Search
Filters
total: 474
Search results for: DATASET QUALITY
-
Herbarium of Division of Marine Biology and Ecology as the Primary Basis for Conservation Status Assessments in the Gulf of Gdańsk
PublicationThe dataset titled Herbarium of Division of Marine Biology and Ecology University of Gdańsk (DMBE) is a research herbarium encompassing specimens of vascular plants and algae hosted by the Laboratory of Marine Plant Ecology at the University of Gdańsk, Poland. The aim of Herbarium is to preserve marine plant and algae collections mostly from the Gulf of Gdańsk, but the herbarium also holds specimens from other parts of the world.
-
Using contextual conditional preferences for recommendation taska: a case study in the movie domain
PublicationRecommendation engines aim to propose users items they are interested in by looking at the user interaction with a system. However, individual interests may be drastically influenced by the context in which decisions are taken. We present an attempt to model user interests via a set of contextual conditional preferences. We show that usage of proposed preferences gives reasonable values of the accuracy and the precision even when...
-
Induction of the common-sense hierarchies in lexical data
PublicationUnsupervised organization of a set of lexical concepts that captures common-sense knowledge inducting meaningful partitioning of data is described. Projection of data on principal components allow for dentification of clusters with wide margins, and the procedure is recursively repeated within each cluster. Application of this idea to a simple dataset describing animals created hierarchical partitioning with each clusters related...
-
Data points of structures of R1233zd(E) flowing in a circular minichannel at low, medium and high values of saturation pressure
Open Research DataDatabase present structures of two-phase flow of R1233zd(E) in 3 mm vertical channel. Database contains datapoints which contain information of reduced pressure (ratio of saturation pressure and critical pressure), quality and mass velocity. 4 two phase structures are distinguished: bubbly flow, slug flow, intermittent flow and annular flow.
-
Split-beam echosounder data from Gdansk Deep Summer 2019
Open Research DataThe acoustic data was collected in 2019, in the Gdansk Deep, in the season: Summer. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected while the ship was sailing. To ensure data quality, echosounders were calibrated and passive...
-
Sensory analysis of confectionery products.
Open Research DataThe data set presents the results of the sensory analysis of confectionery products, which was carried out by the sensory profiling analysis method based on the PN-ISO 11035: 1999 standard – “Sensory analysis - Identification and selection of descriptors for determining the sensory profile using multivariate methods”. The method was used to evaluate...
-
Selection of Visual Descriptors for the Purpose of Multi-camera Object Re-identification
PublicationA comparative analysis of various visual descriptors is presented in this chapter. The descriptors utilize many aspects of image data: colour, texture, gradient, and statistical moments. The descriptor list is supplemented with local features calculated in close vicinity of key points found automatically in the image. The goal of the analysis is to find descriptors that are best suited for particular task, i.e. re-identification...
-
Dataset Relating Collective Angst, Identifications, Essentialist Continuity and Collective Action for Progressive City Policy among Gdańsk Residents
PublicationThis dataset contains the individual responses of 456 residents of Gdańsk who participated in the study. The study was conducted before the second term of the presidential election in Poland in 2020. Demographic variables as well as psychological measures of angst, place attachment, identification in-group continuity and willingness to engage in collective action were collected. We also measured the perception of the risk of...
-
Minimal Sets of Lefschetz Periods for Morse-Smale Diffeomorphisms of a Connected Sum of g Real Projective Planes
PublicationThe dataset titled Database of the minimal sets of Lefschetz periods for Morse-Smale diffeomorphisms of a connected sum of g real projective planes contains all of the values of the topological invariant called the minimal set of Lefschetz periods, computed for Morse-Smale diffeomorphisms of a non-orientable compact surface without boundary of genus g (i.e. a connected sum of g real projective planes), where g varies from 1 to...
