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Search results for: crash prediction model
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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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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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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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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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Accurate modelling of microwave structures using shape-preserving response prediction
PublicationArtykuł prezentuje metodologię dokładnego modelowania struktur mikrofalowych. Jest to zmodyfikowana wersja techniki opartej na procedurze przewidywania odpowiedzi z zachowaniem kształtu (shape-preserving response prediction, SPRP), która oszacowuje odpowiedź struktury mikrofalowej otrzymanej poprzez kosztowną obliczeniowo symulację elektromagnetyczną za pomocą taniego obliczeniowo modelu tejże struktury. Modyfikacja polega na wykorzystaniu...
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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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Increasing the rate of sustainable change: a call for a redefinition of the concept and the model for its implementation
PublicationW pracy dokonano analizy problemu dużej rozbieżności pomiędzy zaproponowanymi strategiami a efektywnością akcji podjętych w celu wprowadzenia w praktyce zasad zrównoważonego rozwoju. Podkreślono konieczność współpracy różnych organizacji i samorządów lokalnych oraz uwzględniono rolę szkół wyższych w procesie wprowadzania zasad zrównoważonego rozwoju.
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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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AN INNOVATIVE APPROACH TO PREDICTION ENERGETIC EFFECTS OF WOOD CUTTING PROCESS WITH CIRCULAR-SAW BLADES
PublicationIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. The aim of the paper is to present a new calculating model using the application of modern fracture mechanics and to compare cutting parameters of native beech, Bendywood...
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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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Discrete-Element bonded particle Sea Ice model DESIgn, version 1.3 – model description and implementation
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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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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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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublicationNowadays, due to improvements in seismic codes and computational devices, retrofitting buildings is an important topic, in which, permanent deformation of buildings, known as Residual Interstory Drift Ratio (RIDR), plays a crucial role. To provide an accurate yet reliable prediction model, 32 improved Machine Learning (ML) algorithms were considered using the Python software to investigate the best method for estimating Maximum...
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Evaluation the environmental fate of pharmaceuticals using a level III model based on poly-parameter linear free energy relationships
PublicationOpisano możliwości zastosowania modelu ''Level III Model'' do opisu losu środowiskowego pozostałości farmaceutyków w środowisku. Zastosowany model umożliwia oszacowanie trwałości, stężeń oraz transportu poszczególnych zanieczyszczeń pomiędzy poszczególnymi elementami składowymi środowiska (powietrze, woda, gleba i osady denne).
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Seismic response and performance prediction of steel buckling-restrained braced frames using machine-learning methods
PublicationNowadays, Buckling-Restrained Brace Frames (BRBFs) have been used as lateral force-resisting systems for low-, to mid-rise buildings. Residual Interstory Drift (RID) of BRBFs plays a key role in deciding to retrofit buildings after seismic excitation; however, existing formulas have limitations and cannot effectively help civil engineers, e.g., FEMA P-58, which is a conservative estimation method. Therefore, there is a need to...
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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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Fatigue life prediction of notched components under size effect using strain energy reformulated critical distance theory
PublicationNotch and size effects show significant impact on the fatigue performance of engineering components, which deserves special attention. In this work, a strain energy reformulated critical distance theory was developed for fatigue life prediction of notched components under size effect. Experimental data of different notched specimens manufactured from GH4169, TC4, TC11 alloys and low carbon steel En3B were used for model validation...
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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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Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries
PublicationCatheter-induced dissections (CID) of coronary arteries and/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified...
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On Bayesian Tracking and Prediction of Radar Cross Section
PublicationWe consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach...
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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...
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Identification of ship’s hull mathematical model with numerical methods
PublicationThe modern maritime industry is moving toward the development of technology that will allow for full or partial autonomy of ship operation. This innovation places high demands on ship performance prediction techniques at the design stage. The researchwork presented in the article is related to the design stage of the ship and concerns methods for prognosis and evaluation of the specific operational condition of the ship, namely...
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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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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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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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Experimental guinea pig model of dermatophytosis: a simple and useful tool for the evaluation of new diagnostics and antifungals
PublicationCelem badań było opracowanie prostego modelu zwierzęcego (świnki morskie) odpowiedniego do sprawdzania systemów diagnostycznych oraz terapii infekcji dermatofitów. Następujące zmienne były analizowane: przygotowanie skóry przez golenie versus użycie taśmy, testowy szczep Microsporum canis czy Trichophyton mentagrophytes jako czynnik etiologiczny, sposób inokulacji. Przebieg infekcji był oceniany poprzez ocenę zaczerwienienia i...
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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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Ductile fracture prediction in thin metallic plates subjected to explosions
PublicationPraca dotyczy modelowania zniszczenia ciągłego. Zaprezentowano wyniki eksperymentów przeprowadzonych na płytach metalowych poddanych eksplozjom oraz wyniki jednoosiowych prób laboratoryjnych. Opisano przyjęty model prawa konstytutywnego oraz kryteriów zniszczenia. Przedstawiono identyfikację parametrów materiałowych dla przyjętego modelu. Zaprezentowano model numeryczny oraz wyniki symulacji które następnie porównano z wynikami...
