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Search results for: ACCURACY
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A new approach to determination of the two-mass model parameters of railway current collector
PublicationThe paper presents two mathematical models of railway current collectors both with two degrees of freedom. The first one, hereinafter Pantograph Articulated Model (PAM), has one degree of freedom in rotational motion and the second degree of freedom in translational motion. The second model, called henceforth as Pantograph Reference Model (PRM), has both degrees of freedom in translational motion. Differential equations of the...
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A new approach to determination of the two-mass model parameters of railway current collector
PublicationThe paper presents two mathematical models of railway current collectors both with two degrees of freedom. The first one, hereinafter Pantograph Articulated Model (PAM), has one degree of freedom in rotational motion and the second degree of freedom in translational motion. The second model, called henceforth as Pantograph Reference Model (PRM), has both degrees of freedom in translational motion. Differential equations of the...
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Comprehensive determination of flavouring additives and nicotine in e-cigarette refill solutions. Part II: Gas-chromatography–mass spectrometry analysis
PublicationFlavouring compounds are an essential part of e-liquid products for cigarettes. In general, they are regarded as safe for ingestion, but they may have unrecognized risks when they are inhaled. In some cases, manufactures do not currently abide by the Tobacco Products Directive (2014/40/EU) and do not declare the detailed contents of e-liquids on their labels. To help evaluate the health impact of flavouring substances, there is...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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A PROPOSAL FOR ONE-IMAGE PHOTOGRAMMETRY SYSTEM FOR MEASURING THE CLEARANCE DISTANCE. CASE STUDY
PublicationMeasurement of the clearance distance (both in the context of the rail and road) is one of the current and increasingly discussed topics in the context of photogrammetric and image processing (computer vision) methods. The article presents a description of a simple and rapid method of measure the clearance distance between the obstacles by using one-image photogrammetry. The proposed method was tested for the railway, tram and...
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublicationCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Application of twin-plane ECT sensor for identification of the internal imperfections inside concrete beams
PublicationThe main purpose of this paper is to investigate application of special construction of Electrical Capacitance Tomography (ECT) sensor to concrete beams internal homogeneity tests. Identification of internal imperfection inside the concrete beams is one of the main problems related to analysis of the construction structure bearing capacity. Therefore, this paper shows attempts to study the measurement prospects for this non-invasive,...
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Calculating the Partition Coefficients of Organic Solvents in Octanol/Water and Octanol/Air
PublicationPartition coefficients define how a solute is distributed between two immiscible phases at equilibrium. The experimental estimation of partition coefficients in a complex system can be an expensive, difficult, and time-consuming process. Here a computational strategy to predict the distributions of a set of solutes in two relevant phase equilibria is presented. The octanol/water and octanol/air partition coefficients are predicted...
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Use of a Least Squares with Conditional Equations Method in Positioning a Tramway Track in the Gdansk Agglomeration
PublicationSatellite measurement techniques have been used for many years in different types of human activity, including work related to staking out and making use of rail infrastructure. First and foremost, satellite techniques are applied to determine the tramway track course and to analyse the changes of its position during its operation. This paper proposes using the least squares with conditional equations method, known in geodesy (LSce)....
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Hyperbolic Asynchronous Method of a Radio Navigation Technique
PublicationHumans have always wanted to determine position in an unknown environment. At the beginning methods were simple. They were based on the observation of characteristic points, in the case of shipping additional observations of the coastline. Then came navigation based on astronomical methods (astronavigation). At the beginning of the XX-century a new way of determining the current location was developed. It has used radiowave signals....
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Self-Adaptive Mesh Generator for Global Complex Roots and Poles Finding Algorithm
PublicationIn any global method of searching for roots and poles, increasing the number of samples increases the chances of finding them precisely in a given area. However, the global complex roots and poles finding algorithm (GRPF) (as one of the few) has direct control over the accuracy of the results. In addition, this algorithm has a simple condition for finding all roots and poles in a given area: it only requires a sufficiently dense...
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Monolithic capsule phase microextraction prior to gas chromatography-mass spectrometry for the determination of organochlorine pesticides in environmental water samples
PublicationIn this study, a capsule phase microextraction (CPME) protocol followed by gas chromatography-mass spectrometry is proposed for the accurate and sensitive monitoring of organochlorine pesticides (OCPs) in environmental water samples. Different monolithic sol–gel encapsulated sorbents were compared and monolithic sol–gel poly(ethylene glycol)-based sorbent incorporated into porous microextraction capsules resulted in the highest...
