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24th International Conference on control Systems and computer science, CSCS 2023

作者： Cimpanu, Corina Gheorge Asachi Technical University of Iai Faculty of Automatic Control and Computer Science Computer Science Department Iai Romania

ISBN: (纸本)9798350313390

computer science developments in medical data processing increase modeling accuracy, speed up data analysis, and obtain automated diagnostics. As a result, the role of machine learning algorithms becomes significant, as well as the need to implement faster and more accurate systems. For example, classification is a common component in computer-aided diagnostics, and choosing the proper set of predictors is critical for training a classifier model. Usually, medical datasets are highly dimensional, and their characteristical data correlations require reducing the set of features used for classification. Besides supervised grouping algorithms, genetic optimization procedures are well known for their robust verification of competing attributes by directly estimating their usefulness on a specific classifier. This paper discusses the assessment of Electroencephalogram data samples acquired during working memory load n-back scenarios using a new embedded feature selection procedure based on Multi-Objective Optimization via Genetic Algorithms enhanced with a hybrid mutation operator. Experimental results focus on both the hybrid mutation operator performances, and obtaining overall higher Support Vector Machine classification accuracy while reducing the number of selected features. © 2023 IEEE.

关键词： Genetic algorithms

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INCREASING THE OBSERVATION CAPABILITIES OF SMALL SOLAR TELESCOPES USING NEURAL NETWORKS 38

INCREASING THE OBSERVATION CAPABILITIES OF SMALL SOLAR TELES...

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38th Annual European Simulation and Modelling Conference, ESM 2024

作者： Jóźwik-Wabik, Piotr Popowicz, Adam Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (纸本)9789492859334

Small solar telescopes play an important role in monitoring dynamic heliophysical phenomena on the Sun, such as solar flares, which affect satellites and ground-based electronic systems. Unfortunately, the quality of the data they obtain is significantly affected by atmospheric turbulence, so they require further processing. Currently, this problem is mainly solved by using a state-of-the-art deterministic algorithm, multi-frame blind deconvolution (MFBD). However, this approach is sensitive to manually adjusted system parameters and requires high computational power and long processing time. In this paper, we explore the possibility of using fully convolutional networks (FCNs) as an alternative to MFBD. In our research, we focus on the data processing time, the quality of the results obtained, as well as the hardware resources required for the practical application of the FCNs by small observatories. We show that the proposed networks can achieve results comparable to MFBD, but in almost real time and using more energy-efficient equipment. © 2024 Modelling and Simulation 2024 - 38th Annual European Simulation and Modelling Conference 2024, ESM 2024. All rights reserved.

关键词： Telescopes

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BIOPHYSICAL SIGNAL PROCESSING FOR automatic ANXIETY CLASSIFICATION IN A VIRTUAL REALITY EXPOSURE THERAPY SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2024年第2期86卷 73-84页

作者： Jinga, Nicolae Petrescu, Cătălin-Dumitru Mitruț, Oana Moldoveanu, Alin Moldoveanu, Florica Petrescu, Livia Dept. of Computer Science National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Automatic Control and Systems Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Faculty of Biology University of Bucharest Romania

This paper presents a signal processing framework for automatic anxiety level classification in a virtual reality exposure therapy system. Two types of biophysical data (heart rate and electrodermal activity) were recorded, pre-processed and passed through a feature extraction procedure that provided input for the real-time anxiety level classification algorithm. We showcase the mathematical and engineering techniques behind the procedures and conclude with the challenges encountered in our research and future development ideas. The proposed method provides a good estimate of the level of anxiety while having at the same time a reduced level of complexity, allowing implementation on equipment with limited computing resources. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Classification (of information)

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Massive Natural Language Processing in Distributed Environment 20th

Massive Natural Language Processing in Distributed Environm...

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20th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2023

作者： Krechowicz, Adam Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland

ISBN: (纸本)9783031383175

Natural Language Processing (NLP) models are one of the most promising topics nowadays. Applications like ChatGPT uncover the power of such models and their broad applications. However, developing such models requires an extensive amount of training data sets to operate on. As such data sets grow, it becomes impossible to process them on a single machine, even using parallel computations. In this paper, the problem of distributing the NLP computations is taken into consideration. The Scalable Distributed Two-Layer Data Structures were used to organize the distributed environment. Stanford Core NLP library was used to perform accurate NLP computations. The experiments focused on the efficiency of the computation in the distributed environment and the accuracy of the predictions in relation to the scale of the distributions. The results clearly show that an increase in performance can be obtained without a significant decrease in accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

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Real-Time Communication Model for IoT Systems 18

Real-Time Communication Model for IoT Systems

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18th Conference on computer science and Intelligence Systems, FedCSIS 2023

作者： Deniziak, Stanislaw Plaza, Miroslaw Arcab, Lukasz Kielce University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science Kielce Poland

ISBN: (纸本)9788396744784

Internet of Things solutions typically involve interaction between sensors, actuators, the cloud, embedded systems and user applications. Often in such cases, there are time constraints specifying the maximum response time to a request. This time depends on the calculation time and transmission time. Existing Internet communication solutions do not ensure the implementation of transmissions in a way that guarantees meeting the set time constraints. This paper proposes a new model of Internet communication dedicated to real-time Internet of Things systems, which includes a communication protocol, as well as a transmission scheduling and routing method. The protocol takes into account information about transmission time constraints, which is used for packet scheduling by routers, allowing to increase quality of service. In addition, the proposed static routing mechanism makes it possible to parallelize transmissions if time constraints are still exceeded. Also presented are preliminary results of experiments showing to what extent the proposed methods allow improving the quality of service in real-time Internet of Things systems. © 2023 Polish Information Processing Society.

