Wyniki wyszukiwania dla: RDF DATASET PROFILING
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Fresh properties of concrete mixes M0-M100 concrete mixes
Dane BadawczeDataset of fresh properties of concretes containing different amount of magnetite aggregate (M0-M100) mixes.*. ODS - open-source spreadsheet file file consists results of:
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Complex modulus of Cement Bitumen Treated Material Mixture C3E4 field mixed/laboratory compacted (7-365 days of curing at 20C)
Dane BadawczeDataset presents data of complex modulus determined for cold recycled mixture – cement bitumen treated material mixture with following binding agents: 3% cement, 4% emulsion (C3E4). Mixture was designed according to Polish requirements for the base course of pavement. Mixture was mixed in the field conditions and later compacted in laboratory. Mixture...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublikacjaThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Transfer learning in imagined speech EEG-based BCIs
PublikacjaThe Brain–Computer Interfaces (BCI) based on electroencephalograms (EEG) are systems which aim is to provide a communication channel to any person with a computer, initially it was proposed to aid people with disabilities, but actually wider applications have been proposed. These devices allow to send messages or to control devices using the brain signals. There are different neuro-paradigms which evoke brain signals of interest...
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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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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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Systematic Literature Review for Emotion Recognition from EEG Signals
PublikacjaResearchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...
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Independent dynamics of low, intermediate, and high frequency spectral intracranial EEG activities during human memory formation
PublikacjaA wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various frequency ranges are coordinated across the space of the human cortex and time of memory processing is inconclusive. They can either be coordinated together across the frequency spectrum at the same cortical site and time or induced independently in particular bands. We used a large dataset of human intracranial...
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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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CNN-CLFFA: Support Mobile Edge Computing in Transportation Cyber Physical System
PublikacjaIn the present scenario, the transportation Cyber Physical System (CPS) improves the reliability and efficiency of the transportation systems by enhancing the interactions between the physical and cyber systems. With the provision of better storage ability and enhanced computing, cloud computing extends transportation CPS in Mobile Edge Computing (MEC). By inspecting the existing literatures, the cloud computing cannot fulfill...
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Ultrasonic wave propagation and digital image correlation measurements of steel bars under 3-point bending
Dane BadawczeThe DataSet contains the results of the mechanical behaviour of a bar under a 3-point bending test. The bar was made of steel and had a cross-section of 5.96 × 5.96 mm2 and a length of 200 mm. The three-point bending test was performed using a Zwick/Roell Z10 universal testing machine (UTM), with a distance between supports of 12 cm. The parameters...
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The complete lists of 1D reversible number-conserving cellular automata with radius one of up to 7 states
Dane BadawczeThis dataset contains complete lists of all one-dimensional reversible number-conserving k-ary cellular automata with radius one of up to 7 states, i.e. with state sets {0,1}, {0,1,2}, {0,1,2,3}, {0,1,2,3,4}, {0,1,2,3,4,5} and {0,1,2,3,4,5,6}.
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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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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Super-resolved Thermal Imagery for High-accuracy Facial Areas Detection and Analysis
PublikacjaIn this study, we evaluate various Convolutional Neural Networks based Super-Resolution (SR) models to improve facial areas detection in thermal images. In particular, we analyze the influence of selected spatiotemporal properties of thermal image sequences on detection accuracy. For this purpose, a thermal face database was acquired for 40 volunteers. Contrary to most of existing thermal databases of faces, we publish our dataset...
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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublikacjaOne of the current popular methods of generating word representations is an approach based on the analysis of large document collections with neural networks. It creates so-called word-embeddings that attempt to learn relationships between words and encode this information in the form of a low-dimensional vector. The goal of this paper is to examine the differences between the most popular embedding models and the typical bag-of-words...
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ELECTRICAL CONDUCTIVITY AND pH IN SURFACE WATER AS TOOL FOR IDENTIFICATION OF CHEMICAL DIVERSITY
PublikacjaIn the present study, the creeks and lakes located at the western shore of Admiralty Bay were analysed. The impact of various sources of water supply was considered, based on the parameters of temperature, pH and specific electrolytic conductivity (SEC25). All measurements were conducted during a field campaign in January-February 2017. A multivariate dataset was also created and a biplot of SEC25 and pH of the investigated waters...
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Emissions and toxic units of solvent, monomer and additive residues released to gaseous phase from latex balloons
PublikacjaThis study describes the VOCs emissions from commercially available latex balloons. Nine compounds are determined to be emitted from 13 types of balloons of different colors and imprints in 30 and 60°C. The average values of total volatile organic compounds (TVOCs) emitted from studied samples ranged from 0.054 up to 7.18 μg∙g-1 and from 0.27 up to 36.13 μg∙g-1 for 30oC and 60oC, respectively. The dataset is treated with principal...
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Dependent self-employed individuals: are they different from paid employees?
PublikacjaThis study focuses on dependent self-employment, which covers a situation where a person works for the same employer as a typical worker while on a self-employment contractual basis, i.e., without a traditional employment contract and without certain rights granted to "regular" employees. The research exploits the individual-level dataset of 35 European countries extracted from the 2017 edition of the European Labour Force Survey...
