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Wyniki wyszukiwania dla: deep l
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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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Investigating Feature Spaces for Isolated Word Recognition
PublikacjaMuch attention is given by researchers to the speech processing task in automatic speech recognition (ASR) over the past decades. The study addresses the issue related to the investigation of the appropriateness of a two-dimensional representation of speech feature spaces for speech recognition tasks based on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and timefrequency signal representation...
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A body position influence on ECG derived respiration
PublikacjaAn influence of a human body position on ECG derived respiration (EDR) signal is presented in the paper. Examinations were performed during deep, suspended and normal breathing for eight people in four different body positions. EDR and thoracic impedance signals were compared using correlation and standard deviation coefficients. Obtained results have shown that it is possible to monitor breath activity of people being in different...
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NATURAL DEEP EUTECTIC SOLVENTS IN EXTRACTION PROCESS
PublikacjaDeveloping new, eco-friendly solvents which would meet technological and economic demands is perhaps the most popular aspects of Green Chemistry. Natural deep eutectic solvents (NADES) fully meet green chemistry principles. These solvents offer many advantages including biodegradability, low toxicity, sustainability, low costs and simple preparation. This paper provides an overview of knowledge regarding NADES with special emphasis...
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Detection of the Oocyte Orientation for the ICSI Method Automation
PublikacjaAutomation or even computer assistance of the popular infertility treatment method: ICSI (Intracytoplasmic Sperm Injection) would speed up the whole process and improve the control of the results. This paper introduces a preliminary research for automatic spermatozoon injection into the oocyte cytoplasm. Here, the method for detection a correct orientation of the polar body of the oocyte is presented. Proposed method uses deep...
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Wycena środowiska w aspekcie odpowiedzialności moralnej
Publikacjathe article '' the pricing of environment in the moral responsibility context" presents ethical protection of natural environment within sustainable development paradigm as well as the problem of individual, moral responsibility in the liberal civilization. it contains different opinions on the environmental ethics, compares flat and deep ecology as well as environmental and ecological economy; it characterizes methods of economic...
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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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Deep eutectic solvents vs ionic liquids: Similarities and differences
PublikacjaDeep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The...
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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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Understanding the early-stage release of volatile organic compounds from rapeseed oil during deep-frying of tubers by targeted and omics-inspired approaches using PTR-MS and gas chromatography
PublikacjaDuring deep-frying, a plethora of volatile products is emitted with the fumes. These compounds could act as oil quality indicators and change the indoor air composition leading to health risks for occupants. The presented experiments focus on deep-frying of different tubers in rapeseed oil at different frying temperatures. Here, two scenarios for real-time monitoring of volatile organic compounds (VOCs) using proton transfer reaction...
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Solvent dependency of carbon dioxide Henry's constant in aqueous solutions of choline chloride-ethylene glycol based deep eutectic solvent
PublikacjaThe Henry's constants of carbon dioxide absorbed in aqueous solutions of ethaline (choline chloride-ethylene glycol) were determined for temperatures ranging from 303.15 to 323.15 K based on solubility measurement at CO2 pressure ranging from 0 to 6 bar (0.6 MPa). These studies revealed that the Henry's constant increased with the increase of temperature. Data indicated the highest capacity of CO2 absorption is obtained for ethaline...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublikacjaEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublikacjaSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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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 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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Deep Eutectic Solvents: Properties and Applications in CO2 Separation
PublikacjaNowadays, many researchers are focused on finding a solution to the problem of global warming. Carbon dioxide is considered to be responsible for the “greenhouse” effect. The largest global emission of industrial CO2 comes from fossil fuel combustion, which makes power plants the perfect point source targets for immediate CO2 emission reductions. A state-of-the-art method for capturing carbon dioxide is chemical absorption using...
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Investigation on the Sources and Impact of Trace Elements in the Annual Snowpack and the Firn in the Hansbreen (Southwest Spitsbergen)
PublikacjaWe present a thorough evaluation of the water soluble fraction of the trace element composition (Ca, Sr, Mg, Na, K, Li, B, Rb, U, Ni, Co, As, Cs, Cd, Mo, Se, Eu, Ba, V, Ge, Ga, Cr, Cr, P, Ti, Mn, Zr, Ce, Zn, Fe, Gd, Y, Pb, Bi, Yb, Al, Nb, Er, Nd, Dy, Sm, Ho, Th, La, Lu, Tm, Pr, Tb, Fe, In, Tl) and their fluxes in the annual snowpack and the firn of the Hansbreen (a tidewater glacier terminating in the Hornsund fjord, southwest...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublikacjaLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Organic solvents aggregating and shaping structural folding of protein, a case study of the protease enzyme
PublikacjaLow solubility of reactants or products in aqueous solutions can result in the enzymatic catalytic reactions that can occur in non-aqueous solutions. In current study we investigated aqueous solutions containing different organic solvents / deep eutectic solvents (DESs) that can influence the protease enzyme's activity, structural, and thermal stabilities. Retroviral aspartic protease enzyme is responsible for the cleavage of the...
