检索结果-内蒙古大学图书馆

7th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2024

作者： Farkas, Imre Kovari, Attila Rajcsanyi-Molnar, Monika Institute of Computer Engineering University of Dunaujvaros Department of Computer Systems and Control Technology Dunaujvaros Hungary Eszterházy Károly Catholic University Institute of Digital Technology Faculty of Computer Science Eger Hungary Obuda University Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary John Von Neumann University GAMF Faculty of Engineering and Computer Science Kecskemét Hungary Institute of Social Sciences University of Dunaujvaros Department of Economics and Management Dunaujvaros Hungary

ISBN: (纸本)9798331531119

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills. © 2024 IEEE.

关键词： digital education digital literacy digital-informatics literacy

来源：评论

学校读者我要写书评

暂无评论

Integration of Large Language Models for Autonomous Navigation of a Mobile Robot

Integration of Large Language Models for Autonomous Navigati...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Andrew N. Kravtsov Boris S. Goryachkin Department of Computer Science and Control Systems Bauman Moscow State Technical University Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The paper considers the integration of large language models (LLMs) to improve autonomous navigation of mobile robots. Traditional navigation methods are often limited by rigid algorithms that cannot adapt to dynamic environments. In contrast, LLMs enable robots to interpret complex spatial scenarios and make more informed decisions. The study demonstrates a new approach to robot control using the ROS with Gazebo simulator, where LLMs transform visual and sensory data into navigation commands. Experimental results demonstrate the feasibility of using LLMs to navigate in a pre-undefined environment improving the adaptability and autonomy of robots. The most successful model was the GPT -4o, and the best camera field of view was $90^{\circ}$ . The paper highlights the potential of LLMs in creating more intelligent and intuitive robot control systems.

关键词： Visualization Large language models Heuristic algorithms Robot control Semantics Robot vision systems Radio navigation Transforms Mobile robots Autonomous robots

来源：评论

学校读者我要写书评

暂无评论

Pole Identification using discrete Laguerre expansion and variable projection

引用

IFAC-PapersOnLine 2023年第2期56卷 3994-3999页

作者： Tamás Dózsa Mátyás Szabari Alexandros Soumelidis Péter Kovács Institute for Computer Science and Control Systems and Control Laboratory Eötvös Loránd University Department of Numerical Analysis Eötvös Loránd University Faculty of Science Institute for Computer Science and Control Systems and Control Laboratory Eötvös Loránd University Department of Numerical Analysis

We propose a novel algorithm for identifying the poles of transfer functions describing SISO-LTI (single input single output, linear time invariant) systems. Our Identification method works in the frequency domain and consists of two parts. In the first part, we extend a discrete Laguerre expansion based method with an automatic parameter selection scheme. This allows us to find an initial estimate of the poles of SISO-LTI transfer functions without the need for human intuition. Then, in the second part, we propose a novel optimization problem to improve our initial estimates. The proposed optimization aims to reduce the least squared error of a parameterized model, which can be interpreted as an orthogonal projection of the system's frequency response onto a subspace spanned by Generalized Orthogonal Rational Basis functions (GOBFs). We solve the corresponding nonlinear optimization task using gradient based methods, where we can analytically calculate the gradient of the error functional. Through robust numerical experiments, we investigate the behavior of the developed methods and show that they work even in scenarios, when the transfer function has a high number of poles.

关键词： Frequency domain identification Recursive identification Linear systems Variable Projection Generalized Orthogonal Basis Functions, Malmquist-Takenaka functions

来源：评论

学校读者我要写书评

暂无评论

SRG Analysis of Lur’e systems and the Generalized Circle Criterion

arXiv

引用

arXiv 2024年

作者： Krebbekx, Julius P.J. Tóth, Roland Das, Amritam Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Netherlands Systems and Control Lab HUN-REN Institute for Computer Science and Control Budapest Hungary

Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from some pitfalls that limit its applicability in analysing practical nonlinear systems. We overcome these pitfalls by modifying the SRG of a linear time invariant operator, combining the SRG with the Nyquist criterion, and apply our result to Lur’e systems. We thereby obtain a generalization of the celebrated circle criterion, which deals with broader class of nonlinearities, and provides (incremental) L2-gain performance bounds. We illustrate the power of the new approach on the analysis of the controlled Duffing oscillator. © 2024, CC BY.