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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...
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Survival time prognosis under a Markov model of cancer development
PublicationIn this study we look at a breast cancer data set of women from Pomerania region collected in year 1987-1992 in the Medical University of Gdańsk. We analyze the clinical risk factors in conjunction with Markov model of cancer development. We evaluate Artificial Neural Network (ANN) survival time prediction via a simulation study.
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Electrochemical simulation of metabolism for antitumor-active imidazoacridinone C-1311 and in silico prediction of drug metabolic reactions
PublicationThe metabolism of antitumor-active 5-diethylaminoethylamino-8-hydroxyimidazoacridinone (C-1311) has been investigated widely over the last decade but some aspects of molecular mechanisms of its metabolic transformation are still not explained. In the current work, we have reported a direct and rapid analytical tool for better prediction of C-1311 metabolism which is based on electrochemistry (EC) coupled on-line with electrospray...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Quality prediction of foil capacitors by acoustic emission signals
PublicationJakość i trwałość kondensatorów foliowych jest zależna od ich warunków pracy (np. nadmiarowego napięcia pracy, temperatury, wilgotności) oraz od potencjalnych defektów wprowadzonych na różnych etapach wytwarzania kondensatorów. Nieustanny nacisk na wzrost jakości wytwarzanych elementów przy jednoczesnej redukcji kosztów wytwarzania oznacza, że nowe, tanie i szybkie metody predykcji jakości tych elementów są mocno poszukiwane. W...
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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublicationLogit and discriminant analyses have been used for corporate bankruptcy prediction in several studies since the last century. In recent years there have been dozens of studies comparing the several models available, including the ones mentioned above and also probit, artificial neural networks, support vector machines, among others. For the first time for Colombia, this paper presents a comparative analysis of the effectiveness...
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Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
PublicationThe aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy (CRT) response and phenotyping of patients eligible for CRT implantation. This systematic review was performed...
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Adaptive prediction of stock exchange indices by state space wavelet networks
PublicationThe paper considers the forecasting of the Warsaw Stock Exchange price index WIG20 by applying a state space wavelet network model of the index price. The approach can be applied to the development of tools for predicting changes of other economic indicators, especially stock exchange indices. The paper presents a general state space wavelet network model and the underlying principles. The model is applied to produce one session...
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Strain energy density and entire fracture surface parameters relationship for LCF life prediction of additively manufactured 18Ni300 steel
PublicationIn this study, the connection between total strain energy density and fracture surface topography is investigated in additively manufactured maraging steel exposed to low-cycle fatigue loading. The specimens were fabricated using laser beam powder bed fusion (LB-PBF) and examined under fully-reversed strain-controlled setup at strain amplitudes scale from 0.3% to 1.0%. The post-mortem fracture surfaces were explored using a non-contact...
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CoRBAC – kontekstowo zorientowany model bezpieczeństwa
PublicationZaproponowano uogólniony model kontroli dostępu do usługowych systemów internetowych uwzględniający różne kategorie kontekstu. Określono wpływ kontekstu na model jak i architekturę systemu bezpieczeństwa. Podano przykład implementacji modelu i architektury bezpieczeństwa dla zestawu usług dotyczących e-uczelni i wstępnie oszacowano zalety takiego rozwiązania.
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Model of identification of events and accident scenarios for a method of risk and safety assessment of ships in damaged conditions
PublicationW pracy opisano podstawowe problemy związane z identyfikacją zdarzeń i scenariuszy wypadku oraz modelowaniem ryzyka dla alternatywnej metody oceny bezpieczeństwa statków w stanie uszkodzonym. Zastosowano podejście do bezpieczeństwa statków oparte na ocenie zachowania się statku i ocenie ryzyka wypadku. Wskazano możliwości zastosowania modelowania do analizy bezpieczeństwa statków na etapie projektowania, w czasie eksploatacji i...
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COMPARISON OF BLOOD PRESSURE PREDICTION METHODS
PublicationIn the paper dierent approaches of predicting blood pressure values are presented. Basically, two methods and theirs modifications are considered. In total, seven algorithms have been examined. Tests have been conducted using both synthetic and clinical data. From our study it follows that none of the examined methods is superior to other.
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Toward Prediction of Environmental Arctic Change
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numerical prediction of vortex generated by hydrofoil
PublicationW pracy przedstawiono wyniki obliczeń programami Fluent i Comet dla płata śruby napędowej. Pola prędkości oraz wirowość za płatem porównano z wynikami pomiarów (LDA- Laser Doppler Anemometry) w tunelu kawitacyjnym Centrum Techik Okrętowych (CTO). Przedstawiono wpływ adaptacji siatki wg różnych kryteriów (lokalnej wirowości lub prędkości) na zgodność wyników obliczeń z danymi eksperymentalnymi.