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DEEP CONVOLUTIONAL NEURAL NETWORKS AS A DECISION SUPPORT TOOL IN MEDICAL PROBLEMS – MALIGNANT MELANOMA CASE STUDY
PublikacjaThe paper presents utilization of one of the latest tool from the group of Machine learning techniques, namely Deep Convolutional Neural Networks (CNN), in process of decision making in selected medical problems. After the survey of the most successful applications of CNN in solving medical problems, the paper focuses on the very difficult problem of automatic analyses of the skin lesions. The authors propose the CNN structure...
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A simple model of the trap-assisted recombination with the excitonic Auger mechanism
PublikacjaWe present a simple model of the trap-assisted recombination combined with the excitonic Auger mechanism. It has been shown that only six independent transitions of electrons and holes should be taken into account to describe a combination of the Shockley–Read–Hall (SRH) recombination with this excitonic process. This is in opposition to a well-known model of the SRH mechanism with the free carriers Auger effect via deep states,...
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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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High order of nongeminate recombination in organic bulk heterojunction solar cells
PublikacjaWe analyze high order of nongeminate recombination in organic donor–acceptor bulk heterojunction solar cells. The model of recombination where an exciton annihilates on an electron–hole Langevin bound pair near donor–acceptor interface has been applied in our studies. We obtained satisfactory agreement between experimental results and theoretical calculations for the concentration dependences of several parameters characterizing...
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AITP - AI Thermal Pedestrians Dataset
PublikacjaEfficient pedestrian detection is a very important task in ensuring safety within road conditions, especially after sunset. One way to achieve this goal is to use thermal imaging in conjunction with deep learning methods and an annotated dataset for models training. In this work, such a dataset has been created by capturing thermal images of pedestrians in different weather and traffic conditions. All images were manually annotated...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublikacjaIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Finite element method simulations of various cases of crash tests with N2/W4/A steel road barrier
PublikacjaThe subject of this study is performance of N2/W4/A steel road safety barrier investigated in numerical simulations. System was checked under several types of initial conditions, which were assumed basing on the TB11 and TB32 normative crash tests. The main goal of present study is to investigate the relationship between initial conditions (angle and velocity) of the impact and the severity indices (associated to the vehicle occupant) during...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublikacjaABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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RSS-Based DoA Estimation Using ESPAR Antenna for V2X Applications in 802.11p Frequency Band
PublikacjaIn this paper, we have proposed direction-of arrival (DoA) estimation of incoming signals for V2X applications in 802. 11p frequency band, based on recording of received signal strength (RSS) at electronically steerable parasitic array radiator (ESPAR) antenna's output port. The motivation of the work was to prove that ESPAR antenna used to increase connectivity and security in V2X communication can be also used for DoA estimation....
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Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublikacjaIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
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Quenching of bright and dark excitons via deep states in the presence of SRH recombination in 2D monolayer materials
PublikacjaTwo-dimensional (2D) monolayer materials are interesting systems due to an existence of optically non-active dark excitonic states. In this work, we formulate a theoretical model of an excitonic Auger process which can occur together with the trap-assisted recombination in such 2D structures. The interactions of intravalley excitons (bright and spin-dark ones) and intervalley excitons (momentum-dark ones) with deep states located...
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New Simple and Robust Method for Determination of Polarity of Deep Eutectic Solvents (DESs) by Means of Contact Angle Measurement
PublikacjaThe paper presents a new method for evaluating the polarity and hydrophobicity of deep eutectic solvents (DESs) based on the measurement of the DES contact angle on glass. DESs consisting of benzoic acid derivatives and quaternary ammonium chlorides–tetrabutylammonium chloride (TBAC) and benzyldimethylhexadecylammonium chloride (16-BAC)—in selected molar ratios were chosen for the study. To investigate the DESs polarity, an optical...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublikacjaOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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LSTM-based method for LOS/NLOS identification in an indoor environment
PublikacjaDue to the multipath propagation, harsh indoor environment significantly impacts transmitted signals which may adversely affect the quality of the radiocommunication services, with focus on the real-time ones. This negative effect may be significantly reduced (e.g. resources management and allocation) or compensated (e.g. correction of position estimation in radiolocalisation) by the LOS/NLOS identification algorithm. This paper...
