Wyszukiwarka
Filtry
wszystkich: 533
wybranych: 457
Wyniki wyszukiwania dla: GEOGRAPHICALLY WEIGHTED REGRESSION
-
Fully Adaptive Savitzky-Golay Type Smoothers
PublikacjaThe problem of adaptive signal smoothing is consid-ered and solved using the weighted basis function approach. Inthe special case of polynomial basis and uniform weighting theproposed method reduces down to the celebrated Savitzky-Golaysmoother. Data adaptiveness is achieved via parallel estimation.It is shown that for the polynomial and harmonic bases andcosinusoidal weighting sequences, the competing signal estimatescan be computed...
-
Identification of nonstationary processes using noncausal bidirectional lattice filtering
PublikacjaThe problem of off-line identification of a nonstationary autoregressive process with a time-varying order and a time-varying degree of nonstationarity is considered and solved using the parallel estimation approach. The proposed parallel estimation scheme is made up of several bidirectional (noncausal) exponentially weighted lattice algorithms with different estimation memory and order settings. It is shown that optimization of...
-
Biomass estimation using a length-weight relationship in beetle larvae (Coleoptera: Aphodiidae, Histeridae, Hydrophilidae, Staphylinidae) obtained from cow dung
PublikacjaThis research enabled the relationship between length and dry body mass to be determined for 158 beetle larvaetaken from cow dung in north-eastern Poland. The larvae were divided into three morphological types, for which the power and linear function of the body length-weight relationship were determined. The linear regression equation characterizes the relationship between body weight and...
-
Rural Landscapes of Roman (northern) Liburnia: Diachronic Development of Organisation and the Economy in Extra-Urban Territories in the Light of Recent Archaeological Research
PublikacjaThe archaeology of Roman rural landscapes in the province of Dalmatia, and especially northern Liburnia, has until recently focused on single-site or single-monument analyses, allowing for only geographically patchy and chronologically limited conclusions. Considering the results of recent research in the wider Kvarner and sub-Velebit area, the paper discusses issues of Roman extra-urban territorial organization, the formation...
-
Disaster-Resilient Routing Schemes for Regional Failures
PublikacjaLarge-scale natural disasters can have a profound effect on the telecommunication services in the affected geographical area. Hence, it is important to develop routing approaches that may help in circumventing damaged regional areas of a network. This prompted the development of geographically diverse routing schemes and also of disaster-risk aware routing schemes. A minimum-cost geodiverse routing, where a minimum geographical...
-
New Approach to Noncasual Identification of Nonstationary Stochastic FIR Systems Subject to Both Smooth and Abrupt Parameter Changes
PublikacjaIn this technical note, we consider the problem of finite-interval parameter smoothing for a class of nonstationary linear stochastic systems subject to both smooth and abrupt parameter changes. The proposed parallel estimation scheme combines the estimates yielded by several exponentially weighted basis function algorithms. The resulting smoother automatically adjusts its smoothing bandwidth to the type and rate of nonstationarity...
-
Complex Monitoring of the Coastal Cliffs on the Example of Cliff in Jastrzebia Gora, Poland
PublikacjaThe cliff coasts, which are in total about 100 km long, are especially vulnerable to abrasion. The mean regression of the studied object which is the seacliff in Jastrzebia Gora depends on time. For example, from 1875 to 1937 the cliff regress 90 m in mean pace of 1.4 meter a year. Besides of natural factors causing the degradation, there is also an anthropogenic activity, which speeds up the abrasion process. Based on these informations,...
-
Temperature influence on tyre/road noise frequency spectra
PublikacjaThe correction for temperature effect on measured tyre/road noise is very important as it may be one of the main sources of errors in measurement results due to substantial influence of this parameter on obtained values. The latest version of the Technical Specification ISO/CD TS 13471-1 about Temperature Corrections contains a proposal of correction procedure for normalizing measured noise levels to a reference air temperature...
-
Design of modified PID controllers for 3D crane control
PublikacjaFrom the control viewpoint, 3D crane is a dynamic, nonlinear and multidimensional electromechanical system. In this paper, five control systems using a set-point weighted PID controllers (modified controllers) are designed. These structures and properties are presented. Optimization process of controllers settings based on integral performance indices is made. Simulation tests of control systems are presented. Comparison of integral...
