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

作者： Gigi Tăbăcaru Simona Moldovanu Marian Barbu Department of Automatic Control and Electrical Engineering Faculty of Automation Computers Electrical Engineering and Electronics "Dunarea de Jos" University of Galati Galati Romania Computer Science and Information Technology Faculty of Automation Computers Electrical Engineering and Electronics The Modelling & Simulation Laboratory "Dunarea de Jos" University of Galati Galati Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

The skin lesion can be thought of as a biological system, so the morpho-granulometry of significant color clusters found in skin lesions is one of the elements that reproduce in a natural way the structure of the lesion, this novelty is highlighted in this study. Important features of skin lesions can be modulated by fusing neural networks (NN) and machine learning (ML). By choosing the nevus and melanoma classes, the primary goal was accomplished, and three databases were used to test the methodology. The characteristics based on morpho-granulometry allowed for the identification of microstructure within the images, which can be very helpful in characterizing the biological system. Based on random forest (RF) and extreme gradient boosting (XGboost) classifiers, this work aimed to improve the classification performance of important feature selection. The selected features from three free image databases with three NNs were classified. In a binary classification of nevus vs. melanoma, the results showed that the pattern recognition neural network (PRNN), according to the PH2 database, provided an accuracy of 0.923 and an F1-score of 0.876. The classification is interpretable if it is not validated. In our study, the best results were verified with a logistic regression (LR) classifier.

关键词： Accuracy Recurrent neural networks Image color analysis Melanoma Biological systems Artificial neural networks Feature extraction Skin Lesions Classification tree analysis

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MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-Resolution

arXiv

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arXiv 2022年

作者： Kowaleczko, Pawel Tarasiewicz, Tomasz Ziaja, Maciej Kostrzewa, Daniel Nalepa, Jakub Rokita, Przemyslaw Kawulok, Michal KP Labs Gliwice Poland Warsaw University of Technology Warsaw Poland Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland

Insufficient image spatial resolution is a serious limitation in many practical scenarios, especially when acquiring images at a finer scale is infeasible or brings higher costs. This is inherent to remote sensing, including Sentinel-2 satellite images that are available free of charge at a high revisit frequency, but whose spatial resolution is limited to 10 m ground sampling distance. The resolution can be increased with super-resolution algorithms, in particular when performed from multiple images captured at subsequent revisits of a satellite, taking advantage of information fusion that leads to enhanced reconstruction accuracy. One of the obstacles in multi-image super-resolution consists in the scarcity of real-world benchmarks—commonly, simulated data are exploited which do not fully reflect the operating conditions. In this paper, we introduce a new MuS2 benchmark for super-resolving multiple Sentinel-2 images, with WorldView-2 imagery used as the high-resolution reference. Within MuS2, we publish the first end-to-end evaluation procedure for this problem which we expect to help the researchers in advancing the state of the art in multi-image super-resolution. Copyright © 2022, The Authors. All rights reserved.

关键词： Remote sensing

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Cyber-Physical Systems Based Business Models

Cyber-Physical Systems Based Business Models

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IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Eugen Pop Daniela Gî fu Mihnea Alexandru Moisescu Automatics and Industrial Informatics Department Faculty of Automatic Control and Computers University "Politehnica" of Bucharest R&#x0026 D Institute for Automation - IPA SA Romania Institute of Computer Science Romanian Academy &#x2013 Ia&#x0219 i branch Faculty of Computer Science "Alexandru Ioan Cuza" University of Ia&#x0219 i Romania Automatics and Industrial Informatics Department Faculty of Automatic Control and Computers University "Politehnica" of Bucharest Romania

Currently, the use of cyber-physical systems is becoming widespread in various fields, primarily, because they enable many innovative functionalities through their networking. These systems include complex computation elements that interacts with the physical environment through sensors or actuators. Their solutions are based on sharing of hardware equipment and software services, targeting to provide added value proposition for various customers. The research and development in this domain are going on not only in the technical direction, but is also targeting the value creation for customers, in a technical and business-oriented manner. This paper presents a cyber-physical systems-based business model realized through services composition. The service composition framework integrates Web services which can be interconnected and can be accessed by mobile clients through smartphones, on mobile and wireless communications channels. The response time for multiuser requests for services access is evaluated, because it is an important quality of service performance criteria of our e-business model service composition framework. The results are promising.

