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Wyniki wyszukiwania dla: VEHICLE DETECTION, TRAFFIC MONITORING SYSTEM, BACKGROUND SUBTRACTION, CONVOLUTIONAL NEURAL NETWORK
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Estimating the Average Speed of Public Transport Vehicles Based on Traffic Control System Data
PublikacjaIntelligent Transport Systems are a valuable source of traffic information, covering both private and public vehicles. The main problem, however, is that very few studies are conducted to determine the speed of buses, trams and trolleys in urban networks in relation to traffic conditions. The paper investigates how ITS systems data could be used to model the speed of Public Transport vehicles. This is now possible thanks to the...
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Food analysis using artificial senses.
PublikacjaNowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring...
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Multifunctional PID Neuro-Controller for Synchronous Generator
PublikacjaThis paper deals with a PID Neuro-Controller (PIDNC) for synchronous generator system. The controller is based on artificial neural network and adaptive control strategy. It ensures two functions: maintaining the generator voltage at its desired value and damping electromechanical oscillations. The performance of the proposed controller is evaluated on the basis of simulation tests. A comparative study of the results obtained with...
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QoS Extensions for Flow-Awareness Networks
PublikacjaThe paper contains a description and research results of the proposal for distributed QoS extensions for Flow-Based Networking. These QoS extensions let the network accept or reject flows based on current network load and QoS promises for each of the flows. Proposed solution consists of two distributed components, each of them performing in every node, measurement system and access control. The solution could be applied in any...
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Smart Approach for Glioma Segmentation in Magnetic Resonance Imaging using Modified Convolutional Network Architecture (U-NET)
PublikacjaSegmentation of a brain tumor from magnetic resonance multimodal images is a challenging task in the field of medical imaging. The vast diversity in potential target regions, appearance and multifarious intensity threshold levels of various tumor types are few of the major factors that affect segmentation results. An accurate diagnosis and its treatment demand strict delineation of the tumor affected tissues. Herein, we focus on...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublikacjaIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Akustyczna analiza parametrów ruchu drogowego z wykorzystaniem informacji o hałasie oraz uczenia maszynowego
PublikacjaCelem rozprawy było opracowanie akustycznej metody analizy parametrów ruchu drogowego. Zasada działania akustycznej analizy ruchu drogowego zapewnia pasywną metodę monitorowania natężenia ruchu. W pracy przedstawiono wybrane metody uczenia maszynowego w kontekście analizy dźwięku (ang.Machine Hearing). Przedstawiono metodologię klasyfikacji zdarzeń w ruchu drogowym z wykorzystaniem uczenia maszynowego. Przybliżono podstawowe...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Evaluation of Street Lighting Efficiency Using a Mobile Measurement System
PublikacjaThe issue concerns the initial stage of work on a method for performing a rapid assessment of the energy efficiency and illuminance of a street lighting installation. The proposed method is based on simultaneous measurement of illuminance from three lux meters placed on the roof of the vehicle. The data are acquired in road traffic, while the vehicle is driving. The proposed solution will allow in the future to quickly and reproducibly...
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Stress Monitoring System for Individuals with Autism Spectrum Disorders
PublikacjaIn this article, a stress monitoring system tailored for individuals with Autism Spectrum Disorders (ASD) and developed for the educational institution is presented. People with ASD face problems with effective stress management due to their high self-perceived levels of stress, poor ability to cope with it, and dificulties with the accurate detection of the source of stress. Consistently, being able to measure stress appears to...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublikacjaShip imaging position plays an important role in visual navigation, and thus significant focuses have been paid to accurately extract ship imaging positions in maritime videos. Previous studies are mainly conducted in the horizontal ship detection manner from maritime image sequences. This can lead to unsatisfied ship detection performance due to that some background pixels maybe wrongly identified as ship contours. To address...
