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Search results for: PRICE CHANGE PREDICTION
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A review of phase change materials and heat enhancement methodologies
PublicationPhase change materials (PCMs) are an efficient alternative to store and release heat at a specific range of temperature. Here PCMs and heat enhancement methodologies for PCM storage are reviewed. A short overview of PCMs and their applications is presented in addition to the progress during the last 10 years. Heat enhancement techniques, that is, extended surfaces, multiple and composite PCMs, and encapsulation techniques, are...
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Analysis of Drone Signals Based on Change Point Detection Algorithm
PublicationThe work presents an algorithm characterized by high precision and efficiency in identifying signals related to data transmission between the controller and the drone. Using an efficient change point detection algorithm and parallel analysis capabilities, this method facilitates rapid signal analysis. These features make the proposed algorithm a solid basis for developing an effective anti-drone defense system.
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Skills Mismatch in the Context of Technological Change
PublicationThis dissertation examines the impact of technological change (TC) on skills and competences and how higher education’s role has changed along the way. Quantitative research was conducted to reveal the perceptions of students and employers in Poland on the relevance of particular skills in an ICT based economy. The results of this research show that there is generally a rather insignificant discrepancy in these perceptions....
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The influence of climate change on the life insurance in the EU: A panel data approach
PublicationThe financial sector, as one of the most sensitive economic sectors, is alert to all trends and changes in the environment. The aim of the article is to study the impact of climate change on the life insurance market using panel data from 28 countries of the European Union (EU) for the last 9 years. This study is based on a panel model, where the amount of premiums under life insurance contracts is defined as a function of the...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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Nature-Inspired Driven Deep-AI Algorithms for Wind Speed Prediction
PublicationPredicting wind energy production accurately is crucial for enhancing grid management and dispatching capacity. However, the inherent unpredictability of wind speed poses significant challenges to achieving high prediction accuracy. To address this challenge, this study introduces a novel pre-processing framework that leverages thirteen nature-inspired optimization algorithms to extract and combine Intrinsic Mode Functions (IMFs)...
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Akaike's final prediction error criterion revisited
PublicationWhen local identification of a nonstationary ARX system is carried out, two important decisions must be taken. First, one should decide upon the number of estimated parameters, i.e., on the model order. Second, one should choose the appropriate estimation bandwidth, related to the (effective) number of input-output data samples that will be used for identification/ tracking purposes. Failure to make the right decisions results...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublicationIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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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...
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BANKRUPTCY PREDICTION IN VISEGRAD GROUP COUNTRIES
PublicationThe novelty of the study is a comprehensive look at the problem of bankruptcy forecasting in Visegrad Group countries (V4) and making a comparison in relation to the achievements obtained in more developed western countries. The conducted research based on a systematic literature review of 151 publications indexed in Scopus and Web of Science and bibliometric analysis. The results showed that the main lines of research are from...
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Dynamic Bankruptcy Prediction Models for European Enterprises
PublicationThis manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and...
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Bridging the gap between architectural and environmental engineering education in the context of climate change
PublicationIndicated in this article is the urgent need to adjust architectural education to the challenges triggered by climate change. Although reports on the future scenarios for cities are alarming, documents that set criteria for architectural education do not indicate competencies related to climate change adaptation and mitigation, mainly by avoiding environmental engineering considerations. An immediate answer to this problem could...
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Balanced Spider Monkey Optimization with Bi-LSTM for Sustainable Air Quality Prediction
PublicationA reliable air quality prediction model is required for pollution control, human health monitoring, and sustainability. The existing air quality prediction models lack efficiency due to overfitting in prediction model and local optima trap in feature selection. This study proposes the Balanced Spider Monkey Optimization (BSMO) technique for effective feature selection to overcome the local optima trap and overfitting problems....
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Influence of Gaps’ Geometry Change on Leakage Flow in Axial Piston Pumps
PublicationAxial piston pumps are the core elements of most medium and high-pressure hydraulic systems. High volumetric efficiency and high working pressures are the main advantages of this type of pumps. Therefore it is necessary to accurately calculate the leakage flow through the gaps to design efficient high-pressure pump. The main difficulty of such calculations is the fact, that the gaps change their geometry during pumping process....
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Systematic Literature Review on Click Through Rate Prediction
PublicationThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
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A new index for statistical analyses and prediction of travelling ionospheric disturbances
PublicationTravelling Ionospheric Disturbances (TIDs) are signatures of atmospheric gravity waves (AGWs) observed in changes in the electron density. The analysis of TIDs is relevant for studying coupling processes in the thermosphere–ionosphere system. A new TID index is introduced, which is based on an easy extension of the commonly used approach for TID detection. This TID activity index, which can be applied for individual Global Navigation...
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Prediction of protein assemblies, the next frontier: The CASP14‐CAPRI experiment
PublicationWe present the results for CAPRI Round 50, the 4th joint CASP-CAPRI protein assembly prediction challenge. The Round comprised a total of 12 targets, including 6 dimers, 3 trimers, and 3 higher-order oligomers. Four of these were easy targets, for which good structural templates were available either for the full assembly, or for the main interfaces (of the higher-order oligomers). Eight were difficult targets for which only distantly...
