检索结果-内蒙古大学图书馆

International Workshop on Advanced Motion Control (AMC)

作者： Andrej Sarjaš Martin Steinberger Dušan Gleich Martin Horn Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia Graz University of Technology Institute of Automation and Control Graz Austria

ISBN: (数字)9781728131894

ISBN: (纸本)9781728131900

The paper presents experimental assessments of different event-triggered sliding mode control strategies. The main purpose of the event-triggered control approach is to reduce the system utilization and relax the scheduling of the tasks on real-time systems. Event triggering is a real-time implementation technique, where the execution of the controller is not fixed to a preselected sampling time. The stability and performance of the controlled system need to be preserved with regard to the sporadic nature of the controller update. Sliding mode controllers are employed in the context of event-triggering to achieve robustness with respect to matched perturbations. Three different sliding mode event-triggered strategies are evaluated on the real-time positioning system. All the obtained experimental results are compared to a time-triggered version. The results confirm that event-triggering sliding mode control is well suited and reduce the system use drastically.

关键词： Tracking Computational modeling Real-time systems Stability analysis Robustness Task analysis Sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Comparative evaluation of training schemes for the locally recurrent probabilistic neural network 28

Comparative evaluation of training schemes for the locally r...

引用

28th International Scientific Conference Electronics, ET 2019 - Proceedings

作者： Dukov, Nikolay Tinkov Ganchev, Todor Dimitrov Department of Computer Science and Engineering Faculty of Computing and Automation Technical University of Varna 1 Studentska str. Varna9000 Bulgaria

ISBN: (纸本)9781728125749

In the present study we evaluate the performance of various training schemes for the locally recurrent probabilistic neural network and seek for advantageous tradeoffs between required training time and classification accuracy. Specifically, we consider training schemes which make use of a simple incremental procedure for adjusting sigma, as well as methods based on particle swarm optimization or differential evolution in different configurations. The experimental evaluation was carried out in common experimental protocol based on the Parkinson speech dataset. The experimental results show that with a proper training configuration a high accuracy can be achieved even with limited training data. © 2019 IEEE.

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

INSTANCE SEGMENTATION AND TEETH CLASSIFICATION IN PANORAMIC X-RAYS

arXiv

引用

arXiv 2024年

作者： Budagam, Devichand Ghosh, Sayan Imanbayev, Azamat Zhanatuly Kaplun, Dmitrii Rychenkov, Artem Sinitca, Aleksandr Kumar, Ayush Shrivastav, Anuj Akhmetov, Iskander Rafailovich Antonov, Sergey Cyganov, Gleb Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur India School of IT and Engineering Kazakh-British Technical University Almaty Kazakhstan Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes St. Petersburg Electrotechnical University"LETI" St. Petersburg Russia Centre for Digital Telecommunication Technologies St. Petersburg Electrotechnical University"LETI" St. Petersburg Russia Department of Humanities and Social Sciences Indian Institute of Technology Kharagpur Kharagpur India Department of Architecture and Regional Planning Indian Institute of Technology Kharagpur Kharagpur India Faculty of Digital Transformation ITMO University St. Petersburg Russia

Teeth segmentation and recognition are critical in various dental applications and dental diagnosis. Automatic and accurate segmentation approaches have been made possible by integrating deep learning models. Although teeth segmentation has been studied in the past, only some techniques were able to effectively classify and segment teeth simultaneously. This article offers a pipeline of two deep learning models, U-Net and YOLOv8, which results in BB-UNet, a new architecture for the classification and segmentation of teeth on panoramic X-rays that is efficient and reliable. We have improved the quality and reliability of teeth segmentation by utilising the YOLOv8 and U-Net capabilities. The proposed networks have been evaluated using the mean average precision (mAP) and dice coefficient for YOLOv8 and BB-UNet, respectively. We have achieved a 3% increase in mAP score for teeth classification compared to existing methods, and a 10-15% increase in dice coefficient for teeth segmentation compared to U-Net across different categories of teeth. A new Dental dataset was created based on UFBA-UESC dataset with Bounding-Box and Polygon annotations of 425 dental panoramic X-rays. The findings of this research pave the way for a wider adoption of object detection models in the field of dental diagnosis. © 2024, CC BY.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

CEBRA Method: Decoding Brain Activity for Advanced Brain-computer Interface Technology

CEBRA Method: Decoding Brain Activity for Advanced Brain-Com...

