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Wyniki wyszukiwania dla: DEEP EUTECTIC SOLVENTS
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Sensitive method for determination of benzoic acid in beverages and food samples using air–assisted hydrophobic deep eutectic solvent-based dispersive liquid-liquid microextraction
PublikacjaA simple, reliable and rapid air–assisted hydrophobic deep eutectic solvent-based dispersive liquid–liquid microextraction (AA-HDES-DLLME) was developed for analysis of benzoic acid in various beverages and food samples. The final determination stage was performed via UV–visible spectrophotometry. The key parameters (extraction time, HDES type and volume, dispersant volume, pH and sample volume) of the AA-HDES-DLLME method were...
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Investigation of vortex assisted magnetic deep eutectic solvent based dispersive liquid–liquid microextraction for separation and determination of vanadium from water and food matrices: Multivariate analysis
PublikacjaA new and simple vortex assisted magnetic deep eutectic solvent dispersive liquid–liquid microextraction procedure (VA-MDES-DLLME) was developed for the determination of vanadium (V) in food and water samples by flame atomic absorption spectrometry (FAAS). In the extraction medium, a bis(acetylpivalylmethane) ethylenediimine (H2APM2en) was used for the complexation of V(V) in sample solution at pH 6. The VA-MDES-DLLME was optimized...
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Organic solvents aggregating and shaping structural folding of protein, a case study of the protease enzyme
PublikacjaLow solubility of reactants or products in aqueous solutions can result in the enzymatic catalytic reactions that can occur in non-aqueous solutions. In current study we investigated aqueous solutions containing different organic solvents / deep eutectic solvents (DESs) that can influence the protease enzyme's activity, structural, and thermal stabilities. Retroviral aspartic protease enzyme is responsible for the cleavage of the...
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Merging Proline:Xylitol Eutectic Solvent in Crosslinked Chitosan Pervaporation Membranes for Enhanced Water Permeation in Dehydrating Ethanol
PublikacjaThe scope of this research aims at merging a new deep eutectic mixture (DES) into a biopolymer-based membrane for a pervaporation application in dehydrating ethanol. Herein, an L-proline:xylitol (at 5:1) eutectic mixture was successfully synthesized and blended with chitosan (CS). A complete characterization of the hybrid membranes, in terms of morphology, solvent uptake, and hydrophilicity, has been conducted. As part of their...
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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
PublikacjaVolatile 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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Surfactants application in sample preparation techniques: Insights, trends, and perspectives
PublikacjaSince the implementation of Green Chemistry into analytical practice, significant efforts have been made to improve the sustainability of chemical analysis. These include reducing the use of hazardous chemicals and solvents, minimizing waste, and improving energy efficiency. Surfactants can be applied in chemical analysis as an environmentally friendly alternative to conventional solvents and chemicals. The use of surfactants can...
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Intermolecular Interactions of Edaravone in Aqueous Solutions of Ethaline and Glyceline Inferred from Experiments and Quantum Chemistry Computations
PublikacjaEdaravone, acting as a cerebral protective agent, is administered to treat acute brain infarction. Its poor solubility is addressed here by means of optimizing the composition of the aqueous choline chloride (ChCl)-based eutectic solvents prepared with ethylene glycol (EG) or glycerol (GL) in the three different designed solvents compositions. The slurry method was used for spectroscopic solubility determination in temperatures...
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Magnetic superhydrophobic melamine sponges for crude oil removal from water
PublikacjaThis paper proposes the preparation of a new sorbent material based on melamine sponges (MS) with superhydrophobic, superoleophilic, and magnetic properties. This study involved impregnating the surface of commercially available MS with eco-friendly deep eutectic solvents (DES) and Fe3O4 nanoparticles. The DES selection was based on the screening of 105 eutectic mixtures using COSMO-RS modeling. Other parameters affecting the efficiency...