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IS THE REGIONAL DIVERGENCE A PRICE FOR THE INTERNATIONAL CONVERGENCE? THE CASE OF THE VISEGRAD GROUP
PublicationThe main goal of this article is to verify whether the Visegrad Group countries are achieving social convergence at national level at the expense of internal divergence. For this purpose, the existence of social beta-, sigma- and gamma-convergence at national and regional level was tested. The author of this article decided to tackle the convergence problem since there is a high risk that countries are trying to catch up at...
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The low price anomaly and the Intriguing Case of the Polish Stock Market
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Price nonsynchronicity, idiosyncratic risk, and expected stock returns in China
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Price range and the cross-section of expected country and industry returns
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Tool Wear Prediction in Single-Sided Lapping Process
PublicationSingle-sided lapping is one of the most effective planarization technologies. The process has relatively complex kinematics and it is determined by a number of inputs parameters. It has been noted that prediction of the tool wear during the process is critical for product quality control. To determine the profile wear of the lapping plate, a computer model which simulates abrasive grains trajectories was developed in MATLAB. Moreover,...
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Phase change thermal energy storage – the experience of the materials preparation for the specific applications.
PublicationThermal energy storage and temperature stabilization is very important in many engineering applications. There are three kinds of thermal energy storage: sensible heat, latent heat and reversible chemical reaction heat. Phase change materials (PCM) absorb, store and release large amounts of energy in the form of latent heat, at constant temperature, called the transition temperature. Many innovative applications could be found...
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Induction machine behavioral modeling for prediction of EMI propagation.
PublicationThis paper presents the results of wideband behavioral modeling of an induction machine (IM). The proposed solution enables modeling the IM differential- and common-mode impedance for a frequency range from 1 kHz to 10 MHz. Methods of parameter extraction are derived from the measured IM impedances. The developed models of 1.5 kW and 7.5 kW induction machines are designed using the Saber Sketch scheme editor and simulated in the...
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Economic growth, structural change and quality upgrading in New Member States
PublicationThe purpose of this research is to present the recent developments concerning structural change and productivity growth in New Member States and the role played in such process by country specific factors. We focus on ten countries (NMS-10) which joined the EU in 2004 and analyze productivity dynamics of their labor structures between the years 1995 and 2005 in a comparative setting versus EU-15 economies. NMS-10 have gone through...
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Baltic Sea climate fever. Creative solutions for waterfront cities in the context of climate change
PublicationThe goal of the research is to recognize climate change impact on Baltic Sea cities and description of strengths and weaknesses of cities strategies and activities. The range of research has been limited to 3 cities in the Baltic Sea (Copenhagen, Gothenburg, Tallinn) and Tricity as an area for which recommendations will be proposed actions in the field of adaptation to climate change. Recommendations for Tricity as a unique group...
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Mobilenet-V2 Enhanced Parkinson's Disease Prediction with Hybrid Data Integration
PublicationThis study investigates the role of deep learning models, particularly MobileNet-v2, in Parkinson's Disease (PD) detection through handwriting spiral analysis. Handwriting difficulties often signal early signs of PD, necessitating early detection tools due to potential impacts on patients' work capacities. The study utilizes a three-fold approach, including data augmentation, algorithm development for simulated PD image datasets,...
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CORPORATE BANKRUPTCY PREDICTION IN POLAND AGAINST THE BACKGROUND OF FOREIGN EXPERIENCE
PublicationIn highly developed countries, research in the field of bankruptcy risk prediction has been conducted for many years. For example, in the United States, which can be considered a pioneering country, the first publications appeared in the early twentieth century. In Poland, due to political and economic reasons, the interest in this issue dates back to the early 1990s. For this reason, this publication attempts to answer the following...
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CORPORATE BANKRUPTCY PREDICTION IN POLAND AGAINST THE BACKGROUND OF FOREIGN EXPERIENCE
PublicationIn highly developed countries, research in the field of bankruptcy risk prediction has been conducted for many years. For example, in the United States, which can be considered a pioneering country, the first publications appeared in the early twentieth century. In Poland, due to political and economic reasons, the interest in this issue dates back to the early 1990s. For this reason, this publication attempts to answer the following...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change: with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Adaptive Dynamical Systems Modelling of Transformational Organizational Change with Focus on Organizational Culture and Organizational Learning
PublicationTransformative Organizational Change becomes more and more significant both practically and academically, especially in the context of organizational culture and learning. However computational modeling and a formalization of organizational change and learning processes are still largely unexplored. This paper aims to provide an adaptive network model of transformative organizational change and translate a selection of organizational...
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Numerical Estimation of Hull Hydrodynamic Derivatives in Ship Maneuvering Prediction
PublicationPrediction of the maneuvering characteristics of the ship at the design stage can be done by means of model tests, computational simulations or a combination of both. The model tests can be realized as direct simulation of the standard maneuvers with the free running model, which gives the most accurate results, but is also the least affordable as it requires very large tank or natural lake, as well as complex equipment of the...
