Search results for: deepfm
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Force transfer and stress distribution in short cantilever deep beams loaded throughout the depth with a various reinforcement
PublicationDeep 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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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Microbial Diversity in Deep-Subsurface Hot Brines of Northwest Poland: from Community Structure to Isolate Characteristics
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Deep eutectic solvents – based green absorbents for effective volatile organochlorine compounds removal from biogas
PublicationVolatile organochlorine compounds (VOXs) presented in biogas can cause many technological and environmental problems. During the combustion of biogas containing VOXs, the corrosion of installation, as well as the formation of toxic by-products (polyhalogenated dioxins and furans) and further emission to the atmosphere, may occur. Therefore, in this study, a new procedure based on physical absorption was developed. In order to meet...
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Fast Fading Influence on the Deep Learning-Based LOS and NLOS Identificationin Wireless Body Area Networks
PublicationIn the article, the fast fading influence on the proposed DL (Deep Learning) approach for LOS (Line-of-Sight) and NLOS (Non-Line-of-Sight) conditions identification in Wireless Body Area Networks is investigated. The research was conducted on the basis of the off-body communication measurements using the developed mobile measurement stand, in an indoor environment for both static and dynamic scenarios. The measurements involved...
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Big Data from Sensor Network via Internet of Things to Edge Deep Learning for Smart City
PublicationData 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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Towards azeotropic MeOH-MTBE separation using pervaporation chitosan-based deep eutectic solvent membranes
PublicationDeep eutectic solvents (DESs) are a new class of solvents that can offset some of the major drawbacks of common solvents and ionic liquids. When dealing with the preparation of dense membranes, the use of DESs is still challenging due to their low compatibility with the polymer phase. In this research, a novel L-proline:sulfolane (molar ratio 1:2) DES was synthesized and used for the preparation of more sustainable bio-based membranes...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe 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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Quenching of bright and dark excitons via deep states in the presence of SRH recombination in 2D monolayer materials
PublicationTwo-dimensional (2D) monolayer materials are interesting systems due to an existence of optically non-active dark excitonic states. In this work, we formulate a theoretical model of an excitonic Auger process which can occur together with the trap-assisted recombination in such 2D structures. The interactions of intravalley excitons (bright and spin-dark ones) and intervalley excitons (momentum-dark ones) with deep states located...
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Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublicationSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
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A natural deep eutectic solvent - protonated L-proline-xylitol - based stationary phase for gas chromatography
PublicationThe paper presents a new kind of stationary phase for gas chromatography based on deep eutectic solvents (DES) in the form of a mixture of L-proline (protonated with hydrochloric acid) as a hydrogen bond acceptor (HBA) and xylitol as a hydrogen bond donor (HBD) in a molar ratio of HBA:HBD 5:1. DES immobilized on a silanized chromatographic support was tested by gas chromatography (GC) in order to determine its resolving power for...
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Techno‐economic evaluation of a natural deep eutectic solvent‐based biorefinery: Exploring different design scenarios
PublicationThis paper presents a comprehensive techno‐economic evaluation of an integrated natural deep eutectic solvent (NADES)‐based biorefinery – a 1 ton day−1 capacity design plant. The key parameters include payback period, net present value (NPV), and internal rate of return (IRR). These were compared with the parameters of conventional biorefineries. The ‘n th plant’ results clearly revealed that the single product‐based biorefinery...
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Theoretical and Economic Evaluation of Low-Cost Deep Eutectic Solvents for Effective Biogas Upgrading to Bio-Methane
PublicationThis paper presents the theoretical screening of 23 low-cost deep eutectic solvents (DESs) as absorbents for effective removal of the main impurities from biogas streams using a conductor-like screening model for real solvents (COSMO-RS). Based on thermodynamic parameters, i.e., the activity coefficient, excess enthalpy, and Henry’s constant, two DESs composed of choline chloride: urea in a 1:2 molar ratio (ChCl:U 1:2), and choline...
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Deep eutectic solvents based assay for extraction and determination of zinc in fish and eel samples using FAAS
PublicationA new assay based on effective (high recovery) extraction by means of deep eutectic solvents (DESs) was developed for ppb level determination of zinc in fishes and eel samples. Choline chloride and Phenol in a 1:2 M ratio was selected as optimal DES-based extraction solvent. 8-Hydroxy quinoline was used as a chelating agent for zinc ions. The optimized conditions were found at pH value of 8, ligand concentration of 10 mg/L, THF...
