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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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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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Transformer-based spectro-temporal fusion for Sentinel-2 super-resolution 30

Transformer-based spectro-temporal fusion for Sentinel-2 sup...

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30th International Conference on Systems, Signals and Image Processing, IWSSIP 2023

作者： Pogodzinski, Bartlomiej Tarasiewicz, Tomasz Kawulok, Michal Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland

ISBN: (纸本)9798350337297

Multi-image super-resolution consists in fusing multiple images of the same scene to generate an image of higher spatial resolution. Recently, it has been demonstrated that for remotely sensed multispectral Sentine1-2 images, fusion performed in both spectral and temporal dimensions improves the reconstruction quality. However, the deep networks elaborated for this purpose are quite large and influence of the input data is difficult to interpret. In this paper, we show how to exploit transformer-based image fusion to reduce the number of trainable parameters by 30% and allow for increased interpretability with means of attention rollout. The reported experimental results performed over simulated and real-world data indicate that this does not affect the reconstruction quality, while at the same time the visualization tools may help in developing techniques for input data selection and preprocessing. © 2023 IEEE.

关键词： Image fusion

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FUSION-BASED ALGORITHM FOR X-RAY PHASE CONTRAST IMAGING TECHNIQUES

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2024年第3期86卷 157-176页

作者： Rasinar, Cezara Safca, Nicoleta Cotorceanu, Elena Ciobanu, Ionut Stefanoiu, Dan Faculty of Automatic Control and Computer Science National University of Science and Technology POLITEHNICA Bucharest Romania Magurele Romania National University of Science and Technology POLITEHNICA Bucharest Romania Faculty of Chemical Engineering and Biotechnologies National University of Science and Technology POLITEHNICA Bucharest Romania

Phase Contrast X-ray Imaging represents a technique that has shown remarkable potential in the research field, by providing better visualization of soft tissue, high-contrast images, and high spatial resolution. In the phase contrast imaging technique, the extraction of the three images represented by attenuation, differential phase contrast, and dark-field contrast is essential, providing, in a specific way, information about the nature of the analyzed tissue. This paper introduces a new method based on the three acquired images merging while adjusting the weighting factors, aiming to identify the interest object and to extract the information provided by each contrast channel. In this regard, a fusion-based algorithm was applied to images acquired, using a 5.66 m long Interferometer Talbot-Lau with ultrahigh sensitivity of 0.84 µradians and mean energy of 30 keV. The obtained results are quite promising, as shown in the end of the article. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Interferometers

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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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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 Multi-object Tracking Using YOLOv8 and SORT on a SoC FPGA 21st

Real-Time Multi-object Tracking Using YOLOv8 and SORT on a...

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21st International Symposium on Applied Reconfigurable Computing, ARC 2025

作者： Danilowicz, Michal Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031879944

Multi-object tracking (MOT) is one of the most important problems in computer vision and a key component of any vision-based perception system used in advanced autonomous mobile robotics. Therefore, its implementation on low-power and real-time embedded platforms is highly desirable. Modern MOT algorithms should be able to track objects of a given class (e.g. people or vehicles). In addition, the number of objects to be tracked is not known in advance, and they may appear and disappear at any time, as well as be obscured. For these reasons, the most popular and successful approaches have recently been based on the tracking paradigm. Therefore, the presence of a high quality object detector is essential, which in practice accounts for the vast majority of the computational and memory complexity of the whole MOT system. In this paper, we propose an FPGA (Field-Programmable Gate Array) implementation of an embedded MOT system based on a quantized YOLOv8 detector and the SORT (Simple Online Realtime Tracker) tracker. We use a modified version of the FINN framework to utilize external memory for model parameters and to support operations necessary required by YOLOv8. We discuss the evaluation of detection and tracking performance using the COCO and MOT15 datasets, where we achieve 0.21 mAP and 38.9 MOTA respectively. As the computational platform, we use an MPSoC system (Zynq UltraScale+ device from AMD/Xilinx) where the detector is deployed in reprogrammable logic and the tracking algorithm is implemented in the processor system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： System-on-chip

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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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Ant Colony Optimization Algorithm for Finding the Maximum Number of d-Size Cliques in a Graph with Not All m Edges between Its d Parts 18th

Ant Colony Optimization Algorithm for Finding the Maximum Nu...

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Dependable computer Systems and Networks - Proceedings of the Eighteenth International Conference on Dependability of computer Systems DepCoS-RELCOMEX

作者： Schiff, Krzysztof Department of Automatic Control and Computer Science Cracow University of Technology Cracow31-155 Poland

ISBN: (纸本)9783031377198

A graph with m vertices in each of its d sections is a d-partite graph. In sections of a d-partite graph, the vertices are not connected by any edges. Each pair of vertices from different sections is always connected by an edge. If in a d-partite graph each section has m vertices, then such a graph can be divided into m d-vertex cliques if it has all edges between each pair of vertices from different sections. If in a graph with m vertices in each section there are no edges between each pair of vertices from different sections of the graph, then such a graph cannot be divided into m cliques. Such a graph can be easily divided into cliques, but their number does not have to be the maximum number of cliques into which such a graph can be divided. So this article deals with the problem of how to divide such a graph into cliques so that their number is the maximum number of cliques. For this purpose ant algorithms without and with two different dynamic desire function were used. The achieved results were compared and discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Ant colony optimization

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Partitioning of an M-Part Weighted Graph with N Vertices in Each Part into N Cliques with M Vertices and the Total Minimum Sum of Their Edges Weights Using Ant Algorithms 18th

Partitioning of an M-Part Weighted Graph with N Vertices in ...

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Dependable computer Systems and Networks - Proceedings of the Eighteenth International Conference on Dependability of computer Systems DepCoS-RELCOMEX

作者： Schiff, Krzysztof Department of Automatic Control and Computer Science Cracow University of Technology Cracow31-155 Poland

ISBN: (纸本)9783031377198

An m-part weighted graph with n vertices in each of its parts is used for tracking objects in multi-camera vision systems. This problem is called: The General Maximum Minimal Clique Problem. Different ant colony optimisation algorithms are presented to solve this problem. New dynamic desire functions are proposed and the results of their influence on the obtained total sum of the weight of cliques are presented. Thus the best dynamic desire functions were determined, which were determined to be better than the existing desire functions in terms of the obtained minimum sum of weights of all cliques. This problem occurs in the area of object tracking on film frames in cameras. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

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