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Wyniki wyszukiwania dla: DEEP BEAMS
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Suspended matter, composition and fluxes, Gdansk Deep, late spring 2001
Dane BadawczeParticulate organic carbon (POC) and nitrogen (PON) concentrations and fluxes were measured in the Gdańsk Deep (Gulf of Gdansk) from 30.05 to 06.06.2001. The vertical profiles of POC and PON were characterised by the highest values in the euphotic layer, a gradual decrease with depth, and an increase below the halocline. The hydrophysical conditions...
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Damage Detection of Steel-Concrete Composite Beam
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GPR simulations for diagnostics of a reinforced concrete beam
PublikacjaThe most popular technique for modelling of an electromagnetic field, the finite difference time domain (FDTD) method, has recently become a popular technique as an interpretation tool for ground penetrating radar (GPR) measurements. The aim of this study is to detect the size and the position of damage in a reinforced concrete beam using GPR maps. Numerical simulations were carried out using the finite differ-ence time domain...
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The effect of mechanical coupling on the beam pattern of a multielementarray
PublikacjaW artykule opisano nową metodę redukcji listków bocznych hydroakustycznej anteny wieloelementowej. Wykorzystano tu efekt ważenia amplitud sygnałów odbieranych przez poszczególne elementy poprzez kontrolowane ich mechaniczne sprzężenie. Opisane zostały wyniki badań kilku modeli anten zbudowanych z pięciu elementów. Wyniki badań zostały zweryfikowane obliczeniami symulacyjnymi. Stwierdzono, zarówno na drodze eksperymentalnej jak...
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Crack identification in cantilever beam using wavelets
PublikacjaPrzedstawiono metodę identyfikacji zniszczeń przy użyciu transformacji falkowej. Rozpatrzono przykład belki wspornikowej. Pokazano, że transformacja falkowa wykrywa miejsce zniszczenia.
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Energy efficient beam control for 5G antennas
PublikacjaThe rapid development of 5G and beyond systems demands improvement in communication speed, latency and safety to maintain the required quality of service. This paper presents an overview of different concepts of energy-efficient antenna systems, which offer beam-shaping and beam-steering functionalities, that enhance connectivity performance and can be used in 5G applications. Different designs for 5.9 GHz, 39 GHz and 60 GHz frequency...
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Experimental validation of the use of energy transfer ratio (ETR) for damage diagnosis of steel-concrete composite beams
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Microbeam radiation therapy: Tissue dose penetration and BANG-gel dosimetry of thick-beams’ array interlacing
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A TPC Detector for Studying Photo-nuclear Reactions at Astrophysical Energies with Gamma-ray Beams at ELI--NP
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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
PublikacjaThe 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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Detection of debonding in reinforced concrete beams using ultrasonic transmission tomography and hybrid ray tracing technique
PublikacjaThis paper concerns inspection of reinforced concrete elements, with particular emphasis on assessing the quality of the adhesive connection between steel and concrete. A novel theoretical model was developed to determine the paths of transmitted, refracted and reflected elastic waves as well as a creeping wave propagated along the inclusion surface. Imaging the internal structure of tested beams was based on wave propagation measurements...
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Non-Destructive Diagnostics of Concrete Beams Strengthened with Steel Plates Using Modal Analysis and Wavelet Transform
PublikacjaExternally bonded reinforcements are commonly and widely used in civil engineering objects made of concrete to increase the structure load capacity or to minimize the negative effects of long-term operation and possible defects. The quality of adhesive bonding between a strengthened structure and steel or composite elements is essential for effective reinforcement; therefore, there is a need for non-destructive diagnostics of adhesive...
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Evaluation of the resistance of steel–concrete adhesive connection in reinforced concrete beams using guided wave propagation
PublikacjaThe development of the nondestructive diagnostic methods is of significant importance in the last decades. A special attention is paid to diagnostics of reinforced concrete structures, which are very popular in the civil engineering field. A possible use of the guided waves in the estimation of the resistance of steel–concrete adhesive connection is studied in the following paper. The relationships relating adhesive connection...
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Chained machine learning model for predicting load capacity and ductility of steel fiber–reinforced concrete beams
PublikacjaOne of the main issues associated with steel fiber–reinforced concrete (SFRC) beams is the ability to anticipate their flexural response. With a comprehensive grid search, several stacked models (i.e., chained, parallel) consisting of various machine learning (ML) algorithms and artificial neural networks (ANNs) were developed to predict the flexural response of SFRC beams. The flexural performance of SFRC beams under bending was...
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Sensitivity analysis of free torsional vibration frequencies of thin-walled laminated beams under axial load
PublikacjaThe paper addresses sensitivity analysis of free torsional vibration frequencies of thin-walled beams of bisymmetric open cross-section made of unidirectional fibre-reinforced laminate. The warping effect and the axial end load are taken into account. The consideration is based upon the classical theory of thin-walled beams of non-deformable cross-section. The first-order sensitivity variation of the frequencies is derived with...
