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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Brunetti, Martina Paci, Paola Fiscon, Giulia Sapienza University of Rome Department of Computer Control and Management Engineering 'A. Ruberti' Rome Italy Karolinska Institutet Stockholm Sweden National Research Council of Rome Institute for Systems Analysis and Computer Science 'A. Ruberti' Rome Italy

ISBN: (纸本)9798350337488

Drug repurposing, also known as drug repositioning, is the process of identifying novel therapeutic indications for existing drugs, offering a cost-effective and time-efficient strategy to drug discovery. In this context, we developed a network-based algorithm, named SAveRUNNER (Searching off-lAbel dRUg aNd NEtwoRk), which predicts drug-disease associations by accounting for the interaction between the drug targets and disease-associated genes in the human interactome, implementing a novel network-based similarity measure that prioritizes associations between drugs and diseases locating in the same network neighborhoods. Following its successful applications to different disorders (such as viral infections and neurological diseases), in this study, we applied SAveRUNNER on a panel of 13 types of cancers using both disease-associated genes downloaded from widely-used databases and from gene expression data. © 2023 IEEE.

关键词： Drug Repurposing Network Medicine Network Theory

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Experimental Research of Modes of Operation of Local Autonomous Sources of Energy Supply with Induction Generator 4

Experimental Research of Modes of Operation of Local Autonom...

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

作者： Zachepa, Iurii Zachepa, Nataliia Khrebtova, Oksana Kobiliansky, Boris Turaev, Ilya Kremenchuk Mykhailo Ostrohradskyi National University Department of Systems of Automatic Control and Electric Drive Kremenchuk Ukraine Ukrainian Engineering Pedagogics Academy Department of Electromechanical and Computer Systems Kharkov Ukraine

ISBN: (纸本)9798350346831

The paper presents the results of experimental studies of autonomous power supply sources formed according to the 'internal combustion engine-induction generator' scheme. Autonomous local sources of energy supply according to this scheme are formed from existing electromechanical and electrotechnical equipment of other functional purposes only for the period of electricity demand. Such sources of electricity are universal for welding and other technological equipment of military and civil, including agricultural, machinery. According to the results, the viability of the proposed concept of creating autonomous power supply sources based on motor vehicles and electrical equipment has been proven. The limits of guaranteed excitation and subsequent trouble-free operation of autonomous local sources of power supply with power to consumers of various categories have been established. © 2022 IEEE.

关键词： Electric loads

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On Space-Filling Input Design for Nonlinear Dynamic Model Learning: A Gaussian Process Approach

arXiv

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arXiv 2025年

作者： Liu, Yuhan Kiss, Máté Tóth, Roland Schoukens, Maarten Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Systems and Control Laboratory HUN-REN Institute for Computer Science and Control Budapest1111 Hungary

While optimal input design for linear systems has been well-established, no systematic approach exists for nonlinear systems, where robustness to extrapolation/interpolation errors is prioritized over minimizing estimated parameter variance. To address this issue, we develop a novel identification-oriented space-filling input design strategy for efficient covering of a well-defined region of interest. By placing a Gaussian Process (GP) prior on the joint input-state space, the proposed strategy leverages the GP posterior variance to construct a space-filling promoting input design cost function from the Bayesian point of view. This accordingly enables maximization of the coverage in the region of interest, thereby facilitating the generation of informative datasets. Furthermore, we theoretically prove that minimization of the cost function indicates the space-filling behavior. The effectiveness of the proposed strategy is demonstrated on both an academic example and a mass-spring-damper system, highlighting its potential practical impact on efficient exploration in identification scenarios for nonlinear dynamical systems. © 2025, CC BY-NC-SA.