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Noise profiling for speech enhancement employing machine learning models
PublicationThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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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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EVALUATION OF 3D MODEL OF REBAR FOR QUANTITATIVE PARAMETERS
PublicationThe construction industry practices and processes are evolving constantly, and with the emergence of Industry 4.0, the use of technologies is expanding. Construction progress monitoring is an essential project lifecycle process; project success and timely completion are linked with effective progress monitoring operations and adopted tools. In the domain of automated construction progress monitoring, 3D modeling techniques have...
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High-temperature Corrosion of ~ 30 Pct Porous FeCr Stainless Steels in Air: Long-Term Evaluation Up to Breakaway
PublicationIn this work, a long-term (up to 6000 hours) corrosion evaluation of three porous (~ 30 pct of initial porosity) ferritic iron-chromium alloys with different Cr contents (20, 22, and 27 wt pct of Cr) was carried out at 600 C, 700 C, 800 C, and 900 C in air. Mass gain measurements and SEM analyses revealed that at temperatures above 600 C, all alloys exhibit breakaway corrosion, whereas at 600 C, none of the alloys were heavily...
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Estimation of Average Speed of Road Vehicles by Sound Intensity Analysis
PublicationConstant monitoring of road traffic is important part of modern smart city systems. The proposed method estimates average speed of road vehicles in the observation period, using a passive acoustic vector sensor. Speed estimation based on sound intensity analysis is a novel approach to the described problem. Sound intensity in two orthogonal axes is measured with a sensor placed alongside the road. Position of the apparent sound...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Orientation-aware ship detection via a rotation feature decoupling supported deep learning approach
PublicationShip 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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Monte-Carlo Modeling of Optical Sensors for Postoperative Free Flap Monitoring
PublicationThis work aims to develop a numerical tissue model and implement software to simulate photon propagation using the Monte Carlo method to determine design guidelines for a physical measurement system. C++ was used for the simulation program, and Python as a programming environment to create an interface that allows the user to customize individual simulation elements, allowing for increased accuracy and flexibility when simulating...
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Fault detection in the marine engine using a support vector data description method
PublicationFast detection and correct diagnosis of any engine condition changes are essential elements of safety andenvironmental protection. Many diagnostic algorithms significantly improve the detection of malfunctions.Studies on diagnostic methods are rarely reported and even less implemented in the marine engine industry.To fill this gap, this paper presents the Support Vector Data Description (SVDD) method as applied to thefault detection...
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Emotion Recognition from Physiological Channels Using Graph Neural Network
PublicationIn recent years, a number of new research papers have emerged on the application of neural networks in affective computing. One of the newest trends observed is the utilization of graph neural networks (GNNs) to recognize emotions. The study presented in the paper follows this trend. Within the work, GraphSleepNet (a GNN for classifying the stages of sleep) was adjusted for emotion recognition and validated for this purpose. The...
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Uncertainty quantification of modal parameter estimates obtained from subspace identification: An experimental validation on a laboratory test of a large-scale wind turbine blade
PublicationThe uncertainty afflicting modal parameter estimates stems from e.g., the finite data length, unknown, or partly measured inputs and the choice of the identification algorithm. Quantification of the related errors with the statistical Delta method is a recent tool, useful in many modern modal analysis applications e.g., damage diagnosis, reliability analysis, model calibration. In this paper, the Delta method-based uncertainty...
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Non-Linear Analysis of Structures Utilizing Load-Discretization of Stiffness Matrix Method with Coordinate Update
PublicationThis paper proposes a stiffness method based structural analysis algorithm for geometrically non-linear structures. In this study, the applied load on the joints has been discretized to a sequence of a few loadings applied. Each loading step produces incremental external nodal displacements, which are added to the corresponding coordinates to get a new geometrical shape of the structure. This process is iteratively repeated until...
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IoT for healthcare applications
PublicationThis chapter summarizes IRACON contributions related to the application of IoT in healthcare. It consists of the following three sections. Section 8.1 presents the measurement campaigns and the related statistical analysis to obtain various channel models for wearable and implantable devices. In addition, the importance of physical human-body phantoms used for channel, Specific Absorption Rate (SAR), and Electromagnetic (EM) exposure...
