Search
Filters
total: 128
filtered: 123
Search results for: globalization, competitiveness, regression models
-
Enhancing women’s engagement in economic activities through information and communication technology deployment: evidence from Central–Eastern European countries
PublicationThis study takes a macro perspective to examine the associations between the economic deployment of information and communication technology (ICT), women’s labor market participation, and economic growth in Central–Eastern European countries between 1990 and 2017. We use data extracted from World Bank Development Indicators, World Development Reports, and the World Telecommunication/ICT Indicators Database. Our methodological framework...
-
Reduced-cost constrained miniaturization of wideband antennas using improved trust-region gradient search with repair step
PublicationIn the letter, an improved algorithm for electromagnetic (EM)-driven size reduction of wideband antennas is proposed. Our methodology utilizes variable-fidelity EM simulation models, auxiliary polynomial regression surrogates, as well as multi-point response correction. The constraint handling is implicit, using penalty functions. The core optimization algorithm is a trust-region gradient search with a repair step added in order...
-
Global sensitivity analysis of membrane model of abdominal wall with surgical mesh
PublicationThe paper addresses the issue of ventral hernia repair. Finite Element simulations can be helpful in the optimization of hernia parameters. A membrane abdominal wall model is proposed in two variants: a healthy one and including hernia defect repaired by implant. The models include many uncertainties, e.g. due to variability of abdominal wall, intraabdominal pressure value etc. Measuring mechanical properties with high accuracy...
-
Bankruptcy system model and efficiency versus the entrepreneurship and innovation in selected European countries
Publicationmodel and its efficiency on the development of entrepreneurship and innovation in selected European countries and Turkey. This goal was achieved by examining the relationships between debtor-friendliness of the bankruptcy law model and its efficiency on one side and entrepreneurship and innovation on the other. The cross-sectional ANOVA test and OLS regression method were chosen as the research method. In order to verify the research...
-
Efficiency of Artificial Intelligence Methods for Hearing Loss Type Classification: an Evaluation
PublicationThe evaluation of hearing loss is primarily conducted by pure tone audiometry testing, which is often regarded as golden standard for assessing auditory function. If the presence of hearing loss is determined, it is possible to differentiate between three types of hearing loss: sensorineural, conductive, and mixed. This study presents a comprehensive comparison of a variety of AI classification models, performed on 4007 pure tone...
-
Shales Leaching Modelling for Prediction of Flowback Fluid Composition
PublicationThe object of the paper is the prediction of flowback fluid composition at a laboratory scale, for which a new approach is described. The authors define leaching as a flowback fluid generation related to the shale processing. In the first step shale rock was characterized using X-ray fluorescence spectroscopy, X-ray diractometry and laboratory analysis. It was proven that shale rock samples taken from the selected sections of horizontal...
-
SENSITIVITY ANALYSIS IN THE REHABILITATION OF HISTORIC TIMBER STRUCTURES ON THE EXAMPLES OF GREEK CATHOLIC CHURCHES IN POLISH SUBCARPATHIA
PublicationThis work concerns structural and sensitivity analysis of carpentry joints used in historic wooden buildings in south-eastern Poland and western Ukraine. These are primarily sacred buildings and the types of joints characteristic for this region are saddle notch and dovetail joints. Thus, in the study the authors focus on these types of corner log joints. Numerical models of the joints are defined and finite element simulations...
-
Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes
PublicationTaste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can...
-
USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
-
Synthesis, Molecular Structure, Metabolic Stability and QSAR Studies of a Novel Series of Anticancer N-Acylbenzenesulfonamides
PublicationA series of novel N-acyl-4-chloro-5-methyl-2-(R1-methylthio)benzenesulfonamides 18–47 have been synthesized by the reaction of N-[4-chloro-5-methyl-2-(R1-methylthio) benzenesulfonyl]cyanamide potassium salts with appropriate carboxylic acids. Some of them showed anticancer activity toward the human cancer cell lines MCF-7, HCT-116 and HeLa, with the growth percentages (GPs) in the range from 7% to 46%. Quantitative structure-activity relationship...
-
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...
-
Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublicationFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
-
Process control of air stream deodorization from vapors of VOCs using a gas sensor matrix conducted in the biotrickling filter (BTF)
PublicationThis article presents the validity, advisability and purposefulness of using a gas sensor matrix to monitor air deodorization processes carried out in a peat-perlite-polyurethane foam-packed biotrickling filter. The aim of the conducted research was to control the effectiveness of air stream purification from vapors of hydrophobic compounds, i.e., n-hexane and cyclohexane. The effectiveness of hydrophobic n-hexane and cyclohexane...
-
Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
-
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...
