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Wyniki wyszukiwania dla: CANTILEVERS DEEP BEAMS
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublikacjaThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
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Deep neural network architecture search using network morphism
PublikacjaThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Challenges and Possibilities of Deep Eutectic Solvent-Based Membranes
PublikacjaDeep eutectic solvents (DES) are a category of a new class of solvents that can overcome some of the main drawbacks of typical solvents and ionic liquids (ILs). DES have been widely investigated and applied by the research community in several applications since their invention. Over the past years, the use of DES has been directed to the production of new materials and items for new products and processes. This is the case for...
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Focused ion beam-based microfabrication of boron-doped diamond single-crystal tip cantilevers for electrical and mechanical scanning probe microscopy
PublikacjaIn this paper, the fabrication process and electromechanical properties of novel atomic force microscopy probes utilising single-crystal boron-doped diamond are presented. The developed probes integrate scanning tips made of chemical vapour deposition-grown, freestanding diamond foil. The fabrication procedure was performed using nanomanipulation techniques combined with scanning electron microscopy and focused ion beam technologies....
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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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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Relativistic electron beams above thunderclouds
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Sorbents modified by deep eutectic solvents in microextraction techniques
PublikacjaIn recent years, considerable attention has been directed towards the employment of green solvents, specifically deep eutectic solvents (DES), in liquid phase microextraction techniques. However, comprehensive and organized knowledge regarding the modification of sorbent surface structures with DES remains limited. Therefore, this paper reviews the application of DES in modifying and improving the properties of sorbents for microextraction...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublikacjaThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Decision making process using deep learning
PublikacjaEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublikacjaIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Verification of Selected Calculation Methods Regarding Shear Strength in Reinforced and Prestressed Concrete Beams
PublikacjaThe 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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Unusual dynamics and nonlinear thermal self-focusing of initially focused magnetoacoustic beams in a plasma
PublikacjaUnusual thermal self-focusing of two-dimensional beams in plasma which axis is parallel to the equilibrium straight magnetic field is considered. The equi- librium parameters of plasma determine scenario of a beam divergence (usual or unusual) which is stronger as compared with a flow without magnetic field. Nonlinear thermal self-action of a magnetosonic beam behaves differently in the ordinary and unusual cases. Damping of wave...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe 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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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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The impact of the shape of deep drilled well screen openings on the filtration process in full saturation conditions
PublikacjaThe authors propose a supplementary method of modelling seepage flow around the deep drilled well screen. The study applies 3D numerical modelling (FEM) in order to provide an in-depth analysis of the seepage process. The analysis of filtration parameters (flow distribution q(x,t) and pressure distribution p) was conducted using the ZSoil.PC software system. The analysis indicates that the shape of perforation is of secondary importance...
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Three-point bending test of sandwich beams supporting the GFRP footbridge design process - validation
PublikacjaSome selected aspects concerning material and construction design issues for pedestrian footbridge made of GFRP composite materials are elaborated in this paper. The analysis is focused on validation tests, which are particularly important because of the advanced technology and materials that are used for this innovative bridge. The considered footbridge is a sandwich-type shell structure comprising of PET foam core and outer skins...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Fatigue Performance of Double-Layered Asphalt Concrete Beams Reinforced with New Type of Geocomposites
PublikacjaThe reinforcement of asphalt layers with geosynthetics has been used for several decades, but proper evaluation of the influence of these materials on pavement fatigue life is still a challenging task. The presented study investigates a novel approach to the reinforcement of asphalt layers using a new type of geogrid composite, in which square or hexagonal polypropylene stiff monolithic paving grid with integral junctions is bonded...
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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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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublikacjaFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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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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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublikacjaThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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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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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Characterization of Corrosion-Induced Fracture in Reinforced Concrete Beams Using Electrical Potential, Ultrasound and Low-Frequency Vibration
PublikacjaThe 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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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publikacjaconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe 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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Laboratory fatigue assessment of large geocomposite-reinforced double-layered asphalt concrete beams
PublikacjaGeosynthetic 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
PublikacjaGeosynthetic 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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Coda wave interferometry in monitoring the fracture process of concrete beams under bending test
PublikacjaEarly detection of damage is necessary for the safe and reliable use of civil engineering structures made of concrete. Recently, the identification of micro-cracks in concrete has become an area of growing interest, especially using wave-based techniques. In this paper, a non-destructive testing approach for the characterization of the fracture process was presented. Experimental tests were made on concrete beams subjected to mechanical...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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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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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Deep Learning Approaches in Histopathology
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Extractive detoxification of hydrolysates with simultaneous formation of deep eutectic solvents
PublikacjaThe hydrolysis of lignocellulosic biomass results in the production of so-called fermentation inhibitors, which reduce the efficiency of biohydrogen production. To increase the efficiency of hydrogen production, inhibitors should be removed from aqueous hydrolysate solutions before the fermentation process. This paper presents a new approach to the detoxification of hydrolysates with the simultaneous formation of in-situ deep eutectic...
