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General concept of reduction process for big data obtained by interferometric methods
PublicationInterferometric sonar systems apply the phase content of the sonar signal to measure the angle of a wave front returned from the seafloor or from a target. It collect a big data – datasets that are so large or complex that traditional data processing application software is inadequate to deal with them. The recording a large number of data is associated with the difficulty of their efficient use. So data have to be reduced. The main...
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Determination of the minimum inhibitory concentration of C-1311 derivatives (C-1296, C-1410, Compound 1, Compound 1-R8) against Candida strains
Open Research DataThe datasets contain the results of determining the minimum inhibitory concentration of imidazoacridinone derivatives against C. albicans ATCC 10231, C. glabrata ATCC 90030, C. krusei ATCC 6258 and C. parapsilosis ATCC 22019 and C. albicans clinical strains by the modified M27-A3 specified by the CLSI.
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Determination of Changes in Viscosity of Hydrogel Depending on Shear Rates
PublicationThe datasets entitled Determination of changes in viscosity of hydrogel depending on shear rate contain the results of viscosity measurements using a Brookfield viscometer, with different kinds of spindles and shear rates. The data allowed the used hydrogel preparations to be characterised and their functional parameters, as substances modifying the rheology of thickeners and determining the effect of shear rate on the viscosity...
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Combining Road Network Data from OpenStreetMap with an Authoritative Database
PublicationComputer modeling of road networks requires detailed and up-to-date dataset. This paper proposes a method of combining authoritative databases with OpenStreetMap (OSM) system. The complete route is established by finding paths in the graph constructed from partial data obtained from OSM. In order to correlate data from both sources, a method of coordinate conversion is proposed. The algorithm queries road data from OSM and provides...
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Playback detection using machine learning with spectrogram features approach
PublicationThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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Compact global association based adaptive routing framework for personnel behavior understanding
PublicationPersonnel behavior understanding under complex scenarios is a challenging task for computer vision. This paper proposes a novel Compact model, which we refer to as CGARPN that incorporates with Global Association relevance and Adaptive Routing Pose estimation Network. Our framework firstly introduces CGAN backbone to facilitate the feature representation by compressing the kernel parameter space compared with typical algorithms,...
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Video of LEGO Bricks on Conveyor Belt Dataset Series
PublicationThe dataset series titled Video of LEGO bricks on conveyor belt is composed of 14 datasets containing video recordings of a moving white conveyor belt. The recordings were created using a smartphone camera in Full HD resolution. The dataset allows for the preparation of data for neural network training, and building of a LEGO sorting machine that can help builders to organise their collections.
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Determination of the minimum inhibitory concentration of new bisacridines IKE15-19 and IKE21, against yeast strains
Open Research DataThe datasets contain the results of determining the minimum inhibitory concentration of new bisacridines against C. albicans ATCC 10231, C. glabrata ATCC 90030, C. krusei ATCC 6258 and C. parapsilosis ATCC 22019, S. cerevisiae ATCC 9763 and fluconazole resistant C. albicans strains by the modified M27-A3 specified by the CLSI.
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Detection of Alzheimer's disease using Otsu thresholding with tunicate swarm algorithm and deep belief network
PublicationIntroduction: Alzheimer’s Disease (AD) is a degenerative brain disorder characterized by cognitive and memory dysfunctions. The early detection of AD is necessary to reduce the mortality rate through slowing down its progression. The prevention and detection of AD is the emerging research topic for many researchers. The structural Magnetic Resonance Imaging (sMRI) is an extensively used imaging technique in detection of AD, because...
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Towards classification of patients based on surface EMG data of temporomandibular joint muscles using self-organising maps
PublicationThe study considers the need for an effective method of classification of patients with a temporomandibular joint disorder (TMD). The self-organising map method (SOM) was applied to group patients and used together with the cross-correlation approach to interpret the processed (rectified and smoothed by using root mean square (RMS) algorithm) surface electromyography signal (sEMG) obtained from testing the muscles (two temporal...