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Electricity demand prediction by multi-agent system with history-based weighting
PublicationEnergy and load demand forecasting in short-horizons, over an interval ranging from one hour to one week, is crucial for on-line scheduling and security functions of power system. Many load forecasting methods have been developed in recent years which are usually complex solutions with many adjustable parameters. Best-matching models and their relevant parameters have to be determined in a search procedure. We propose a hybrid...
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Prediction based on integration of Decisional DNA and a feature selection algorithm Relief-F
PublicationThe paper presents prediction model based on Decisional DNA and Set of experienced integrated with Relief_F algorithm for feature selection
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Adaptation of Architectural Heritage in the Era of Climate Change. Torpedo Platform in Babie Doły
PublicationThe paper provides original insight into the problem of adap¬tation of historical objects in the era of climate change. It conveys a message that in times of climate crisis, there is a need to go beyond an anthropocentric perspective, specifically, that architec¬ture should not only be designed for people, but should also provide a framework for nature. As well as shaping spaces for human beings, the architect is also responsible...
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Evaluation of the prediction ability of air pollutants based on the electronic nose responses
PublicationElectronic noses are able to perform on-line measurements of the toxic volatile compounds in air. Due to their low cost and compact size they can be placed in the areas exposed to pollution, outside the laboratory. Those advantages, on the other side, force the need for development of the reliable sensors data analysis procedures. One of the most important issues connected with electronic noses is the lack of stability of the gas...
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Impact of AlphaFold on structure prediction of protein complexes: The CASP15‐CAPRI experiment
PublicationWe present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody–antigen complexes, and 7 large assemblies. On average 70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups...
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublicationIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.
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Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
PublicationBackground: In the context of Warehouse Management Systems, knowledge related to motion trajectory prediction methods utilizing machine learning techniques seems to be scattered and fragmented. Objective: This study seeks to fill this research gap by using a systematic literature review approach. Methods: Based on the data collected from Google Scholar, a systematic literature review was performed, covering the period from 2016...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublicationPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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NUMERICAL ESTIMATION OF HULL HYDRODYNAMIC DERIVATIVES IN SHIP MANOUVERING PREDICTION
PublicationOperating in crowded waterways pose a risk of accidents and disasters due to maneuvering limitations of the ship. In order to predict ship’s maneuvering characteristics at the design stage, model tests are often executed as the most accurate prediction tool. Two approaches can be distinguished here: free running model tests and numerical simulations based on planar motion model with the use of hydrodynamic derivatives obtained...
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METHOD FOR SHIP'S ROLLING PERIOD PREDICTION WITH REGARD TO NON-LINEARITY OF GZ CURVE
PublicationThe paper deals with the problem of prediction of the rolling period. A special emphasis is put on the practical application of the new method for rolling period prediction with regard to non-linearity of the GZ curve. The one degree-of-freedom rolling equation is applied with using the non-linear stiffness moment and linear damping moment formulas. A number of ships are considered to research the discrepancies between the pending...
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Personal bankruptcy prediction using machine learning techniques
PublicationIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
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Prediction of coking dynamics for wet coal charge
PublicationA one-dimensional transient mathematical model describing thermal and flow phenomena during coal coking in an oven chamber was studied in the paper. It also accounts for heat conduction in the ceramic oven wall when assuming a constant temperature at the heating channel side. The model was solved numerically using partly implicit methods for gas flow and heat transfer problems. The histories of temperature, gas evolution and internal...
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ColorNephroNet: Kidney tumor malignancy prediction using medical image colorization
PublicationRenal tumor malignancy classification is one of the crucial tasks in urology, being a primary factor included in the decision of whether to perform kidney removal surgery (nephrectomy) or not. Currently, tumor malignancy prediction is determined by the radiological diagnosis based on computed tomography (CT) images. However, it is estimated that up to 16% of nephrectomies could have been avoided because the tumor that had been...
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Evaluati on of long-term start up costs impact on short-term price based operational optimization of a CCGT using MILP
PublicationAn increasing share of the weather-dependent RES generation in the power system leads to the growing importance of flexibility of conventional power plants. They were usually designed for base load operation and it is a challenge to determine the actual long-term cycling costs, which account for an increase in maintenance and overhaul expenditures, increased forced outage rates and shortened life expectancy of the plant and components....
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The Effect of CO2 Gas Emissions on the Market Value, Price and Shares Returns
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Accounting Quality and Audit Attributes on the Stock Price Crashes in an Emerging Market
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The evolution of market integration between the eu and poland - price and trade approach
Publicationw artykule przedstawiono dwa podejscia do mierzenia integracji ekonomicznej tj. podejscie od strony cen i podejscie od strony przepływów handlowych. na podstawie 49 wyselekcjonowanych cen produków oraz danych o wolumenie i wartosci eksportu i importu tych produktów autorki wyliczyły przy zastosowaniu wybranych modeli panelowych stopień rynkowej integracji między Polską a krajami UE15.