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Search results for: STRUCTURE PREDICTION
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Numerical Modelling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia
PublicationIn this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four...
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Thermodynamic interpretation and prediction of CO2 solubility in imidazolium ionic liquids based on regular solution theory
PublicationRegular solution theory (RST) is the most popular model for the interpretation of the interaction between CO2 and ionic liquids. In the present work, the parameters of this model were determined for the CO2 absorption in eleven imidazolium ionic liquids. The y-intercept (A) of the RST model for the investigated imidazolium liquids increases with increasing temperature whereas the slope (B) remains constant. The values of RST parameters...
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Prediction Model for Hemorrhagic Complications after Laparoscopic Sleeve Gastrectomy: Development of SLEEVE BLEED Calculator
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FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublicationThe increasing environmental contamination forces the need to design reliable devices for detecting of the volatile compounds present in the air. For this purpose semiconductor gas sensors, which have been widely used for years, are often utilized. Although they have many advantages such as low price and quite long life time, they still lack of long term stability and selectivity. Namely, environmental conditions have significant...
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Recovering Sound Produced by Wind Turbine Structures Employing Video Motion Magnification
PublicationThe recordings were made with a fast video camera and with a microphone. Using fast cameras allowed for observation of the micro vibrations of the object structure. Motion-magnified video recordings of wind turbines on a wind farm were made for the purpose of building a damage prediction system. An idea was to use video to recover sound & vibrations in order to obtain a contactless diagnostic method for wind turbines. The recovered signals...
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Numerical investigations on early indicators of fracture in concrete at meso-scale.
PublicationFracture is a major reason of the global failure of concretes. The understanding of fracture is important to ensure the safety of structures and to optimize the material behaviour. In particular an early prediction possibility of fracture in concretes is of major importance. In this paper, concrete fracture under bending was numerically analysed using the Discrete Element Method (DEM). The real mesoscopic structure of a concrete...
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Prediction of Pile Shaft Capacity in Tension Based on Some Direct CPT Methods—Vistula Marshland Test Site
PublicationThis paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with diameter 0.4 m and the length varied from 8 m to 14.6 m were subjected to static load tests in tension. Their...
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Prediction of pile shaft capacity in tension based on some direct CPT methods – Vistula Marshland test site
PublicationThis paper presents different CPT methodologies for the prediction of the pile shaft resistance in tension on the example of three reference screw piles of the Jazowa test site in Poland. The shaft capacity was estimated based on the cone resistance, sleeve friction and CPT excess pore water pressure. Three piles with a diameter of 0.4 m and the length...
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Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled 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
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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Effect of temperature and composition on physical properties of deep eutectic solvents based on 2-(methylamino)ethanol – measurement and prediction
PublicationNovel deep eutectic solvents were synthesized using 2-(methylamino)ethanol as hydrogen bond donor with tetrabutylammonium bromide or tetrabutylammonium chloride or tetraethylammonium chloride as hydrogen bond acceptors. Mixtures were prepared at different molar ratios of 1:6, 1:8 and 1:10 salt to alkanolamine and then Fourier Transform Infrared Spectroscopy measurements were performed to confirm hydrogen bonds interactions between...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Comparison of selected parametric methods for prediction of inland waterways ship hull resistance in towing tank test
PublicationIn the paper selected approximate methods for calculation of inland waterways ship resistance and their verification by towing tests, compared on the example of a small urban ferry, are presented. The test results are made for both the bare hull and the hull with appendages (skeg, azimuthal propeller). Significant differences between results of the theoretical methods and experimental ones, especially in the case of the model with...
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Principles for the Application of Vibration Intensity Scale for the Prediction and Assessment of Impact of Actions of Exploitation Mine on Buildings and People
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Comparative Analysis of MicroRNA-Target Gene Interaction Prediction Algorithms Based on Integrated P-Value Calculation
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Solubility of sulfanilamide in binary solvents containing water: Measurements and prediction using Buchowski-Ksiazczak solubility model
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Comparative Analysis of microRNA-Target Gene Interaction Prediction Algorithms - The Attempt to Compare the Results of Three Algorithms
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Plasma Amino Acids May Improve Prediction Accuracy of Cerebral Vasospasm after Aneurysmal Subarachnoid Haemorrhage
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Model Based Monitoring of Dynamic Loads and Remaining Useful Life Prediction in Rolling Mills and Heavy Machinery
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Prediction of Thymine Dimer Repair by Electron Transfer from Photoexcited 8-Aminoguanine or Its Deprotonated Anion
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Short clinically-based prediction model to forecast transition to psychosis in individuals at clinical high risk state
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Improved Consensus-Fragment Selection in Template-Assisted Prediction of Protein Structures with the UNRES Force Field in CASP13
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Evaluation of the scale-consistent UNRES force field in template-free prediction of protein structures in the CASP13 experiment
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Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study
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Prediction of Wastewater Quality at a Wastewater Treatment Plant Inlet Using a System Based on Machine Learning Methods
PublicationOne of the important factors determining the biochemical processes in bioreactors is the quality of the wastewater inflow to the wastewater treatment plant (WWTP). Information on the quality of wastewater, sufficiently in advance, makes it possible to properly select bioreactor settings to obtain optimal process conditions. This paper presents the use of classification models to predict the variability of wastewater quality at...
