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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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Automated Assessment of Medical Rehabilitation of Gait by Means of Video Processing in Cloud Environment

Automated Assessment of Medical Rehabilitation of Gait by Me...

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E-Health and Bioengineering Conference (EHB)

作者： Elena-Claudia Maftei Otilia Zvorişteanu Hariton-Nicolae Costin Silviu Bejinariu Florin Rotaru Vasile Manta Ramona Luca Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Institute of Computer Science Romanian Academy Iaşi Branch Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Human gait analysis provides qualitative and quantitative information concerning different characteristics of walking of a certain person. Cloud computing proves to be a modern and valuable technology when dealing with data scalability, security and efficiency of processing and storage. Also, this paradigm has some key-benefits like real-time data sharing, fast computation as well as collaborative research. The applications gamut which uses cloud computing is getting bigger and bigger, and healthcare sector is an important domain in this respect. Our approach proposed a cloud-based service designed for the automated assessment of medical rehabilitation of human gait by using video processing. We have chosen this processing technology because it is marker-less, allows fast computation and offers a very good precision of the gait analysis. Cloud computing approach proved to be encouraging and underscores remarkable advantages in comparison with traditional on-site video processing. In this way the patient, after a short training session, can himself/herself make tests and assessments of his/her mobility status, avoiding many consultations of medical or kineto-therapeutic staff.

关键词： Legged locomotion Training Cloud computing Scalability Medical services Gain measurement People with disabilities Real-time systems Security Personnel

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Analysis of selected dielectric parameters of insulating liquids

Analysis of selected dielectric parameters of insulating liq...

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International Scientific Conference on Electric Power engineering (EPE)

作者： Aleksandra Płużek Łukasz Nagi Michał Kozioł Małgorzata Zygarlicka Department of Electrical Power and Renewable Energy Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

During the last few years, there has been a growing interest in the topic of using natural or synthetic esters as an alternative to mineral oils in oil transformers due to the easier way to obtain them and their ability to exhibit better electrical properties. In addition, more and more researchers are describing in their work that doping esters with nanoparticles is capable of further improving these properties. Therefore, in the current work, it was decided to see what effect the addition of a hydrophobic carbon shell iron nanoparticle to ORLEN mineral oil and Midel 7131 synthetic ester would have on selected electrical parameters of the insulating fluid, i.e. breakdown voltage and electrical strength.

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Estimating the AGV load and a battery lifetime based on the current measurement and random forest application

Estimating the AGV load and a battery lifetime based on the ...

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IEEE International Conference on Big Data

作者： Krzysztof Hanzel Damian Grzechca Adam Ziebinski Lukas Chruszczyk Artur Janus Department of Telecommunications and Teleinformatics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Electronics Electrical Engineering and Microelectronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Department of Distributed Systems and Informatics Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Student of Electrical Engineering Faculty of Electrical Engineering Silesian University of Technology Gliwice Poland

The paper describes the energy consumption from the battery based on the current measurements for various cases, i.e., speed (PWL adjustment) and loads. The main purpose of the research is to have additional and reliable information about power consumption and battery life estimation for autonomous guided vehicles (AGV). The authors propose a two-step algorithm. In the first step, a linear classifier was proposed. Then, the KNN classifier was tested; however, it did not give satisfactory results, so it was finally decided to use the random forest to estimate the load and PWL. The time domain current measurement is evaluated, and the beforementioned algorithms process the selected statistical measures. It has been proven that a two-step algorithm allows for achieving high accuracy. Based on the current observation, the paper is a good starting point for further investigation of the AGV because it is usually implemented in the AGV – so it does not require additional hardware. Moreover, it can lead to better energy management and increase battery lifetime.

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Feature Selection via Genetic Multiobjective Optimization with Fuzzy Rejection Mechanisms 17

Feature Selection via Genetic Multiobjective Optimization wi...

