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International Conference on System Theory, control, and Computing (ICSTCC)

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

ISBN: (数字)9781728198095

ISBN: (纸本)9781728198101

The classification and segmentation of small region of interest from ground images is important in many domains: flood detection and evaluation, crop monitoring, environment monitoring, defense, etc. The paper uses a fusion scheme to classify small regions from remote images in four classes (different for satellite and unmanned aerial vehicle -UAVs). As novelty, two neural networks, considered as primary classifiers, AlexNet and Perceptron (the last based on ten textural image features) are combined in a convolutional scheme to make up the global classifier. The weights from the convolutional layer are calculated according to the performances of the primary classifiers in a validation phase. Two datasets with different images are used for classifier learning, validation, and testing, one consisting in images from satellite and another consisting in images from UAVs. The global system performances were better than those of the individual neural network (system components) accuracies.

关键词： Neural networks Satellites Unmanned aerial vehicles Image segmentation Testing Feature extraction Monitoring

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Condition attributes, properties of decision rules, and discretisation: Analysis of relations and dependencies

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Procedia computer science 2021年 192卷 3922-3931页

作者： Beata Zielosko Urszula Stańczyk University of Silesia in Katowice Będzińska 39 41-200 Sosnowiec Poland Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A 44-100 Gliwice Poland

When mining of input data is focused on rule induction, knowledge, discovered in exploration of existing patterns, is stored in combinations of certain conditions on attributes included in rule premises, leading to specific decisions. Through their properties, such as lengths, supports, cardinalities of rule sets, inferred rules characterise relations detected among variables. The paper presents research dedicated to analysis of these dependencies, considered in the context of various discretisation methods applied to the input data from stylometric domain. For induction of decision rules from data, Classical Rough Set Approach was employed. Next, based on rule properties, several factors were proposed and evaluated, reflecting characteristics of available condition attributes. They allowed to observe how variables and rule sets changed depending on applied discretisation algorithms.

关键词： Discretisation Decision rule Rule length Support Attribute Rough Sets

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An exponential stability test for a messenger rna–micro rna ode model

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 11-16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 obtain a numerically tractable test (sufficient condition) for the exponential stability of the unique positive equilibrium point of an ODE system. The result (Theorem 3.1) is based on Lyapunov theory and Linear Ma-trix Inequalities techniques. The ODE model is related to the messengerRNA-microRNA interaction. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： RNA

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The Search for Assembly Line Balance Oriented on the Allocation of Quality control Points

The Search for Assembly Line Balance Oriented on the Allocat...

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International Conference on control, Automation and Robotics (ICCAR)

作者： Sara Bysko Jolanta Krystek Szymon Bysko Krzysztof Majchrowicz Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland

ISBN: (数字)9781728161396

ISBN: (纸本)9781728161402

In the paper important aspects of the proper use of quality inspection in production process were presented. The paper deals with the problem of assembly line balance analysis taking into account occurrence of quality checkpoints. It is very important for producers, because the earlier the detection of a defect, the greater the possibility of reducing the costs of manufacturing a faulty product. In order to present the real assembly line balancing problem taking into account occurrence of checkpoints in strictly defined places, simplified process of USB flash drive production was analyzed. The assembly line balancing was performed and the indicators evaluating quality of the solutions were obtained. The calculations were made for different conditions regarding the type and location of quality inspections. Approaches like classical assembly line balancing without and with quality inspection, and fragmentary assembly line balancing with quality inspection were verified. All results and discussion are presented in the paper.

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Skinny: A Lightweight U-Net For Skin Detection And Segmentation

Skinny: A Lightweight U-Net For Skin Detection And Segmentat...

