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27th International Conference on Computer Networks, CN 2020

作者： Kozielski, Stanislaw Mrozek, Dariusz Department of Applied Informatics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9783030507183

The aim of the work is to present the development trends of high performance computers. The analysis focused on system architecture, processors and computing accelerators used. Particular attention was paid to interconnection networks, connecting system nodes. The problem of energy saving in the construction of large systems was also discussed. The data from the list of 500 largest computer systems was used in the analysis. © Springer Nature Switzerland AG 2020.

关键词： Energy conservation

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Multi-Agent Economic Modeling Automation Technologies 9

Multi-Agent Economic Modeling Automation Technologies

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9th International Conference on control, Decision and Information Technologies, CoDIT 2023

作者： Zhukova, Aleksandra A. Pilnik, Nikolai P. Kamenev, Ivan G. Iusup-Akhunov, Batyrzhan B. Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Modelling in Economic Social and Ecological Systems Vavilov st. 44 building 2 Moscow119333 Russia Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Department of Mathematical Modelling of Economic Systems Vavilov st. 44 building 2 Moscow119333 Russia Hse University Faculty of Economic Sciences Department of Applied Economics Pokrovsky Bulvar 11 Moscow109028 Russia Fsbeihe Bauman Moscow State Technical University Department of Fundamental Sciences-11 2nd Baumanskaya street 5-1 Moscow05005 Russia The Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology 9 Institutskiy per. Moscow Region Dolgoprudny141701 Russia

ISBN: (纸本)9798350311402

Complex economic models often describe the agent's decisions, i.e. choice of some controlled variables in accordance with criteria set by agents. Unlike purely statistical ones, agent-based models allow to describe processes with different modes, in which the agent's behavior changes quali-tatively when the environment (including the actions of other agents) change. The practical use of mathematical models of complex systems with a number of interacting agents is limited by complexity of their construction and possible errors when dealing with multitude of expressions. Computer tools, such as the 'Ecomod' system discussed in the article, can substantially reduce the time spent on model creation and processing, and help to coordinate the work of several researchers on the model. © 2023 IEEE.

关键词： Autonomous agents

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Simplified Mecanum Wheel Modelling using a Reduced Omni Wheel Model for Dynamic Simulation of an Omnidirectional Mobile Robot 11

Simplified Mecanum Wheel Modelling using a Reduced Omni Whee...

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11th International Conference and Exposition on Electrical And Power Engineering, EPE 2020

作者： Dosoftei, Catalin Horga, Vasile Doroftei, Ioan Popovici, Tudor Custura, Stefan 'Gheorghe Asachi' Technical University of Iasi Dept. of Automatic Control and Applied Informatics Romania Self Trust Company Dept. of Mechanical Engineering Design Iasi Romania

ISBN: (纸本)9781728181264

Industrial and technical applications of omnidirectional mobile robots, with Mecanum wheels, are continuously gaining in importance because their excellent mobility, especially in areas with static or dynamic obstacles. The perspective of Industry 4.0 imposes an effective and efficient approach for production in general and then, specific to this application, to implement the control algorithm able to deliver to robot the deliberatively and reactively behaviour. An important tool to achieve these goals is virtualization of the prototype and his simulation in a 3D virtual *** paper presents a simplified method of modelling and kinematics simulation in Simscape Multibody™, taking an omnidirectional mobile robot with advantages related to simulation time. The necessary steps to develop inverse kinematics in robots and global reference frame, for specific omnidirectional mobile robot, are depicted in the paper using bottom-up approach with matrix transformation. The 3D modelling process starts from the CAD design, which is then transferred into a Simscape Multibody™ model in order to study the kinematic and dynamic characteristics. Four typical motion models including moving forward, moving laterally, moving in the diagonal direction and rotation have been simulated in Simscape Multibody™. © 2020 IEEE.

关键词： Inverse kinematics

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On Multi-Robot Path Planning Based on Petri Net Models and LTL specifications

arXiv

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arXiv 2022年

作者： Hustiu, Sofia Mahulea, Cristian Kloetzer, Marius Lesage, Jean-Jacques The Dept. of Automatic Control and Applied Informatics Technical University "Gheorghe Asachi" of Iasi Romania University of Zaragoza Maria de Luna 1 Zaragoza50018 Spain Université Paris-Saclay ENS Paris-Saclay LURPA Gif-sur-Yvette91190 France

This work considers the path planning problem for a team of identical robots evolving in a known environment. The robots should satisfy a global specification given as a Linear Temporal Logic (LTL) formula over a set of regions of interest. The proposed method exploits the advantages of Petri net models for the team of robots and Büchi automata modeling the specification. The approach in this paper consists in combining the two models into one, denoted Composed Petri net and use it to find a sequence of action movements for the mobile robots, providing collision free trajectories to fulfill the specification. The solution results from a set of Mixed Integer Linear Programming (MILP) problems. The main advantage of the proposed solution is the completeness of the algorithm, meaning that a solution is found when exists, this representing the key difference with our previous work in [1]. The simulations illustrate comparison results between current and previous approaches, focusing on the computational complexity. © 2022, CC BY.

