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Search results for: HIGH-VALUE DATASETS
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Towards High-Value Datasets Determination for Data-Driven Development: A Systematic Literature Review
PublicationOpen 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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High resolution optical and acoustic remote sensing datasets of the Puck Lagoon
PublicationThe very shallow marine basin of Puck Lagoon in the southern Baltic Sea, on the Northern coast of Poland, hosts valuable benthic habitats and cultural heritage sites. These include, among others, protected Zostera marina meadows, one of the Baltic’s major medieval harbours, a ship graveyard, and likely other submerged features that are yet to be discovered. Prior to this project, no comprehensive high-resolution remote sensing...
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High performance filtering for big datasets from Airborne Laser Scanning with CUDA technology
PublicationThere are many studies on the problems of processing big datasets provided by Airborne Laser Scanning (ALS). The processing of point clouds is often executed in stages or on the fragments of the measurement set. Therefore, solutions that enable the processing of the entire cloud at the same time in a simple, fast, efficient way are the subject of many researches. In this paper, authors propose to use General-Purpose computation...
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Silybum marianum glycerol extraction for the preparation of high-value anti-ageing extracts
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Identification of High-Value Dataset determinants: is there a silver bullet for efficient sustainability-oriented data-driven development?
PublicationOpen Government Data (OGD) are seen as one of the trends that has the potential to benefit the economy, improve the quality, efficiency, and transparency of public administration, and change the lives of citizens, and the society as a whole facilitating efficient sustainability-oriented data-driven services. However, the quick achievement of these benefits is closely related to the “value” of the OGD, i.e., how useful, and reusable...
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Ammonium Enhances Food Waste Fermentation to High-Value Optically Active l-Lactic acid
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New insights into the role of lattice oxygen in the catalytic carbonization of polypropylene into high value-added carbon nanomaterials
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Activated Carbon Modification towards Efficient Catalyst for High Value-Added Products Synthesis from Alpha-Pinene
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Correction: New insights into the role of lattice oxygen in the catalytic carbonization of polypropylene into high value-added carbon nanomaterials
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Potential Energy Curves of Diatomic Alkali Molecules Datasets
PublicationThe datasets described in this article contain potential energy curves for several diatomic systems. The data was obtained via high-performance computing using MOLPRO, a system of ab initio programs for advanced molecular electronic structure calculations. The datasets allow to model bond lengths, energy levels, spectra and time-evolution of molecular dimers for which the data are presented.
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Distribution and extent of benthic habitats in Puck Bay (Gulf of Gdańsk, southern Baltic Sea)
PublicationThe majority of the southern Baltic Sea seabed encompasses homogenous soft-bottom sediments of limited productivity and low biological diversity, but shallow productive areas in the coastal zone such as wetlands, vegetated lagoons and sheltered bays show a high variety of benthic habitat types offering favourable biotopic conditions for benthic fauna. Within Polish marine areas, semi-enclosed Puck Bay (the western part of the...
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Anna Rzeczycka dr hab.
PeopleAnna Rzeczycka is the deputy head of the Department of Finance at the Faculty of Economics and Management of the Gdańsk University of Technology. Publications are situated in the field of social sciences in the discipline of economics and finance. They include books, monographs, articles, publications and scientific editions of monographs and scientific journals. In terms of numbers, it includes the following items: 12 monographs...
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Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets
PublicationThis paper continues the work by Wang et al. [17]. Its goal is to verify the robustness of the NGCF (Neural Graph Collaborative Filtering) technique by assessing its ability to generalize across different datasets. To achieve this, we first replicated the experiments conducted by Wang et al. [17] to ensure that their replication package is functional. We received sligthly better results for ndcg@20 and somewhat poorer results for...
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Application of Regression Line to Obtain Specified Number of Points in Reduced Large Datasets
PublicationModern measurement techniques like scanning technology or sonar measurements, provide large datasets, which are a reliable source of information about measured object, however such datasets are sometimes difficult to develop. Therefore, the algorithms for reducing the number of such sets are incorporated into their processing. In the reduction algorithms based on the...
