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Neural Graph Collaborative Filtering: Analysis of Possibilities on Diverse Datasets
PublikacjaThis 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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Journal of Investigative Psychology and Offender Profiling
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SegSperm - a dataset of sperm images for blurry and small object segmentation
Dane BadawczeMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
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Effect of process parameters on food waste conversion - dataset 1
Dane BadawczeData obtained during studies (food waste pretreatment and conversion), describing the effect of process parameters (sonocavitation) on food waste conversion.
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Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych
PublikacjaCelem rozprawy jest zbadanie algorytmów do identyfikacji instrumentów występujących w sygnale polifonicznym z wykorzystaniem sztucznych sieci neuronowych. W części teoretycznej przywołano podstawy przetwarzania sygnałów fonicznych w kontekście ekstrakcji parametrów sygnałów wykorzystywanych w treningu sieci neuronowych. Dodatkowo dokonano analizy rozwoju metod uczenia maszynowego z uwzględnieniem podziału na sieci neuronowe pierwszej,...
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Reduction of measurement data before Digital Terrain Model generation vs. DTM generalisation
PublikacjaModern 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...
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A Reduction Method for Bathymetric Datasets that Preserves True Coastal Water Geodata
PublikacjaWater areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and the objects located on it. Information about the quality and reliability of the depth data is important, especially during coastal modelling. In-shore areas are liable...
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Recognition of Emotions in Speech Using Convolutional Neural Networks on Different Datasets
PublikacjaArtificial 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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High resolution optical and acoustic remote sensing datasets of the Puck Lagoon
PublikacjaThe 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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Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublikacjaConsidering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images....
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SESNED: Dataset for Event-Based Non-Intrusive Load Monitoring Research
Dane BadawczeSescom NILM Energy Dataset (SESNED ) description
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Vident-real: an intra-oral video dataset for multi-task learning
Dane BadawczeWe introduce Vident-real, a large dataset of 100 video sequences of intra-oral scenes from real conservative dental treatments performed at the Medical University of Gdańsk, Poland. The dataset can be used for multi-task learning methods including:
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Effective Air Quality Prediction Using Reinforced Swarm Optimization and Bi-Directional Gated Recurrent Unit
PublikacjaIn 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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Selecting Features with SVM
PublikacjaA 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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Application of Regression Line to Obtain Specified Number of Points in Reduced Large Datasets
PublikacjaModern 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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Influence of datasets decreased by applying reduction and generation methods on Digital Terrain Models
PublikacjaThe 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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Testing the Diagnostic Utility of Recombinant Toxoplasma Gondii Chimeric Antigens – Generated Datasets
PublikacjaThe 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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Intelligent Audio Signal Processing − Do We Still Need Annotated Datasets?
PublikacjaIn 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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Region-Specific Methylation Profiling in Acute Myeloid Leukemia
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mRNA profiling for vaginal fluid and menstrual blood identification
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Substrate profiling of Zika virus NS2B‐NS3 protease
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Fecal Serine Protease Profiling in Inflammatory Bowel Diseases
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Standard deviation as the optimization criterion in the OptD method and its influence on the generated DTM
PublikacjaReduction 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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Elgold: gold standard, multi-genre dataset for named entity recognition and linking
Dane BadawczeThe dataset contains 276 multi-genre texts with marked named entities, which are linked to corresponding Wikipedia articles if available. Each entity was manually verified by at least three people, which makes the dataset a high-quality gold standard for the evaluation of named entity recognition and linking algorithms.
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Vident-synth: a synthetic intra-oral video dataset for optical flow estimation
Dane BadawczeWe introduce Vident-synth, a large dataset of synthetic dental videos with corresponding ground truth forward and backward optical flows and occlusion masks. It can be used for:
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Dataset 1 on nitrobenzene degradation after 60 minutes of the ARP at 20 °C
Dane BadawczeTHis set od date presents a nitrobenzene degradation after 60 minutes of the process at 20 °C - Advanced Reduction Process based on dithionate application.
