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Search results for: AIR QUALITY PREDICTION
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Prediction of fracture toughness in fibre-reinforced concrete, mortar, and rocks using various Machine learning techniques
PublicationMachine 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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Coastal Cliffs Monitoring and Prediction of Displacements Using Terrestial Laser Scanning
PublicationCoastal cliffs are very sensitive to degradation caused by erosion and abrasion. Thus, it is very important to monitor susceptibility of the cliffs in terms of slope angles and ground fall resulting from vertical morphology of the cliffs. The results could be used for example to establish the boundaries of the safe investments zone or retreat infrastructure buildings in case of real threat such as degradation of the objects of...
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Electromagnetic interference frequencies prediction model of flyback converter for snubber design
PublicationSnubber design for flyback converters usually requires experimental prototype measurements or simulation based on accurate and complex models. In this study simplified circuit modelling of a flyback converter has been described to dimension snubbers in early stage of design process. Simulation based prediction of the transistor and diode ringing frequencies has been validated by measurements in a prototype setup. In that way obtained...
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Sensitivity of the Baltic Sea level prediction to spatial model resolution
Publicationhe three-dimensional hydrodynamic model of the Baltic Sea (M3D) and...
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A New Approach for Investigating the Impact of Pesticides and Nutrient Flux from Agricultural Holdings and Land-Use Structures on Baltic Sea Coastal Waters
PublicationKnowledge related to land-use management impacts on the Baltic Sea ecosystem is limited. The constant release of pollutants into water bodies has resulted in water quality degradation. Therefore, only the innovative approaches integrated with research will provide accurate solutions and methods for proper environment management and will enable understanding and prediction of the impacts of land-use in the Baltic Sea region. Modelling...
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Employing flowgraphs for forward route reconstruction in video surveillance system
PublicationPawlak’s flowgraphs were utilized as a base idea and knowledge container for prediction and decision making algorithms applied to experimental video surveillance system. The system is used for tracking people inside buildings in order to obtain information about their appearance and movement. The fields of view of the cameras did not overlap. Therefore, when an object was moving through unsupervised areas, prediction was needed...
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Flow Maps and Flow Patterns of R1233zd(E) in a Circular Minichannel at Low, Medium and High Values of Saturation Pressure
PublicationThere is a gap in knowledge regarding the flow pattern of low-boiling working fluids in the range of high saturation temperatures (above 120°C) and medium and high reduced pressures (0.5-0.9). Data are present in the literature for similar values of reduced pressures, but for lower values of saturation temperature. This is due to the existing refrigeration applications of these working fluids. At high values of reduced pressure,...
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Algorytmy hybrydowe optymalizacji w zastosowaniu do problemu sterowania systemami dystrybucji wody
PublicationW pracy analizowany jest problem optymalizującego zintegrowanego sterowania ilością i jakością w systemach dystrybucji wody. Proponowane decyzje i sterowania powinny zapewniać optymalizację przyjętego wskaźnika jakości, przy spełnieniu ograniczeń właściwych tej klasie systemów. Ostatecznie do rozwiązania złożonych zadań optymalizacji dynamicznej zaproponowane zostało podejście hybrydowe, wspomagające predykcyjne algorytmy sterowania...
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Applying artificial neural networks for modelling ship speed and fuel consumption
PublicationThis paper deals with modelling ship speed and fuel consumption using artificial neural network (ANN) techniques. These tools allowed us to develop ANN models that can be used for predicting both the fuel consumption and the travel time to the destination for commanded outputs (the ship driveline shaft speed and the propeller pitch) selected by the ship operator. In these cases, due to variable environmental conditions, making...
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Personal bankruptcy prediction using machine learning techniques
PublicationIt has become crucial to have an early prediction model that provides accurate assurance for users about the financial situation of consumers. Recent studies have focused on predicting corporate bankruptcies and credit defaults, not personal bankruptcies. Due to this situation, the present study fills the literature gap by comparing different machine learning algorithms to predict personal bankruptcy. The main objective of the...
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Assessment of under power ed propulsion machinery in electrically driven small inland waterway passenger ships from classification society point of view
PublicationPaper presents short operat ional a nd engineering analysis of underpowered propulsion in small electrically propelled small inland passenger ships. There is evidence that in certain weather conditions the phenomena of added aerodynamic resistance of small water crafts may have seriou s influence on their speed and manoeuvrability. Existing regulations like class societies rules for ship classification and construction or EU Directive 2006/87/EC do...