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Temperature-Based Prediction of Joint Hardness in TIG Welding of Inconel 600, 625 and 718 Nickel Superalloys
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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Compatibility of Crude Oil Blends─Processing Issues Related to Asphaltene Precipitation, Methods of Instability Prediction─A Review
PublicationProcessing crude oil of variable composition, especially due to the need to process crude oil blends obtained from various sources, presents a tremendous process challenge. This is mainly due to the destabilization of the colloidal system manifested mostly by the precipitation of the asphaltene fraction. The precipitation of asphaltenes from crude oil is a serious problem during extraction, transport, and processing. In the latter...
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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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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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Prediction of Bioactive Peptides From Chicken Feather and Pig Hair Keratins Using In Silico Analysis Based on Fragmentomic Approach
PublicationBackground: 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
PublicationLine 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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Defining a novel domain that provides an essential contribution to site-specific interaction of Rep protein with DNA
PublicationAn essential feature of replication initiation proteins is their ability to bind to DNA. In this work, we describe a new domain that contributes to a replication initiator sequence-specific interaction with DNA. Applying biochemical assays and structure prediction methods coupled with DNA–protein crosslinking, mass spectrometry, and construction and analysis of mutant proteins, we identified that the replication initiator of 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
PublicationNitrous 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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High temperature corrosion evaluation and lifetime prediction of porous Fe22Cr stainless steel in air in temperature range 700–900 °C
PublicationThis 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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Predicting bankruptcy with the use of macroeconomic variables
PublicationRegarding the current global financial crisis, the firms can expect the increased uncertainty of their existence. The relevant literature includes extensive studies on bankruptcy prediction. Studies show that the most popular method used for prediction of firms' failures are discriminant analyses (30,3% of all models), then logit and probit models (21,3%), which all three are parametric models. The nature, the structure of the...
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Performance of various risk prediction models in a large lung cancer screening cohort in Gdańsk, Poland—a comparative study
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Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublicationThe formation of pitting is a major problem in most metals, which is caused by extremely localized corrosion that creates small holes in metal and subsequently, it changes into cracks under mechanical load, thermo-mechanical stress, and corrosion process factors. This research aims to study pit to crack transition phenomenon of steel boiler heat tubes under cyclic thermal load, and mathematical modeling...
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A subdomain model for armature reaction field and open‐circuit field prediction in consequent pole permanent magnet machines
PublicationIn this paper, the machine quantity, such as electromagnetic torque, self and mutual inductances, and electromotive force, is analytically calculated for non-overlapping winding consequent pole slotted machine for open-circuit field and armature reaction. The sub-domain approach of (2-D) analytical model is developed using Maxwell's equations and divide the problem into slots, slot-openings, airgap and magnets region, the magnet...
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An ANN-Based Approach for Prediction of Sufficient Seismic Gap between Adjacent Buildings Prone to Earthquake-Induced Pounding
PublicationEarthquake-induced structural pounding may cause major damages to structures, and therefore it should be prevented. This study is focused on using an artificial neural network (ANN) method to determine the sufficient seismic gap in order to avoid collisions between two adjacent buildings during seismic excitations. Six lumped mass models of structures with a different number of stories (from one to six) have been considered in...
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Application of reversed-phase thin layer chromatography and QSRR modelling for prediction of protein binding of selected β-blockers
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Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublicationThe study targeted towards drying of cantaloupe slices with various thicknesses in a microwave dryer. The experiments were carried out at three microwave powers of 180, 360, and 540 W and three thicknesses of 2, 4, and 6 mm for cantaloupe drying, and the weight variations were determined. Artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) were exploited to investigate energy and exergy indices of...
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Verification of the theoretical methods for the prediction of resistance of sailing yachts based on model test results of a yacht V.O.60
PublicationWeryfikacja opiera się głównie na serii systematycznych badań modelowych wykonanych w roku 2001 w Laboratorium Hydromechaniki Okrętu WOIO PG. Zademonstrowano prognozy oporu jachtu wykonane trzema metodami z oszacowaniem i dyskusją rozbieżności wyników. Przeprowadzone badania są zorientowane na opracowanie wiarygodnego programu komputerowego dla prognozowania prędkości i innych parametrów ruchu żaglowych, regatowych jachtów oceanicznych...
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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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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
PublicationThis 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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Predicting seismic response of SMRFs founded on different soil types using machine learning techniques
PublicationPredicting the Maximum Interstory Drift Ratio (M-IDR) of Steel Moment-Resisting Frames (SMRFs) is a useful tool for designers to approximately evaluate the vulnerability of SMRFs. This study aims to explore supervised Machine Learning (ML) algorithms to build a surrogate prediction model for SMRFs to reduce the need for complex modeling. For this purpose, twenty well-known ML algorithms implemented in Python software are trained...
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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 near-bottom water salinity in the Baltic Sea using Ordinary Least Squares and Geographically Weighted Regression models
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