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Combination of homogeneous liquid–liquid extraction and vortex assisted dispersive liquid–liquid microextraction for the extraction and analysis of ochratoxin A in dried fruit samples: Central composite design optimization
PublikacjaThis paper presents a new analytical procedure based on combination of homogeneous liquid–liquid extraction (HLLE) and vortex-assisted dispersive liquid–liquid microextraction (VA-DLLME) for the accurate and reliable determination of ochratoxin A (OTA) in dried fruit samples. To enable selective extraction of the OTA, six hydrophobic deep eutectic solvents (hDESs) were prepared and tested as extraction solvents. Optimization of...
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Process Control of Biogas Purification Using Electronic Nose
PublikacjaNowadays, biogas produced from landfills and wastewater treatment plants or lignocellulosic biomass is important sustainable and affordable source of energy. Impurities from biogas stream can cause a serious odor problem, especially for residents of areas immediately adjacent to production plants. Therefore, biogas pre-treatment is necessary to protect engines that convert biogas into energy and in order to increase the specific...
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Betaine and L-carnitine ester bromides: Synthesis and comparative study of their thermal behaviour and surface activity
PublikacjaSix esters of both betaine and L-carnitine bromides, featuring alkyl groups ranging from C8 to C18 in length, have been synthesized. The thermal behaviour of these twelve bio-based salts has been analyzed and compared by thermal gravimetric analysis and differential scanning calorimetry. The L-carnitine alkyl ester bromides melted below 100 C and can hence be considered ionic liquids (ILs) with full rights. Conversely, the betaine...
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Application of Aqueous Biphasic Systems Extraction in Various Biomolecules Separation and Purification: Advancements Brought by Quaternary Systems
PublikacjaAqueous biphasic systems (ABS) extraction is a simple, selective, efficient and easy to scale-up technology that, over the years, has attracted a considerable attention from the researcher community as an alternative methodology in downstream processing of a wide variety of biomolecules. This review summarizes and discusses the fundamental features of ABS, as well as its advantages and disadvantages, as a separation and purification...
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Management of Dark Fermentation Broth via Bio Refining and Photo Fermentation
PublikacjaLignocellulose and starch-based raw materials are often applied in the investigations regarding biohydrogen generation using dark fermentation. Management of the arising post-fermentation broth becomes a problem. The Authors proposed sequential processes, to improve the efficiency of both hydrogen generation and by-products management carried under model conditions. During the proposed procedure, the simple sugars remaining in...
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A Perspective on Missing Aspects in Ongoing Purification Research towards Melissa officinalis
PublikacjaMelissa officinalis L. is a medicinal plant used worldwide for ethno-medical purposes. Today, it is grown everywhere; while it is known to originate from Southern Europe, it is now found around the world, from North America to New Zealand. The biological properties of this medicinal plant are mainly related to its high content of phytochemical (bioactive) compounds, such as flavonoids, polyphenolic compounds, aldehydes, glycosides...
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Performance tuning of chitosan-based membranes by protonated 2-Pyrrolidone-5-carboxylic acid-sulfolane DES for effective water/ethanol separation by pervaporation
PublikacjaToday, the applicability of deep eutectic solvents (DES) in various fields, including membrane science and technology, is extensively investigated. In pioneering works, we have implemented different DES as a component of chitosan (CS)-based flat membranes for pervaporation (PV) separation. Herein, we present a new protonated (by sulphuric acid) 2-Pyrrolidone-5-carboxylic acid: sulfolane DES, as a green additive for its chemical...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Hybrid cross-linked chitosan/protonated-proline:glucose DES membranes with superior pervaporation performance for ethanol dehydration
PublikacjaThis work explores a protonated L-proline:glucose (molar ratio 5:1) deep eutectic solvent (DES) in fabricating biopolymer membranes utilizing chitosan (CS). Initially, the miscibility of CS and DES to prepare homogeneous dense blend membranes has been investigated. Different techniques, such as scanning electron microscopy, contact angle (CA), atomic force microscopy (AFM), Fourier transformed infrared spectroscopy (FTIR) and swelling...