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Impact of optimization of ALS point cloud on classification
PublikacjaAirborne laser scanning (ALS) is one of the LIDAR technologies (Light Detection and Ranging). It provides information about the terrain in form of a point cloud. During measurement is acquired: spatial data (object’s coordinates X, Y, Z) and collateral data such as intensity of reflected signal. The obtained point cloud is typically applied for generating a digital terrain model (DTM) and a digital surface model (DSM). For DTM...
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Detecting type of hearing loss with different AI classification methods: a performance review
PublikacjaHearing is one of the most crucial senses for all humans. It allows people to hear and connect with the environment, the people they can meet and the knowledge they need to live their lives to the fullest. Hearing loss can have a detrimental impact on a person's quality of life in a variety of ways, ranging from fewer educational and job opportunities due to impaired communication to social withdrawal in severe situations. Early...
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Diurnal variability of atmospheric water vapour, precipitation and cloud top temperature across the global tropics derived from satellite observations and GNSS technique
PublikacjaThe diurnal cycle of convection plays an important role in clouds and water vapour distribution across the global tropics. In this study, we utilize integrated moisture derived from the global navigation satellite system (GNSS), satellite precipitation estimates from TRMM and merged infrared dataset to investigate links between variability in tropospheric moisture, clouds development and precipitation at a diurnal time scale. Over...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Rediscovering Automatic Detection of Stuttering and Its Subclasses through Machine Learning—The Impact of Changing Deep Model Architecture and Amount of Data in the Training Set
PublikacjaThis work deals with automatically detecting stuttering and its subclasses. An effective classification of stuttering along with its subclasses could find wide application in determining the severity of stuttering by speech therapists, preliminary patient diagnosis, and enabling communication with the previously mentioned voice assistants. The first part of this work provides an overview of examples of classical and deep learning...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublikacjaThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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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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Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
PublikacjaEven in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublikacjaThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Interrelations between Travel Patterns and Urban Spatial Structure of the Largest Russian Cities
PublikacjaThe study presented within this dissertation involves the analysis of the relationship between urban spatial structure and travel patterns in the largest Russian cities. It is an empirical investigation of how the spatial structure, formed during the Soviet and post-Soviet periods, affects the travel patterns in the largest cities of contemporary Russia. It aims to determine what measures, both urban structure and transportation...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublikacjaLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublikacjaA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublikacjaData reusability is an important feature of current research, just in every field of science. Modern research in Affective Computing, often rely on datasets containing experiments-originated data such as biosignals, video clips, or images. Moreover, conducting experiments with a vast number of participants to build datasets for Affective Computing research is time-consuming and expensive. Therefore, it is extremely important to...
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Platelet RNA Sequencing Data Through the Lens of Machine Learning
PublikacjaLiquid biopsies offer minimally invasive diagnosis and monitoring of cancer disease. This biosource is often analyzed using sequencing, which generates highly complex data that can be used using machine learning tools. Nevertheless, validating the clinical applications of such methods is challenging. It requires: (a) using data from many patients; (b) verifying potential bias concerning sample collection; and (c) adding interpretability...
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Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublikacjaOpen government data (OGD) is seen as a political and socio-economic phenomenon that promises to promote civic engagement and stimulate public sector innovations in various areas of public life. To bring the expected benefits, data must be reused and transformed into value-added products or services. This, in turn, sets another precondition for data that are expected to not only be available and comply with open data principles,...
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublikacjaThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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Fusion-based Representation Learning Model for Multimode User-generated Social Network Content
PublikacjaAs mobile networks and APPs are developed, user-generated content (UGC), which includes multi-source heterogeneous data like user reviews, tags, scores, images, and videos, has become an essential basis for improving the quality of personalized services. Due to the multi-source heterogeneous nature of the data, big data fusion offers both promise and drawbacks. With the rise of mobile networks and applications, UGC, which includes...
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The luminescence study of CsPbI3 nanoparticles embedded in Cs4PbI6 crystals.
Dane BadawczeCs4PbI6, as a rarely investigated member of the Cs4PbX6 (X is a halogen element) family, has been successfully synthesized atlow temperatures by collaborators from National Taiwan University. Strong red to near-infrared (NIR) emission properties have been detected, and its optical emission centers have been identified to be numerous embedded perovskite-type...
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Fatigue data of Cement Bitumen Treated Material Mixture C3E5.5 (over 28 days of curing at 20C)
Dane BadawczeFatigue data of Cement Bitumen Treated Material Mixture C3E5.5 (over 28 days of curing at 20C)
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Time series of Doppler blood flow recordings
Dane BadawczeVital signals registration plays a grate role in biomedical engineering and education process. Well acquired data allow future engineers to observe certain physical phenomenons as well learn how to correctly process and interpret the data. This data set was designed for students to learn about Doppler phenomena and to demonstrate correctly and incorrectly...
