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Search results for: SYSTEM TESTING , SENSITIVITY , COMPUTATIONAL MODELING , NEURAL NETWORKS , OBJECT DETECTION , DISTORTION , DATA MODELS
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Coastline change-detection method using remote sensing satellite observation data
PublicationCoastal zones are not only the fundaments for local economics based on trade, shipping and transport services, but also a source of food, energy and resources. Apart from offering diverse opportunities for recreation and tourism, coastal zones provide protection against storms and other meteorological disturbances. Environmental information is also essential because of the direct influence on a country’s maritime zones, which are...
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System of breath collection and analysis for diseases detection
PublicationCollection and study of composition of the exhaled air is now intensively investigated to develop non-invasive medical diagnostics based on presence of metabolic compounds in the exhaled air. The process of collecting and processing of the exhaled air must fulfill relevant conditions to achieve satisfactory results. The paper presents the system of collecting samples of exhaled breath and the proposed methods of its analysis, using...
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An automatic system for identification of random telegraph signal (RTS) noise in noise signals
PublicationIn the paper the automatic and universal system for identification of Random Telegraph Signal (RTS) noise as a non-Gaussian component of the inherent noise signal of semiconductor devices is presented. The system for data acquisition and processing is described. Histograms of the instantaneous values of the noise signals are calculated as the basis for analysis of the noise signal to determine the number of local maxima of histograms...
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Simulation of Direct-Sequence Spread Spectrum Data Transmission System for Reliable Underwater Acoustic Communications
PublicationUnderwater acoustic communication (UAC) system designers tend to transmit as much information as possible, per unit of time, at as low as possible error rate. It is a particularly difficult task in a shallow underwater channel in which the signal suffers from strong time dispersion due to multipath propagation and refraction phenomena. The direct-sequence spread spectrum technique (DSSS) applied successfully in the latest standards...
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Aerodynamic excitations generated in turbine shroud clearance determined bymeans of neural networks
PublicationSiły aerodynamiczne generowane w uszczelnieniach turbinowych z reguły opisywane są modelem liniowym. Przy dużych drganiach wirnika sposób ten daje niezbyt dokładne wyniki. Zaproponowano wykorzystanie sieci neuronowych do określania sił ciśnieniowych powstających w uszczelnieniu. Wyniki porównano z badaniami eksperymentalnymi.
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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Introductory modeling for decision-making using AMPL
e-Learning CoursesIntroductory modeling for decision-making using AMPL
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Modeling projects for decision-making using AMPL
e-Learning CoursesModeling projects for decision-making using AMPL
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Recent Developments in Data-Assisted Modeling of Flexible Proteins
PublicationMany proteins can fold into well-defined conformations. However, intrinsically-disordered proteins (IDPs) do not possess a defined structure. Moreover, folded multi-domain proteins often digress into alternative conformations. Collectively, the conformational dynamics enables these proteins to fulfill specific functions. Thus, most experimental observables are averaged over the conformations that constitute an ensemble. In this...
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M-Split Estimation in Laser Scanning Data Modeling
PublicationPublikacja traktuje o wykorzystaniu estymacji M-Split do modelowania danych pozyskanych w wyniku skaningu laserowego. Autorzy prezentują rozwiązanie w oparciu o detekcję krawędzi dwóch płaszczyzn.
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The automation of test stand for engine cooling system testing
PublicationW rozdziale przedstawiono budowę stanowiska do badań układu chłodzenia silnika samochodowego typu M111920. Układ był wyposażony w obwód podgrzewania paliwa gazowego i układ akumulacji ciepła. Stanowisko wyposażono w liczne termopary do pomiaru temperatur płynów i części metalowych silnika. Ważnym opracowanym zagadnieniem było rejestrowanie wielu pomiarów w czasie rzeczywistym, do czego użyto sieci transmisji danych CAN.
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A method of self-testing of analog circuits based on fully differential op-amps with theTCBF classifier
PublicationA new approach of self-testing of analog circuits based on fully differential op-amps of mixed-signal systems controlled by microcontrollers is presented. It consists of a measurement procedure and a fault diagnosis procedure. We measure voltage samples of a time response of a tested circuit on a stimulation of a unit step function given at the common-mode reference voltage input of the op-amp. The fault detection and fault localization...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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System pomiarowy do sprawdzania dokładności elementów układu pomiaru prądu. Measuring system for testing the current measuring system components
PublicationPrzedstawiono badany układ pomiarowy składający się z przetworników pomiaro-wych, filtrów, komputera z kartą akwizycji danych. Zaprezentowano skompute-ryzowany system pomiarowy do badania niepewności pomiaru układem pomiarowym.Podano wyniki badań.
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Integration Data Model of the Bathymetric Monitoring System for Shallow Waterbodies Using UAV and USV Platforms
PublicationChanges in the seafloor relief are particularly noticeable in shallow waterbodies (at depths up to several metres), where they are of significance for human safety and environmental protection, as well as for which the highest measurement accuracy is required. The aim of this publication is to present the integration data model of the bathymetric monitoring system for shallow waterbodies using Unmanned Aerial Vehicles (UAV) and...
