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Wyniki wyszukiwania dla: DEEP EUTECTIC SOLVENT
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Deep Learning Approaches in Histopathology
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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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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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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...
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OPTICAL STRAIN MEASUREMENT OF CONCRETE VERSUS MANUAL EXTENSOMETER MEASUREMENT BASED ON THE TEST RC DEEP BEAM IN A COMPLEX STATE OF STRESS
PublikacjaThe purpose of this study is to compare the strain measurement techniques of concrete in R-C element subjected to the monotonic load up to the failure. In the analysis manual extensometer methods of measurements and the optical system ARAMIS for non-contact three-dimensional measurements of deformation was used. The test sample was a cantilever deep beam loaded throughout the depth which was a part of the reinforced concrete deep...
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A closer look at how the dispersive liquid–liquid microextraction method works. Investigation of the effect of solvent mixture composition on the quality and stability of the cloudy state
PublikacjaThe dispersive liquid–liquid microextraction (DLLME) is one of the most popular miniaturized extraction procedures. In this paper, the degree of dispersion and dispersion stability were studied with the aim to assess the correlations of these parameters with efficiency for the selected analytical application. The dependence between the degree of dispersion (cloudy state quality) and its stability obtained by various emulsification...
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Bimodal deep learning model for subjectively enhanced emotion classification in films
PublikacjaThis research delves into the concept of color grading in film, focusing on how color influences the emotional response of the audience. The study commenced by recalling state-of-the-art works that process audio-video signals and associated emotions by machine learning. Then, assumptions of subjective tests for refining and validating an emotion model for assigning specific emotional labels to selected film excerpts were presented....
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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...
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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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Optimization of vortex-assisted supramolecular solvent-based liquid liquid microextraction for the determination of mercury in real water and food samples
PublikacjaA novel method was developed for sample preparation for spectrophotometric determination of Hg(II) in water and food samples. The method was based on vortex-assisted supramolecular solvent-assisted liquid-liquid microextraction (VA-SUPRASs-LLME). Analytical parameters such as pH, chelating agent, solvent type and volume, vortex time and salting out effect were optimized. Surface and normal probability plots were drawn for the variables...
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Green aspects of sample preparation - a need for solvent reduction
PublikacjaWzrastające zainteresowanie ochroną środowiska zmusza chemików, łącznie z chemikami analitykami, do modyfikacji chemicznej aktywności w taki sposób aby była ona prowadzona zgodnie z zasadami zielonej chemii. W artykule przedstawiono przegląd problemów zielonej chemii w dziedzinie przygotowania próbek do analizy, koncentrując się szczególnie na zaletach tzw. bezrozpuszczalnikowych technik przygotowania próbek. Przedstawiono techniki...
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Pervaporation Zeolite-Based Composite Membranes for Solvent Separations
PublikacjaThanks to their well-defined molecular sieving and stability, zeolites have been proposed in selective membrane separations, such as gas separation and pervaporation. For instance, the incorporation of zeolites into polymer phases to generate composite (or mixed matrix) membranes revealed important advances in pervaporation. Therefore, the goal of this review is to compile and elucidate the latest advances (over the last 2-3 years)...
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Face with Mask Detection in Thermal Images Using Deep Neural Networks
PublikacjaAs 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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Application of ultrasound-assisted solvent extraction of porous membrane packed liquid samples for polyphenols determination in wine samples
PublikacjaPolyphenols play a crucial role in a proper human health maintenance as well as their presence very often correspond to the quality assessment of producs like wine. Thus, their monitoring is of high interest. However, as they occur in a complex matrices their extraction is very often necessary prior the analysis. Herein, a new ultrasound-assisted solvent extraction of porous membrane packed liquid sample technique has been optimized...
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Influence of Thermal Imagery Resolution on Accuracy of Deep Learning based Face Recognition
PublikacjaHuman-system interactions frequently require a retrieval of the key context information about the user and the environment. Image processing techniques have been widely applied in this area, providing details about recognized objects, people and actions. Considering remote diagnostics solutions, e.g. non-contact vital signs estimation and smart home monitoring systems that utilize person’s identity, security is a very important factor....
