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total: 921
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Search results for: SPECTRAL ESTIMATION, MULTIVARIATE AUTOREGRESSIVEPROCESS, MODEL AVERAGING, FINAL PREDICTION ERROR
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Evaluating the risk of endometriosis based on patients’ self-assessment questionnaires
PublicationBackground Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered. Methods In...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String
PublicationA new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard...
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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublicationIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublicationThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
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Evaluation of Response Amplitude Operator of Ship Roll Motions Based on the Experiments in White Noise Waves
PublicationEvaluation of the response amplitude operator (RAO) function for ship wave frequency motions by means of scale model tests in regular waves is a standard procedure conducted by hydrodynamic model testing institutions. The resulting RAO function allows for evaluating sufficiently reliable seakeeping predictions for low to moderate sea states. However, for standard hull forms, correct prediction of roll motion in irregular wave (and...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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Simplified, multiregional fuzzy model of a nuclear power plant steam turbine
PublicationPower systems, including steam turbines and synchronous generators, are complex nonlinear systems with parameters varying over time. The paper presents the developed simplified, multiregional fuzzy model of the steam turbine of a nuclear power plant turbine generator set and compares the results with a full nonlinear model and commonly used linear input-output model of a steam turbine. The proposed model consist of series of linear...
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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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A predictive estimation based control strategy for a quasi-resonant dc-link inverter
PublicationIn this paper the predictive estimation based control strategy for a quasi-resonant dc link inverter (PQRDCLI) is developed. Instead of direct measurement of dc link input inverter current – its estimation with one step prediction is applied. The PQRDCLI fed induction motor, controlled with a predictive current estimation stabilized inverter output voltage slopes independently of load. Moreover, reduction of overvoltage spikes...
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Wykorzystanie algorytmów ewolucyjnych do doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej
PublicationW pracy opisano sposób doboru wzmocnień rozszerzonego obserwatora prędkości maszyny indukcyjnej przy wykorzystaniu algorytmów ewolucyjnych. Zaproponowano funkcję celu opartą na rozkładzie biegunów obserwatora. Ze względu na wpływ prędkości maszyny na dynamikę obserwatora zaproponowano dobór wzmocnień obserwatora dla różnych przedziałów prędkości. Dla poszczególnych przedziałów zaprezentowano wyniki doboru wzmocnień w postaci tabel...
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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Acoustic heating produced in the boundary layer
Publication: Instantaneous acoustic heating of a viscous fluid flow in a boundary layer is the subject of investigation. The governing equation of acoustic heating is derived by means of a special linear combination of conservation equations in the differential form, which reduces all acoustic terms in the linear part of the final equation but preserves terms belonging to the thermal mode. The procedure of decomposition is valid in a weakly...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublicationLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Audio codec employing frequency-derived tonality measure
PublicationA transform codec employing efficient algorithm for detection of spectral tonal components is presented. The tonality measure used in MPEG psychoacoustic model is replaced with the method providing adequate tonality estimates even if the tonal components are deeply frequency modulated. The reliability of hearing threshold estimated using psychoacoustic model with standardized tonality measure and the proposed one is investigated...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublicationIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Things You Might Not Know about the k-Nearest Neighbors Algorithm
PublicationRecommender Systems aim at suggesting potentially interesting items to a user. The most common kind of Recommender Systems is Collaborative Filtering which follows an intuition that users who liked the same things in the past, are more likely to be interested in the same things in the future. One of Collaborative Filtering methods is the k Nearest Neighbors algorithm which finds k users who are the most similar to an active user...
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Online sound restoration system for digital library applications
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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A Novel Approach of Using Selected Unconventional Geodesic Methods of Estimation on VTS Areas
PublicationThe Vessel Traffic Service (VTS) systems belong to the fundamental tools used in ensuring a high level of safety across sea basins with heavy traffic, where the presence of navigational hazards poses a great risk of collision or a ship running aground. In order to determine the mutual location of ships, VTS systems obtain information from different facilities, such as coastal radar stations, AIS, and vision systems. Fixing a ship’s...
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MAPPING SOUTH BALTIC NEAR-SHORE BATHYMETRY USING SENTINEL-2 OBSERVATIONS
PublicationOne of the most promising new applications of remote observation satellite systems (RO) is the near-shore bathymetry estimation based on spaceborn multispectral imageries. In recent years, many experiments aiming to estimate bathymetry in optically shallow water with the use of remote optical observations have been presented. In this paper, optimal models of satellite derived bathymetry (SDB) for relatively turbid waters of the...
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N-point estimators of the Instantaneous Complex Frequency
PublicationIn this paper estimators of the instantaneous complex frequency (ICF) are presented and discussed. The differential approach for the estimation of the ICF is used, therefore the estimators are based on maximally flat N-point FIR filters: differential and delay. The investigation of the filter performance includes static characteristics of ICF estimation and the error of the ICF estimation in the discrete frequency domain.W pracy...