-
On Bayesian Tracking and Prediction of Radar Cross Section
PublicationWe consider the problem of Bayesian tracking of radar cross section. The adopted observation model employs the gamma family, which covers all Swerling cases in a unified framework. State dynamics are modeled using a nonstationary autoregressive gamma process. The principal component of the proposed solution is a nontrivial gamma approximation, applied during the time update recursion. The superior performance of the proposed approach...
-
Destruction of AFM probes during normal operation
Open Research DataThe quality of the images obtained with the use of an atomic force microscope is determined by the state of the blade interacting with the tested material. Image artifacts can be generated by various reasons, such as oxidation, contamination or an error in blade fabrication, but also appear as a result of the repeated scanning process and inevitable...
-
Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublicationArtificial Neural Network (ANN) models, specifically Convolutional Neural Networks (CNN), were applied to extract emotions based on spectrograms and mel-spectrograms. This study uses spectrograms and mel-spectrograms to investigate which feature extraction method better represents emotions and how big the differences in efficiency are in this context. The conducted studies demonstrated that mel-spectrograms are a better-suited...
-
Description of the Dataset Rhetoric at School – a Selection of the Syllabi from the Academic Gymnasium in Gdańsk – Transcription and Photographs
PublicationThe research dataset described in the article was based on photographs and transcription of a textual record from Latin syllabi for classes at the Gdańsk Academic Gymnasium. The syllabi concern the years 1645/1648/1652/1653. The original document is held in the collection of the Gdańsk Library of the Polish Academy of Sciences [reference number: Ma 3920 8o]. The collected research material can be used for studying the practical...
-
Surf Zone Currents in the Coastal Zone of the Southern Baltic Sea – a Modelling Approach
PublicationNearshore currents in a multi-bar non-tidal coastal zone environment located in the Southern Baltic Sea are studied. Spatiotemporal seaward-directed jets – so-called rip currents – are an important part of the nearshore current system. In previous research, Dudkowska et al. (2020) performed an extended modelling experiment to determine the wave conditions that are conducive to the emergence of rip currents. In this paper, the...
-
On Computing Curlicues Generated by Circle Homeomorphisms
PublicationThe dataset entitled Computing dynamical curlicues contains values of consecutive points on a curlicue generated, respectively, by rotation on the circle by different angles, the Arnold circle map (with various parameter values) and an exemplary sequence as well as corresponding diameters and Birkhoff averages of these curves. We additionally provide source codes of the Matlab programs which can be used to generate and plot the...
-
Split-beam echosounder data from Puck Bay autumn 2018
Open Research DataThe acoustic data was collected in 2018, in the Bay of Puck, in the seasons: autumn. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected at a designated study area not far from the city of Hel, while the ship was sailing. To ensure...
-
Split-beam echosounder data from Puck Bay spring 2019
Open Research DataThe acoustic data was collected in 2019, in the Bay of Puck, in the season: spring. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected at a designated study area not far from the city of Hel, while the ship was sailing. To ensure...
-
Split-beam echosounder data from Puck Bay spring 2019 Part II
Open Research DataThe acoustic data was collected in 2019, in the Bay of Puck, in the season: spring. Data was collected during the sunrise and sunset. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected at a designated study area not far from the city of Hel, while the ship was sailing....
-
AVHRR Level1CD covering Baltic Sea area year 2001
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
-
Comprehensive Comparison of a Few Variants of Cluster Analysis as Data Mining Tool in Supporting Environmental Management
PublicationA few variants of hierarchical cluster analysis (CA) as tool of assessment of multidimensional similarity in environmental dataset are compared. The dataset consisted of analytical results of determination of metals (Na, K, Ca, Sc, Fe, Co, Zn, As, Br, Rb, Mo, Sb, Cs, Ba, La, Ce, Sm, Hf and Th) in ambient air dried and kept alive, by the means of hydroponics, moss baskets collected in 12 locations on the area of Tricity (Poland)....
