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Monitoring of n-butanol vapors biofiltration process using an electronic nose combined with calibration models
PublicationMalodours, by definition, are generally unpleasant, nuisance smells that are a mixture of volatile chemical compounds which can be perceptible even at low concentrations. Due to the more frequent occurrence of odour nuisance associated with the odour sensations, and thus the need to remove them from the air, deodorization techniques are commonly used. Biofiltration is one of the methods of reducing odorants in the air stream. In...
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On low-fidelity models for variable-fidelity simulation-driven design optimization of compact wideband antennas
PublicationThe paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband...
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Methodology of research on the impact of ITS services on the safety and efficiency of road traffic using transport models
PublicationThe current assessment of the impact of Intelligent Transport System (ITS) services on the level of traffic safety and efficiency is based mainly on expert assessments, statistical surveys or several traffic safety models requiring development. There is no structured, uniform assessment method that would give the opportunity to compare the impact of ITS services and their different configurations. The paper presents the methodology...
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Inverse and forward surrogate models for expedited design optimization of unequal-power-split patch couplers
PublicationIn the paper, a procedure for precise and expedited design optimization of unequal power split patchcouplers is proposed. Our methodology aims at identifying the coupler dimensions that correspond to thecircuit operating at the requested frequency and featuring a required power split. At the same time, thedesign process is supposed to be computationally efficient. The proposed methodology involves two typesof auxiliary models (surrogates):...
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CAUSALITY IN MODELS OF THERMAL PROCESSES IN SHIP ENGINE ROOMS WITH THE USE OF BOND GRAPH (BG) METHOD
PublicationWith a single approach to modeling elements of different physical nature, the method of Bond Graph (BG) is particularly well suited for modeling energy systems consisting of mechanical, thermal, electrical and hydraulic elements that operate in the power system engine room. The paper refers to the earlier presented new concept of thermal process modeling using the BG method. The authors own suggestions for determining causality...
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The congruence of mental models in entrepreneurial teams – implications for performance and satisfaction in teams operating in an emerging economy
PublicationPurpose – The paper aims to explore the relationship between the congruence of mental models held by the members of entrepreneurial teams operating in an emerging economy (Poland) and entrepreneurial outcomes (performance and satisfaction). Design/methodology/approach – The data obtained from 18 nascent and 20 established entrepreneurial teams was analysed to answer hypotheses. The research was quantitative and was conducted using...
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Methodology of research on the impact of ramp metering on the safety and efficiency of road traffic using transport models
PublicationThe methods currently used to assess the impact of Intelligent Transport Systems (ITS) services on traffic safety and efficiency are mainly based on expert assessments, statistical studies or traffic models that need further development. There is no structured, uniform evaluation method to compare the impact of different ITS services and their different configurations. The impact of ITS deployment on the road network adjacent to...
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Buried Object Characterization Using Ground Penetrating Radar Assisted by Data-Driven Surrogate-Models
PublicationThis work addresses artificial-intelligence-based buried object characterization using 3-D full-wave electromagnetic simulations of a ground penetrating radar (GPR). The task is to characterize cylindrical shape, perfectly electric conductor (PEC) object buried in various dispersive soil media, and in different positions. The main contributions of this work are (i) development of a fast and accurate data driven surrogate modeling...
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Matrix Strengthening the Identification of Observations with Split Functional Models in the Squared Msplit(q) Estimation Process
PublicationThis article addresses the issue of raising the level of identification of observations with either single or more split functional models in the squared Msplit(q) estimation process. The theoretical part of the study presents the theoretical grounds for the classical method for estimating parameters in a split functional model and proposes a modification of the computational algorithm to increase the quality of the determinations...
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Data set generation at novel test-rig for validation of numerical models for modeling granular flows
PublicationSignificant effort has been exerted on developing fast and reliable numerical models for modeling particulate flow; this is challenging owing to the complexity of such flows. To achieve this, reliable and high-quality experimental data are required for model development and validation. This study presents the design of a novel test-rig that allows the visualization and measurement of particle flow patterns during the collision...
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Cost-Efficient EM-Driven Size Reduction of Antenna Structures by Multi-Fidelity Simulation Models
PublicationDesign of antenna systems for emerging application areas such as the Internet of Things (IoT), fifth generation wireless communications (5G), or remote sensing, is a challenging endeavor. In addition to meeting stringent performance specifications concerning electrical and field properties, the structure has to maintain small physical dimensions. The latter normally requires searching for trade-off solutions because miniaturization...
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Which Curve Fits Best: Fitting ROC Curve Models to Empirical Credit-Scoring Data
PublicationIn the practice of credit-risk management, the models for receiver operating characteristic (ROC) curves are helpful in describing the shape of an ROC curve, estimating the discriminatory power of a scorecard, and generating ROC curves without underlying data. The primary purpose of this study is to review the ROC curve models proposed in the literature, primarily in biostatistics, and to fit them to actual credit-scoring ROC data...