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The effect of multiaxial geocomposite reinforcement on fatigue performance and crack propagation delay in double-layered asphalt beams
PublikacjaThe presented study investigates the effect of a recently developed multiaxial geocomposite made of polypropylene geogrid and non-woven fabric on the delay of crack propagation, based on four-point bending tests of large asphalt concrete beams – both for reinforced and non-reinforced specimens. Several approaches are described in this study, including analysis of stiffness modulus decrease and analysis of crack propagation using...
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Calculations of fracture process zones on meso-scale in notched concrete beams subjected to three-point bending.
PublikacjaW artykule przedstawiono wyniki numeryczne MES modelowanie belek betonowych z nacięciem na poziomie skali mezo. Beton został opisany na poziomie skali mezo jako stochastyczny materiał 3-składnikowy złożony z kruszywa, zaczynu cementowego oraz stref kontaktu. Obliczenia wykonano przy wykorzystaniu modelu degradacji sztywności z nielokalnym osłabieniem. Zbadano wpływ stochastycznego rozkładu kruszywa, średnicy, kształtu oraz zagęszczenia...
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Modelling of reinforced concrete beams under mixed shear-tension failure with different continuous FE approaches
PublikacjaW artykule omówiono wyniki modelowania numerycznego MES zachowania się wysokich belek żelbetowych podczas zniszczenia mieszanego ścinanie-rozciąganie. Obliczenia wykonano stosując różne modele dla betonu rozszerzone o długość charakterystyczną mikrostruktury w oparciu o teorie nielokalna. Otrzymano dobrą zgodność z wynikami doświadczalnymi.
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Parametric FE studies on a coupled energetic-statistical size effect in plain concrete beams under bending
PublikacjaW artykule omówiono wyniki połączonego deterministyczno-statystycznego efektu skali w betonowych belkach podczas zginania. Obliczenia wykonano stosując MES w zakresie sprężysto-plastyczności z nielokalnym osłabieniem. Obliczenia wykonano dla różnych długości korelacji i współczynnika zmienności.
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Modelling reinforced concrete beams under mixed shear-tension failure with different continuous FE approaches
PublikacjaThe paper presents quasi-static numerical simulations of the behaviour of short reinforced concrete beams without shear reinforcement under mixed shear-tension failure using the FEM and four various constitutive continuum models for concrete. First, an isotropic elasto-plastic model with a Drucker-Prager criterion defined in compression and with a Rankine criterion defined in tension was used. Next, an anisotropic smeared crack...
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Investigations on fracture in reinforced concrete beams in 3-point bending using continuous micro-CT scanning
PublikacjaThis study explores a fracture process in rectangular reinforced concrete (RC) beams subjected to quasi-static three-point bending. RC beams were short and long with included longitudinal reinforcement in the form of a steel or basalt bar. The ratio of the shear span to the effective depth was 1.5 and 0.75. The focus was on the load–deflection diagram and crack formation. Three-dimensional (3D) analyses of the size and distribution...
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FE analysis of a coupled energetic-statistical size effect in plain concrete beams with varying material properties.
PublikacjaThe numerical FE investigations of a coupled energetic-statistical size effect in unnotched concrete beams of similar geometry under quasi-static three point bending were performed within elasto-plasticity with non-local softening. The stochastic FE analyses were carried out with three different beam sizes. Deterministic calculations were performed with the uniform distribution of a uniaxial tensile strength. In statistical calculations...
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On FEM analysis of Cosserat-type stiffened shells. Static and stability linear analysis
PublikacjaThe present research investigates the theory and numerical analysis of shells stiffened with beams in the framework based on the geometrically exact theories of shells and beams. Shell’s and beam’s kinematics are described by the Cosserat surface and the Cosserat rod respectively, which are consistent including deformation and strain measures. A FEM approximation of the virtual work principle leads to the conforming shell and beam...
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Solubility advantage of sulfanilamide and sulfacetamide in natural deep eutectic systems: experimental and theoretical investigations
PublikacjaObjective: The aim of this study was to explore the possibility of using natural deep eutectic solvents (NADES) as solvation media for enhancement of solubility of sulfonamides, as well as gaining some thermodynamic characteristics of the analyzed systems. Significance: Low solubility of many active pharmaceutical ingredients is a well-recognized difficulty in pharmaceutical industry, hence the need for different strategies addressing...
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Use of Bioluminescence for Monitoring Brown Coal Mine Waters from Deep and Surface Drainage
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Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)
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Deep learning model for automated assessment of lexical stress of non-native english speakers
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The Effectiveness of Using a Pretrained Deep Learning Neural Networks for Object Classification in Underwater Video
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Increasing the Durability of Critical Parts in Heavy-Duty Industrial Machines by Deep Cryogenic Treatment
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The Effect of Montmorillonites on the Physicochemical Properties of Potato Starch Films Plasticized with Deep Eutectic Solvent
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Pose-Invariant Face Detection by Replacing Deep Neurons with Capsules for Thermal Imagery in Telemedicine
PublikacjaAbstract— The aim of this work was to examine the potential of thermal imaging as a cost-effective tool for convenient, non- intrusive remote monitoring of elderly people in different possible head orientations, without imposing specific behavior on users, e.g. looking toward the camera. Illumination and pose invariant head tracking is important for many medical applications as it can provide information, e.g. about vital signs, sensory...
