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Wyniki wyszukiwania dla: PREDICTION
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublikacjaControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
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Fatigue life prediction of notched components under size effect using strain energy reformulated critical distance theory
PublikacjaNotch 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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A comparative analysis of the effectiveness of corporate bankruptcy prediction models based on financial ratios: Evidence from Colombia, 2008 to 2015
PublikacjaLogit 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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Strain energy density and entire fracture surface parameters relationship for LCF life prediction of additively manufactured 18Ni300 steel
PublikacjaIn 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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Prediction of Bioactive Peptides From Chicken Feather and Pig Hair Keratins Using In Silico Analysis Based on Fragmentomic Approach
PublikacjaBackground: Keratin is among the most abundant structural proteins of animal origin, however it remains broadly underutilized. Objective: Bioinformatic investigation was performed to evaluate selected keratins originating from mass-produced waste products, i.e., chicken feathers and pig hair, as potential sources of bioactive peptides. Methods: Pepsin, trypsin, chymotrypsin, papain, and subtilisin were used for in silico keratinolysis...
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Prediction of metal deformation due to line heating; an alternative method of mechanical bending, based on artificial neural network approach
PublikacjaLine heating is one of the alternative methods of forming metals and this kind of forming uses the heating torch as a source of heat input. During the process, many parameters are considered like the size of the substrate, thickness, cooling method, source power intensity, the travel speed of the power source, the sequence of heating, and so on. It is important to analyze the factors affecting the...
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Application of a hybrid mechanistic/machine learning model for prediction of nitrous oxide (N2O) production in a nitrifying sequencing batch reactor
PublikacjaNitrous oxide (N2O) is a key parameter for evaluating the greenhouse gas emissions from wastewater treatment plants. In this study, a new method for predicting liquid N2O production during nitrification was developed based on a mechanistic model and machine learning (ML) algorithm. The mechanistic model was first used for simulation of two 15-day experimental trials in a nitrifying sequencing batch reactor. Then, model predictions...
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Use of the UNRES force field in template-assisted prediction of protein structures and the refinement of server models: Test with CASP12 targets
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Prediction of protein structure using a knowledge-based off-lattice united-residue force field and global optimization methods
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Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
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Prediction of near-bottom water salinity in the Baltic Sea using Ordinary Least Squares and Geographically Weighted Regression models
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Prediction of Stress and Deformation Caused by Magnetic Attraction Force in Modulation Elements in a Magnetically Geared Machine Using Subdomain Modeling
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Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
PublikacjaThe genome feature of SARS-CoV-2 leads the virus to mutate and creates new variants of concern. Tackling viral mutations is also an important challenge for the development of a new vaccine. Accordingly, in the present study, we undertook to identify B- and T-cell epitopes with immunogenic potential for eliciting responses to SARS-CoV-2, using computational approaches and its tailoring to coronavirus variants. A total of 47 novel...
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Prediction of Ship Resonant Rolling - Related Dangerous Zones with Regard to the Equivalent Metacentric Height Governing Natural Frequency of Roll
PublikacjaPotentially dangerous zones corresponding to dynamical stability phenomena, possibly encountered by ships sailing in rough sea, are estimated nowadays with the use of the method recommended by IMO in the guidance coded MSC.1/Circ.1228. In this IMO method the parameter governing the natural period of roll is the initial metacentric height. Some earlier studies revealed that the initial metacentric height...
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Fracture prediction in flat PMMA notched specimens under tension - effectiveness of the equivalent material concept and fictitious material concept
PublikacjaThe fracture of notched elements under mode I loading (tension) remains an inexhaustible research topic, especially when it comes to the fracture of thermoplastic materials such as polymethylmethacrylate (PMMA), which experience considerable plastic strains under tension. The paper points out that traditional brittle fracture criteria such as mean stress (MS) or maximum tangential stress (MTS) criteria used to predict this phenomenon do...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublikacjaRegarding the unpredictable and complex nature of seismic excitations, there is a need for vulnerability assessment of newly constructed or existing structures. Predicting the seismic limit-state capacity of steel Moment-Resisting Frames (MRFs) can help designers to have a preliminary estimation and improve their views about the seismic performance of the designed structure. This study improved data-driven decision techniques in...
