检索结果-内蒙古大学图书馆

Mediterranean Conference on control and Automation (MED)

作者： Fotis Panetsos George C. Karras Kostas J. Kyriakopoulos School of Mechanical Engineering Control Systems Lab National Technical University of Athens Athens Greece Dept. of Computer Science and Telecommunications University of Thessaly Lamia Greece

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

This paper addresses the problem of controlling a multirotor UAV with a cable-suspended load. In order to ensure the safe transportation of the load, the swinging motion, induced by the strongly coupled dynamics, has to be minimized. Specifically, using the Twin Delayed Deep Deterministic Policy Gradient (TD3) Reinforcement Learning algorithm, a policy Neural Network is trained in a model-free manner which navigates the vehicle to the desired waypoints while, simultaneously, compensating for the load oscillations. The learned policy network is incorporated into the cascaded control architecture of the autopilot by replacing the common PID position controller and, thus, communicating directly with the inner attitude one. The performance of the proposed policy is demonstrated through a comparative simulation and experimental study while using an octorotor UAV.

关键词： Navigation Attitude control Transportation Reinforcement learning Water pollution Autopilot Sensors

来源：评论

学校读者我要写书评

暂无评论

Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

引用

IEEE Symposium on Network Operations and Management

作者： Árpád Somogyi Tamás Tettamanti Pál Varga Zsolt Szalay Dániel Baranyai Tamás Lovas Dept. of Photogrammetry and Geoinformatics Fac. of Civil Engineering Budapest University of Technology and Economics Budapest Hungary Systems and Control Laboratory Institute for Computer Science and Control of the Eötvös Loránd Research Network Budapest Hungary Dept. of Telecommunications and Media Informatics Fac. of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Dept. of Automotive Technologies Fac. of Transportation Eng. and Vehicle Eng. Budapest University of Technology and Economics Budapest Hungary

One major goal of digital twin technology applied in the Architecture, engineering, and Construction (AEC) Industry is the mapping of roads and road environments with their associated information. Such digital twins can support cost-effective testing, simulations, and the production of mapping backgrounds for automated vehicles and generally for Cooperative, Connected and Automated Mobility (CCAM) developments. The efficient workflow that leads from data acquisition to finished products depends on a number of requirements and knowledge sets. The main contribution of the paper is a general methodology of creating HD-map from point cloud and image data set. Accordingly, the most widely used survey techniques are presented and the requirements for the objects to be derived are summarized. The paper then outlines a general implementation procedure as an expert knowledge through a real-life example, where the results obtained for the ZalaZONE Automotive Proving Ground are demonstrated.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Sliding mode control of a dc-dc dual active bridge using the generalized space-state averaging description

Sliding mode control of a dc-dc dual active bridge using the...

引用

European control Conference (ECC)

作者： Arnau Dò ria-Cerezo Federico M. Serra Domingo Biel Robert Griñ ó Dept. of Electrical Engineering Inst. of Industrial and Control Engineering Universitat Polit&#x00E8 cnica de Catalunya Barcelona Spain Laboratorio de Control Autom&#x00E1 tico (LCA) Universidad Nacional de San Luis and CONICET Villa Mercedes Argentina Dept. of Electronic Engineering Inst. of Industrial and Control Engineering Universitat Polit&#x00E8 Dept. of Automatic Control Inst. of Industrial and Control Engineering Universitat Polit&#x00E8

ISBN: (数字)9789463842365

ISBN: (纸本)9781665479455

This paper presents a sliding mode control strategy for a dc-dc dual active bridge converter. The controller is based on a truncated model obtained using the generalized state space averaging method that transforms the mixed dc-ac dynamics of the converter into a regulation problem. The proposed controller, that uses a dynamic extension to overcome the structural problem of the non-affine control input, provides good results in terms of performance and robustness. Numerical simulations are included to validate the proposed modelling methodology and the control design.

关键词： Bridges State feedback control design Heuristic algorithms Dynamics Transforms Robustness

来源：评论

学校读者我要写书评

暂无评论

Validation of a two-wheel vehicle model using Genetic Algorithm

Validation of a two-wheel vehicle model using Genetic Algori...