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Investigating COVID-19 active pharmaceutical ingredients (APIs) degradation using Peroxydisulfate/FeMnOx binary metal oxide/Ultrasound System
PublikacjaDegradation of Favipiravir using a hybrid system of peroxydisulfate, FeMnOx binary metal oxide, and ultrasound irradiation was studied. A novel catalyst was synthesized with deep eutectic solvent (DES). The effects of DES type on catalytic performance was evaluated and the catalysts were characterized using XRD, SEM, BET, XPS, and EDS. DES-based catalysts exhibited higher efficiency due to structure change, surface area enhancement...
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Morphology control through the synthesis of metal-organic frameworks
PublikacjaDesignable morphology and predictable properties are the most challenging goals in material engineering. Features such as shape, size, porosity, agglomeration ratio significantly affect the final properties of metal- organic frameworks (MOFs) and can be regulated throughout synthesis parameters but require a deep under- standing of the mechanisms of MOFs formation. Herein, we systematically summarize the effects of the indi- vidual...
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Extraction with environmentally friendly solvents
PublikacjaThe ever-increasing demand for determining compounds at low concentration levels in complex matrices requires a preliminary step of analytes isolation/enrichment in order to employ a detection technique characterized by high sensitivity at low LOQ. Sample preparation is considered as crucial part of analytical procedures. Previously the parameter of “greenness” is as important as selectivity in order to avoid using harmful organic...
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Novel fast analytical method for indirect determination of MCPD fatty acid esters in edible oils and fats based on simultaneous extraction and derivatization
PublikacjaA novel method for indirect determination of MCPD esters levels in lipid samples has been developed. The method is based on combination of extraction and derivatisation in the same sample preparation step. It is achieved by the application of diethyl ether as extraction solvent for isolation of released from esterified forms analytes from water phase and dilution solvent for solid PBA – derivatisation agent. It is a noteworthy...
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Greener organic solvents in analytical chemistry
PublikacjaThe paper presents the most recent advances in analytical applications of greener organic solvents. Substitution of problematic solvents with more benign organic ones is much easier than shifting to technique applying alternative solvents, such as ionic liquids or supercritical fluids. In the area of liquid chromatography greener mobile phases, much attention is given to application ethanol or acetone instead of acetonitrile. Solvent-based...
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Monetary values estimates of solvents emissions
PublikacjaThe impact values for environmental emissions of 52 solvents are estimated and expressed in monetary units. The impact values of solvents present in the air are calculated on the basis of 13 impact indicators and for solvents present in water on additional 2 impact indicators. These impact values are weighted with the results obtained with multi-compartment distribution model, allowing to calculate the fraction of solvent emitted...
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Deep Learning
PublikacjaDeep 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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Sorption of Chlorinated Solvents on Pine and Oak sawdust
PublikacjaThe article presents assessment of pine and oak sawdusts as sorbents for removal of chlorinated solvents from water. Sawdusts as potential sorbents were characterized with elemental analysis and BET analyses. Sorption capacity was determined for both pine and oak sawdust towards 1,1,2-trichloroethane, tetrachloroethene and 1,1,1,2-tetrachloroethane. Pine sawdust was able to adsorb greater amounts of chlorinated solvents compared...
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Trends in the new generation of green solvents in extraction processes
PublikacjaAnalytical chemistry, like other scientific fields, has undergone a number of changes to make it more consistent with the concept of sustainable development. Among the various steps of chemical analysis, without a doubt, sample preparation is the bottleneck in regard to following a green protocol, especially in terms of solvent consumption. Therefore, many attempts have been made to improve the environmental friendliness of this...
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Neural networks and deep learning
PublikacjaIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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Experimental tests of reinforced concrete deep-beams
PublikacjaThe paper presents results of experimental research of the reinforced concrete deep beam with a spatial arrangement. Tested structural elements consist of the cantilever deep beam loaded on the height and transverse deep beam with hanging on it another one. The analysis includes crack morphology, effort of steel and load distribution. The article verified effectiveness of two different kind of reinforcement in both tested deep...
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Pre-selection and assessment of green organic solvents by clustering chemometric tools
PublikacjaThe study presents the result of the application of chemometric tools for selection of physicochemical parameters of solvents for predicting missing variables – bioconcentration factors, water-octanol and octanol-air partitioning constants. EPI Suite software was successfully applied to predict missing values for solvents commonly considered as “green”. Values for logBCF, logKOW and logKOA were modelled for 43 rather nonpolar solvents...