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IEEE International Conference on Image Processing

作者： Tomasz Tarasiewicz Jakub Nalepa Michal Kawulok Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

The use of deep-learned features has recently allowed for improving the performance of skin detection and segmentation. In particular, fully-convolutional U-Nets, proposed for segmenting medical images, occurred to be extremely effective here. However, the spatial context, which is rather narrow for U-Nets, may be more important for skin segmentation than for segmenting other image structures. We propose Skinny-a lightweight U-Net-based architecture that extends the range of multi-scale analysis. The results of our experiments indicate that Skinny outperforms the state-of-the-art skin segmentation techniques, rendering the F-score of 92.3% and 94.9% for the ECU and HGR datasets, respectively.

关键词： Skin Image segmentation Feature extraction Training Bayes methods Kernel computer architecture

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Implementing a solution for monitoring SLA violations in Cloud 6

Implementing a solution for monitoring SLA violations in Clo...

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6th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Application, DependSys 2020

作者： Floricu, Andreea Buzatu, Razvan Negru, Catalin Pop, Florin Castiglione, Aniello University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Romania National Institute for Research and Development in Informatics-ICI Bucharest Romania University of Naples Dipartimento di Scienze e Tecnologie Parthenope Italy

ISBN: (纸本)9781728176512

Over time, the increased use of the Internet has led to the widespread adoption of web and cloud applications. More and more applications are coming to the aid of persons or companies to make their work easier. A Service Level Agreement (SLA) gathers information about all contracted services and their expected reliability in a single document and plays a very important role when it comes to IT (Information Technology) sales. This paper examines the extent to which the SLA is complied with through a series of specific reports and graphs. The usefulness of this application is to get an overview of web services to know the frequency of situations unforeseen and the moments when they deviated from the operation in good conditions. © 2020 IEEE.

关键词： Web services

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TextBenDS: A generic textual data benchmark for distributed systems

arXiv

引用

arXiv 2021年

作者： Truicǎ, Ciprian-Octavian Apostol, Elena Darmont, Jérôme Assent, Ira Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania Department of Computer Science Aarhus University Aarhus Denmark Université de Lyon ERIC Lyon 2 EA 3083 France DIGIT Department of Computer Science Aarhus University Denmark

Extracting top-k keywords and documents using weighting schemes are popular techniques employed in text mining and machine learning for different analysis and retrieval tasks. The weights are usually computed in the data preprocessing step, as they are costly to update and keep track of all the modifications performed on the dataset. Furthermore, computation errors are introduced when analyzing only subsets of the dataset. Therefore, in a Big Data context, it is crucial to lower the runtime of computing weighting schemes, without hindering the analysis process and the accuracy of the machine learning algorithms. To address this requirement for the task of top-k keywords and documents, it is customary to design benchmarks that compare weighting schemes within various configurations of distributed frameworks and database management systems. Thus, we propose a generic document-oriented benchmark for storing textual data and constructing weighting schemes (TextBenDS). Our benchmark offers a generic data model designed with a multidimensional approach for storing text documents. We also propose using aggregation queries with various complexities and selectivities for constructing term weighting schemes, that are utilized in extracting top-k keywords and documents. We evaluate the computing performance of the queries on several distributed environments set within the Apache Hadoop ecosystem. Our experimental results provide interesting insights. As an example, MongoDB proves to have the best overall performance, while Spark's execution time remains almost the same, regardless of the weighting schemes. Copyright © 2021, The Authors. All rights reserved.

关键词： Machine learning

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BrightBox — A rough set based technology for diagnosing mistakes of machine learning models

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Applied Soft Computing 2023年 141卷

作者： Janusz, Andrzej Zalewska, Andżelika Wawrowski, Lukasz Biczyk, Piotr Ludziejewski, Jan Sikora, Marek Ślęzak, Dominik QED Software sp. z o.o. Mazowiecka 11/49 Warsaw00-052 Poland Institute of Informatics University of Warsaw Banacha 2 Warsaw02-097 Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland Research Network Lukasiewicz – Institute of Innovative Technologies EMAG ul. Leopolda 31 Katowice40–189 Poland