-
Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublicationIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
-
Technical State Assessment of Charge Exchange System of Self-Ignition Engine, Based On the Exhaust Gas Composition Testing
PublicationThis paper presents possible use of results of exhaust gas composition testing of self - ignition engine for technical state assessment of its charge exchange system under assumption that there is strong correlation between considered structure parameters and output signals in the form of concentration of toxic compounds (ZT) as well as unambiguous character of their changes. Concentration of the analyzed ZT may be hence considered...
-
An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
-
Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
-
News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublicationStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
-
Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
-
GVC and wage dispersion. Firm-level evidence from employee-employer database
PublicationResearch background: Wage inequalities are still part of an interesting policy-oriented research area. Given the developments in international trade models (heterogeneity of firms) and increasing availability of micro-level data, more and more attention is paid to wage differences observed within and be-tween firms. Purpose of the article: The aim of the paper is to address the research gap concerning limited cross-country evidence...
-
Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
-
Wear of electroplated diamond tools in lap-grinding of Al2O3 ceramic materials
PublicationCurrent development of modern products, together with ever-increasing demands for their operation and usage, necessitate the search for new processing methods. Abrasive machining is widely used in many industrial areas, especially for processing difficult-to-machine materials such as advanced ceramics. Grinding with lapping kinematics, also called lap-grinding, is still one of the innovative methods of abrasive processing being...
-
Degree of monopoly and market power vs. price flexibility in Polish economy: empirical analysis based on COICOP classification
PublicationResearch background: The issue of price flexibility is crucial in the economy both in the aspect of company theory and its macroeconomic consequences. In a number of publications, the sources of variable price flexibility are linked to the market power of enterprises as well as the market structure that has developed in a given branch. It is difficult to indicate empirical studies that would state clearly whether price flexibility...
-
Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
-
Energy Losses Due to Imperfect Payment Infrastructure and Payment Instruments
PublicationOne of the strategic objectives of the European Union is a reduction in greenhouse gas emissions and improvement of energy efficiency by at least 32.5% in different areas of the economy by 2030. However, little is known about the impact of payment in retail on energy consumption. The purpose of this paper is to assess the chain of losses of time and energy, and therefore financial losses, that occur due to the imperfection of payment...
-
Information and communication technologies versus diffusion and substitution of financial innovations. The case of exchange-traded funds in Japan and South Korea
PublicationThe substitution between financial innovations, exchange-traded funds (ETFs), and stock index derivatives (i.e. index financial instruments) is one of the relatively understudied topics of the financial sciences. The current study aims to verify empirically the diffusion and substitution of ETFs in the market for index financial instruments. It presents in-depth analysis of the development of index financial instruments traded...
-
Dependence of Housing Real Estate Prices on Inflation as One of the Most Important Factors: Poland’s Case
PublicationThe study aimed to examine the impact of inflation on the real estate market using Polish panel data for the last 13 years. It is based on a panel model, where price changes of one square meter of housing are determined as a function in changes of inflation, the central bank's base rate, dwellings built, as well as new mortgage loans. The quarterly dynamics of the average price of 1 square meter of housing in...
-
Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublicationAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
-
Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...
-
Ontology-based text convolution neural network (TextCNN) for prediction of construction accidents
PublicationThe construction industry suffers from workplace accidents, including injuries and fatalities, which represent a significant economic and social burden for employers, workers, and society as a whole.The existing research on construction accidents heavily relies on expert evaluations,which often suffer from issues such as low efficiency, insufficient intelligence, and subjectivity.However, expert opinions provided in construction...
-
Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
-
Analysis of the Factors Affecting Static In Vitro Pepsinolysis of Food Proteins
PublicationIn this meta-analysis, we collected 58 publications spanning the last seven decades that reported static in vitro protein gastric digestion results. A number of descriptors of the pepsinolysis process were extracted, including protein type; pepsin activity and concentration; protein concentration; pH; additives; protein form (e.g., ‘native’, ‘emulsion’, ‘gel’, etc.); molecular weight of the protein; treatment; temperature; and...
-
Development of Gas Sensor Array for Methane Reforming Process Monitoring
PublicationThe article presents a new method of monitoring and assessing the course of the dry methane reforming process with the use of a gas sensor array. Nine commercially available TGS chemical gas sensors were used to construct the array (seven metal oxide sensors and two electrochemical ones). Principal Component Regression (PCR) was used as a calibration method. The developed PCR models were used to determine the quantitative parameters...
-
A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
-
Study of pH and temperature effect on lipophilicity of catechol-containing antioxidants by reversed phase liquid chromatography
PublicationLipophilicity of selected antioxidant phytochemicals, including flavonoids, phenolic acids and xanthonoids, was determined by reversed phase high performance liquid chromatography with UV detection (RP-HPLC-UV). The analyses run at different temperature and pH conditions in isocratic mode suggested that lipophilicity as distribution coefficient (logD) between aqueous and organic phase decreases with increasing temperature. For...
