" rotation of the object. then, we use geometrical relations on the image and the camera model to recover the full 6D object pose. As a result, we avoid the direct estimation of the object orientation defined in SO3 using a neural network. We propose the 4D-NET neural network to estimate translation and "in-place" rotation of the object. Finally, we show results on the images generated from the Pascal VOC and ShapeNet datasets.

关键词： Object Pose Estimation Convolutional Neural Networks Deep Learning in robotics

来源：评论

学校读者我要写书评

暂无评论

Smart City Air Quality Prediction using Machine Learning

Smart City Air Quality Prediction using Machine Learning

引用

international conference on ent Computing and control Systems (ICICCS)

作者： Rishanti Murugan Naveen Palanichamy Faculty of Computing and Informatics Multimedia University Cyberjaya Selangor Malaysia

Air pollution in smart cities in the world has been drastically increasing lately and the increase in the concentration of particulate matter (PM2.5) in the air is a threat for the country and citizens as it can out-t... 详细信息

Air pollution in smart cities in the world has been drastically increasing lately and the increase in the concentration of particulate matter (PM_2.5) in the air is a threat for the country and citizens as it can out-turn unbearable consequences such as cardiovascular disease and worsen asthma. PM_2.5 is a deadly air pollutant that is a mixture of solid and liquid coarse particles and has a diameter of 2.5 micrometres. In Malaysia, traffic congestion has been the main contributor to developing air pollution in smart cities such as Kuala Lumpur and Johor Bahru. the systemic way of air pollution prediction using machine learning has been widely studied globally over the years and many machine learning algorithms were studied and tested to find the solution to air pollution in their country. However, very few approaches were done in Malaysia to predict air pollution using machine learning methods. this study aims to implement machine learning algorithms to find the accuracy of the prediction of particulate matter, PM_2.5 in air pollution in smart cities of Malaysia. To test the implementation of machine learning in this prediction, Multi-Layer Perceptron (MLP), and Random Forest are chosen and compared between these two algorithms using the Malaysia Air Pollution dataset. the outcome of this research is that Random Forest gave the best accuracy in prediction of Particulate Matter, PM_2.5 Air Pollution Index in smart cities of Malaysia than MLP.

关键词： Micrometers Machine learning algorithms Liquids Smart cities Air pollution Solids Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

PREFACE

引用

Journal of Mathematical Sciences (United States) 2024年第3期280卷 275-277页

作者： Meskhi, Alexander Natroshvili, David Kutaisi International University 5th Lane K Building Kutaisi 4600 Georgia A. Razmadze Mathematical Institute I. Javakhishvili Tbilisi State University 2 Merab Aleksidze II Lane Tbilisi 0193 Georgia Department of Mathematics Faculty of Informatics and Control Systems Georgian Technical University 77 Kostava Str. Tbilisi Georgia

this is a preface for the special issue "Selected papers of the XIII Annual international conference of the Georgian Mathematical Union. © the Author(s), under exclusive licence to Springer Nature Switzerlan... 详细信息

关键词： Andrea Razmadze Annual international conference of the Georgian Mathematical Union Georgian Mathematical Union Viktor Kupradze

来源：评论

学校读者我要写书评

暂无评论

Progression of Human Hand Trajectory Variabilities during a Pick-and-Place Task 16

Progression of Human Hand Trajectory Variabilities during a ...

引用

16th international conference on informatics in control, automation and robotics (ICINCO)

作者： Kuehnlenz, Kolja Hermann, Sergej Kalb, Kevin Marschollek, Lucas Kuehnlenz, Barbara Coburg Univ Appl Sci & Arts Robot Res Lab Dept Elect Engn & Comp Sci D-96450 Coburg Germany Tech Univ Munich Inst Cognit Syst Dept Elect Engn & Informat Technol D-80290 Munich Germany

ISBN: (纸本)9789897583803

this paper investigates the progression of human hand trajectory variabilities during a pick-and-place task. A user study is conducted and human hand positions are tracked optically. Standard deviations of human hand positions over all trajectories within a trial are computed point-wise orthogonally to the direct path between start and goal positions. Statistical tests reveal a decrease of standard deviations from hand start to goal positions. Moreover, stronger variations of standard deviations are noted in during the center part of the trajectories. Contrary to expectations, a longitudinal study design does not reveal learning effects in terms of reduction of trajectory variabilities. the results suggest, that uncertainties of human hand positions increase with the distance to a goal location and could constitute a larger risk for collisions within a cooperative human-robot pick-and-place scenario, e.g. assembly.

