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Electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Esraa Ali Abdulmahdi Adnan Hussein Ali Raed Khalid Ibrahim Ali Al-Askery Hayder Jasim Alhamdane Amal Ibrahim Mahmood Student at Dept. of Computer Engineering Techniques Electrical Engineering College Middle Technical University Baghdad Iraq Electrical Techniques Department Institute of Technology Middle Technical University Baghdad Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Department of Control and Automation Technical Engineering Electrical Engineering College Middle Technical University Baghdad Iraq College of Applied Arts Middle Technical University Baghdad Iraq Dept. of Computer Engineering Techniques Electrical Engineering College Middle Technical University Baghdad Iraq

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

The technology of reconfigurable optical networks (RONs) is growing to be a promising solution to effectively cater to the rapidly increasing traffic generated by the digital society. Optical technology emerges as a viable alternative because to its capacity to offer a substantial bandwidth, little latency, and enhanced overall performance. Nevertheless, it is imperative to effectively manage the physical resources comprising a data center. This study provides an experimental demonstration of the RONs, which is enhanced by a control plane. The implementation relies on the monitoring of real-time network statistics. This enables the execution of various activities, including as network slice provisioning and reconfiguration, assignment of packet priority classes, and dynamic operations. These actions are performed to ensure the attainment of the desired Quality of Service level. The experimental results show the successfully implementation of RONs using Mininet Emulator and sFlow traffic monitoring technology. The results approve that optical datacenter has minimum delay with low OSNR even with long distance and fast switching time.

关键词： Data centers Optical switches Optical fiber networks Traffic control Real-time systems Service-oriented architecture Monitoring

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An optimization-based algorithm for simultaneous shaping of poles and zeros for non-collocated vibration suppression

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IFAC-PapersOnLine 2022年第16期55卷 394-399页

作者： Adrian Saldanha Haik Silm Wim Michiels Tomáš Vyhlídal Department of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

This article presents a control design method for simultaneous shaping of the poles and zeros of linear time-invariant systems, motivated by the application of non-collocated vibration suppression to flexible multi-body systems. An entire suppression of vibrations at a target mass for a given excitation frequencies can be recast into the problem of assigning zeros of the transfer function from the excitation force to the target mass' position. The design requirement of achieving sufficient damping in the closed loop system combined with suppressing vibrations at the target, leads to the minimization of the spectral abscissa function of the closed loop system as a function of the controller parameters, subject to zero location constraints. These constraints exhibit polynomial dependence on the controller parameters. We present two approaches to solve the optimization problem which are both based on constraint elimination followed by application of an algorithm for non-smooth unconstrained optimization. The design approach is applicable to delay-free models as well as time-delay models of retarded and neutral type. Simulations results illustrate its applicability to a spring-mass-damper system.

关键词： vibration suppression zero placement time-delay systems spectral optimization

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A Visual Servoing Strategy for Coastline Tracking using an Unmanned Aerial Vehicle

A Visual Servoing Strategy for Coastline Tracking using an U...

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Mediterranean Conference on control and Automation (MED)

作者： Sotirios N. Aspragkathos George C. Karras Kostas J. Kyriakopoulos Control Systems Lab School of Mechanical Engineering 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

In this paper, an Image-based Visual Servo (IBVS) control strategy for the autonomous surveillance of coastlines using an octocopter aerial vehicle is proposed. The implemented strategy is focused on the vision-based detection and tracking of dynamic coastlines and in the presence of waves while flying in low altitudes. For this purpose, a Deep Neural Network (DNN) for the detection of the coastline is employed. The DNN is ac-companied by an analytical formulation of an Extended Kalman Filter (EKF), which considers an approximate periodical wave motion model to provide an online estimate of the coastline motion directly in image space. The estimated feedback is provided to an appropriately formulated IBVS tracking controller for the autonomous guidance of the octocopter along the coastline, ensuring the latter is always kept inside the camera’s field of view. The efficacy of the proposed scheme is demonstrated via a set of comparative outdoor experiments using an octocopter flying along the coastline on various weather and beach settings.

关键词： Visualization Tracking Trajectory planning Surveillance Neural networks Estimation Visual servoing

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A Deep Reinforcement Learning Motion control Strategy of a Multi-rotor UAV for Payload Transportation with Minimum Swing

A Deep Reinforcement Learning Motion Control Strategy of a M...

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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

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Digital Map Generation Workflow Demonstrated on ZalaZONE Automotive Proving Ground Elements

Digital Map Generation Workflow Demonstrated on ZalaZONE Aut...

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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.

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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...

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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

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Validation of a two-wheel vehicle model using Genetic Algorithm

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

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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

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

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

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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

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

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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

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

arXiv

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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

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