关键词： Petri nets

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Continual Learning of a Time Series Model Using a Mixture of HMMs with Application to the IoT Fuel Sensor Verification

Continual Learning of a Time Series Model Using a Mixture of...

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Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Przemysław Głomb Michał Cholewa Paweł Foszner Jakub Bularz Institute of Theoretical and Applied Informatics Polish Academy of Sciences Gliwice Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland AIUT Sp. z o.o. ul Gliwice Poland

This paper presents an application of a mixture of Hidden Markov Models (HMMs) as a tool for verification of IoT fuel sensors. The IoT fuel sensors report the level of fuel in tanks of a petrol station, and are a key component for monitoring system reliability (billing), safety (fuel/oil leak detection) and security (theft prevention). We propose an algorithm for learning a mixture of HMMs based on a continual learning principle, i.e. it adapts the model while monitoring a sensor over time, signalling unexpected or anomalous sensor reports. We have tested the proposed approach on a real-life data of 15 fuel tanks being monitored with the FuelPrime system, where it has shown a very good performance (average area under ROC curve of 0.94) of detecting anomalies in the sensor data. Additionally we show that the proposed method can be used for trend monitoring and present qualitative analysis of the short and long term learning performance. The proposed method has promising performance score, the resulting model has a high degree of explainability, limited memory and computation requirements and can be easily generalized to other domains of sensor verification.

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Departure Counting Process in a Finite-Buffer Queue with Batch Arrivals and Multiple Vacation Policy

SSRN

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SSRN 2024年

作者： Marjasz, Rafal Kempa, Wojciech M. Kovtun, Viacheslav Institute of Theoretical and Applied Informatics Polish Academy of Sciences 5 Baltycka Str. Gliwice44-100 Poland Silesian University of Technology Faculty of Applied Mathematics 23 Kaszubska Str. Gliwice44-100 Poland Vinnytsia National Technical University Faculty of Intelligent Information Technologies and Automation Department of Computer Control Systems 95 Khmelnitske Shose Str. Vinnytsia21000 Ukraine

The study investigates the departure counting process in a finite-buffer queueing system with batch arrivals and multiple vacation policy. A representation for the mixed double transform of the number of departures up to the fixed time moment is obtained in the explicit form applying analytic approach based on integral equations and linear algebra. Numerical study is attached that focuses on understanding the impact of various system parameters on the behaviour of the mean number of packets processed within a fixed time frame. Utilizing numerical experiments, the study examines the influence of vacation duration, initial buffer state, arrival intensity, and processing rate on the departure process. Results reveal significant dependencies between these parameters and the transient behaviour of the queueing system. Notably, the service speed parameter demonstrates the most substantial influence on the mean number of processed packets, followed by the arrival rate. Conversely, variations in vacation duration and initial packet count exhibit comparatively minor effects on system behaviour. Overall, the findings provide valuable insights into the dynamics of departure processes in finite-buffer queue systems with batch arrivals and multiple vacation policies, offering implications for system optimization and performance enhancement strategies. © 2024, The Authors. All rights reserved.

关键词： Integral equations

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Machine Learning-Based Cascade Filtering System for fNIRS Data Analysis

Machine Learning-Based Cascade Filtering System for fNIRS Da...

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Progress in applied Electrical Engineering (PAEE)

作者： Mariusz Pelc Dariusz Mikołajewski Tuukka Ruotsalo Luis A. Leiva Adam Sudoł Edward Jacek Gorzelańczyk Adam Łysiak Aleksandra Kawala-Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Institute of Computer Science Kazimierz Wielki University Bydgoszcz Poland University of Helsinki Finland University of Copenhagen Denmark Department of Computer Science University of Luxembourg Luxembourg Luxembourg Faculty of Natural and Technical Sciences University of Opole Opole Poland Institute of Philosophy Kazimierz Wielki University Bydgoszcz Poland

This paper presents a preliminary study on the use of machine learning-based methods to select the appropriate parameters of cascade filters in the analysis of brain signals recorded using functional infrared spectroscopy (fNIRS), which shows the level of oxygenation in the brain and, unlike EEG signals (showing electrical brain activity), are less prone to potential interference, disturbances or artifacts occurrence.

