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Indoor vehicle-in-the-loop simulation of unmanned micro aerial vehicle with artificial companion

Indoor vehicle-in-the-loop simulation of unmanned micro aeri...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Antal Hiba Viktor Kortvelyesi Albert Kiskaroly Omkar Bhoite Patrik David Andras Majdik ELKH Computational Optical Sensing and Processing Laboratory Institute for Computer Science and Control (SZTAKI) Budapest Hungary ELKH Machine Perception Research Laboratory Institute for Computer Science and Control (SZTAKI) Budapest Hungary

Vehicle-in-the-loop simulation is an extension of the well-known hardware-in-the-loop technique, where a vehicle moves in real space while a simulator generates input for onboard sensors real-time. VIL frameworks designed for unmanned aerial vehicles have many open challenges. This paper introduces an indoor VIL for micro aerial vehicles in a drone arena equipped with precise positioning system and reliable wireless communication. This indoor setup stands as a prototype and predecessor for other outdoor VIL simulators for large scale applications. The raw optical navigation performance is tested which is the building block for sensor fusion and on-board fast sensor consistency check. A use-case of a companion drone in cooperative navigation is also presented.

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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...

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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

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Zero-Order Stochastic Conditional Gradient Sliding Method for Non-smooth Convex Optimization 22nd

Zero-Order Stochastic Conditional Gradient Sliding Method fo...

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22nd International Conference on Mathematical Optimization Theory and Operations research , MOTOR 2023

作者： Lobanov, Aleksandr Anikin, Anton Gasnikov, Alexander Gornov, Alexander Chukanov, Sergey Moscow Institute of Physics and Technology Dolgoprudny Russia ISP RAS Research Center for Trusted Artificial Intelligence Moscow Russia Moscow Aviation Institute Moscow Russia Matrosov Institute for System Dynamics and Control Theory Irkutsk Russia Institute for Information Transmission Problems RAS Moscow Russia Caucasus Mathematical Center Adyghe State University Maikop Russia Federal Research Center "Computer Science and Control" RAS Moscow Russia

ISBN: (纸本)9783031432569

The conditional gradient idea proposed by Marguerite Frank and Philip Wolfe in 1956 was so well received by the community that new algorithms (also called Frank–Wolfe type algorithms) are still being actively created. In this paper, we study a non-smooth stochastic convex optimization problem with constraints. Using a smoothing technique and based on an accelerated batched first-order Stochastic Conditional Gradient Sliding method, we propose a novel gradient-free Frank–Wolfe type algorithm called Zero-Order Stochastic Conditional Gradient Sliding (ZO-SCGS). This algorithm is robust not only for the class of non-smooth problems, but surprisingly also for the class of smooth black box problems, outperforming the SOTA algorithms in the smooth case in term oracle calls. In practical experiments we confirm our theoretical results. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Stochastic systems

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

Differential gene correlation analysis to investigate evolut...

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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

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Open-circuit fault diagnosis method for inverters using deep learning and the evidence reasoning rule

Open-circuit fault diagnosis method for inverters using deep...

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2022 International Conference on Smart Energy and Electrical Engineering, SEEE 2022

作者： Yu, Hang Gao, Haibo He, Yelan Lin, Zhiguo Xu, Xiaobin Pan, Zhiqiang School of Marine and Energy Power Engineering Wuhan University of Technology Wuhan China School of Computer Science and Technology Wuhan University of Technology Wuhan China Institute of System Science and Control Engineering Hangzhou Dianzi University Hangzhou China Shanghai Marine Diesel Engine Research Institute Shanghai China

Inverters having high voltage levels, high power density, and high integration are widely used. However, many high-frequency switch units also increase the probability of failure. Therefore, developing an accurate and stable fault diagnosis method is necessary. This paper proposes a fault diagnosis algorithm based on deep learning and the evidence reasoning (ER) rule. It not only ensures high diagnostic accuracy, but also enhances the stability of the diagnostic results. The algorithm takes the three-phase voltage source inverter as the research object and extracts the three-phase current signals with different types of faults as features. First, Convolutional and Deep Neural Network methods were utilized independently to determine a preliminary diagnosis. Second, the softmax functions of the Convolutional and Deep Neural Network outputs provided the probability distribution of the fault category, which was used as the evidence body for the ER rule to construct the fusion diagnosis. In addition, a new method of determining the reliability and the importance factors of the evidence was proposed in which the evaluation index of the deep-learning diagnosis result was applied. Finally, the final classification result was obtained using the ER rule. The proposed method can effectively enhance the accuracy and robustness compared with a single classifier. © Published under licence by IOP Publishing Ltd.

关键词： Deep neural networks

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Supervised Classification and Finding Frequent Elements in Data 8

Supervised Classification and Finding Frequent Elements in D...

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8th International Conference on Information Technology and Nanotechnology, ITNT 2022

作者： Dragunov, Nikita Djukova, Elena Djukova, Anastasia Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Moscow Russia St. Petersburg Pasteur Institute St. Petersburg Russia

ISBN: (数字)9781665485715

ISBN: (纸本)9781665485715

Correct logical classifiers the construction of which uses the ideas underlying the well-known 'Kora' algorithm and the ideas of estimates calculating algorithms are considered. A modification of the training stage that in certain cases makes it possible to reduce the time cost without loss in the classification quality is proposed. Results of experiments on model and real-life data are presented, and new theoretical estimates of the complexity of training Kora-Type classifiers are obtained. © 2022 IEEE.

