Search results for: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych
PublicationCelem rozprawy jest zbadanie algorytmów do identyfikacji instrumentów występujących w sygnale polifonicznym z wykorzystaniem sztucznych sieci neuronowych. W części teoretycznej przywołano podstawy przetwarzania sygnałów fonicznych w kontekście ekstrakcji parametrów sygnałów wykorzystywanych w treningu sieci neuronowych. Dodatkowo dokonano analizy rozwoju metod uczenia maszynowego z uwzględnieniem podziału na sieci neuronowe pierwszej,...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Electron impact iozization of CCl4 and SF6 embedded in superfluid helium droplets
PublicationElectron impact ionization of helium nano-droplets containing several 104 He atoms and doped with CCl4 or SF6 molecules is studied with high-mass resolution. The mass spectra show significant clustering of CCl4 molecules, less so for SF6 under our experimental conditions. Positive ion efficiency curves as a function of electron energy indicate complete immersion of the molecules inside the helium droplets in both cases. For CCl4...
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Positron binding to alkali-metal hydrides: The role of molecular vibrations
PublicationThe bound vibrational levels for J=0 have been computed for the series of alkali-metal hydride molecules from LiH to RbH, including NaH and KH. For all four molecules the corresponding potential-energy curves have been obtained for each isolated species and for its positron-bound complex (e+XH). It is found that the calculated positron affinity values strongly depend on the molecular vibrational state for which they are obtained...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne 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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Magnetic deep eutectic solvents – Fundamentals and applications
PublicationMagnetic deep eutectic solvents (MDES), a relatively new subclass of conventional deep eutectic solvents (DES) containing additional paramagnetic components in their structure. MDES exhibit a strong response toward external magnetic fields, thus they can improve many industrial and analytical applications. In addition, this new group of solvents present unique physicochemical properties that can be easily tuned by selecting the...
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Novel “acid tuned” deep eutectic solvents based on protonated L-proline
PublicationThe paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...
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Poly-L-Lysine-modified boron-doped diamond electrodes for the amperometric detection of nucleic acid bases
PublicationBoron-doped diamond (BDD) is a very promising supporting material used in the construction of biosensors for molecular recognition. The direct immobilization of structurally-organized huge molecules, such as poly-L-Lysine (PLL) provides the possibility of determining organic molecules, e.g. nucleic acid bases (e.g. adenine, guanine) or peptides and proteins. This paper describes the direct method for chemical and electrochemical...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Adsorption-assisted transport of water vapour in super-hydrophobic membranes filled with multilayer graphene platelets
PublicationThe effects of confinement of multilayer graphene platelets in hydrophobic microporous polymeric membranes are here examined. Intermolecular interactions between water vapour molecules and nanocomposite membranes are envisaged to originate assisted transport of water vapour in membrane distillation processes when a suitable filler-polymer ratio is reached. Mass transport coefficients are estimated under different working conditions,...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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ABSORPCJA, METABOLIZM I ROLA BIOLOGICZNA KWASÓW NUKLEINOWYCH OBECNYCH W ŻYWNOŚCI
PublicationKwasy nukleinowe należą do niedocenianych składników żywności, szczególnie surowej lub nisko przetworzonej. W niniejszej publikacji skupiono się na omówieniu przemian, jakim podlegają kwasy nukleinowe w przewodzie pokarmowym człowieka, procesie absorpcji nukleotydów oraz nukleozydów z przewodu pokarmowego, a także przedstawiono podstawowe etapy ich metabolizmu w komórkach organizmu. Produkty trawienia kwasów nukleinowych stanowią...
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Studies of the Interaction Dynamics in Albumin-Chondroitin Sulfate Systems by Recurrence Method
PublicationThe physicochemical basis of lubrication of articular cartilage is still not fully understood. However, the synergy between components of the synovial fluid can be a crucial factor that could explain this phenomenon. This work presents a nonlinear data analysis technique named the recurrence method, applied to the system involving two components of synovial fluid: albumin and chondroitin sulfate (CS) immersed in a water environment....
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Prognostic and diagnostic capabilities of OOBN in assessing investment risk of complex construction projects
PublicationModelling decision problems using Bayesian networks is extremely valuable especially in case of issues related to uncertainty; it is also very helpful in constructing and understanding visual representation of the elements and their relations. This approach facilitates subsequent application of Bayesian networks, however there can be situations where using simple Bayesian networks is impractical or even ineffective. The aim of...