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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublicationIn this paper, intelligent audio signal processing examples are shortly described. The focus is, however, on the machine learning approach and datasets needed, especially for deep learning models. Years of intense research produced many important results in this area; however, the goal of fully intelligent signal processing, characterized by its autonomous acting, is not yet achieved. Therefore, a review of state-of-the-art concerning...
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Integrating Statistical and Machine‐Learning Approach for Meta‐Analysis of Bisphenol A‐Exposure Datasets Reveals Effects on Mouse Gene Expression within Pathways of Apoptosis and Cell Survival
PublicationBisphenols are important environmental pollutants that are extensively studied due to different detrimental effects, while the molecular mechanisms behind these effects are less well understood. Like other environmental pollutants, bisphenols are being tested in various experimental models, creating large expression datasets found in open access storage. The meta‐analysis of such datasets is, however, very complicated for various...
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Testing the Diagnostic Utility of Recombinant Toxoplasma Gondii Chimeric Antigens – Generated Datasets
PublicationThe datasets titled Toxoplasma gondii recombinant chimeric antigens – IgM and IgG ELISAs – mouse serum samples and Toxoplasma gondii recombinant chimeric antigens – IgG and IgM ELISAs – human serum samples contain absorbance measurements obtained during serological tests using mouse and human sera in enzyme-linked immunosorbent assay (ELISA) tests based on recombinant chimeric antigens. The datasets allows a comparison of absorbance...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Determination of the MIC (minimum inhibitory concentration) of new bisacridines IKE16-19, IKE21 and IE10 against C. glabrata clinical strains
Open Research DataThe datasets contain the results of determining the MIC value (minimum inhibitory concentration) of new bisacridines IKE16-19, IKE21 and IE10 against Candida glabrata clinical strains CZD 310, 373, 377, 513 and collection strain DSM 11226 by the modified M27-A3 specified by the CLSI.
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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...
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Selecting Features with SVM
PublicationA common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection. Experiments were performed on three text datasets generated from a Wikipedia dump. Amount...
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Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
PublicationThere are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors...
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Influence of datasets decreased by applying reduction and generation methods on Digital Terrain Models
PublicationThe number of point clouds provided by LiDAR technology can be sometimes seen as a problem in development and further processing for given purposes (e.g. Digital Terrain Model (DTM) generation). Therefore, there is still a need to reduce the obtained big datasets. Reducing can be done, inter alia, by reducing the size of the set or by generating the set. This paper presents two variants of the reduction of point clouds in order...
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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublicationThis paper is devoted to the problem of class imbalance in machine learning, focusing on the intrusion detection of rare classes in computer networks. The problem of class imbalance occurs when one class heavily outnumbers examples from the other classes. In this paper, we are particularly interested in classifiers, as pattern recognition and anomaly detection could be solved as a classification problem. As still a major part of...
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Deep learning-based waste detection in natural and urban environments
PublicationWaste 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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Andrzej Chybicki dr inż.
PeopleA graduate of the Faculty of Electronics, Telecommunications and Informatics at the Gdańsk University of Technology, PhD in technical sciences in the field of IT specializing in distributed data processing in IT . Aimed at exploiting the achievements and knowledge in the field of industrial research. He cooperated with a number of companies including OpeGieka Elbląg, Reson Inc., Powel Sp. z o. o., Wasat, Better Solutions, the European...
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Photos and rendered images of LEGO bricks
PublicationThe paper describes a collection of datasets containing both LEGO brick renders and real photos. The datasets contain around 155,000 photos and nearly 1,500,000 renders. The renders aim to simulate real-life photos of LEGO bricks allowing faster creation of extensive datasets. The datasets are publicly available via the Gdansk University of Technology “Most Wiedzy” institutional repository. The source files of all tools used during...
