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Wyniki wyszukiwania dla: artificial neural network, gis, diagnosis, machine learning, expert system
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Artificial neural networks as a tool for selecting the parameters of prototypical under sleeper pads produced from recycled rubber granulate
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<title>Recurrent neural network application to image filtering: 2-D Kalman filtering approach</title>
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Modelling of a medium-term dynamics in a shallow tidal sea, based on combined physical and neural network methods
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Izabela Mironowicz dr hab. inż. arch.
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Control system based on the modified multiscalar model for the double fed machine
PublikacjaPrzedstawiono układ sterowania maszyną asynchroniczą dwustronnie zasilaną wykorzystujący zmodyfikowany model multisaklarny. Wprowadzone nielinowe sprzężenia pozwalają na podział systemu na dwa niezależne podukłady. Pododuje to brak zauważalnych sprzężeń przy regulacji mocy czynnej i biernej regulowanej przez kontrolery PI. W układzie wyeliminowano konieczność stosowania kaskadowego połączenia regulatorów. Przedstawiono wyniki symulacji.
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Experimental examination and modification of chip suction system in circular sawing machine
PublikacjaThe article presents the results of experimental examination of the wood chip suction system in the existing sliding table saw before and after its modifi cation. The studies focused on the extraction hood of the mentioned system. The methodical experimental research of the pressure distribution inside the hood during wood chip removal for the selected rotational speed of saw blades of 3500 and 6000 min-1 with a diameter of 300...
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Algorithm for searching out similar ships within expert system of computer aided preliminary design of ship power plant
PublikacjaW pracy zaprezentowano algorytm wyszukiwania statków podobnych zaimplementowany w hybrydowym systemie wspomagania projektowania wstępnego siłowni okrętowej na podstawie nowych funkcji podobieństwa oraz zaadaptowanych z literatury. Do wyszukiwania statków podobnych została zastosowana metoda optymalizacji wielokryterialnej ważonych zysków.
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Raman system for monitoring of dye doping to hybrid polymer network
PublikacjaZrealizowano i przedstawiono system ramanowski do zdalnego monitorowania procesu zol-żel, dedykowany do monitorowania procedury wprowadznia cząstek barwnika do sieci polimeru hybrydowego. System umożliwia wykonywanie pomiarów zdalnych, bez zakłócania i przerywania przebiegu procesu technologicznego. Zademonstrowano i skomentowano wyniki pomiarów dla przykładowego procesu.
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Full Network Coverage Monitoring Solutions – The netBaltic System Case
PublikacjaThis paper defines the problem of monitoring a specific network, and more precisely – part of reporting process, which is responsible for the transport of data collected from network devices to station managers. The environment requires additional assumptions, as a specific network related to the netBaltic Project is to be monitored. Two new monitoring methods (EHBMPvU and EHBMPvF) are proposed, which priority is full network coverage....
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A Method of Fast and Simultaneous Calibration of Many Mobile FMCW Radars Operating in a Network Anti-Drone System
PublikacjaA market for small drones is developing very fast. They are used for leisure activities and exploited in commercial applications. However, there is a growing concern for accidental or even criminal misuses of these platforms. Dangerous incidents with drones are appearing more often, and have caused many institutions to start thinking about anti-drone solutions. There are many cases when building stationary systems seems to be aimless...
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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
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Development of advanced machine learning for prognostic analysis of drying parameters for banana slices using indirect solar dryer
PublikacjaIn this study, eXtreme Gradient Boosting (XGBoost) and Light Gradient Boosting (LightGBM) algorithms were used to model-predict the drying characteristics of banana slices with an indirect solar drier. The relationships between independent variables (temperature, moisture, product type, water flow rate, and mass of product) and dependent variables (energy consumption and size reduction) were established. For energy consumption,...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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Conference on Artificial Neural Networks and Expert systems
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Optimal Selection of Input Features and an Acompanying Neural Network Structure for the Classification Purposes - Skin Lesions Case Study
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IT support for OKNO broadband Internet-based distant learning system at WUT
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Adsorption chiller in a combined heating and cooling system: simulation and optimization by neural networks
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<title>Management system of ELHEP cluster machine for FEL photonics design</title>
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Analytical model of torsional vibrations of typical sawing machine main drive system
PublikacjaPrzedstawiono model fizyczny i matematyczny drgań skrętnych napędu głównego typowej pilarki tarczowej. Model tworzą elementy sztywne SES połączone między sobą za pośrednictwem elementów sprężysto - tłumiących EST w układzie szeregowym. W modelu matematycznym uwzględniono: właściwości dynamiczne silnika napędowego, wymiary piły tarczowej, cechy materiału obrabianego (wymiary, rodzaj drewna, wilgotność drewna) oraz właściwości dynamiczne...