-
Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublicationThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
-
Personalized prediction of the secondary oocytes number after ovarian stimulation: A machine learning model based on clinical and genetic data
PublicationControlled ovarian stimulation is tailored to the patient based on clinical parameters but estimating the number of retrieved metaphase II (MII) oocytes is a challenge. Here, we have developed a model that takes advantage of the patient’s genetic and clinical characteristics simultaneously for predicting the stimulation outcome. Sequence variants in reproduction-related genes identified by next-generation sequencing were matched...
-
The Central European GNSS Research Network (CEGRN) dataset
PublicationThe Central European GNSS Research Network (CEGRN) collects GNSS data since 1994 from contributors which today include 42 Institutions in 33 Countries. CEGRN returns a dataset of coordinates and velocities computed according to international standards and the most recent processing procedures and recommendations. We provide a dataset of 1229 positions and velocities resulting from 3 or more repetitions of coordinate measurements...
-
Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
-
X-ray images of Baltic herring
Open Research DataA methodology for studying the geometric shape of Baltic herring swimbladders including the optimal way of catching, transporting and storing fish, the X-ray measurements and the X-ray image analysis, that does not change the natural shape of the fish swimbladder was developed. Fish for research was obtained in the area of the Polish coastal zone...
-
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...
-
High Resolution Sea Ice Floe Size and Shape Data from Knox Coast, East Antarctica
PublicationThis dataset contains floe size distribution data from a very high resolution (pixel size: 0.3 m) optical satellite image of sea ice, acquired on 16 Feb. 2019 off the Knox Coast (East Antarctica). The image shows relatively small ice floes produced by wave-induced breakup of landfast ice between Mill Island and Bowman Island. The ice floes are characterised by a narrow size distribution and angular, polygonal shapes, typical...
-
Thermal imaging in automatic rodent’s social behaviour analysis
PublicationLaboratory rodent social behaviour analysis is an extremely important task for biological, medical and pharmacological researches. In this work thermal images features that facilitate analysis are presented. Methods to distinguish objects on the basis of thermal distribution are tested. Actions of grooming or biting one rodent by another - important social behaviour incidents - are clearly visible...
-
Split-beam echosounder data from Puck Bay winter 2019
Open Research DataThe acoustic data was collected in 2019, in the Bay of Puck, in the season: winter. Data was collected during the day and night. Three split-beam echosounders with frequencies of 38 kHz, 120 kHz and 333 kHz were used to collect the data. The data was collected at a designated study area not far from the city of Hel, on the route Hel - Gdynia and on...
-
From Data to Decision: Interpretable Machine Learning for Predicting Flood Susceptibility in Gdańsk, Poland
PublicationFlood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and...
-
Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing
PublicationCirculating tumor cells (CTCs) are tumor cells that separate from the solid tumor and enter the bloodstream, which can cause metastasis. Detection and enumeration of CTCs show promising potential as a predictor for prognosis in cancer patients. Furthermore, single-cells sequencing is a technique that provides genetic information from individual cells and allows to classify them precisely and reliably. Sequencing data typically...
-
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...
-
Assessing the attractiveness of human face based on machine learning
PublicationThe attractiveness of the face plays an important role in everyday life, especially in the modern world where social media and the Internet surround us. In this study, an attempt to assess the attractiveness of a face by machine learning is shown. Attractiveness is determined by three deep models whose sum of predictions is the final score. Two annotated datasets available in the literature are employed for training and testing...
-
News that Moves the Market: DSEX-News Dataset for Forecasting DSE Using BERT
PublicationStock market is a complex and dynamic industry that has always presented challenges for stakeholders and investors due to its unpredictable nature. This unpredictability motivates the need for more accurate prediction models. Traditional prediction models have limitations in handling the dynamic nature of the stock market. Additionally, previous methods have used less relevant data, leading to suboptimal performance. This study...
-
Pedestrian detection in low-resolution thermal images
PublicationOver one million people die in car accidents worldwide each year. A solution that will be able to reduce situations in which pedestrian safety is at risk has been sought for a long time. One of the techniques for detecting pedestrians on the road is the use of artificial intelligence in connection with thermal imaging. The purpose of this work was to design a system to assist the safety of people and car intelligence with the use...