The paper presents a novel approach to investigating mistakes in machine learning model operations. The considered approach is the basis for BrightBox – a diagnostic technology that can be used for analyzing prediction models and identifying model- and data-related issues. The idea is to generate surrogate rough set-based models from data that approximate decisions made by monitored black-box models. Such approximators are used to compute neighborhoods of instances that undergo the diagnostic process — the neighborhoods consist of historical instances that were processed in a similar way by rough set-based models. The diagnostic process is then based on the analysis of mistakes registered in such neighborhoods. The experiments performed on real-world data sets confirm that such analysis can provide us with efficient and valid insights about the reasons for the poor performance of machine learning models. © 2023

关键词： Machine learning

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Future Flight Deck Design: Implementation of a Touchscreen as Flight Inceptor for Single Pilot Operation

SSRN

引用

SSRN 2023年

作者： Li, Wen-Chin Wang, Yifan Korek, Wojciech Tomasz Braithwaite, Graham Safety and Accident Investigation Centre SATM Cranfield University Cranfield United Kingdom Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Aerospace Integration Research Centre SATM Cranfield University Cranfield United Kingdom Safety and Accident Investigation Center Cranfield University Martell House Cranfield BedfordshireMK43 0TR United Kingdom

There is a trend leading to progressively "de-crewing" aircraft by implementing innovative technology on the flight deck. Currently, touchscreens can combine the input and output functions of different systems. However, it does not yet serve as an inceptor to replace the sidestick or control column for aircraft manoeuvres. The aim of this study is to examine the potential of a touchscreen as a flight inceptor compared with a traditional sidestick and gamepad. This research recruited 51 pilots who interacted with three inceptors for both an instrument landing with disturbance and one without disturbance using the Future System Simulator. The findings demonstrated that both system usability and pilots’ situation awareness of touchscreen inceptor were significantly inferior to those of traditional sidesticks and gamepads. Compared to the sidestick and gamepad, the touchscreen provided a poorer situation awareness with the highest supply and demand. In addition, the performance of all inceptors was significantly influenced by disturbance. There is still a long way to go for certification of a touchscreen as an inceptor on the future flight deck. This research showed that even though the touchscreen inceptor scored the lowest on both SUS and SART, the majority of pilots agreed that the touchscreen inceptor provided a better attentional supply in challenging disturbance circumstances. There is a potential that the emerging touchscreen as an inceptor may develop further along with human-system integration flight deck design. It will enable a single pilot to safely operate a highly automated aircraft in the future. © 2023, The Authors. All rights reserved.

关键词： Human computer interaction

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Development of a Realistic Crowd Simulation Environment for Fine-grained Validation of People Tracking Methods

arXiv

引用

arXiv 2023年

作者： Foszner, Pawel Szczęsna, Agnieszka Ciampi, Luca Messina, Nicola Cygan, Adam Bizon, Bartosz Cogiel, Michal Golba, Dominik Macioszek, Elżbieta Staniszewski, Michal Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Institute of Information Science and Technologies National Research Council Pisa Italy QSystems.pro sp. z o.o. Mochnackiego 34 Bytom41-907 Poland Blees sp. z o.o. Zygmunta Starego 24a/10 Gliwice44-100 Poland Department of Transport Systems Traffic Engineering and Logistics Faculty of Transport and Aviation Engineering Silesian University of Technology Katowice Poland

Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or other sensors). The use of simulation tools can significantly reduce the time required to generate scenario-specific crowd datasets, facilitate data-driven research, and next build functional machine learning models. The main goal of this work was to develop an extension of crowd simulation (named CrowdSim2) and prove its usability in the application of people-tracking algorithms. The simulator is developed using the very popular Unity 3D engine with particular emphasis on the aspects of realism in the environment, weather conditions, traffic, and the movement and models of individual agents. Finally, three methods of tracking were used to validate generated dataset: IOU-Tracker, Deep-Sort, and Deep-TAMA. © 2023, CC BY.

关键词： Deep learning

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