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High temperature corrosion evaluation and lifetime prediction of porous Fe22Cr stainless steel in air in temperature range 700–900 °C
PublikacjaThis work describes a high temperature corrosion kinetics study of ~30% porous Fe22Cr alloys. The surface area of the alloy (~0.02 m2 g-1) has been determined by tomographic microscopy. The weight gain of the alloys was studied by isothermal thermogravimetry in the air for 100 hours at 700 - 900 °C. Breakaway oxidation was observed after oxidation at 850 °C (~100 hours) and 900 °C (~30 hours). The lifetime prediction shows the...
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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Use of Restraints from Consensus Fragments of Multiple Server Models To Enhance Protein-Structure Prediction Capability of the UNRES Force Field
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Protein structure prediction with the UNRES force-field using Replica-Exchange Monte Carlo-with-Minimization; Comparison with MCM, CSA, and CFMC
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Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: Assessment in two blind tests
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Teicoplanin-Modified HPLC Column as a Source of Experimental Parameters for Prediction of the Anticonvulsant Activity of 1,2,4-Triazole-3-Thiones by the Regression Models
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Machine learning-based prediction of residual drift and seismic risk assessment of steel moment-resisting frames considering soil-structure interaction
PublikacjaNowadays, 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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Validation study on a new semi-empirical method for the prediction of added resistance in waves of arbitrary heading in analyzing ship speed trial results
PublikacjaThis paper describes an open and extensive validation study carried out by the Specialist Committee on Ships in Operation at Sea (SOS) of the International Towing Tank Conference (ITTC) on the newly developed SHOPERA-NTUA-NTU-MARIC (SNNM) wave-added resistance prediction method. The SNNM method aims at a simple, fast and transparent determination of the added resistance in regular waves of arbitrary encounter directions, even when...
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Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information
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Validation study on a new semi-empirical method for the prediction of added resistance in waves of arbitrary heading in analyzing ship speed trial results
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Trends in In Silico Approaches to the Prediction of Biologically Active Peptides in Meat and Meat Products as an Important Factor for Preventing Food-Related Chronic Diseases
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublikacjaPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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Modelowanie przepływu wód podziemnych w strefie brzegowej morza - możliwości prognozowania = Groundwater flow modeling in the coastline area - prediction possibilities
PublikacjaSpecyficzne warunki występowania wód podziemnych w strefie brzegowej morza sprawiają, że ich eksploatacja jest sprawą złożoną i powinna być weryfikowana na modelu numerycznym. Zasadniczym zagrożeniem jest ingresja słonych wód morskich, która może być wzbudzona eksploatacją. Innym czynnikiem, który może przyczynić się do ingresji wód słonych do warstwy wodonośnej może być podniesienie się poziomu morza. W pracy przedstawiono wyniki...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublikacjaWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Parametrization of Backbone−Electrostatic and Multibody Contributions to the UNRES Force Field for Protein-Structure Prediction from Ab Initio Energy Surfaces of Model Systems
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Potential of Serum Proteome Patterns Analysis by MALDI-TOF Mass Spectrometry for Prediction of Acute Radiation Injury Response in Head and Neck Cancers Patients
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Prediction of Overall In Vitro Microsomal Stability of Drug Candidates Based on Molecular Modeling and Support Vector Machines. Case Study of Novel Arylpiperazines Derivatives
PublikacjaOther than efficacy of interaction with the molecular target, metabolic stability is the primary factor responsible for the failure or success of a compound in the drug development pipeline. The ideal drug candidate should be stable enough to reach its therapeutic site of action. Despite many recent excellent achievements in the field of computational methods supporting drug metabolism studies, a well-recognized procedure to model...