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On the relationship between the structural and volumetric properties of solvated metal ions in O-donor solvents using new structural data in amide solvents
PublikacjaThe structures of the N,N-dimethylformamide (dmf), N,N-dimethylacetamide (dma), and N,N-dimethylpropionamide (dmp) solvated strontium and barium ions have been determined in solution using large angle X-ray scattering and EXAFS spectroscopy. The strontium ion has a mean coordination number (CN) between 6.2 and 6.8, and the barium ion has a mean CN between 7.1 and 7.8 in these amide solvents. The non-integer numbers indicates that...
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EXPERIMENTAL AND THEORETICAL FLOW OF THE FORCES IN DEEP BEAMS WITH CANTILEVAR
PublikacjaThis article presents the results of experimental research carried out on deep beams with cantilever which was loaded throughout the depth. The main deep beam was directly simply supported on the one side. On the other side the deep beam was suspended in another deep member situated at right angles. All deep beams created a spatial arrangement. The paper is focused on the analysis of the cracks morphology and flow of the internal...
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Fuzzy Divisive Hierarchical Clustering of Solvents According to Their Experimentally and Theoretically Predicted Descriptors
PublikacjaThe present study describes a simple procedure to separate into patterns of similarity a large group of solvents, 259 in total, presented by 15 specific descriptors (experimentally found and theoretically predicted physicochemical parameters). Solvent data is usually characterized by its high variability, dierent molecular symmetry, and spatial orientation. Methods of chemometrics can usefully be used to extract and explore accurately...
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A Closed Bipolar Electrochemical Cell for the Interrogation of BDD Single Particles: Electrochemical Advanced Oxidation
PublikacjaA closed bipolar electrochemical cell containing two conductive boron-doped diamond (BDD) particles of size 250 – 350 m, produced by high-pressure high-temperature (HPHT) synthesis, has been used to demonstrate the applicability of single BDD particles for electrochemical oxidative degradation of the dye, methylene blue (MB). The cell is fabricated using stereolithography 3D printing and the BDD particles are located at either...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Precipitation and Transformation of Vaterite Calcium Carbonate in the Presence of Some Organic Solvents
PublikacjaIn 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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Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublikacjaSolubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...
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Expectation-Maximization Model for Substitution of Missing Values Characterizing Greenness of Organic Solvents
PublikacjaOrganic solvents are ubiquitous in chemical laboratories and the Green Chemistry trend forces their detailed assessments in terms of greenness. Unfortunately, some of them are not fully characterized, especially in terms of toxicological endpoints that are time consuming and expensive to be determined. Missing values in the datasets are serious obstacles, as they prevent the full greenness characterization of chemicals. A featured...
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New Screening Protocol for Effective Green Solvents Selection of Benzamide, Salicylamide and Ethenzamide
PublikacjaNew protocol for screening efficient and environmentally friendly solvents was proposed and experimentally verified. The guidance for solvent selection comes from computed solubility via COSMO-RS approach. Furthermore, solute-solvent affinities computed using advanced quantum chemistry level were used as a rationale for observed solvents ranking. The screening protocol pointed out that 4-formylomorpholine (4FM) is an attractive...
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Environmental risk- based ranking of solvents by the combination of multimedia model and multi-criteria decision analysis
PublikacjaA novel procedure for assessing the environmental risk related to solvents emissions has been developed. The assessment of risk is based on hazard and exposure detailed investigations. The potential exposure related to different environmental phases is calculated with basic multimedia model, that gives the percentage distribution of solvent in environmental compartments as a result. Specific hazards– toxicological, environmental...
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Searching for Solvents with an Increased Carbon Dioxide Solubility Using Multivariate Statistics
PublikacjaIonic liquids (ILs) are used in various fields of chemistry. One of them is CO2 capture, a process that is quite well described. The solubility of CO2 in ILs can be used as a model to investigate gas absorption processes. The aim is to find the relationships between the solubility of CO2 and other variables—physicochemical properties and parameters related to greenness. In this study, 12 variables are used to describe a dataset...
