Filtry
wszystkich: 417
wybranych: 413
-
Katalog
Filtry wybranego katalogu
Wyniki wyszukiwania dla: deep l
-
Static load test on concrete pile – instrumentation and results interpretation
PublikacjaFor 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...
-
Polish experience with cold in-place recycling
PublikacjaDeep cold in-place recycling using cement and asphalt emulsion has been used for reconstruction of existing roads since the beginning of the 1990s. This paper describes the first Polish requirements for mineral-cement-emulsion mixtures. As requirements stated for the strength of the mineral-cement-emulsion mixtures were quite high, most of the mixtures were designed using high amount of cement and aggregate added for the improvement...
-
Performance Analysis of the OpenCL Environment on Mobile Platforms
PublikacjaToday’s smartphones have more and more features that so far were only assigned to personal computers. Every year these devices are composed of better and more efficient components. Everything indicates that modern smartphones are replacing ordinary computers in various activities. High computing power is required for tasks such as image processing, speech recognition and object detection. This paper analyses the performance of...
-
Morphology control through the synthesis of metal-organic frameworks
PublikacjaDesignable morphology and predictable properties are the most challenging goals in material engineering. Features such as shape, size, porosity, agglomeration ratio significantly affect the final properties of metal- organic frameworks (MOFs) and can be regulated throughout synthesis parameters but require a deep under- standing of the mechanisms of MOFs formation. Herein, we systematically summarize the effects of the indi- vidual...
-
DevEmo—Software Developers’ Facial Expression Dataset
PublikacjaThe COVID-19 pandemic has increased the relevance of remote activities and digital tools for education, work, and other aspects of daily life. This reality has highlighted the need for emotion recognition technology to better understand the emotions of computer users and provide support in remote environments. Emotion recognition can play a critical role in improving the remote experience and ensuring that individuals are able...
-
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...
-
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...
-
Assessment and design of greener deep eutectic solvents – A multicriteria decision analysis
PublikacjaDeep 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...
-
Propagation of Acoustic Disturbances in Shallow Sea
PublikacjaPropagation of acoustic waves in shallow sea differs fundamentally from the same phenomenon occurring in deep sea in view of non-negligible distance from the sea bottom in the first case, where presence of two regions limiting the water layer results in the acoustic pressure distribution induced by a harmonic source has an interferential nature as a result of multi-path propagation of the acoustic signal. These interferential properties...
-
Enabling Deeper Linguistic-based Text Analytics – Construct Development for the Criticality of Negative Service Experience
PublikacjaSignificant progress has been made in linguistic-based text analytics particularly with the increasing availability of data and deep learning computational models for more accurate opinion analysis and domain-specific entity recognition. In understanding customer service experience from texts, analysis of sentiments associated with different stages of the service lifecycle is a useful starting point. However, when richer insights...
-
Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
-
Deep eutectic solvents based highly efficient extractive desulfurization of fuels – Eco-friendly approach
PublikacjaThe developed process is based on alternative, green and cheap solvents for efficient desulfurization of fuels. Several deep eutectic solvents (DESs) were successfully synthesized and studied as extraction solvents for desulfurization of model fuel containing thiophene (T), benzothiophene (BT) and dibenzothiophene (DBT). The most important extraction parameters (i.e. kind of DES, DES: fuel volume ratio, hydrogen bond acceptor:...
-
Silica Gel Impregnated by Deep Eutectic Solvents for Adsorptive Removal of BTEX from Gas Streams
PublikacjaThe paper presents the preparation of new adsorbents based on silica gel (SiO2) impregnated with deep eutectic solvents (DESs) to increase benzene, toluene, ethylbenzene, and p-xylene (BTEX) adsorption efficiency from gas streams. The DESs were synthesized by means of choline chloride, tetrapropylammonium bromide, levulinic acid, lactic acid, and phenol. The physico-chemical properties of new sorbent materials, including surface...
-
Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
-
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,...