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17th IEEE International Conference on Intelligent computer Communication and Processing, ICCP 2021

作者： Cimpanu, Corina Ferariu, Lavinia Dumitriu, Tiberius Gheorghe Asachi Technical University of Iaşi Faculty of Automatic Control and Computer Engineering Iaşi Romania

ISBN: (纸本)9781665409766

In pattern identification, embedded Feature Selection (FS) determines a detailed data description and an efficient and accurate classification. Most Genetic Algorithm (GA) based optimization procedures tackle the minimization of a classifier's error rate. Independent of how feature selection procedures are configured, either in Single (SOO) or Multi-Objective Optimization (MOO) manners, the major problem with all classifiers is multidimensionality and quantity of redundant and noisy data recordings. This paper compares six GA-based optimizations as viable solutions for an accurate and efficient assessment of working memory load levels during arithmetic computations based on Electroencephalogram (EEG) data. An objective layout analysis of a randomly generated population motivates both SOO and MOO further explorations. The single objective error-based optimization, the aggregation of error, and the number of selected features illustrate the limitations of SOOs. The third SOO incorporates a fuzzy rejection mechanism for unnecessary features. The baseline for MOO comparison is Deb's NSGA. Two new MOO procedures for feature selection are proposed: a MOO Fuzzy Rejection of Irrelevant Features (MOO-FRIF) and a Fuzzy Progressive Deletion of Irrelevant Features (MOO-FPDIF). Both new MOO approaches gradually eliminate or discourage the EEG features that negatively influence the classifier. Two classifiers address the problem distinctively, namely Random Forests (RF) and a multi-class Support Vector Machine (SVM) with one vs. one comparison mechanism and RBF kernel. © 2021 IEEE.

关键词： Multiobjective optimization

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Post-Processing of Thresholding or Deep Learning Methods for Enhanced Tissue Segmentation of Whole-Slide Histopathological Images

Post-Processing of Thresholding or Deep Learning Methods for...

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18th International Joint Conference on Biomedical engineering Systems and Technologies, BIOSTEC 2025

作者： Marczyk, Michal Wrobel, Agata Merta, Julia Polanska, Joanna Department of Data Science and Engineering Silesian University of Technology Gliwice44-100 Poland Yale Cancer Center Yale School of Medicine New HavenCT06511 United States Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice44-100 Poland

Digital pathology allows for the efficient storage and advanced computational analysis of stained histopathological slides of various tissues. Tissue segmentation is a crucial first step of digital pathology aimed at eliminating background, pen markings, and other artifacts, reducing image size, and increasing the efficiency of further analysis. In most cases, color thresholding or deep learning models are used, but their effectiveness is reduced due to complex artifacts and huge color variations between slides. We propose a post processing method to increase the tissue segmentation performance of any initial segmentation algorithm. Using a set of 197 manually annotated histopathological images of breast cancer patients and 63 images of endometrial cancer patients, we tested our method with 3 thresholding techniques and 3 deep learning-based algorithms by calculating the Dice index, Jaccard index, precision, and recall. In both datasets, applying post processing increased precision and recall for thresholding methods and mostly precision for deep learning models. Overall, applying post-processing gave better tissue segmentation performance than initial segmentation methods, significantly increasing Dice and Jaccard indices. Our results proved that thanks to post-processing, the tissue segmentation pipeline is more robust to noises and artifacts commonly present in histopathological images. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Image segmentation

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Finite-time robust performance improvement for non-linear systems in the presence of input non-linearity and external disturbance

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IET control Theory and Applications 2023年第6期17卷 672-682页

作者： Wang, Haoping Ghaffari, Valiollah Mobayen, Saleh Bartoszewicz, Andrzej Fekih, Afef Assawinchaichote, Wudhichai School of Automation Nanjing University of Science and Technology Nanjing China Department of Electrical Engineering Persian Gulf University Bushehr Iran Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Yunlin Douliou Taiwan Institute of Automatic Control Lodz University of Technology Lodz Poland Department of Electrical and Computer Engineering University of Louisiana at Lafayette LafayetteLA United States Department of Electronic and Telecommunication Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Thailand