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Study of photophysical properties of Cdq2 thin film

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Materials Today: Proceedings 2022年 66卷 202-204页

作者： Lougdali, M. El Kouari, Y. Anoua, R. Zazoui, M. El Oudghiri-Idrissi, I. Abboud, Y. Zawadzka, A. Sahraoui, B. Laboratory of Materials Energy and Control System Faculty of Sciences and Technology Hassan II University of Casablanca Mohammedia B.P 146 Morocco Department of Automatic and Measurement Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Torun Poland Laboratory of Engineering Sciences for Energy National School of Applied Sciences of El Jadida El Jadida BP 1166 Morocco Faculty of Sciences Ben M'sik University of Hassan II of Casablanca Casablanca Morocco Centre for Modern Interdisciplinary Technologies Nicolaus Copernicus University Wilenska 4 Torun 87-100 Poland MOLTECH-Anjou UMR 6200 CNRS UNIV Angers 2 bd Lavoisier Angers 49045 France

In this work, the morphological and optical properties of the cadmium (II) bis(8-hydroxyquinoline) (Cdq2) thin film are presented. The film was elaborated by physical deposition technique. The Atomic Force Microscopy (AFM) image shows a homogenous surface. The transmittance was measured in the range of 300–1200 nm with UV–visible spectroscopy. The emission of the film was characterized via the photoluminescence spectroscopy, a strong luminescence has been found. The measurements done at low temperatures show a decrease of the intensity of luminescence in the temperature range of 77–300 K. © 2022

关键词： Thin films

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Intelligent model for assessing the suitability of water based on its chemical and biological parameters 24

Intelligent model for assessing the suitability of water bas...

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24th International Symposium INFOTEH-JAHORINA, INFOTEH 2025

作者： Tynchenko, Yadviga Tynchenko, Vadim Degtyareva, Ksenia Kuznetsov, Georgy Kukartseva, Svetlana Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk Russia Department of Systems Analysis and Operations Research Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Department of Applied Informatics Moscow Timiryazev Agricultural Academy Moscow Russia Center for Continuing Education Bauman Moscow State Technical University Moscow Russia Information-Control Systems Department Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia

ISBN: (纸本)9798331515799

This paper presents a study on the development and testing of a machine learning model for classifying water according to its purpose, based on chemical and microbiological indicators. The aim of the study is to create an accurate and stable model that can effectively determine the categories of water - drinking, industrial, agricultural and technical - based on the analysis of its qualitative characteristics. The gradient boosting method was chosen as the algorithm for classification, which demonstrated high accuracy and reliability when working with multidimensional data. The study included the processing of a synthetic dataset containing information on water parameters such as calcium concentration, total bacterial content, phosphate levels, alkalinity, sulfates and oxidizability. The analysis of the correlation matrix made it possible to identify the relationships between the features, which made it possible to optimize the operation of the model and improve its accuracy. The quality of the model was tested using accuracy, completeness and F1-score metrics, which demonstrated almost perfect results for all categories. In conclusion, it is concluded that the proposed model can be successfully used to automate the analysis of water quality in ecology, industry and agriculture. The use of intelligent technologies opens up new opportunities for monitoring water resources, increasing the efficiency and reliability of quality control. © 2025 IEEE.

关键词： Taxonomies

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Assessment of the mineral potential of rocks using intelligent data analysis technologies 24

Assessment of the mineral potential of rocks using intellige...

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24th International Symposium INFOTEH-JAHORINA, INFOTEH 2025

作者： Tynchenko, Yadviga Tynchenko, Vadim Degtyareva, Ksenia Kalmykova, Ekaterina Kukartseva, Svetlana Bauman Moscow State Technical University Artificial Intelligence Technology Scientific and Education Center Moscow Russia Siberian Federal University School of Petroleum and Natural Gas Engineering Department of Technological Machines and Equipment of Oil and Gas Complex Krasnoyarsk Russia Reshetnev Siberian State University of Science and Technology Information-Control Systems Department Krasnoyarsk Russia Reshetnev Siberian State University of Science and Technology Department of Systems Analysis and Operations Research Krasnoyarsk Russia Bauman Moscow State Technical University Center for Continuing Education Moscow Russia Moscow Timiryazev Agricultural Academy Department of Applied Informatics Moscow Russia

ISBN: (纸本)9798331515799

This paper presents a study aimed at developing and evaluating a classification model for the mineral potential of geological layers using machine learning methods. The main goal was to create an algorithm capable of predicting the categories of mineral potential - low, medium and high - based on key geological characteristics such as ore content, density, depth, permeability and rock type. The results obtained demonstrated the overall accuracy of the model at 98%, with an almost ideal classification for the categories of medium and high mineral potential. The analysis of the significance of the features showed that the ore content and density have the greatest impact on the classification. The work also revealed certain difficulties in classifying low mineral potential, which is due to limited data or the intersection of characteristics between classes. These results highlight the importance of further research in feature selection and improving data balance. The findings demonstrate the effectiveness of using machine learning methods in geological research and their potential for automating mineral resource assessment processes. The developed methodology can be adapted to solve other problems in the field of geology, such as forecasting deposits and optimizing mining. © 2025 IEEE.

关键词： Radioactive prospecting

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