-
Similarity Measures for Face Images: An Experimental Study
PublikacjaThis work describes experiments aimed at finding a straightforward but effective way of comparing face images.We discuss properties of the basic concepts, such as the Euclidean, cosine and correlation metrics, test the simplest version of elastic templates, and compare these solutions with distances based on texture descriptors (Local Ternary Patterns). The influence of selected image processing methods (e.g. bilateral ltering)...
-
Optimizing the parameters of a small standalone hybrid power system
PublikacjaA hybrid power plant consists of renewable energy resources, an energy storage, a discharge load and an emergency power supply. Power plant parameters are tailored to meet the requirements of continuity of supply, cost minimization, return on investment period and system capacity utilization. The papaer presents the methodology for selecting power plant parameters with a larger number of decision criteria. The task is solved...
-
Employment of passive sampling in monitoring indoor air quality in selected residences in a Tri-city area in Poland
PublikacjaTime-weighted average concentrations of selected volatile compounds were measured in chosen residences in a Tri-City area of Poland by means of passive sampling. The results were compared to those obtained by dynamic technique – sorption tubes filled with Tenax TA sorbent. Results obtained by employing the two techniques were similar. Total volatile organic compound (TVOC) parameters were also determined. An attempt was also...
-
Mean drift detection using statistical process control
PublikacjaCelem niniejszego rozdziału jest opisanie narzędzi statystycznej kontroli procesu (ang. Statistical Process Control - SPC), służących do detekcji dryfu wartości średniej w procesie. W oparciu o dane pochodzące z modelu: karty wartości średniej, odchylenia standardowego, karty oparte na testach sekwencyjnych oraz wykładniczo ważonej średniej ruchomej (ang. Exponentially Weighted Moving Average - EWMA), zostały porównane z punktu...
-
Using phase of short-term Fourier transform for evaluation of spectrogram performance
PublikacjaThe concept of spectrogram performance evaluation which exploits information on phase of short-term Fourier transform (STFT) is presented. A spectrograph which is time-frequency analyzing tool, is compared to a filter bank that demultiplexes a signal. Local group delay (LGD) and channelized instantaneous frequency (CIF) is obtained for each filtered component signal. In presented solution the performance is evaluated using so-called...
-
Shared processor scheduling of multiprocessor jobs
PublikacjaWe study a problem of shared processor scheduling of multiprocessor weighted jobs. Each job can be executed on its private processor and simultaneously on possibly many processors shared by all jobs. This simultaneous execution reduces their completion times due to the processing time overlap. Each of the m shared processors may charge a different fee but otherwise the processors are identical. The goal is to maximize the total...
-
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...
-
Nanodiamonds Doped with Manganese for Applications in Magnetic Resonance Imaging
PublikacjaNanodiamonds (NDs) are emerging with great potential in biomedical applications like biomarking through fluorescence and magnetic resonance imaging (MRI), targeted drug delivery, and cancer therapy. The magnetic and optical properties of NDs could be tuned by selective doping. Therefore, we report multifunctional manganese-incorporated NDs (Mn-NDs) fabricated by Mn ion implantation. The fluorescent properties of Mn-NDs were tuned...
-
A spatio-temporal approach to intersectoral labour and wage mobility
PublikacjaThe article presents the spatio-temporal approach for intersectoral labor and wage mobility. Analyses of interindustry mobility were performed with the use of general entropy mobility indices (GEMM). Spatio- temporal approach was obtained thanks to the separate measurement of spatial autocorrelation and regression for each set of sectoral wage and employment structure and was conducted in each year of the research period separately....
-
A Spatio-temporal Approach to Intersectoral Labour and Wage Mobility
PublikacjaThe article presents the spatio-temporal approach for intersectoral labor and wage mobility. Analyses of interindustry mobility were performed with the use of general entropy mobility indices (GEMM). Spatio-temporal approach was obtained thanks to the separate measurement of spatial autocorrelation and regression for each set of sectoral wage and employment structure and was conducted in each year of the research period separately....
-
CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublikacjaThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
-
Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
-
Selected Features of Dynamic Voting
PublikacjaIn multi-agent systems composed of autonomous agents with local knowledge, it is often desirable to aggregate their knowledge in order to make an educated decision. One of the methods of agreeing to a common decision is voting. A new history-based dynamic weight protocol allows for identification of the agents which contribute to the correct system decision. The main advantage of this approach, compared to static weighted system...