引用

International Symposium on Computational Intelligence and Informatics

作者： Attila Widner Balázs Varga Dániel Medgyesi Tamás Tettamanti Dept. of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Fac. of Transportation Engineering and Vehicle Engineering Budapest Hungary Dept. of Innovative Vehicles and Materials John von Neumann University GAMF Fac. of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350398830

Vehicle dynamics simulation is widely used in the automotive industry. The usability of each model depends on how well it can replicate the behaviour of the real vehicle. Each simulation model must go through a thorough investigation process- model validation- before use. Accordingly, the research introduces a comprehensive methodological framework for vehicle dynamics model validation using a sophisticated vehicle dynamics measurement system and a machine learning algorithm. The validation process of a two-wheel vehicle model (bicycle model) is presented where the authors’ previously proposed work is exploited as a base and further developed, i.e. by using a Genetic Algorithm (GA) the vehicle parameters (yaw inertia, axle cornering stiffness) are estimated in an automatized fashion.

关键词： Industries computer science Mechatronics Machine learning algorithms Computational modeling Vehicle dynamics Usability

来源：评论

学校读者我要写书评

暂无评论

BOTQUAS: Blockchain-based Solutions for Trustworthy Data Sharing in Sustainable and Circular Economy

BOTQUAS: Blockchain-based Solutions for Trustworthy Data Sha...

引用

Euromicro Conference on Software engineering and Advanced Applications (SEAA)

作者： Alberto Amico Vincenzo Apicella Devis Bianchini Alberto Butera Matteo Cesana Gabriele Digregorio Massimiliano Garda Valentina Gatteschi Corrado Innamorati Francesco Leotta Stefano Longari Maria Rosa Pizzo Pierluigi Plebani Noemi Romani Letizia Tanca Andrea Vitaletti Stefano Zanero Italtel S.p.A. Palermo Italy Italtel S.p.A. Milano Italy Dept. of Information Engineering University of Brescia Brescia Italy Politecnico di Torino Dip. di Automatica e Informatica Torino Italy Politecnico di Milano Dip. Elettronica Informazione e Bioingegneria Milan Italy Dept. of Computer Control and Management Engineering Sapienza Universita di Roma Rome Italy

ISBN: (数字)9798350380262

ISBN: (纸本)9798350380279

Monitoring business processes within complex supply chains demands efficient data collection and analytics tailored to diverse phenomena. Traditional centralized solutions face limitations in adapting to the dynamic nature of supply chains. This calls for distributed solutions which break the usual architectural assumption to have a central entity in charge of collecting, integrating and offering tools for the analysis. This project, embedded in a larger initiative called MICS, proposes an inno-vative distributed monitoring solution integrating blockchain for a trustworthy and efficient data analytics strategy that preserves data sovereignty in complex collaborative environments. Leveraging the cloud -edge continuum, the solution aims to ensure secure data exchange, adherence to agreements, and real-time analytics. Expected outcomes include an innovative federated architecture, 5G slice management solutions, an adversarial analysis of supply chain security, and a proof-of-concept implementation of the blockchain-based data flow tracking system. These developments aim to enhance the reliability, security, and efficiency of supply chain monitoring in dynamic industrial environments.

关键词： Microwave integrated circuits Data analysis Supply chains Data collection Real-time systems Software reliability Security Monitoring Faces Software engineering

来源：评论

学校读者我要写书评

暂无评论

MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects

Computer Methods and Programs in Biomedicine Update

引用

computer Methods and Programs in Biomedicine Update 2025年 7卷

作者： Lofù, Domenico Sorino, Paolo Colafiglio, Tommaso Bonfiglio, Caterina Donghia, Rossella Giannelli, Gianluigi Lombardi, Angela Di Noia, Tommaso Di Sciascio, Eugenio Narducci, Fedelucio Dept. of Electrical and Information Engineering (DEI) Politecnico di Bari BA Bari 70125 Italy Dept. of Computer Automatic and Management Engineering (DIAG) Sapienza Università di Roma RM Roma 00185 Italy Unit of Data Science National Institute of Gastroenterology ”Saverio de Bellis” IRCCS Hospital BA Castellana Grotte 70013 Italy Scientific Direction National Institute of Gastroenterology ”Saverio de Bellis” IRCCS Hospital BA Castellana Grotte 70013 Italy

