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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Youssef Aboudorra Aaron Saini Antonio Franchi Robotics and Mechatronics Faculty of Electrical Engineering Mathematics & Computer Science University of Twente Enschede The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

This work presents techniques for scheduling the position controller gains for a class of fully-actuated morphing multi-rotor UAVs that use synchronized tilting to change their actuation capabilities. The feasible set of forces and torques that can be produced by the platform changes with the tilting angle, thus the tracking and disturbance rejection capabilities also change. To exploit the platform limits, two methods are proposed for gain scheduling using a simplified example, then one method is tested in simulation with an omnidirectional morphing multi-rotor (OmniMorph). The simulation results show that the developed techniques achieve consistent position tracking performance along the range of tilting angles when rejecting step disturbance forces of values close to the maximum force capabilities. The proposed methods offer a trade-off between simplicity and accuracy, that could be potentially applied for any multi-rotor with synchronized tilting capabilities. A video summary can be found in: https://***/kH-rrO8gWeU

关键词： Accuracy Processor scheduling Attitude control Simulation Force Rotors Position control

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Pneumonia Detection from X-ray Images Using Convolutional Neural Networks

Pneumonia Detection from X-ray Images Using Convolutional Ne...

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International Conference on control Systems and computer science (CSCS)

作者： Viorel Dediu Andreea Udrea Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Bucharest Romania

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia.

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Stability and stabilization of a class of switched stochastic systems with saturation control

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science China(Information sciences) 2021年第12期64卷 147-159页

作者： Yingxin GUO Shuzhi Sam GE Jianting FU Chao XU School of Mathematical Sciences Qufu Normal University Department of Electrical and Computer Engineering National University of Singapore Chongqing Institutes of Green and Intelligent Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Control Science and Engineering Zhejiang University

A switching system always comprises of several subsystems and a rule supervising the switching between the subsystems. A major problem that is often inherent to all dynamical systems is actuator saturation. Saturation is a nonlinear property that nonlinearly maps small input signals to the output,which may affect the system properties and even destroy them. In this study, stability and stabilization of a class of switched stochastic systems with saturation control was investigated. First, the variation parameter method was used to present the integral form of switched stochastic systems. Second, to guarantee that the zero solution is globally exponentially stable in mean square, two sufficient conditions were obtained using direct computation with Gronwall inequality and indirect method with matrix theory, respectively. Further,another simple sufficient condition was obtained for the stability of the systems using the row norm, column norm, and Frobenius norm. Finally, two examples were used to illustrate the preciseness and effectiveness of the results. Moreover, various control designs were observed to stabilize the systems, which differ from the technique of linear matrix inequalities.

关键词： switched stochastic systems matric theory Gronwall inequality stability

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Transforming stroop task cognitive assessments with multimodal inverse reinforcement learning

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Smart Health 2025年 36卷

作者： Abbasi, Ali Gong, Jiaqi Korivand, Soroush Department of Control and Computer Engineering Polytechnic University of Turin Italy Department of Computer Science The University of Alabama United States Department of Mechanical Engineering Mississippi State University United States

Stroop tasks, recognized for their cognitively demanding nature, hold promise for diagnosing and monitoring neurodegenerative diseases. Understanding how humans allocate attention and resolve interference in the Stroop test remains a challenge;yet addressing this gap could reveal key opportunities for early-stage detection. Traditional approaches overlook the interplay between overt behavior and underlying neural processes, limiting insights into the complex color-word associations at play. To tackle this, we propose a framework that applies Inverse Reinforcement Learning (IRL) to fuse electroencephalography (EEG) signals with eye-tracking data, bridging the gap between neural and behavioral markers of cognition. We designed a Stroop experiment featuring congruent and incongruent conditions to evaluate attention allocation under varying levels of interference. By framing gaze as actions guided by an internally derived reward, IRL uncovers hidden motivations behind scanning patterns, while EEG data — processed with advanced feature extraction — reveals task-specific neural dynamics under high conflict. We validate our approach by measuring Probability Mismatch, Target Fixation Probability-Area Under the Curve, Sequence Score, and MultiMatch metrics. Results show that the IRL-EEG model outperforms an IRL-Image baseline, demonstrating improved alignment with human scanpaths and heightened sensitivity to attentional shifts in incongruent trials. These findings highlight the value of integrating neural data into computational models of cognition and illuminate possibilities for early detection of neurodegenerative disorders, where subclinical deficits may first emerge. Our IRL-based integration of EEG and eye-tracking further supports personalized cognitive assessments and adaptive user interfaces. © 2025 The Authors

关键词： Cognitive assessment EEG Eye-tracking Inverse reinforcement learning Neurodegenerative diseases

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Optimizing Membrane Distillation Configuration for Superior Heat and Mass Transfer

Optimizing Membrane Distillation Configuration for Superior ...