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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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Simultaneous grouping and ranking with combination of SOM and TOPSIS for selection of preferable analytical procedure for furan determination in food
PublicationNovel methodology for grouping and ranking with application of self-organizing maps and multicriteria decision analysis is presented. The dataset consists of 22 objects that are analytical procedures applied to furan determination in food samples. They are described by 10 variables, referred to their analytical performance, environmental and economic aspects. Multivariate statistics analysis allows to limit the amount of input...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Driver’s Condition Detection System Using Multimodal Imaging and Machine Learning Algorithms
PublicationTo this day, driver fatigue remains one of the most significant causes of road accidents. In this paper, a novel way of detecting and monitoring a driver’s physical state has been proposed. The goal of the system was to make use of multimodal imaging from RGB and thermal cameras working simultaneously to monitor the driver’s current condition. A custom dataset was created consisting of thermal and RGB video samples. Acquired data...
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Assessment of Fuel Cells’ State of Health by Low-Frequency Noise Measurements
PublicationWe proposed applying low-frequency (flicker) noise in proton-exchange membrane fuel cells under selected loads to assess their state of health. The measurement set-up comprised a precise data acquisition board and was able to record the DC voltage and its random component at the output. The set-up estimated the voltage noise power spectral density at frequencies up to a few hundred mHz. We observed the evolution of the electrical...
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Dynamical description of quantum computing: generic nonlocality of quantumnoise
PublicationWe develop a dynamical non-Markovian description of quantum computing in the weak-coupling limit, in the lowest-order approximation. We show that the long-range memory of the quantum reservoir (such as the 1/t4 one exhibited by electromagnetic vacuum) produces a strong interrelation between the structure of noise and the quantum algorithm, implying nonlocal attacks of noise. This shows that the implicit assumption of quantum error...
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Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublicationNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
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ZASTOSOWANIE FILTRACJI CZĄSTECZKOWEJ DO ESTYMACJI POŁOŻENIA W SYSTEMIE LOKALIZACYJNYM UWB
PublicationNiniejszy artykuł dotyczy kwestii poprawy dokładności estymacji położenia w systemie lokalizacji wewnątrzbudynkowej, bazującym na radiowych pomiarach odległości realizowanych przez modemy UWB. Proponuje się zastosowanie metody filtracji cząsteczkowej do zmniejszenia błędu wyznaczania pozycji obiektu przy braku bezpośredniej widoczności ze stacją referencyjną. W artykule opisano algorytm filtru cząsteczkowego, jego przykładową implementację...
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Calibration of precipitation estimation algorithm with particular emphasis on the Pomeranian region using high performance computing
PublicationFast and accurate precipitation estimation is an important element of remote atmosphere monitoring, as it allows, for example, to correct short-term weather forecasts and the prediction of several types of meteorological threats. The paper presents methodology for calibrating precipitation estimation algorithm based on MSG SEVIRI sensor data, and Optimal Cloud Analysis product available via EumetCast transmission. Calibration is...
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Online sound restoration system for digital library applications.
PublicationAudio signal processing algorithms were introduced to the new online non-commercial service for audio restoration intended to enhance the content of digitized audio repositories. Missing or distorted audio samples are predicted using neural networks and a specific implementation of the Jannsen interpolation method based on the autoregressive model (AR) combined with the iterative restoring of missing signal samples. Since the distortion...
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Automated Reduced Model Order Selection
PublicationThis letter proposes to automate generation of reduced-order models used for accelerated -parameter computation by applying a posteriori model error estimators. So far,a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select...
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1D Model Callibration on the Basis on 3D calculations for Tesla Turbine
PublicationThe paper presents the system of equations for axisymmetriclaminar flow, after averaging, through the width of interdisk slit ofTesla turbine. Coefficients were introduced, as a result ofaveraging, that improve the efficiency of 1D model. The minimalnumber of such coefficients was determined. The 1D modelmakes it possible to attain analytical solutions to an accuracylimited by these coefficients. Calibration of 1D model depends...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Assessment of Trajectories of Non-bankrupt and Bankrupt Enterprises
PublicationThe aim of this study is to show how long-term trajectories of enterprises can be used to increase the forecasting horizon of bankruptcy prediction models. The author used seven popular forecasting models (two from Europe, two from Asia, two from North America and one from Latin America). These models (five multivariate discriminant analysis models and two logit models) were used to develop 17-year trajectories separately for non-bankrupt...
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Speech codec enhancements utilizing time compression and perceptual coding
PublicationA method for encoding wideband speech signal employing standardized narrowband speech codecs is presented as well as experimental results concerning detection of tonal spectral components. The speech signal sampled with a higher sampling rate than it is suitable for narrowband coding algorithm is compressed in order to decrease the amount of samples. Next, the time-compressed representation of a signal is encoded using a narrowband...
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A hierarchical observer for a non-linear uncertain CSTR model of biochemical processes
PublicationThe problem of estimation of unmeasured state variables and unknown reaction kinetic functions for selected biochemical processes modelled as a continuous stirred tank reactor is addressed in this paper. In particular, a new hierarchical (sequential) state observer is derived to generate stable and robust estimates of the state variables and kinetic functions. The developed hierarchical observer uses an adjusted asymptotic observer...