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Calculating the Partition Coefficients of Organic Solvents in Octanol/Water and Octanol/Air
PublikacjaPartition coefficients define how a solute is distributed between two immiscible phases at equilibrium. The experimental estimation of partition coefficients in a complex system can be an expensive, difficult, and time-consuming process. Here a computational strategy to predict the distributions of a set of solutes in two relevant phase equilibria is presented. The octanol/water and octanol/air partition coefficients are predicted...
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Discussion:Horizontal stress increase induced by deep vibratory compaction
PublikacjaDeep compaction control of granular material using the results of field tests. The analysis include the CPTU and DMT tests terformed before and after compaction works.
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Deep compaction control of sandy soils
PublikacjaVibroflotation, vibratory compaction, micro-blasting or heavy tamping are typical improvement methods for the cohesionless deposits of high thickness. The complex mechanism of deep soil compaction is related to void ratio decrease with grain rearrangements, lateral stress increase, prestressing effect of certain number of load cycles, water pressure dissipation, aging and other effects. Calibration chamber based interpretation...
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SORPTION OF SELECTED CHLORINATED SOLVENTS ON PLANT DEBRIS COLLECTED IN A CITY PARK
PublikacjaDebris from deciduous trees in the form of park green waste was investigated as a potential biosorbent for the removal of chlorinated solvents from water. The sorption properties of beech leaves and cupules, oak leaves and acorns, birch leaves and lime leaves (all tree species common for a moderate climate) in a non-modified form were investigated with regard to the removal of perchloroethylene, 1,1,2-trichloroethane and 1,1,1,2-tetrachlorothane....
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Breast MRI segmentation by deep learning: key gaps and challenges
PublikacjaBreast 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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Thermodynamic Characteristics of Phenacetin in Solid State and Saturated Solutions in Several Neat and Binary Solvents
PublikacjaThe thermodynamic properties of phenacetin in solid state and in saturated conditions in neat and binary solvents were characterized based on differential scanning calorimetry and spectroscopic solubility measurements. The temperature-related heat capacity values measured for both the solid and melt states were provided and used for precise determination of the values for ideal solubility, fusion thermodynamic functions, and...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep 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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Exploring the Solubility Limits of Edaravone in Neat Solvents and Binary Mixtures: Experimental and Machine Learning Study
PublikacjaThis study explores the edaravone solubility space encompassing both neat and binary dissolution media. Efforts were made to reveal the inherent concentration limits of common pure and mixed solvents. For this purpose, the published solubility data of the title drug were scrupulously inspected and cured, which made the dataset consistent and coherent. However, the lack of some important types of solvents in the collection called...
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The influence of reinforcement on load carrying capacity and cracking of the reinforced concrete deep beam joint
PublikacjaThe paper presents the results of experimental research of the spatial reinforced concrete deep beam systems orthogonally reinforced and with additional inclined bars. Joint of the deep beams in this research was composed of the longitudinal deep beam with a cantilever suspended at the transversal deep beam. The cantilever deep beam was loaded throughout the depth and the transversal deep beam was loaded at the mid-span by longitudinal...
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Podand Solvents for Organic Reactions
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Studies of Silicon Podand Solvents
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Chlorinated solvents in a petrochemical wastewater treatment plant: Anassessment of their removal using self-organising maps
PublikacjaThe self-organising map approach was used to assess the efficiency of chlorinated solvent removal frompetrochemical wastewater in a refinery wastewater treatment plant. Chlorinated solvents and inorganicanions (11 variables) were determined in 72 wastewater samples, collected from three different purificationstreams. The classification of variables identified technical solvents, brine from oil desalting andrunoff sulphates as pollution...
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Deep learning for recommending subscription-limited documents
PublikacjaDocuments recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with...