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Simulations of the Derecho Event in Poland of 11th August 2017 Using WRF Model
PublicationThis series contains datasets related to the forecasting of a severe weather event, a derecho, in Poland on 11 August 2017. The simulations were conducted using the Weather Research and Forecasting (WRF) model version 4.2.1 with different initial and boundary conditions of the pressure and model levels derived from 5 global models: Global Forecast System (GFS), Global Data Assimilation System (GDAS), European Centre for Medium-Range...
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Simulation of the derecho event in Poland of 11th August 2017 using the WRF model and ERA5 data on pressure levels as initial conditions
Open Research DataThis series contains datasets related to the forecasting of a severe weather event, a derecho, in Poland on 11 August 2017. The simulations were conducted using the Weather Research and Forecasting (WRF) model version 4.2.1 with initial and boundary conditions from ERA5 on pressure levels. Simulation was performed for two starting hours: at 00:00 and...
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Simulation of the derecho event in Poland of 11th August 2017 using the WRF model and GFS data as initial conditions
Open Research DataThis series contains datasets related to the forecasting of a severe weather event, a derecho, in Poland on 11 August 2017. The simulations were conducted using the Weather Research and Forecasting (WRF) model version 4.2.1 with initial and boundary conditions from Global Forecast System (GFS). Simulation was performed for two starting hours: at 00:00...
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Simulation of the derecho event in Poland of 11th August 2017 using the WRF model and GDAS data as initial conditions
Open Research DataThis series contains datasets related to the forecasting of a severe weather event, a derecho, in Poland on 11 August 2017. The simulations were conducted using the Weather Research and Forecasting (WRF) model version 4.2.1 with initial and boundary conditions from Global Data Assimilation System (GDAS). Simulation was performed for two starting hours:...
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Simulation of the derecho event in Poland of 11th August 2017 using the WRF model and ECMWF data as initial conditions
Open Research DataThis series contains datasets related to the forecasting of a severe weather event, a derecho, in Poland on 11 August 2017. The simulations were conducted using the Weather Research and Forecasting (WRF) model version 4.2.1 with initial and boundary conditions from European Centre for Medium-Range Weather Forecasts (ECMWF). Simulation was performed...
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Simulation of the derecho event in Poland of 11th August 2017 using the WRF model and ERA5 data on model levels as initial conditions
Open Research DataThis series contains datasets related to the forecasting of a severe weather event, a derecho, in Poland on 11 August 2017. The simulations were conducted using the Weather Research and Forecasting (WRF) model version 4.2.1 with initial and boundary conditions from ERA5 on model levels. Simulation was performed for two starting hours: at 00:00 and 12:00...
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Application of Web-GIS and Cloud Computing to Automatic Satellite Image Correction
PublicationRadiometric calibration of satellite imagery requires coupling of atmospheric and topographic parameters, which constitutes serious computational problems in particular in complex geographical terrain. Successful application of topographic normalization algorithms for calibration purposes requires integration of several types of high-resolution geographic datasets and their processing in a common context. This paper presents the...
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Standard deviation as the optimization criterion in the OptD method and its influence on the generated DTM
PublicationReduction of the measurement dataset is one of the current issues related to constantly developing technologies that provide large datasets, eg. laser scanning. It could seems that presence and evolution of processors computer, increase of hard drive capacity etc. is the solution for development of such large datasets. And in fact it is, however, the “lighter” datasets are easier to work with. Additionally, reduced datasets can...
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Bibliographic data on datasets (from 2020) affiliated to Most Wiedzy and indexed in Data Citation Index (retrieved by Web of Science service in December 2021)
Open Research DataThe file contains the number of datasets published by the researchers affiliated to Most Wiedzy and indexed in Data Citation Index by Web of Science. The Search was perfprmed using the name of institution in the 'assress' filed or 'group author' field. Data retrieved and published during the 5th Open Science Conference (1-3.12.2021).