关键词： Supervised learning

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Automation of Technological Processes for controlling Grain Moisture in the Flowu

Automation of Technological Processes for Controlling Grain ...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Kalandarov, Palvan I. Ubaydullayeva, Shakhnoza R. Gaziyeva, Rano T. Nikolov, Nikola N. Alexandrova, Mariela I. 'Tashkent Institute of Irrigation and Agricultural Mechanization Engineers' National Research University Department 'Automation and Control of Technology Process in Production' Tashkent Uzbekistan Technical University of Varna Faculty of Computer Science and Automation Department of Automation Varna Bulgaria

ISBN: (纸本)9798350312911

The paper deals with the problems of grain wounding requires large energy costs, requiring a multi-stage process of grain processing, installation and perfect and reliable automation systems for the storage and processing of raw materials, theoretical and experimental studies and the results of the use of the microwave method in measuring the moisture content of grain and grain materials. The method under consideration is based on the principle of selective absorption of microwave radiation energy by water in materials and its derivatives. By the degree of absorption of radiation, the concentration of moisture is judged. The paper investigates the amplitude and phase methods of the passing wave in free space. The influence of the elastic properties of the material under study on the electrical characteristics of the microwave wave, suggesting fundamentally new ways of measuring the attenuation and phase shift of the electromagnetic wave, including discrete conversion of the signal of the primary converter, which does not require rigid metrological support and the use of a phase shift, is substantiated. Information on the values of the thickness of the material is analyzed in order to correct the influence of this value, consisting of two parameters: the signal of the passing wave, the attenuation and phase shift which characterizes the humidity and the additional signal - the phase wave reflected from the front surface of the materials and carrying information about its thickness. © 2023 IEEE.

关键词： Automation

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Comparison of EKF and Neural Network based wing shape estimation of a flexible wing demonstrator 19

Comparison of EKF and Neural Network based wing shape estima...

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19th International Forum on Aeroelasticity and Structural Dynamics, IFASD 2022

作者： Hadlaczky, Bence Zs. Friedman, Noémi Takarics, Béla Vanek, Bálint Institute for Computer Science and Control Eötvös Lóránd Research Network Kende u. 13-17 Budapest1111 Hungary

ISBN: (纸本)9788409423538

Structural flexibility of advanced, large-wingspan aircrafts is a crucial factor which has huge influence on the dynamics and stability of these vehicles. In case of a highly flexible wing structure, there is a need for an efficient observer to measure and predict the structural changes and dynamics of the wing. However, the modal coordinates of the wing cannot be measured directly so designing a state observer is necessary. Since the flexible aircraft model is nonlinear, the classical Kalman filter approach can have limited performance. Instead, two state observer approaches are investigated in the paper. First, we present a model-based method for designing an extended Kalman filter (EKF) when only a linear parameter-varying model (LPV) is available to describe the behaviour of the real aircraft. Second, we present a data-driven approach for this problem which is based on the new KalmanNet architecture. Finally, the results of the two methods are evaluated on the T-Flex model of the FLiPASED H2020 project. © Proceedings of the International Forum of Aeroelasticity and Structural Dynamics 2022, IFASD 2022.

关键词： Aeroelasticity

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Reinforcement Learning with Success Induced Task Prioritization 21st

Reinforcement Learning with Success Induced Task Prioritiza...

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21st Mexican International Conference on Artificial Intelligence, MICAI 2022

作者： Nesterova, Maria Skrynnik, Alexey Panov, Aleksandr Moscow Institute of Physics and Technology Moscow Russia AIRI Moscow Russia Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031194924

Many challenging reinforcement learning (RL) problems require designing a distribution of tasks that can be applied to train effective policies. This distribution of tasks can be specified by the curriculum. A curriculum is meant to improve the results of learning and accelerate it. We introduce Success Induced Task Prioritization (SITP), a framework for automatic curriculum learning, where a task sequence is created based on the success rate of each task. In this setting, each task is an algorithmically created environment instance with a unique configuration. The algorithm selects the order of tasks that provide the fastest learning for agents. The probability of selecting any of the tasks for the next stage of learning is determined by evaluating its performance score in previous stages. Experiments were carried out in the Partially Observable Grid Environment for Multiple Agents (POGEMA) and Procgen benchmark. We demonstrate that SITP matches or surpasses the results of other curriculum design methods. Our method can be implemented with handful of minor modifications to any standard RL framework and provides useful prioritization with minimal computational overhead. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Reinforcement learning

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research and Analysis of the Method for Measuring the Moisture Content of Cottonmaterials at Ultrahigh Frequencies

Research and Analysis of the Method for Measuring the Moistu...

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2023 International Conference Automatics and Informatics, ICAI 2023

作者： Kalandarov, Palvan I. Turkmenov, Khasan E. Ubaydullayeva, Shakhnoza R. Nikolov, Nikola N. Alexandrova, Mariela I. 'Tashkent Institute of Irrigation and Agricultural Mechanization Engineers' National Research University Department 'Automation and Control of Technology Process in Production' Tashkent Uzbekistan Technical University of Varna Faculty of Computer Science and Automation Department of Automation Varna Bulgaria

ISBN: (纸本)9798350312911

The article provides a theoretical analysis of the ultrahigh frequency (microwave) method of humidity measurement, discusses the problems of instrumentation of the method in question, and proposes a scheme of an experimental installation. Bulk cotton materials were selected as the objects of research. The electromagnetic wave radiation is analyzed during measurement and the evaluation of electrophysical characteristics requires the study of the functional dependence of the amplitude and phase shift on the mass ratio of humidity, mathematical models for various bulk cotton materials describing the joint effect of humidity, material density on the attenuation and phase shift of the passing wave are obtained. © 2023 IEEE.

关键词： Humidity control

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