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检索条件"机构=Faculty of Automatic Control and Computer Science Bucharest"

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Biological Influence of Low-Frequency Electromagnetic Field Exposition Based on Selected Cell Death Markers 15

Biological Influence of Low-Frequency Electromagnetic Field ...

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15th International Conference Elektro, ELEKTRO 2024

作者： Cichorowski, Robert Kocikowska, Olga Bajtos, Marek Radil, Roman Janousek, Ladislav De Carrillo, Daria Gendosz Student, Sebastian Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Department of Engineering and Systems Biology Gliwice Poland Silesian University of Medicine Faculty of Medical Sciences Department of Physiology Katowice Poland Faculty of Electrical Engineering and Informational Technology Department of Electromagnetic and Biomedical Engineering Žilina Slovakia Silesian University of Medicine Faculty of Medical Sciences in Zabrze Department of Histology Zabrze Poland Silesian University of Technology Biotechnology Center Gliwice Poland

ISBN: (纸本)9798350372359

This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell death. The examination of cell death hallmarks were examined by estimation levels of selected proteins - FACL4 (a protein that is a part of the ferroptosis pathway) and CK18 (Cytokeratin related to necrosis and apoptosis pathways) in the proposed model of workers exposed to ELF-EMF week. © 2024 IEEE.

关键词： Electromagnetic fields

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Decision System for Ensuring Thermal Comfort of Occupants in a Smart Building

Decision System for Ensuring Thermal Comfort of Occupants in...

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International Conference on control Systems and computer science (CSCS)

作者： Mihaela - Gabriela Boicu Grigore Stamatescu Cosmin - Florin Fudulu Marius - Alexandru Dobrea Mihaela Vasluianu Giorgian Neculoiu Faculty of Automatic Control and Computer Science University POLITEHNICA of Bucharest Romania Faculty of Hidrotechnics Technical University of Civil Engineering of Bucharest Romania

This paper presents the development of a system that uses fuzzy logic in order to evaluate the thermal comfort conditions expressed by means of a score by the occupants of an office room The inputs of the system are represented by three datasets relevant to the study: the air temperature, the positioning of the occupant and the level of activity carried out by the occupant. Based on the comfort score obtained, the HVAC system located at the room level will maintain a comfortable environment. The proposed solution also contributes to the minimization of energy consumption in buildings. In order to collect the data sets necessary for the study, we used the *** module as a wearable device.

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Evaluating the usage of Text to3D scene generation methods in Game-Based Learning

Evaluating the usage of Text to3D scene generation methods i...

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International Conference on control Systems and computer science (CSCS)

作者： Alexandru Gradinaru Mihnea Vrejoiu Florica Moldoveanu Maria-Anca Balutoiu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania National Institute for Research and Development in Informatics Bucharest Romania

computer games as an educational tool significantly improved information retention, student involvement, and motivation. Despite the growing popularity and the demonstrated positive impact, little progress is made to let educators create games without learning game programming or investing massive amounts of time, money, and human resources. This paper considers the usage of procedural content generation in simplifying the generation of game environments. Given that most educational material is in text format, we evaluate the possibility of generating 3D scenes starting from natural language text. A comprehensive survey of the current methods is presented, analyzing whether they can be successfully used in game-based learning. The study discusses several current limitations and possible improvements, highlighting a need for better progress in the domain.

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How transformations of representation for input data can affect the properties of induced decision reducts and rules 27

How transformations of representation for input data can aff...