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Real-time testing of vision-based systems for AGVs with ArUco markers

Real-time testing of vision-based systems for AGVs with ArUc...

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IEEE International Conference on Big Data

作者： Katarzyna Filus Łukasz Sobczak Joanna Domańska Adam Domański Rafał Cupek Polish Academy of Sciences Institute of Theoretical and Applied Informatics Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland

ISBN: (纸本)9781665480468

Automated Ground Vehicles (AGVs) use deep-learning-based vision systems to perceive the surrounding environment and extract relevant information about it. Although deep learning models offer high capabilities, they require large amounts of data to be properly trained and tested. Testing is especially important when off-the-shelf models are used by the AGVs - to examine whether they can meet the demands of complex environments such as the production halls of automated factories. One area of such perception algorithms is object recognition. To test such systems, we propose a solution based on ArUco fiducial markers used for automatic labeling of objects. Our solution can be used to test deep learning systems in real time directly on a robot. Our solution requires minimal interference with the environment and additional infrastructure - the desired objects only need to be marked with a marker printed on a home printer. Therefore, the presented testing procedure can be used for testing of AGVs in real-life environments during a real ride from an actual robot perspective. Data gathered during the online testing can be used for the offline comparison of the accuracy of different deep learning models. Although we focus on the online and offline testing in our study, we also incorporated a marker masking procedure. Therefore, the resulting datasets may also be used for training.

关键词： Deep learning Training Computational modeling Big Data Real-time systems Data models Object recognition

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FQSqueezer: k-mer-based compression of sequencing data (vol 10, 578, 2020)

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SCIENTIFIC REPORTS 2020年第1期10卷 1-9页

作者： Deorowicz, Sebastian Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 44-100 Gliwice Poland. sebastian.deorowicz@polsl.pl.

The amount of data produced by modern sequencing instruments that needs to be stored is huge. Therefore it is not surprising that a lot of work has been done in the field of specialized data compression of FASTQ files. The existing algorithms are, however, still imperfect and the best tools produce quite large archives. We present FQSqueezer, a novel compression algorithm for sequencing data able to process single- and paired-end reads of variable lengths. It is based on the ideas from the famous prediction by partial matching and dynamic Markov coder algorithms known from the general-purpose-compressors world. The compression ratios are often tens of percent better than offered by the state-of-the-art tools. The drawbacks of the proposed method are large memory and time requirements.

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Magnetization Dynamics in Nanofiber Networks 11

Magnetization Dynamics in Nanofiber Networks

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11th IEEE International Conference "Nanomaterials: Applications and Properties", NAP 2021

作者： Blachowicz, Tomasz Steblinski, Pawel Grzybowski, Jacek Ehrmann, Andrea Institute of Physics Center for Science and Education Silesian University of Technology Gliwice Poland Faculty of Electronics and Informatics Koszalin University of Technology Koszalin Poland Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Gliwice Poland Faculty of Engineering and Mathematics Bielefeld University of Applied Sciences Bielefeld Germany

ISBN: (纸本)9781665439077

Magnetic nanofibers are of great interest for applications like data transport and storage as well as in basic research. Especially bent nanofibers, which can unambiguously be produced by electrospinning, show a broad spectrum of possible magnetization reversal processes, depending on bending radius, geometry, magnetic field orientation, etc. Besides these quasistatic processes, dynamic investigations are necessary for investigating data transport properties of magnetic nanofibers. We report on domain wall transport through coupled bent nanowires, forming networks with multiple data inputs and outputs. Our results show diverse phenomena which have to be taken into account during these dynamic processes, such as domain wall instabilities or interference between converging signals, and suggest possible architectures of nanowire-based logics. ©2021 IEEE

关键词： Nanofibers

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Energy, QoS and Security Aware Edge Services 1

引用

2nd International Symposium on Security in computer and Information sciences, EuroCybersec 2021

作者： Gelenbe, Erol Nowak, Mateusz P. Frohlich, Piotr Fiolka, Jerzy Checinski, Jacek Institute of Theoretical and Applied Informatics Polish Academy of Sciences Baltycka 5 Gliwice44-100 Poland LabI3S Universite Cote d’Azur Grand Chateau Nice06103 France Faculty of Automatic Control Electronics and Computer Science The Silesian University of Technology Akademicka 16 Gliwice44-100 Poland

ISBN: (数字)9783031093579

ISBN: (纸本)9783031093562

With the development of communication technologies and the increasing bandwidth of optical fibres and transmission speeds in current 5G and future 6G wireless networks, there is a growing demand for solutions organising traffic in such networks, taking into account both end-to-end transmissions and the possibility of data processing by edge services. The most pressing problems of today’s computer networks are not only bandwidth and transmission delays, but also security and energy consumption, which is becoming increasingly important in today’s climate. This paper presents a solution based on neural networks that organises network traffic taking into account the above criteria - quality of service (QoS), energy consumption and security. © 2022, The Author(s).