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A Hierarchical Multiscale Approach to Protein Structure Prediction: Production of Low‐Resolution Packing Arrangements of Helices and Refinement of the Best Models with a United‐Residue Force Field
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Wyznaczanie współczynnika przejmowania ciepła podczas wrzenia w przepływie dwutlenku węgla (Prediction of flow boling heat transfer coefficient for carbon dioxide in minichannels)
PublikacjaW pracy przedstawiono wyniki obliczeń uzyskane za pomocą własnego modelu półemirycznego dla wybranych danych eksperymentalnych dla wrzenia w przepływie dwutlenku węgla. Metoda obliczeniowa została zweryfikowana z danymi eksperymentalnymi Docoulombiera i innych (2011) oraz Mastrullo i innych (2009). Badania eksperymentalne dotyczą pełnego zakresu zmienności stopnia suchości oraz zakresu prędkości masowej G=200-1200 kg/m2s. rozwijany...
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Polybrominated diphenyl ether (PBDE) concentrations in dust from various indoor environments in Gdańsk, Poland: Prediction of concentrations in indoor air and assessment of exposure of adults
PublikacjaMonitoring of polybrominated diphenyl ethers (PBDEs) in indoor environments involves the determination of their concentrations in air, airborne particles, and settled dust. Each of these is a source of human exposure to PBDEs. In this study, we attempted to model PBDEs concentrations in various typical indoor environments on the basis of real PBDEs measurements in dust collected from them. The analytical procedure for determining...
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Market Price Prediction of Property Rights from Gas Fired Plants or Plants with Total Installed CHP Source Capacity Below 1 MW until 2025
PublikacjaThe resolution on the Polish Energy Policy until 2030 (PEP-30) was adopted by the Council of Ministers on 10 November 2009. The document specifies the combined electricity and heat generation as a direction of pursuing the goals of energy efficiency, fuel and energy supply security, competitive fuel and energy markets development, and reduction of the energy sector’s environmental impact. PEP-30 assumes that electricity generation...
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Validation of EORTC, CUETO, and EAU risk stratification in prediction of recurrence, progression, and death of patients with initially non–muscle‐invasive bladder cancer (NMIBC): A cohort analysis
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Comparative Study of Pavement Rehabilitation Using Hot in-Place Recycling and Hot-Mix Asphalt: Performance Evaluation, Pavement Life Prediction, and Life Cycle Cost Analysis
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Analiza porównawcza metod predykcji chwili zgodności fazowejw automatycznym synchronizatorze prądnic = Comparison of the methods of prediction time phase coincidence in automatic synchronizer of power generators
PublikacjaW artykule porównano dokładność wybranych metod realizacji warunku fazowego podczas synchronizacji obiektów elektroenergetycznych. Do porównania wybrano trzy metody: liniową, wielomianową oraz metodę adaptacyjnej synchronizacji prądnic z ekstrapolacją funkcją wymierną. Badania przeprowadzono dla różnych warunków pracy. Przyjęto stałą różnicę częstotliwości napięć synchronizowanych obiektów, różnicę częstotliwości zmieniającą się...
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Theoretical designing of selenium heterocyclic non-fullerene acceptors with enhanced power conversion efficiency for organic solar cells: a DFT/TD-DFT-based prediction and understanding
PublikacjaIn this study, we have designed and explored a new series of non-fullerene acceptors for possible applications in organic solar cells. We have designed four molecules named as APH1 to APH4 after end-capped modification of recently synthesized Y6-Se-4Cl molecule. Density functional theory and time dependent-density functional theory have been employed for computing geometric and photovoltaic parameters of the designed molecules....
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Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries (prezentacja na konferencji TWENTY-SIXTH ANNUAL CONFERENCE MULTINATIONAL FINANCE SOCIETY)
PublikacjaUlotka konferencyjna: http://www.mfsociety.org/modules/modMainContent/uploadFiles/miscFiles/1562848077-MFC2019-Booklet-for-Distribution_2019-06-25.pdf
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Cytokine TGFβ Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model Development)
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AOP173 key event associated pathway predictor – online application for the prediction of benchmark dose lower bound (BMDLs) of a transcriptomic pathway involved in MWCNTs-induced lung fibrosis
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Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
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Validation of EORTC, CUETO and EAU risk stratification in prediction of recurrence, progression and death of patients with initially non-muscle invasive bladder cancer (NMIBC): a cohort analysis with systematic review.
