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Search results for: DATASET FEATURES, DATASET PROFILING VOCABULARIES
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Dependent self-employed individuals: are they different from paid employees?
PublicationThis study focuses on dependent self-employment, which covers a situation where a person works for the same employer as a typical worker while on a self-employment contractual basis, i.e., without a traditional employment contract and without certain rights granted to "regular" employees. The research exploits the individual-level dataset of 35 European countries extracted from the 2017 edition of the European Labour Force Survey...
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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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Know your safety indicator – A determination of merchant vessels Bow Crossing Range based on big data analytics
PublicationEven in the era of automatization maritime safety constantly needs improvements. Regardless of the presence of crew members on board, both manned and autonomous ships should follow clear guidelines (no matter as bridge procedures or algorithms). To date, many safety indicators, especially in collision avoidance have been proposed. One of such parameters commonly used in day-to-day navigation but usually omitted by researchers is...
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imPlatelet classifier: image‐converted RNA biomarker profiles enable blood‐based cancer diagnostics
PublicationLiquid biopsies offer a minimally invasive sample collection, outperforming traditional biopsies employed for cancer evaluation. The widely used material is blood, which is the source of tumor-educated platelets. Here, we developed the imPlatelet classifier, which converts RNA-sequenced platelet data into images in which each pixel corresponds to the expression level of a certain gene. Biological knowledge from the Kyoto Encyclopedia...
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Quantitative Risk Assessment in Construction Disputes Based on Machine Learning Tools
PublicationA high monetary value of the construction projects is one of the reasons of frequent disputes between a general contractor (GC) and a client. A construction site is a unique, one-time, and single-product factory with many parties involved and dependent on each other. The organizational dependencies and their complexity make any fault or mistake propagate and influence the final result (delays, cost overruns). The constant will...
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Graph Representation Integrating Signals for Emotion Recognition and Analysis
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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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublicationThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Interrelations between Travel Patterns and Urban Spatial Structure of the Largest Russian Cities
PublicationThe study presented within this dissertation involves the analysis of the relationship between urban spatial structure and travel patterns in the largest Russian cities. It is an empirical investigation of how the spatial structure, formed during the Soviet and post-Soviet periods, affects the travel patterns in the largest cities of contemporary Russia. It aims to determine what measures, both urban structure and transportation...
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ELECTRICAL CONDUCTIVITY AND pH IN SURFACE WATER AS TOOL FOR IDENTIFICATION OF CHEMICAL DIVERSITY
PublicationIn the present study, the creeks and lakes located at the western shore of Admiralty Bay were analysed. The impact of various sources of water supply was considered, based on the parameters of temperature, pH and specific electrolytic conductivity (SEC25). All measurements were conducted during a field campaign in January-February 2017. A multivariate dataset was also created and a biplot of SEC25 and pH of the investigated waters...
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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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Emissions and toxic units of solvent, monomer and additive residues released to gaseous phase from latex balloons
PublicationThis study describes the VOCs emissions from commercially available latex balloons. Nine compounds are determined to be emitted from 13 types of balloons of different colors and imprints in 30 and 60°C. The average values of total volatile organic compounds (TVOCs) emitted from studied samples ranged from 0.054 up to 7.18 μg∙g-1 and from 0.27 up to 36.13 μg∙g-1 for 30oC and 60oC, respectively. The dataset is treated with principal...
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Forecasting risks and challenges of digital innovations
PublicationForecasting and assessment of societal risks related to digital innovation systems and services is an urgent problem, because these solutions usually contain artificial intelligence algorithms which learn using data from the environment and modify their behaviour much beyond human control. Digital innovation solutions are increasingly deployed in transport, business and administrative domains, and therefore, if abused by a malicious...
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Metoda OptD do redukcji danych w opracowaniu wyników pomiarów linii elektroenergetycznych
PublicationSkaning laserowy to technologia dostarczająca we względnie krótkim czasie dużą ilość danych pomiarowych. Jest to zarazem pozytywna jak i negatywna cecha tej technologii. Z jednej strony w wyniku skaningu otrzymuje się dane, które szczegółowo odzwierciedlają pomierzony obiekt. Z drugiej strony trudność sprawia przetwarzanie takiej ilości danych i nie zawsze wszystkie dane ze skaningu są niezbędne do realizacji wybranego zadania....
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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach
PublicationMonitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in...
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How do responsible universities perceive their social engagement? In search of signs of Creating Shared Value by the University
PublicationObjectives: University social responsibility still lacks legitimisation and is perceived as a burden that hinders academics from doing research and teaching. Creating Shared Value by the University may serve as a tool to motivate universities to engage in initiatives for society, as this is beneficial for both parties. Yet, some researchers perceive the creation of economic value as inappropriate for academia. Thus, it was interesting...
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Spatiotemporal Assessment of Satellite Image Time Series for Land Cover Classification Using Deep Learning Techniques: A Case Study of Reunion Island, France
PublicationCurrent Earth observation systems generate massive amounts of satellite image time series to keep track of geographical areas over time to monitor and identify environmental and climate change. Efficiently analyzing such data remains an unresolved issue in remote sensing. In classifying land cover, utilizing SITS rather than one image might benefit differentiating across classes because of their varied temporal patterns. The aim...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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Towards Scalable Simulation of Federated Learning
PublicationFederated learning (FL) allows to train models on decentralized data while maintaining data privacy, which unlocks the availability of large and diverse datasets for many practical applications. The ongoing development of aggregation algorithms, distribution architectures and software implementations aims for enabling federated setups employing thousands of distributed devices, selected from millions. Since the availability of...
