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Search results for: DEEP BEAMS
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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Deep sea habitats in the chemical warfare dumping areas of the Baltic Sea
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Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublicationIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1: 4, 1: 6 and 1: 8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
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Ionic Liquids and Deep Eutectic Mixtures: Sustainable Solvents for Extraction Processes
PublicationIn recent years, ionic liquids and deep eutectic mixtures have demonstrated great potential in extraction processes relevant to several scientific and technological activities. This review focuses on the applicability of these sustainable solvents in a variety of extraction techniques, including but not limited to liquid- and solid-phase (micro) extraction, microwave-assisted extraction, ultrasound-assisted extraction and pressurized...
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Simulation of backup rolls quenching with experimental study of deep cryogenic treatment
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Deep Features Class Activation Map for Thermal Face Detection and Tracking
PublicationRecently, capabilities of many computer vision tasks have significantly improved due to advances in Convolutional Neural Networks. In our research, we demonstrate that it can be also used for face detection from low resolution thermal images, acquired with a portable camera. The physical size of the camera used in our research allows for embedding it in a wearable device or indoor remote monitoring solution for elderly and disabled...
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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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Influence of parameters of deep grinding on nanohardness and surface roughness of C45 steel
PublicationPrzedstawiono wyniki badań wpływu głębokości współbieżnego szlifowania powierzchni płaskich na chropowatość i nanotwardość warstwy wierzchniej stali C45 o strukturze ferrytyczno-perlitycznej i średniej wielkości ziarna 20 μm. Dla wszystkich wartości głębokości szlifowania uzyskano znaczny wzrost twardości warstwy wierzchniej przedmiotu obrabianego.
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publicationconvolutional 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 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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Assessment and design of greener deep eutectic solvents – A multicriteria decision analysis
PublicationDeep eutectic solvents (DES) are often considered as green solvents because of their properties, such as negligible vapor pressure, biodegradability, low toxicity or natural origin of their components. Due to the fact that DES are cheaper than ionic liquids, they have gained many applications in a short period of time. However, claims about their greenness sometimes seem to be exaggerated. Especially, bearing in mind lots of data...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublicationMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublicationAs the interest in facial detection grows, especially during a pandemic, solutions are sought that will be effective and bring more benefits. This is the case with the use of thermal imaging, which is resistant to environmental factors and makes it possible, for example, to determine the temperature based on the detected face, which brings new perspectives and opportunities to use such an approach for health control purposes. The...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublicationIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1:4, 1:6 and 1:8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
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Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
PublicationThe 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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Deep learning for ultra-fast and high precision screening of energy materials
PublicationSemiconductor materials for energy storage are the core and foundation of modern information society and play important roles in photovoltaic system, integrated circuit, spacecraft technology, lighting applications, and other fields. Unfortunately, due to the long experiment period and high calculation cost, the high-precision band gap (the basic characteristic parameter) of semiconductor is difficult to obtain, which hinders the...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublicationThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublicationThe 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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Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated 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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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublicationGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep learning approach on surface EEG based Brain Computer Interface
PublicationIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe 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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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublicationThe 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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Lignocellulosic waste biosorbents infused with deep eutectic solvents for biogas desulfurization
PublicationThis paper introduces an innovative method for treating biogas streams, employing lignocellulosic biosorbents infused with environmentally friendly solvents known as deep eutectic solvents (DES). The primary focus of this study was the elimination of volatile organosulfur compounds (VSCs) from model biogas. Biosorbents, including energetic poplar wood, antipka tree, corncobs, and beech wood, were used, each with varying levels...
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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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Purification of model biogas from toluene using deep eutectic solvents
PublicationBiogas 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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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublicationThis 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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Photocatalytic activity of TiO2 immobilized on glass beads
PublicationAktywność fotokatalityczną czystego TiO2 oraz TiO2 modyfikowanego borem zbadano w reakcji degradacji wodnego roztworu fenolu. TiO2 osadzono na szklanych kulkach i umieszczono w reaktorze wyposażonym w szklaną, kwarcową rurę, którą naświetlano promieniowaniem z zakresu UV-Vus
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Attributes of Entrepreneurial Teams as Elements of a Mental Model
PublicationAn entrepreneurial team can be defined as a small group of individuals holding ownership or control positions who create or develop an entrepreneurial venture and have shared commitments towards each other. Entrepreneurial teams start numerous new ventures or affect the performance of firms due to their social capital based on some characteristic attributes. The mental models of teams refer to internal, organised representation...