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Rheology of potato starch chemically modified with microwave-assisted reactions
PublicationNative potato starch was sulfated, selenated, borated, silicated and zincatated by means of microwave-assisted reactions with varying doses of relevant reagents. Resulting products were characterized involving rheological behavior of pastes, their weight-average molecular weight (Mw), and radius of gyration (Rg). Most of the pastes showed shear-thinning behavior, with the flow behavior index (n) below unity. The pastes of starch...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Perspectives on the replacement of harmful organic solvents in analytical methodologies: a framework toward the implementation of a generation of eco-friendly alternatives
PublicationVolatile organic solvents derived from non-renewable fossil feedstocks are commonplace in analytical laboratories. In spite of their convenient performance in countless unit operations, their environmental, health and safety issues represent a major area of concern. The progressive replacement of organic solvents obtained from fossil resources by eco-friendly alternatives would involve remarkable advances within the framework of...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Magnetic deep eutectic solvents as efficient media for extraction of furfural and 5-hydroxymethylfurfural from aqueous samples
PublicationThe extraction of furfural (FF) and 5-hydroxymethylfurfural (HMF) from hydrolysates is currently one of the main challenges in bio-refinery. In this work, the separation of FF and HMF from the aqueous phase was carried out using a new type of green solvents – Magnetic Deep Eutectic Solvents (MDES). A conductor-like screening model for realistic solvents (COSMO-RS) was used for the preselection of 400 MDES. MDES which exhibit the...
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Green adsorbents and solvents in food analysis
PublicationGreen analytical chemistry aims to minimize the negative impact of analytical procedures on the environment and human health. This can be achieved through the use of non-toxic and environmentally friendly reagents. Classical green solvents include water, ethanol, acetone, and supercritical fluids. Water has been used for the extraction of water-soluble compounds (sugars, amino acids). Ethanol and acetone have been used for the...
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Removal of Siloxanes from Model Biogas by Means of Deep Eutectic Solvents in Absorption Process
PublicationThe paper presents the screening of 20 deep eutectic solvents (DESs) composed of tetrapropylammonium bromide (TPABr) and glycols in various molar ratios, and 6 conventional solvents as absorbents for removal of siloxanes from model biogas stream. The screening was achieved using the conductor-like screening model for real solvents (COSMO-RS) based on the comparison of siloxane solubility in DESs. For the DES which was characterized...
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Organic solvents aggregating and shaping structural folding of protein, a case study of the protease enzyme
PublicationLow 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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Interactions of positrons with atoms and molecules
PublicationThe positron is the antiparticle of the electron. It has the same mass as the electron, but opposite charge. The understanding of the interactions of positrons with normal matter, like atoms and molecules, is of interest in various scientific fields, like nuclear medicine, plasma physics and astronomy. In this talk we will give a short introduction to some theoretical methods to describe the interactions of positrons with atoms...
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Rotational state-changing collisions of C2H− and C2N− anions with He under interstellar and cold ion trap conditions: A computational comparison
PublicationWe present an extensive range of quantum calculations for the state-changing rotational dynamics involving two simple molecular anions that are expected to play some role in the evolutionary analysis of chemical networks in the interstellar environments, C2H− (X1Σ+) and C2N− (X3Σ−), but for which inelastic rates are only known for C2H−. The same systems are also of direct interest in modeling selective photo-detachment experiments...
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Neural network simulator's application to reference performance determination of turbine blading in the heat-flow diagnostics.
PublicationIn the paper, the possibility of application of artificial neural networks to perform the fluid flow calculations through both damaged and undamaged turbine blading was investigated. Preliminary results are presented and show the potentiality of further development of the method for the purpose of heat-flow diagnostics.
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Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning
PublicationDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep neural network architecture search using network morphism
PublicationThe 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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Dynamic mechanical properties and flexing fatigue resistance of tire sidewall rubber as function of waste tire rubber reclaiming degree
PublicationA stepwise downsizing method of gel particles in reclaimed rubber to a micro-nano scale and its excellent dynamic performance in tire sidewall were introduced by this work. The results showed that the size of gel particles decreased from several micrometers to micro-nanometers with the increase of reclaiming degree, accompanied by reduced molecular weight and widened molecular weight distribution of sol fraction. The addition of...
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Hydrophobic deep eutectic solvents in microextraction techniques–A review
PublicationOver the past decade, deep eutectic solvents (DES) have been widely studied and applied in sample preparation techniques. Until recently, most of the synthesized DES were hydrophilic, which prevented their use in the extraction of aqueous samples. However, after 2015 studies on the synthesis and application of hydrophobic deep eutectic solvents (HDES) has rapidly expanded. Due to unique properties of HDES i.e. density, viscosity,...
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Hyaluronan-Chondroitin Sulfate Anomalous Crosslinking Due to Temperature Changes
PublicationGlycosaminoglycans are a wide class of biopolymers showing great lubricating properties due to their structure and high affinity to water. Two of them, hyaluronic acid and chondroitin sulfate, play an important role in articular cartilage lubrication. In this work, we present results of the all-atom molecular dynamics simulations of both molecules placed in water-based solution. To mimic changes of the physiological conditions,...
