Search
Filters
total: 128
filtered: 123
Search results for: globalization, competitiveness, regression models
-
Estimating the Impact of Globalization on International Competitiveneess : a Multidimensional Approach
PublicationThis paper examines the effects of globalization on international competitiveness (IC). The aggregated and disaggregated indices of IC (World Economic Forum) and globalization (KOF) for 132 countries in 2008 are used for the estimation of regression functions. The results show that globalization positively influences IC at the highest aggregation levels of the indices used. Social and political globalization affect IC at intermediate...
-
Globalisation and world economic poverty: The significance of hidden dimensions
PublicationThe 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...
-
International Competitiveness in the Economics Literature: A Bibliometric Study
PublicationThis paper has as its main aim to consolidate the state of the art of academic research on international competitiveness, based on a bibliometric study of the economics literature published over the past 70 years. Citation data is collected from the ISI WEB of Science website, Scopus and Google Scholar and is analysed using Histcite and Vosviewer software. The growth pattern of the international competitiveness literature is investigated...
-
ARCHITECTURE IN BRANDING AND OVERBRANDING PROCESS. HOW GLOBALIZATION INFLUENCED ARCHITECTURE QUALITY.
PublicationGlobalization is unification. In the field of architecture and in the social structure alike, the globalization leads to a blending of economies and cultures that produces uniformly branded public space as a response to universal assumptions of integration and correlation. While branding consists in creating a recognizable and outstanding image a strong contradiction exists between both of these approaches. As a result, regional...
-
Effect of the integration into Global Value Chains on the employment contract in Central and Eastern European countries
PublicationResearch background: In the era of globalization, there is a need to address decent work deficits in Global Value Chains (GVCs). The forms of working conditions reveal a broad dispersion of contents. The literature review exposes hardly any Europe-focused research assessing the socioeconomic impact of global production links and going beyond their pure economic effects assessed in terms of employment, productivity or wages. Purpose...
-
Renewable Energy in the Pomerania Voivodeship—Institutional, Economic, Environmental and Physical Aspects in Light of EU Energy Transformation
PublicationIn the era of globalization and rapid economic growth, affecting most world economies, increased production and consumption are leading to higher levels of energy production and consumption. The growing demand for energy means that energy resources from conventional sources are not sufficient; moreover, its production generates high costs and contributes to the emission of greenhouse gases and waste. In view of the above, many...
-
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...
-
Iterative‐recursive estimation of parameters of regression models with resistance to outliers on practical examples
PublicationHere, identification of processes and systems in the sense of the least sum of absolute values is taken into consideration. The respective absolute value estimators are recognised as exceptionally insensitive to large measurement faults or other defects in the processed data, whereas the classical least squares procedure appears to be completely impractical for processing the data contaminated with such parasitic distortions. Since...
-
Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models
Publication -
Prediction of near-bottom water salinity in the Baltic Sea using Ordinary Least Squares and Geographically Weighted Regression models
Publication -
Teicoplanin-Modified HPLC Column as a Source of Experimental Parameters for Prediction of the Anticonvulsant Activity of 1,2,4-Triazole-3-Thiones by the Regression Models
Publication -
A Panel Analysis of the Impact of Green Transformation and Globalization on the Labor Share in the National Income
PublicationThis study aims to examine the impact of green transition and globalization processes on changes in the labour share. The study covers 76 national economies diversified in development, global production share and energy transition stage from 2000 to 2018. Based on the Total Economy Database data, panel models of the relationship between green transition, globalization and the labour share in the national income were estimated....
-
Impact of the Manufacturing Sector on the Export Competitiveness of European Countries – a Spatial Panel Analysis
PublicationThe purpose of this paper is to determine how changes in the export competitiveness of the EU economy (measured by exports and net exports) depend on changes in the competitiveness of processing industries, on the basis of manufacturing data from 19 EU countries over years 1995-2009 and using a spatial panel data model. The determinants of export competitiveness are selected in the light of predictions from international trade...
-
Bibliometric approach to tracking the concept of international competitiveness
PublicationThe main aim of paper is to identify the growth pattern in the international competitiveness literature, its core publications and key research domains on the basis of bibliometric data from the years 1945–2015. Citation data is collected from the ISI Web of Science Website, Scopus and Google Scholar, and analysed using HistCite, Pajek and VOSviewer software. Bibliometric indicators, network citation, key-route path methods and...
-
A systematic retrieval of international competitiveness literature: a bibliometric study
PublicationOver the last three decades there has been growing interest in international competitiveness research. However, as evidenced by the academic literature, there is a lack of systematic chronological studies synthesizing how this field has evolved over time. The main aim of this paper is to consolidate the state of the art of academic research on international competitiveness in the discipline of economics by using a new method: a...