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Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer
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ANALYSIS OF EFFECTIVENESS AND COMPUTATIONAL COMPLEXITY OF TREND REMOVAL METHODS
PublicationThe paper presents a method of processing measurement data due to remove slowly varying component of the trend occurring in the recorded waveforms. Comparison of computational complexity and trend removal efficiency between some commonly used methods is presented. The impact of these procedures on probability distribution and power spectral density is shown. Effectiveness and computational complexity of these methods depend essentially...
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Testing HIADAC high impedance analyzer in Trento University laboratory on "unknown" object using 2-wire probe
Open Research DataThe dataset presents impedance spectrum of "black-box" object with interesting phase characteristics. This object was used to test high-impedance analyzer for diagnostic of anticorossion coatings (HIADAC) realized in the frame of Eureka project E!3174. The impedance spectrum frequency range (1 Hz – 100 kHz) was selected in order to test the whole measureement...
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Application of the Msplitmethod for filtering airborne laser scanning data-sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Open Research DataMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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Results of modeling of pharmaceuticals mixtures toxicity with deviation ratio and best-fit functions models using Aliivibrio fischeri bacterium as model organism
Open Research DataThe research was concerned with verifying the impact of mixtures of nine pharmaceuticals against a selected organism, i.e., the bacterium Aliivibrio fischeri. A. fisheri is used as a model organism in the monitoring of acute toxicity in environmental and reference samples in Microtox® systems. Tested pharmaceuticals, namely: diclofenac (sodium salt),...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublicationIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublicationThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging
PublicationUtilization of fast surrogate models has become a viable alternative to direct handling of fullwave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques...
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Modeling of pharmaceuticals mixtures toxicity with deviation ratio and best-fit functions models
PublicationThe present study deals with assessment of ecotoxicological parameters of 9 drugs (diclofenac (sodium salt), oxytetracycline hydrochloride, fluoxetine hydrochloride, chloramphenicol, ketoprofen, progesterone, estrone, androstenedione and gemfibrozil), present in the environmental compartments at specific concentration levels, and theirmutual combinations by couples against Microtox® and XenoScreen YES/YAS® bioassays. As the quantitative...
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Numerical Modeling of Hydrosystems 2024/2025
e-Learning CoursesKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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Numerical Modeling of Hydrosystems 2024/2025
e-Learning CoursesKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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Numerical Modeling of Hydrosystems 2023/2024
e-Learning CoursesKurs do przedmiotu NUMERICAL MODELING OF HYDROSYSTEMS Specjalność: Environmental Engineering (WILiŚ), II stopnia, stacjonarne dr hab. inż. Michał Szydłowski, prof. PG
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A review on analytical models of brushless permanent magnet machines
PublicationThis study provides an in-depth investigation of the use of analytical and numerical methods in analyzing electrical machines. Although numerical models such as the finite-element method (FEM) can handle complex geometries and saturation effects, they have significant computational burdens, are time-consuming, and are inflexible when it comes to changing machine geometries or input values. Analytical models based on magnetic equivalent...
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Reduction of Computational Complexity in Simulations of the Flow Process in Transmission Pipelines
PublicationThe paper addresses the problem of computational efficiency of the pipe-flow model used in leak detection and identification systems. Analysis of the model brings attention to its specific structure, where all matrices are sparse. With certain rearrangements, the model can be reduced to a set of equations with tridiagonal matrices. Such equations can be solved using the Thomas algorithm. This method provides almost the same values...
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Low-Cost Behavioral Modeling of Antennas by Dimensionality Reduction and Domain Confinement
PublicationBehavioral modeling has been rising in importance in modern antenna design. It is primarily employed to diminish the computational cost of procedures involving massive full-wave electromagnetic (EM) simulations. Cheaper alternative offer surrogate models, yet, setting up data-driven surrogates is impeded by, among others, the curse of dimensionality. This article introduces a novel approach to reduced-cost surrogate modeling of...
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Place attachment, place identity, and visual pollution sensitivity.
Open Research DataThe data include individual responses on the following scales (1) place attachment, (2) place identity, and (3) visual pollution sensitivity. Each line represents responses obtained from one participant and his or her demographic characteristics. like gender, age, and education level.
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublicationThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Autoencoder application for anomaly detection in power consumption of lighting systems
PublicationDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Asynchronous Method of Simultaneous Object Position and Orientation Estimation with Two Transmitters
PublicationThis paper proposes an object location method for all types of applications, including the Internet of Things. The proposed method enables estimations of the position and orientation of an object on a plane or in space, especially during motion, by means of location signals transmitted simultaneously from two transmitters placed on the object at a known distance from each other. A mathematical analysis of the proposed method and...
