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Search results for: PREDICTION
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Early prediction of macrocrack location in concrete and other granular composite materials
PublicationHeterogeniczne kruche kompozyty, takie jak beton, ceramika i skały składają się z ziaren połączonych wiązaniami. Pytanie, czy ścieżka pęknięcia, która prowadzi do zniszczenia może być przewidziania na podstawie znanych cech mikrostrukturalnych, a mianowicie łączności wiązań, rozmiaru, energii pękania, wytrzymałości pozostają otwarte. Istnieje wiele kryteriów pęknięć. Najczęściej używane są oparte na postulowanym ekstremum naprężenia...
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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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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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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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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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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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Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries
PublicationIn developed countries, the first studies on forecasting bankruptcy date to the early 20th century. In Central and Eastern Europe, due to, among other factors, the geopolitical situation and the introduced economic system, this issue became the subject of researcher interest only in the 1990s. Therefore, it is worthwhile to analyze whether these countries conduct bankruptcy risk assessments and what their level of advancement is....
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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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Towards trustworthy multi‐modal motion prediction: Holistic evaluation and interpretability of outputs
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The Round Robin approach applied to nanoinformatics: consensus prediction of nanomaterials zeta potential
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Self-Concept Clarity and Religious Orientations: Prediction of Purpose in Life and Self-Esteem
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Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field
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Recent improvements in prediction of protein structure by global optimization of a potential energy function
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Hybrid Numerical-Analytical Approach for Force Prediction in End Milling of 42CrMo4 Steel
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Risk factors assessment and risk prediction models in lung cancer screening candidates
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Empirical verification in industrial conditions of fracture mechanics models of cutting power prediction
PublicationA comparison of experimental results obtained in the industrial conditions at a sawmill located in the Baltic Natural Forest Region (PL) and theoretical cutting power consumption forecasted with the models which include work of separation (fracture toughness) in addition to plasticity and friction has been described. In computations of cutting power consumption during rip sawing of Scots pine wood (Pinus sylvestris L.) values of...
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Prediction of flow boiling heat transfer data for R134a, R600a and R290 in minichannels
PublicationIn the paper presented is the analysis of the results of calculations using a model to predict flow boiling of refrigerants such as R134a, R600a and R290. The latter two fluids were not used in development of model semiempirical correction. For that reason the model was verified with present experimental data. The experimental research was conducted for a full range of quality variation and a relatively wide range of mass velocity....
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Autocovariance based weighting strategy for time series prediction with weighted LS-SVM
PublicationPrzedstawiono metodę konstrukcji algorytmów z funkcją jądra, a także dwa algorytmy uzyskane poprzez użycie różnych funkcji straty. Zaproponowano kowariacyjną strategię ważenia algorytmów z kwadratową funkcją straty do problemu predykcji chaotycznych przebiegów czasowych.
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Failure mode prediction for composite structural insulated panels with MgO board facings
PublicationSandwich panels are readily used in civil engineering due to their high strength to weight ratio and the ease and speed of assembly. The idea of a sandwich section is to combine thin and durable facings with a light-weight core and the choice of materials used allows obtaining the desired behaviour. Panels in consideration consist of MgO (magnesium oxide) board facings and expanded polystyrene core and are characterized by immunity...
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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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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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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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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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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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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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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models
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An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12
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Artificial Neural Network (ANN)-Based Voltage Stability Prediction of Test Microgrid Grid
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Prediction of cutting forces during micro end milling considering chip thickness accumulation
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Is the Identification of SNP-miRNA Interactions Supporting the Prediction of Human Lymphocyte Transcriptional Radiation Responses?
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Prediction of Early Childhood Caries Based on Single Nucleotide Polymorphisms Using Neural Networks
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Prediction of the Segmental Pelvic Ring Fractures Under Impact Loadings During Car Crash
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Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines
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Prediction of flow boiling heat transfer coefficient for carbon dioxide in minichannels and conventional channels
PublicationIn the paper are presented the results of calculations using authors own model to predict heat transfer coefficient during flow boiling for carbon dioxide. The experimental data from various researches were scrutinised conducted for a full range of quality variation and wide range of mass velocity. The aim of the study was to test the sensitivity of the in-house model. The work shows the importance of taking into account surface...
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A prediction of the fault-induced instability of circuit under test as a new approach in categorisation of faults.