-
Robust Object Detection with Multi-input Multi-output Faster R-CNN
PublikacjaRecent years have seen impressive progress in visual recognition on many benchmarks, however, generalization to the out-of-distribution setting remains a significant challenge. A state-of-the-art method for robust visual recognition is model ensembling. However, recently it was shown that similarly competitive results could be achieved with a much smaller cost, by using multi-input multi-output architecture (MIMO). In this work,...
-
Using Long-Short term Memory networks with Genetic Algorithm to predict engine condition
PublikacjaPredictive maintenance (PdM) is a type of approach for maintenance processes, allowing maintenance actions to be managed depending on the machine's current condition. Maintenance is therefore carried out before failures occur. The approach doesn’t only help avoid abrupt failures but also helps lower maintenance cost and provides possibilities to manufacturers to manage maintenance budgets in a more efficient way. A new deep neural...
-
Autoencoder application for anomaly detection in power consumption of lighting systems
PublikacjaDetecting energy consumption anomalies is a popular topic of industrial research, but there is a noticeable lack of research reported in the literature on energy consumption anomalies for road lighting systems. However, there is a need for such research because the lighting system, a key element of the Smart City concept, creates new monitoring opportunities and challenges. This paper examines algorithms based on the deep learning...
-
A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine 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...
-
Robustness in Compressed Neural Networks for Object Detection
PublikacjaModel compression techniques allow to significantly reduce the computational cost associated with data processing by deep neural networks with only a minor decrease in average accuracy. Simultaneously, reducing the model size may have a large effect on noisy cases or objects belonging to less frequent classes. It is a crucial problem from the perspective of the models' safety, especially for object detection in the autonomous driving...
-
Long Distance Vital Signs Monitoring with Person Identification for Smart Home Solutions
PublikacjaAbstract— Imaging photoplethysmography has already been proved to be successful in short distance (below 1m). However, most of the real-life use cases of measuring vital signs require the system to work at longer distances, to be both more reliable and convenient for the user. The possible scenarios that system designers must have in mind include monitoring of the vital signs of residents in nursing homes, disabled people, who...
-
Vertical Temperature Stratification of the Gulf of Gdansk Water
PublikacjaThe Baltic Sea is characterized by variable hydroacoustic conditions, which depend on hydrological conditions throughout the year. The temperature of the water is the factor that has the greatest impact on the changes in the speed of the sound in this basin. Even at a small depth, we can observe a large temperature gradient affecting the accuracy of the conducted research using hydroacoustic devices. A characteristic feature of...
-
Metal dusting phenomena of 501 AISI furnace tubes in refinery fractional distillation unit
PublikacjaThe purpose of this investigation was to conduct the failure analysis of 501 AISI furnace tubes places before distillation column in fractional distillation unit. The investigated furnace tubes were planned to work for ten years however after just two years of exploitation <30% of the material left. The observed corrosion process had the intense and complex character. The well-adhered shiny black deposits and deep, round pits were...
-
Speaker Recognition Using Convolutional Neural Network with Minimal Training Data for Smart Home Solutions
PublikacjaWith the technology advancements in smart home sector, voice control and automation are key components that can make a real difference in people's lives. The voice recognition technology market continues to involve rapidly as almost all smart home devices are providing speaker recognition capability today. However, most of them provide cloud-based solutions or use very deep Neural Networks for speaker recognition task, which are...
-
Extractive detoxification of feedstocks for the production of biofuels using new hydrophobic deep eutectic solvents – Experimental and theoretical studies
PublikacjaThe paper presents a synthesis of novel hydrophobic deep eutectic solvents (DESs) composed of natural components, which were used for removal of furfural (FF) and 5-hydroxymethylfurfural (HMF) from lignocellulosic hydrolysates. The main physicochemical properties of DESs were determined, followed by explanation of the DES formation mechanism, using 1H NMR, 13C NMR and FT-IR analysis and density functional theory (DFT). The most...