关键词： Frequency domain analysis

来源：评论

学校读者我要写书评

暂无评论

On the Efficiency of Economic Activity of Small Enterprises Operating in the Field of Ground Passenger Transportation (Code 34 in All-Russian Classifier of Economic Activities OKVED2)

On the Efficiency of Economic Activity of Small Enterprises ...

引用

International Conference on Management of Large-Scale System Development (MLSD)

作者： Irina Promakhina Department of Information Systems Federal Research Center “Computer Science and Control” of the RAS Moscow Russia

ISBN: (数字)9798350375718

ISBN: (纸本)9798350375725

The aim of the work was to identify factors affecting the total revenue of regional small enterprises operating in the field of ground passenger transportation, and to evaluate the efficiency of these enterprises. This was done using production function and stochastic frontier models. The statistics were taken from the Complete statistical survey of small and medium-sized businesses in 2020.

关键词： Surveys Rails Costs Codes Transportation Stochastic processes Production Large-scale systems Petroleum Business

来源：评论

学校读者我要写书评

暂无评论

AggFollower: Aggressiveness Informed Car-Following Modeling

IEEE Transactions on Intelligent Vehicles

引用

IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Chen, Xianda Yuan, Xinyi Zhu, Meixin Zheng, Xinhu Shen, Shaojie Wang, Xuesong Wang, Yinhai Wang, Fei-Yue Guangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong SAR China School of Transportation Engineering Tongji University Shanghai China Department of Civil and Environmental Engineering University of Washington Seattle WA USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style through pre-defined patterns and failed to encode driving style into data-driven car-following models. To address these limitations, we propose the Aggressiveness Informed Car-Following (AICF) modeling approach, which embeds driving style as a dynamic input feature in data-driven car-following models. In detail, We design driving aggressiveness tokens using four physical quantities (jerk, acceleration, relative speed, and relative spacing) to capture the heterogeneity of driving aggressiveness. These tokens were then embedded into a physics-informed Long Short-Term Memory (LSTM) based car-following model for trajectory prediction. To evaluate the effectiveness of our approach, we conducted extensive experiments based on 12,540 car-following events extracted from the HighD dataset and 24,093 events from the Lyft dataset. Compared to models devoid of considerations for driving aggressiveness levels, AICF exhibits superior efficacy in mitigating the Mean Square Error (MSE) of spacing and collision rate. To the best of our knowledge, this is the first work to directly incorporate real-time driving aggressiveness tokens as input features into data-driven car-following models, enabling a more comprehensive understanding of aggressiveness in car-following behavior. IEEE

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

A network-based bioinformatic analysis for identifying potential repurposable drugs for obesity avoiding hepatic steatosis side-effect

A network-based bioinformatic analysis for identifying poten...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Brunetti, Martina Fiscon, Giulia Costanzo, Alessia Di Arca, Marcello Paci, Paola Sapienza University of Rome Department of Experimental Medicine Rome Italy Sapienza University of Rome Institute for Systems Analysis and Computer Science "a. Ruberti" National Research Council of Rome Department of Computer Control and Management Engineering "a. Ruberti" Rome Italy Sapienza University of Rome Policlinico Umberto I Department of Translational and Precision Medicine Rome Italy Sapienza University of Rome Department of Computer Control and Management Engineering "a. Ruberti" Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (纸本)9798350386226

Obesity is a complex multifactorial disorder characterized by the excess accumulation of body fat that impairs human health due to the risk of developing other diseases, including cardiovascular and hepatic diseases, hypertension, diabetes, hyperlipidemia. Its spread has been progressively accelerating, resulting in an unprecedented epidemic with no significant signs of slowing down any time soon. Drug therapy via the proposal repurposing solutions can represent an actionable treatment strategy, even if the emergence of drug-induced adverse effects can affect the treatment of this pathology. In this study, we propose a network-based analysis to identify a list of drug candidates predicted to be repurposable for obesity that are unlikely to produce specific adverse side-effect, such as hepatic steatosis. © 2024 IEEE.

