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Wyniki wyszukiwania dla: DEEP EUTECTIC SOLVENT
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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...
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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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Combined pH/organic solvent gradient HPLC in analysis of forensic material
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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...
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Solvent extraction of copper ions by 3-substituted derivatives of β-diketones
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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.
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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).
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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...
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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...
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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....
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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...
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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...
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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....
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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...
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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...
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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...
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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...
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AGAR a Microbial Colony Dataset for Deep Learning Detection
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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...
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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...
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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...
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Determination of aliphatic amines in water by gas chromatography using headspace solvent microextraction
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One‐Pot Synthesis of Selected P‐Vinylbenzyls under Solvent‐Free Conditions
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Solvent effects on the nitrogen NMR chemical shifts in 1-methylazoles – a theoretical study
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Theoretical analysis of solvent effects on nitrogen NMR chemical shifts in oxazoles and oxadiazoles
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Distinguishing of cocrystals from simple eutectic mixtures: phenolic acids as potential pharmaceutical coformers
PublikacjaThe multiparameter model comprising 1D and 2D QSPR/QSAR descriptors was proposed and validated for phenolic acid binary systems. This approach is based on the optimization of regression coefficients for maximization of the percentage of true positives in the pool of systems comprising either simple binary eutectics or cocrystals. The training set consisted of 58 eutectics and 168 cocrystals. The solid dispersions collection used...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublikacjaIn the paper we present performance-energy trade-off investigation of training Deep Convolutional Neural Networks for image recognition. Several representative and widely adopted network models, such as Alexnet, VGG-19, Inception V3, Inception V4, Resnet50 and Resnet152 were tested using systems with Nvidia Quadro RTX 6000 as well as Nvidia V100 GPUs. Using GPU power capping we found other than default configurations minimizing...
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Understanding ion–ion and ion–solvent interactions in aqueous solutions of morpholinium ionic liquids with N-acetyl-L-alaninate anion through partial molar properties and molecular dynamics simulations
PublikacjaAmino acid ionic liquids (AAILs) provide a low toxicity, biodegradable alternative to conventional ionic liquids, while also maintaining solubility in water. Densities and sound velocities of aqueous solutions of four amino acid ionic liquids (AAILs), based on the N-alkyl-N-methylmorpholinium ([Mor1,R], R = 2, 3, 6, 8) cation and N-acetyl-L-alaninate ([N-Ac-L-Ala]) anion were measured at T = (293.15–313.15) K and at atmospheric...
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Deep learning-based waste detection in natural and urban environments
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Generation of microbial colonies dataset with deep learning style transfer
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Deep brain stimulation: new possibilities for the treatment of mental disorders
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The Impact of Dredging Deep Pits on Organic Matter Decomposition in Sediments
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Problem of selection of reference plane with deep and wide valleys analysis
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Efficiency of deep bed filtration in treatment of swimming pool water
PublikacjaPrzebadano efektywność filtracji wody w filtrach ze złożem żwirowo-piaskowym w instalacji basenu rehabilitacyjnego. Obok analizy instrumentalnej wody, w badaniach uwzględniono rozkład wielkości cząstek i analizę termiczną osadu zgromadzonego w złożu piaskowym filtrów wgłębnych i usuwanego podczas płukania.
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublikacjaDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Diffusive properties of solvent molecules in the neighborhood of a polymer chain as seen by Monte-Carlo simulations
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Solvent effects on fluorescence properties of protochlorophyll and its derivatives with various porphyrin side chains
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Solvent-Free Synthesis of Phosphonic Graphene Derivative and Its Application in Mercury Ions Adsorption
PublikacjaFunctionalized graphene was efficiently prepared through ball-milling of graphite in the presence of dry ice. In this way, oxygen functional groups were introduced into material. The material was further chemically functionalized to produce graphene derivative with phosphonic groups. The obtained materials were characterized by spectroscopic and microscopic methods, along with thermogravimetric analysis. The newly developed material...
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Release Kinetics Studies of Early-Stage Volatile Secondary Oxidation Products of Rapeseed Oil Emitted during the Deep-Frying Process
PublikacjaThe research concerns the use of proton transfer reaction mass spectrometer to track real-time emissions of volatile secondary oxidation products released from rapeseed oil as a result of deep-frying of potato cubes. Therefore, it was possible to observe a sudden increase of volatile organic compound (VOC) emissions caused by immersion of the food, accompanied by a sudden release of steam from a potato cube and a decrease of the...
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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,...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublikacjaObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Using deep learning to increase accuracy of gaze controlled prosthetic arm
PublikacjaThis paper presents how neural networks can be utilized to improve the accuracy of reach and grab functionality of hybrid prosthetic arm with eye tracing interface. The LSTM based Autoencoder was introduced to overcome the problem of lack of accuracy of the gaze tracking modality in this hybrid interface. The gaze based interaction strongly depends on the eye tracking hardware. In this paper it was presented how the overall the...
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Autonomous pick-and-place system based on multiple 3Dsensors and deep learning
PublikacjaGrasping objects and manipulating them is the main way the robot interacts with its environment. However, for robots to operate in a dynamic environment, a system for determining the gripping position for objects in the scene is also required. For this purpose, neural networks segmenting the point cloud are usually applied. However, training such networks is very complex and their results are unsatisfactory. Therefore, we propose...
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Deep learning approach on surface EEG based Brain Computer Interface
PublikacjaIn this work we analysed the application of con-volutional neural networks in motor imagery classification for the Brain Computer Interface (BCI) purposes. To increase the accuracy of classification we proposed the solution that combines the Common Spatial Pattern (CSP) with convolutional network (ConvNet). The electroencephalography (EEG) is one of the modalities we try to use for controlling the prosthetic arm. Therefor in this...
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Deep learning approach for delamination identification using animation of Lamb waves
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Deep learning super-resolution for the reconstruction of full wavefield of Lamb waves
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OmicSelector: automatic feature selection and deep learning modeling for omic experiments
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Simulation of backup rolls quenching with experimental study of deep cryogenic treatment
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Deep Data Analysis of a Large Microarray Collection for Leukemia Biomarker Identification
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