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Modeling and Strength Calculations of Parts Made Using 3D Printing Technology and Mounted in a Custom-Made Lower Limb Exoskeleton
PublicationThis study is focused on the application of 3D-printed elements and conventional elements to create a prototype of a custom-made exoskeleton for lower limb rehabilitation. The 3D-printed elements were produced by using Fused Deposition Modeling technology and acrylonitrile butadiene styrene (ABS) material. The scope of this work involved the design and construction of an exoskeleton, experimental testing of the ABS material and...
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Safety assessment of ships in critical conditions using a knowledge-based system for design and neural network system
PublicationW pracy opisano wybrane elementy metody oceny bezpieczeństwa statków w stanie uszkodzonym, ukierunkowanej na ocenę osiągów statku i ocenę ryzyka. Metoda analizy osiągów i zachowania się statku w stanie uszkodzonym została wykorzystana do oceny charakterystyk hydromechanicznych statku uszkodzonego. Do oceny ryzyka wykorzystano elementy metodyki Formalnej Oceny Bezpieczeństwa. System ekspertowy został wykorzystany do analziy podziału...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublicationIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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VISUALIZATION OF SCANTER AND ARPA RADAR DATA IN THE DISTRIBUTED TELEINFORMATION SYSTEM FOR THE BORDER GUARD
PublicationMonitoring of country maritime border is an important task of the Border Guard. This activity can be enhanced with the use of the technology enabling gathering information from distributed sources, processing of that information and its visualization. The paper presents the next stage of development of the STRADAR project (Streaming of real-time data transmission in distributed dispatching and teleinformation systems of the Border...
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Optimal shape design of multi-element trawl-doors using local surrogate models
PublicationTrawl-doors have a large influence on the fuel consumption of fishing vessels. Design and optimiza-tion of trawl-doors using computational models are a key factor in minimizing the fuel consump-tion. This paper presents an optimization algorithm for the shape design of trawl-door shapes using computational fluid dynamic (CFD) models. Accurate CFD models are computationally expensive. Therefore, the direct use of traditional optimization...
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Towards More Realistic Probabilistic Models for Data Structures: The External Path Length in Tries under the Markov Model
PublicationTries are among the most versatile and widely used data structures on words. They are pertinent to the (internal) structure of (stored) words and several splitting procedures used in diverse contexts ranging from document taxonomy to IP addresses lookup, from data compression (i.e., Lempel- Ziv'77 scheme) to dynamic hashing, from partial-match queries to speech recognition, from leader election algorithms to distributed hashing...
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Kriging Models for Microwave Filters
PublicationSurrogate modeling of microwave filters’ response is discussed. In particular, kriging is used to model either the scattering parameters of the filter or the rational representation of the filter’s characteristics. Surrogate models for these two variants of kriging are validated in solving a microwave filter optimization problem. A clear advantage of surrogate models based on the rational representation over the models based on scattering...
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Graph security testing
PublicationSet S ⊂ V is called secure set iff ∀ X ⊂ S | N [ X ] ∩ S | ≥ | N ( X ) \ S | [3]. That means that every subset of a secure set has at least as many friends (neighbour vertices in S) as enemies (neighbour vertices outside S) and will be defended in case of attack. Problem of determining if given set is secure is co −NP -complete, there is no efficient algorithm solving it [3]. Property testers are algorithms that distinguish inputs...
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MEMS based voice message system for elevators
PublicationW artykule przedstawiono implementację systemu głosowych komunikatów w windach. Prezentowany system posiada unikalną cechę polegającą na tym, że do działania nie potrzebuje połączenia z systemem sterującym windy. Zasilany z baterii lub akumulatorów może być zamontowany w ścianie windy, wymaga tylko prostej kalibracji. System oparty jest na akcelerometrach MEMS dokonujących pomiaru przeciążeń w kabinie windy. W artykule przedstawiono...
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Rafał Leszczyna dr hab. inż.
PeopleDr hab. Rafal Leszczyna is an associate professor at Gdansk University of Technology, Faculty of Management and Economics. He holds the M.Sc. degrees of Computer Science and Business Management. In December, 2006 he earned a Ph.D. in Computer Science, specialisation - Computer Security at the Faculty of Electronics, Telecommunications and Informatics of Gdansk University of Technology. Between 2004 and 2008 he worked in the European...
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Self-Testing of Analog Parts Terminated by ADCs Based on Multiple Sampling of Time Responses
PublicationA new approach for self-testing of analog parts terminated by analog-to-digital converters in mixed-signal electronic microsystems controlled by microcontrollers is presented. It is based upon a new fault diagnosis method using a transformation of the set of voltage samples of the time response of a tested analog part to a square impulse into localization curves placed in a multidimensional measurement space. The method can be used...
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Grand Challenges on the Theory of Modeling and Simulation
PublicationModeling & Simulation (M&S) is used in many different fields and has made many significant contributions. As a field in its own right, there have been many advances in methodologies and technologies. In 2002 a workshop was held in Dagstuhl, Germany, to reflect on the grand challenges facing M&S. Ten years on, a series of M& S Grand Challenge activities are marking a decade of progress and are providing an opportunity to reflect...