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PHYSICAL MODEL OF ENERGY-RELATED PROCESSES IN A ROTATING MECHANICAL SYSTEM FOR THE PURPOSES OF DIAGNOSIS OF TRANSMISSION SHAFTS
PublikacjaIn the present article, selected problems connected with identification of slowly changing energy-related processes accompanying high cyclic fatigue of construction materials of simple mechanical systems, with special consideration of transmission shafts, are mentioned for diagnostic purposes. The article also presents physical models of object and processes that in a simplified way reflect mechanical energy transmission from transmission...
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Remote Monitoring System for Impedance Spectroscopy using Wireless Sensor Network
PublikacjaThe architecture of a miniaturized impedanceanalyser with wireless communication module for remoteImpedance Spectroscopy (IS) of anticorrosion coatings ondifficult-to-reach objects (e.g. on the steel construction ofthe bridge) is described in this paper. Some practical aspectsof implementation of a Wireless Sensor Network (WSN) arealso discussed. A low scale, middle range, WSN networkcomposed of a Base Station (BS) with a Personal...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging
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A new analyzer based on pellistor sensor with neural network data postprocessing for measurement of hydrocarbons in lower explosive limit range
PublikacjaW pracy przedstawiono rezultaty pierwszego etapu badań nad nowym typem analizatora do oznaczania stężenia wodoru i lotnych węglowodorów w zakresie dolnej granicy wybuchowości. Analizator ten zbudowano w oparciu o pojedynczy czujnik pelistorowy z układem przetwarzania danych wykorzystującym sztuczną sieć neuronową.
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Hardware accelerated implementation of wavelet transform for machine vision in road traffic monitoring system
PublikacjaW artykule został opisany system monitorowania ruchu drogowego wykorzystujący sprzętową implementację transformacji falkowej. System został zaimplementowany za pomocą procesora zrealizowanego w technologii FPGA i małej kamery z układem konwersji analogowo-cyfrowej. System wykorzystuje transformację falkową do detekcji zatorów na skrzyżowaniach. W artykule zostały przedstawione przykładowe rezultaty rozpoznawania zatorów drogowych...
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Sensorless control system of induction machine supplied by voltage source inverter with output filter
PublikacjaThe paper focuses on sensorless control of the induction machines supplied by inverter with the output filters. “The novel” idea of the speed observer which is based on the backstepping approach is shown. The standard structure of the exponential observer is extended by the integrators and additional Z vector. The simulation and experimental results validate the proposed solution.
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Problems associated with the up of actuating system of a single-disc lapping machine for flat surfaces
PublikacjaPrzedstawiono wyniki badań nagrzewania się podstawowych elementów układu wykonawczego docierarki jednotarczowej o standardowej kinematyce do obróbki powierzchni płaskich. Analizowano przyrost temperatury zespołu napędowego, rolek i pierścieni prowadzących separatory oraz tarczy docierającej i obrabianych elementów. Badano nagrzewanie się układu obróbkowego podczas wyrównywania żeliwnego narzędzia i docierania powierzchni płaskich....
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Computational intelligence methods in production management
PublikacjaThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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Analysis of pedestrian activity before and during COVID-19 lockdown, using webcam time-lapse from Cracow and machine learning
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Determinants of anxiety levels among young males in a threat of experiencing military conflict–Applying a machine-learning algorithm in a psychosociological study
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Medical Digital Library Services as an Improvement of the Teleconsultation System in the Regional Health Network
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Proposal of a System Loss Model for Body Area Network in Passenger Ferry Environment
PublikacjaIn the paper, proposal of an empirical off-body system loss model for Body Area Networks working in a passenger ferry environment at 2.45 GHz has been presented. The measurements were carried out for dynamic scenarios in the discotheque passenger ferry environment. The general model formula consists of three components: mean system loss, attenuation resulting from the variable antenna position on the human body, and attenuation...
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INFLUENCE OF DATA NORMALIZATION ON THE EFFECTIVENESS OF NEURAL NETWORKS APPLIED TO CLASSIFICATION OF PAVEMENT CONDITIONS – CASE STUDY
PublikacjaIn recent years automatic classification employing machine learning seems to be in high demand for tele-informatic-based solutions. An example of such solutions are intelligent transportation systems (ITS), in which various factors are taken into account. The subject of the study presented is the impact of data pre-processing and normalization on the accuracy and training effectiveness of artificial neural networks in the case...
