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Search results for: PREDICTIVE%20CONTROL
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Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
PublicationLightweight concrete (LWC) is a group of cement composites of the defined physical, mechanical, and chemical performance. The methods of designing the composition of LWC with the assumed density and compressive strength are used most commonly. The purpose of using LWC is the reduction of the structure’s weight, as well as the reduction of thermal conductivity index. The highest possible strength, durability and low thermal conductivity...
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An enhanced method in predicting tensile behaviour of corroded thick steel plate specimens by using random field approach
PublicationThe present work investigates the possibility of using random field techniques in modelling the mechanical behaviour of corroded thick steel plate specimens. The nonlinear Finite Element method, employing the explicit dynamic solver, is used to analyse the mechanical properties of typical specimens. A material model considering full nonlinearity is used to evaluate the stress-strain response. The influence of major governing parameters...
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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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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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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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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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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational 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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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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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Predicting cutting power for band sawing process of pine and beech wood dried with the use of four different methods
PublicationWood drying is an important stage in the woodworking process. After drying, wood is subject to a re-sawing process, for which a high quality surface, low material loss, and high efficiency are often required. In this paper, forecasted values were presented of cutting power for the re-sawing process of pine and beech wood that were dried with four different methods. Forecasting of cutting power for an industrial band saw machine...
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Improving the prediction of biochar production from various biomass sources through the implementation of eXplainable machine learning approaches
PublicationExamining the game-changing possibilities of explainable machine learning techniques, this study explores the fast-growing area of biochar production prediction. The paper demonstrates how recent advances in sensitivity analysis methodology, optimization of training hyperparameters, and state-of-the-art ensemble techniques have greatly simplified and enhanced the forecasting of biochar output and composition from various biomass...
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The importance of evaluating metal exposure and predicting human health risks in urban–periurban environments influenced by emerging industry
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Key activities to improve energy management in DC microgrids connected by urban traction
PublicationDC MicroGrids must have Energy Management Systems to guarantee efficient, dependable, and environmentally friendly electricity. The application of Model Predictive Control, proved to be helpful due to its adaptability and capacity to use non-linear models. This paper, based on an extensive literature review, identifies and discusses the three key activities to improve the characteristics of DC MicroGrids, i.e.: the use of Energy...
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Using LSTM networks to predict engine condition on large scale data processing framework
PublicationAs the Internet of Things technology is developing rapidly, companies have an ability to observe the health of engine components and constructed systems through collecting signals from sensors. According to output of IoT sensors, companies can build systems to predict the conditions of components. Practically the components are required to be maintained or replaced before the end of life in performing their assigned task. Predicting...
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Predykcyjne sterowanie równoległym filtrem aktywnym ze sprzężeniem od prądu zasilającego
PublicationArtykuł przedstawia nowatorską strategię predykcyjnego sterowania równoległym energetycznym filtrem aktywnym (EFA). Proponowane sterowanie zawiera sprzężenie zwrotne od prądu zasilającego i wiąże zalety sterowania w układzie otwartym oraz zamkniętym – szybkość reakcji na zmianę prądu odbioru i bardzo wysoką skuteczność kompensacji. Wysoka jakość prądu kompensacyjnego wynika również z zastosowania w sterowaniu algorytmów predykcyjnych,...
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Advanced Control With PLC—Code Generator for aMPC Controller Implementation and Cooperation With External Computational Server for Dealing With Multidimensionality, Constraints and LMI Based Robustness
PublicationThe manufacturers of Programmable Logic Controllers (PLC) usually equip their products with extremely simple control algorithms, such as PID and on-off regulators. However, modern PLCs have much more efficient processors and extensive memory, which enables implementing more sophisticated controllers. The paper discusses issues related to the implementation of matrix operations, time limitations for code execution within one PLC...
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High energy radiation – Induced cooperative reductive/oxidative mechanism of perfluorooctanoate anion (PFOA) decomposition in aqueous solution
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Can Web Search Queries Predict Prices Change on the Real Estate Market?
PublicationThis study aims to explore whether the intensity of internet searches, according to the Google Trends search volume index (SVI), is a predictor of changes in real estate prices. The motivation of this study is the possibility to extend the understanding of the extra predictive power of Google search engine query volume of future housing price change (shift direction) by (i) the introduction of a research approach that combines...
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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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Predicting Outcome and Conservative Treatment Failure in Patients with Skull Fracture after Traumatic Brain Injury: A Retrospective Cohort Study
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Crystal Structure Prediction by Global Optimization as a Tool for Evaluating Potentials: Role of the Dipole Moment Correction Term in Successful 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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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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Predicting enthalpy of vaporization for Persistent Organic Pollutants with Quantitative Structure–Property Relationship (QSPR) incorporating the influence of temperature on volatility
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The Use of Chlorophyll Fluorescence as an Indicator of Predicting Potato Yield, Its Dry Matter and Starch in the Conditions of Using Microbiological Preparations
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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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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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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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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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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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Machine Learning- and Artificial Intelligence-Derived Prediction for Home Smart Energy Systems with PV Installation and Battery Energy Storage
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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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Prediction of Ship Resonant Rolling - Related Dangerous Zones with Regard to the Equivalent Metacentric Height Governing Natural Frequency of Roll
PublicationPotentially 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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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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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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Reverse vaccinology-based prediction of a multi-epitope SARS-CoV-2 vaccine and its tailoring to new coronavirus variants
PublicationThe 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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Fracture prediction in flat PMMA notched specimens under tension - effectiveness of the equivalent material concept and fictitious material concept
PublicationThe 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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<title>DOOCS and MatLab control environment for SIMCON 2.1 FPGA based control system for TESLA FEL part III: readouts</title>
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Teaching Adaptive Control with DS1102 DSP Controller Board
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Nonlinear control systems modelling: global vs. local
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Conditionality of the system of control of the financial economy of selfgovernment units
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The assessment of exploitation process of power for access control system
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Application of Reversible Logic in Synthesis of Traffic Control Systems
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Motion stability during optimal control of the mobile platform
PublicationPraca przedstawia metodę badania stabilności robotów mobilnych podczas sterowania optymalnego na przykładzie 3-kołowej platformy mobilnej. Robot posiada więzy nieholonomiczne. Model matematyczny 3-kołowej platformy mobilnej opisuje skończona liczba nieliniowych równań różniczkowych. Stąd, prognozowanie stabilności ruchu takiego obiektu wymaga zastosowania efektywnych algorytmów.
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Optimal and safe control planning with the use of discrete optimization
PublicationW opracowaniu zaproponowano metodę projektowania optymalnych i tolerujących uszkodzenia systemów sterowania opartych na wykorzystaniu algorytmów optymalizacji dyskretnej. Publikacja przedstawia potencjalne wady i zalety metody. Główna idea proponowanego algorytmu sprowadza się do wykorzystania struktury grafu przepływowego w celu stworzenia reprezentacji dynamiki własnej danego procesu. Poszukiwana trajektoria optymalna, jeśli...
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Cavity parameters identification for TESLA control system development
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