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Managing Virtual Teams: The Three Dimensions Scope
PublicationDue to globalisation and economic reasons the number of people working as a team in a virtual environment is increasing. Although virtual team can outperform teams working in a traditional environment still many managers face difficulties in achieving this goal. This article describes the idea of a system that would support knowledge management in virtual teams focusing on three dimensions of virtual work: location, organisation,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-002)
Open Research DataThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-Con)
Open Research DataThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-004)
Open Research DataThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Ultrasonic wave propagation and digital image correlation measurements of polyolefin fibre-reinforced concrete beams under 3-point bending (beam B-006)
Open Research DataThe DataSet contains the results of the mechanical behaviour of a concrete beam under a 3-point bending test. The beams had dimensions 15 x 15 x 70 cm3. The beam B-Con was made of concrete without fibres (as the reference beam), while beams B-002, B-004, and B-006 were manufactured from the concrete mix containing 2 kg/m3, 4 kg/m3 and 6 kg/m3 of fibres,...
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Effect of Electron Beam Power Density on the Structure of Titanium Under Non-Vacuum Electron-Beam Treatment
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Antifungal activity of propolis extracts produced with deep eutectic solvents.
Open Research DataThis dataset contains results of our investigation aiming in determination of antimicrobial potential of the propolis extracts produced with deep eutectic solvents. The activity was determined against C. albicans and C. glabarat strains. On the basis of these results MIC values can be calculated. Three samples of propolis were tested.
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Nutrients, oxygen and suspended matter - Gdansk Deep (2001-2005)
Open Research DataThe results show short-term changes in the concentration of nutrients (nitrates, nitrites, ammonium ions, phosphates and total forms of nitrogen and phosphorus), dissolved oxygen and suspended particulate matter - SPM and its main components (organic carbon - POC, nitrogen - PON, phosphorus - TPP) in the water column of the Gdańsk Deep (Gdańsk Bay).
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Vibration signals collected for concrete beams with GFRP reinforcement subjected to elevated temperatures (120C-240C)
Open Research DataThe dataset contains the time domain signals obtained during dynamic tests of concrete beams reinforced with GFRP bars. The vibration were induced with the use of modal hammer, while the signals were collected by the accelerometers attached at the beam surface. The signals were captured before and after subjecting the concrete beams to elevated temperatures.
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SIMPLIFIED DYNAMIC MODEL OF ROTATING BEAM
PublicationIn the paper a hybrid model of rotating beam is presented. It was obtained by using two methods: modal decomposition and spatial discretization. Reduced modal model was built for the system without the load related to inertia forces that occur during beam rotation. This inertia load was next modeled by using the method of simply spatial discretization and combined with reduced modal model. This approach allows to obtain accurate...
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Distorsional analysis of I-section beam
PublicationAn elastic stiffness matrix was derived in the case of distortion of a restrained thin-walled I-section beam using the minimum total stationary elastic energy condition. The function describing the angle of distortion was adopted form the solution of differential equation in the case of restrained distortion. The example presented in the paper helps to assess the correctness of the proposed solution. The proposed elastic stiffness...
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Enriched buckling for beam-lattice metamaterials
PublicationWe discuss two examples of beam-lattice metamaterials which show attractive mechanical properties concerning their enriched buckling. The first one considers pantographic beams and the nonlinear solution is traced out numerically on the base of a Hencky’s model and an algorithm based on Riks’ arc-length scheme. The second one concerns a beam-lattice with sliders and the nonlinear solution is discussed in analytic way and, finally,...
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Performance of CMS hadron calorimeter timing and synchronization using test beam, cosmic ray, and LHC beam data
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Modelling and parameter identification of steel–concrete composite beams in 3D rigid finite element method
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Performance of the CMS Level-1 trigger during commissioning with cosmic ray muons and LHC beams
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Three-point bending test of sandwich beams supporting the GFRP footbridge design process - validation
PublicationSome 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...