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ASSESSMENT OF UNDERPOWER ED PROPULSION MACHINERY IN ELECTRICALLY DRIVEN SMALL INLAND WATERWAY PASSENGER SHIPS FROM CLASSIFICATION SOCIETY POINT OF View
PublicationPaper presents short operat ional a nd engineering analysis of underpowered propulsion in small electrically propelled small inland passenger ships. There is evidence that in certain weather conditions the phenomena of added aerodynamic resistance of small water crafts may have serious influence on their speed and manoeuvrability. Existing regulations like class societies rules for ship classification and construction or EU Directive 2006/87/EC do...
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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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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Two Stage SVM and kNN Text Documents Classifier
PublicationThe paper presents an approach to the large scale text documents classification problem in parallel environments. A two stage classifier is proposed, based on a combination of k-nearest neighbors and support vector machines classification methods. The details of the classifier and the parallelisation of classification, learning and prediction phases are described. The classifier makes use of our method named one-vs-near. It is...
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Semantic Analysis and Text Summarization in Socio-Technical Systems
PublicationIn this chapter the authors present the results of the development the methodology for increasing the reliability of the functioning of the Socio-Technical System. The existed methods and algorithms for processing unstructured (textual) information were studied. Taking into account noted above strengths and weaknesses of Discriminant and Probabilistic approaches of Latent Semantic Relations analysis in of the summarization projection...
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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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SkinDepth - synthetic 3D skin lesion database
Open Research DataSkinDepth is the first synthetic 3D skin lesion database. The release of SkinDepth dataset intends to contribute to the development of algorithms for:
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Prediction of manoeuvring abilities of 10000 DWT pod-driven coastal tanker
PublicationThis paper aims to present a new approach in the prediction of manoeuvring abilities of pod-driven ships. A new mathematical model of motions based on MMG methodology was developed and a new type of description of forces acting on azimuth drives is presented. Captive model tests of medium-size coastal tanker and pod open water tests were carried out in CTO S.A. (Ship Design and Research Centre S.A.) to obtain hull hydrodynamic derivatives...
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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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Introduction to the special issue on machine learning in acoustics
PublicationWhen we started our Call for Papers for a Special Issue on “Machine Learning in Acoustics” in the Journal of the Acoustical Society of America, our ambition was to invite papers in which machine learning was applied to all acoustics areas. They were listed, but not limited to, as follows: • Music and synthesis analysis • Music sentiment analysis • Music perception • Intelligent music recognition • Musical source separation • Singing...
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MP3vec: A Reusable Machine-Constructed Feature Representation for Protein Sequences
Publication—Machine Learning (ML) methods have been used with varying degrees of success on protein prediction tasks, with two inherent limitations. First, prediction performance often depends upon the features extracted from the proteins. Second, experimental data may be insufficient to construct reliable ML models. Here we introduce MP3vec, a transferable representation for protein sequences that is designed to be used specifically for sequence-to-sequence...
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AN INNOVATIVE APPROACH TO PREDICTION ENERGETIC EFFECTS OF WOOD CUTTING PROCESS WITH CIRCULAR-SAW BLADES
PublicationIn the classical approach, energetic effects (cutting forces and cutting power) of wood sawing process are generally calculated on the basis of the specific cutting resistance, which is in the case of wood cutting the function of more or less important factors. The aim of the paper is to present a new calculating model using the application of modern fracture mechanics and to compare cutting parameters of native beech, Bendywood...
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Machine learning-based prediction of seismic limit-state capacity of steel moment-resisting frames considering soil-structure interaction
PublicationRegarding 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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Fast and reliable knowledge-based design closure of antennas by means of iterative prediction-correction scheme
PublicationA novel framework for expedited antenna optimization with an iterative prediction-correction scheme is proposed. The methodology is comprehensively validated using three real-world antenna structures: narrow-band, dual-band and wideband, optimized under various design scenarios. The keystone of the proposed approach is to reuse designs pre-optimized for various sets of performance specifications and to encode them into metamodels...