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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
PublicationThe 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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Effect of choline chloride based natural deep eutectic solvents on aqueous solubility and thermodynamic properties of acetaminophen
PublicationIn this work, natural deep eutectic solvents (NADESs) containing choline chloride as hydrogen bond acceptor and 1,2-propanediol, malic acid and tartaric acid as hydrogen bond donors have been synthesized and applied to enhance the aqueous solubility of model sparingly water-soluble drug – acetaminophen. The results indicate that the greatest impact on the solubility of acetaminophen have deep eutectic solvents based on 1,2-propanediol...
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Employing Subjective Tests and Deep Learning for Discovering the Relationship between Personality Types and Preferred Music Genres
PublicationThe purpose of this research is two-fold: (a) to explore the relationship between the listeners’ personality trait, i.e., extraverts and introverts and their preferred music genres, and (b) to predict the personality trait of potential listeners on the basis of a musical excerpt by employing several classification algorithms. We assume that this may help match songs according to the listener’s personality in social music networks....
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Variable Data Structures and Customized Deep Learning Surrogates for Computationally Efficient and Reliable Characterization of Buried Objects
PublicationIn this study, in order to characterize the buried object via deep-learning-based surrogate modeling approach, 3-D full-wave electromagnetic simulations of a GPR model has been used. The task is to predict simultaneously and independent of each characteristic parameters of a buried object of several radii at different positions (depth and lateral position) in various dispersive subsurface media. This study has analyzed variable...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep 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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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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A Novel Spatio–Temporal Deep Learning Vehicle Turns Detection Scheme Using GPS-Only Data
PublicationWhether the computer is driving your car or you are, advanced driver assistance systems (ADAS) come into play on all levels, from weather monitoring to safety. These modern-day ADASs use various assisting tools for drivers to keep the journey safe; these sophisticated tools provide early signals of numerous events, such as road conditions, emerging traffic scenarios, and weather warnings. Many urban applications, such as car-sharing...
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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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Towards the 4th industrial revolution: networks, virtuality, experience based collective computational intelligence, and deep learning
PublicationQuo vadis, Intelligent Enterprise? Where are you going? The authors of this paper aim at providing some answers to this fascinating question addressing emerging challenges related to the concept of semantically enhanced knowledge-based cyber-physical systems – the fourth industrial revolution named Industry 4.0.
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Grzegorz Boczkaj dr hab. inż.
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Deep submarine groundwater discharge indicated by pore water chloride anomalies in the Gulf of Gdańsk, southern Baltic Sea
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New Simple and Robust Method for Determination of Polarity of Deep Eutectic Solvents (DESs) by Means of Contact Angle Measurement
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Deep analysis of Loop L1 HVRs1-4 region of the hexon gene of adenovirus field strains isolated in Poland
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Association of LBX1 Gene Methylation Level with Disease Severity in Patients with Idiopathic Scoliosis: Study on Deep Paravertebral Muscles
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Pore water alkalinity below the permanent halocline in the Gdańsk Deep (Baltic Sea) - Concentration variability and benthic fluxes
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Deep Eutectic Solvent Stir Bar Sorptive Extraction: A Rapid Microextraction Technique for the Determination of Vitamin D3 by Spectrophotometry
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Glycerol and Natural Deep Eutectic Solvents Extraction for Preparation of Luteolin-Rich Jasione montana Extracts with Cosmeceutical Activity
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Latest Insights on Novel Deep Eutectic Solvents (DES) for Sustainable Extraction of Phenolic Compounds from Natural Sources
PublicationPhenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability....
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Deep eutectic solvent based method for analysis of Niclosamide in pharmaceutical and wastewater samples – A green analytical chemistry approach
PublicationThe paper presents a simple, but very effective and sensitive spectrophotometric method for trace analysis of Niclosamide based on liquid–liquid microextraction using deep eutectic solvents (DESs) prior to its quantification. Here, different DES systems, such as Choline chloride (ChCl) + Urea, ChCl + Citric acid, ChCl + Ethylene glycol and ChCl + Phenol, were synthesized and evaluated at different molar ratios, selecting ChCl + Phenol...
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GPU Power Capping for Energy-Performance Trade-Offs in Training of Deep Convolutional Neural Networks for Image Recognition
PublicationIn 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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New Simple and Robust Method for Determination of Polarity of Deep Eutectic Solvents (DESs) by Means of Contact Angle Measurement
PublicationThe paper presents a new method for evaluating the polarity and hydrophobicity of deep eutectic solvents (DESs) based on the measurement of the DES contact angle on glass. DESs consisting of benzoic acid derivatives and quaternary ammonium chlorides–tetrabutylammonium chloride (TBAC) and benzyldimethylhexadecylammonium chloride (16-BAC)—in selected molar ratios were chosen for the study. To investigate the DESs polarity, an optical...