Metabolic dysfunction-associated fatty liver disease (MAFLD) introduces new diagnostic criteria for fatty liver disease that are independent of alcohol consumption and viral hepatitis infection. Therefore, investigating how biochemical and anthropometric factors influence mortality in MAFLD subjects is of significant interest. In this work, we propose MORIX, an Artificial Intelligence-based framework capable of predicting fatal mortality outcomes in subjects with MAFLD. MORIX utilizes data from epidemiological datasets containing carefully selected anthropometric and biochemical information. This selection is achieved through Recursive Feature Elimination (RFE) using a Random Forest (RF) to train Machine Learning (ML) algorithms and provide a mortality risk (Yes/No) output. To provide physicians with a valuable tool, MORIX was trained and tested on a dataset of MAFLD subjects, comparing five different models: Random Forest (RF), eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Light Gradient Boosting Model (LGBM) in a 5-fold cross-validation training strategy. Experimental results identified the RF as the best model, achieving a high accuracy for both mortality risks predicted. Additionally, an eXplainable Artificial Intelligence (XAI) analysis was conducted to clarify the diagnostic logic of the RF model and to assess the impact of each feature to the prediction. Moreover, a web application was developed to predict mortality risk and provide explanations of how the input features influenced the final prediction. In conclusion, the MORIX framework is easy to apply, and the required parameters are readily available in healthcare datasets, making it a practical tool for medical professionals. © 2025 The Authors

关键词： Epidemiology Interpretability Machine learning techniques MAFLD Mortality

来源：评论

学校读者我要写书评

暂无评论

ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning

arXiv

引用

arXiv 2023年

作者： Montaruli, Biagio Floris, Giuseppe Scano, Christian Demetrio, Luca Valenza, Andrea Compagna, Luca Ariu, Davide Piras, Luca Balzarotti, Davide Biggio, Battista Dept. of Digital Security EURECOM Biot06410 France Dept. of Electrical and Electronic Engineering University of Cagliari Cagliari09124 Italy Department of Computer Control and Management Engineering Sapienza University Rome Italy University of Genova Genova16146 Italy Prima Assicurazioni Milano20131 Italy Endor Labs United States Pluribus One Cagliari09128 Italy

Many Web Application Firewalls (WAFs) leverage the OWASP Core Rule Set (CRS) to block incoming malicious requests. The CRS consists of different sets of rules designed by domain experts to detect well-known web attack patterns. Both the set of rules to be used and the weights used to combine them are manually defined, yielding four different default configurations of the CRS. In this work, we focus on the detection of SQL injection (SQLi) attacks, and show that the manual configurations of the CRS typically yield a suboptimal trade-off between detection and false alarm rates. Furthermore, we show that these configurations are not robust to adversarial SQLi attacks, i.e., carefully-crafted attacks that iteratively refine the malicious SQLi payload by querying the target WAF to bypass detection. To overcome these limitations, we propose (i) using machine learning to automate the selection of the set of rules to be combined along with their weights, i.e., customizing the CRS configuration based on the monitored web services;and (ii) leveraging adversarial training to significantly improve its robustness to adversarial SQLi manipulations. Our experiments, conducted using the well-known open-source ModSecurity WAF equipped with the CRS rules, show that our approach, named ModSec-AdvLearn, can (i) increase the detection rate up to 30%, while retaining negligible false alarm rates and discarding up to 50% of the CRS rules;and (ii) improve robustness against adversarial SQLi attacks up to 85%, marking a significant stride toward designing more effective and robust WAFs. We release our open-source code at https://***/pralab/modsec-advlearn. © 2023, CC BY-SA.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Feedforward control in the Presence of Input Nonlinearities: A Learning-based Approach

arXiv

引用

arXiv 2022年

作者： van Hulst, Jilles Poot, Maurice Kostić, Dragan Yan, Kai Wa Portegies, Jim Oomen, Tom Control Systems Technology Section Dept. of Mechanical Engineering Eindhoven University of Technology Netherlands Center of Competency ASM Pacific Technology Netherlands CASA Dept. of Mathematics and Computer Science Eindhoven University of Technology Netherlands Delft Center for Systems and Control Delft University of Technology Netherlands

Advanced feedforward control methods enable mechatronic systems to perform varying motion tasks with extreme accuracy and throughput. The aim of this paper is to develop a data-driven feedforward controller that addresses input nonlinearities, which are common in typical applications such as semiconductor back-end equipment. The developed method consists of parametric inverse-model feedforward that is optimized for tracking error reduction by exploiting ideas from iterative learning control. Results on a simulated set-up indicate improved performance over existing identification methods for systems with nonlinearities at the input. © 2022, CC BY-NC-ND.

