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Wyniki wyszukiwania dla: MACHINE LEARNING ALGORITHM SOIL-STRUCTURE INTERACTION SEISMIC RISK ASSESSMENT RESIDUAL INTERSTORY DRIFT SEISMIC DEMAND SEISMIC FAILURE PROBABILITY
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Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublikacjaThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublikacjaMy doctoral dissertation is intended as the compound of four publications considering: structure and randomness in planning and reinforcement learning, continuous control with ensemble deep deterministic policy gradients, toddler-inspired active representation learning, and large-scale deep reinforcement learning costs.
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Interference aware bluetooth scatternet (re)configuration algorithm IBLUERA
PublikacjaThis paper presents a new algorithm IBLUEREA, which enables reconfiguration of Bluetooth scatternet to reduce interference. IBLUEREA makes use of the complex model comparing ISM environment efficiency. The mechanism envisages the use of the assessment of the probability of successful (unsuccessful) frame transmission in order to take a decision concerning co-existence of technologies which make use of the same ISM band (here Bluetooth...
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Assessment of chemical‐crosslink‐assisted protein structure modeling in CASP13
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Low-frequency tripping characteristics of residual current devices
PublikacjaFast development of various types of converters makes their utilization in industry and in domestic installations very common. Due to converters, an earth fault current waveform in modern circuits can be distorted or its frequency can be different than 50/60 Hz. Frequency of earth fault (residual) current influences tripping of residual current devices which are widely used in low voltage systems. This paper presents the behaviour...
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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...
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Optimal retrofit strategy using viscous dampers between adjacent RC and SMRFs prone to earthquake‑induced pounding
PublikacjaNowadays, retrofitting-damaged buildings is an important challenge for engineers. Finding the optimal placement of Viscous Dampers (VDs) between adjacent structures prone to earthquake-induced pounding can help designers to implement VDs with optimizing the cost of construction and achieving higher performance levels for both structures. In this research, the optimal placement of linear and nonlinear VDs between the 3-story, 5-story,...
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Robust-adaptive dynamic programming-based time-delay control of autonomous ships under stochastic disturbances using an actor-critic learning algorithm
PublikacjaThis paper proposes a hybrid robust-adaptive learning-based control scheme based on Approximate Dynamic Programming (ADP) for the tracking control of autonomous ship maneuvering. We adopt a Time-Delay Control (TDC) approach, which is known as a simple, practical, model free and roughly robust strategy, combined with an Actor-Critic Approximate Dynamic Programming (ACADP) algorithm as an adaptive part in the proposed hybrid control...
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Modular machine learning system for training object detection algorithms on a supercomputer
PublikacjaW pracy zaprezentowano architekturę systemu służącego do tworzenia algorytmów wykorzystujących metodę AdaBoost i służących do wykrywania obiektów (np. twarzy) na obrazach. System został podzielony na wyspecjalizowane moduły w celu umożliwienia łatwej rozbudowy i efektywnego zrównoleglenia implementacji przeznaczonej dla superkomputera. Na przykład, system może być rozszerzony o nowe cechy i algorytmy ich ekstrakcji bez konieczności...
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Efficient sampling of high-energy states by machine learning force fields
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Stacking and rotation-based technique for machine learning classification with data reduction
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POPULATION-BASED MULTI-AGENT APPROACH TO SOLVING MACHINE LEARNING PROBLEMS
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublikacjaThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Preferred Benchmarking Criteria for Systematic Taxonomy of Embedded Platforms (STEP) in Human System Interaction Systems
PublikacjaThe rate of progress in the field of Artificial Intelligence (AI) and Machine Learning (ML) has significantly increased over the past ten years and continues to accelerate. Since then, AI has made the leap from research case studies to real production ready applications. The significance of this growth cannot be undermined as it catalyzed the very nature of computing. Conventional platforms struggle to achieve greater performance...
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Analysis of pounding between adjacent buildings founded on different soil types
PublikacjaEarthquake-induced pounding was experienced in many previous earthquakes and it was found to be a critical issue. This study investigates the effect of pounding between buildings founded on the same and different soil types. Three 3-D buildings with 4, 6 and 8 storeys were considered in this study. Three pounding scenarios were taken into account, i.e. pounding between 4-storey and 6-storey buildings, between 4-storey and 8-storey...