-
Regression points in non-intrusive polynomial chaos expansion method and D-optimal design
PublicationThe paper addresses selected issues of uncertainty quantification in the modelling of a system containing surgical mesh used in ventral hernia repair. Uncertainties in the models occur e.g. due to variability of abdominal wall properties among others. In order to include them, a non-intrusive regression-based polynomial chaos expansion method is employed. Its accuracy depends on the choice of regression points. In the study a relation...
-
Computing methods for fast and precise body surface area estimation of selected body parts
PublicationCurrently used body surface area (BSA) formulas give satisfactory results only for individuals with typical physique, while for elderly, obese or anorectic people accurate results cannot be expected. Particularly noteworthy are the results for individuals with severe obesity (body-mass index greater than 35 kg/m2), for which BSA estimation errors reached 80%. The main goal of our study is the development of precise BSA models for...
-
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...
-
Fuzzy regresion approach to road safety analysis at regional level
PublicationRoad safety modelling on regional level of NUTS 2 in the EU is the complex issue and authors of this article indicate this in previous publications. NUTS 2 are basic regions for the application of regional policies (0.8-3 m inhabitants). During multivariate models development they discovered that it is difficult to make regression model well described all regions, even if they are from one country. In the first step Poisson model...
-
Branża IT – wyzwania związane z zarządzaniem kapitałem ludzkim
PublicationArtykuł dotyczy procesów zarządzania kapitałem ludzkim w firmach IT, w których największe wyzwania wiążą się z dwoma obszarami: zatrudniania i zatrzymywania specjalistów IT w organizacji. Działy HR prześcigają się w stosowaniu coraz to nowszych rozwiązań, aby pozyskać oraz motywować kompetentnych informatyków do pracy na rzecz firmy. Głównym celem artykułu jest prezentacja działań dotyczących rekrutacji oraz motywowania pracowników...
-
Finding the Right Solvent: A Novel Screening Protocol for Identifying Environmentally Friendly and Cost-Effective Options for Benzenesulfonamide
PublicationThis 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...
-
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...
-
Three-dimensional geographically weighted inverse regression (3GWR) model for satellite derived bathymetry using Sentinel-2 observations
PublicationCurrent trends of development of satellite derived bathymetry (SDB) models rely on applying calibration techniques including analytical approaches, neuro-fuzzy systems, regression optimization and others. In most of the cases, the SDB models are calibrated and verified for test sites, that provide favourable conditions for the remote derivation of bathymetry such as high water clarity, homogenous bottom type, low amount of sediment...
-
User-assisted methodology targeted for building structure interpretable QSPR models for boosting CO2 capture with ionic liquids
PublicationTask-specific ionic liquid (IL) is an emerging class of compounds that may be environmentally friendly. Properly selected, these compounds may be green alternative to amine solutions and can replace them in post-combustion carbon dioxide (CO2) capture processes on an industrial scale. However, owing to the vast diversity of ions and their possible combinations, laboratory research is time consuming and expensive. Therefore, computational...
-
Heavy Duty Vehicle Fuel Consumption Modelling Based on Exploitation Data by Using Artificial Neural Networks
PublicationOne of the ways to improve the fuel economy of heavy duty trucks is to operate the combustion engine in its most efficient operating points. To do that, a mathematical model of the engine is required, which shows the relations between engine speed, torque and fuel consumption in transient states. In this paper, easy accessible exploitation data collected via CAN bus of the heavy duty truck were used to obtain a model of a diesel...
-
Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
PublicationFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...
-
Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
-
Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method
PublicationElectrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric...
-
Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
-
Problems of modelling toxic compounds emitted by a marine internal combustion engine in unsteady states
PublicationContemporary engine tests are performed based on the theory of experiment. The available versions of programmes used for analysing experimental data make frequent use of the multiple regression model, which enables examining effects and interactions between input model parameters and a single output variable. The use of multi-equation models provides more freedom in analysing the measured results, as those models enable simultaneous...
-
Globalized Parametric Optimization of Microwave Passive Components Using Simplex-Based Surrogates
PublicationOptimization-based parameter adjustment involving full-wave electromagnetic (EM) simulation models is a crucial stage of present-day microwave design process. In fact, rigorous optimization is the only reliable mean permitting to simultaneously handle multiple geometry/material parameters, objectives, and constraints. Unfortunately, EM-driven design is a computationally intensive endeavor. While local tuning is usually manageable,...
-
A Machine Learning Approach for Estimating Overtime Allocation in Software Development Projects
PublicationOvertime 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...
-
Models of using the Internet by young Poles and their social capital.
PublicationHighlights • Study examining Polish youth on internet usage styles. • Online communication is the most common form of spending time on the Internet. •...