-
Globalisation and world economic poverty: The significance of hidden dimensions
PublikacjaThe aim of our research is to examine how individual dimensions of globalization affect economic poverty in the World. for this, regression models are estimated with FGT0 or FGT1 poverty measures as dependent variables and KOF indices of globalization as despendent variables. The poverty indices are estimated for 119 countries' income didtributions assuming log-normality and using Gini estimates from the WID2 database and GDP/capita...
-
A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublikacjaOvertime planning in software projects has traditionally been approached with search-based multi-objective optimization algorithms. However, the explicit solutions produced by these algorithms often lack applicability and acceptance in the software industry due to their disregard for project managers' intuitive knowledge. This study presents a machine learning model that learns the preferred overtime allocation patterns from solutions...
-
An electronic nose for quantitative determination of gas concentrations
PublikacjaThe practical application of human nose for fragrance recognition is severely limited by the fact that our sense of smell is subjective and gets tired easily. Consequen tly, there is considerable need for an instrument that can be a substitution of the human sense of smell. Electronic nose devices from the mid 1980s are used in growing number of applications. They comprise an array of several electrochemical gas sensors...
-
Quality of Test Specification by Application of Patterns
PublikacjaEmbedded system and software testing requires sophisticated methods, which are nowadays frequently supported by application of test patterns. This eases the test development process and contributes to the reusability and maintainability of the test specification. However, it does not guarantee the proper level of quality and test coverage in d ifferent dimensions of the test specification. In this paper the quality of the test...
-
Elimination of Impulsive Disturbances From Stereo Audio Recordings Using Vector Autoregressive Modeling and Variable-order Kalman Filtering
PublikacjaThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. Online tracking of signal model parameters is performed using the exponential ly weighted least squares algo- rithm. Detection of noise pulses an d model-based interpolation of the irrevocably distorted sampl es is realized using an adaptive, variable-order...
-
Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
-
Propagation Path Loss Modeling in Container Terminal Environment
PublikacjaThis paper describes novel method of path loss modeling for radio communication channels in container port area. Multi-variate empirical model is presented, based on multidimensional regression analysis of real path loss measurements from container terminal environment. The measurement instruments used in propagation studies in port area are also described.
-
Implementation of Non-Probabilistic Methods for Stability Analysis of Nonlocal Beam with Structural Uncertainties
PublikacjaIn this study, a non-probabilistic approach based Navier’s Method (NM) and Galerkin Weighted Residual Method (GWRM) in term of double parametric form has been proposed to investigate the buckling behavior of Euler-Bernoulli nonlocal beam under the framework of the Eringen's nonlocal elasticity theory, considering the structural parameters as imprecise or uncertain. The uncertainties in Young’s modulus and diameter of the beam are...
-
Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublikacjaIn this paper an artificial neural network (ANN) approach to modelling fuel consumption of heavy duty vehicles is presented. The proposed method uses easy accessible data collected via CAN bus of the truck. As a benchmark a conventional method, which is based on polynomial regression model, is used. The fuel consumption is measured in two different tests, performed by using a unique test bench to apply the load to the engine. Firstly,...
-
Usefulness of chest perfusion computed tomography in the diagnosis of diabetic pulmonary microangiopathy
PublikacjaThis paper presents the usefulness of perfusion computed tomography (pCT) in the diagnosis of diabetic pulmonary microangiopathy. Our previous works have shown that perfusion parameters are useful in the diagnosis of diabetic pulmonary microangiopathy. We are looking for such measurements and perfusion parameters that provide the most accurate diagnosis. Two types of comparison were made based on the results of clinical trials:...
-
On ''cheap smoothing'' opportunities in identification of time-varying systems
PublikacjaIn certain applications of nonstationary system identification the model-based decisions can be postponed, i.e. executed with a delay. This allows one to incorporate into the identification process not only the currently available information, but also a number of ''future'' data points. The resulting estimation schemes, which involve smoothing, are not causal. Despite the possible performance improvements, the existing smoothing...
-
The dimensions of national competitiveness: the empirical analysis based on The World Economic Forum’s data
PublikacjaThe aim of this research is to determine the minimum number of uncorrelated dimensions which can describe national competitiveness (NC). NC is thought of as the ability of a nation to provide a conducive environment for its firms to prosper. It is shown that the environment affects national productivity catalytically through the interactions with the production factors while itself remaining unchanged. Selected World Economic...
-
On noncausal identification of nonstationary stochastic systems
PublikacjaIn this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing...