引用

Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jingcheng Yang Frank Kulwa Xuanwei Liu Yiqing Lu Yufa Fu Guanglin Li Yaping Huai Xin Zhang Yongcheng Li CAS Key Laboratory of Human-Machine Intelligence Synergy Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences (CAS) Shenzhen China Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Shenzhen Dapeng New District Nanao People’s Hospital Shenzhen China Department of Rehabilitation Medicine Shenzhen Longhua District Central Hospital Shenzhen China Brain Cognition and Brain-Computer Intelligence Integration Group Kunming University of Science and Technology Kunming China Shandong Zhongke Advanced Technology Co. Ltd. Jinan China

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

The emerging neurorehabilitation technology, Brain-computer Interface (BCI), provides a novel prospect for stroke recovery. However, decoding brain activity during the movement present substantial challenges, and feature extraction is crutial to build a better decoder. In this study the CEBRA method were employed to extract features first based on electroencephalogram(EEG) data during Motor Execution(ME) and Motor lmagery (Ml) tasks for 20 participants (including 10 stroke patients). The results revealed that, in MI tasks, CEBRA-RF (Random Forests) achieved an average classification accuracy of 91.33%, with an average F1-score of 91.19%, and CEBRA-SVM (Support Vector Machine) achieved an average classification accuracy of 91.32%, with an average F1-score of 90.83%. Compared to other conventional feature extraction methods, CEBRA shows significantly higher accuracy (t-test, p<0.01). However, in ME tasks, CEBRA-RF achieved an average classification accuracy of 75.67%, with an average F1-score of 75.39%, and CEBRA-SVM achieved an average classification accuracy of 76.13%, with an average F1-score of 75.80%. Nevertheless, no significant differences were observed compared to other feature extraction methods. These findings demonstrate the potential of CEBRA in decoding patients’ brain activity. The results of this study hold promise in addressing the current challenges of low decoding accuracy in BCI systems, offering a new approach for designing BCI-assisted rehabilitation systems for stroke patients.

关键词： Support vector machines Brain Accuracy Stroke (medical condition) Feature extraction Motors Brain-computer interfaces Neurorehabilitation Decoding Paralysis

来源：评论

学校读者我要写书评

暂无评论

3D Semantic Segmentation Algorithm for Indoor Scenes based on Long-term Memory

3D Semantic Segmentation Algorithm for Indoor Scenes based o...

引用

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Ziyang Liu Weihai Chen Jianhua Wang Xingming Wu Haosong Yue Zongju Peng Zhengguo Li School of Automation Science and Electrical Engineering Beihang University Beijing China Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Institute for Infocomm Research Singapore Singapore

ISBN: (数字)9781728151694

ISBN: (纸本)9781728151700

Deep learning has a strong ability to tackle pixel- level labeling tasks in image understanding. However, the disorder and irregularity of 3D point cloud data make it difficult to be applied. Though there are a few approaches that have acquired satisfied results on 3D data processing recently, there is no consideration of the relationships between each point, which plays an important role in indoor objects semantic segmentation and has been proved on plane images. In this paper, a spatial long-term connection of points is modeled by a fully connected conditional random field (CRF) to enhance the memory ability of the network. Since it is infeasible to compute due to the dimension explosion caused by potentially fully connected CRF, a highly efficient method in utilizing linear combination of multiple Gaussian kernels is proposed to approximate it. Finally, the CRF has been integrated into the deep learning framework, making it trainable end-to-end. The test evaluation of the experiments show that this network reaches current benchmarks and have a strong performance on public 3D indoor datasets. From these results, it is concluded that the relationships of each pair of points are conductive to semantic segmentation for indoor scenes.