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An improvement of body surface area formulas using the 3D scanning technique
PublicationObjectives: Body surface area (BSA) is one of the major parameters used in several medical fields. However, there are concerns raised about its usefulness, mostly due to the ambiguity of its estimation. Material and Methods: Authors have conducted a voluntary study to investigate BSA distribution and estimation in a group of 179 adult people of various sex, age, and physique. Here, there is provided an extended analysis of the...
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A fast time-frequency multi-window analysis using a tuning directional kernel
PublicationIn this paper, a novel approach for time-frequency analysis and detection, based on the chirplet transform and dedicated to non-stationary as well as multi-component signals, is presented. Its main purpose is the estimation of spectral energy, instantaneous frequency (IF), spectral delay (SD), and chirp rate (CR) with a high time-frequency resolution (separation ability) achieved by adaptive fitting of the transform kernel. We...
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Quality of Analytical Results: Classifiying Errors and Estimating Measurement Uncertainty
PublicationThe most important parameter of each analytical result is its reliability. An analytical result is not a constant value; each result has two properties, error and uncertainty. The sources of both these parameters have to be known and their values determined (estimated). All analytical results are obtained by applying an appropriate measuring procedure. The need for reliable results requires application of reliable analytical procedures,...
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Determination of Odour Interactions of Three-Component Gas Mixtures Using an Electronic Nose
PublicationThe paper presents an application of an electronic nose prototype comprised of six TGS-type sensors and one PID-type sensor to identify odour interaction phenomena in odorous three-component mixtures. The investigation encompassed eight odorous mixtures—toluene-acetone-triethylamine and formaldehyde-butyric acid-pinene — characterized by different odour intensity and hedonic tone. A principal component regression (PCR) calibration...
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Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
PublicationIn this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzymodel is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and theparameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation(RLSE) algorithm. The rules of the fuzzy model can be added, replaced or...
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Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublicationNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
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Badanie i analiza efektywności alokacji strumieni danych w heterogenicznej sieci WBAN
PublicationW niniejszej dysertacji doktorskiej poddano dyskusji efektywność alokacji strumieni danych w heterogenicznej radiowej sieci WBAN (Wireless Body Area Networks). Biorąc pod uwagę dynamiczny rozwój nowoczesnych sieci radiokomunikacyjnych piątej generacji (5G), którego część stanowią radiowe sieci działające w obrębie ciała człowieka, bardzo ważnym aspektem są metody maksymalizujące wykorzystanie dostępnych zasobów czasowo –częstotliwościowych...
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ANALYSIS OF POSSIBILITIES FOR THE USE OF VOLUME-DELAY FUNCTIONS IN THE PLANNING MODULE OF THE TRISTAR SYSTEM
PublicationTravel time is a measure commonly used for traffic flow modelling and traffic control. It also helps to evaluate the quality of traffic control systems in urban areas. Traffic control systems that use traffic models to predict changes and disruptions in vehicle flows have to use vehicle speed-prediction models. Travel time estimation studies the effects of traffic volumes on a street section at an average speed. The TRISTAR Integrated...
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Behavioral state classification in epileptic brain using intracranial electrophysiology
PublicationOBJECTIVE: Automated behavioral state classification can benefit next generation implantable epilepsy devices. In this study we explored the feasibility of automated awake (AW) and slow wave sleep (SWS) classification using wide bandwidth intracranial EEG (iEEG) in patients undergoing evaluation for epilepsy surgery. APPROACH: Data from seven patients (age [Formula: see text], 4 women) who underwent intracranial depth electrode...
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Recovering Sound Produced by Wind Turbine Structures Employing Video Motion Magnification
PublicationThe recordings were made with a fast video camera and with a microphone. Using fast cameras allowed for observation of the micro vibrations of the object structure. Motion-magnified video recordings of wind turbines on a wind farm were made for the purpose of building a damage prediction system. An idea was to use video to recover sound & vibrations in order to obtain a contactless diagnostic method for wind turbines. The recovered signals...
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Stereo vision with Equal Baseline Multiple Camera Set (EBMCS) for obtaining depth maps of plants
PublicationThis paper presents a method of improving the estimation of distances between an autonomous harvesting robot and plants with ripe fruits by using the vision system based on five cameras. The system is called Equal Baseline Multiple Camera Set (EBMCS). EBMCS has some features of a camera matrix and a camera array. EBMCS is regarded as a set of stereo cameras for estimating distances by obtaining disparity maps and depth maps. This...
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Resistant to correlated noise and outliers discrete identification of continuous non-linear non-stationary dynamic objects
PublicationIn this article, specific methods of parameter estimation were used to identify the coefficients of continuous models represented by linear and nonlinear differential equations. The necessary discrete-time approximation of the base model is achieved by appropriately tuned FIR linear integral filters. The resulting discrete descriptions, which retain the original continuous parameterization, can then be identified using the classical...