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Detecting Apples in the Wild: Potential for Harvest Quantity Estimation
PublicationKnowing the exact number of fruits and trees helps farmers to make better decisions in their orchard production management. The current practice of crop estimation practice often involves manual counting of fruits (before harvesting), which is an extremely time-consuming and costly process. Additionally, this is not practicable for large orchards. Thanks to the changes that have taken place in recent years in the field of image...
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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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Forecasting energy consumption and carbon dioxide emission of Vietnam by prognostic models based on explainable machine learning and time series
PublicationThis study assessed the usefulness of algorithms in estimating energy consumption and carbon dioxide emissions in Viet- nam, in which the training dataset was used to train the models linear regression, random forest, XGBoost, and AdaBoost, allowing them to comprehend the patterns and relationships between population, GDP, and carbon dioxide emissions, energy consumption. The results revealed that random forest, XGBoost, and AdaBoost...
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Concurrent Video Denoising and Deblurring for Dynamic Scenes
PublicationDynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning pixel-to-pixel mappings, which is commonly enhanced by larger region awareness. This is a difficult yet simplified scenario because noise is neglected when it is omnipresent in a wide...
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Influence of Soft Soil Samples Quality on the Compressibility and Undrained Shear Strength – Seven Lessons Learned From the Vistula Marshlands
PublicationThis technical article presents the influence of sample quality on the compressibility parameters and undrained shear strength ( c u ) of soft soils from the Vistula Marshlands. The analysis covers: (1) quality of soft soil according to three criteria: void ratio (Δ e / e 0 index), volumetric strain (Δ ɛ v ) and C r / C c ratio; (2) influence of storage time on quality; (3) influence of sample quality on undrained shear strength...
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Role of miR-15b/16–2 cluster network in endometrial cancer: An in silico pathway and prognostic analysis
PublicationEndometrial cancer (EC) is the second most common cancer in women. A large number of human cancers exhibit dysregulation of microRNA expression including EC. MiR-15b/16–2 is one of the best-known miRNA clusters that is expressed in many types of cancer tissues. Herein, we analyzed the expression of individual miR-15b/16–2 cluster members, its paralogues, and their target network analysis, as well as their prognostic significance...
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Fermentative Conversion of Two-Step Pre-Treated Lignocellulosic Biomass to Hydrogen
PublicationFermentative hydrogen production via dark fermentation with the application of lignocellulosic biomass requires a multistep pre-treatment procedure, due to the complexed structure of the raw material. Hence, the comparison of the hydrogen productivity potential of different lignocellulosic materials (LCMs) in relation to the lignocellulosic biomass composition is often considered as an interesting field of research. In this study,...
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DEEP LEARNING BASED ON X-RAY IMAGING IMPROVES COXARTHROSIS DETECTION
PublicationObjective: The purpose of the study was to create an Artificial Neural Network (ANN) based on X-ray images of the pelvis, as an additional tool to automate and improve the diagnosis of coxarthrosis. The research is focused on joint space narrowing, which is a radiological symptom showing the thinning of the articular cartilage layer, which is translucent to X-rays. It is the first and the most important of the radiological signs...
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Deep Learning-Based, Multiclass Approach to Cancer Classification on Liquid Biopsy Data
PublicationThe field of cancer diagnostics has been revolutionized by liquid biopsies, which offer a bridge between laboratory research and clinical settings. These tests are less invasive than traditional biopsies and more convenient than routine imaging methods. Liquid biopsies allow studying of tumor-derived markers in bodily fluids, enabling the development of more precise cancer diagnostic tests for screening, disease monitoring, and...
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A machine learning approach to classifying New York Heart Association (NYHA) heart failure
PublicationAccording to the European Society of Cardiology, globally the number of patients with heart failure nearly doubled from 33.5 million in 1990 to 64.3 million in 2017, and is further projected to increase dramatically in this decade, still remaining a leading cause of morbidity and mortality. One of the most frequently applied heart failure classification systems that physicians use is the New York Heart Association (NYHA) Functional...
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Petrophysical analyses of rock construction materials from the Roman rural settlement in Podšilo bay on Rab island (NE Adriatic, Croatia)
PublicationThis article presents the results of petrophysical analyses of limestones and sandstones used for the construction of the wall structures of a Roman rural settlement located in Podšilo Bay on Rab Island (Croatia). An on-site analysis of the walls indicated the use of different lithotypes, which is an uncommon case in the area. So far, no petrophysical properties of the applied materials have been tested, and their provenance...
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Research on the Use of Mobile Devices and Headphones on Pedestrian Crossings—Pilot Case Study from Slovakia
PublicationThe topic of the use of mobile devices and headphones on pedestrian crossings is much less explored in comparison to the use of the mobile phone while driving. Recent years have seen many discussions on this issue, especially in foreign countries. The Slovak Republic, however, has not been giving it enough attention (and it is not mentioned in the National Road Safety Plan for the Slovak Republic from 2011 to 2020). This paper...
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Elemental and water-insoluble organic carbon in Svalbard snow: a synthesis of observations during 2007–2018
PublicationLight-absorbing carbonaceous aerosols emitted by biomass or fossil fuel combustion can contribute to amplifying Arctic climate warming by lowering the albedo of snow. The Svalbard archipelago, being near to Europe and Russia, is particularly affected by these pollutants, and improved knowledge of their distribution in snow is needed to assess their impact. Here we present and synthesize new data obtained on Svalbard between 2007...