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AUTOMATYCZNA KLASYFIKACJA MOWY PATOLOGICZNEJ
PublikacjaAplikacja przedstawiona w niniejszym rozdziale służy do automatycznego wykrywania mowy patologicznej na podstawie bazy nagrań. W pierwszej kolejności przedstawiono założenia leżące u podstaw przeprowadzonych badan wraz z wyborem bazy mowy patologicznej. Zaprezentowano również zastosowane algorytmy oraz cechy sygnału mowy, które pozwalają odróżnić mowę niezaburzoną od mowy patologicznej. Wytrenowane sieci neuronowe zostały następnie...
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Adaptacyjny system sterowania ruchem drogowym
PublikacjaAdaptacyjny system sterowania ruchem drogowym to rodzaj systemu sterowania, który dynamicznie, w czasie rzeczywistym, dostosowuje swoje parametry w oparciu o bieżące warunki ruchu drogowego. Celem niniejszej rozprawy jest sprawdzenie wpływu wybranych cech systemu, zbudowanego w oparciu o zaprojektowane i zbudowane z udziałem autora inteligentne znaki drogowe, na wybrane parametry mające wpływ na bezpieczeństwo i płynność ruchu....
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Evaluation of Vehicle Routing Problem Algorithms for Transport Logistics Using Dedicated GIS System
PublikacjaThe development and research related to optimization of fleet management is of high interest among many industrial and scientific entities related to logistics and transport. Optimal distribution of transportation resources leads to significant cost reduction. In this context, scientific research related to so called Vehicle Routing Problem (VRP) which relies on determining the shortest transport routes for a strictly limited number...
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Verification of the Parameterization Methods in the Context of Automatic Recognition of Sounds Related to Danger
PublikacjaW artykule opisano aplikację, która automatycznie wykrywa zdarzenia dźwiękowe takie jak: rozbita szyba, wystrzał, wybuch i krzyk. Opisany system składa się z bloku parametryzacji i klasyfikatora. W artykule dokonano porównania parametrów dedykowanych dla tego zastosowania oraz standardowych deskryptorów MPEG-7. Porównano też dwa klasyfikatory: Jeden oparty o Percetron (sieci neuronowe) i drugi oparty o Maszynę wektorów wspierających....
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: 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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Systemy bezprzewodowej łączności i transmisji danych dla potrzeb bezpieczeństwa publicznego (studium stanu i rozwiązań)
PublikacjaW niniejszym rozdziale przedstawiono charakterystyki rozwiązań użytkowych zrealizowanych w Katedrze Systemów i Sieci Radiokomunikacyjnych Politechniki Gdańskiej. Autorzy scharakteryzowali opracowane przez zespół badawczy Katedry, systemy bezprzewodowego monitoringu zagrożeń bezpieczeństwa oraz zarządzania i sterowania infrastrukturami krytycznymi. W tym też kontekście omówiono następujące systemy i aplikacje użytkowe: − globalny...
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Small rov to detection and identification of dangerous underwater objects
PublikacjaA small unmanned underwater vehicle (UUV) to inspection of an undersea space is presented in the paper. Its behavior is controlled by a trained pilot. Correct detection and identification of targets depends on vehicle'sprecise displacement along a predefined route. Nowadays, the UUVs are equipped with an automatic control system to execute some basic maneuvers without constant human interventions. Hence, in the paper, an autopilot...
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Verification of the Analytical Traffic Model of a Multidomain IMS/NGN Using the Simulation Model
PublikacjaIn this paper we verify the previously proposed analytical traffic model of a multidomain Next Generation Network (NGN), which is standardized for delivering multimedia services based on the IP Multimedia Subsystem (IMS). For this reason a proper simulation model used, in which not theoretical queuing system models but the operation of real network elements and standardized call scenarios are accurately implemented. Consequently,...
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MULTI-CRITERIA MODEL IN MULTIFUNCTIONAL BUILDING SYSTEM DESIGN PROCESS
PublikacjaThe paper presents a multi-criteria approach in multifunctional building system design process. The aim is to develop a theory relative to the engineering system of multifunctional with a mathematical representation defined by a holistic network for the lifecycle of the designed object. The idea of work was to define the structure of a complex system. Background for the presented field is to develop a design strategy for multifunctional...