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Application of Rapid Prototyping technology in the manufacturing of turbine blade with small diameter holes
PublicationThe article presents the possibilities of using Rapid Prototyping (RP) technology in the manufacturing of turbine blades with small diameter holes. The object under investigation was gas turbine blade with small diameter cooling holes and holes for generating longitudinal vortices. A turbine blade model was produced by means of Direct Metal Laser Sintering (DMLS) technology and subsequently validated in terms of detection and accuracy...
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Three-Dimensional Models of Liver Vessels for Navigation during Laparotomic Attenuation of Intrahepatic Portosystemic Shunt in Dogs
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Selected mice models based on APP, MAPT and presenilin gene mutations in research on the pathogenesis of Alzheimer’s disease
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Initializing the EM Algorithm for Univariate Gaussian, Multi-Component, Heteroscedastic Mixture Models by Dynamic Programming Partitions
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Direct elemental analysis of honeys by atmospheric pressure glow discharge generated in contact with a flowing liquid cathode
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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Transcriptome Changes in Three Brain Regions during Chronic Lithium Administration in the Rat Models of Mania and Depression
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Effects of scatter plot initial solutions on regular grid facility layout algorithms in typical production models
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Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
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Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study
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Flavonoids as tyrosinase inhibitors in in silico and in vitro models: basic framework of SAR using a statistical modelling approach
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On the usefulness of selected radio waves propagation models for designing mobile wireless systems in container terminal environment
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Cobalt(II) tri-tert-butoxysilanethiolates: in search of models for catalytic metal site of liver alcohol dehydrogenase
PublicationPrzeprowadzono syntezę trzech kompleksów: [Co{SSi(OBut)3}2(NH3)(L-pic)],[Co{SSi(OBut)3}2(NH3)2]xMeCN i [Co{SSi(OBut)3}3(H2O)][NHEt3]. Kompleksy są monomeryczne, dla nich wyznaczono strukturę krystalograficzną. Kompleks [Co{SSi(OBut)3(NH3)(L-pic)] o rdzeniu CoN2OS2 posiada dwa różne ligandy azotowe, zaś [Co{SSi(OBut)3(L-pic)] stanowi substrat do syntezy związku modelującego centrum katalityczne LADH.
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Discrete-time predictive control design based on overparameterized delay-plant models and identified cancellation order.
PublicationPraca dotyczy uogólnionego sterowania predykcyjnego (GPC) obiektami opisanymi dyskretnoczasowymi modelami CARIMA z uproszczeniami (nieminimalnych, przeparametryzowanych) oraz o niezerowym opóźnieniu transportowym. Optymalne sterowanie predykcyjne wyznacza się na podstawie minimalnowariancyjnego oszacowania przyszłej odpowiedzi sterowanego obiektu. Poprzez analizę warunków rozwiązywalności zadania syntezy sterownika GPC, sformułowano...
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Genetic and pharmacologic proteasome augmentation ameliorates Alzheimer’s-like pathology in mouse and fly APP overexpression models
PublicationThe proteasome has key roles in neuronal proteostasis, including the removal of misfolded and oxidized proteins, presynaptic protein turnover, and synaptic efficacy and plasticity. Proteasome dysfunction is a prominent feature of Alzheimer’s disease (AD). We show that prevention of proteasome dysfunction by genetic manipulation delays mortality, cell death, and cognitive deficits in fly and cell culture AD models. We developed...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Comparison of 2D and 3D culture models in the studies of the biological response induced by unsymmetrical bisacridines in cancer cells
PublicationMulticellular tumor spheroids are a good tool for testing new anticancer drugs, including those that may target cancer stem cells (CSCs), responsible for cancer progression, metastasis, and recurrence. Therefore, following the initial evaluation of the impact of antitumor unsymmetrical bisacridines (UAs) on lung and colon cancer cells using traditional monolayer cultures, I extended my investigations and applied the spherical model....
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Surface sliding in human abdominal wall numerical models: Comparison of single-surface and multi-surface composites
PublicationDetermining mechanical properties of abdominal soft tissues requires a coupled experimental-numerical study, but first an appropriate numerical model needs to be built. Precise modeling of human abdominal wall mechanics is difficult because of its complicated multi-layer composition and large variation between specimens. There are several approaches concerning simplification of numerical models, but it is unclear how far one could...
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Results of the application of tropospheric corrections from different troposphere models for precise GPS rapid static positioning
PublicationIn many surveying applications, determination of accurate heights is of significant interest. The delay caused by the neutral atmosphere is one of the main factors limiting the accuracy of GPS positioning and affecting mainly the height coordinate component rather than horizontal ones. Estimation of the zenith total delay is a commonly used technique for accounting for the tropospheric delay in static positioning. However, in the...