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Algorithms for Ship Movement Prediction for Location Data Compression
PublicationDue to safety reasons, the movement of ships on the sea, especially near the coast should be tracked, recorded and stored. However, the amount of vessels which trajectories should be tracked by authorized institutions, often in real time, is usually huge. What is more, many sources of vessels position data (radars, AIS) produces thousands of records describing route of each tracked object, but lots of that records are correlated...
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Rapid antenna design optimization using shape-preserving response prediction
PublicationAn approach to rapid optimization of antennas using the shape-preserving response-prediction (SPRP) technique and coarsediscretization electromagnetic (EM) simulations (as a low-fidelity model) is presented. SPRP allows us to estimate the response of the high-fidelity EM antenna model, e.g., its reflection coefficient versus frequency, using the properly selected set of so-called characteristic points of the low-fidelity model...
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Electrochemical simulation of metabolism for antitumor-active imidazoacridinone C-1311 and in silico prediction of drug metabolic reactions
PublicationThe metabolism of antitumor-active 5-diethylaminoethylamino-8-hydroxyimidazoacridinone (C-1311) has been investigated widely over the last decade but some aspects of molecular mechanisms of its metabolic transformation are still not explained. In the current work, we have reported a direct and rapid analytical tool for better prediction of C-1311 metabolism which is based on electrochemistry (EC) coupled on-line with electrospray...
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BANKRUPTCY PREDICTION IN VISEGRAD GROUP COUNTRIES
PublicationThe novelty of the study is a comprehensive look at the problem of bankruptcy forecasting in Visegrad Group countries (V4) and making a comparison in relation to the achievements obtained in more developed western countries. The conducted research based on a systematic literature review of 151 publications indexed in Scopus and Web of Science and bibliometric analysis. The results showed that the main lines of research are from...
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Multicomponent ionic liquid CMC prediction
PublicationWe created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (Sˆ), solvation enthalpy (DsolvGN), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen...
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Adaptacyjny algorytm filtracji sygnału fonokardiograficznego wykorzystujący sztuczną sieć neuronową
PublicationPodstawowym problemem podczas projektowania systemu autodiagnostyki chorób serca, bazującego na analizie sygnału fonokardiograficznego (PCG), jest konieczność zapewnienia, niezależnie od warunków zewnętrznych, sygnału o wysokiej jakości. W artykule, bazując na zdolności Sztucznej Sieci Neuronowej (SSN) do predykcji sygnałów periodycznych oraz quasi-periodycznych, został opracowany adaptacyjny algorytm filtracji dźwięków serca....
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Vibro piles performance prediction using result of CPT
PublicationVibro piles belong to the group of full displacement piles with an expanded base, characterised by a very high load capacity, especially in non-cohesive soils. The problem is to adopt a reliable method for the determination of full load–settlement (Q–s) curve. A frequent difficulty is the determination of the load capacity limit based on the static load test because the course of the load–settlement curve is of a linear nature....
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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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Estimation and Prediction of Vertical Deformations of Random Surfaces, Applying the Total Least Squares Collocation Method
PublicationThis paper proposes a method for determining the vertical deformations treated as random fields. It is assumed that the monitored surfaces are subject not only to deterministic deformations, but also to random fluctuations. Furthermore, the existence of random noise coming from surface’s vibrations is also assumed. Such noise disturbs the deformation’s functional models. Surface monitoring with the use of the geodetic levelling...
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Shales Leaching Modelling for Prediction of Flowback Fluid Composition
PublicationThe object of the paper is the prediction of flowback fluid composition at a laboratory scale, for which a new approach is described. The authors define leaching as a flowback fluid generation related to the shale processing. In the first step shale rock was characterized using X-ray fluorescence spectroscopy, X-ray diractometry and laboratory analysis. It was proven that shale rock samples taken from the selected sections of horizontal...
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Artificial intelligence models in prediction of response to cardiac resynchronization therapy: a systematic review
PublicationThe aim of the presented review is to summarize the literature data on the accuracy and clinical applicability of artificial intelligence (AI) models as a valuable alternative to the current guidelines in predicting cardiac resynchronization therapy (CRT) response and phenotyping of patients eligible for CRT implantation. This systematic review was performed...