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Analysis of the Suitability of Selected Data Tranmission Systems in RSMAD
PublikacjaThis paper analyses the suitability of the selected radio communication systems currently used for data transmission, or usable in the future, in Radio System for Monitoring and Acquisition of Data from Traffic Enforcement Cameras (in short RSMAD). The paper also presents the advantages and disadvantages of each systems, paying particular attention to features that directly affect the suitability of the solution in the RSMAD system....
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Badanie stanu nawierzchni drogowej z wykorzystaniem uczenia maszynowego
PublikacjaW artykule opisano budowę systemu informowania o stanie nawierzchni drogowej z wykorzystaniem metod cyfrowego przetwarzania obrazów oraz uczenia maszynowego. Efektem wykonanych prac badawczych jest eksperymentalna platforma, pozwalająca na rejestrację uszkodzeń na drogach, system do analizy, przetwarzania i klasyfikacji danych oraz webowa aplikacja użytkownika do przeglądu stanu nawierzchni w wybranej lokalizacji.
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Simulating Power Generation from Photovoltaics in the Polish Power System Based on Ground Meteorological Measurements—First Tests Based on Transmission System Operator Data
PublikacjaThe Polish power system is undergoing a slow process of transformation from coal to one that is renewables dominated. Although coal will remain a fundamental fuel in the coming years, the recent upsurge in installed capacity of photovoltaic (PV) systems should draw significant attention. Owning to the fact that the Polish Transmission System Operator recently published the PV hourly generation time series in this article, we aim...
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Guided waves for monitoring of plate structures with linear cracks of variable length
PublikacjaDamage occurring at the work of plate structures may grow to a considerable size. The joint action – the detection of a defect at the earliest possible stage, the monitoring of its growth and the determination of its critical size in the context of structural reliability allows optimizing the cost of the maintenance and repair of structural elements. Thus the development of monitoring systems for permanent observation of fault...
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Determination of Vehicles Load Equivalency Factors for Polish Catalogue of Typical Flexible and Semi-rigid Pavement Structures
PublikacjaThe new Polish Catalog of Typical Flexible and Semi-rigid Pavement Structures was introduced to use in practice in 2014. Much of works were focused on actualization of vehicles load equivalency factors. For this purpose data delivered from weigh-inmotion were analyzed. Four methods of determination of load equivalency factors for pavement structure design were compared. The analysis showed that fourth power equation, AASHTO 1993...
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TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads
PublikacjaTensorHive is a tool for organizing work of research and engineering teams that use servers with GPUs for machine learning workloads. In a comprehensive web interface, it supports reservation of GPUs for exclusive usage, hardware monitoring, as well as configuring, executing and queuing distributed computational jobs. Focusing on easy installation and simple configuration, the tool automatically detects the available computing...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublikacjaAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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"Creating a numerical model of noise conditions based on the analysis of traffic volume changes in cities with low and medium structure.
PublikacjaThe subject of this research study is to analyze noise conditions of the selected area in the city of Gdańsk using data related to traffic volume changes during a day. This is because daily distribution of noise levels is much more helpful for noise control and reduction than traditional maps with Lden levels indicated. Calculations are made with the use of a numerical model developed at the Gdansk Univ. of Technology and implemented...
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"Creating a numerical model of noise conditions based on the analysis of traffic volume changes in cities with low and medium structure.
PublikacjaThe subject of this research study is to analyze noise conditions of the selected area in the city of Gdańsk using data related to traffic volume changes during a day. This is because daily distribution of noise levels is much more helpful for noise control and reduction than traditional maps with Lden levels indicated. Calculations are made with the use of a numerical model developed at the Gdansk Univ. of Technology and implemented...