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Technical Engine for Democratization of Modeling, Simulations, and Predictions
PublikacjaComputational science and engineering play a critical role in advancing both research and daily-life challenges across almost every discipline. As a society, we apply search engines, social media, and se- lected aspects of engineering to improve personal and professional growth. Recently, leveraging such aspects as behavioral model analysis, simulation, big data extraction, and human computation is gain- ing momentum. The nexus...
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From Scores to Predictions in Multi-Label Classification: Neural Thresholding Strategies
PublikacjaIn this paper, we propose a novel approach for obtaining predictions from per-class scores to improve the accuracy of multi-label classification systems. In a multi-label classification task, the expected output is a set of predicted labels per each testing sample. Typically, these predictions are calculated by implicit or explicit thresholding of per-class real-valued scores: classes with scores exceeding a given threshold value...
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Predictions of cervical cancer identification by photonic method combined with machine learning
PublikacjaCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors...
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Application of Fracture Mechanics for Energetic Effects Predictions While Wood Sawing
PublikacjaIn 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. On the other hand, cutting forces (or power - more interesting from energetic point of view) could be considered from a point of view of modern fracture mechanics. Cutting...
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Large eddy simulation predictions of absolutely unstable round hot jet
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Application of fracture mechanics for energetic effects predictions while wood sawing
PublikacjaIn 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. On the other hand, cutting forces (power) could be considered from a point of view of modern fracture mechanics. Cutting forces may be employed to determine not only toughness...
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Lessons from application of the UNRES force field to predictions of structures of CASP10 targets
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Performance of protein-structure predictions with the physics-based UNRES force field in CASP11
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Forced Degradation Studies of Ivabradine and In Silico Toxicology Predictions for Its New Designated Impurities
PublikacjaAll activities should aim to eliminate genotoxic impurities and/or protect the API against degradation. There is a necessity to monitor impurities from all classification groups, hence ivabradine forced degradation studies were performed. Ivabradine was proved to be quite durable active substance, but still new and with insufficient stability data. Increased temperature, acid, base, oxidation reagents and light were found to cause...
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Forced degradation studies of ivabradine and in silico toxicology predictions for its new designated impurities
PublikacjaAll activities should aim to eliminate genotoxic impurities and/or protect the API againstdegradation. There is a necessity to monitor impurities from all classification groups,hence ivabradine forced degradation studies were performed. Ivabradine was provedto be quite durable active substance, but still new and with insufficient stability data.Increased temperature, acid, base, oxidation reagents and...
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Predictions of cutting power while sawing of birch and beech with the use of modern fracture mechanics
PublikacjaPraca zawiera wyniki badań eksperymentalnych procesu przecinania drewna brzozy i buka piłami o rzazie 2 mm na pilarce ramowej PRW15M. Na podstawie teoretycznego modelu Atkinsa, wyznaczono z danych eksperymentalnych stałe materiałowe (wiązkość i naprężenia tnące w strefie ścinania) i opracowano model do prognozowania mocy skrawania podczas przecinania drewna piłami na pilarce ramowej dla innych wartości rzazu w funkcji posuwu na...
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Structural, functional, and stability change predictions in human telomerase upon specific point mutations,
PublikacjaOverexpression of telomerase is one of the hallmarks of human cancer. Telomerase is important for maintaining the integrity of the ends of chromosomes, which are called telomeres. A growing number of human disease syndromes are associated with organ failure caused by mutations in telomerase (hTERT or hTR). Mutations in telomerase lead to telomere shortening by decreasing the stability of the telomerase complex, reducing its accumulation,...
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Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
PublikacjaBackground. Dapsone (DAP) is an anti-inflammatory and antimicrobial active pharmaceutical ingredient used to treat, e.g., AIDS-related diseases. However, low solubility is a feature hampering its efficient use. Objectives. First, deep eutectic solvents...
