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Search results for: CORPORATE BANKRUPTCY PREDICTION
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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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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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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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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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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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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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Corporate Finance summer sem. 2022/2023
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Prediction of Processor Utilization for Real-Time Multimedia Stream Processing Tasks
PublicationUtilization of MPUs in a computing cluster node for multimedia stream processing is considered. Non-linear increase of processor utilization is described and a related class of algorithms for multimedia real-time processing tasks is defined. For such conditions, experiments measuring the processor utilization and output data loss were proposed and their results presented. A new formula for prediction of utilization was proposed...
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Algorithms for Ship Movement Prediction for Location Data Compression
PublicationDue to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated...
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Category-Based Workload Modeling for Hardware Load Prediction in Heterogeneous IaaS Cloud
PublicationThe paper presents a method of hardware load prediction using workload models based on application categories and high-level characteristics. Application of the method to the problem of optimization of virtual machine scheduling in a heterogeneous Infrastructure as a Service (IaaS) computing cloud is described.
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Preeclampsia Risk Prediction Using Machine Learning Methods Trained on Synthetic Data
PublicationThis paper describes a research study that investigates the use of machine learning algorithms on synthetic data to classify the risk of developing preeclampsia by pregnant women. Synthetic datasets were generated based on parameter distributions from three real patient studies. Four models were compared: XGBoost, Support Vector Machine (SVM), Random Forest, and Explainable Boosting Machines (EBM). The study found that the XGBoost...
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Rhamnolipid CMC Prediction
PublicationRelationships between the purity, pH, hydrophobicity (log Kow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure–property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered....
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Vibro piles performance prediction using result of CPT
PublicationVibro piles belong to the group of full displacement piles with an expanded base, characterised by a very high load capacity, especially in non-cohesive soils. The problem is to adopt a reliable method for the determination of full load–settlement (Q–s) curve. A frequent difficulty is the determination of the load capacity limit based on the static load test because the course of the load–settlement curve is of a linear nature....
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Warning systems of enterprises against the risk of bankruptcy : Artificial intelligence in financial management.
PublicationJest to tłumaczenie na jęz.angielski monografii autora z 2010 roku. Monografia została podzielona na trzy części. I tak, w części pierwszej przedstawiono ocenę przyczyn upadłości firm ze względu nie tylko na źródło (zewnętrzne lub wewnętrzne) przyczyn kłopotów finansowych przedsiębiorstw, ale także na etap kryzysu, w jakim ono się znajduje, cechy "demograficzne" organizacji i rodzaj upadłości. Zdefiniowano również czynniki wpływające...
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A CNN based coronavirus disease prediction system for chest X-rays
PublicationCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...
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Color prediction from first principle quantum chemistry computations: a case of alizarin dissolved in methanol
PublicationThe electronic spectrum of alizarin (AZ) in methanol solution was measured and used as reference data for color prediction. The visible part of the spectrum was modelled by different DFT functionals within the TD-DFT framework. The results of a broad range of functionals applied for theoretical spectrum prediction were compared against experimental data by a direct color comparison. The tristimulus model of color expressed in terms...
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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...
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Corporate social responsibility (CSR) and sustainable development during the Covid-19 pandemic
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Personal Branding in the Knowledge Economy: The Inter-relationship between Corporate and Employee Brands
Publicationhttps://www.taylorfrancis.com/books/mono/10.4324/9781003178248/personal-branding-knowledge-economy-wioleta-kucharska
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Robust Parameter Estimation and Output Prediction for Reactive Carrier-Load Nonlinear Dynamic Networks
PublicationIn this paper an extension of on-line model simplification technique for a class of networked systems, namely reactive carrier-load nonlinear dynamic networked system (RCLNDNS), kept within point-parametric model (PPM) framework is addressed. The PPM is utilised to acquire a piece wise constant time-varying parameter linear structure for the RCLNDNS suitable for the on-line one step ahead prediction that may be applied to monitoring...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublicationIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Coastal Cliffs Monitoring and Prediction of Displacements Using Terrestial Laser Scanning
PublicationCoastal cliffs are very sensitive to degradation caused by erosion and abrasion. Thus, it is very important to monitor susceptibility of the cliffs in terms of slope angles and ground fall resulting from vertical morphology of the cliffs. The results could be used for example to establish the boundaries of the safe investments zone or retreat infrastructure buildings in case of real threat such as degradation of the objects of...