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Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
PublikacjaDapsone is an effective antibacterial drug used to treat a variety of conditions. However, the aqueous solubility of this drug is limited, as is its permeability. This study expands the available solubility data pool for dapsone by measuring its solubility in several pure organic solvents: N-methyl-2-pyrrolidone (CAS: 872-50-4), dimethyl sulfoxide (CAS: 67-68-5), 4-formylmorpholine (CAS: 4394-85-8), tetraethylene pentamine (CAS:...
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Explainable AI for Inspecting Adversarial Attacks on Deep Neural Networks
PublikacjaDeep Neural Networks (DNN) are state of the art algorithms for image classification. Although significant achievements and perspectives, deep neural networks and accompanying learning algorithms have some important challenges to tackle. However, it appears that it is relatively easy to attack and fool with well-designed input samples called adversarial examples. Adversarial perturba-tions are unnoticeable for humans. Such attacks...
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Analytical procedures for quality control of pharmaceuticals in terms of residual solvents content: Challenges and recent developments
PublikacjaResidual solvents play an important role in the synthesis of drugs and in product formulations. In addition, they pose a serious problem, that is toxicity, as many of them exhibit toxic or environmentally hazardous properties. Therefore, constant monitoring of quality control is needed. In this study, we present an overview of regulatory and general methods described by various pharmacopoeias. Then, the most commonly used methodologies...
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Training of Deep Learning Models Using Synthetic Datasets
PublikacjaIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublikacjaThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Hydration of aprotic donor solvents studied by means of FTIR spectroscopy
PublikacjaThe paper attempts to explain the mutual influence of nonpolar and electron-donor groups on solute hydration,the problem of big importance for biological aqueous systems. Aprotic organic solvents have been used asmodel solutes, differing in electron-donating power. Hydration of acetonitrile, acetone, 2-butanone, andtriethylamine has been studied by HDO and (partially) H2O spectra. The quantitative version of...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Data augmentation for improving deep learning in image classification problem
PublikacjaThese 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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The impact of the AC922 Architecture on Performance of Deep Neural Network Training
PublikacjaPractical deep learning applications require more and more computing power. New computing architectures emerge, specifically designed for the artificial intelligence applications, including the IBM Power System AC922. In this paper we confront an AC922 (8335-GTG) server equipped with 4 NVIDIA Volta V100 GPUs with selected deep neural network training applications, including four convolutional and one recurrent model. We report...
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Classifying Emotions in Film Music - A Deep Learning Approach
PublikacjaThe paper presents an application for automatically classifying emotions in film music. A model of emotions is proposed, which is also associated with colors. The model created has nine emotional states, to which colors are assigned according to the color theory in film. Subjective tests are carried out to check the correctness of the assumptions behind the adopted emotion model. For that purpose, a statistical analysis of the...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublikacjaIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Determination of chlorinated solvents in industrial water and wastewater by DAI- GC-ECD
PublikacjaA very simple and quick analytical method, basedon direct aqueous injection, for determination of halogenatedsolvents in refinery water and wastewater, is described.There is a need to determine halogenated solvents in refinerywater streams, because they may originate from severalprocesses. There is also a need to develop methods enablingVOX to be determined in samples containing oil fractions.The method described enables simultaneous...
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Outlier detection method by using deep neural networks
PublikacjaDetecting outliers in the data set is quite important for building effective predictive models. Consistent prediction can not be made through models created with data sets containing outliers, or robust models can not be created. In such cases, it may be possible to exclude observations that are determined to be outlier from the data set, or to assign less weight to these points of observation than to other points of observation....
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Deep learning techniques for biometric security: A systematic review of presentation attack detection systems
PublikacjaBiometric technology, including finger vein, fingerprint, iris, and face recognition, is widely used to enhance security in various devices. In the past decade, significant progress has been made in improving biometric sys- tems, thanks to advancements in deep convolutional neural networks (DCNN) and computer vision (CV), along with large-scale training datasets. However, these systems have become targets of various attacks, with...
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Deep Learning-Based LOS and NLOS Identification in Wireless Body Area Networks
PublikacjaIn this article, the usage of deep learning (DL) in ultra-wideband (UWB) Wireless Body Area Networks (WBANs) is presented. The developed approach, using channel impulse response, allows higher efficiency in identifying the direct visibility conditions between nodes in off-body communication with comparison to the methods described in the literature. The effectiveness of the proposed deep feedforward neural network was checked on...