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2024 International Conference on Emerging Trends in Smart Technologies, ICETST 2024

作者： Arslan, Muhammad Haizhen, Xian Nouman Khalid Khan, M. Ali, Kashif Baig, Zaid Bin Tariq North China Electric Power University School Of Energy Power And Mechanical Engineering Beijing China University Of Engineering & Technology School Of Mechanical Engineering Lahore Pakistan North China Electric Power University School Of Renewable And Clean Energy Beijing China North China Electric Power University Department Of Control And Computer Science Beijing China

ISBN: (纸本)9798331515850

Membrane distillation (MD) has emerged as a promising technique for desalination and water purification, offering potential advantages in terms of energy efficiency and operational flexibility. However, challenges related to heat and mass transfer inefficiencies limit its widespread adoption. This study explores the use of innovative materials and optimized configurations to enhance heat and mass transfer in direct contact membrane distillation (DCMD) systems. By integrating advanced hybrid membranes with nano-coating techniques and evaluating their performance through simulation-based methodologies, we demonstrate significant improvements in thermal conductivity, mass transfer efficiency, and fouling resistance. The results indicate that the newly developed hybrid membranes not only enhance heat and mass transfer rates but also maintain high separation efficiency, ultimately leading to improved overall system performance. These findings provide a foundation for the further development of MD technologies and suggest pathways for overcoming existing limitations, paving the way for more sustainable and efficient water treatment solutions. © 2024 IEEE.

关键词： Desalination

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Towards Responsible AI Music: an Investigation of Trustworthy Features for Creative Systems

arXiv

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arXiv 2025年

作者： de Berardinis, Jacopo Porcaro, Lorenzo Meroño-Peñuela, Albert Cangelosi, Angelo Buckley, Tess Department of Computer Science University of Liverpool United Kingdom Department of Computer Control and Management Engineering Sapienza University of Rome Italy Department of Informatics King’s College London United Kingdom Department of Computer Science University of Manchester United Kingdom Association of AI Ethicists

Generative AI is radically changing the creative arts, by fundamentally transforming the way we create and interact with cultural artefacts. While offering unprecedented opportunities for artistic expression and commercialisation, this technology also raises ethical, societal, and legal concerns. Key among these are the potential displacement of human creativity, copyright infringement stemming from vast training datasets, and the lack of transparency, explainability, and fairness mechanisms. As generative systems become pervasive in this domain, responsible design is crucial. Whilst previous work has tackled isolated aspects of generative systems (e.g., transparency, evaluation, data), we take a comprehensive approach, grounding these efforts within the Ethics Guidelines for Trustworthy Artificial Intelligence produced by the High-Level Expert Group on AI appointed by the European Commission – a framework for designing responsible AI systems across seven macro requirements. Focusing on generative music AI, we illustrate how these requirements can be contextualised for the field, addressing trustworthiness across multiple dimensions and integrating insights from the existing literature. We further propose a roadmap for operationalising these contextualised requirements, emphasising interdisciplinary collaboration and stakeholder engagement. Our work provides a foundation for designing and evaluating responsible music generation systems, calling for collaboration among AI experts, ethicists, legal scholars, and artists. This manuscript is accompanied by a website: https://***/raim-framework/. Copyright © 2025, The Authors. All rights reserved.

关键词： Generative adversarial networks

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A Novel Blockchain-Integrated Distributed Data Storage Model with Built-in Load Balancing 16

A Novel Blockchain-Integrated Distributed Data Storage Model...

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16th IEEE International Conference on Application of Information and Communication Technologies, AICT 2022

作者： Hammoud, Obadah Tarkhanov, Ivan A. National University of Science and Technology Department of Engineering Cybernetics Moscow Russia State Academic University for Humanities Federal Research Center 'Computer Science and Control' of Russian Academy of Sciences Russia

ISBN: (纸本)9781665451628

Most companies relay on centralized servers, which are considered as a fast and easy to deploy solution for file sharing, but they have many downsides, like security and trust issues, which can be solved using DLT (blockchain) solutions. However, DLT-based solutions have many challenges, such as nodes orchestration, adjusting reliability and double-spending, as well as load balancing. This research proposes a DLT (Distributed Ledger Technology) based model for files storage for companies using p2p networks, which takes into account both data reliability and storage space efficiency. More efficient data storage is achieved through the use of the Erasure coding technique. For load balancing, a set of algorithms that can be implemented in the form of a smart contract were proposed. The described model can become the basis of the IT infrastructure for trusted exchange of documents, technical and scientific information, games distributions, mobile applications, updates of scientific, regulatory and technical databases in b2b and b2c format © 2022 IEEE.

关键词： Blockchain

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Renewable integration and energy reduction in multiple stage evaporator

Renewable integration and energy reduction in multiple stage...