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Hydrophobic (deep) eutectic solvents (HDESs) as extractants for removal of pollutants from water and wastewater – A review
PublikacjaDeep eutectic solvents (DESs) are a new generation of solvents that attracted increasing attention in diverse applications. In last years, growing number of studies on hydrophobic (deep) eutectic solvents (HDESs) as an alternative extractants for various chemicals from aqueous environments have been reported. This article provides an overview on the usage of HDESs in liquid–liquid extraction (LLE) of different pollutants from water...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublikacjaBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Supramolecular deep eutectic solvents and their applications
PublikacjaIn recent years, the growing awareness of the harmfulness of chemicals to the environment has resulted in the development of green and sustainable technologies. The compromise between economy and environmental requirements is based on the development of new efficient and green solutions. Supramolecular deep eutectic solvents (SUPRADESs), a new deep eutectic solvent (DES) subclass characterized by inclusion properties, are a fresh...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublikacjaIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Are deep eutectic solvents useful in chromatography? A short review
PublikacjaA literature update has been done concerning Deep Eutectic Solvents (DES) use in chromatography applications. The literature survey was based on the period from 2010 till 2020 and manuscripts reported in the data bases Web of Science and Scopus. The use of DES as mobile phase and mobile phase additives, stationary phases and solid phase modifiers and the use of DES as reaction solvents for chromatography use, were evaluated. Emphasis...
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Application of deep eutectic solvents (DES) in analytical chemistry
PublikacjaRecent years have been associated with efforts to reduce the impact on the natural environment. A greener approach has been introduced in various areas of science, including analytical chemistry. One of the basic procedures for preparing a sample for analysis is its extraction. Traditional methods involve the use of large amounts of organic compounds, often toxic, with an unfavorable impact on the environment. A representative...
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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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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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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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Awaria ściany szczelinowej stanowiącej obudowę wykopu głębokiego
PublikacjaW artykule przedstawiono awarię ściany szczelinowej stanowiącej obudowę wykopu głębokiego. Omówiono warunki geologiczne, hydrogeologiczne i geotechniczne podłoża. Przeprowadzono analizę rozwiązań konstrukcyjnych w kolejnych oszczędnościowych modyfikacjach projektu oraz zrealizowanej wersji. Wykonano obliczenia porównawcze. Wskazano przyczyny wystąpienia awarii. In the paper a failure of diaphragm wall protecting deep excavation...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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The role of water in deep eutectic solvent-base extraction
PublikacjaDeep eutectic solvents (DESs) are currently being used in different sectors, such as electrochemistry, electrodeposition, organic synthesis, nanoparticle preparation, bioactive compound separation, etc. Their use in analytical chemistry has only recently begun to expand. Despite the publication of a sufficient number of DES-based analytical extraction procedures, some details, such as interaction of DESwith the sample and target...
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Superhydrophobic sponges based on green deep eutectic solvents for spill oil removal from water
PublikacjaThe paper described a new method for crude oil-water separation by means of superhydrophobic melamine sponges impregnated by deep eutectic solvents (MS-DES). Due to the numerous potential of two-component DES formation, simple and quick screening of 156 non-ionic deep eutectic solvents using COSMO-RS (Conductor-like Screening Model for Real Solvents) computational model was used. DES which were characterized by high solubility...
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublikacjaDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Zastosowanie mieszania wgłębnego i iniekcji strumieniowej do wzmocnienia podłoża pod budynkiem basenu.
PublikacjaPrzedstawiono jeden z pierwszych przykładów zastosowania w Europie nowoczesnej technologii wgłębnego mieszania gruntu na mokro (ang. wet Deep Soil Mixing) w celu posadowienia budynku basenu na uwarstwionym podłożu zawierającym grunt organiczny. Technologia DSM, wprowadzona w Polsce przez firmę Keller, polega na mechanicznym mieszaniu in situ gruntu z zaczynem cementowym i pozwala na formowanie w gruncie kolumn z cementogruntu w...
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Deep compaction control of sandy soils
PublikacjaVibroflotation, vibratory compaction, micro-blasting or heavy tamping are typical improvement methods for the cohesionless deposits of high thickness. The complex mechanism of deep soil compaction is related to void ratio decrease with grain rearrangements, lateral stress increase, prestressing effect of certain number of load cycles, water pressure dissipation, aging and other effects. Calibration chamber based interpretation...