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Water Behavior Near the Lipid Bilayer
PublicationIn this chapter, we focus on the dynamics of water molecules situated in the vicinity of a phospholipid bilayer. Using a molecular dynamics simulation method, we studied interactions between water and the bilayer and tracked trajectories of the water molecules. Based on the hypothesis that molecules trapped inside the bilayer make different motions than the ones which are either attached to the surface or move freely in the water...
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Electron impact fragmentation of pyrrole molecules studied by fluorescence emission spectroscopy
PublicationThe fluorescence emission spectroscopy using electron impact excitation technique was employed to study fragmentation processes of the gas phase pyrrole molecules. The following excited fragmentation species were observed by detection of their fluorescence decay: the atomic hydrogen H(n), n = 4-7 and the diatomic CH(A2Δ), CN(B2Σ+), NH(A3Π) and C2(d3Πg) fragments. These atomic and molecular products differ from those previously...
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Why is the cubic structure preferred in newly formed ice?
PublicationMolecular dynamics was employed to explain the preference for the cubic structure in newly formed crystals of ice. The results showed that in supercooled liquid water the molecules connected by hydrogen bonds are more likely to adopt relative orientations similar to the ones characteristic for cubic ice. The observed preference for certain relative orientations of molecules in the hydrogen-bonded pairs results in the higher probability...
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Modelowanie przepływu pary przez okołodźwiękowe wieńce turbinowe z użyciem sztucznych sieci neuronoych
PublicationNiniejszy artykuł stanowi opis modelu przepływu pary przez okołodźwiękowe stopnie turbinowe, stworzonego w oparciu o sztuczne sieci neuronowe (SSN). Przedstawiony model neuronowy pozwala na wyznaczenie rozkładu wybranych parametrów w analizowanym przekroju kanału przepływowego turbiny dla rozpatrywanego zakresu wartości ciśnienia wlotowego.
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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The POCOBIO Database for Computed Scattering Cross-Sections for Positron Collisions with Biomolecular Systems
PublicationThe design of a database for positron interactions with biomolecular systems is outlined. The database contains only scattering cross sections, which are derived from theory. The data model is defined in a very flexible way, which facilitates the usage of weakly bound clusters of molecules and molecular systems with many tautomeric forms.
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Deep eutectic solvents with solid supports used in microextraction processes applied for endocrine-disrupting chemicals
PublicationThe determination of endocrine-disrupting chemicals (EDCs) has become one of the biggest challenges in Analytical Chemistry. Due to the low concentration of these compounds in different kinds of samples, it becomes necessary to employ efficient sample preparation methods and sensitive measurement techniques to achieve low limits of detection. This issue becomes even more struggling when the principles of the Green Analytical Chemistry...
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Assessment and design of greener deep eutectic solvents – A multicriteria decision analysis
PublicationDeep eutectic solvents (DES) are often considered as green solvents because of their properties, such as negligible vapor pressure, biodegradability, low toxicity or natural origin of their components. Due to the fact that DES are cheaper than ionic liquids, they have gained many applications in a short period of time. However, claims about their greenness sometimes seem to be exaggerated. Especially, bearing in mind lots of data...
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Chitin and derivative chitosan-based structures — Preparation strategies aided by deep eutectic solvents: A review
PublicationThe high molecular weight of chitin, as a biopolymer, challenges its extraction due to its insolubility in the solvents. Also, chitosan, as the N-deacetylated form of chitin, can be employed as a primary material for different industries. The low mechanical stability and poor plasticity of chitosan films, as a result of incompatible interaction between chitosan and the used solvent, have limited its industrialization. Deep eutectic...
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublicationSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Precipitation and Transformation of Vaterite Calcium Carbonate in the Presence of Some Organic Solvents
PublicationIn this paper, the production of CaCO3 particles via the carbonation route in the reaction of CaCl2 and CO2, using NH3 as a promoter of CO2 absorption, was studied. The solvents used as the reaction media for CaCO3 precipitation were aqueous solutions of methanol, isopropanol and dimethyl sulfoxide (DMSO), in a concentration range of 0–20% (v/v). It was found that the presence of an organic additive influenced the precipitation...
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Optical photoluminescent, and electroluminescent properties of organic solids
PublicationThis chapter discusses optical, photoluminescence and electroluminescence properties of organic materials. First, the spectral features of individual molecules and molecular solid states are analysed. Next, the excitonic processes in organic materials are discussed. The chapter reviews experimental methods leading to the determination of basic excitonic parameters. Finally, the electroluminescence phenomena in organic materials...