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Dynamic impedance spectra of programmable dynamically changing RC model based on digital potentiometers
Dane BadawczeThe dataset presents non-stationary impedance spectra of the RC model presented in the figure below. This model contains two digital potentiometers controlled digitally by the microcontroller. This solution allows to programmably control the value of the model impedance. Thanks to this, the model can be used as a test engine for evaluation of the dynamic...
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Genome-Wide DNA Methylation and Gene Expression in Patients with Indolent Systemic Mastocytosis
PublikacjaMastocytosis is a clinically heterogenous, usually acquired disease of the mast cells with a survival time that depends on the time of onset. It ranges from skin-limited to systemic disease, including indolent and more aggressive variants. The presence of the oncogenic KIT p. D816V gene somatic mutation is a crucial element in the pathogenesis. However, further epigenetic regulation may also affect the expression of genes that...
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Keratinocyte-derived small extracellular vesicles supply antigens for CD1a-resticted T cells and promote their type 2 bias in the context of filaggrin insufficiency
PublikacjaIntroduction: Exosome-enriched small extracellular vesicles (sEVs) are nanosized organelles known to participate in long distance communication between cells, including in the skin. Atopic dermatitis (AD) is a chronic inflammatory skin disease for which filaggrin (FLG) gene mutations are the strongest genetic risk factor. Filaggrin insufficiency affects multiple cellular function, but it is unclear if sEV-mediated cellular communication...
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Circulating miRNA profiles and the risk of hemorrhagic transformation after thrombolytic treatment of acute ischemic stroke: a pilot study
PublikacjaBackground: Hemorrhagic transformation (HT) in acute ischemic stroke is likely to occur in patients treated with intravenous thrombolysis (IVT) and may lead to neurological deterioration and symptomatic intracranial hemorrhage (sICH). Despite the complex inclusion and exclusion criteria for IVT and some useful tools to stratify HT risk, sICH still occurs in approximately 6% of patients because some of the risk factors for this...
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Database of the convergence analysis results of the nonstandard approximation of the generalized Burgers–Huxley equation for the solution bounded within [0,1].
Dane BadawczeThe presented dataset is a result of the convergence analysis of the Mickens-type, nonlinear, finite-difference discretization of a generalized Burgers–Huxley partial differential equation.
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Database of the convergence analysis results of the nonstandard approximation of the generalized Burgers–Huxley equation for the solution bounded within [0, γ^(1/p)].
Dane BadawczePresented dataset is a result of the convergence analysis of the Mickens-type, nonlinear, finite-difference discretization of a generalized Burgers–Huxley partial differential equation. The generalized Burgers–Huxley equation is a diffusive partial differential equation with nonlinear advection and diffusion. The boundary problem for this equation possesses...
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Nanoindentation tests of the hydroxyapatite composite coatings applicated on titanium alloys by the electrophoretic method
Dane BadawczeCurrently, there are no metal materials that meet all biomechanical and biochemical requirements needed for long life implantable biomaterials. The main purpose of the study was to functionalize the surface of the titanium alloys used in biomaterial implants.
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The luminescence study of Sr0.98Li2.5 + zAl1.5 – zO3 + 2zN1 – 2z:0.02Eu coumpounds.
Dane BadawczeEu2+-doped UCr4C4-type oxynitride phosphors are emerging innovative materials to replace oxide and nitride phosphors for high-end light-emitting devices. A series of Sr0.98Li2.5 + zAl1.5 – zO3 + 2zN1 – 2z:0.02Eu phosphors were synthesized by collaborators from the National Taiwan University by precursor engineering, and these products showed an unexpected...
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Measurement spectrum obtained with the use of ZnO coated microsphere-based fiber-optic sensor - microsphere inspection s.4
Dane BadawczeApplication of a microsphere-based fiber-optic sensor with 200 nm zinc oxide (ZnO) coating, deposited by Atomic Layer Deposition (ALD) method, for temperature measurements between 100°C and 300°C, is presented. The main advantage of integrating a fiber-optic microsphere with a sensing device is the possibility of monitoring the integrity of the sensor...
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The luminescence study of Sr2−xSrxPN3:Eu2+ nitridophosphate.
Dane BadawczeIn this work, a series of Ca2−xSrxPN3:Eu2+ nitridophosphate phosphors through a solid-solution strategy involving a hot isostatic press was developed by collaborators from National Taiwan University. Unexpected dual emissions in the red and infrared regions are observed, different from previous research results. The unique change in red and near-infrared...
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Thermogravimetric analysis data of hydration in air and nitrogen for BaCe0.6Zr0.2Y0.1M0.1O3-δ (M = Fe, Pr, Tb)
Dane BadawczeThe dataset consists of 6 files of thermogravimetric analysis (TGA) data. The TGA experiments of hydration for BaCe0.6Zr0.2Y0.1Fe0.1O3-δ (BCZYFe), BaCe0.6Zr0.2Y0.1Pr0.1O3-δ (BCZYPr), and BaCe0.6Zr0.2Y0.1Tb0.1O3-δ (BCZYTb) were conducted on Netzsch STA 449.