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Wyniki wyszukiwania dla: LIFE PREDICTION
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublikacjaForecasting ice phenomena in river systems is of great importance because these phenomena are a fundamental part of the hydrological regime. Due to the stochasticity of ice phenomena, their prediction is a difficult process, especially when data sets are sparse or incomplete. In this study, two machine learning models—Multilayer Perceptron Neural Network (MLPNN) and Extreme Gradient Boosting (XGBoost)—were developed to predict...
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Numerical Estimation of Hull Hydrodynamic Derivatives in Ship Maneuvering Prediction
PublikacjaPrediction of the maneuvering characteristics of the ship at the design stage can be done by means of model tests, computational simulations or a combination of both. The model tests can be realized as direct simulation of the standard maneuvers with the free running model, which gives the most accurate results, but is also the least affordable as it requires very large tank or natural lake, as well as complex equipment of the...
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GIS Solution for Weather Forecast Data Analysis
PublikacjaIn this paper authors present the GIS system for the analysis of the numerical weather prediction data. This kind of data has multidimensional character (three dimensions and time) and its analysis should consider all the available factors. Proposed GIS system consists of RASDAMAN application with implemented OLAP cube mechanism, which enables the user to process data in the spatial-time domain. It also simplifies the meteorological...
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A new quantum-inspired approach to reduce the blocking probability of demands in resource-constrained path computation scenarios
PublikacjaThis article presents a new approach related with end-to-end routing, which, owing to quantum-inspired mecha-nisms of prediction of availability of network resources, results in improved blocking probability of incoming requests to establish transmission paths. The proposed scheme has been analyzed for three network topologies and several scenarios of network load. Obtained results show a significant (even twofold) reduction of...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublikacjaMachine Learning (ML) method is widely used in engineering applications such as fracture mechanics. In this study, twenty different ML algorithms were employed and compared for the prediction of the fracture toughness and fracture load in modes I, II, and mixed-mode (I-II) of various materials, including fibre-reinforced concrete, cement mortar, sandstone, white travertine, marble, and granite. A set of 401 specimens of “Brazilian...
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A CNN based coronavirus disease prediction system for chest X-rays
PublikacjaCoronavirus disease (COVID-19) proliferated globally in early 2020, causing existential dread in the whole world. Radiography is crucial in the clinical staging and diagnosis of COVID-19 and offers high potential to improve healthcare plans for tackling the pandemic. However high variations in infection characteristics and low contrast between normal and infected regions pose great challenges in preparing radiological reports....
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A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine
PublikacjaRNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA....
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Cost assessment of computer security activities
PublikacjaComprehensive cost-benefit analysis plays a crucial role in the decision-making process when it comes to investments in information security solutions. The cost of breaches needs to be analysed in the context of spending on protection measures. However, no methods exist that facilitate the quick and rough prediction of true expenditures on security protection systems. Rafal Leszczyna of Gdansk University of Technology presents...
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The Concept of Geodetic Analyses of the Measurement Results Obtained by Hydrostatic Leveling
PublikacjaThe article discusses the issue of hydrostatic leveling. Its application is presented in structural health monitoring systems in order to determine vertical displacements of controlled points. Moreover, the article includes a complete computation scheme that utilizes the estimation from observation differences, allowing the elimination of the influence of individual sensors’ systematic errors. The authors suggest two concepts of...
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Application of Majority Voting Protocols to Supporting Trading Decisions
PublikacjaA broad spectrum of analysis and prediction indicators and methods exists to support trading decisions, but no hard knowledge exist to tell in advance which of them will fit best in a given timeframe. To support trading decisions, a multi-agent self-organizing system has been proposed. The system is based on history based dynamic weight voting and selects the right indicators based on their past performance. The formal analysis...
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APPLICATION OF MAJORITY VOTING PROTOCOLS TO SUPPORTING TRADING DECISIONS
PublikacjaA broad spectrum of analysis and prediction indicators and methods exists to support trading decisions, but no hard knowledge exist to tell in advance which of them will fit best in a given timeframe. To support trading decisions, a multi-agent self-organizing system has been proposed. The system is based on history based dynamic weight voting and selects the right indicators based on their past performance. The formal analysis...
