Filtry
wszystkich: 1037
-
Katalog
wyświetlamy 1000 najlepszych wyników Pomoc
Wyniki wyszukiwania dla: deep eutectic solvent
-
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...
-
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.
-
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.
-
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.
-
THE INFLUENCE OF THE TYPE SOLVENT ON THE STRUCTURE OF CHITOSAN BLENDS WITH HYALURONIC ACID
Publikacja -
pH/Organic Solvent Double-Gradient Reversed-Phase HPLC
Publikacja -
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,...
-
Deep learning-enabled integration of renewable energy sources through photovoltaics in buildings
PublikacjaInstalling photovoltaic (PV) systems in buildings is one of the most effective strategies for achieving sustainable energy goals and reducing carbon emissions. However, the requirement for efficient energy management, the fluctuating energy demands, and the intermittent nature of solar power are a few of the obstacles to the seamless integration of PV systems into buildings. These complexities surpass the capabilities of rule-based...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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...
-
Paradigm of deep pectoral myopathy in broiler chickens
Publikacja -
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...
-
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...
-
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,...
-
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...
-
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...
-
Changes in conditions of acoustic wave propagation in the Gdansk deep as an effect of climate changes in the Baltic Sea region
PublikacjaThe article presents the results from a research project investigating acoustic climate changes in the Gdansk Deep based on data extending from 1902 to 2019. This part of the southern Gotland Basin, is rarely discussed in the scientific literature. The speed of sound in the seawater is a function of temperature, salinity, and depth. In such shallow sea as Baltic Sea, the impact of depth is not substantial. The other two factors...
-
Solvent extraction of copper ions by 3-substituted derivatives of β-diketones
Publikacja -
Accelerated solvent extraction-gas chromatographic determination of acidic herbicides in soil
PublikacjaPrzyspieszona ekstrakcja rozpuszczalnikiem z wykorzystaniem wody jako ekstraktanta okazała się skutecznym sposobem izolacji herbicydów kwasowych (MCPP, MCPA, 2,4-D, 2,4,5-T, PCP, dinoseb, dinoterb) z próbek gleby. Wysoka zawartość substancji iłowych powodowała problemy techniczne, które udało się pokonać poprzez zwiększenie stosunku piasku do gleby w celce ekstrakcyjnej. Anality przenoszono z ekstraktu wodnego do rozpuszczalnika...
-
Combined pH/organic solvent gradient HPLC in analysis of forensic material
Publikacja -
Solvent residue determination in Uncaria Tomentosa Bark by HS-GC technique
PublikacjaPrzedstawiono wyniki oznaczeń pozostałości rozpuszczalników organicznych w preparacie uzyskanym z kory liany U. Tomentosa, wykorzystywanej do produkcji farmaceutyków i dodatków do żywności. 1,1,2-trichloroeten oraz dichlorometan są powszechnie stosowane do usunięcia z kory kilku grup alkaloidów o znanych właściwościach biologicznych, co umożliwia zbadanie pozostałych jej związków. Ilościowe oznaczanie tych rozpuszcalników jest...
-
Influence of surfactants on interaction forces between polyethylene surfaces in a hydrocarbon solvent.
PublikacjaPrzeprowadzono bezpośrednie pomiary oddziaływań międzyfazowych pomiędzy cząstkami polietylenowymi w środowisku n-tetradekanu z dodatkiem surfaktantów(kwasu larynowego i dodecyloaminy). Dodatek surfaktantów wpłynął na wzrost oddziaływań odpychających pomiędzy powierzchniami polietylenowymi, szczególnie w przypadku dodecyloaminy. Zaobserwowano obecność wzrostu sferycznych sił odpychających ze wzrostem temperatury.
-
Controlling the size and morphology of precipitated calcite particles by the selection of solvent composition
PublikacjaCalcium carbonate particles were obtained in the reaction of calcium hydroxide with carbon dioxide at 65°C. Initial Ca(OH)2 suspensions were prepared in pure water and aqueous solutions of ethylene glycol or glycerol of the concentration range up to 20% (vol.). The course of reaction was monitored by conductivity measurements. Precipitated solids were analyzed by FTIR, XRD, SEM and the particles size distribution was determined...
-
Extraction of acidic herbicides from soil by means of accelerated solvent extraction.