关键词： Deep learning Three-dimensional displays Semantics Memory modules Labeling Task analysis Kernel

来源：评论

学校读者我要写书评

暂无评论

ASCAPE: An open AI ecosystem to support the quality of life of cancer patients

arXiv

引用

arXiv 2023年

作者： Lampropoulos, Konstantinos Kosmidis, Thanos Autexier, Serge Savić, Miloš Athanatos, Manos Kokkonidis, Miltiadis Koutsouri, Tzortzia Vizitiu, Anamaria Valachis, Antonios Padron, Miriam Quintero Department of Electrical & Computer Engineering University of Patras Patras Greece CareAcross Research CareAcross LTD London United Kingdom Bremen Germany Division of Informatics Faculty of Sciences University of Novi Sad Novi Sad Serbia Institute of Computer Science Foundation for Research and Technology – Hellas Heraklion Crete Greece Research & Innovation Development INTRASOFT International S.A. Luxembourg Luxembourg SPHYNX Research SPHYNX Technology Solutions AG Zug Switzerland Department of Automation and Information Technology Transilvania University of Brasov Brasov Romania Advanta Siemens SRL Brasov Romania Department of Oncology Faculty of Medicine and Health Örebro University Örebro Sweden Atos Research Innovation Atos S.A.E Madrid Spain

The latest cancer statistics indicate a decrease in cancer-related mortality. However, due to the growing and ageing population, the absolute number of people living with cancer is set to keep increasing. This paper presents ASCAPE, an open AI infrastructure that takes advantage of the recent advances in Artificial Intelligence (AI) and Machine Learning (ML) to support cancer patients’ quality of life (QoL). With ASCAPE health stakeholders (e.g. hospitals) can locally process their private medical data and then share the produced knowledge (ML models) through the open AI infrastructure. Copyright © 2023, The Authors. All rights reserved.

关键词： Intelligent systems

来源：评论

学校读者我要写书评

暂无评论

The Energy Efficiency of a Prosumer in a Photovoltaic System

The Energy Efficiency of a Prosumer in a Photovoltaic System

引用

International Symposium for Design and Technology of Electronics Packages (SIITME)

作者： Marius-Alexandru Dobrea Stefan Bichiu Ioana Opris Mihaela Vasluianu Faculty of Automatic Control and Computer Science UPB Bucharest Romania Faculty of Power Engineering UPB Bucharest Romania Collective of Automation and Applied Informatics Faculty of Hidrotehnics UTCB Bucharest Romania

ISBN: (数字)9781728175065

ISBN: (纸本)9781728175072

This article aims to calculate the net income achieved by a prosumer for an existing On-Grid system of photovoltaic panels consisting of a set of 12 poly crystalline panels with a nominal power of 250 Wand 60 cells and an On-Grid inverter (StecaGrid model) with a maximum power of 3000 W. The prosumer is located in southern Romania, Ilfov County. Modeling of the photovoltaic panel in Matlab / SIMULINK was performed using a mathematical model, and it was compared with a real data set. Next, an analysis was made of the energy produced by the photovoltaic system, and the energy consumed by the prosumer, the excess energy being introduced in the national energy system. We have achieved a net income saving for March, so the analyzed photovoltaic system has energy efficiency that can significantly reduce electricity costs over time. Thus, using the Matlab / Simulink model, photovoltaic systems can be designed to satisfy the needs of prosumers.

关键词： Photovoltaic systems Mathematical model Solar power generation Software packages Inverters Temperature Temperature measurement

来源：评论

学校读者我要写书评

暂无评论

Developing an AI literacy test for junior secondary students: The first stage

Developing an AI literacy test for junior secondary students...