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Force transfer and stress distribution in short cantilever deep beams loaded throughout the depth with a various reinforcement
PublikacjaDeep beams used as the main reinforced concrete structural elements which taking over the load and stiffening construction are often found in high-rise buildings. The architecture of these buildings is sometimes sophisticated and varied, arouse the admiration of the majority of recipients, and thus causing an engineering challenge to correctly design the structural system and force transfer. In such structures is important to shape...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublikacjaThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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SYNTHESIZING MEDICAL TERMS – QUALITY AND NATURALNESS OF THE DEEP TEXT-TO-SPEECH ALGORITHM
PublikacjaThe main purpose of this study is to develop a deep text-to-speech (TTS) algorithm designated for an embedded system device. First, a critical literature review of state-of-the-art speech synthesis deep models is provided. The algorithm implementation covers both hardware and algorithmic solutions. The algorithm is designed for use with the Raspberry Pi 4 board. 80 synthesized sentences were prepared based on medical and everyday...
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Deep neural network architecture search using network morphism
PublikacjaThe paper presents the results of the research on neural architecture search (NAS) algorithm. We utilized the hill climbing algorithm to search for well-performing structures of deep convolutional neural network. Moreover, we used the function preserving transformations which enabled the effective operation of the algorithm in a short period of time. The network obtained with the advantage of NAS was validated on skin lesion classification...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Deep learning based thermal image segmentation for laboratory animals tracking
PublikacjaAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
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Decision making process using deep learning
PublikacjaEndüstri 4.0, dördüncü endüstri devrimi veya Endüstriyel Nesnelerin İnterneti (IIoT) olarak adlandırılan sanayi akımı, işletmelere, daha verimli, daha büyük bir esneklikle, daha güvenli ve daha çevre dostu bir şekilde üretim yapma imkanı sunmaktadır. Nesnelerin İnterneti ile bağlantılı yeni teknoloji ve hizmetler birçok endüstriyel uygulamada devrim niteliği taşımaktadır. Fabrikalardaki otomasyon, tahminleyici bakım (PdM – Predictive...
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Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublikacjaIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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The impact of the shape of deep drilled well screen openings on the filtration process in full saturation conditions
PublikacjaThe authors propose a supplementary method of modelling seepage flow around the deep drilled well screen. The study applies 3D numerical modelling (FEM) in order to provide an in-depth analysis of the seepage process. The analysis of filtration parameters (flow distribution q(x,t) and pressure distribution p) was conducted using the ZSoil.PC software system. The analysis indicates that the shape of perforation is of secondary importance...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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Ionic liquids - greener solvents or environmental threat?
PublikacjaZe względu na niemierzalnie niską prężność par ciecze jonowe były uważane za 'zielone rozpuszczalniki'. Ich zastosowanie w technologiach (bio)chemicznych przynosi korzyści nie tylko ekologiczne ale również ekonomiczne. Niemniej jednak zanieczyszczenie środowiska poprzez przedostanie się cieczy jonowych do gleb i wód gruntowych wraz ze ściekami/odciekami przemysłowymi lub w wyniku przypadkowych rozlewów stanowi realne zagrożenie....
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The potential anti-tumor activity of neoteric solvents
PublikacjaCiecze jonowe stały się obiektem zainteresowania naukowców. Znajdują one coraz to szersze zastosowanie. Dlatego też ważne jest określenie ich właściwości Eko-toksycznych. Aktywność anty-nowotworowa i cytotoksyczna cieczy jonowych stała się zatem ważnym aspektem badań. Artykuł podsumowuje najnowsze wyniki badań nad cytotoksycznością tych rozpuszczalników
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Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning
PublikacjaFollowing the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides...
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Evaluation of Facial Pulse Signals Using Deep Neural Net Models
PublikacjaThe reliable measurement of the pulse rate using remote photoplethysmography (PPG) is very important for many medical applications. In this paper we present how deep neural networks (DNNs) models can be used in the problem of PPG signal classification and pulse rate estimation. In particular, we show that the DNN-based classification results correspond to parameters describing the PPG signals (e.g. peak energy in the frequency...