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublikacjaQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Removal of Siloxanes from Model Biogas by Means of Deep Eutectic Solvents in Absorption Process
PublikacjaThe paper presents the screening of 20 deep eutectic solvents (DESs) composed of tetrapropylammonium bromide (TPABr) and glycols in various molar ratios, and 6 conventional solvents as absorbents for removal of siloxanes from model biogas stream. The screening was achieved using the conductor-like screening model for real solvents (COSMO-RS) based on the comparison of siloxane solubility in DESs. For the DES which was characterized...
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Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
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Deep Eutectic Solvents or Eutectic Mixtures? Characterization of Tetrabutylammonium Bromide and Nonanoic Acid Mixtures
PublikacjaDeep eutectic solvents have quickly attracted the attention of researchers because they better meet the requirements of green chemistry and thus have the potential to replace conventional hazardous organic solvents in some areas. To better understand the nature of these mixtures, as well as expand the possibilities of their use in different industries, a detailed examination of their physical properties, such as density, viscosity,...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Monitoring of deep foundation deflection in model experiments by means of a magnetic method: theoretical study.
PublikacjaZaproponowano oryginalną nieinwazyjną metodę pomiaru ugięcia pali bocznie obciążonych niespoistymi i małospoistymi gruntami suchymi lub wilgotnymi. Metoda ma zastosowanie do pomiaru ugięcia pali i ścian szczelnych oraz określania położenia innych fundamentów lub elementów zagłębionych w gruncie.
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Green monoterpenes based deep eutectic solvents for effective BTEX absorption from biogas
PublikacjaThe combustion of biogas which contains significant amounts of monoaromatic hydrocarbons, i.e. benzene, ethylbenzene, toluene, and xylene (BTEX) can cause many technological, environmental, and health problems. Therefore, in these studies, a new physical absorption method based on deep eutectic solvents (DES) consisting of monoterpenes and carboxylic acids was developed for BTEX removal. A total of 39 DES were synthesized, of which...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublikacjaIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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CO2 Separation Using Supported Deep Eutectic Liquid Membranes Based on 1,2-propanediol
PublikacjaIn this work, deep eutectic solvents (DESs) composed of choline chloride, acetylcholine chloride or tetrabutylammonium chloride, and 1,2-propanediol were used as a liquid phase for polypropylene-based supported liquid membranes (SLMs) and evaluated for the separation of carbon dioxide from CO2/N2 mixtures. Fourier transform infrared spectra were obtained to confirm DES formation, and the thermal stability of solvents was investigated...
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Methods of deep modification of low-bearing soil for the foundation of new and spare air runways
PublikacjaAfter analyzing the impact of aircraft on the airport pavement (parking spaces, runways, startways), it was considered advisable to consider the problem of deep improvement or strengthening of its subsoil. This is especially true for low-bearing soil. The paper presents a quick and effective method of strengthening the subsoil intended for the construction of engineering structures used for civil...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Automated detection of pronunciation errors in non-native English speech employing deep learning
PublikacjaDespite significant advances in recent years, the existing Computer-Assisted Pronunciation Training (CAPT) methods detect pronunciation errors with a relatively low accuracy (precision of 60% at 40%-80% recall). This Ph.D. work proposes novel deep learning methods for detecting pronunciation errors in non-native (L2) English speech, outperforming the state-of-the-art method in AUC metric (Area under the Curve) by 41%, i.e., from...
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Dataset Related Experimental Investigation of Chess Position Evaluation Using a Deep Neural Network
PublikacjaThe idea of training Articial Neural Networks to evaluate chess positions has been widely explored in the last ten years. In this paper we investigated dataset impact on chess position evaluation. We created two datasets with over 1.6 million unique chess positions each. In one of those we also included randomly generated positions resulting from consideration of potentially unpredictable chess moves. Each position was evaluated...
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Superhydrophobic and superoleophilic melamine sponges impregnated with deep eutectic solvents for oil spill cleanup
PublikacjaThe extensive extraction of oil from the bottom of seas and oceans and its transportation by tankers increase the risk of potential environmental disasters associated with hydrocarbon fractions entering water reservoirs. Therefore, this paper presents the preparation of a simple impregnation of a melamine sponge with deep eutectic solvents (DES), which can be obtained from natural sources, including coconut oil, palm kernel oil,...
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Analysis of the Capability of Deep Learning Algorithms for EEG-based Brain-Computer Interface Implementation
PublikacjaMachine learning models have received significant attention for their exceptional performance in classifying electroencephalography (EEG) data. They have proven to be highly effective in extracting intricate patterns and features from the raw signal data, thereby contributing to their success in EEG classification tasks. In this study, we explore the possibilities of utilizing contemporary machine learning algorithms in decoding...
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Tagged images with LEGO bricks - Technic Beams Special
Dane BadawczeThe set contains images of LEGO bricks (from Technic Beams Special category). The images were prepared for training neural network for recognition and labeling of LEGO bricks. The images contain one brick each. The images were taken from different sides by handheld camera hovering over the bricks lying on a white, non reflective surface.