关键词： robotics Human-robot Interaction Human Factors

来源：评论

学校读者我要写书评

暂无评论

Mobile Technologies in Blended Learning of Engineering Students in Digital Measurements on Geodetic Equipment 5

Mobile Technologies in Blended Learning of Engineering Stude...

引用

5th international conference on Information Technologies in Engineering Education, Inforino 2020

作者： Solnyshkova, Olga Dudysheva, Elena State University of Economics and Managemen Department of Engineering Geodesy Novosibirsk State University of Architecture and Civil Engineering SIBSTRIN Environmental Safety and Management Department Novosibirsk Novosibirsk Russia Shukshin Altai State University for Humanities and Pedagogy Department of Mathematics Physics Informatics Biysk Russia

ISBN: (纸本)9781728148106

Vocational training of engineering students includes digital measurements using a lot of portable devices and instruments. the probability of erroneous actions also significantly increases with complications and number of devices. At the initial stages of training, students are encouraged to master the basic actions with virtual laboratory equipment before start and further in the process of working with devices. the article discusses the possible options for hybrid laboratory construction to support engineering courses such as enginery geodesy at the University of Architecture and Civil Engineering. Hybrid laboratories provide both physical and online forms of operation with the same equipment or devices of the same functionality. Since online tools should simulate correct and erroneous sampling with the possibility of user's automated control the choice of virtual tools rather than remote access to production laboratory equipment is more preferable for didactic tasks at initial stages. A simple configuration of hybrid learning environment based on interactive virtual learning tools and mobile devices is offered for training of inexperienced students to make digital measurements on geodetic equipment. the hybrid environment is equally suitable for use in stationary university laboratories and for terrain practice. In conclusion, the article discusses the use of distance and mobile technologies in blended learning for students using flipped class and professional business game methods in the engineering geodesy course at the University of Architecture and Civil Engineering. © 2020 IEEE.

关键词： Engineering education

来源：评论

学校读者我要写书评

暂无评论

Development of Scenario-Type Robot Recreation Program for the Elderly with Dementia and Its Evaluation 5

Development of Scenario-Type Robot Recreation Program for th...

引用

5th international conference on Universal Village, UV 2020

作者： Itai, Shiroh Shimoda, Atsushi Yoneoka, Toshihiko Hamada, Toshimitsu Tsukuba Gakuin University Economics and Informatics Department Tsukuba Japan Chiba Institute of Technology Department of Project Management Narashino Japan Passe-temps ASAMADAI Misuzukai Social Welfare Corporation Ageo Japan

ISBN: (纸本)9781728195230

In Japan where the super-aging society is rapidly growing, we expect that the work burden of the care staff in a welfare facility for the elderly should be reduced, and robot-assisted recreation (RAR) has attracted attention. therefore, in the current research, we propose a scenario-type robot recreation program as an initial research to systematize the implementing method of RAR. And we developed a scenario-type robot recreation program that was aimed at activating communication of the elderly with dementia. this program consisted of "ball game with robots,""contact with robots,""gymnastics with robots,"and "sing with robots"activities. We also developed a system to operate the robot using a smart device. therefore, even the care staff of a nursing home who do not have any specialized knowledge about robots could control these robots without any problems. Our experimental results demonstrated that the scenario-type robot recreation increased the level of participation of the elderly with dementia compared with the conventional non-scenario-type robot recreation. Furthermore, we confirmed the increase in the frequency of communication and the time for expressing positive emotions when the elderly with dementia participated in the scenario-type robot recreation. © 2020 IEEE.