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Big Data i 5V – nowe wyzwania w świecie danych (Big Data and 5V – New Challenges in the World of Data)
PublicationRodzaje danych, składające się na zbiory typu Big Data, to m.in. dane generowane przez użytkowników portali internetowych, dane opisujące transakcje dokonywane poprzez Internet, dane naukowe (biologiczne, astronomiczne, pomiary fizyczne itp.), dane generowane przez roboty w wyniku automatycznego przeszukiwania przez nie Internetu (Web mining, Web crawling), dane grafowe obrazujące powiązania pomiędzy stronami WWW itd. Zazwyczaj,...
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Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA
PublicationLarge-scale Graph Convolutional Network (GCN) inference on traditional CPU/GPU systems is challenging due to a large memory footprint, sparse computational patterns, and irregular memory accesses with poor locality. Intel’s Programmable Integrated Unffied Memory Architecture (PIUMA) is designed to address these challenges for graph analytics. In this paper, a detailed characterization of GCNs is presented using the Open-Graph Benchmark...
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublicationIn the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective...
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BASECOL2023 scientific content
PublicationContext. The global context of making numerous data produced by researchers available requires collecting and organising the data, assigning meaningful metadata, and presenting the data in a meaningful and homogeneous way. The BASECOL database, which collects inelastic rate coefficients for application to the interstellar medium and to circumstellar and cometary atmospheres, meets those requirements. Aims. We aim to present the...
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Integration, Processing and Dissemination of LiDAR Data in a 3D Web-GIS
PublicationThe rapid increase in applications of Light Detection and Ranging (LiDAR) scanners, followed by the development of various methods that are dedicated for survey data processing, visualization, and dissemination constituted the need of new open standards for storage and online distribution of collected three-dimensional data. However, over a decade of research in the area has resulted in a number of incompatible solutions that offer...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this...
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Energy-Efficient Self-Supervised Technique to Identify Abnormal User Over 5G Network for E-Commerce
PublicationWithin the realm of e-commerce networks, it is frequently observed that certain users exhibit behavior patterns that differ substantially from the normative behaviors exhibited by the majority of users. The identification of these atypical individuals and the understanding of their behavioral patterns are of significant practical significance in maintaining order on e-commerce platforms. One such method for accomplishing this objective...
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The atlas of inequality aversion: theory and empirical evidence on 55 countries from the Luxembourg Income Study database
PublicationResearch background: In the distributive analysis, the constant relative inequality aversion utility function is a standard tool for ethical judgements of income distributions. The sole parameter ε of this function expresses a society’s aversion to inequality. However, the profession has not committed to the range of ε. When assessing inequality and other welfare characteristics, analysts assume an arbitrary level of ε, common...
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Evaluation of aspiration problems in L2 English pronunciation employing machine learning
PublicationThe approach proposed in this study includes methods specifically dedicated to the detection of allophonic variation in English. This study aims to find an efficient method for automatic evaluation of aspiration in the case of Polish second-language (L2) English speakers’ pronunciation when whole words are analyzed instead of particular allophones extracted from words. Sample words including aspirated and unaspirated allophones...
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Improving Accuracy of Contactless Respiratory Rate Estimation by Enhancing Thermal Sequences with Deep Neural Networks
PublicationEstimation of vital signs using image processing techniques have already been proved to have a potential for supporting remote medical diagnostics and replacing traditional measurements that usually require special hardware and electrodes placed on a body. In this paper, we further extend studies on contactless Respiratory Rate (RR) estimation from extremely low resolution thermal imagery by enhancing acquired sequences using Deep...
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Reliable Surrogate Modeling of Antenna Input Characteristics by Means of Domain Confinement and Principal Components
PublicationA reliable design of contemporary antenna structures necessarily involves full-wave electromagnetic (EM) analysis which is the only tool capable of accounting, for example, for element coupling or the effects of connectors. As EM simulations tend to be CPU-intensive, surrogate modeling allows for relieving the computational overhead of design tasks that require numerous analyses, for example, parametric optimization or uncertainty...