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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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Incorporating installation effects into the probability analysis of controlled modulus columns
PublikacjaThis technical report presents the probabilistic analysis which integrates the Monte Carlo simulation (MCS) with random field theory to model the load–displacement behavior of Controlled Modulus Columns (CMCs) in overconsolidated Poznań clay. Presented study focuses on the practical aspects of statistical analysis of geotechnical data, numerical model development, and results evaluation. Variability and spatial distribution of...
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On a systematic perspective on risk for formal safety assessment (FSA)
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A Model of Risk for Assessment of Safety of Ships in Damaged Conditions
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Risk assessment of biocides in roof paint. Part 1
PublikacjaSzereg pokryć dachowych, jak farby dachowe, zawiera w swoim składzie biocydy. Dotychczas nie wiadomo do jakiego stopnia biocydy wymywane są z farb dachowych, a ponadto jakie ich stężenie może występować w systemach zbierających wodę deszczową. Zbadano podatność na wymywanie biocydów z różnych niemieckich farb dachowych oraz oszacowano ich stężenie w zebranej wodzie deszczowej
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Methodological issues of security vulnerability analysis and risk assessment
PublikacjaArtykuł przedstawia wybrane aspekty metodyczne związane z zarządzaniem bezpieczeństwem i ochroną instalacji podwyższonego ryzyka. Podkreślono, że występują instalacje podwyższonego ryzyka, które wymagają specjalnej uwagi w zarządzaniu bezpieczeństwem. Zaproponowano metodykę opartą na wiedzy do zintegrowanej analizy LOPA (warstw zabezpieczeń) i ROPA (pierścieni zabezpieczeń). Nadrzędnym celem jest opracowanie metod i narzędzi wspomagających...
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Uncertainty assessment in the safety and security oriented risk analyses
PublikacjaW artykule przedstawiono uwzględnienie oceny niepewności w procesie związanym z analizą ryzyka i analizą bezpieczeństwa oraz ochroną informacji. Przedstawiona została koncepcja oceny bezpieczeństwa i zarządzania ryzykiem z uwzględnieniem analizy warstw zabezpieczeń LOPA. W artykule nakreślono wyzwania związane z integracją podejścia oceny bezpieczeństwa (safety) i ochrony informacji (security) w projektowaniu systemów zabezpieczeń...
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A risk assessment of dietary exposure to ochratoxin A for the Polish population
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Failure Analysis of footbridge made of composite materials
PublikacjaFinite element method analysis of a pedestrian footbridge made of sandwich material is presented. The internal structure of the material is modelled as a structural shell assuming the Equivalent Single Layer approach (ESL). Two FEM commercial codes are employed. The response of the structure is studied in order to determine the load level that activates Hashin and Tsai-Wu failure criteria. Some practical aspects of designing footbridges...
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INFLUENCE OF WRONGLY ASSUMED PROBABILITY DISTRIBUTION ON THE UNCERTAINTY OF RESISTANCE MEASUREMENT BY TECHNICAL METHOD
PublikacjaThe paper presents studies on the influence of probability distributions on the expanded uncertainty of the resistance measurement. Choosing the correct probability distribution is very important to estimate of measurement uncertainty. The most commonly used distribution is the rectangular distribution. The paper presents the results of analysis of the resistance measurement uncertainty using the technical method of two resistances:...
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Designing RBF Networks Using the Agent-Based Population Learning Algorithm
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Learning from Imbalanced Data Using Over-Sampling and the Firefly Algorithm
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Evaluation of thermal cracking probability for asphalt concretes with high percentage of RAP
PublikacjaThe paper presents determination of the probability of thermal cracking of asphalt mixtures with different reclaimed asphalt pavement (RAP) content on the basis of laboratory tests and analytical evaluation using thermal stress development method. Probability was evaluated taking into consideration: the type and gradation of the mixture and the quality and content of RAP. Thermal stresses were determined using two models: elastic and...
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The trajectories of the financial crisis of companies at risk of bankruptcy
PublikacjaThis article concerns the assessment of the trajectory of the collapse of enterprises in Central Europe. The author has developed a model of a Kohonen artificial neural network. This model was used to determine 6 different classes of risk and was allowed to graphically determine the 5- to 10-year trajectory of going bankrupt. The study used data on 140 companies listed on the Warsaw Stock Exchange. This population was divided into...
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Software Factory project for enhancement of student experiential learning
PublikacjaProviding opportunities for students to work on real-world software development projects for real customers is critical to prepare students for the IT industry. Such projects help students to understand what they will face in the industry and experience real customer interaction and challenges in collaborative work. To provide this opportunity in an academic environment and enhance the learning and multicultural teamwork experience,...