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Fast Multi-Objective Optimization of Narrow-Band Antennas Using RSA Models and Design Space Reduction
PublicationComputationally efficient technique for multi-objective design optimization of narrow-band antennas is presented. In our approach, the corrected low-fidelity antenna model (obtained through coarse-discretization EM simulations) is enhanced using frequency scaling and response correction, sampled, and utilized to obtain a fast response surface approximation (RSA) antenna surrogate. The RSA model is constructed in the reduced design space....
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Levels of 13 multi-class pesticide residues in Polish honeys determined by LC-ESI-MS/MS
PublicationLevels of 13 pesticides in 40 honey samples form Poland are reported. A rapid and sensitive method was developed for the LC-ESI-MS/MS determination of multi-class pesticide residues in honey samples. Liquid-liquid extraction (LLE) on a diatomaceous earth support (requiring the use of small amounts of organic solvent), followed by chromatographic separation on a C18 column and gradient elution were employed. The method quantifies...
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3D Morphable Models Application for Expanding Face Database Limited to Single Frontal Face Per Person
Publication1. Zaprezentowany materiał dotyczył badań nad rozszerzeniem dysponowanej bazy wzorców wizerunków twarzy, o dodatkowe wzorce z wariacją w ustawieniu. Dodatkowe wzorce były usyskiwane poprzez przejście z wizerunku twarzy 2D na model 3D, zasymulowanie zadanego ustawienia i powrót do dziedziny 2D (poprzez rzutowanie 3D->2D). W fazie konstrukcji modelu 3D, z wizerunku 2D była ściągana zarówno tekstura twarzy jak i siatka punktów charakterystycznych....
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A Method for the Evaluation of Urban Freight Transport Models as a Tool for Improving the Delivery of Sustainable Urban Transport Policy
PublicationThe article presents a method which helps local authorities to evaluate urban freight transport models. Given the complex requirements for input data and the inability to supply them for most cities, a proper quantitative evaluation of model functionality may be quite difficult for local authorities. Freight transport models designed to support sustainable urban freight transport objectives are a particular example. To overcome...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Constructing genuinely entangled multipartite states with applications to local hidden variables and local hidden states models
PublicationBuilding upon the results of R. Augusiak et al. [Phys. Rev. Lett. 115, 030404 (2015)] we develop a general approach to the generation of genuinely entangled multipartite states of any number of parties from genuinely entangled states of a fixed number of parties, in particular, the bipartite entangled ones. In our approach, certain isometries whose output subspaces are either symmetric or genuinely entangled in some multipartite...
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Experimental validation of pressure drop models during flow boiling of R134a – effect of flow acceleration and entrainment
PublicationA crucial step to assure proficient work of power and process apparatus is their proper design. A wide array of those devices operates within boiling or condensation of the working fluid to benefit from high heat transfer rates. Two-phase flows are associated with high heat transfer coefficients because of the latent heat of evaporation and high turbulence level between the liquid and the solid surface. Predicting heat transfer...
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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
PublicationThis 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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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublicationThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Genetic and pharmacologic proteasome augmentation ameliorates Alzheimer’s-like pathology in mouse and fly APP overexpression models
PublicationThe proteasome has key roles in neuronal proteostasis, including the removal of misfolded and oxidized proteins, presynaptic protein turnover, and synaptic efficacy and plasticity. Proteasome dysfunction is a prominent feature of Alzheimer’s disease (AD). We show that prevention of proteasome dysfunction by genetic manipulation delays mortality, cell death, and cognitive deficits in fly and cell culture AD models. We developed...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublicationThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Improving the Accuracy of Automatic Reconstruction of 3D Complex Buildings Models from Airborne Lidar Point Clouds
PublicationDue to high requirements of variety of 3D spatial data applications with respect to data amount and quality, automatized, effcient and reliable data acquisition and preprocessing methods are needed. The use of photogrammetry techniques—as well as the light detection and ranging (LiDAR) automatic scanners—are among attractive solutions. However, measurement data are in the form of unorganized point clouds, usually requiring transformation...
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Volatile Compound Emissions from Stereolithography Three-Dimensional Printed Cured Resin Models for Biomedical Applications
PublicationStereolithography three-dimensional printing is used increasingly in biomedical applications to create components for use in healthcare and therapy. The exposure of patients to volatile organic compounds (VOCs) emitted from cured resins represents an element of concern in such applications. Here, we investigate the biocompatibility in relation to inhalation exposure of volatile emissions of three different cured commercial resins...
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A new anisotropic bending model for nonlinear shells: Comparison with existing models and isogeometric finite element implementation
PublicationA new nonlinear hyperelastic bending model for shells formulated directly in surface form is presented, and compared to four existing prominent bending models. Through an essential set of elementary nonlinear bending test cases, the membrane and bending stresses of each model are examined analytically. Only the proposed bending model passes all the test cases, while the other bending models either fail or only pass the test cases for...
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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...