-
Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-Learned Features
PublicationNematodes Caenorhabditis elegans (C. elegans) have been used as model organisms in a wide variety of biological studies, especially those intended to obtain a better understanding of aging and age-associated diseases. This paper focuses on automating the analysis of C. elegans imagery to classify the muscle age of nematodes based on the known and well established IICBU dataset. Unlike many modern classification methods, the proposed...
-
Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe 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...
-
Macrophytobenthos in the Puck Bay in 2010–2018 Dataset
PublicationThe dataset titled Biomass of macrophytobenthos in the Puck Bay in 2010-2018 con-tains data on the qualitative composition and biomass of macrophytobenthos (flow-er plants and macroalgae) in samples collected in the Puck Bay area (Gulf of Gdańsk, southern Baltic Sea) at 20 stations between 2010–2018. The data was supplemented with additional information: values of measured parameters of water and sediment, e.g. tem-perature...
-
KEMR-Net: A Knowledge-Enhanced Mask Refinement Network for Chromosome Instance Segmentation
PublicationThis article proposes a mask refinement method for chromosome instance segmentation. The proposed method exploits the knowledge representation capability of Neural Knowledge DNA (NK-DNA) to capture the semantics of the chromosome’s shape, texture, and key points, and then it uses the captured knowledge to improve the accuracy and smoothness of the masks. We validate the method’s effectiveness on our latest high-resolution chromosome...
-
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...
-
Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
-
AVHRR Level1CD covering Baltic Sea area year 2005
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
-
AVHRR Level1CD covering Baltic Sea area year 2004
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
-
AVHRR Level1CD covering Baltic Sea area year 2003
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
-
AVHRR Level1CD covering Baltic Sea area year 2002
Open Research DataThe dataset contains data derived from recordings of the AVHRR/3 radiometer operating on board the NOAA POES (Polar Orbiting Environmental Satellites) Series - 5th Generation Satellites covering the Baltic Sea area. The satellite data was recorded in the years 2000-2012 directly by the HRPT station installed at the University of Gdańsk. The registration...
-
Legislation and Practice of Selected State Aid Issues, According to EU and Polish Law
PublicationThe dataset encompasses several tables, each consisting of three elements: legislation, jurisprudence and scientific articles on numerous subjects and economic activities receiving public financial support in the form of state aid instruments. The set includes a subjective list of the most commonly used and/or disputable examples of granting aid, such as for (local) airports and airlines, steel production, shipyards, and coalmines....
-
Long-term Hindcast Simulation of Currents, Sea Level, Water Temperature and Salinity in the Baltic Sea
PublicationThis dataset contains the results of numerical modelling of currents, sea level, water temperature and salinity over a period of 50 years (1958–2007) in the Baltic Sea. A long-term hindcast simulation was performed using a three-dimensional hydrodynamic model (PM3D) based on the Princeton Ocean Model (POM). The spatial resolution was 3 nautical miles, i.e. about 5.5 km. Currents, water temperature, and salinity were recorded...
-
Toward Intelligent Recommendations Using the Neural Knowledge DNA
PublicationIn this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep...
-
Towards semantic-rich word embeddings
PublicationIn recent years, word embeddings have been shown to improve the performance in NLP tasks such as syntactic parsing or sentiment analysis. While useful, they are problematic in representing ambiguous words with multiple meanings, since they keep a single representation for each word in the vocabulary. Constructing separate embeddings for meanings of ambiguous words could be useful for solving the Word Sense Disambiguation (WSD)...
-
Operational Enhancement of Numerical Weather Prediction with Data from Real-time Satellite Images
PublicationNumerical weather prediction (NWP) is a rapidly expanding field of science, which is related to meteorology, remote sensing and computer science. Authors present methods of enhancing WRF EMS (Weather Research and Forecast Environmental Modeling System) weather prediction system using data from satellites equipped with AMSU sensor (Advanced Microwave Sounding Unit). The data is acquired with Department of Geoinformatics’ ground...