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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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Direct shear stress vs strain relation for fiber reinforced composites
PublicationThe majority of fiber reinforced composites exhibit strong non-linear behavior in in-plane shear state. The effect is attributed to the micro-cracks appearing in the matrix and can be modeled on the micro and macro level. In this work the author proposes constitutive laws describing the non-linear in-plane shear response, which can be alternative for the relations commonly considered in the literature. The proposed equations are...
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Influence of stirrups in a concrete shell on strengthening reinforced concrete column
PublicationTwelve concrete columns, with a 150x150mm square section and three columns with a circular section (d=200mm), are tested to investigate the effect of strengthening by RC jacket. Based on a confined concrete model for axial static loading, an analytical methods, reported in the literature are proposed to predict the behavior of columns with RC jacket. The results support the conception that the effect of strengthening depends...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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SIMULATIONS OF FRACTURE IN CONCRETE BEAMS UNDER BENDING USING A CONTINUUM AND DISCRETE APPROACH
PublicationThe paper describes two-dimensional meso-scale results of fracture in notched concrete beams under bending. Concrete was modelled as a random heterogeneous 4-phase material composed of aggregate particles, cement matrix, interfacial transitional zones and air voids. Within continuum mechanics, the simulations were carried out with the finite element method based on a isotropic damage constitutive model enhanced by a characteristic...
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublicationNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Processing of musical data employing rough sets and artificial neural networks
PublicationArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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The effect of external load on ultrasonic wave attenuation in steel bars under bending stresses
PublicationThe stress state in deformed solids has a significant impact on the attenuation of an ultrasonic wave propagating through the medium. Measuring a signal with certain attenuation characteristics can therefore provide useful diagnostic information about the stress state in the structure. In this work, basic principles behind a novel attenuation-based diagnostic framework are introduced. An experimental study on steel bars under three-point...
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Preparation and Characterization of Microsphere ZnO ALD Coating Dedicated for the Fiber-Optic Refractive Index Sensor
PublicationWe report the fabrication of a novel fiber-optic sensor device, based on the use of a microsphere conformally coated with a thin layer of zinc oxide (ZnO) by atomic layer deposition (ALD), and its use as a refractive index sensor. The microsphere was prepared on the tip of a single-mode optical fiber, on which a conformal ZnO thin film of 200 nm was deposited using an ALD process based on diethyl zinc (DEZ) and water at 100 °C....
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublicationLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Parameter estimation of a discrete model of a reinforced concrete slab
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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COVID-19 severity forecast based on machine learning and complete blood count data
PublicationProper triage of COVID-19 patients is a key factor in eective case management, especially with limited and insucient resources. In this paper, we propose a machine-aided diagnostic system to predict how badly a patient with COVID-19 will develop disease. The prognosis of this type is based on the parameters of commonly used complete blood count tests, which makes it possible to obtain data from a wide range of patients.We chose...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublicationThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep 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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Graph Neural Networks and Structural Information on Ionic Liquids: A Cheminformatics Study on Molecular Physicochemical Property Prediction
PublicationIonic liquids (ILs) provide a promising solution in many industrial applications, such as solvents, absorbents, electrolytes, catalysts, lubricants, and many others. However, due to the enormous variety of their structures, uncovering or designing those with optimal attributes requires expensive and exhaustive simulations and experiments. For these reasons, searching for an efficient theoretical tool for finding the relationship...
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Load capacity of steel-aluminium brackets under static and cyclic laboratory tests
PublicationThe aim of the research is the laboratory investigation of steel-aluminium brackets employed to fasten lightweight curtain walls to building facilities. Static pressure, suction forces, and cyclic loads parallel to end plates (horizontal – to simulate wind influence) were applied in the study. The steel-aluminium brackets were tested on a reinforced concrete substrate made of C30/37 concrete class to simulate the real working conditions....
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A novel formulation of 3D spectral element for wave propagation in reinforced concrete
PublicationThe paper deals with numerical simulations of wave propagation in reinforced concrete for damage detection purposes. A novel formulation of a 3D spectral element was proposed. The reinforcement modelled as the truss spectral element was embedded in the 3D solid spectral finite element. Numerical simulations have been conducted on cuboid concrete specimens reinforced with two steel bars. Different degradation models were considered...
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Integrating Experience-Based Knowledge Representation and Machine Learning for Efficient Virtual Engineering Object Performance
PublicationMachine learning and Artificial Intelligence have grown significant attention from industry and academia during the past decade. The key reason behind interest is such technologies capabilities to revolutionize human life since they seamlessly integrate classical networks, networked objects and people to create more efficient environments. In this paper, the Knowledge Representation technique of Set of Experience...
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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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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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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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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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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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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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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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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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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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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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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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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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Bone healing under different lay‐up configuration of carbon fiber‐reinforced PEEK composite plates
PublicationSecondary healing of fractured bones requires an application of an appropriate fixa-tor. In general, steel or titanium devices are used mostly. However, in recent years,composite structures arise as an attractive alternative due to high strength to weightratio and other advantages like, for example, radiolucency. According to Food andDrug Administration (FDA), the only unidirectionally reinforced composite allowed tobe implanted...
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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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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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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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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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DESIGN ERRORS CAUSE AN EMERGENCY OF THE REINFORCED CONCRETE TANK FOR COKE
PublicationThe quality of the developed design documentation and the maintenance of the technological regime during construction works have a decisive impact on the subsequent safety of the structure, as well as the safety of use of the building. The paper describes the defects and damages of an open, rectangular reinforced concrete tank for hot process water, which failed during a short period of operation. The article also presents the...
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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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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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Estimation of the parameters of the discrete model of a steel–concrete composite beam
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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:...