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Sensitivity analysis of thin-walled beams and frames.
PublikacjaPraca zawiera pełen tekst referatu wygloszonego na Konferencji w Wilnie.Referat przedstawia problem numerycznej analizy wrażliwości belek i ramstalowych zbudowanych z bi-symetrycznych profili cienkościennychpoddanych skręceniu lub skręceniu ze zginaniem. Przedstawiono wynikianalizy wrażliwości przemieszczeń i sił wewnętrznych przy zmianiegrubosci półek, sztywności dodatkowych stężeń poprzecznych orazszerokości przewiązek.
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Detection of delamination in multi layer composite beams.
PublikacjaW pracy przedstawiono model belki kompozytowej z delaminacją. Omówiono czynniki propagacji fali sprężystej w belce i możliwości wykorzystania zmian w propagującej fali wywołanych delaminacją do jej detekcji.
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Modeling and simulation of thin-walled beams and frames
PublikacjaPrzedstawiono koncepcję zastosowania superelementów węzłowych do modelowania połączeń słupów i rygli ram zbudowanych z prętów cienkościennych oraz stężeń konstrukcyjnych w belkach cienkościennych. Przeprowadzono analizę pracy ramy stalowej zbudowanej z prętów cienkościennych ze szczególnym uwzględnieniem problemu przekazywania bimomentu poprzez węzeł takiej ramy.
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Electronic stabilization of beams in sonar with cylindrical array
PublikacjaArtykuł prezentuje podstawy opisu beamformera dla sonaru z antena cylindryczną. Artykuł pokazuje, że zmodyfikowany beamformer może zostać użyty do stabilizacji osi wiązki w horyzontalnej płaszczyźnie, gdy znany jest przechył i zanurzenie statku. Artykuł przedstawia także problem elektronicznego odchylania wiązki.
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Thermal Images Analysis Methods using Deep Learning Techniques for the Needs of Remote Medical Diagnostics
PublikacjaRemote medical diagnostic solutions have recently gained more importance due to global demographic shifts and play a key role in evaluation of health status during epidemic. Contactless estimation of vital signs with image processing techniques is especially important since it allows for obtaining health status without the use of additional sensors. Thermography enables us to reveal additional details, imperceptible in images acquired...
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Charge-based deep level transient spectroscopy of B-doped and undoped polycrystalline diamond films
PublikacjaThe undoped and B-doped polycrystalline diamond thin film was synthesized by hot filament chemical vapor deposition and microwave plasma, respectively. The structural characterization was performed by scanning electron microscopy, X-ray diffraction and Raman spectroscopy. The electrical properties of synthesized diamond layer were characterized by dc-conductivity method and charge deep level transient spectroscopy. The B-doped...
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Purification of model biogas from toluene using deep eutectic solvents
PublikacjaBiogas from landfills and wastewater treatment facilities typically contain a wide range of volatile organic compounds (VOCs), that can cause severe operational problems when biogas is used as fuel. Among the contaminants commonly occur aromatic compounds, i.e. benzene, ethylbenzene, toluene and xylenes (BTEX). In order to remove BTEX from biogas, different processes can be used. A promising process for VOCs removal is their absorption...
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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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PHYSICAL REVIEW SPECIAL TOPICS-ACCELERATORS AND BEAMS
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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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Deep learning-based waste detection in natural and urban environments
PublikacjaWaste pollution is one of the most significant environmental issues in the modern world. The importance of recycling is well known, both for economic and ecological reasons, and the industry demands high efficiency. Current studies towards automatic waste detection are hardly comparable due to the lack of benchmarks and widely accepted standards regarding the used metrics and data. Those problems are addressed in this article by...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublikacjaThe increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated...
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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...