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Microscopic traffic simulation models for connected and automated vehicles (CAVs) – state-of-the-art
PublicationResearch on connected and automated vehicles (CAVs) has been gaining substantial momentum in recent years. However, thevast amount of literature sources results in a wide range of applied tools and datasets, assumed methodology to investigate thepotential impacts of future CAVs traffic, and, consequently, differences in the obtained findings. This limits the scope of theircomparability and applicability and calls for a proper standardization...
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Multiple Group Membership and Collective Action Intention
PublicationDatasets from two studies conducted in Poland on the relation between identity fusion, group identification, multiple group membership, perceived injustice, and collective action intention. The presented studies, in the context of protests against attempts to restrict abortion law, were conducted to examine the link between belonging to multiple groups, group efficacy & identification, perceived injustice and collective...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
PublicationData 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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An Analysis of Neural Word Representations for Wikipedia Articles Classification
PublicationOne 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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How ethics combine with big data: a bibliometric analysis
PublicationThe term Big Data is becoming increasingly widespread throughout the world, and its use is no longer limited to the IT industry, quantitative scientific research, and entrepreneurship, but entered as well everyday media and conversations. The prevalence of Big Data is simply a result of its usefulness in searching, downloading, collecting and processing massive datasets. It is therefore not surprising that the number of scientific...
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Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model
PublicationDepth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size...
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublicationThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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Empirical analysis of tree-based classification models for customer churn prediction
PublicationCustomer churn is a vital and reoccurring problem facing most business industries, particularly the telecommunications industry. Considering the fierce competition among telecommunications firms and the high expenses of attracting and gaining new subscribers, keeping existing loyal subscribers becomes crucial. Early prediction of disgruntled subscribers can assist telecommunications firms in identifying the reasons for churn and...
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Upgrading low value-added activities in global value chains: a functional specialisation approach
PublicationThis paper aims to identify patterns of functional specialisation (FS) in global value chains (GVCs) and determinants of upgrading them for selected Central Eastern European (CEE) economies. By combing the World Input-Output Database with data on occupations, we reveal a new FS pattern among subgroups of CEEs. Poland and Slovakia have an unfavourable GVC position and specialise in low value-added fabrication function. In contrast,...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Multiple Cues-Based Robust Visual Object Tracking Method
PublicationVisual object tracking is still considered a challenging task in computer vision research society. The object of interest undergoes significant appearance changes because of illumination variation, deformation, motion blur, background clutter, and occlusion. Kernelized correlation filter- (KCF) based tracking schemes have shown good performance in recent years. The accuracy and robustness of these trackers can be further enhanced...
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Optimized AVHRR land surface temperature downscaling method for local scale observations: case study for the coastal area of the Gulf of Gdańsk
PublicationSatellite imaging systems have known limitations regarding their spatial and temporal resolution. The approaches based on subpixel mapping of the Earth’s environment, which rely on combining the data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution, are of considerable interest. The paper presents the downscaling process of the land...
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SOLAP GIS in maritime research
PublicationMultidimensional Geographical Information System is a system especially designed to acquire, distribute, analyze and visualize complicated spatio-temporal data. Modern Geographical Information System technology can provide easy-to-use, near real-time solutions to many problems from different areas of research. In the article, authors summarize recent works on Spatial Online Analytical Processing (SOLAP) and multidimensional Geographical...
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Educational Dataset of Handheld Doppler Blood Flow Recordings
PublicationVital signals registration plays a significant role in biomedical engineering and education process. Well acquired data allow future engineers to observe certain physical phenomena as well learn how to correctly process and interpret the data. This dataset was designed for students to learn about Doppler phenomena and to demonstrate correctly and incorrectly acquired signals as well as the basic methods of signal processing. This...
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Language Value
Journals -
VALUE IN HEALTH
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A fuzzy logic model for forecasting exchange rates
PublicationThis article is devoted to the issue of forecasting exchange rates. The objective of the conducted research is to develop a predictive model with the use of an innovative methodology - fuzzy logic theory - and to evaluate its effectiveness in times of prosperity and during the financial crisis. The model is based on sets of rules written by the author in the form of IF-THEN, where expert knowledge is stored. This model is the result...