关键词： Nutrition

来源：评论

学校读者我要写书评

暂无评论

Differential gene correlation analysis to investigate evolutionary divergence between Cardamine hirsuta and Arabidopsis thaliana

Differential gene correlation analysis to investigate evolut...

引用

2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： D'Annunzio, Federica Fiscon, Giulia Bertolotti, Gaia Dello Ioio, Raffaele Paci, Paola Sapienza University of Rome Department of Translational and Precision Medicine Rome Italy Sapienza University of Rome Institute for Systems Analysis and Computer Science 'A. Ruberti' National Research Council of Rome Department of Computer Control and Management Engineering 'A. Ruberti' Rome Italy Sapienza University of Rome Department of Biology and Biotechnology 'Charles Darwin' Rome Italy Department of Computer Control and Management Engineering 'A. Ruberti' Sapienza University of Rome Rome Italy Karolinska Institutet Stockholm Sweden

ISBN: (纸本)9798350386226

Dissecting the intricate regulatory dynamics between genes stands as a critical step towards the development of precise predictive models within biological systems. A highly effective strategy in this pursuit involves an examination of variations in correlation among gene pairs across different conditions trough differential gene correlation analysis. We anticipated that the application of this method to phylogenetically close plant species could reveal powerful insights on how genes' relationships have a fundamental role in evolutionary dynamics. Building upon this principle, our investigation focused primarily on conducting a comprehensive differential correlation analysis of the roots' orthologous genes of two closely related plant species: Cardamine hirsuta and Arabidopsis thaliana. By leveraging their shared phylogenetic proximity, we were able to draw comparisons that shed light on how evolutionary pressures might have shaped their gene regulatory networks. By integrating differential expression analysis, differential correlation analysis and functional enrichment analysis, we offer a robust framework for future studies aiming to unravel the complexities of adaptation and evolution across a wide range of biological systems. © 2024 IEEE.

关键词： Plant diseases

来源：评论

学校读者我要写书评

暂无评论

Learning Reduced-Order Linear Parameter-Varying Models of Nonlinear systems ⁎

引用

IFAC-PapersOnLine 2024年第15期58卷 265-270页

作者： Patrick J.W. Koelewijn Rajiv Singh Peter Seiler Roland Tóth Sioux Technologies B.V. Eindhoven The Netherlands Control Systems Group Eindhoven University of Technology Eindhoven The Netherlands The MathWorks Inc. Natick USA Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor USA Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the learning of a Reduced-Order Linear Parameter-Varying Model (ROLPVM) of a nonlinear dynamical system based on data. This is achieved by a two-step procedure. In the first step, we learn a projection to a lower dimensional state-space. In step two, an LPV model is learned on the reduced-order state-space using a novel, efficient parameterization in terms of neural networks. The improved modeling accuracy of the method compared to an existing method is demonstrated by simulation examples.

关键词： Reduced-order modeling Neural Networks Linear Parameter-Varying Models

来源：评论

学校读者我要写书评

暂无评论

PointPillars Backbone Type Selection for Fast and Accurate LiDAR Object Detection

PointPillars Backbone Type Selection for Fast and Accurate L...

引用

International Conference on computer Vision and Graphics, ICCVG 2022

作者： Lis, Konrad Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031220241

3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolutional neural network on detection accuracy and computation speed. We chose the PointPillars network, which is characterised by a simple architecture, high speed, and modularity that allows for easy expansion. During the experiments, we paid particular attention to the change in detection efficiency (measured by the mAP metric) and the total number of multiply-addition operations needed to process one point cloud. We tested 10 different convolutional neural network architectures that are widely used in image-based detection problems. For a backbone like MobilenetV1, we obtained an almost 4x speedup at the cost of a 1.13% decrease in mAP. On the other hand, for CSPDarknet we got an acceleration of more than 1.5x at an increase in mAP of 0.33%. We have thus demonstrated that it is possible to significantly speed up a 3D object detector in LiDAR point clouds with a small decrease in detection efficiency. This result can be used when PointPillars or similar algorithms are implemented in embedded systems, including SoC FPGAs. The code is available at https://***/vision-agh/pointpillars-backbone. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

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：