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Polystyrene/polybutadiene blends: An analysis of the phase-inversion region and cophase continuity and a comparison with theoretical predictions
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Polystyrene/polybutadiene blends: An analysis of the phase-inversion region and cophase continuity and a comparison with theoretical predictions
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Geographic Information System for Flood Hazard Analysis and Early Warning Using Numerical Weather Predictions
PublikacjaFloods are a phenomenon which causes significant losses of lives as well as property damage, which in turn severely impact the local economy. The nature of a flooding has been well researched, and several methods of flood hazard simulation have been established over the last decades. The current legislation in the European Union requires the Member States to create, maintain and update flood risk and hazard maps, as well as identify...
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Polystyrene/polybutadiene blends: an analysis of the phase inversion regionand cophase continuity and a comparison with theoretical predictions.
PublikacjaMieszaniny przygotowano przez mieszanie w stopie. Występowanie jednego lubobu polimerów w postaci fazy ciągłej stwierdzano przez badanie morfologii przy pomocy skaningowego mikroskopu elektronowego i przez rozpuszczanie jednego ze składników mieszaniny. Badania morfologii mieszanin wykazały, że polistyren występował w postaci globul przy jego zawartości do 30%. Przy zawartości od 40% do 60% obserwowano fazy ciągłe obu...
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ADAPTIVE PREDICTIONS OF THE EURO/ZŁOTY CURRENCY EXCHANGE RATE USING STATE SPACE WAVELET NETWORKS AND FORECAST COMBINATIONS
PublikacjaThe paper considers the forecasting of the euro/Polish złoty (EUR/PLN) spot exchange rate by applying state space wavelet network and econometric forecast combination models. Both prediction methods are applied to produce one-trading-day- ahead forecasts of the EUR/PLN exchange rate. The paper presents the general state space wavelet network and forecast combination models as well as their underlying principles. The state space...
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Evolution of Ag nanostructures created from thin films: UV–vis absorption and its theoretical predictions
PublikacjaAg-based plasmonic nanostructures were manufactured by thermal annealing of thin metallic films. Structure and morphology were studied using scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS). SEM images show that the formation of nanostructures is influenced by the initial layer thickness as well as the...
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Analytical predictions for the buckling of a nanoplate subjected to non-uniform compression based on the four-variable plate theory
PublikacjaIn the present study, the buckling analysis of the rectangular nanoplate under biaxial non-uniform compression using the modified couple stress continuum theory with various boundary conditions has been considered. The simplified first order shear deformation theory (S-FSDT) has been employed and the governing differential equations have been obtained using the Hamilton’s principle. An analytical approach has been applied to obtain...
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Rapid increase in the incidence of type 1 diabetes in Polish children from 1989 to 2004, and predictions for 2010 to 2025
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Ionic liquids: predictions of physicochemical properties with experimental and/or DFT-calculated LFER parameters to understand molecular interactions in solution
PublikacjaPublikacja zawiera modele pozwalające na przewidywanie współczynnika podziału oktanol-woda (log P), rozpuszczalności w wodzie oraz krytycznego stężenia micelizacji (CMC) cieczy jonowych oraz współczynników aktywności anionowej i hydrofobowości w wodzie i w mieszaninie oktanolu z wodą. Modele oparte są na liniowych zależnościach energii swobodnej (LFER) i wykorzystują parametry zmierzone i/lub wyliczone na podstawie funkcjonalnej...
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Temperature, velocity and mean turbulence structure in strongly heated internal gas flows. Comparison of numerical predictions with data
PublikacjaW pracy przedstawiono symulacje numeryczne przy użyciu szeregu modeli turbulencji celem analizy silnie ogrzewanego przepływu powietrza w pionowych rurach. Obliczenia porównano z danymi eksperymentalnymi. Analizowano modyfikacje pola prędkości, temperatury i turbulencji. W rozpatrywanych warunkach odnotowano silną wrażliwość obliczeń na silnie zmieniające się pole temperatury. Stwierdzono, że analizowane przypadki najlepiej odzwierciedla...