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LOS and NLOS identification in real indoor environment using deep learning approach
PublikacjaVisibility conditions between antennas, i.e. Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) can be crucial in the context of indoor localization, for which detecting the NLOS condition and further correcting constant position estimation errors or allocating resources can reduce the negative influence of multipath propagation on wireless communication and positioning. In this paper a deep learning (DL) model to classify LOS/NLOS...
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Pursuing the Deep-Learning-Based Classification of Exposed and Imagined Colors from EEG
PublikacjaEEG-based brain-computer interfaces are systems aiming to integrate disabled people into their environments. Nevertheless, their control could not be intuitive or depend on an active external stimulator to generate the responses for interacting with it. Targeting the second issue, a novel paradigm is explored in this paper, which depends on a passive stimulus by measuring the EEG responses of a subject to the primary colors (red,...
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Ultrasound-assisted solvent extraction of porous membrane packed solid samples: A new approach for extraction of target analytes from solid samples
PublikacjaFor the first time, a porous membrane-based method is proposed for the extraction of target analytes directly from the solid samples. This method involves the packing of solid sample inside a porous polypropylene membrane sheet whose edges are heat-sealed to fabricate a bag. This bag is immersed in a suitable solvent and the analytes are extracted by the application of ultrasound energy. The various factors that affect the extraction...
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Deep convolutional neural network for predicting kidney tumour malignancy
PublikacjaPurpose: According to the statistics, up to 15-20% of removed solid kidney tumors turn out to be benign in postoperative histopathological examination, despite having been identified as malignant by a radiologist. The aim of the research was to limit the number of unnecessary nephrectomies of benign tumors. Methods or Background: We propose a machine-aided diagnostic system for kidney...
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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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A hierarchical porous composite magnetic sorbent of reduced graphene oxide embedded in polyvinyl alcohol cryogel for solvent‐assisted‐solid phase extraction of polycyclic aromatic hydrocarbons
PublikacjaA hierarchical porouscomposite magnetic sorbent was fabricated and applied tothe dispersive solvent-assisted solid-phase extraction of five polycyclic aromatichydrocarbons. A sorbent was first prepared by incorporating graphene oxide,calcium carbonate, and magnetite nanoparticles into a polyvinyl alcohol cryo-gel. The graphene oxide was converted to reduced graphene oxide using ascorbicacid and a hierarchical porous structure was...
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublikacjaIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Deep learning for ultra-fast and high precision screening of energy materials
PublikacjaSemiconductor 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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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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pH/Organic Solvent Double-Gradient Reversed-Phase HPLC
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Influence of aprotic solvent on selectivity of an amperometric sensor with nafion membrane
PublikacjaW publikacji przedstawiono rezultaty badań dotyczące selektywności amperometrycznego czujnika ditlenku siarki z membraną nafionową wobec tlenku węgla i dwutlenku azotu jako interferentów. Zostały porównane współczynniki selektywności dla czujników wypełnionych roztworami elektrolitów zawierających wodne roztwory kwasu siarkowego i różne ilości rozpuszczalnika aprotycznego - dimetylosulfotlenku.
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Impedance investigations of amperometric gas sensor containing aprotic solvent
PublikacjaSkonstruowany został amperometryczny czujnik gazowy w układzie trójelektrodowym ze złotą elektrodą roboczą bezpośrednio napyloną na membranę Nafionową. W publikacji przedstawiono wyniki badań charakterystyk czujnika do oznaczania ditlenku siarki wypełnionego elektrolitem zawierającym różne względne zawartości DMSO/H2O. Wyniki badań impedancyjnych zostały przeanalizowane w oparciu o zaproponowany elektryczny układ zastępczy.
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Influence of aprotic solvent on a signal of an amperometric sensor with Nafion membrane
PublikacjaW pracy przedstawiono wyniki badań charakterystyk analitycznych amperometrycznego czujnika ditlenku siarki wyposażonego w mebranę nafionową i wypełnionego roztworami elektrolitów o różnej zawartości dimetylosulfotlenku. Ocenie poddany został wpływ zawartości DMSO w roztworze elektrolitu wewnętrznego czujnika oraz prędkości przepływu gazu na czułość czujnika i czas odpowiedzi na zmiany stężenia ditlenku siarki.