引用

27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Stanczyk, Urszula Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Decision reducts and rules belong to forms used for the representation of knowledge learnt from input data while using a rough set approach in the exploration stage. As with any patterns that capture properties of data, the size is considered as the most important indicator of their quality, as a more general and concise description allows for improved understanding and simplified interpretation. The size of a reduct is given by its cardinality, and for a rule it is a number of included conditions, both referred to as lengths. These lengths undergo transformations along with data transformations, so such processing as discretisation leads to changed characteristics of existing patterns and through them also reducts and rules. The paper presents research with contributions in the observations focused on the influence of supervised and unsupervised discretisation on properties of attributes, induced decision reducts, and rules, offering a deeper insight into relations among them. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Data exploration decision reduct decision rule discretisation knowledge representation rough set theory transformation

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Should supervised discretisation always be trusted unreservedly? On combining characteristics of supervised and unsupervised discretisation algorithms in two-step processing 27

Should supervised discretisation always be trusted unreserve...

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27th International Conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Stanczyk, Urszula Baron, Grzegorz Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

The paper presents a description of the research methodology dedicated to a two-step discretisation process applied to the input numeric data, with combining the characteristics of selected supervised and unsupervised algorithms, which leads to extended processing of some attributes in train and test sets. The methodology was illustrated with the investigations carried out in the domain of stylometric analysis of texts, for two datasets prepared for the task of binary authorship attribution. The several variants of transformed input data obtained were subjected to exploration using two selected machine learning methods capable of inducing knowledge from both continuous and categorical forms, namely the PART and J48 classifiers. The results from the experiments indicate that, as can be expected, supervised transformations of data work well enough, however, they do not always return the best outcome. The two-step processing of some attributes shows sufficient promise to warrant a closer study, as opposed to always unconditionally relying only on supervised algorithms as outperforming all other approaches. © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Authorship attribution Data representation Pattern recognition Stylometry Supervised discretisation Unsupervised discretisation

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Client request analysis tool for CERN ALICE grid services

Client request analysis tool for CERN ALICE grid services

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2020 International Conference on Computing and Data science, CDS 2020

作者： Margineanu, Cristian Grigoras, Costin Carabas, Mihai Weisz, Sergiu Mihai, Darius Mihailescu, Maria-Elena Tapus, Nicolae Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania Alice Cern Geneva Switzerland

ISBN: (纸本)9781728171067

ALICE is an experiment hosted at the CERN facilities in Geneva. The data collected by the experiment is distributed in multiple geo-locations. ALICE software development team is managing the technologies that offer a unitary view to the distributed resources. AliEn API Services and JAliEn Services are used by the researchers to access and analyze the collected data. The ALICE developers cannot analyze the client-server interactions, while the only information available is gathered in the log files. The main requirement of the project is to provide an analysis tool to extract vital information out the log files. The tool is tested against log files generated by the ALICE production servers and is deployed on a custom ALICE-owned instance. As of June 2020, the project is being used by the developers to extract near real-time viable requests information and have a correct picture of the researcher's interaction with the services. © 2020 IEEE

关键词： Software design

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Weighting Attributes Based on the Greedy Algorithm Properties 28th

Weighting Attributes Based on the Greedy Algorithm Propertie...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Zielosko, Beata Stanczyk, Urszula Jablonski, Kamil University of Silesia in Katowice Institute of Computer Science Bedzinska 39 Sosnowiec41-200 Poland Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

Estimation of importance for considered features is an important issue for any knowledge exploration process and it can be executed by a variety of approaches. In the research reported in this study, the primary aim was the development of a methodology for creating attribute rankings. Based on the properties of the greedy algorithm for inducing decision rules, a new application of this algorithm has been proposed. Instead of constructing a single ordering of features, attributes were weighted multiple times. The input datasets were discretised with several algorithms representing supervised and unsupervised discretisation approaches. Each resulting discrete data variant was exploited to construct a ranking of attributes. The effectiveness of the obtained rankings was confirmed through a rule filtering process governed by weighted attributes. The methodology was applied to the stylometric task of authorship attribution. The experimental outcomes demonstrate the value of the proposed research method, as it generally led to improved predictions while taking into account a noticeably decreased sets of attributes and decision rules. © 2024 The Authors.

