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Search results for: FIBER-REINFORCED CONCRETE BEAM, CHAINED MACHINE LEARNING MODEL, DUCTILITY INDEX, BENDING LOAD CAPACITY, ARTIFICIAL NEURAL NETWORKS
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The application of neural networks in forecasting the influence of traffic-induced vibrations on residential buildings
PublicationTraffic-induced vibrations may cause the cracking of plaster, damage to structural elements and, in extreme cases, may even lead to the structural collapse of residential buildings. The aim of this article is to analyse the effectiveness of a method of forecasting the impact of vibrations on residential buildings using the concept of artificial intelligence. The article presents several alternative forecasting systems for which...
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Robustness in Compressed Neural Networks for Object Detection
PublicationModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
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Designing acoustic scattering elements using machine learning methods
PublicationIn the process of the design and correction of room acoustic properties, it is often necessary to select the appropriate type of acoustic treatment devices and make decisions regarding their size, geometry, and location of the devices inside the room under the treatment process. The goal of this doctoral dissertation is to develop and validate a mathematical model that allows predicting the effects of the application of the scattering...
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Composite Beams with glass and reinforced or prestressed concrete - early stage of a theorethical and experimental analysis of a shear zone
PublicationThe aim of this article is to present a forgoing preparation for a theoretical and experimental analysis of a shear zone of a composite beams with glass and reinforced or prestressed concrete. Authors present their current knowledge, achievements and predicted challenges in later stages of the research. Properties of component materials are presented in the context of compensating weaknesses of one material with strengths of the...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublicationBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Screw displacement pile shaft deformations measured by vibrating wire and fiber optic systems during a static load test
PublicationThis paper describes a full scale static load test performed on a 400 mm diameter screw displacement pile equipped with four different strain measuring systems. Three types of vibrating wire strain gauges (VWSG) were used: global - retrievable, local attached to steel pipe and local concrete embedded. The fourth system was distributed fiber optic sensors based on Rayleigh back scattering (DFOS) - three in the pile cross section....
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Condition of Reinforced Concrete Structures and Their Degradation Mechanism at the Former Auschwitz Concentration and Extermination Camp
PublicationThis paper presents the results of investigations on reinforced concrete structures present in the former Auschwitz I and Auschwitz II-Birkenau concentration and extermination camp. Field inspection employing the non-destructive method of reinforcement potential measurement according to the ASTM-C 876–15 standard, followed by laboratory investigations performed on genuine historic reinforced concrete samples collected from the...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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The effect of macro polymer fibres length and content on the fibre reinforced concrete
PublicationThe paper presents studies of a ready-mix concrete containing polymer fibres of three different lengths: 24, 38 and 54 mm. The performed tests allowed to determine the effect of fibre volume fraction and length on the concrete strength. The basic parameters of concrete mixture (consistency, air content and bulk density) were identified. Fibre reinforced concrete belongs to a group of composite materials. The polymer fibres are...
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublicationThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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A robust optimization model for affine/quadratic flow thinning: A traffic protection mechanism for networks with variable link capacity
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MACHINE LEARNING
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Organizational Wisdom: The Impact of Organizational Learning on the Absorptive Capacity of an Enterprise
PublicationPurpose: In this article, we analyze the concept of organizational wisdom, indicating its key elements and verifieng the relationships between them. Design/Methodology/Approach: The study was conducted at Vive Textile Recycling Sp. z o.o in Poland. Empirical data was collected from 138 managers using the PAPI technique. Structural equation modelling (SEM) was performed to test the research hypotheses. Additionally, the significance...
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Reference-free determination of debonding length in reinforced concrete beams using guided wave propagation
PublicationThis paper presents theoretical and experimental investigations of guided wave propagation in reinforced concrete beams, with pre-existing debonding between steel rebars and concrete blocks, for the purpose of damage detection. The primary aim of these investigations was a detailed analysis of the possible applications of wave propagation in single and multiple debonding detection in reinforced concrete structures and reference-free...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublicationWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Sławomir Jerzy Ambroziak dr hab. inż.