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THE INFLUENCE OF THE TYPE SOLVENT ON THE STRUCTURE OF CHITOSAN BLENDS WITH HYALURONIC ACID
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Large-scale DFT calculations in implicit solvent-A case study on the T4 lysozyme L99A/M102Q protein
PublikacjaW ostatnich latach zaproponowano szereg modeli typu implicit solvent, ktore bazują na bezpośrednim rozwiązaniu niejednorodnego równania Poissona w przestrzeni rzeczywistej. Modele te charakteryzują się elegancją, ponieważ wnęka, w której umieszczona jest molekuła substancji rozpuszczanej zdefiniowana jest bezpośrednio w funkcji gęstości elektronowej, a rozkład ładunku jest w sposób samouzgodniony polaryzowany dzięki reakcji dielektryka,...
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Explicit solvent repulsive scaling replica exchange molecular dynamics ( RS‐REMD ) in molecular modeling of protein‐glycosaminoglycan complexes
PublikacjaGlycosaminoglcyans (GAGs), linear anionic periodic polysaccharides, are crucial for many biologically relevant functions in the extracellular matrix. By interacting with proteins GAGs mediate processes such as cancer development, cell proliferation and the onset of neurodegenerative diseases. Despite this eminent importance of GAGs, they still represent a limited focus for the computational community in comparison to other classes...
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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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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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Ultrasound assisted solvent extraction of porous membrane-packed samples followed by liquid chromatography-tandem mass spectrometry for determination of BADGE, BFDGE and their derivatives in packed vegetables
PublikacjaThe problem of the presence of trace organic pollutants in food is of growing importance due to increasing awareness about their impact on newborns, infants and adults of reproductive age. Despite the fact that packaged food products offer many advantages, packaging can be a source of contamination for stored food. Thus, monitoring such pollution in food is of high importance. In this work, a novel methodology based on the solvent...
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Classification of objects in the LIDAR point clouds using Deep Neural Networks based on the PointNet model
PublikacjaThis work attempts to meet the challenges associated with the classification of LIDAR point clouds by means of deep learning. In addition to achieving high accuracy, the designed system should allow the classification of point clouds covering an area of several dozen square kilometers within a reasonable time interval. Therefore, it must be characterized by fast processing and efficient use of memory. Thus, the most popular approaches...
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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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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublikacjaIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry
PublikacjaWe describe a novel method for the quality assessment of oil utilized for deep frying. The method is based on the analysis of frying fumes using a custom electronic nose. The quality score could be obtained after less than 3 min of analysis and without interrupting the frying process or sampling the oil directly. The obtained results were correlated with the peroxide value using a multivariate linear regression model. The most...
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublikacjaIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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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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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Paradigm of deep pectoral myopathy in broiler chickens
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Impact of deep excavation on nearby urban area
PublikacjaObciążenia i odciążenia gruntu wywołane są wykonaniem i obciążeniem konstrukcji. Wpływ technologii wykonawstwa powiązany jest z metodami wykonawstwa budowli i zależy od: rodzaju ścianki, sposobu jej wykonania, sztywności ścianki, sposobu obniżenia zwierciadła wody, drgań wywołanych wprowadzeniem ścianki i innych. Podano przykłady wykonania głębokich wykopów za pomocą ścianek stalowych i palisad w miejscach zurbanizowanych i różnych...
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Nonlinear properties of the Gotland Deep – Baltic Sea
PublikacjaThe properties of the nonlinear phenomenon in water, including sea water, have been well known for many decades. The feature of the non homogeneous distribution of the speed of sound along the depth of the sea is very interesting from the physical and technical point of view. It is important especially in the observation of underwater area by means of acoustical method ( Grelowska et al ., 2013; 2014). The observation of the underwater...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublikacjaHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Performance and Energy Aware Training of a Deep Neural Network in a Multi-GPU Environment with Power Capping
PublikacjaIn this paper we demonstrate that it is possible to obtain considerable improvement of performance and energy aware metrics for training of deep neural networks using a modern parallel multi-GPU system, by enforcing selected, non-default power caps on the GPUs. We measure the power and energy consumption of the whole node using a professional, certified hardware power meter. For a high performance workstation with 8 GPUs, we were...