The main focus of this research is on improving the performance of dynamic systems with actuator non-linearities and time-varying disturbances. To this end, using the concept of finite-time stability, a novel observer is presented to estimate the disturbances in systems with input non-linearities. Then, introducing an innovative sliding manifold, a robust observer-based technique is derived to guarantee the finite-time stability of the sliding surface. Hence, the closed-loop system would be stable in the presence of hard non-linearities and time-varying disturbances. The performance of the proposed approach was assessed in using a simulation study of two numerical examples. The obtained results and comparison with a conventional method confirmed the benefits of the suggested approach. © 2022 The Authors. IET control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of engineering and Technology.

关键词： Closed loop systems

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Deep Convolutional Neural Networks for Real-Time Human Detection and Tracking on UAVs Embedded Systems

Deep Convolutional Neural Networks for Real-Time Human Detec...

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Mediterranean Conference on control and Automation (MED)

作者： Trandafir-Liviu Serghei Petrișor Valentin Pârvu Mădălina-Oana Serghei Dan Popescu Loretta Ichim Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania Faculty of Aerospace Engineering University Politehnica of Bucharest Bucharest Romania

Human detection for critical missions with unmanned aerial vehicle (UAV) support becomes more and more important in the actual context when tension at borders builds up for an increasing number of countries. Although convolutional neural networks are continuously evolving, the required computational resources pose a great problem when implemented on portable embedded systems such as UAVs, with limited processing power and autonomy. This demand becomes even more drastic when running real-time human detection and tracking. This paper proposes an improved implementation of the YOLOv.7, trained on a custom dataset, for real-time human detection and tracking with confidence scores above 80% on NVIDIA Jetson TX2 neural processing unit equipped on DJI Matrice 100 UAV. The authors created a YOLOv.7 model running independently on an embedded system for real-time human detection and tracking.

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Person Detection and Tracking Using UAV and Neural Networks

Person Detection and Tracking Using UAV and Neural Networks

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Mediterranean Conference on control and Automation (MED)

作者： Andrei-Stelian Stan Loretta Ichim Valentin-Petrisor Parvu Dan Popescu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania Faculty of Aerospace Engineering University Politehnica of Bucharest Bucharest Romania

With the recent advancements in drone technology, there has been an increase in the development of human detection and tracking techniques for various applications, especially near borders. In this research, we propose methods to enhance people detection performance in diverse outdoor scenarios. Our dataset design includes a wide range of lighting and color changes, different target distances, angles, and postures. The experimental data consists of images taken in various environmental situations, such as changing the drone’s flight height and capturing pictures in intensive light. To evaluate the performance of our proposed method, we enhanced the generic YOLOv5 model using the gathered data, and calculated key performance indicators, including loss functions, recall, accuracy, and mAP50. We compared the performance of our enhanced model against the standard YOLOv5 model and its versions on the same testing set.

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MPPT techniques application and comparison for photovoltaic panels 23

MPPT techniques application and comparison for photovoltaic ...

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

作者： Dobrea, Marius-Alexandru Arghira, Nicoleta Vasluianu, Mihaela Neculoiu, Giorgian Moldoveanu, Ana-Maria Cristiana University POLITEHNICA of Bucharest Faculty of Automatic Control and Computer Science Romania Technical University of Civil Engineering Faculty of Hidrotechnics Bucharest Romania

ISBN: (纸本)9781665439398

Photovoltaic (PV) panel modelling and control is very important in renewable energy systems. Due to it variability, PV panel generation power should be maximized for the given climate conditions. This paper considers three Maximum Power Point Tracking (MPPT) algorithms: Perturb Observe, Incremental Conductance and Fuzzy Logic. After a clear description for each algorithm, modelling, testing and validation is conducted on real experimental data for a 250W PV panel. Over one day period, a comparison between the 3 control MPPT algorithms show that Perturb Observe gives the best results, close to Incremental Conductance algorithm application. © 2021 IEEE.

关键词： Fuzzy logic

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