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Melanoma skin cancer detection using mask-RCNN with modified GRU model
PublicationIntroduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic...
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Study of Statistical Text Representation Methods for Performance Improvement of a Hierarchical Attention Network
PublicationTo effectively process textual data, many approaches have been proposed to create text representations. The transformation of a text into a form of numbers that can be computed using computers is crucial for further applications in downstream tasks such as document classification, document summarization, and so forth. In our work, we study the quality of text representations using statistical methods and compare them to approaches...
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Calculations of the resistance values of 10 ratio resistors
Open Research DataThe presented data set is part of the research aimed at determining the actual characteristics of each thermistor in a package of twenty NTC10k type sensors.
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Exploring the landscape of automatic cerebral microbleed detection: A comprehensive review of algorithms, current trends, and future challenges
PublicationThis paper provides the first review to date which gathers, describes, and assesses, to the best of our knowledge, all available publications on automating cerebral microbleed (CMB) detection. It provides insights into the current state of the art and highlights the challenges and opportunities in this topic. By incorporating the best practices identified in this review, we established guidelines for the development of CMB detection...
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Computer-Aided Detection of Hypertensive Retinopathy Using Depth-Wise Separable CNN
PublicationHypertensive retinopathy (HR) is a retinal disorder, linked to high blood pressure. The incidence of HR-eye illness is directly related to the severity and duration of hypertension. It is critical to identify and analyze HR at an early stage to avoid blindness. There are presently only a few computer-aided systems (CADx) designed to recognize HR. Instead, those systems concentrated on collecting features from many retinopathy-related...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublicationIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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BADANIE WPŁYWU INDUKCJI REMANENCJI NA STAN PRZEJŚCIOWY JEDNOFAZOWEGO UKŁADU TRANSFORMATOROWEGO
PublicationW referacie przedstawiono wyniki badań eksperymentalnych i symulacyjnych wpływu indukcji remanencji w rdzeniu transformatora jednofazowego na jego stan przejściowy przy jego pracy jałowej. Badany obiekt jest układem transformatorowym o dwóch uzwojeniach nawiniętych na zwijanym z blachy anizotropowej rdzeniu w kształcie toroidu. Doświadczenia eksperymentalne polegały na rozładowywaniu kondensatora przez uzwojenie strony pierwotnej...
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Wpływ wysokiej osteotomii piszczelowej na mechanikę stawu kolanowego
PublicationW rozprawie podjęto próbę weryfikacji wpływu zabiegu chirurgicznego wysokiej osteotomii piszczelowej na mechanikę stawu kolanowego. Po wykonanym przeglądzie literatury, postawiono trzy hipotezy, które poddano weryfikacji na drodze badań numerycznych. Otrzymane wyniki zwalidowano poprzez badania nacisków powierzchniowych występujących w stawach kolanowych świni domowej, prowadzonych na maszynie do jednoosiowego ściskania. Praca...
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Application of COSMO-RS-DARE as a Tool for Testing Consistency of Solubility Data: Case of Coumarin in Neat Alcohols
PublicationCoumarin is a naturally occurring lactone-type benzopyrone with various applications in the pharmaceutical, food, perfume, and cosmetics industries. This hydrophobic compound is poorly soluble in water but dissolves well in protic organic solvents such as alcohols. Despite the extensive use of coumarin, there are only a few reports documenting its solubility in organic solvents, and some reported data are incongruent, which...
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Intelligent Decision Forest Models for Customer Churn Prediction
PublicationCustomer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non‐churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones....
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Analysis of the Water Level Variation at the Polish Part of the Vistula Lagoon (2008-2017)
Open Research DataThe dataset consists of the following data:
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Content-Based Approach to Automatic Recommendation of Music
PublicationThis paper presents a content-based approach to music recommendation. For this purpose, a database which contains more than 50000 music excerpts acquired from public repositories was built. Datasets contain tracks of distinct performers within several music genres. All music pieces were converted to mp3 format and then parameterized based on MPEG-7, mel-cepstral and time-related dedicated parameters. All feature vectors are stored...