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Bibliographic data on datasets affiliated to Maria Curie-Skłodowska University and indexed in Data Citation Index (retrieved by Web of Science service in February2022)
Open Research DataThe file contains the number of datasets published by the researchers affiliated to Maria Curie-Skłodowska University and indexed in Data Citation Index provided by Web of Science. The Search was performer using the name of institution in the address field or group author field. Data retrieved and published during the 5th Open Science Conference (1-3.12.2021)
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Bibliographic data on datasets affiliated to Gdansk University of Technology and indexed in Data Citation Index (retrieved by Web of Science service in December 21)
Open Research DataThe file contains the number of datasets published by the researchers affiliated to Gdansk University of Technology and indexed in Data Citation Index provided by Web of Science. The Search was performed on the 1st of December 2021 using the name of institution in the 'address' and 'group author' field. Data retrieved and published during the 5th Open...
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Bibliographic data on datasets affiliated to University of Technology and Humanities in Radom and indexed in Data Citation Inex (retrievd by Web of Science service in December 2021)
Open Research DataThe file contains the number of datasets published by the researchers affiliated to University of Technology and Humanities in Radom and indexed in Data Citation Index provided by Web of Science. The Search was performed using the name of institution in the address field or group author field. Data retrieved and published during the 5th Open Science...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublicationThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublicationOne of the major challenges facing the field of Affective Computing is the reusability of datasets. Existing affective-related datasets are not consistent with each other, they store a variety of information in different forms, different formats, and the terms used to describe them are not unified. This paper proposes a new ontology, ROAD, as a solution to this problem, by formally describing the datasets and unifying the terms...
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A new multi-process collaborative architecture for time series classification
PublicationTime series classification (TSC) is the problem of categorizing time series data by using machine learning techniques. Its applications vary from cybersecurity and health care to remote sensing and human activity recognition. In this paper, we propose a novel multi-process collaborative architecture for TSC. The propositioned method amalgamates multi-head convolutional neural networks and capsule mechanism. In addition to the discovery...
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X-ray Photoelectron Spectroscopy of Carboxylic Acids as Corrosion Inhibitors of Aluminium Alloys
PublicationThe datasets, titled X-ray Photoelectron Spectroscopy studies of citric acid adsorption on aluminium alloy 5754 in alkaline media and X-ray Photoelectron Spectroscopy studies of various carboxylic acids adsorption on aluminium alloys in alkaline media, contain XPS studies of the corrosion inhibitory action of selected dicarboxylic acids towards commercially available aluminium alloy 5754 in alkaline media at pH=11. These datasets...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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OOA-modified Bi-LSTM network: An effective intrusion detection framework for IoT systems
PublicationCurrently, the Internet of Things (IoT) generates a huge amount of traffic data in communication and information technology. The diversification and integration of IoT applications and terminals make IoT vulnerable to intrusion attacks. Therefore, it is necessary to develop an efficient Intrusion Detection System (IDS) that guarantees the reliability, integrity, and security of IoT systems. The detection of intrusion is considered...
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Rating mathematical models for first-pass of tracer in pCT lung studies
PublicationThis paper presents a comparison of model based on the Gauss function and the most commonly used Gamma-variate model in perfusion computed tomography (pCT) lung studies. It also verifies whether used model affects value of blood volume parameter. Three mean concentration-time curves were created from actual pCT measurements: arterial input function, blood vessels in lungs and lung parenchyma. On the basis of these mean curves we...
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Parallel Computations of Text Similarities for Categorization Task
PublicationIn this chapter we describe the approach to parallel implementation of similarities in high dimensional spaces. The similarities computation have been used for textual data categorization. A test datasets we create from Wikipedia articles that with their hyper references formed a graph used in our experiments. The similarities based on Euclidean distance and Cosine measure have been used to process the data using k-means algorithm....
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublicationModern data acquisition technologies provide large datasets that are not always necessary in its entirety to properly accomplish the goal of the study. In addition, such datasets are often cumbersome for rational processing, and their processing is time and labour consuming. Therefore, methods that enable to reduce the size of the measurement dataset, such as the generalization of the Digital Terrain Model (DTM) or the reduction...