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Electromagnetic interference frequencies prediction model of flyback converter for snubber design
PublicationSnubber design for flyback converters usually requires experimental prototype measurements or simulation based on accurate and complex models. In this study simplified circuit modelling of a flyback converter has been described to dimension snubbers in early stage of design process. Simulation based prediction of the transistor and diode ringing frequencies has been validated by measurements in a prototype setup. In that way obtained...
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CORPORATE GOVERNANCE-AN INTERNATIONAL REVIEW
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Corporate Communications: an International Journal
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Journal of Corporate Accounting and Finance
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Journal of Corporate Real Estate
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Journal of Corporate Law Studies
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Journal of Applied Corporate Finance
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Review of Corporate Finance Studies
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Indian Journal of Corporate Governance
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Corporate and Business Strategy Review
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EVALUATION OF THE NO2CONCENTRATION PREDICTION POSSIBILITYBASED ON STATIC AND DYNAMIC RESPONSES OF TGS SENSORSAT CHANGING HUMIDITY LEVELS
PublicationThe commercially available metal-oxide TGS sensors are widely used in many applications due to thefact that they are inexpensive and considered to be reliable. However, they are partially selective and theirresponses are influenced by various factors,e.g. temperature or humidity level. Therefore, it is importanttodesign a proper analysis system of the sensor responses. In this paper, the results of examinations of eightcommercial...
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Integrated information and prediction Web Service WaterPUCK General concept
PublicationIn this paper, general concept of a new method as ‘Integrated information and prediction Web Service WaterPUCK’ for investigation influence of agricultural holdings and land-use structures on coastal waters of the southern Baltic Sea is presented. WaterPUCK Service is focused on determination of the current and future environmental status of the surface water and groundwater located in the Puck District (Poland) and its impact...
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Prediction of manoeuvring abilities of 10000 DWT pod-driven coastal tanker
PublicationThis paper aims to present a new approach in the prediction of manoeuvring abilities of pod-driven ships. A new mathematical model of motions based on MMG methodology was developed and a new type of description of forces acting on azimuth drives is presented. Captive model tests of medium-size coastal tanker and pod open water tests were carried out in CTO S.A. (Ship Design and Research Centre S.A.) to obtain hull hydrodynamic derivatives...
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Wioleta Kucharska dr hab. inż.
PeopleWioleta Kucharska (Associate Professor at the Faculty of Management and Economics of the Gdansk University of Technology, Fahrenheit Universities Union, Poland), published so far with Wiley, Springer, Taylor & Francis, Emerald, Sage, Elsevier, and Routledge. She is scientifically involved in tacit knowledge and the company culture of knowledge, learning, and collaboration (KLC approach) topics. Recently, she discovered the...
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Robust output prediction of differential – algebraic systems – application to drinking water distribution system
PublicationThe paper presents the recursive robust output variable prediction algorithm, applicable for systems described in the form of nonlinear algebraic-differential equations. The algorithm bases on the uncertainty interval description, the system model, and the measurements. To improve the algorithm efficiency, nonlinear system models are linearised along the nominal trajectory. The effectiveness of the algorithm is demonstrated on...
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Rapid antenna design optimization using shape-preserving response prediction
PublicationAn approach to rapid optimization of antennas using the shape-preserving response-prediction (SPRP) technique and coarsediscretization electromagnetic (EM) simulations (as a low-fidelity model) is presented. SPRP allows us to estimate the response of the high-fidelity EM antenna model, e.g., its reflection coefficient versus frequency, using the properly selected set of so-called characteristic points of the low-fidelity model...
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Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
PublicationThe described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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A Fast Prediction of the OCR Results Based on Binary Image Quality Assessment Methods
PublicationSince the first step of the Optical Character Recognition (OCR) procedure is usually image binarization and the execution of the OCR process takes longer time than image quality assessment (IQA) of binary images, a fast prediction of the OCR results before text recognition would be interesting for non-uniformly illuminated document images, also for applications in mobile devices. Since IQA methods for binary images usually require...
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How to survive a pandemic: The corporate resiliency of travel and leisure companies to the COVID-19 outbreak
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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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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...