PublikacjaZaprezentowano opracowanie procedury izolacji herbicydów kwasowych z gleby z zastosowaniem urządzenia DIONEX ASE 200. Celem było zoptymalizowanie warunków pracy urządzenia: czasu, temperatury, ciśnienia oraz ilości cykli ekstrakcji. Ostatecznie ekstrakty, po przeprowadzeniu analitów w pochodne metylowe, poddano analizie chromatograficznej (GC).
-
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...
-
Changes in conditions of acoustic wave propagation in the Gdansk deep as an effect of climate changes in the Baltic Sea region
PublikacjaThe article presents the results from a research project investigating acoustic climate changes in the Gdansk Deepbased on data extending from 1902 to 2019. This part of the southern Gotland Basin, is rarely discussed in thescientific literature.The speed of sound in the seawater is a function of temperature, salinity, and depth. In such shallow sea asBaltic Sea, the impact of depth is not substantial....
-
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...
-
Application of analytical procedure based on accelerated solvent extraction and ion chromatography technique for determination of thiocyanate and other inorganic ions in human placenta samples
PublikacjaExposure of a pregnant woman during pregnancy is a special case of exposure to toxic substances. Samples of placenta collected for the studies had been prepared with the technique of accelerated solvent extraction and later analyzed for the presence of thiocyanate ion and other inorganic ions, with the use of the technique of ion chromatography. The concentration of thiocyanate ion in placenta samples collected from active smokers...
-
Deep neural networks for human pose estimation from a very low resolution depth image
PublikacjaThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
-
Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
-
Ultrasound-Assisted Solvent Extraction of a Porous Membrane Packed Sample for the Determination of Tobacco-Specific Nitrosamines in the Replacement Liquids for E-Cigarettes
PublikacjaThe content of tobacco-specific nitrosamines (TSNAs) possessing carcinogenic properties has been an important area of research since replacement liquids were introduced for e-cigarettes. A method for determining N′-nitrosonornicotine (NNN), 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), N′-nitrosoanatabine (NAT), and N′-nitrosoanabasine (NAB) in replacement liquids for electronic cigarettes was developed using liquid chromatography–tandem...
-
Accurate Modeling of Antenna Structures by Means of Domain Confinement and Pyramidal Deep Neural Networks
PublikacjaThe importance of surrogate modeling techniques has been gradually increasing in the design of antenna structures over the recent years. Perhaps the most important reason is a high cost of full-wave electromagnetic (EM) analysis of antenna systems. Although imperative in ensuring evaluation reliability, it entails considerable computational expenses. These are especially pronounced when carrying out EM-driven design tasks such...
-
AGAR a Microbial Colony Dataset for Deep Learning Detection
Publikacja -
Musical Instrument Identification Using Deep Learning Approach
PublikacjaThe work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related to musical instrument identification. It focuses on tasks performed, input type, algorithms employed, and metrics used. The paper starts with the background presentation, i.e., metadata...
-
Detecting Lombard Speech Using Deep Learning Approach
PublikacjaRobust Lombard speech-in-noise detecting is challenging. This study proposes a strategy to detect Lombard speech using a machine learning approach for applications such as public address systems that work in near real time. The paper starts with the background concerning the Lombard effect. Then, assumptions of the work performed for Lombard speech detection are outlined. The framework proposed combines convolutional neural networks...
-
Machine Learning and Deep Learning Methods for Fast and Accurate Assessment of Transthoracic Echocardiogram Image Quality
PublikacjaHigh-quality echocardiogram images are the cornerstone of accurate and reliable measurements of the heart. Therefore, this study aimed to develop, validate and compare machine learning and deep learning algorithms for accurate and automated assessment of transthoracic echocardiogram image quality. In total, 4090 single-frame two-dimensional transthoracic echocardiogram...
-
Attention-Based Deep Learning System for Classification of Breast Lesions—Multimodal, Weakly Supervised Approach
PublikacjaBreast cancer is the most frequent female cancer, with a considerable disease burden and high mortality. Early diagnosis with screening mammography might be facilitated by automated systems supported by deep learning artificial intelligence. We propose a model based on a weakly supervised Clustering-constrained Attention Multiple Instance Learning (CLAM) classifier able to train under data scarcity effectively. We used a private...
-
Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublikacjaCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
-
Solvent effects on the nitrogen NMR chemical shifts in 1-methylazoles – a theoretical study
Publikacja -
Theoretical analysis of solvent effects on nitrogen NMR chemical shifts in oxazoles and oxadiazoles
Publikacja -
Determination of aliphatic amines in water by gas chromatography using headspace solvent microextraction
Publikacja