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作者： Pati, Smitarani Kumar Sharma, Tarun Kumar Goyal, Kapil Prakash Verma, Om Department of Instrumentation and Control Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Punjab Jalandhar144011 India Department of Computer Science and Engineering Shobhit University UP Saharanpur-247341 India Department of Industrial and Production Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Punjab Jalandhar144011 India

Multiple Effect Evaporator (MEE) is an imperative part of the paper industry. It is used to process the waste byproduct named Black Liquor to enhance its solid concentration that may be further utilized to produce biomass-based energy. This process accounts very high energy consumption which leads to the energy intensiveness of this unit. A substantial amount of energy-saving may be accumulated by integrating various Energy Reduction Schemes (ERSs) with the MEE. Steam splitting, feed splitting, feed liquor preheating, thermo-vapor compressor, etc. are the well-known ERSs that may be incorporated with the MEE to reduce energy utilization. Hence, this study investigates the hybrid ERSs incorporated with MEE to observe their energy efficiency in an optimal manner. The prime focus of this investigation is to achieve enhanced energy efficiency in teams of maximum steam efficiency which is computed by formulating the nonlinear mathematical models of the MEE. To achieve the maximized energy efficiency, an optimization function has been developed under a constraint environment and solved by using metaheuristic-based approach named Flow Direction Algorithm. Another ERSs named flash tanks can also be integrated with this system to encourage waste heat re-utilization and ensures an increase in energy efficiency with constant steam consumption. This work also deals with the incorporation of the Linear Fresnel Reflector with ERSs integrated MEE which is capable of reducing the conventional energy load. The overall integrated MEE model achieves an energy-efficient and renewably operated MEE unit that may enhance the self-sustainability of the industry. © 2022

关键词： Energy efficiency

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Minimization of Trim Loss During Reel Cutting at Paper Mill by Using Different Optimization Algorithms 2nd

Minimization of Trim Loss During Reel Cutting at Paper Mill ...

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2nd International Congress on Advances in Mechanical and Systems engineering, CAMSE 2021

作者： Srivastava, Manish Pati, Smitarani Verma, Om Prakash Sharma, Tarun Kumar Gupta, Himanshu Arya, Raj Kumar Tiwari, Anurag Kumar Sahu, Deepak Department of Instrumentation and Control Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar144011 India Department of Computer Science and Engineering Shobhit University Saharanpur India Department of Chemical Engineering Dr. B. R. Ambedkar National Institute of Technology Punjab Jalandhar144011 India

ISBN: (纸本)9789811921872

Trim loss is one of the major issues in the paper industry and occurs during the cutting of master and stocked reels to fulfill the ordered demands of reels with smaller widths. The trims (paper waste) produced during this reel cutting need to be reprocessed and follow a heavy chemical process that causes a significant amount of effluent discharge to the water surface which is hazardous as per environmental concern. Hence, this work aims to reduce the trim loss problem by using the flexible width master reels and stocked over-product and usable leftover reels. The minimization is performed with a linear single objective optimization problem with consideration of different operational and technological constraints. Three different solution approaches named simplex method, particle swarm optimization, and genetic algorithm have been proposed to optimize this trim loss problem employed for solving a real-world industrial problem. Again, the obtained solutions are analyzed in contrast with some reported results to prove the validity of the model and check the efficiency of the algorithms. The optimized result produces minimization in trim production due to which a lesser reproduction required that depletes the chemical use and tends to economic saving and reduction in environmental pollution. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Genetic algorithms

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A Machine Learning based Real-Time Application for Engagement Detection 9

A Machine Learning based Real-Time Application for Engagemen...

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9th Scholar's Yearly Symposium of Technology, engineering and Mathematics, SYSTEM 2023

作者： Iacobelli, Emanuele Russo, Samuele Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome Roma00185 Italy Department of Psychology Sapienza University of Rome Roma00185 Italy Institute for Systems Analysis and Computer Science Italian National Research Council Roma00185 Italy Department of Computational Intelligence Czestochowa University of Technology Czestochowa42-201 Poland

The study of human engagement has significantly grown in recent years, particularly accelerated by the interaction with a growing number of smart computing machines [1, 2, 3]. Engagement estimation has significant importance across various domains of study, including advertising, marketing, human-computer interaction, and healthcare [4, 5, 6]. In this paper, we propose a real-time application that leverages a single RGB camera to capture user behavior. Our approach implements a novel method for estimating human engagement in real-world scenarios by extracting valuable information from the combination of facial expressions and gaze direction analysis. To acquire this data, we employed fast and accurate machine learning algorithms from the external library dlib, along with custom versions of Residual Neural Networks implemented from scratch. For training our models, we used a modified version of the DAiSEE dataset, a multi-label user affective states classification dataset that collects frontal videos of 112 different people recorded in real-world scenarios. In the absence of a baseline for comparing the results obtained by our application, we conducted experiments to assess its robustness in estimating engagement levels, leading to very encouraging results. © 2023 Copyright for this paper by its authors.

关键词： Eye tracking

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