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Application of Generalized Regression Neural Network and Gaussian Process Regression for Modelling Hybrid Micro-Electric Discharge Machining: A Comparative Study
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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BETWEEN IDEA AND INTERPRETATION - DESIGN PROCESS AUGMENTATION
PublikacjaThe following paper investigates the idea of reducing the human digital intervention to a minimum during the advanced design process. Augmenting the outcome attributes beyond the designer's capabilities by computational design methods, data collection, data computing and digital fabrication, altogether imitating the human design process. The primary technical goal of the research was verification of restrictions and abilities used...
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Importance of artificial intelligence to support the process of anaerobicdigestion of kitchen waste with bioplastics / Znaczenie sztucznej inteligencji we wspomaganiu procesu beztlenowej fermentacji odpadów kuchennych zawierających bioplastiki
PublikacjaArtificial intelligence (AI) and machine learning were used to obtain more effective methods for conducting the digestion process and achieving final products. Data acquisition was carried out by an automatic monitoring and anal. research. The knowledge describing the anaerobic digestion process was summarized in the form of rules: IF (premise) THEN (conclusion). The compiled set of rules created a knowledge base of the expert...
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland—Swietokrzyskie Voivodeship
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Using Deep Neural Network Methods for Forecasting Energy Productivity Based on Comparison of Simulation and DNN Results for Central Poland – Swietokrzyskie Voivodeship
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Paweł Wysocki dr inż.
OsobyW roku 1995 zdał maturę i ukończył Technikum Elektroniczne w Zespole Szkół Technicznych w Suwałkach. Następnie studiował na kierunku Geodezja i Kartografia w zakresie geodezji i systemów informacji przestrzennej na Uniwersytecie Warmińsko-Mazurskim w Olsztynie, gdzie w 2001 roku obronił dyplom magisterski. Tam też ukończył studia podyplomowe w zakresie szacowania nieruchomości. Od 2001 roku był uczestnikiem dziennych studiów doktoranckich...
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Fractional-Order PID Controller (FOPID)-Based Iterative Learning Control for a Nonlinear Boiler System
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Development of an emulation platform for synchronous machine power generation system using a nonlinear functional level model
PublikacjaThe article presents the Power Hardware in the Loop (PHIL) approach for an autonomous power system analysis based on the synchronous generator model incorporating magnetic saturation effects. The model was prepared in the MATLAB/Simulink environment and then compiled into the C language for the PHIL platform implementation. The 150 kVA bidirectional DC/AC commercial-grade converter was used to emulate the synchronous generator....
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Chip suction system in circular sawing machine: empirical research and computational fluid dynamics numerical simulations
PublikacjaThe experimental analysis of the wood chip removing system during its redesigning in the existing sliding table circular saw and computational fluid dynamic (CFD) numerical simulations of the air flow process is presented in the paper. The attention was focused on the extraction hood and the bottom shelter of the actual existing system. The main aim was to perform experimental research on the pressure distribution inside the...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese 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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FPGA and optical-network-based LLRF distributed control system for TESLA-XFEL linear accelerator
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Critical analysis of laboratory measurements and monitoring system of water-pipe network corrosion-case study.
PublikacjaCase study of corrosion failure of urban water supply system caused by environmental factors was presented. Nowadays corrosion monitoring of water distribution systems is an object of major concern. There is possibility of application broad range of techniques like gravimetric and electrochemical. Both kinds of techniques can be applied in laboratory and field conditions. In many cases researches limit the case analysis to measurements...
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Zastosowanie algorytmu ewolucyjnego do uczenia neuronowego regulatora napięcia generatora synchronicznego. Evolutionary algorithm for training a neural network of synchronous generator voltage controller
PublikacjaNajpopularniejsza metoda uczenia wielowarstwowych sieci neuronowych -metoda wstecznej propagacji błędu - charakteryzuje się słabą efektywnością. Z tego względu podejmowane są próby stosowania innych metod do uczenia sieci. W pracy przedstawiono wyniki uczenia sieci realizującej regulator neuronowy, za pomocą algorytmu ewolucyjnego. Obliczenia symulacyjne potwierdziły dobrą zbieżność algorytmu ewolucyjnego w tym zastosowaniu.
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...