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Comparison of mass spectrometry data and bioinformatics predictions to assess the bona fide localization of proteins identified in cell wall proteomics studies
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Employing flowgraphs for forward route reconstruction in video surveillance system
PublikacjaPawlak’s flowgraphs were utilized as a base idea and knowledge container for prediction and decision making algorithms applied to experimental video surveillance system. The system is used for tracking people inside buildings in order to obtain information about their appearance and movement. The fields of view of the cameras did not overlap. Therefore, when an object was moving through unsupervised areas, prediction was needed...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublikacjaComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publikacja—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublikacjaAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Road noise mapping in the city area: measurements compared to model-based estimations
PublikacjaThe paper presents an approach to the verification of noise prediction models in selected localization in the city of Gdansk. The experiments described include a comparison between environmentalmeasurement results performed in the terrain and the noise level prediction results. The NMPB-96 (Nouvelle Méthode de Prévision du Bruit) and Harmonoise models outcomes provide the subject ofthe analysis. The proposed solution of continuous...
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Evaluation of Response Amplitude Operator of Ship Roll Motions Based on the Experiments in White Noise Waves
PublikacjaEvaluation of the response amplitude operator (RAO) function for ship wave frequency motions by means of scale model tests in regular waves is a standard procedure conducted by hydrodynamic model testing institutions. The resulting RAO function allows for evaluating sufficiently reliable seakeeping predictions for low to moderate sea states. However, for standard hull forms, correct prediction of roll motion in irregular wave (and...
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Detection of impulsive disturbances in archive audio signals
PublikacjaIn this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublikacjaPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions
PublikacjaIn this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e....
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Identification of ship’s hull mathematical model with numerical methods
PublikacjaThe 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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Wireless intelligent audio-video surveillance prototyping system
PublikacjaThe presented system is based on the Virtex6 FPGA and several supporting devices like a fast DDR3 memory, small HD camera, microphone with A/D converter, WiFi radio communication module, etc. The system is controlled by the Linux operating system. The Linux drivers for devices implemented in the system have been prepared. The system has been successfully verified in a H.264 compression accelerator prototype in which the most demanding...
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Analiza bibliometryczna w badaniach dotyczących prognozowania upadłości przedsiębiorstw w Polsce
PublikacjaCelem opracowania jest ukazanie obrazu piśmiennictwa poświęconego zagadnieniom prognozowania upadłości przedsiębiorstw w Polsce. Jako metodę badawczą zastosowano analizę bibliometryczną. Do analizy wykorzystano bazę Google Scholar oraz narzędzie Publish or Perish 7. Okresem badań objęto lata 1995– 2019. Jako frazy do wyszukiwania publikacji zastosowano: „prognozowanie upadłości”, „prognozowanie zagrożenia finansowego”, „systemy...
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Elimination of impulsive disturbances from archive audio files – comparison of three noise pulse detection schemes
PublikacjaThe problem of elimination of impulsive disturbances (such as clicks, pops, ticks, crackles, and record scratches) from archive audio recordings is considered and solved using autoregressive modeling. Three classical noise pulse detection schemes are examined and compared: the approach based on open-loop multi-step-ahead signal prediction, the approach based on decision-feedback signal prediction, and the double threshold approach,...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublikacjaUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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On ship roll resonance frequency
PublikacjaThe paper deals with the problem of modeling of rolling motion under a variety of excitation parameters. Special emphasis is put on the analysis and prediction of the frequency of the resonant mode of rolling, since it is often an essential issue in terms of motion of a ship related to her safety against capsizing or excessive amplitudes of roll. The research is performed for both free rolling and excited rolling and it is based...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublikacjaThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
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Elimination of clicks from archive speech signals using sparse autoregressive modeling
PublikacjaThis paper presents a new approach to elimination of impulsivedisturbances from archive speech signals. The proposedsparse autoregressive (SAR) signal representation is given ina factorized form - the model is a cascade of the so-called formantfilter and pitch filter. Such a technique has been widelyused in code-excited linear prediction (CELP) systems, as itguarantees model stability. After detection of noise pulses usinglinear...