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Thermal buckling of functionally graded piezomagnetic micro- and nanobeams presenting the flexomagnetic effect
PublicationGalerkin weighted residual method (GWRM) is applied and implemented to address the axial stability and bifurcation point of a functionally graded piezomagnetic structure containing flexomagneticity in a thermal environment. The continuum specimen involves an exponential mass distributed in a heterogeneous media with a constant square cross section. The physical neutral plane is investigated to postulate functionally graded material...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Ultrasound assisted dispersive solid phase microextraction using polystyrene-polyoleic acid graft copolymer for determination of Sb(III) in various bottled beverages by HGAAS
PublicationA new polyoleic acid-polystyrene (PoleS) block/graft copolymer was synthesized and applied as adsorbent for ultrasound assisted dispersive solid phase microextraction (UA-DSPME) of Sb(III) in different bottled beverages and analysis using hydride generation atomic absorption spectrometry (HGAAS). Adsorption capacity of the PoleS was 150 mg g−1. Several sample preparation parameters such as sorbent amount, solvent type, pH, sample...
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Comparing traffic intensity estimates employing passive acoustic radar and microwave Doppler radar sensor
PublicationThe purpose of our applied research project is to develop an autonomous road sign with built-in radar devices of our design. In this paper, we show that it is possible to calibrate the acoustic vector sensor so that it can be used to measure traffic volume and count the vehicles involved in the traffic through the analysis of the noise emitted by them. Signals obtained from a Doppler radar are used as a reference source. Although...
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Self-Supervised Learning to Increase the Performance of Skin Lesion Classification
PublicationTo successfully train a deep neural network, a large amount of human-labeled data is required. Unfortunately, in many areas, collecting and labeling data is a difficult and tedious task. Several ways have been developed to mitigate the problem associated with the shortage of data, the most common of which is transfer learning. However, in many cases, the use of transfer learning as the only remedy is insufficient. In this study,...
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Using UAV Photogrammetry to Analyse Changes in the Coastal Zone Based on the Sopot Tombolo (Salient) Measurement Project
PublicationThe main factors influencing the shape of the beach, shoreline and seabed include undulation, wind and coastal currents. These phenomena cause continuous and multidimensional changes in the shape of the seabed and the Earth’s surface, and when they occur in an area of intense human activity, they should be constantly monitored. In 2018 and 2019, several measurement campaigns took place in the littoral zone in Sopot, related to...
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Detection of the First Component of the Received LTE Signal in the OTDoA Method
PublicationIn a modern world there is a growing demand for localization services of various kinds. Position estimation can be realized via cellular networks, especially in the currently widely deployed LTE (Long Term Evolution) networks. However, it is not an easy task in harsh propagation conditions which often occur in dense urban environments. Recently, time-methods of terminal localization within the network have been the focus of attention,...
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Numerical Investigation on Dynamic Performance of a Multi-storey Steel Structure Model and Comparison with Experimental Results
PublicationShaking table testing is the most commonly adopted method to simulate earthquake forces. This approach allows us to analyze the dynamic performance and provides a valuable insight into the dynamics of building structures, which helps to improve their future safety and reliability. The present study aims to conduct a numerical evaluation of dynamic response of a multi-storey steel structure model, which was previously examined during...
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Assessing Highway Travel Time Reliability using Probe Vehicle Data
PublicationProbe vehicle data (also known as “floating car data”) can be used to analyze travel time reliability of an existing road corridor in order to determine where, when, and how often traffic congestion occurs at particular road segments. The aim of the study is to find the best reliability performance measures for assessing congestion frequency and severity based on probe data. Pilot surveys conducted on A2 motorway in Poland confirm...
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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublicationAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...
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An MOR Algorithm Based on the Immittance Zero and Pole Eigenvectors for Fast FEM Simulations of Two-Port Microwave Structures
PublicationThe aim of this article is to present a novel model-order reduction (MOR) algorithm for fast finite-element frequency-domain simulations of microwave two-port structures. The projection basis used to construct the reduced-order model (ROM) comprises two sets: singular vectors and regular vectors. The first set is composed of the eigenvectors associated with the poles of the finite-element method (FEM) state-space system, while...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Development of a simple biogas analyzer module (BAM) for real-time biogas production monitoring
PublicationAnaerobic digestion (AD) relies on the cooperation of specific microbial communities, making it susceptible to process disruptions that could impact biogas production. In this regard, this study presents a technological solution based on the Arduino platform, in the form of a simple online monitoring system that can track the produced biogas profile, named as biogas analyzer module (BAM). The applicability of the BAM focused on...