关键词： Cost functions

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Platoon-Local Dynamic Map: Hierarchical cooperative perception for platooning vehicles

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IEEE Transactions on Vehicular Technology 2025年

作者： Carletti, Carlos Mateo Risma Casetti, Claudio Harri, Jerome Risso, Fulvio Politecnico di Torino Department of Control and Computer Engineering Turin Italy EURECOM - Communication Systems Department Sophia-Antipolis France

Onboard perception systems found on modern vehicles generate data that are incredibly rich in contextual information, and thanks to the increasing number of vehicles equipped with communication capabilities, the valuable data generated can be shared with nearby vehicles. One of the most studied vehicular applications for autonomous driving is platooning, for which all maneuvers are managed by the Platoon Leader (PL) with the aid of context information available through Vehicle-to-Vehicle (V2V) messages. However, redundant context information from nearby vehicles in the platoon creates an additional workload for the platoon leader resulting in elevated computational costs. To overcome the challenge of redundant context information, the formation of vehicular micro-clouds can offload the platoon leader by enabling vehicles in a cluster to more effectively utilize the available context data through collective data processing and aggregation. The proposed solution, called Platoon Local Dynamic Map (P-LDM), creates a single database of context information, distributing the data aggregation load among all members of the platoon. Simulation results evaluate the collective perception enhancement and the distribution of the computational load, comparing the proposed scheme with usual Cooperative Perception mechanisms. © 1967-2012 IEEE.

关键词： Data reduction

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A Review of Evaluation Metrics Algorithmic Used in Scholarly Research Recommender System

A Review of Evaluation Metrics Algorithmic Used in Scholarly...

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International Multidisciplinary Information Technology and engineering Conference (IMITEC)

作者： Gerald Ovono Travos Zuva Temidayo Otunniyi Department of Computer Faculty of Applied and Computer Sciences South Africa Department of Process Control and Computer Systems Faculty of Engineering and Technology VaalUniversity of Technology South Africa

ISBN: (数字)9798350387988

ISBN: (纸本)9798350387995

The exponential growth of academic publications has made scholarly research recommender systems indispensable tools for researchers. These systems rely on diverse evaluation metrics to assess their effectiveness and relevance. This paper provides a comprehensive review and analysis of these metrics, categorizing them into accuracy, ranking, diversity, user-centric, coverage, temporal, and computational metrics. By employing a mixed-methods approach, combining systematic literature review and empirical analysis, we identify the prevalence and application of these metrics across various scholarly domains such as literature, conferences, and reviewers. Our findings highlight the widespread use of traditional metrics like precision, recall, and Fl-score, while emphasizing the growing importance of novel metrics such as unexpectedness and serendipity, especially in literature and conference recommendations. We also underscore the domain-specific nature of metric selection, with user-centric evaluations more prominent in literature recommendations, and ranking-focused metrics dominant in conference and reviewer recommendations. Furthermore, the study reveals a significant gap in the use of temporal and computational metrics, suggesting key areas for future research. This review offers valuable insights for researchers and practitioners, guiding them in metric selection and highlighting potential directions for enhancing the effectiveness, adaptability, and user satisfaction of scholarly recommender systems.

关键词： Measurement Accuracy Diversity reception Solids Information technology Recommender systems Systematic literature review

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Automatic Detection of Myotonia using a Sensory Glove with Resistive Flex Sensors and Machine Learning Techniques 6

Automatic Detection of Myotonia using a Sensory Glove with R...

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6th IEEE International Workshop on Metrology for Industry 4.0 and IoT, MetroInd4.0 and IoT 2023

作者： Cesarini, Valerio Costantini, Giovanni Amato, Federica Errico, Vito Pietrosanti, Luca Calado, Alexandre Luis Massa, Roberto Frezza, Erica Irrera, Fernanda Manoni, Alessandro Saggio, Giovanni University of Rome Tor Vergata Department of Electronic Engineering Rome Italy Polytechnic University of Turin Department of Control and Computer Engineering Turin Italy University of Rome Tor Vergata Department of Systems Medicine Rome Italy University of Rome la Sapienza Department of Information Engineering Electronics and Telecommunications Rome Italy

ISBN: (纸本)9798350396577

This paper deals with the automatic detection of Myotonia from a task based on the sudden opening of the hand. Data have been gathered from 44 subjects, divided into 17 controls and 27 myotonic patients, by measuring a 2-point articulation of each finger thanks to a calibrated sensory glove equipped with a Resistive Flex Sensor (RFS). RFS gloves are proven to be reliable in the analysis of motion for myotonic patients, which is a relevant task for the monitoring of the disease and subsequent treatment. With the focus on a healthy VS pathological comparison, customized features were extracted, and several classifications entailing motion data from single fingers, single articulations and aggregations were prepared. The pipeline employed a Correlation-based feature selector followed by a SVM classifier. Results prove that it's possible to detect Myotonia, with aggregated data from four fingers and upper/lower articulations providing the most promising accuracies (91.1%). © 2023 IEEE.