-
Techno‐economic evaluation of a natural deep eutectic solvent‐based biorefinery: Exploring different design scenarios
PublikacjaThis paper presents a comprehensive techno‐economic evaluation of an integrated natural deep eutectic solvent (NADES)‐based biorefinery – a 1 ton day−1 capacity design plant. The key parameters include payback period, net present value (NPV), and internal rate of return (IRR). These were compared with the parameters of conventional biorefineries. The ‘n th plant’ results clearly revealed that the single product‐based biorefinery...
-
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...
-
Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublikacjaAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
-
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...
-
Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
-
Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
-
Classification of Covid-19 using Differential Evolution Chaotic Whale Optimization based Convolutional Neural Network
PublikacjaCOVID-19, also known as the Coronavirus disease-2019, is an transferrable disease that spreads rapidly, affecting countless individuals and leading to fatalities in this worldwide pandemic. The precise and swift detection of COVID-19 plays a crucial role in managing the pandemic's dissemination. Additionally, it is necessary to recognize COVID-19 quickly and accurately by investigating chest x-ray images. This paper proposed a...
-
BP-EVD: Forward Block-Output Propagation for Efficient Video Denoising
PublikacjaDenoising videos in real-time is critical in many applications, including robotics and medicine, where varying light conditions, miniaturized sensors, and optics can substantially compromise image quality. This work proposes the first video denoising method based on a deep neural network that achieves state-of-the-art performance on dynamic scenes while running in real-time on VGA video resolution with no frame latency. The backbone...
-
Process Control of Biogas Purification Using Electronic Nose
PublikacjaNowadays, biogas produced from landfills and wastewater treatment plants or lignocellulosic biomass is important sustainable and affordable source of energy. Impurities from biogas stream can cause a serious odor problem, especially for residents of areas immediately adjacent to production plants. Therefore, biogas pre-treatment is necessary to protect engines that convert biogas into energy and in order to increase the specific...
-
Medical Image Dataset Annotation Service (MIDAS)
PublikacjaMIDAS (Medical Image Dataset Annotation Service) is a custom-tailored tool for creating and managing datasets either for deep learning, as well as machine learning or any form of statistical research. The aim of the project is to provide one-fit-all platform for creating medical image datasets that could easily blend in hospital's workflow. In our work, we focus on the importance of medical data anonimization, discussing the...
-
Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublikacjaIn 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...
-
Preparation and characterization of TiO2 nanostructures for catalytic CO2 photoconversion
PublikacjaThe titanium dioxide target (99.7%) of 1 cm in dia was ablated in vacuum by laser pulses(6 ns) at 266 nm and at repetition rate of 10 Hz. During deposition the laser fluence between 1 and 3.5 J/cm2 and the O2 pressure from the range of 10-2 - 1 Pa were applied. The thin TiO2 films were deposited on glass substrate (1 × 1 cm2) heated up to 500 °C. The chemical composition of the film and samples produced by annealing were investigated...
-
Distortion of speech signals in the listening area: its mechanism and measurements
PublikacjaThe paper deals with a problem of the influence of the number and distribution of loudspeakers in speech reinforcement systems on the quality of publicly addressed voice messages, namely on speech intelligibility in the listening area. Linear superposition of time-shifted broadband waves of a same form and slightly different magnitudes that reach a listener from numerous coherent sources, is accompanied by interference effects...
-
Endohedral gallide cluster superconductors and superconductivity in ReGa5
PublikacjaWe present transition metal-embedded (T@Gan) endohedral Ga clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2 Ga9 are all previously known superconductors. The well-known exotic superconductor...
-
Bacterial community succession in an Arctic lake–stream system (Brattegg Valley, SW Spitsbergen)
PublikacjaThe factors affecting prokaryotic and virus structure dynamics and bacterial commu-nity composition (BCC) in aquatic habitats along a ca. 1500 m of the Brattegg Valley lake–stream system (SW Spitsbergen) composed of three postglacial lakes created by Brattegg Glacier meltwater were examined. A high number of small-volume prokaryotic cells were found in the recently-formed, deep, upper,...