引用

IEEE International Conference on Teaching, Assessment and Learning for engineering (TALE)

作者： King Woon Yau Ching Sing Chai Thomas K. F. Chiu Helen Meng Irwin King Savio Wai-Ho Wong Chandni Saxena Yeung Yam Faculty of Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Curriculum and Instruction The Chinese University of Hong Kong Shatin Hong Kong China Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin Hong Kong China Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong China Department of Educational Psychology The Chinese University of Hong Kong Shatin Hong Kong China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong China

Artificial Intelligence (AI) education for K-12 is increasingly important as the emerging AI technologies are pervasively infused into human daily lives. Eleven countries have endorsed and implemented the AI curricula at K-12 levels [1]. The "Five Big Ideas" about AI, as proposed by the Association for the Advancement of Artificial Intelligence (AAAI) and the computer science Teacher Association (CSTA) have emerged to form the core components of K-12 AI education [2], [3]. However, the assessment of students’ learning in AI education for K-12 is still in its initial stage. Surveys and interviews are the major assessing tools based on students’ self- perceptions. Standardized tests on students’ AI literacy are still rare. This paper focuses on the first stage of an AI literacy test based on the Five Big Ideas for Grade 7 to Grade 9 students. The test aims to measure the changes of students’ AI literacy before and after attending a one-year AI course. The preliminary findings show the students have increased in their AI literacy after attending the course. The test can provide insights for understanding students’ competencies and needs in AI literacy and improving the curriculum guidelines for students’ effective learning.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Robust Iterative Learning Control for Spatially Interconnected Systems using 2D Control Theory

Robust Iterative Learning Control for Spatially Interconnect...

引用

European Control Conference (ECC)

作者： Bartłomiej Sulikowski Krzysztof Gałkowski Daniel Trzciński Eric Rogers Anton Kummert Institute of Control and Computation Engineering University of Zielona Góra Zielona Góra Poland Institute of Automation Electronic and Electrical Engineering University of Zielona Góra Zielona Góra Poland Department of Electronics and Computer Science University of Southampton Southampton UK Faculty of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany

This paper develops a class of iterative learning control (ILC) laws for a subclass of uncertain spatially interconnected systems. Model uncertainties appear both in the state and the output equation of the dynamics modeled in the 2D systems setting to which existing results are not applicable. The first stage is to write the dynamics in 2D model form. Then the stability theory for a distinct class of 2D systems known as repetitive processes is used to develop the ILC law in the case of differential dynamics. This analysis results in a design algorithm that can be applied using linear matrix inequalities.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Distributed Nash Equilibrium Seeking in Coalition Games for Uncertain Euler-Lagrange Systems With Application to USV Swarm Confrontation

arXiv

引用

arXiv 2025年

作者： Yuwen, Cheng Wen, Guanghui Zhou, Jialing Luan, Meng Huang, Tingwen School of Automation Southeast University Nanjing210096 China State Key Laboratory of CNS/ATM Beijing Institute of Technology Beijing519088 China Department of System Science School of Mathematics Southeast University Nanjing211189 China Faculty of Computer Science and Control Engineering Shenzhen University of Advanced Technology Shenzhen218055 China

In this paper, a coalition game with local and coupling constraints is studied for uncertain Euler-Lagrange (EL) systems subject to disturbances with unknown bounds. In the coalition game, each agent collaborates with other agents within the same coalition to optimize its coalition’s cost function while simultaneously competing against agents in other coalitions. Under a distributed framework where each agent has access only to its own action, cost function, and constraint parameters, a distributed strategy is proposed to seek the Nash equilibrium (NE). By combining adaptive methods and sign functions, model uncertainties and disturbances with unknown bounds in the EL system are compensated and suppressed, respectively. Furthermore, an integration of adaptive methods and consensus protocols is employed to update the Lagrange multipliers of both local and coupling constraints. A dynamic average consensus is employed to estimate the gradient of coalition function, while the leader-following protocol is adopted to estimate the actions of other agents. By leveraging Lyapunov theory, the NE is proven to be asymptotically stable. Moreover, an unmanned surface vehicle swarm confrontation is meticulously modeled and analyzed in the coalition game framework. A diverse array of tasks, including formation, encirclement, and interception, are systematically formulated. A numerical example demonstrates the effectiveness of the proposed algorithm. Copyright © 2025, The Authors. All rights reserved.

关键词： Lagrange multipliers

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：