关键词： Quality of service

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Trends and Challenges of Sustainable Agriculture in the Iraqi Environment

Trends and Challenges of Sustainable Agriculture in the Iraq...

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2022 IEEE International Conference on Blockchain, Smart Healthcare and Emerging Technologies, SmartBlock4Health 2022

作者： Al-Asadi, Hanan Hussein Goga, Maria Ali, Haider Abdullah Popa, Ramona Cristina Oludele, Awodele University POLITEHNICA of Bucharest Faculty of Automatic Control and Computers Bucharest Romania University of Technology-Iraq Baghdad Iraq Technical University of Civil Engineering of Bucharest UTCB Department for Training of Teaching Personnel Bucharest Romania Madenat Alelem University College Baghdad Iraq Babcock University Computer Science Department Ogun State Nigeria

ISBN: (纸本)9781665460149

The use of Agriculture Intelligent Systems (AISs) in Iraq has become popular among farmers. The greenhouse is a solution for plant growth, which uses an effective microclimate to simulate seasons and to use alternative energy sources like solar, thermal, and photovoltaic systems for microclimate control. Greenhouses are considered a successful solution with developments and achievements in the technology of this field. However, problems like high costs, difficulties in installation and maintenance, or the need for some procedures should be considered. Because Iraq is close to the equator (3669 km), it receives sufficient solar power. It also has large areas available for the building of solar greenhouse systems. The farmers need an affordable and functional smart greenhouse to enable and encourage them to use the environment efficiently. We intend to develop low-cost, accurate, and easy-to-use greenhouse systems controlled by artificial intelligence algorithms. Farmers will be able to control the greenhouse by using simple commands. Machine learning algorithms provide real-time and effective analysis that could support farmers in decision-making and provide relevant data for researchers and policymakers. AISs algorithms can lead to a sustainable and productive agriculture system. The system can be used in Iraq with sufficient government support and subsidy. © 2022 IEEE.

关键词： Intelligent systems

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An Efficient and Secured Energy Management System for Automated Guided Vehicles

An Efficient and Secured Energy Management System for Automa...

引用

IEEE International Conference on Big Data

作者： Jia-Hao Syu Jerry Chun-Wei Lin Dariusz Mrozek Department of Computer Science and Information Engineering National Taiwan University Taiwan Department of Computer Science Electrical Engineering and Mathematical Sciences Western Norway University of Applied Sciences Norway Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland

ISBN: (纸本)9781665480468

In this paper, we propose a Secure Energy Management System (SEMS) with anomaly detection and Q-Learning decision modules for Automated Guided Vehicles (AGV). The anomaly detection module is a multi-task learning network to simultaneously classify suppliers and predict the real supply quantities. The Q-learning decision module can then determine operating reserve and subsidies to manage the energy grid. Experimental results illustrate that the proposed anomaly detection module has an excellent performance in classifying malicious suppliers, excels at shaping supply distribution, and outperforms the existing benchmark systems.

关键词： Q-learning Remotely guided vehicles Big Data Benchmark testing Multitasking Energy management systems Anomaly detection

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Modeling and simulation of a 3 kw photovoltaic system for an autonomous consumer

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

引用

UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2021年第2期83卷 35-46页

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

The paper aims to model and simulate an assembly composed of 12 photovoltaic panels, each with a nominal power of 250W in order to power a consumer. Starting from the monitoring of the parameters of temperature and solar radiation, a comparison was made during a period of one year, between the simulated power and the real measured one, monitored with a power meter. The paper analyzes the particularities between measured and simulated values in both clear sky and shade conditions. The measured data were compared with a data set used for the simulation which resulted in a correlation coefficient of 93%. The modeling and simulation of this set of photovoltaic panels were performed in the Matlab / Simulink environment. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： MATLAB

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