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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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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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Baseline-free debonding detection in reinforced concrete structures by elastic wave propagation
PublicationThe article presents the results of the numerical and experimental analysis concerning wave propagation in reinforced concrete (RC) beams with various extent of debonding between the steel rod and concrete cover. The main aim of the paper was to consider the unsolved research gaps, which considerably limit the application of wave-based methods in practice. The propagation of the flexural wave modes excited and registered on the...
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ZnO coated fiber optic microsphere sensor for the enhanced refractive index sensing
PublicationOptical fiber-based sensors are expected to become key components in the control of industrial processes,and the tuning and the enhancement of their sensing properties are crucial for the further developmentof this technology. Atomic Layer Deposition (ALD), a vapor phase technique allowing for the deposition ofconformal thin films, is particularly suited for the deposition of controllable thin films on challenging sub-strates....
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Debonding Detection in Reinforced Concrete Beams with the Use of Guided Wave Propagation
PublicationOne of the most frequent damage of the reinforced concrete structures is debonding between steel bar and concrete cover. In the case of debonding occurrence not only the strength of the structure decreases, but also it is more vulnerable to corrosion damages. For this reason fast and effective methods of debonding detection in an early stage of its development need a significant boost. The paper presents analytical and experimental...
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A novel heterogeneous model of concrete for numerical modelling of ground penetrating radar
PublicationThe ground penetrating radar (GPR) method has increasingly been applied in the non-destructive testing of reinforced concrete structures. The most common approach to the modelling of radar waves is to consider concrete as a homogeneous material. This paper proposes a novel, heterogeneous, numerical model of concrete for exhaustive interpretation of GPR data. An algorithm for determining the substitute values of the material constants...
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STABILITY AND LOAD BEARING CAPACITY OF A BARS WITH BUILT UP CROSS SECTION AND ELASTIC SUPPORTS
PublicationThe present paper is devoted to the numerical analysis and experimental tests of compressed bars with built–up cross section which are commonly used as a top chord of the roof trusses. The significant impact on carrying capacity for that kind of elements in case of out-of-plane buckling is appropriate choice of battens which are used to provide interaction between separate members. Linear buckling analysis results and nonlinear static...
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Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services
PublicationThis paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of...
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A Proposed Soft Computing Model for Ultimate Strength Estimation of FRP-Confined Concrete Cylinders
PublicationIn this paper, the feed-forward backpropagation neural network (FFBPNN) is used to propose a new formulation for predicting the compressive strength of fiber-reinforced polymer (FRP)-confined concrete cylinders. A set of experimental data has been considered in the analysis. The data include information about the dimensions of the concrete cylinders (diameter, length) and the total thickness of FRP layers, unconfined ultimate concrete...
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Remote sensing in laboratory diagnostics of reinforced concrete elements – current development and vision for the future
PublicationContinuous emergence of new concrete types and kinds of reinforcement, as well as technological solutions in the field of structural engineering have made great demand for diagnostic tests of reinforced concrete elements. New challenges and problems facing people require new more efficient tools for laboratory diagnostics than those commonly used. Remote sensing may be the answer to this demand. In this paper the author describes...
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Remote sensing in laboratory diagnostics of reinforced concrete elements – current development and vision for the future
PublicationContinuous emergence of new concrete types and kinds of reinforcement, as well as technological solutions in the field of structural engineering have made great demand for diagnostic tests of reinforced concrete elements. New challenges and problems facing people require new more efficient tools for laboratory diagnostics than those commonly used. Remote sensing may be the answer to this demand. In this paper the author describes...
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Development of a tropical disease diagnosis system using artificial neural network and GIS
PublicationExpert systems for diagnosis of tropical diseases have been developed and implemented for over a decade with varying degrees of success. While the recent introduction of artificial neural networks has helped to improve the diagnosis accuracy of such systems, this aspect is still negatively affected by the number of supported diseases. A large number of supported diseases usually corresponds to a high number of overlapping symptoms,...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublicationThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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Artificial Neural Networks in Classification of Steel Grades Based on Non-Destructive Tests
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Designing the Composition of Cement Stabilized Rammed Earth Using Artificial Neural Networks
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The Influence of Input Data Standardization Method on Prediction Accuracy of Artificial Neural Networks
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Self-organizing Artificial Neural Networks into Hydrographic Big Data Reduction Process
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Flexural behaviour of concrete slabs reinforced with FRP bars in experiments and according to aci ACI 440.1R guide
PublicationThe paper presents research conducted on two concrete slabs reinforced with the carbon composite bars and two other concrete slabs reinforced with basalt composite bars. The carbon bars were plain, while the basalt ones were ribbed. The slabs were experimentally investigated in the flexural state of effort with the concentrated forces applied. The results are compared with the analytical solution proposed in the guide ACI 440.1R-06...
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Characterization of Corrosion-Induced Fracture in Reinforced Concrete Beams Using Electrical Potential, Ultrasound and Low-Frequency Vibration
PublicationThe paper deals with the non-destructive experimental testing of the reinforced concrete beams under progressive corrosion. A series of experiments using electrical potential, ultrasound and low-frequency vibrations techniques are reported. Electrical potential and natural frequencies were used to characterise and monitor the corrosion process at its initial state. The P-wave velocity measurements were proved to be effective in...
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Finite element analysis on failure of reinforced concrete corner in sewage tank under opening bending moment
PublicationW artykule omówiono mechanizm uszkodzenia żelbetowego zbiornika ściekowego w narożniku ściany, który uległ uszkodzeniu podczas próby wypełnienia na skutek nadmiernych przemieszczeń poziomych ścian pod wpływem otwierającego momentu zginającego. Aby wyjaśnić przyczyny awarii, przeprowadzono kompleksowe obliczenia metodą elementów skończonych (MES) żelbetowego zbiornika w warunkach odkształcenia płaskiego. Beton zamodelowano za pomocą...
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Load capacity and serviceability conditions for footbridges made of fibre-reinforced polymer laminates = Warunki nośności i użytkowalności w odniesieniu do kładek z laminatów polimerowych
PublicationThe contribution is focused on derivation of the Ultimate Limit State (ULS) and Serviceability Limit State (SLS) design criteria for footbridges built of fibre-reinforced polymer matrix (FRP) laminates. The ULS design criterion is based on the design guidelines for above-ground, pressure, FRP composite tanks and the Tsai-Wu failure criterion, which is used to predict the onset of FRP laminates damage. The SLS criterion is based...
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Static load test on concrete pile – instrumentation and results interpretation
PublicationFor some time (since 8-10 years in Poland) a special static load tests on instrumented piles are carried out. Such studies are usually of a scientific nature and provide detailed quantitative data on the load transfer into the ground and characteristics of particular soil layers interaction with a pile shaft and pile base. Deep knowledge about the pile-subsoil interaction can be applied for a various design purposes, e.g. numerical...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe 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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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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Estimation of the parameters of the discrete model of a steel–concrete composite beam
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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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A Novel Iterative Decoding for Iterated Codes Using Classical and Convolutional Neural Networks
PublicationForward error correction is crucial for communication, enabling error rate or required SNR reduction. Longer codes improve correction ratio. Iterated codes offer a solution for constructing long codeswith a simple coder and decoder. However, a basic iterative code decoder cannot fully exploit the code’s potential, as some error patterns within its correction capacity remain uncorrected.We propose two neural network-assisted decoders:...
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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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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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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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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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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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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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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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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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A robust optimization model for affine/quadratic flow thinning: A traffic protection mechanism for networks with variable link capacity
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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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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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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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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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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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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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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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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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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.