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New approach to railway noise modeling employing Genetic Algorithms
PublikacjaMain goal of this paper was to describe an innovative method of noise prediction based on Genetic Algorithms. First part of the paper addresses the problem of growing noise, mainly in the context of a unified method for measuring noise. Further, Genetic Algorithms are described with regards to their fundamental features. Further a description is provided as to how Genetic Algorithms were used in the area of noise modeling. Next...
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The Analysis of Patients' Airflow with Respect to Early Detection of Sleep Apnea
PublikacjaThe paper discusses the analysis of the respiratory events of sleep apnea patients. The analysis was carried out on the basis of the patient's airflow. As a result of the conducted analysis we proposed an algorithm which establishes an individual respiratory pattern for each subject. The algorithm could be implemented in the measurement - control system which manages the prosthetic device applying positive airway pressure. Its...
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Dynamic fracture of brittle shells in a space-time adaptive isogeometric phase field framework
PublikacjaPhase field models for fracture prediction gained popularity as the formulation does not require the specification of ad-hoc criteria and no discontinuities are inserted in the body. This work focuses on dynamic crack evolution of brittle shell structures considering large deformations. The energy contributions from in-plane and out-of-plane deformations are separately split into tensile and compressive components and the resulting...
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New type T-Source inverter
PublikacjaThis paper presents different topologies of voltage inverters with alternative input LC networks. The basic topology is known in the literature as a Z-source inverter (ZSI). Alternative passive networks were named by the authors as T-sources. T-source inverter has fewer reactive components in comparison to conventional Z-source inverter. The most significant advantage of the T-source inverter (TSI) is its use of a common voltage...
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Non-Contact Temperature Measurements Dataset
PublikacjaThe dataset titled The influence of the distance of the pyrometer from the surface of the radiating object on the accuracy of measurements contains temperature measurements using a selection of four commercially available pyrometers (CHY 314P, TM-F03B, TFA 31.1125 and AB-8855) as a function of the measuring distance. The dataset allows a comparison of the accuracy and measuring precision of the devices, which are very important...
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Verification of the new viscoelastic method of thermal stress calculation in asphalt layers of pavements
PublikacjaThe new viscoelastic method of thermal stress calculations in asphalt layers has been developed and published recently by the author. This paper presents verification of this method. The verification is based on the comparison of the results of calculations with results of testing of thermal stresses in Thermal Stress Restrained Specimen Test. The calculations of thermal stresses according to the new method were based on rheological...
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Explainable machine learning for diffraction patterns
PublikacjaSerial crystallography experiments at X-ray free-electron laser facilities produce massive amounts of data but only a fraction of these data are useful for downstream analysis. Thus, it is essential to differentiate between acceptable and unacceptable data, generally known as ‘hit’ and ‘miss’, respectively. Image classification methods from artificial intelligence, or more specifically convolutional neural networks (CNNs), classify...
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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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A predictive estimation based control strategy for a quasi-resonant dc-link inverter
PublikacjaIn this paper the predictive estimation based control strategy for a quasi-resonant dc link inverter (PQRDCLI) is developed. Instead of direct measurement of dc link input inverter current – its estimation with one step prediction is applied. The PQRDCLI fed induction motor, controlled with a predictive current estimation stabilized inverter output voltage slopes independently of load. Moreover, reduction of overvoltage spikes...
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New results on estimation bandwidth adaptation
PublikacjaThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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Full scale measurements of pressure field induced on the quay wall by bow thrusters – indirect method for seabed velocities monitoring
PublikacjaThe paper presents the results of full-scale experimental investigation of loads generated on the quay wall by bow thrusters during unberthing of a self-manoeuvring vessel. The presented research allowed for the comparison of the measurements results with generally accepted empirical prediction methods and confirmed the utility of the developed measuring setup for the on-line monitoring of jet induced loads. The conclusions from the...