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Grey wolf optimizer integrated within boosting algorithm: Application in mechanical properties prediction of ultra high-performance concrete including carbon nanotubes
PublicationNowadays, the construction industry has increasingly recognized the superior performance characteristics of ultra high-performance concrete (UHPC). Known for its exceptional durability and high tensile strength, UHPC material is revolutionizing structure standards subjected to extreme environmental conditions and heavy loads. This paper explores the enhancement of UHPC with nano- and micromaterials, employing advanced machine-learning...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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Consumer Bankruptcy Prediction Using Balanced and Imbalanced Data
PublicationThis paper examines the usefulness of logit regression in forecasting the consumer bankruptcy of households using an imbalanced dataset. The research on consumer bankruptcy prediction is of paramount importance as it aims to build statistical models that can identify consumers in a difficult financial situation that may lead to consumer bankruptcy. In the face of the current global pandemic crisis, the future of household finances...
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Integrated information and prediction Web Service WaterPUCK General concept
PublicationIn this paper, general concept of a new method as ‘Integrated information and prediction Web Service WaterPUCK’ for investigation influence of agricultural holdings and land-use structures on coastal waters of the southern Baltic Sea is presented. WaterPUCK Service is focused on determination of the current and future environmental status of the surface water and groundwater located in the Puck District (Poland) and its impact...
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Modeling SARS‐CoV‐2 proteins in the CASP‐commons experiment
PublicationCritical Assessment of Structure Prediction (CASP) is an organization aimed at advancing the state of the art in computing protein structure from sequence. In the spring of 2020, CASP launched a community project to compute the structures of the most structurally challenging proteins coded for in the SARS-CoV-2 genome. Forty-seven research groups submitted over 3000 three-dimensional models and 700 sets of accuracy estimates on...
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Accurate modelling of microwave structures using shape-preserving response prediction
PublicationArtykuł prezentuje metodologię dokładnego modelowania struktur mikrofalowych. Jest to zmodyfikowana wersja techniki opartej na procedurze przewidywania odpowiedzi z zachowaniem kształtu (shape-preserving response prediction, SPRP), która oszacowuje odpowiedź struktury mikrofalowej otrzymanej poprzez kosztowną obliczeniowo symulację elektromagnetyczną za pomocą taniego obliczeniowo modelu tejże struktury. Modyfikacja polega na wykorzystaniu...
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UNRES web server: Extensions to nucleic acids, prediction of peptide aggregation, and new types of restrained calculations
PublicationThe third version of the UNRES web server is described, in which the range of biological macromolecules treated and calculation types has been extended significantly. DNA and RNA molecules have been added to enable the user to run simulations of their folding/hybridization and dynamics. To increase the accuracy of the simulated proteins models, the restraints on secondary structure have been enhanced to include the probabilities...
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Road noise mapping in the city area: measurements compared to model-based estimations
PublicationThe paper presents an approach to the verification of noise prediction models in selected localization in the city of Gdansk. The experiments described include a comparison between environmentalmeasurement results performed in the terrain and the noise level prediction results. The NMPB-96 (Nouvelle Méthode de Prévision du Bruit) and Harmonoise models outcomes provide the subject ofthe analysis. The proposed solution of continuous...
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Evaluation of Response Amplitude Operator of Ship Roll Motions Based on the Experiments in White Noise Waves
PublicationEvaluation of the response amplitude operator (RAO) function for ship wave frequency motions by means of scale model tests in regular waves is a standard procedure conducted by hydrodynamic model testing institutions. The resulting RAO function allows for evaluating sufficiently reliable seakeeping predictions for low to moderate sea states. However, for standard hull forms, correct prediction of roll motion in irregular wave (and...
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Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
PublicationThe described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublicationPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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Detection of impulsive disturbances in archive audio signals
PublicationIn this paper the problem of detection of impulsive disturbances in archive audio signals is considered. It is shown that semi-causal/noncausal solutions based on joint evaluation of signal prediction errors and leave-one-out signal interpolation errors, allow one to noticeably improve detection results compared to the prediction-only based solutions. The proposed approaches are evaluated on a set of clean audio signals contaminated...
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Fuzzy Gaussian Decision Tree
PublicationThe Decision Tree algorithm is one of the first machine learning algorithms developed. It is used both as a standalone model and as an ensemble of many cooperating trees like Random Forest, AdaBoost, Gradient Boosted Trees, or XGBoost. In this work, a new version of the Decision Tree was developed for classifying real-world signals using Gaussian distribution functions and a fuzzy decision process. The research was carried out...