PublicationW artykule przedstawiono nowy sposób kategoryzacji uszkodzeń w analogowych układach elektronicznych. Zaproponowano kryterium oparte na predykcji niestabilności indukowanej przez uszkodzenie w testowanym układzie. Przyjeto, że granicą pomiędzy uszkodzeniem miękkim i katastroficznym jest najmniejsza odchyłka parametru elementu, która sprowadza układ testowany do granicy stabilności. Wzrost wartości odchyłki poza wyznaczony margines...
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Ship weather routing optimization with dynamic constraints based on reliable synchronous roll prediction
PublicationShip routing process taking into account weather conditions is a constrained multi-objective optimization problem and it should consider various optimization criteria and constraints. Formulation of a stability-related, dynamic route optimization constraint is presented in this paper. One of the key objectives of a cross ocean sailing is finding a compromise between ship safety and economics of operation. This compromise should...
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Prediction of corrosion fatigue crack propagation life for welded joints under cathodic potentials
PublicationPrzy ochronie katodowej poniżej potencjału optymalnego obserwuje się przyspieszenie propagacji pęknięcia korozyjno-zmęczeniowego w porównaniu do konstrukcji nie chronionej. Zaproponowano własną formułę empiryczną na wpływ potencjału ochronnego na prędkość propagacji pęknięcia oraz własny wzór na [delta]K w złączu pachwinowym. Wyprowadzono wzór na krzywą ''S-Np'' (naprężenie - długość okresu propagacji pęknięcia). Zaprezentowana...
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In silico epitope prediction of Borrelia burgdorferi sensu lato antigens for the detection of specific antibodies
PublicationDespite many years of research, serodiagnosis of Lyme disease still faces many obstacles. Difficulties arise mainly due to the low degree of amino acid sequence conservation of the most immunogenic antigens among B. burgdorferi s.l. genospecies, as well as differences in protein production depending on the environment in which the spirochete is located. Mapping B-cell epitopes located on antigens allows for a better understanding...
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Prediction of the fatigue lifetime of PUR structural elements using a combined experimental-numerical approach
PublicationThis paper presents a method for estimating the fatigue life of polyurethane elastomeric components. A rubber replacement - polyurethane of hardness 80ShA commonly used in vibration damping systems, for example, in motor vehicle suspensions, was used for the study. A metal-rubber bushing component was selected for analysis, and numerical analysis was carried out along with a fatigue model proposal based on a modification of the...
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Prediction of the Mechanical Properties of P91 Steel by Means of Magneto-acoustic Emission and Acoustic Birefringence
PublicationThe paper describes an application of nondestructive volumetric magnetic and ultrasonic techniques for evaluation of the selected mechanical parameter variations of P91 steel having direct influence on its suitability for further use in critical components used in power plants. Two different types of deformation processes were carried out. First, a series of the P91 steel specimens was subjected to creep and second, one to plastic...
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Wind resource assessment and energy yield prediction for the small wind turbine on the Szubieniczne Hill
PublicationThe goal of this study is to preliminary assess the wind resources on the Szubieniczne Hill in order to predict the annual energy production for planned small wind turbine. The analyzed site is located close to the Gdańsk University of Technology campus, in complex urban environment additionally surrendered by forested hills. The assessment is based on Computational Fluid Dynamics simulations which allow to evaluate the wind energy potential...
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Prediction of flow boiling heat transfer coefficient for carbon dioxide in minichannels and conventional channels
PublicationIn the paper presented are the results of calculations using authors own model to predict heat transfer coefficient during flow boiling of carbon dioxide. The experimental data from various resea rches were collected. Calculations were conducted for a full range of quality variation and a wide range of mass velocity. The aim of the study was to test the sensitivity of the in-house model. The results show the importance of taking into...
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New, fast and cheap prediction tests for BRCA1 gene mutations identification in clinical samples.
PublicationDespite significant progress in cancer therapy, cancer is still the second cause of mortality in the world. The necessity to make quick therapeutic decisions forces the development of procedures allowing to obtain a reliable result in a quick and unambiguous manner. Currently, detecting predictive mutations, including BRCA1, is the basis for effectively treating advanced breast cancer. Here, we present new insight on gene mutation...
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Vessel Energy Requirement Prediction from Acceleration Stage Towing Tests on Scale Models
PublicationOne of the most crucial tasks for naval architects is computing the energy required to meet the ship’s operational needs. When predicting a ship’s energy requirements, a series of hull resistance tests on a scale model vessel is carried out in constant speed stages, while the acceleration stage measurements are ignored. Another important factor in seakeeping analysis is the ship’s hydrodynamic added mass. The second law of dynamics...
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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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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...