PeopleSławomir J. Ambroziak was born in Poland, in 1982. He received the M.Sc., Ph.D. and D.Sc. degrees in radio communication from Gdańsk University of Technology (Gdańsk Tech), Poland, in 2008, 2013, and 2020 respectively. Since 2008 he is with the Department of Radiocommunication Systems and Networks of the Gdańsk Tech: 2008-2013 as Research Assistant, 2013-2020 as Assistant Professor, and since 2020 as Associate Professor. He is...
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Laboratory fatigue assessment of large geocomposite-reinforced double-layered asphalt concrete beams
PublicationGeosynthetic reinforcement of asphalt layers has been used for several decades. Evaluation of the influence of these materials on pavement fatigue life is still ongoing, especially for new types of geocomposites. This paper presents the evaluation of fatigue performance of large asphalt concrete beams reinforced with a new type of composite in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions...
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Laboratory fatigue assessment of large geocomposite-reinforced double-layered asphalt concrete beams
PublicationGeosynthetic reinforcement of asphalt layers has been used for several decades. Evaluation of the influence of these materials on pavement fatigue life is still ongoing, especially for new types of geocomposites. This paper presents the evaluation of fatigue performance of large asphalt concrete beams reinforced with a new type of composite in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions...
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Optical method supported by machine learning for urinary tract infection detection and urosepsis risk assessment
PublicationThe study presents an optical method supported by machine learning for discriminating urinary tract infections from an infection capable of causing urosepsis. The method comprises spectra of spectroscopy measurement of artificial urine samples with bacteria from solid cultures of clinical E. coli strains. To provide a reliable classification of results assistance of 27 algorithms was tested. We proved that is possible to obtain...
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An Automated Method for Biometric Handwritten Signature Authentication Employing Neural Networks
PublicationHandwriting biometrics applications in e-Security and e-Health are addressed in the course of the conducted research. An automated graphomotor analysis method for the dynamic electronic representation of the handwritten signature authentication was researched. The developed algorithms are based on dynamic analysis of electronically handwritten signatures employing neural networks. The signatures were acquired with the use of the...
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RMS-based damage detection in reinforced concrete beams: numerical simulations
PublicationImage-based damage detection methods using guided waves are well known and widely applied approaches in structural diagnostics. They are usually utilized in detection of surface damages or defects of plate-like structures. The article presents results of the study of applicability of imaging wave-based methods in detection in miniscule internal damage in the form of debonding. The investigations were carried out on numerical models...
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Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
PublicationTreatment of municipal wastewater to meet the stringent effluent quality standards is an energy-intensive process and the main contributor to the costs of wastewater treatment plants (WWTPs). Analysis and prediction of energy consumption (EC) are essential in designing and operating sustainable energy-saving WWTPs. In this study, the effect of wastewater, hydraulic, and climate-based parameters on the daily consumption of EC by...
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Process of Medical Dataset Construction for Machine Learning-Multifield Study and Guidelines
PublicationThe acquisition of high-quality data and annotations is essential for the training of efficient machine learning algorithms, while being an expensive and time-consuming process. Although the process of data processing and training and testing of machine learning models is well studied and considered in the literature, the actual procedures of obtaining data and their annotations in collaboration with physicians are in most cases...
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Application of artificial neural networks (ANN) as multiple degradation classifiers in thermal and flow diagnostics
PublicationPrzedyskutowano problem zwiększenia dokładności rozpoznawania wielokrotnych degradacji eksploatacyjnych urządzeń składowych dużych obiektów energetycznych. Zastosowani sieć neuronową (SSN) o skokowych funkcjach przejścia. Sprawdzono możliwości przyspieszenia treningu sieci neuronowych. Zastosowano modułową metodę budowy SSN, polegającą na dedykowaniu pojedynczej sieci do rozpoznawania tylko jednego typu degradacji.