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Ship Dynamic Positioning Based on Nonlinear Model Predictive Control
PublikacjaThe presented work explores the simulation test results of using nonlinear model predictive control algorithm for ship dynamic positioning. In the optimization task, a goal function with a penalty was proposed with a variable prediction step. The results of the proposed control algorithm were compared with backstepping and PID. The effect of estimation accuracy on the control quality with the implemented algorithms was investigated....
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Systematic Literature Review on Click Through Rate Prediction
PublikacjaThe ability to anticipate whether a user will click on an item is one of the most crucial aspects of operating an e-commerce business, and clickthrough rate prediction is an attempt to provide an answer to this question. Beginning with the simplest multilayer perceptrons and progressing to the most sophisticated attention networks, researchers employ a variety of methods to solve this issue. In this paper, we present the findings...
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Sensorless predictive control of three-phase parallel active filter
PublikacjaThe paper presents the control system of parallel active power filter (APF) with predictive reference current calculation and model based predictive current control. The novel estimator and predictor of grid emf is proposed for AC voltage sensorless operation of APF, regardless of distortion of this voltage. Proposed control system provides control of APF current with high precision and dynamics limited only by filter circuit parameters....
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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile...
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FEM modelling of screw displacement pile interaction with subsoil
PublikacjaPredicting the-settlement characteristics of piles is an important element in the designing of pile foundations. The most reliable method in evaluating pile-soil interaction is the static load test, preferably performed with instrumentation for measuring shaft and pile base resistances. This, however, is a mostly post-implementation test. In the design phase, prediction methods are needed, in which numerical simulations play an...
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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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Machine learning-based prediction of preplaced aggregate concrete characteristics
PublikacjaPreplaced-Aggregate Concrete (PAC) is a type of preplaced concrete where coarse aggregate is placed in the mold and a Portland cement-sand grout with admixtures is injected to fill the voids. Due to the complex nature of PAC, many studies were conducted to determine the effects of admixtures and the compressive and tensile strengths of PAC. Considering that a prediction tool is needed to estimate the compressive and tensile strengths...
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NUMERICAL ESTIMATION OF HULL HYDRODYNAMIC DERIVATIVES IN SHIP MANOUVERING PREDICTION
PublikacjaOperating in crowded waterways pose a risk of accidents and disasters due to maneuvering limitations of the ship. In order to predict ship’s maneuvering characteristics at the design stage, model tests are often executed as the most accurate prediction tool. Two approaches can be distinguished here: free running model tests and numerical simulations based on planar motion model with the use of hydrodynamic derivatives obtained...
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Lattice filter based autoregressive spectrum estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running forward in...
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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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Progressive failure analysis of laminates in the framework of 6-field nonlinear shell theory
PublikacjaThe paper presents the model of progressive failure analysis of laminates incorporated into the 6-field non-linear shell theory with non-symmetrical strain measures of Cosserat type. Such a theory is specially recommended in the analysis of shells with intersections due to its specific kinematics including the so-called drilling rotation. As a consequence of asymmetry of strain measures, modified laminates failure criteria must...
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Simplified AutoDock force field for hydrated binding sites
Publikacjahas been extracted from the Protein Data Bank and used to test and recalibrate AutoDock force field. Since for some binding sites water molecules are crucial for bridging the receptor-ligand interactions, they have to be included in the analysis. To simplify the process of incorporating water molecules into the binding sites and make it less ambiguous, new simple water model was created. After recalibration of the force field on...
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Recovering Sound Produced by Wind Turbine Structures Employing Video Motion Magnification
PublikacjaThe 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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Residence time distribution in rapid multiphase reactors
PublikacjaResidence time distribution (RTD) provides information about average hydraulic residence time and the distribution of material in the reactor. A method for determining RTD for reactors with very short hydraulic residence times is deconvolution based on extraction of real RTD by the analysis of a non-ideal input signal. The mean residence time and dispersion were determined for the spinning fluids reactor (SFR). For the first time...