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Investigation of use of hydrophilic/hydrophobic NADESs for selective extraction of As(III) and Sb(III) ions in vegetable samples: Air assisted liquid phase microextraction and chemometric optimization
PublicationIn this paper, a green, cost-effective sample preparation method based on air assisted liquid phase microextraction (AA-LPME) was developed for the simultaneous extraction of As(III) and Sb(III) ions from vegetable samples using hydrophilic/hydrophobic natural deep eutectic solvents (NADESs). Central composite design was used for the optimization of extraction factors including NADES volume, extraction cycle, pH, and curcumin concentration....
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Development of an orbital shaker-assisted fatty acid-based switchable solvent microextraction procedure for rapid and green extraction of amoxicillin from complex matrices: Central composite design
PublicationIn this study, a cheap, fast and simple orbital shaker-assisted fatty acid-based switchable solvent microextraction (OS-FASS-ME) procedure was developed for the extraction of amoxicillin (AMOX) in dairy products, pharmaceutical samples and wastewater prior to its spectrophotometric analysis. Fatty acid-based switchable solvents were investigated for extracting AMOX. The key factors of the OS-FASS-ME procedure were optimized using...
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Evaluation of high-frequency roughness measurement errors for composite and ceramic surfaces after machining
PublicationPrecise characterisation of surface topography is of the greatest importance since many factors directly affect the accuracy of the whole measurement process. In this paper, the variety of surface topographies from machined composite and ceramic workpieces was studied with a special emphasis on the measurement results. Surfaces were subjected to the ground diamond, honing and milling processes. Measurement results were analysed...
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Determination of Glycerol, Propylene Glycol, and Nicotine as the Main Components in Refill Liquids for Electronic Cigarettes
PublicationRefill liquids for electronic cigarettes are an important area of research due to the health safety and quality control of such products. A method was developed for the determination of glycerol, propylene glycol, and nicotine in refill liquids using liquid chromatography, coupled with tandem mass spectrometry (LC-MS/MS) in multiple reaction monitoring (MRM) mode with electrospray ionisation (ESI). Sample preparation was based...
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Automatic singing quality recognition employing artificial neural networks
PublicationCelem 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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Dynamic mass measurement in checkweighers using a discrete time-variant low-pass filter
PublicationConveyor belt type checkweighers are complex mechanical systems consisting of a weighing sensor (strain gauge load cell, electrodynamically compensated load cell), packages (of different shapes, made of different materials) and a transport system (motors, gears, rollers). Disturbances generated by the vibrating parts of such a system are reflected in the signal power spectra in a form of strong spectral peaks, located usually in...
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Geminate-pair dissociation yield in systems with exponential energetic disorder — A Monte Carlo study
PublicationGeminate electron–hole recombination in systems with exponential energetic disorder is studied by Monte Carlo method. The field and temperature dependencies of geminate-pair dissociation probability are calculated. It is established that the dissociation yield of carrier pairs depends mainly on the extent of carrier thermalization, which influences the Einstein relationship. The approximate limiting temperature is given by Te =...
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Dimensional Synthesis of Coupled-Resonator Pseudoelliptic Microwave Bandpass Filters with Constant and Dispersive Couplings
PublicationIn this paper, we propose a novel technique for the dimensional synthesis of coupled-resonator pseudoelliptic microwave filters with constant and dispersive couplings. The proposed technique is based on numerical simulations of small structures, involving up to two adjacent resonators, and it accounts for a loading effect from other resonators by replacing them with terminations coupled through appropriately scaled inverters. The...
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Wavelet transform-based approach to defect identification in railway carbon contact strips.
PublicationPantographs of electric rail vehicles are fitted with carbon contact strips, which slide along the contact wire of catenary to provide constant electrical contact. Contact strips are exposed to wear and damages. Using damaged contact strips significantly increases the risk of catenary rupture. Therefore, their technical condition has to be inspected frequently. In previous work a 3D laser scanning system was proposed for recording...
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Reliable Microwave Modeling By Means of Variable-Fidelity Response Features
PublicationIn this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...