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Accidental wow defect evaluation using sinusoidal analysis enhanced by artificial neural networks
PublicationArtykuł przedstawia metodę do wyznaczania charakterystyki pasożytniczych modulacji częstotliwości (kołysanie) obecnych w archiwalnych nagraniach dźwiękowych. Prezentowane podejście wykorzystuje śledzenie zmian sinusoidalnych komponentów dźwięku które odzwierciedlają przebieg kołysania. Analiza sinusoidalna wykorzystana jest do ekstrakcji składowych tonalnych ze zniekształconych nagrań dźwiękowych. Dodatkowo, w celu zwiększenia...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublicationThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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IEEE Transactions on Neural Networks and Learning Systems
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Deep learning in the fog
PublicationIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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MACHINE LEARNING–BASED ANALYSIS OF ENGLISH LATERAL ALLOPHONES
PublicationAutomatic classification methods, such as artificial neural networks (ANNs), the k-nearest neighbor (kNN) and selforganizing maps (SOMs), are applied to allophone analysis based on recorded speech. A list of 650 words was created for that purpose, containing positionally and/or contextually conditioned allophones. For each word, a group of 16 native and non-native speakers were audio-video recorded, from which seven native speakers’...
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2D Mathematical Model of the Commutator Sliding Contact of an Electrical Machine
PublicationW artykule przedstawiono model matematyczny 2D komutatorowego zestyku ślizgowego z wieloma stopniami swobody. W modelu uwzględniono zmienne wymuszenia działające na szczotkę. Wymuszenia te są wynikiem falistości wirującego komutatora. Szczotka została zamodelowana jako system wielu mas, elementów sprężystych i tłumików rozłożonych w kierunku stycznym i promieniowym. Zamodelowano wszystkie oddziaływania lepkosprężyste pomiędzy komutatorem...
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Predicting Ice Phenomena in a River Using the Artificial Neural Network and Extreme Gradient Boosting
PublicationForecasting 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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Size effect in concrete beams under bending – influence of the boundary layer and the numerical description of cracks
PublicationIn the paper the size effect phenomenon in concrete is analysed. The results of numerical simulations of using FEM on geometrically similar un-notched and notched concrete beams under bending are presented. Concrete beams of four different sizes and five different notch heights under three-point bending test were simulated. In total 18 beams were analysed. Two approaches were used to describe cracks in concrete. First, eXtended...
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Influence of local bush wear on water lubricated sliding bearing load carrying capacity
PublicationOne of main problems concerning water-lubricated bearings is their durability. There are known cases of bearings with life time measured in decades, and some, whose refurbishment was necessary just days after start-up. Obtaining stable fluid film friction plays key role in the durability of these bearings. Unfortunately, their load-carrying capacity is limited due to water's low-viscosity. The conducted experimental...
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Acoustic emission signals in concrete beams under 3-point bending (beams #1, #2, #3)
Open Research DataThe DataSet contains the results of the mechanical behaviour of concrete beams with dimensions 40 x 40 x 160 cm3under the 3-point bending. The beams were made of concrete with the following ingredients: cement CEM I 42.5R (330 kg/m3), aggregate 0/2 mm (710 kg/m3), aggregate 2/8 mm (664 kg/m3), aggregate 8/16 mm (500 kg/m3), water (165 kg/m3) and super-plasticizer...
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Advancing Solar Energy: Machine Learning Approaches for Predicting Photovoltaic Power Output
PublicationThis research is primarily concentrated on predicting the output of photovoitaic power, an essential field in the study of renewable energy. The paper comprehensively reviews various forecasting methodologies, transitioning from conventional physical and statistical methods to advanced machine learning (ML) techniques. A significant shift has been observed from traditional point forecasting to machine learning-based forecasting...