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Modeling of Performance, Reliability and Energy Efficiency in Large-Scale Computational Environment
PublikacjaLarge scale of complexity of distributed computational systems imposes special challanges for prediction of quality in such systems.Existing quality models for lower-scale systems include functionality,performance,reliability,flexibility and usability.Among these attributes,performance and reliability have a particular significance to the large-scale systems computing quality modeling due to their strong dependence on the system...
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Numerical modelling and experimental verification of compressible squeeze film pressure
PublikacjaThe validity of using the Reynolds equation for compressible squeeze film pressure was tested with computational fluid dynamics (CFD). A squeeze film air bearing was instrumented with pressure sensors and non-contacting displacement probes to provide transient measurements of film thickness and pressure. The film thickness measurements also provided input parameters to the numerical prediction. However, numerical results showed...
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Tool Wear Prediction in Single-Sided Lapping Process
PublikacjaSingle-sided lapping is one of the most effective planarization technologies. The process has relatively complex kinematics and it is determined by a number of inputs parameters. It has been noted that prediction of the tool wear during the process is critical for product quality control. To determine the profile wear of the lapping plate, a computer model which simulates abrasive grains trajectories was developed in MATLAB. Moreover,...
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Numerical investigations on early indicators of fracture in concrete at meso-scale.
PublikacjaFracture 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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Modeling of Performance, Reliability and Energy Efficiency in Large-Scale Computational Environments
PublikacjaLarge scale of complexity of distributed computational systems imposes special challenges for prediction of quality in such systems. Existing quality models for lower-scale systems include functionality, performance, reliability, flexibility and usability. Among these attributes, performance and reliability have a particular significance to the large-scale systems computing quality modeling due to their strong dependence on the...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublikacjaThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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A history of the physical and chemical stability of pharmaceuticals : a review
Publikacja: There is a great need for a broad range review of stability tests of active pharmaceutical ingredients (APIs) in comparison with current requirements contained in the pharmacopoeia. This review focuses on a pharmaceutical history of physical and chemical stability determination. Traditional knowledge must be considered in the context of physical stability, while new knowledge must be applied and acquired in terms of identification...
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Geo-engineering computer simulation seems attractive but is it the real world?
PublikacjaCorrect formulation of the differential equation system for equilibriom conditions of subsoil, especially in terms of controlled numerical calculation, is discussed. The problem of solution stability is also considered. The solution of problems, which are ill-posed, have no practical value in the majority of cases and is this way the engineering prognosis can lead to real disaster. The object of this paper is quite relevant if...
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RECSYS CHALLENGE 2015: a BUY EVENT PREDICTION IN THE E-COMMERCE DOMAIN
PublikacjaIn this paper we present our approach to RecSys Challenge 2015. Given a set of e-commerce events, the task is to predict whether a user will buy something in the current session and, if yes, which of the item will be bought. We show that the data preparation and enrichment are very important in finding the solution for the challenge and that simple ideas and intuitions could lead to satisfactory results. We also show that simple...
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Induction machine behavioral modeling for prediction of EMI propagation.
PublikacjaThis paper presents the results of wideband behavioral modeling of an induction machine (IM). The proposed solution enables modeling the IM differential- and common-mode impedance for a frequency range from 1 kHz to 10 MHz. Methods of parameter extraction are derived from the measured IM impedances. The developed models of 1.5 kW and 7.5 kW induction machines are designed using the Saber Sketch scheme editor and simulated in the...
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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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Wideband Modeling of DC-DC Buck Converter with GaN Transistors
PublikacjaThe general wideband modeling method of the power converter is presented on the example of DC-DC buck converter with GaN High Electron Mobility Transistors (HEMT). The models of all basic and parasitic components are briefly described. The two methods of Printed Circuit Board (PCB) layout parameter extraction are presented. The results of simulation in Saber@Sketch simulation software and measurements are compared. Next, the model...
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Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment
PublikacjaThe UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES- contact group), and (iii) template-assisted (the UNRES-template...