Wyniki wyszukiwania dla: PREDICTION
-
FFT analysis of temperature modulated semiconductor gas sensor response for the prediction of ammonia concentration under humidity interference
PublikacjaThe 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...
-
Prediction of Pile Shaft Capacity in Tension Based on Some Direct CPT Methods—Vistula Marshland Test Site
PublikacjaThis 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...
-
Prediction of pile shaft capacity in tension based on some direct CPT methods – Vistula Marshland test site
PublikacjaThis 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...
-
Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublikacjaThe 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...
-
Effect of temperature and composition on physical properties of deep eutectic solvents based on 2-(methylamino)ethanol – measurement and prediction
PublikacjaNovel 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...
-
Performance of various risk prediction models in a large lung cancer screening cohort in Gdańsk, Poland—a comparative study
Publikacja -
Mathematical modeling and prediction of pit to crack transition under cyclic thermal load using artificial neural network
PublikacjaThe 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...
-
Application of reversed-phase thin layer chromatography and QSRR modelling for prediction of protein binding of selected β-blockers
Publikacja -
Exergy and Energy Analyses of Microwave Dryer for Cantaloupe Slice and Prediction of Thermodynamic Parameters Using ANN and ANFIS Algorithms
PublikacjaThe 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...
-
An ANN-Based Approach for Prediction of Sufficient Seismic Gap between Adjacent Buildings Prone to Earthquake-Induced Pounding
PublikacjaEarthquake-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...
-
Verification of the theoretical methods for the prediction of resistance of sailing yachts based on model test results of a yacht V.O.60
PublikacjaWeryfikacja 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...
-
A subdomain model for armature reaction field and open‐circuit field prediction in consequent pole permanent magnet machines
PublikacjaIn 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...
-
Reply to “Comment on ‘Crystal Structure Prediction by Global Optimization as a Tool for Evaluating Potentials: Role of the Dipole Moment Correction Term in Successful Predictions'” by B. P. van Eijck and J. Kroon
Publikacja -
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
Publikacja -
Prediction of near-bottom water salinity in the Baltic Sea using Ordinary Least Squares and Geographically Weighted Regression models
Publikacja -
Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
Publikacja -
Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
Publikacja -
Use of the UNRES force field in template-assisted prediction of protein structures and the refinement of server models: Test with CASP12 targets
Publikacja -
Prediction of protein structure using a knowledge-based off-lattice united-residue force field and global optimization methods
Publikacja -
Prediction of Stress and Deformation Caused by Magnetic Attraction Force in Modulation Elements in a Magnetically Geared Machine Using Subdomain Modeling
Publikacja -
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...
-
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...
-
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...
-
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...
-
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...
-
Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
Publikacja -
Use of Restraints from Consensus Fragments of Multiple Server Models To Enhance Protein-Structure Prediction Capability of the UNRES Force Field
Publikacja -
Protein structure prediction with the UNRES force-field using Replica-Exchange Monte Carlo-with-Minimization; Comparison with MCM, CSA, and CFMC
Publikacja -
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
Publikacja -
Physics-based protein-structure prediction using a hierarchical protocol based on the UNRES force field: Assessment in two blind tests
Publikacja -
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...
-
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...
-
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
Publikacja -
Reversed-phase and normal-phase thin-layer chromatography and their application to the lipophilicity prediction of synthetic pyrethroids based on quantitative structure–retention relationships
Publikacja -
Prediction of protein structure with the coarse-grained UNRES force field assisted by small X-ray scattering data and knowledge-based information
Publikacja -
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
Publikacja -
Method for prediction of the frost resistance ability of air‐entrained concrete based on the 3D air void characteristics by x‐ray micro‐CT
PublikacjaIn modern construction, one of the most important factors in the execution of contracts is time. Standard procedures for assessing the frost resistance or concrete are usually very time-consuming and can take up to 40 days. The current paper is experimentally and practically oriented. It presents an alternative testing method, based on air void network, that allows to assess the frost resistance of concrete within just a few days...
-
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...
-
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...
-
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...
-
Potential of Serum Proteome Patterns Analysis by MALDI-TOF Mass Spectrometry for Prediction of Acute Radiation Injury Response in Head and Neck Cancers Patients
Publikacja -
Chemometric analysis of bio-inspired micellar electrokinetic chromatographic systems – modelling of retention mechanism and prediction of biological properties using bile salts surfactants
Publikacja -
Toxicity of the New Psychoactive Substance (NPS) Clephedrone (4-Chloromethcathinone, 4-CMC): Prediction of Toxicity Using In Silico Methods for Clinical and Forensic Purposes
Publikacja