-
BLOOD PRESSURE ESTIMATION BY MEANS OF A JOINT IMPEDANCE– PHOTOPLETYSMOGRAPHIC METHOD
PublicationThe knowledge of patient’s day to day blood pressure changes is invaluable to physicians for both diagnostics and health monitoring reasons. Constant observation of the pressure throughout a day would provide even more valuable clinical information. A convenient non-invasive methods of blood pressure estimation for monitoring purposes are widely proposed. This work shows a statistical approach to...
-
Heavy duty vehicle fuel consumption modelling using artificial neural networks
PublicationIn 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,...
-
Problemy modelowania liczby podróży generowanych i absorbowanych na przykładzie Gdańska
PublicationJedną z podstawowych danych niezbędnych do planowania elementów systemu transportowego jest informacja o liczbie podróży odbywanych na analizowanym obszarze. Dane te uzyskiwane są najczęściej za pomocą symulacyjnych modeli transportowych. Jednym z istotnych elementów i pierwszym etapem najczęściej stosowanego, klasycznego modelu czterostopniowego jest modelowanie liczby podróży generowanych i absorbowanych, podczas którego to...
-
Performance and Power-Aware Modeling of MPI Applications for Cluster Computing
PublicationThe paper presents modeling of performance and power consumption when running parallel applications on modern cluster-based systems. The model includes basic so-called blocks representing either computations or communication. The latter includes both point-to-point and collective communication. Real measurements were performed using MPI applications and routines run on three different clusters with both Infiniband and Gigabit Ethernet...
-
Sensitivity analysis based on non-intrusive regression-based polynomial chaos expansion for surgical mesh modelling
PublicationThe modelling of a system containing implants used in ventral hernia repair and human tissue suffers from many uncertainties. Thus, a probabilistic approach is needed. The goal of this study is to define an efficient numerical method to solve non-linear biomechanical models supporting the surgeon in decisions about ventral hernia repair. The model parameters are subject to substantial variability owing to, e.g., abdominal wall...
-
Towards New Mappings between Emotion Representation Models
PublicationThere are several models for representing emotions in affect-aware applications, and available emotion recognition solutions provide results using diverse emotion models. As multimodal fusion is beneficial in terms of both accuracy and reliability of emotion recognition, one of the challenges is mapping between the models of affect representation. This paper addresses this issue by: proposing a procedure to elaborate new mappings,...
-
Determination of Odor Air Quality Index (OAQII) Using Gas Sensor Matrix
PublicationThis article presents a new way to determine odor nuisance based on the proposed odor air quality index (OAQII), using an instrumental method. This indicator relates the most important odor features, such as intensity, hedonic tone and odor concentration. The research was conducted at the compost screening yard of the municipal treatment plant in Central Poland, on which a self-constructed gas sensor array was placed. It consisted...
-
Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach
PublicationMonitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in...
-
Open Data Capability Architecture - An Interpretive Structural Modeling Approach
PublicationDespite of increasing availability of open data as a vital organizational resource, large numbers of startups and organizations fail when it comes to utilizing open data effectively. This shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse....
-
When all we have is not enough: a search for the optimal method of quantifying inflation expectations
PublicationAlthough 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...
-
Detecting type of hearing loss with different AI classification methods: a performance review
PublicationHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
-
ARIMA vs LSTM on NASDAQ stock exchange data
PublicationThis study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange. Research shows which model performs better in terms of the chosen input data, parameters and number of features. The chosen models were compared using...
-
Problems of modelling toxic compounds emitted by a marine internal combustion engine for the evaluation of its structure parameters
PublicationThe paper presents the possibility of using an analytical study of the engine exhaust ignition to evaluate the technical condition of the selected components. Software tools available for the analysis of experimental data commonly use multiple regression model that allows the study of the effects and iterations between model input quantities and one output variable. The use of multi-equation models gives a lot of freedom in the...
-
Triple correlation states between in-situ tested soil parameters
PublicationWhen testing soil parameters, the measured parameter values are only approximations of the true values. The measurand is determined based on metrological uncertainties or using statistical models for analysing data. Some parameters of the soil state present strong correlations, but others do not always provide simple correspondences. Multiple correlations between geotechnical parameters can provide a new perspective regarding the...
-
Polynomial Chaos Expansion in Bio-and Structural Mechanics
PublicationThis monograph presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the...
-
Polynomial Chaos Expansion in Bio- and Structural Mechanics
PublicationThis thesis presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the repair...
-
Advanced sensitivity analysis of the impact of the temporal distribution and intensity of rainfall on hydrograph parameters in urban catchments
PublicationKnowledge of the variability of the hydrograph of outflow from urban catchments is highly important for measurements and evaluation of the operation of sewer networks. Currently, hydrodynamic models are most frequently used for hydrograph modeling. Since a large number of their parameters have to be identified, there may be problems at the calibration stage. Hence, sensitivity analysis is used to limit the number of parameters....