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Tool Wear Monitoring Using Improved Dragonfly Optimization Algorithm and Deep Belief Network
PublikacjaIn recent decades, tool wear monitoring has played a crucial role in the improvement of industrial production quality and efficiency. In the machining process, it is important to predict both tool cost and life, and to reduce the equipment downtime. The conventional methods need enormous quantities of human resources and expert skills to achieve precise tool wear information. To automatically identify the tool wear types, deep...
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BIG DATA SIGNIFICANCE IN REMOTE MEDICAL DIAGNOSTICS BASED ON DEEP LEARNING TECHNIQUES
PublikacjaIn this paper we discuss the evaluation of neural networks in accordance with medical image classification and analysis. We also summarize the existing databases with images which could be used for training deep models that can be later utilized in remote home-based health care systems. In particular, we propose methods for remote video-based estimation of patient vital signs and other health-related parameters. Additionally, potential...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Analysis of 2D Feature Spaces for Deep Learning-based Speech Recognition
Publikacjaconvolutional neural network (CNN) which is a class of deep, feed-forward artificial neural network. We decided to analyze audio signal feature maps, namely spectrograms, linear and Mel-scale cepstrograms, and chromagrams. The choice was made upon the fact that CNN performs well in 2D data-oriented processing contexts. Feature maps were employed in the Lithuanian word recognition task. The spectral analysis led to the highest word...
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Deep neural networks approach to skin lesions classification — A comparative analysis
PublikacjaThe paper presents the results of research on the use of Deep Neural Networks (DNN) for automatic classification of the skin lesions. The authors have focused on the most effective kind of DNNs for image processing, namely Convolutional Neural Networks (CNN). In particular, three kinds of CNN were analyzed: VGG19, Residual Networks (ResNet) and the hybrid of VGG19 CNN with the Support Vector Machine (SVM). The research was carried...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublikacjaData from a physical world is sampled by sensor networks, and then streams of Big Data are sent to cloud hosts to support decision making by deep learning software. In a smart city, some tasks may be assigned to smart devices of the Internet of Things for performing edge computing. Besides, a part of workload of calculations can be transferred to the cloud hosts. This paper proposes benchmarks for division tasks between an edge...
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The structure of Al-Cu and Al-Si eutectic melts
PublikacjaStrukturę ciekłych stopów eutektycznych Al_{83}Cu_{17} i Al_{88}Si_{12} zbadano metodami dyfrakcyjnymi i RMC. Przeanalizowano uzyskane całkowite i cząstkowe funkcje korelacyjne i parametry strukturalne.
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Deep slot effect in the squirrel-cage induction motors with scalar (V/F) control
PublikacjaQualitative characteristics of the electrical drive considerably depend on identification accuracy of math model parameters. In particular, it is depend on detection accuracy of stator active resistance r1 that is used in calculation of flux linkages, rotary speed in sensorless control systems. Paper provides analysis of influence of stator deep slot effect to stator active resistance value
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Chromatographic lipophilicity determination using large volume injections of the solvents non-miscible with the mobile phase
PublikacjaA new perspective in the lipophilicity evaluation through RP-HPLC is permitted by analysis of the retentionfactor (k) obtained by injecting large volumes of test samples prepared in solvents immiscible withmobile phase. The experiment is carried out on representative groups of compounds with increasedtoxicity (mycotoxins and alkaloids) and amines with important biological activity (naturally occurringmonoamine compounds and related...
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Data, Information, Knowledge, Wisdom Pyramid Concept Revisited in the Context of Deep Learning
PublikacjaIn this paper, the data, information, knowledge, and wisdom (DIKW) pyramid is revisited in the context of deep learning applied to machine learningbased audio signal processing. A discussion on the DIKW schema is carried out, resulting in a proposal that may supplement the original concept. Parallels between DIWK pertaining to audio processing are presented based on examples of the case studies performed by the author and her collaborators....
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Deep Learning 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...