-
Binary Mixtures of Selected Bisphenols in the Environment: Their Toxicity in Relationship to Individual Constituents
PublicationBisphenol A (BPA) is one of the most popular and commonly used plasticizer in the industry. Over the past decade, new chemicals that belong to the bisphenol group have increasingly been used in industrial applications as alternatives to BPA. Nevertheless, information on the combined effects of bisphenol (BP) analogues is insufficient. Therefore, our current study aimed to find the biological response modulations induced by the...
-
Adaptacyjny system oświetlania dróg oraz inteligentnych miast
PublicationPrzedmiotem rozprawy jest zbadanie praktycznej możliwości wykrywania w czasie rzeczywistym anomalii w systemie oświetlenia drogowego w oparciu o analizę danych ze inteligentnych liczników energii. Zastosowanie inteligentnych liczników energii elektrycznej (Smart Meter) w systemach oświetlenia drogowego stwarza nowe możliwości w zakresie automatycznej diagnostyki takich niepożądanych zjawisk jak awarie lamp, odstępstwa od harmonogramu...
-
Experimental and numerical study of thermal and electrical potential of BIPV/T collector in the form of air-cooled photovoltaic roof tile
PublicationAmong renewable energy sources, Building-Integrated Photovoltaic/Thermal (BIPV/T) systems are gaining increasing interest. To improve their economic competitiveness, technologies that increase their efficiency are searched for. The paper is devoted to evaluating the impact of various air-cooling configurations on the thermal and electrical performance of a photovoltaic roof tile. A numerical model of the own experimental system...
-
The significance of proximity in cluster initiatives
PublicationPurpose – The main aim of this paper is to analyse relations between geographical and competence proximity and development of cooperation in cluster initiatives. Design/methodology/approach – The research was based on an original theoretical concept referring to the trajectory of development of cooperative relations in cluster initiatives. The research was carried out in mid-2017, in four purposefully selected clusterinitiatives....
-
Speed estimation of a car at impact with a W-beam guardrail using numerical simulations and machine learning
PublicationThis paper aimed at developing a new method of estimating the impact speed of a passenger car at the moment of a crash into a W-beam road safety barrier. The determination of such a speed based on the accident outcomes is demanding, because often there is no access to full accident data. However, accurate determination of the impact speed is one of the key elements in the reconstruction of road accidents. A machine learning algorithm...
-
Sex contribution to average age at onset of Huntington's disease depends on the number of (CAG)n repeats
PublicationHuntington’s disease (HD) is a hereditary neurodegenerative disorder caused by the extension of the CAG repeats in exon 1 of the HTT gene and is transmitted in a dominant manner. The present study aimed to assess whether patients’ sex, in the context of mutated and normal allele length, contributes to age on onset (AO) of HD. The study population comprised a large cohort of 3723 HD patients from the European Huntington’s Disease...
-
Determination of the active ingredient in pharmaceutical gel formulation by NIR spectroscopy
PublicationPharmaceuticals of their intended must be thoroughly controlled. The traditional analytical methods are very costly and time consuming. NIR spectroscopy allows to analyze pharmaceutical materials very quickly and with very low costs. First pharmaceutical applications of the NIR spectroscopy appeared with some incuriosity in the late 1960s. Application of NIR in the contemporary pharmaceutical industry is very large. The most common...
-
Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
PublicationThe phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based...
-
Reshaping financial systems: The role of ICT in the diffusion of financial innovations – Recent evidence from European countries
PublicationExchange-traded funds (ETFs) are among the fastest-growing types of innovative financial products. The emergence and spread of these instruments have been facilitated by the digital revolution. Information and communication technology (ICT) is profoundly reshaping the global economic landscape, laying solid foundations for unrestricted and unbounded flows of information and knowledge, eliminating information asymmetries, and furthering...
-
Multicomponent ionic liquid CMC prediction
PublicationWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
-
Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
-
Kluczowe kompetencje jako narzędzie do tworzenia nowych modeli biznesu w przedsiębiorstwach
PublicationKoncepcja kluczowych kompetencji wywodzi się z nurtu zasobowego, który zakłada, iż o efektywności i konkurencyjności każdego podmiotu decydują odpowiednio dobrane zasoby i umiejętności ich optymalnego wykorzystania. Model biznesu to narzędzie do realizacji strategii organizacji, które wspomaga rozwój oraz zarządzanie strategiczne w przedsiębiorstwie. Dysertacja wypełnia lukę, jaką było wskazanie na zależność pomiędzy kluczowymi...
-
FACTORS AFFECTING THE CONCLUSION OF AN ARRANGEMENT IN RESTRUCTURING PROCEEDINGS: EVIDENCE FROM POLAND
PublicationThe EU Restructuring Directive (2019/1023) requires Member States to provide a preventive restructuring framework for financially distressed entities that remain viable or are likely to readily restore economic viability. The first step to a successful restructuring is the approval of an arrangement between the debtor and creditors. The main research objective of the article is to identify factors affecting the conclusion of an...