-
Coherent-wave Monte Carlo method for simulating light propagation in tissue
PublikacjaSimulating propagation and scattering of coherent light in turbid media, such as biological tissues, is a complex problem. Numerical methods for solving Helmholtz or wave equation (e.g. finite-difference or finite-element methods) require large amount of computer memory and long computation time. This makes them impractical for simulating laser beam propagation into deep layers of tissue. Other group of methods, based on radiative...
-
Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublikacjaIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
-
Application of soil nailing technique for protection and preservation historical buildings
PublikacjaSoil nailing is one of the recent in situ techniques used for soil improvement and in stabilizing slopes. The process of soil nailing consists of reinforcing the natural ground with relatively small steel bars or metal rods, grouted in the pre-drilled holes. This method has a wide range of applications for stabilizing deep excavations and steep slopes. Soil nailing has recently become a very common method of slope stabilisation...
-
Evaluating Accuracy of Respiratory Rate Estimation from Super Resolved Thermal Imagery
PublikacjaNon-contact estimation of Respiratory Rate (RR) has revolutionized the process of establishing the measurement by surpassing some issues related to attaching sensors to a body, e.g. epidermal stripping, skin disruption and pain. In this study, we perform further experiments with image processing-based RR estimation by using various image enhancement algorithms. Specifically, we employ Super Resolution (SR) Deep Learning (DL) network...
-
Music information retrieval—The impact of technology, crowdsourcing, big data, and the cloud in art.
PublikacjaThe exponential growth of computer processing power, cloud data storage, and crowdsourcing model of gathering data bring new possibilities to music information retrieval (mir) field. Mir is no longer music content retrieval only; the area also comprises the discovery of expressing feelings and emotions contained in music, incorporating other than hearing modalities for helping this issue, users’ profiling, merging music with social...
-
Effect of Thermal Treatment and Erosion Aggressiveness on Resistance of S235JR Steel to Cavitation and Slurry
PublikacjaS235JR steel is used in many applications, but its resistance to the erosion processes has been poorly studied. To investigate this resistance, cavitation, and slurry erosion tests were conducted. These tests were carried out at different erosion intensities, i.e., different flow rates in the cavitation tunnel with a system of barricades and different rotational speeds in the slurry pot. The steel was tested as-received and after...
-
Smartphones as tools for equitable food quality assessment
PublikacjaBackground: The ubiquity of smartphones equipped with an array of sophisticated sensors, ample processing power, network connectivity and a convenient interface makes them a promising tool for non-invasive, portable food quality assessment. Combined with the recent developments in the areas of IoT, deep learning algorithms and cloud computing, they present an opportunity for advancing wide-spread, equitable and sustainable food...
-
Investigation of tetrabutylammonium bromide-glycerol-based deep eutectic solvents and their mixtures with water by spectroscopic techniques
PublikacjaDeep eutectic solvents (DES) are formed by an acceptor and a donor of hydrogen bonds. They are generally considered as a possible alternative to hazardous organic solvents in various fields. Very recently they have also appeared in analytical chemistry, used mainly for the separation of analytes before instrumental quantification. For the development of new extraction procedures, it is important, among other things, to understand...
-
Deep eutectic solvents – based green absorbents for effective volatile organochlorine compounds removal from biogas
PublikacjaVolatile organochlorine compounds (VOXs) presented in biogas can cause many technological and environmental problems. During the combustion of biogas containing VOXs, the corrosion of installation, as well as the formation of toxic by-products (polyhalogenated dioxins and furans) and further emission to the atmosphere, may occur. Therefore, in this study, a new procedure based on physical absorption was developed. In order to meet...
-
Combination of homogeneous liquid–liquid extraction and vortex assisted dispersive liquid–liquid microextraction for the extraction and analysis of ochratoxin A in dried fruit samples: Central composite design optimization
PublikacjaThis paper presents a new analytical procedure based on combination of homogeneous liquid–liquid extraction (HLLE) and vortex-assisted dispersive liquid–liquid microextraction (VA-DLLME) for the accurate and reliable determination of ochratoxin A (OTA) in dried fruit samples. To enable selective extraction of the OTA, six hydrophobic deep eutectic solvents (hDESs) were prepared and tested as extraction solvents. Optimization of...