关键词： Machine learning

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Automation and measurement classes for power engineering students in the online-mode 44

Automation and measurement classes for power engineering stu...

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44th International Convention on Information, Communication and Electronic Technology, MIPRO 2021

作者： Merzlikina, E.I. Dolbikova, N.S. Kuznetsova, A.V. Farafonov, G.V. National Research University Moscow Power Engineering Institute Department of Automated Control Systems for Thermal Processes Moscow Russia

ISBN: (纸本)9789532331011

This paper considers online classes for power engineering students. The work embraces two subjects: automation in industry and power engineering and measurements and measuring instruments in power engineering. Both subjects have in common a very important thing from the online teaching and learning point of view. They have laboratory classes, during which students work with real control devices and measuring instruments, that is why it is rather challenging to organize the classes in the online mode. Besides the laboratory classes, the courses under consideration consist of lectures and term project consultations. Having completed the courses students take exams. This paper describes the experience the authors obtained in organizing the classes and teaching techniques that allowed them to provide their students with the necessary skills and knowledge. For the online classes, the authors used several software packages: Cisco Webex, Moodle, CODESYS, and some special programs developed in MPEI university. This paper also describes the results the authors obtained and the difficulties they faced. © 2021 Croatian Society MIPRO.

关键词： Students

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Evaluation of the Energy Efficiency of Software Calculations in the Design of Microcontroller Devices 17

Evaluation of the Energy Efficiency of Software Calculations...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Topalov, Andrii Styslo, Taras Tkach, Vitalii Peschanenko, Volodymyr Styslo, Oksana Skrypyuk, Rostyslav Admiral Makarov National University of Shipbuilding Department of computerized control systems Mykolaiv Ukraine King Danylo University Department of IT Ivano-Frankivsk Ukraine Kherson State University Department of computer science and software engineering Ivano-Frankivsk Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of automation and computer-integrated technologies Ivano-Frankivsk Ukraine

ISBN: (纸本)9798331520564

The paper presents a study of the effectiveness of software from the point of view of minimizing the energy consumption of microprocessor devices. In this case, the programming of the microcontroller in various programming languages for arithmetic operations, as well as data output through the port, is considered. In the course of the tests, the peculiarities of the application of this or that program and their operation, taking into account the energy saving of the microcontroller, are noted. © 2024 IEEE.

关键词： Microcontrollers

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A Graph-Based Self-Calibration Technique for Cable-Driven Robots with Sagging Cable

A Graph-Based Self-Calibration Technique for Cable-Driven Ro...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： M. R. Dindarloo A. S. Mirjalili S. A. Khalilpour R. Khorrambakht Stephan Weiss H. D. Taghirad Advanced Robotics and Automated Systems (ARAS) Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering Tandon School of Engineering Control/Robotics Research Laboratory New York University Brooklyn NY Department of Smart Systems Technologies University of Klagenfurt Austria

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

The efficient operation of large-scale Cable-Driven Parallel Robots (CDPRs) relies on precise calibration of kinematic parameters and the simplicity of the calibration process. This paper presents a graph-based self-calibration framework that explicitly addresses cable sag effects and facilitates the calibration procedure for large-scale CDPRs by only relying on internal sensors. A unified factor graph is proposed, incorporating a catenary cable model to capture cable sagging. The factor graph iteratively refines kinematic parameters, including anchor point locations and initial cable length, by considering jointly onboard sensor data and the robot’s kineto-static model. The applicability and accuracy of the proposed technique are demonstrated through Finite Element (FE) simulations, on both large and small-scale CDPRs subjected to significant initialization perturbations.

关键词： Meters Accuracy Perturbation methods Kinematics Robot sensing systems End effectors Software Calibration Sensors Finite element analysis

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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