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SHM System of the Roof Structure of Sports Arena “Olivia”
PublikacjaThe paper presents a structural health monitoring system of the Sports Arena “Olivia” in Gdansk, Poland. The system was installed because of doubts about the roof stability due to observed buckling of the steel truss members. The SHM system was based on nonlinear FEM models used for detection of type of near failure modes of the roof. The application of detailed FEM model in current state updated on data from in situ loading testes...
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Practical Approach to IP Scheduled Throughput Measurements in Dual Connectivity Systems
PublikacjaIP scheduled throughput defined according to 3GPP TS 36.314 reflects user throughput regardless of traffic characteristics, and therefore has become one of the most important indicators for monitoring Quality of Service (QoS) of the end user in Evolved Universal Terrestrial Radio Access Network (E-UTRAN). However, networks built on a distributed architecture make the above definition impossible to be applied directly due to the...
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Machine Learning and Text Analysis in an Artificial Intelligent System for the Training of Air Traffic Controllers
PublikacjaThis chapter presents the application of new information technology in education for the training of air traffic controllers (ATCs). Machine learning, multi-criteria decision analysis, and text analysis as the methods of artificial intelligence for ATCs training have been described. The authors have made an analysis of the International Civil Aviation Organization documents for modern principles of ATCs education. The prototype...
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Ruchotwórczość wielkopowierzchniowych obiektów handlowych trzeciej generacji na przykładzie Trójmiasta
PublikacjaWielkopowierzchniowe obiekty (handlowe, usługowe itp.) generują ruch o dużych natężeniach, które często przekraczają możliwości przepustowe przyległego układu ulicznego. Wpływają w ten sposób na znaczne pogorszenie się warunków ruchu w najbliższym otoczeniu obiektu i zakłócenia w prawidłowym funkcjonowaniu systemu transportowego miasta. Wobec braku polskich doświadczeń konieczne jest badanie wpływu wybranych czynników demograficznych,...
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Perspectives of Telematics Implementation in Tri-City Transport Systems Management and Planning
PublikacjaIn 2010 the City of Gdynia applied for match funding the project ''Implementation of the Integrated Traffic Management System TRISTAR in Tri-City" under the Operational Programme Infrastructure and Environment. This year the project has been placed on a list approved by the Ministry of Infrastructure. Tri-City proceeds with a tender for the implementation of the system. The project will be implemented in key elements are included...
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Automatic singing quality recognition employing artificial neural networks
PublikacjaCelem artykułu jest udowodnienie możliwości automatycznej oceny jakości technicznej głosów śpiewaczych. Pokrótce zaprezentowano w nim stworzoną bazę danych głosów śpiewaczych oraz zaimplementowane parametry. Przy pomocy sztucznych sieci neuronowych zaprojektowano system decyzyjny, który oceniono w pięciostopniowej skali jakość techniczną głosu. Przy pomocy metod statystycznych udowodniono, że wyniki generowane przez ten system...
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Diagnosis of damages in family buildings using neural networks
PublikacjaThe article concerns a problem of damages in family buildings, which result from traffic-induced vibrations. These vibrations arise from various causes and their size is influenced by many factors. The most important is the type of a road, type and weight of vehicles that run on the road, type and condition of the road surface, the distance from the house to the source of vibrations and many others which should be taken into account....
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Multisensor System for the Protection of Critical Infrastructure of Seaport
PublikacjaThere are many separated infrastructural objects within a harbor area that may be considered “critical”, such as gas and oil terminals or anchored naval vessels. Those objects require special protection, including security systems capable of monitoring both surface and underwater areas, because an intrusion into the protected area may be attempted using small surface vehicles (boats, kayaks, rafts, floating devices with weapons...
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Kernel PCA in Application to Leakage Detection in Drinking Water Distribution System
PublikacjaMonitoring plays an important role in advanced control of complex dynamic systems. Precise information about system's behaviour, including faults detection, enables efficient control. Proposed method- Kernel Principal Component Analysis (KPCA), a representative of machine learning, skilfully takes full advantage of the well known PCA method and extends its application to nonlinear case. The paper explains the general idea of KPCA...