关键词： Feedforward control

来源：评论

学校读者我要写书评

暂无评论

Mathematical Model of a Three-Phase Induction Motor with Asymmetrical Twelve-Zone Stator Windings 4

Mathematical Model of a Three-Phase Induction Motor with Asy...

引用

4th IEEE International Conference on Modern Electrical and Energy System, MEES 2022

作者： Tytiuk, Valerii Chornyi, Oleksii Busher, Victor Siverskaya, Tatyana Baranovskaya, Mila Kuznetsov, Vitalii Njsc 'Karaganda Industrial University' Department 'Artificial Intelligence Technologies' Temirtau Kazakhstan Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine National University 'Odessa Maritime Academy' Dept. of Electrical Engineering and Electronics Odessa Ukraine Njsc 'Karaganda Industrial University' Department 'Power Engineering' Temirtau Kazakhstan Kryvyi Rih National University Department of Electromechanics Kryvyi Rih Ukraine Ukrainian State University of Science and Technologies Department of the Electrical Engineering Dnipro Ukraine

ISBN: (纸本)9798350346831

The paper proposes a mathematical model of a three-phase induction motor with an asymmetrical twelve-zone winding of stator with parallel connection of subwindings. The mathematical model was developed using the theory of generalized electromechanical converter and contains equations of electrical equilibrium of six stator windings and three rotor windings. The equations for calculating the electromagnetic moment and the equations of motion of the induction motor with an asymmetrical twelve-zone stator winding rotor were obtained. The developed mathematical model in the form of cell-matrix equations has been implemented in MATLAB/Simulink. © 2022 IEEE.

关键词： Induction motors

来源：评论

学校读者我要写书评

暂无评论

The role of attribute ranker using classification for software defect-prone data-sets model: An empirical comparative study 14

The role of attribute ranker using classification for softwa...

引用

14th Annual IEEE International Systems Conference, SYSCON 2020

作者： Malik, Maaz Rasheed Yining, Liu Shaikh, Salahuddin Dept. Information and Communication Engineering Guilin University of Electronics Technology Guilin China Dept. School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781728153650

Feature selection, is an issue firmly identified with size decrease of data-sets model. The target of feature selection is to recognize features in the data-set as significant, and dispose of some other feature as unimportant and repetitive data. Since feature selection diminishes the dimensionality of the data-sets model, it holds out the probability of increasingly successful and quick activity of data mining algorithm which can be worked quicker and all the more adequately by utilizing feature selection. In this research paper we will investigate feature extraction Principal Component Analysis (PCA) with attribute ranker search technique. In practice, Principal Component Analysis with attribute ranker search strategy isn't just used to improve extra storage space or the computational accuracy and efficiency of the classification algorithm, however can likewise enhance the prescient presentation by diminishing the scourge of dimensionality - particularly on the off chance that we are working with software defect-prone or non-defected data-sets models. We have used 10 datasets models, these datasets models basically REPOSITORY model of NASA which contain binary class defected and non-defected datasets models. We have also used 6 classifiers for comparatively analysis between objective model and real datasets model. We illustrated the comparatively analysis between PCA Ranker Search method with No-PCA. We have also compared classifiers efficiency with each other. The most efficient and useful classifier are the Bagging and Multilayer Perceptron at all attribute ranking search method. But the comparatively analysis between the classifiers that Naïve bayes and MultiLayer Perceptron have well increased the correctly classified instances percentage in overall software fault forecast. One more comparison between the PCA Ranker Search Method and No-PCA that is attribute ranker search method is really good for increasing accuracy and efficiency for software fault forecast

关键词： Defects

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：