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Vident-lab: a dataset for multi-task video processing of phantom dental scenes
Dane BadawczeWe introduce a new, asymmetrically annotated dataset of natural teeth in phantom scenes for multi-task video processing: restoration, teeth segmentation, and inter-frame homography estimation. Pairs of frames were acquired with a beam splitter. The dataset constitutes a low-quality frame, its high-quality counterpart, a teeth segmentation mask, and...
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High performance filtering for big datasets from Airborne Laser Scanning with CUDA technology
PublikacjaThere 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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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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Study of Multi-Class Classification Algorithms’ Performance on Highly Imbalanced Network Intrusion Datasets
PublikacjaThis 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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Selected Features of Dynamic Voting
PublikacjaIn multi-agent systems composed of autonomous agents with local knowledge, it is often desirable to aggregate their knowledge in order to make an educated decision. One of the methods of agreeing to a common decision is voting. A new history-based dynamic weight protocol allows for identification of the agents which contribute to the correct system decision. The main advantage of this approach, compared to static weighted system...
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Oxylipin profiling for clinical research: Current status and future perspectives
PublikacjaOxylipins are potent lipid mediators with increasing interest in clinical research. They are usually measured in systemic circulation and can provide a wealth of information regarding key biological processes such as inflammation, vascular tone, or blood coagulation. Although procedures still require harmonization to generate comparable oxylipin datasets, performing comprehensive profiling of circulating oxylipins in large studies...
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Metabolic profiling of pteridines for determination of potential biomarkers in cancer diseases
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Noise profiling for speech enhancement employing machine learning models
PublikacjaThis paper aims to propose a noise profiling method that can be performed in near real-time based on machine learning (ML). To address challenges related to noise profiling effectively, we start with a critical review of the literature background. Then, we outline the experiment performed consisting of two parts. The first part concerns the noise recognition model built upon several baseline classifiers and noise signal features...
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The dataset of coupling coefficients for rotating receiver of multicoil dynamic wireless power transfer system
Dane BadawczeThe provided dataset is part of the simulation results shown in related journal paper "Optimal Rotating Receiver Angles Estimation for Multicoil Dynamic Wireless Power Transfer".
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Rust QA: question answering dataset for "The Rust Programming Language" in SQuAD 2.0 format
Dane BadawczeRust QA is a dataset for training and evaluating QA systems. The dataset consists of 1068 questions to "The Rust Programming Language" book (https://doc.rust-lang.org/stable/book/) with the answers provided as text spans from the book. The dataset is released in SQuAD 2.0 format.
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Dataset of bibliometric data for a research study on tax research retrived from Web of Science.
Dane BadawczeThis dataset was created for the purpose of research study on taxation research. Analytical data come from the Web of Science (WoS) databases provided by Clarivate Analytics and was retrived in March 2021.
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MULTI-OBJECTIVE OPTIMIZATION PROBLEM IN THE OptD-MULTI METHOD
PublikacjaNew measurement technologies, e.g. Light Detection And Ranging (LiDAR), generate very large datasets. In many cases, it is reasonable to reduce the number of measuring points, but in such a way that the datasets after reduction satisfy specific optimization criteria. For this purpose the Optimum Dataset (OptD) method proposed in [1] and [2] can be applied. The OptD method with the use of several optimization criteria is called...
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Entropy Measures of heart rate variability for short ECG datasets in patients with congestive heart failure
PublikacjaWe investigated the usefulness of entropy measures calculated for short ECG series in distinguishing healthy subjects from patients with congestive heart failure (CHF). Four entropy measures were tested: Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (Fuzzy En) and Permutation Entropy (PE), each computed for ECG series of 1000, 500, 250 and 100 RR intervals. We found that with a reduction of the data set length...