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Extractive detoxification of feedstocks for the production of biofuels using new hydrophobic deep eutectic solvents – Experimental and theoretical studies
PublicationThe paper presents a synthesis of novel hydrophobic deep eutectic solvents (DESs) composed of natural components, which were used for removal of furfural (FF) and 5-hydroxymethylfurfural (HMF) from lignocellulosic hydrolysates. The main physicochemical properties of DESs were determined, followed by explanation of the DES formation mechanism, using 1H NMR, 13C NMR and FT-IR analysis and density functional theory (DFT). The most...
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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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Deep eutectic solvent-based shaking-assisted extraction for determination of bioactive compounds from Norway spruce roots
PublicationPolyphenolic compounds play an essential role in plant growth, reproduction, and defense mechanisms against pathogens and environmental stresses. Extracting these compounds is the initial step in assessing phytochemical changes, where the choice of extraction method significantly influences the extracted analytes. However, due to environmental factors, analyzing numerous samples is necessary for statistically significant results,...
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Application of deep eutectic solvents in analytical sample pretreatment (update 2017–2022). Part A: Liquid phase microextraction
PublicationSustainable development in all branches of human activity has become an unequivocal necessity in the last two decades, and green chemistry goes hand in hand with it. Various ways have been proposed in analytical chemistry to meet the current requirements of green chemistry. One such approach is the research of new reagents and solvents for analytical purposes. Deep eutectic solvents (DESs) began being investigated and used in analytical...
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Effect of temperature and composition on physical properties of deep eutectic solvents based on 2-(methylamino)ethanol – measurement and prediction
PublicationNovel deep eutectic solvents were synthesized using 2-(methylamino)ethanol as hydrogen bond donor with tetrabutylammonium bromide or tetrabutylammonium chloride or tetraethylammonium chloride as hydrogen bond acceptors. Mixtures were prepared at different molar ratios of 1:6, 1:8 and 1:10 salt to alkanolamine and then Fourier Transform Infrared Spectroscopy measurements were performed to confirm hydrogen bonds interactions between...
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Olgun Aydin dr
PeopleOlgun Aydin finished his PhD by publishing a thesis about Deep Neural Networks. He works as a Principal Machine Learning Engineer in Nike, and works as Assistant Professor in Gdansk University of Technology in Poland. Dr. Aydin is part of editorial board of "Journal of Artificial Intelligence and Data Science" Dr. Aydin served as Vice-Chairman of Why R? Foundation and is member of Polish Artificial Intelligence Society. Olgun is...
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Solar radiation (PAR, UV-B and UV-A) reaching the sea surface - Gdańsk Deep (2001-2005)
Open Research DataSolar radiation reaching the sea surface was measured in spring (2001, 2003, 2005) and autumn (2002, 2004). For measurements of the photosynthetic active radiation - PAR (400-700 nm), the Ejkelkamp SKP 210 / I 0896 13595 sensor was used, the UV-B radiation (280-315 nm) was measured with the Ejkelkamp SKU 430 0497 14854 sensor, while UV-A (315- 380 nm)...
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On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry
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Proline, glutamic acid, and leucine rich protein 1 (PELP1) expression in deep paravertebral muscles in idiopathic scoliosis girls
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Novel binary mixtures of alkanolamine based deep eutectic solvents with water - thermodynamic calculation and correlation of crucial physicochemical properties
PublicationThis paper demonstrates the assessment of physicochemical and thermodynamic properties of aqueous solutions of novel deep eutectic solvent (DES) built of tetrabutylammonium chloride and 3-amino-1-propanol or tetrabutylammonium bromide and 3-amino-1-propanol or 2-(methylamino)ethanol or 2-(butylamino)ethanol. Densities, speeds of sound, refractive indices, and viscosities for both pure and aqueous mixtures of DES were investigated...
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STUDY IN MECHANICAL FAULT ELEMENT THERMOGRAPHY THROUGH THE MACHINE: The case of deep groove ball bearings of a career without screen.
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Deep insight into the pore size distribution of N-doped porous carbon materials on electrochemical energy storage and CO2 sorption
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Predicting Compressive Strength of Cement-Stabilized Rammed Earth Based on SEM Images Using Computer Vision and Deep Learning
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High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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