关键词： Internet of things

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EQUILIBRIA AND STABILITY OF ONE MESSENGER RNA AND TWO MICRO RNA DYNAMICS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2022年第4期84卷 3-8页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

In this paper we study an ODE model on the microRNA-mRNA dynamics. We prove the existence of two equilibrium points (one with strictly positive compo-nents) and obtain a biologically consistent, sufficient asymptotic stability condition for the strictly positive equilibrium. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Asymptotic stability

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Integrating photovoltaic systems into HVAC control using fuzzy algorithms for optimizing thermal comfort 30

Integrating photovoltaic systems into HVAC control using fuz...

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30th IEEE International Symposium for Design and Technology in Electronic Packaging, SIITME 2024

作者： Boicu, Mihaela-Gabriela Dobrea, Marius-Alexandru Vasluianu, Mihaela Olteanu, Gabriela-Valentina Neculoiu, Giorgian University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Technical University of Civil Engineering of Bucharest Faculty of Hidrotechnics Bucharest Romania

ISBN: (纸本)9798331539511

This article presents a study on the use of photovoltaic panels for storing electrical energy intended to power an HVAC unit placed in a residential room. To highlight this aspect, two specific scenarios will be considered. Thus, we aim to analyze whether the generated and stored energy is sufficient to fulfil the thermal comfort requirements of the user, while also considering the primary objective of minimizing energy consumption. To achieve this goal, the HVAC unit will be controlled by implementing a fuzzy system that determines its optimal activation based on the comfort level obtained from the user. The fuzzy system presents as inputs both environmental parameters and specific personal perception parameters of the user. The research results provide an insight into the efficiency of implementing photovoltaic energy storage systems for residential applications and propose solutions for optimizing energy consumption in the context of ensuring adequate thermal comfort. Thus, the study contributes to the development of sustainable and personalized energy solutions for smart homes. © 2024 IEEE.

关键词： Thermal comfort

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Development of control Strategies for an Industrial Robot to Increase Energy Efficiency 30

Development of Control Strategies for an Industrial Robot to...

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30th IEEE International Symposium for Design and Technology in Electronic Packaging, SIITME 2024

作者： Dobrea, Marius-Alexandru Vasluianu, Mihaela Neculoiu, Giorgian Olteanu, Gabriela-Valentina Boicu, Mihaela-Gabriela Varlan, Eduard University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Technical University of Civil Engineering of Bucharest Faculty of Hidrotechnics Bucharest Romania

ISBN: (纸本)9798331539511

The paper aims to optimize the energy consumption of industrial robots, with the goal of reducing operational costs and improving the sustainability of the production process. The methods discussed include using energy-efficient components, reducing idle times, and optimizing robot trajectory programming to minimize unnecessary movements. The project presents a simulation of an industrial process for sorting and depalletizing parts using a KUKA KR 4 Agilus robot, along with Arduino development boards for control and coordination. A color sensor system is employed for object detection, optimizing the robot's movements based on the data collected. To analyze energy and time efficiency, two movement routines were compared: one based on SLIN and the other on SPTP. © 2024 IEEE.

关键词： Industrial robots

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A Distributed automatic Domain-Specific Multi-Word Term Recognition Architecture using Spark Ecosystem 22

A Distributed Automatic Domain-Specific Multi-Word Term Reco...

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22nd International Symposium on Parallel and Distributed Computing, ISPDC 2023

作者： Truica, Ciprian-Octavian Istrate, Neculai-Ovidiu Apostol, Elena-Simona University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (纸本)9798350341270

automatic Term Recognition is used to extract domain-specific terms that belong to a given domain. In order to be accurate, these corpus and language-dependent methods require large volumes of textual data that need to be processed to extract candidate terms that are afterward scored according to a given metric. To improve text preprocessing and candidate terms extraction and scoring, we propose a distributed Spark-based architecture to automatically extract domain-specific terms. The main contributions are as follows: (1) propose a novel distributed automatic domain-specific multi-word term recognition architecture built on top of the Spark ecosystem;(2) perform an in-depth analysis of our architecture in terms of accuracy and scalability;(3) design an easy-to-integrate Python implementation that enables the use of Big Data processing in fields such as Computational Linguistics and Natural Language Processing. We prove empirically the feasibility of our architecture by performing experiments on two real-world datasets. © 2023 IEEE.

关键词： Ecosystems

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On the development of autonomous agents using deep reinforcement learning

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2021年第3期83卷 97-116页

作者： Barbu, Clara Mocanu, Ștefan Alexandru Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharesti Romania

This paper presents a study on the general concept of autonomous agents, with an accent on the development of such agents using deep reinforcement learning. This is combined with the domain of autonomous vehicles, as illustrated by a practical application: having a vehicle agent learn how to navigate and park by itself on a designated spot, in a virtual parking lot environment created in Unity. The reinforcement learning method Deep Q–Learning is implemented, with the addition of a few improvements such as Double Deep Q–Learning and Experience Replay. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： Reinforcement learning

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