关键词： Robots

来源：评论

学校读者我要写书评

暂无评论

Modern Network Technologies and Dependability 3

Modern Network Technologies and Dependability

引用

3rd international Science and Technology conference "Modern Network Technologies 2020", MoNeTeC 2020

作者： Netes, Victor Moscow Technical University of Communications and Informatics Department of Communication Networks and Switching Systems Moscow Russia

ISBN: (数字)9781728182681

ISBN: (纸本)9781728182681

this paper discusses the dependability issues of modern network technologies. these include cloud computing, software-defined networking, Internet of things, the 5th generation mobile networks. Particular attention is paid to the selection of appropriate dependability measures, target values for them, and methods for dependability assurance. the consideration is based on standards and other documents of international organizations (ITU, IEC, ISO, 3GPP). Inconsistencies and inaccuracies in some of these documents regarding dependability are identified. the necessity of using end-to-end availability in service level agreements for cloud computing is rationalized. the complexity of estimating end-to-end network availability for software-defined networks is justified, and the lower bound for it is derived. For Internet of things systems, the use of the effectiveness retention ratio as a dependability measure is suggested. © 2020 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Research on water quality prediction method based on AE-LSTM

Research on water quality prediction method based on AE-LSTM

引用

automation, control and robotics Engineering (CACRE), international conference on

作者： Huiqing Zhang Kemei Jin School of Automation Department of Informatics Beijing University of Technology

ISBN: (数字)9781728198880

ISBN: (纸本)9781728198897

Aiming at the traditional prediction methods of related parameters that affect water quality, they usually only consider the temporal characteristics of the related parameters of water quality and ignore the problem that water quality changes are multivariate related, A prediction method of spatiotemporal correlation water quality parameters based on automatic encoder(AE) dimensionality reduction and long and short time memory(LSTM) neural network is proposed. Firstly, considering that water quality parameter changes have obvious time characteristics, a time series prediction model of water quality parameters is established based on LSTM. Secondly, considering that the water quality changes have multiple correlations, the upstream water quality will also affect the downstream water quality. If all the water quality parameters of the upstream station are added to the prediction model, redundant features will reduce the accuracy of parameter prediction. therefore, the automatic encoder is used to reduce the dimensionality of the relevant parameters. Finally, the data set of Lang fang Water Quality Automatic Monitoring Station is applied to monitor the effectiveness of the method. By predicting the concentration of total phosphorus(TP) and total nitrogen(TN), the method is found to have better prediction accuracy and robustness.

关键词： long-short-term memory network auto-encoder water quality prediction feature extraction multivariate correlation

来源：评论

学校读者我要写书评

暂无评论

Human-aware Robot Navigation in Logistics Warehouses 16

Human-aware Robot Navigation in Logistics Warehouses

引用

16th international conference on informatics in control, automation and robotics (ICINCO)

作者： Kenk, Mourad A. Hassaballah, M. Brethe, Jean-Francois Normandy Univ Electrotech & Automat Res Grp GREAH Le Havre France South Valley Univ Dept Math Qena Egypt South Valley Univ Dept Comp Sci Luxor Egypt

ISBN: (纸本)9789897583803

Industrial and mobile robots demand reliable and safe navigation capabilities to operate in human populated environments such as advanced manufacturing industries and logistics warehouses. Currently mobile robot platforms can navigate through their environment avoiding coworkers in the shared workspace, considering them as static or dynamic obstacles. this strategy is efficient for safety, strictly speaking, but is not sufficient to provide humans integrity and comfortable working conditions. To this end, this paper proposes a human-aware navigation framework for comfortable, reliable and safely navigation designed to run in real-time on a mobile robot platform in logistics warehouses. this is accomplished by estimating human localization using RGB-D detector, then generating a virtual circular obstacle enclosing human pose. this virtual obstacle is then fused with the 2D laser range scan and used in ROS navigation stack local costmap for human-aware navigation. this strategy guarantees a different approach distance to obstacles depending on the human or non-human nature of the obstacle. Hence the mobile robot can approach closely to pallet to pick up objects while maintaining an integrity distance to humans. the reliability of the proposed framework is demonstrated in a workbench of experiments using simulated mobile robot navigation in logistics warehouses environment.

关键词： Human-aware Navigation Collision Avoidance Human Detection in RGB-D Camera 2D-LIDAR Sensor Logistics Warehouses Mobile Robot Autonomous Navigation robotics

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：