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Doped Nanocrystalline Diamond Films as Reflective Layers for Fiber-Optic Sensors of Refractive Index of Liquids
PublicationThis paper reports the application of doped nanocrystalline diamond (NCD) films—nitrogen-doped NCD and boron-doped NCD—as reflective surfaces in an interferometric sensor of refractive index dedicated to the measurements of liquids. The sensor is constructed as a Fabry–Pérot interferometer, working in the reflective mode. The diamond films were deposited on silicon substrates by a microwave plasma enhanced chemical vapor deposition...
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Vibration of Steel–Concrete Composite Beams Using the Timoshenko Beam Model
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Comparative study on fracture evolution in steel fibre and bar reinforced concrete beams using acoustic emission and digital image correlation techniques
PublicationIn recent decades, the demand for sustainable construction practices has increased, but raw materials such as reinforcing steel remain scarce. Therefore, steel fibres have emerged as a popular and sustainable choice in the construction industry, offering a cost-effective alternative to traditional steel bar reinforcement for both flatwork and elevated structures. The purpose of this study is therefore to compare the performance...
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Improvement of the load capacity of the road overpass as a result of repairs after breakage caused by vehicle impacts
PublicationDamage of spans of the overpass caused by impact of underpassing vehicles are a frequent case. Objects that use prefabricated load-bearing elements that are not designed for such impacts are particularly exposed. After impact, such parts suffer extensive damage that need repair. Taking advantages of this recovery actions it is worth to perform strengthening that will protect object against possible future impacts. In this study...
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Verification of Selected Calculation Methods Regarding Shear Strength in Reinforced and Prestressed Concrete Beams
PublicationThe purpose of this article was an attempt to compare selected calculation methods regarding shear strength in reinforced and prestressed concrete beams. Several calculation methods were tested. This included codes: PN-EN 1992-1-1:2008 [1], ACI 318- 14 [2] and fib Model Code for Concrete Structures 2010 [3]. The analysis also consists of methods published in technical literature. Calculations of shear strengths were made based...
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Network lifetime maximization in wireless mesh networks for machine-to-machine communication
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Restoration and preservation of the reinforced concrete poles of fence at the former Auschwitz concentration and extermination camp
PublicationThe objective of this study was to assess the present state of the reinforced concrete poles of fence at the former Auschwitz I and Auschwitz II-Birkenau concentration and extermination camp. The poles were subjected to renovation about 10 years ago. After this time some deficiencies of applied renovation method were noticed. Cracks appeared between fresh and original part of concrete cover. Analysis of the reasons of these failures...
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Restoration and preservation of the reinforced concrete poles of fence at the former Auschwitz concentration and extermination camp
PublicationThe objective of this study was to assess the present state of the reinforced concrete poles of fence at the former Auschwitz I and Auschwitz II-Birkenau concentration and extermination camp. The poles were subjected to renovation about 10 years ago. After this time some deficiencies of applied renovation method were noticed. Cracks appeared between fresh and original part of concrete cover. Analysis of the reasons of these failures...
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Determination of refractive index dispersion using fiber-optic low-coherence Fabry–Perot interferometer: implementation and validation
PublicationWe present the implementation and validation of low-coherence Fabry–Perot interferometer for refractive index dispersion measurements of liquids. A measurement system has been created with the use of four superluminescent diodes with different optical parameters, a fiber-optic coupler and an optical spectrum analyzer. The Fabry–Perot interferometer cavity has been formed by the fiber-optic end and mirror surfaces mounted on a micromechanical...
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Model-free and Model-based Reinforcement Learning, the Intersection of Learning and Planning
PublicationMy 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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Testing of low temperature behaviour of asphalt mixtures in bending creep test
PublicationThe paper presents a method of bending beam test and its importance for evaluation of asphalt mixtures behaviour at low temperatures. Two types of asphalt mixtures: asphalt concrete AC with normal paving grade bitumen and stone mastic asphalt SMA with SBS-modified bitumen were tested. Long-term oven ageing (LTOA) test was also used in the laboratory according to SHRP procedure. The Burgers model was applied and rheological parameters...