关键词： Consensus algorithm

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A Framework for Analyzing GPU-Executed Malware 23

A Framework for Analyzing GPU-Executed Malware

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Apostol, Teodor-Petrut Velea, Radu Deaconescu, Razvan University Politehnica of Bucharest Faculty of Automatic Control and Computers Computer Science and Engineering Department Romania

ISBN: (纸本)9781665439398

Graphics processing units (GPU) are an integral part of today's computing environment. The marketing emphasis on user experience pushes vendors to constantly look for better graphics hardware and newer drivers to integrate into their products. Most commodity GPUs function as accelerators for image and video processing tasks and are present (either as dedicated or integrated form factor) in everyday devices including desktops, laptops, smartphones or other portable gadgets. Recent trends have seen the GPU move to perform additional tasks such as offloading some of the computation from the CPU or solve highly parallel problems. As GPUs become more powerful and widespread they will naturally become a very attractive target for attackers. Cybercriminals will look for any vulnerability in the GPU hardware or software, and will try to use it as an attack vector to compromise the system. This paper presents some of the incidents that involve the use of GPUs to perform malicious actions and proposes a framework to allow analysts to inspect the code executed on the GPU and trigger security alerts. The proposed solution will look at the processes running inside an operating system, it will identify which of them require access to the GPU and will try to intercept and scan for any suspicious activities, similar to a conventional security solution. © 2021 IEEE.

关键词： Graphics processing unit

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Analysis of YouTube Video Comments with NLP Methods

Analysis of YouTube Video Comments with NLP Methods

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Pirnau Mironela Priescu Iustin Priescu Catalina Mihaela Pirnau Claudiu Ghiculescu Liviu Daniel Department of Informatics Faculty of Informatics “Titu Maiorescu” University Bucharest Romania Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania Manufacturing Engineering Department Faculty of Industrial Engineering and Robotics National University of Science and Technology POLITEHNICA Bucharest Bucharest Romania

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

This study proposes methods that can be used to examine and interpret comments that users have made after watching videos on YouTube on a particular topic. YouTube tutorials are very popular among young people. They have become an important pillar in informal education, thus contributing to the rapid acquisition of skills and knowledge. Under these circumstances, we were interested in analysing the YouTube videos comments, knowing that the platform has a continuous increase in popularity, which is also due to the opportunities of sharing them. Since ChatGPT-themed YouTube videos have seen a significant surge in popularity since 2022, we were interested to analyse some videos that approach the topics of “ChatGPT, AI clone, AI robot and Deep Learning.”

关键词： Video on demand Social networking (online) Education Tutorials Chatbots Web sites Artificial intelligence

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Comparative Study of Neural Networks Used in Halyomorpha Halys Detection*

Comparative Study of Neural Networks Used in Halyomorpha Hal...

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Mediterranean Conference on control and Automation (MED)

作者： Dan Popescu Loretta Ichim Mihai Dimoiu Raluca Trufelea Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

The paper’s purpose was to investigate some methods based on neural networks for the detection and classification of harmful insects for agriculture as the Halyomorpha Halys. The implementation of different object detection networks for image categorization was analyzed. Images from the Maryland Biodiversity database were used for neural network training and testing. Rotation, scaling, blurring, mirroring, and other techniques were employed for data augmentation. For the detection and classification of Halyomorpha Halys, some neural networks that include multiple smaller networks were implemented and investigated. The networks used are the following: YOLOv5s, SSD with different backbones such as MobileNet V1, MobileNet V2, and ResNet-50, Faster R-CNN with ResNet-50 backbone, and EfficientDet-D0. Moreover, neural networks were evaluated and compared based on performance metrics such as accuracy and time. Performances like accuracy between 0.49 – 0.86 and time between 36 ms – 55 ms were obtained. The best results were obtained for YOLOv5s, in terms of accuracy, and EfficientDet-D0, in terms of time.

关键词： Training Insects Neural networks Transfer learning Object detection Real-time systems Agriculture

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