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Pounding mitigation of a short-span cable-stayed bridge using a new hybrid passive control system
PublikacjaThis paper investigates the effectiveness of a new hybrid passive control system on the seismic response of an existing steel cable-stayed bridge considering the pounding effect. The proposed hybrid passive control system comprises a seismic isolator and a metallic damper. The bridge is located in a high seismic zone and has suffered several damages including the earthquake-induced pounding damage during the 1988 earthquake....
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Simplified probabilistic analysis of settlement of cyclically loaded soil stratum using point estimate method
PublikacjaThe paper deals with the probabilistic analysis of settlement of a non-cohesive soil layer subjected to cyclic loading. Originally, the settlement assessment is based on deterministic compaction model which requires integration of a set of differential equations. However, making use of the Bessel functions the settlement of the soil stratum can be calculated by means of simplified algorithm. The compaction model parameters were...
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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublikacjaThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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From the Dynamic Lattice Liquid Algorithm to the Dedicated Parallel Computer – mDLL Machine
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Measurements of electron drift velocity in OCS
PublikacjaWykonano pomiary prędkości dryfu elektronów w funkcji zredukowanego pola elektrycznego E/N. Wyniki tych pomiarów porównano z wynikami pomiarów w CO2 i N2O.
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MACHINE VISION DETECTION OF THE CIRCULAR SAW VIBRATIONS
PublikacjaDynamical properties of rotating circular saw blades are crucial for both production quality and personnel safety. This paper presents a novel method for monitoring circular saw vibrations and deviations. A machine vision system uses a camera and a laser line projected on the saw’s surface to estimate vibration range. Changes of the dynamic behaviour of the saw were measured as a function of the rotational speed. The critical rotational...
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Detection of high frequency current components by residual current devices
PublikacjaThe negative impact of current harmonics on the main components of residual current devices is presented. A solution for the improvement of the operation of residual current devices is proposed.
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Residual current devices in installations with PV energy sources
PublikacjaThe paper presents the principles of residual current devices (RCDs) application in photovoltaic (PV) installations. Provisions of standards in this regard are commented on, in particular, attention is drawn to the lack of obligation to use of RCDs in PV installations. The issue of the shape of the earth fault current and the level of leakage currents in such installations are discussed. These factors influence the selection of...
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Testing Question Order Effects of Self-perception of Risk Propensity on Simple Lottery Choices as Measures of the Actual Risk Propensity
PublikacjaUncertainty together with the necessity of making choices inevitably results in risky decisions. For many years now, scientists have been studying notions connected with risk such as risk management, risk perception or risk propensity. While many sophisticated methods regarding measurement of risk propensity have been developed so far, it seems that little attention has been paid to checking whether they are not inherently flawed....
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Subsoil degradation effect in reliability analysis of the jack-up platform structure
PublikacjaStructural reliability analysis is considered, by FORM and SORM applied to a certain idealized soil-platform structure interaction problem due to cyclic water wave and wind loads. Wave and wind loads are random variables, whereas dead load is deterministic. Load parameters are typical for storm conditions in the Baltic Sea. The soil-structure interaction is idealized as a set of linear translational and rotational springs. Due...
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Fundamental Schemes to Determine Disjoint Paths for Multiple Failure Scenarios
PublikacjaDisjoint path routing approaches can be used to cope with multiple failure scenarios. This can be achieved using a set of k (k> 2) link- (or node-) disjoint path pairs (in single-cost and multi-cost networks). Alternatively, if Shared Risk Link Groups (SRLGs) information is available, the calculation of an SRLG-disjoint path pair (or of a set of such paths) can protect a connection against the joint failure of the set of links...
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Multivariate Features Extraction and Effective Decision Making Using Machine Learning Approaches
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Machine learning techniques combined with dose profiles indicate radiation response biomarkers
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Overcoming “Big Data” Barriers in Machine Learning Techniques for the Real-Life Applications
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Machine Learning and data mining tools applied for databases of low number of records
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublikacjaThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublikacjaIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
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EU Enlargement and Labour Demand in the New Member States
PublikacjaResearch to date on labour market responses to EU integration has tended to concentrate on the labour markets of the 'old' EU members. But what effects has the integration of trade had on wages in the new member states? The following article attempts to answer this question using and empirical model of conditional labour demand.