-
Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
-
Investigation into MPI All-Reduce Performance in a Distributed Cluster with Consideration of Imbalanced Process Arrival Patterns
PublikacjaThe paper presents an evaluation of all-reduce collective MPI algorithms for an environment based on a geographically-distributed compute cluster. The testbed was split into two sites: CI TASK in Gdansk University of Technology and ICM in University of Warsaw, located about 300 km from each other, both connected by a fast optical fiber Ethernet-based 100 Gbps network (900 km part of the PIONIER backbone). Each site hosted a set...
-
A variational approach of homogenization of piezoelectric composites towards piezoelectric and flexoelectric effective media
PublikacjaThe effective piezoelectric properties of heterogeneous materials are evaluated in the context of periodic homogenization, whereby a variational formulation is developed, articulated with the extended Hill macrohomogeneity condition. The entire set of homogenized piezoelectric moduli is obtained as the volumetric averages of the microscopic properties of the individual constituents weighted by the displacement and polarization...
-
M-integral for finite anti-plane shear of a nonlinear elastic matrix with rigid inclusions
PublikacjaThe path-independent M-integral plays an important role in analysis of solids with inhomogeneities. However, the available applications are almost limited to linear-elastic or physically non-linear power law type materials under the assumption of infinitesimal strains. In this paper we formulate the M-integral for a class of hyperelastic solids undergoing finite anti-plane shear deformation. As an application we consider the problem...
-
On optimal tracking of rapidly varying telecommunication channels
PublikacjaWhen parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the...
-
Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublikacjaWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
-
Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublikacjaThis study investigated the solubility of benzenesulfonamide (BSA) as a model compound using experimental and computational methods. New experimental solubility data were collected in the solvents DMSO, DMF, 4FM, and their binary mixtures with water. The predictive model was constructed based on the best-performing regression models trained on available experimental data, and their hyperparameters were optimized using a newly...
-
Intelligent Decision Forest Models for Customer Churn Prediction
PublikacjaCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
-
Review and comparison of smoothing algorithms for one-dimensional data noise reduction
PublikacjaThe paper considers the choice of parameters of smoothing algorithms for data denoising. The impact of the window size on smoothing accuracy was analyzed. The parameters of denoising filters were selected with respect to the meansquare error between the computed linear regression and the noisy signal. Finally, we have compared mean, median, SavitzkyGolay, Kalman and Gaussian filter algorithms for the data from the digital sensor....
-
Benchmarking overlapping communication and computations with multiple streams for modern GPUs
PublikacjaThe paper presents benchmarking a multi-stream application processing a set of input data arrays. Tests have been performed and execution times measured for various numbers of streams and various compute intensities measured as the ratio of kernel compute time and data transfer time. As such, the application and benchmarking is representative of frequently used operations such as vector weighted sum, matrix multiplication etc....
-
Karhunen-Loeve-based approach to tracking of rapidly fading wireless communication channels
PublikacjaWhen parameters of wireless communication channels vary at a fast rate, simple estimation algorithms, such as weighted least squares (WLS) or least mean squares (LMS) algorithms, cannot estimate them with the accuracy needed to secure the reliable operation of the underlying communication systems. In cases like this, the local basis function (LBF) estimation technique can be used instead, significantly increasing the achievable...
-
Proposal of New Tracer Concentration Model in Lung PCT Study Comparison with Commonly Used Gamma-variate Model
PublikacjaPerfusion computed tomography (pCT) is one of the methods that enable non-invasive imaging of the hemodynamics of organs and tissues. On the basis of pCT measurements, perfusion parameters such as blood flow (BF), blood volume (BV), mean transit time (MTT) and permeability surface (PS) are calculated and then used for quantitative evaluation of the tissue condition. To calculate perfusion parameters it is necessary to approximate...
-
When all we have is not enough: a search for the optimal method of quantifying inflation expectations
PublikacjaAlthough inflation expectations are pivotal variables for central banks, they are not directly observable. Therefore, central banks use qualitative survey results to proxy consumer expectations, and their quantification in this manner is often criticized. In this study, we investigate and identify an optimal quantification procedure for survey results based on a set of regression and probabilistic models. Specifically, we seek...
-
Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublikacjaThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...
-
Feature Reduction Using Similarity Measure in Object Detector Learning with Haar-like Features
PublikacjaThis paper presents two methods of training complexity reduction by additional selection of features to check in object detector training task by AdaBoost training algorithm. In the first method, the features with weak performance at first weak classifier building process are reduced based on a list of features sorted by minimum weighted error. In the second method the feature similarity measures are used to throw away that features...