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Software Agents for Computer Network Security
PublikacjaThe chapter presents applications of multi-agent technology for design and implementation of agent-based systems intended to cooperatively solve several critical tasks in the area of computer network security. These systems are Agent-based Generator of Computer Attacks (AGCA), Multi-agent Intrusion Detection and Protection System (MIDPS), Agent-based Environment for Simulation of DDoS Attacks and Defense (AESAD) and Mobile Agent...
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Diagnostyka łożysk silnika indukcyjnego na podstawie prądu zasilającego przy użyciu sztucznych sieci neuronowych
PublikacjaW artykule zawarto wyniki badań dotyczące diagnostyki łożysk silnika indukcyjnego na podstawie pomiarów prądu zasilającego z wykorzystaniem sztucznych sieci neuronowych. Zaprezentowano wyniki uczenia sieci oraz rezultaty testów przeprowadzonych na danych spoza zbioru uczącego. Badania wykonane zostały na obiektach z celowo wprowadzonymi uszkodzeniami łożysk. Przedstawiona nowa koncepcja zakłada użycie zestawu sieci neuronowych...
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Instance segmentation of stack composed of unknown objects
PublikacjaThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
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ANALIZA PRZEPUSTOWOŚCI WYBRANEGO UKŁADU TOROWEGO W PRZESTRZENI CZĘŚCIOWO – UPORZĄDKOWANEJ
PublikacjaNa sieci kolejowej istotny wpływ na płynność ruchu mają odpowiednio usytuowane odcinki odstępowe. Z podobną sytuacją mamy do czynienia przy modernizacji stacji kolejowych i tworzeniu nowych rozwiązań, w których należy uwzględnić prognozy rozwoju ruchu na danym elemencie sieci kolejowej. Jednak w przypadku stacji sytuacja staje się dużo bardziej skomplikowana i kosztowna, gdyż poprawa przepustowości wymaga istotnych zmian organizacyjnych...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Automated Parameter Determination for Horizontal Curves for the Purposes of Road Safety Models with the Use of the Global Positioning System
PublikacjaThis paper presents the results of research conducted to develop an automated system capable of determining parameters for horizontal curves. The system presented in this article could calculate the actual course of a road by means of a two-stage positioning of recorded points along the road. In the first stage, measurements were taken with a Real-Time Network (RTN) receiver installed in a research vehicle. In the second stage,...
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Comparison of Absorbed and Intercepted Fractions of PAR for Individual Trees Based on Radiative Transfer Model Simulations
PublikacjaThe fraction of absorbed photosynthetically active radiation (fAPAR) is a key parameter for estimating the gross primary production (GPP) of trees. For continuous, dense forest canopies, fAPAR, is often equated with the intercepted fraction, fIPAR. This assumption is not valid for individual trees in urban environments or parkland settings where the canopy is sparse and there are well-defined tree crown boundaries. Here, the distinction...
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Gas Detection Using Resistive Gas Sensors And Radial Basis Function Neural Networks
PublikacjaWe present a use of Radial Basis Function (RBF) neural networks and Fluctuation Enhanced Sensing (FES) method in gas detection system utilizing a prototype resistive WO3 gas sensing layer with gold nanoparticles. We investigated accuracy of gas detection for three different preprocessing methods: no preprocessing, Principal Component Analysis (PCA) and wavelet transformation. Low frequency noise voltage observed in resistive gas...
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Airborne and mobile laser scanning in measurements of sea cliffs on the southern Baltic
PublikacjaMeasurements of sea cliffs performed using periodic surveying based on laser scanning is currently one of the fastest and most accurate solutions. Supported with the technology of satellite measurements using GNSS (Global Navigation Satellite System) positioning and photographic measurements with the use of aerial vehicle, they enable an effective monitoring of the sea cliffs affected by the erosion. In case of the coast of southern...