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Entropy measures of heart rate variability for short ECG datasets in patients with congestive heart failure
PublikacjaWe investigated the usefulness of entropy measures calculated for short ECG series in distinguishing healthy subjects from patients with congestive heart failure (CHF). Four entropy measures were tested: Approximate Entropy (ApEn), Sample Entropy (SampEn), Fuzzy Entropy (FuzzyEn) and Permutation Entropy (PE), each computed for ECG series of 1000, 500, 250 and 100 RR intervals. We found that with a reduction of the data set length...
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Ontological Model for Contextual Data Defining Time Series for Emotion Recognition and Analysis
PublikacjaOne 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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Bi-GRU-APSO: Bi-Directional Gated Recurrent Unit with Adaptive Particle Swarm Optimization Algorithm for Sales Forecasting in Multi-Channel Retail
PublikacjaIn the present scenario, retail sales forecasting has a great significance in E-commerce companies. The precise retail sales forecasting enhances the business decision making, storage management, and product sales. Inaccurate retail sales forecasting can decrease customer satisfaction, inventory shortages, product backlog, and unsatisfied customer demands. In order to obtain a better retail sales forecasting, deep learning models...
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Molecular Profiling for Predictors of Radiosensitivity in Patients with Breast or Head-and-Neck Cancer
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Transcriptome profiling and environmental linkage to salinity across Salicornia europaea vegetation
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Piotr Krajewski dr
OsobyPiotr Krajewski pracuje jako starszy bibliotekarz w Bibliotece Politechniki Gdańskiej. Jako pracownik Sekcji Informacji Naukowo-Technicznej skupia się przede wszystkim na zagadnieniach związanych z ruchem Open Access oraz rolą repozytoriów instytucjonalnych w jego rozwoju. Jest także autorem artykułów poruszających kwestie standaryzacji statystyk wykorzystania zasobów elektronicznych jak również problematykę „drapieżnych wydawców”....
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Visual Features for Endoscopic Bleeding Detection
PublikacjaAims: To define a set of high-level visual features of endoscopic bleeding and evaluate their capabilities for potential use in automatic bleeding detection. Study Design: Experimental study. Place and Duration of Study: Department of Computer Architecture, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, between March 2014 and May 2014. Methodology: The features have...
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Cardinal regenerative features of the MRL mouse
PublikacjaIn this review, we discuss recent studies relating to major features of adult MRL mouse biology that contribute to the regenerative responses seen. These include an increased inflammatory cell profile, a unique glycolytic metabolic state typically found during embryogenesis, and a cell cycle phenotype of DNA damage and G2/M arrest. These traits have been found in other mammalian and non-mammalian regenerative systems. How these...
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Dataset for systematic literature review about phosphorus magnetic resonance spectroscopy (31 P MRS).
Dane BadawczeThe file contains the publications retrived for systematic literature review from sleceted databases: Web of Science Core Collection, Scopus, Chochrane Library, and Pubmed. Records were identified by using nesting technique. Our search log stated as follow: "phosphorus" AND ("mri spectroscopy" OR "31P MRS").
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Dataset for a research study on scientific productivity of Polish technical universities (Gdańsk Tech 2016-2020)
Dane BadawczeThis dataset was created for the purpose of research on scientific productivity at Polish technical universities. The raw data was retrieved in June 2021 by the SciVal benchmarking tool in xlsx format and will be used to create the research profiles of the universities and underlying data of journals articles. The most common definition of research...
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A Text as a Set of Research Data. A Number of Aspects of Data Acquisition and Creation of Datasets in Neo-Latin Studies
PublikacjaIn this paper, the authors, who specialise in part in neo-Latin studies and the his-tory of early modern education, share their experiences of collecting sources for Open Research Data sets under the Bridge of Data project. On the basis of inscription texts from St. Mary’s Church in Gdańsk, they created 29 Open Research Data sets. In turn, the text of the lectures of the Gdańsk scholar Michael Christoph Hanow, Praecepta de arte...