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Trim Optimisation - Theory and Practice
PublikacjaForce Technology has been working intensively with trim optimisation tests for almost last 10 years. Focus has primarily been put on the possible power savings and exhaust gases reduction. This paper describes the trim optimisation process for a large cargo vessel. The physics behind changed propulsive power is described and the analyses in order to elaborate the optimum trimmed conditions are presented. Different methods for prediction...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublikacjaThis 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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Traffic Noise Analysis Applied to Automatic Vehicle Counting and Classification
PublikacjaProblems related to determining traffic noise characteristics are discussed in the context of automatic dynamic noise analysis based on noise level measurements and traffic prediction models. The obtained analytical results provide the second goal of the study, namely automatic vehicle counting and classification. Several traffic prediction models are presented and compared to the results of in-situ noise level measurements. Synchronized...
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TOWARDS EXPLAINABLE CLASSIFIERS USING THE COUNTERFACTUAL APPROACH - GLOBAL EXPLANATIONS FOR DISCOVERING BIAS IN DATA
PublikacjaThe paper proposes summarized attribution-based post-hoc explanations for the detection and identification of bias in data. A global explanation is proposed, and a step-by-step framework on how to detect and test bias is introduced. Since removing unwanted bias is often a complicated and tremendous task, it is automatically inserted, instead. Then, the bias is evaluated with the proposed counterfactual approach. The obtained results...
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Machine learning-based seismic response and performance assessment of reinforced concrete buildings
PublikacjaComplexity and unpredictability nature of earthquakes makes them unique external loads that there is no unique formula used for the prediction of seismic responses. Hence, this research aims to implement the most well-known Machine Learning (ML) methods in Python software to propose a prediction model for seismic response and performance assessment of Reinforced Concrete Moment-Resisting Frames (RC MRFs). To prepare 92,400 data...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublikacjaThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Computational collective intelligence for enterprise information systems
PublikacjaCollective intelligence is most often understood as a kind of intelligence which arises on the basis of a group (collective) of autonomous unites (people, systems) which is taskoriented. There are two important aspects of an intelligent collective: The cooperation aspect and the competition aspect (Levy 1997). The first of them means the possibility for integrating the decisions made by the collective members for creating the decision of...
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Multi-Criteria Knowledge-Based Recommender System for Decision Support in Complex Business Processes
PublikacjaIn this paper, we present a concept of a multi-criteria knowledge-based Recommender System (RS) designed to provide decision support in complex business process (BP) scenarios. The developed approach is based on the knowledge aspects of Stylistic Patterns, Business Sentiment and Decision-Making Logic extracted from the BP unstructured texts. This knowledge serves as an input for a multi-criteria RS algorithm. The output is prediction...
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Aerodynamic shape optimization by variable-fidelity computational fluid dynamics models: a review of recent progress
PublikacjaA brief review of some recent variable-fidelity aerodynamic shape optimization methods is presented.We discuss three techniques that—by exploiting information embedded in low-fidelity computationalfluid dynamics (CFD) models—are able to yield a satisfactory design at a low computational cost, usu-ally corresponding to a few evaluations of the original, high-fidelity CFD model to be optimized. Thespecific techniques considered here...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Akcelerator predykcji wewnątrzramkowej H.264 do kompresji obrazu w sensorach wizyjnych
PublikacjaW artykule przedstawiono konfigurowalny cyfrowy akcelerator predykcji wewnątrzramkowej przeznaczony dla enkodera wideo standardu H.264. Akcelerator realizuje predykcję typu „intra” dla makrobloków luminancji o wymiarach 4x4 i 16x16. Akcelerator wstępnie zaimplementowano w układzie FPGA, gdzie został on pomyślnie zweryfikowany, a następnie zaimplementowano go w układzie ASIC w technologii UMC 90 nm. Szczegółowe wyniki testów akceleratora...
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System do prototypowania bezprzewodowych inteligentnych urządzeń monitoringu audio-video
PublikacjaW komunikacie przedstawiono system prototypowania bezprzewodowych urządzeń do monitoringu audio-video. System bazuje na układach FPGA Virtex6 i wielu dodatkowych wspierających urządzeniach jak: szybka pamięć DDR3, mała kamera HD, mikrofon z konwerterem A/C, moduł radiowy WiFi, itp. Funkcjonalność systemu została szczegółowo opisana w komunikacie. System został zoptymalizowany do pracy pod kontrolą systemu operacyjnego Linux, zostały...