The pandemic has led to the production and accumulation of various types of data related to coronavirus disease 2019 (COVID-19). To understand the features and characteristics of COVID-19 data, we summarized representative databases and determined th...
A multifunctional weir was built on the Nakdong River. As a result, changes in the river environment occurred, such as an increase in river residence time. This causes changes in water quality, including green algae. The occurrence of green algae in...
This study examined the relationships between financial literacy, financial product ownership, confidence in financial advisers, and confidence in retirement readiness across Estonia, Latvia, and Lithuania. By using data from the Flash Eurobarometer...
We established a universality of logarithmic loss over a finite alphabet as a distortion criterion in fixed-length lossy compression. For any fixed-length lossy-compression problem under an arbitrary distortion criterion, we show that there is an equ...
We introduce a new approach to clustering categorical data: Condorcet clustering with a fixed number of groups, denoted
The present study explores the field of text classification in the Greek language. A novel ensemble classification scheme based on generated embeddings from Greek text made by the multilingual capabilities of the E5 model is presented. Our approach i...
Assessing genetic distinctness and redundancy is an important part of plant germplasm characterization. Over the last decade, such assessment has become more feasible and informative, thanks to the advances in genomic analysis. An attempt was made he...
Manufacturing polypropylene (PP) composites to meet customers’ needs is difficult, time-consuming, and costly, owing to the ever-increasing diversity and complexity of the corresponding specifications and the trial-and-error method currently us...
In deep engineering, rockburst hazards frequently result in injuries, fatalities, and the destruction of contiguous structures. Due to the complex nature of rockbursts, predicting the severity of rockburst damage (intensity) without the aid of comput...
The pervasive presence of artificial intelligence (AI) in our everyday life has nourished the pursuit of explainable AI. Since the dawn of AI, logic has been widely used to express, in a human-friendly fashion, the internal process that led an (intel...
COVID-19 has hit the hotel sector in a hitherto unknown way. This situation is producing a fundamental change in client behavior that makes crucial an adequate knowledge of their profile to overcome an uncertain environment. Customer Relationship Man...
Individual subjects’ ratings neither are metric nor have homogeneous meanings, consequently digital- labeled collections of subjects’ ratings are intrinsically ordinal and categorical. However, in these situations, the literature privileg...
The world population will reach 9.8 billion by 2050, with increased urbanization. Cycling is one of the fastest developing sustainable transport solutions. With the spread of public bike sharing (PBS) systems, it is very important to understand the d...
The dismantled components of retired oil-immersed power transformers, particularly the windings and core, have high recycling economic value. However, accurately estimating their weight based solely on nameplate information prior to disassembly remai...
Although the application of new wake turbulence categories, the so-called “RECAT (wake turbulence category re-categorization)”, will realize lower aircraft separation minima and directly increase runway throughput, the impacts of increasing arrival t...
Natural resource assets inherently integrate tripartite synthesis of legal, economic, and ecological attributes. They serve dual critical functions as foundational elements supporting the evolution of new-quality productive forces and pivotal mechani...
Loeys-Dietz syndrome (LDS) is a connective tissue disorder first described in 2005 featuring aortic/arterial aneurysms, dissections, and tortuosity associated with craniofacial, osteoarticular, musculoskeletal, and cutaneous manifestations. Heterozyg...
Deep-seated gravitational slope deformations (DsGSDs) are slope-scale phenomena which are widespread in mountainous regions. Despite interacting with human infrastructures and settlements, only a few cases are monitored with ground-based systems. Rem...
It is known that artificial intelligence algorithms are based on calculations performed using various mathematical operations. In order for these calculation processes to be carried out correctly, some types of data cannot be fed directly into the al...
In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary...
This study introduces deep convolutional neural network-based methods for the detection and classification of skin lesions, enhancing system accuracy through a combination of architectures, pre-processing techniques and data augmentation. Multiple ne...
We develop Categorical Exploratory Data Analysis (CEDA) with mimicking to explore and exhibit the complexity of information content that is contained within any data matrix: categorical, discrete, or continuous. Such complexity is shown through visib...
Categorical data analysis becomes challenging when high-dimensional sparse covariates are involved, which is often the case for omics data. We introduce a statistical procedure based on multinomial logistic regression analysis for such scenarios, inc...
As key technologies of the fourth industrial revolution, blockchain and digital twins have great potential to enhance collaboration, data sharing, efficiency, and sustainability in the construction industry. Blockchain can improve data integrity and...
This paper presents a nonparametric regression model of categorical time series in the setting of conditional tensor factorization and Bayes network. The underlying algorithms are developed to provide a flexible and parsimonious representation for fu...
Forecasting hydraulic data such as pressure and demand in water distribution system (WDS) is an important task that helps ensure efficient and accurate operations. Despite high-performance data prediction, missing data can still occur, making it diff...
Manufacturers are struggling to use data from multiple products production lines to predict rare events. Improving the quality of training data is a common way to improve the performance of algorithms. However, there is little research about how to s...
Interaction between variables is often found in statistical models, and it is usually expressed in the model as an additional term when the variables are numeric. However, when the variables are categorical (also known as nominal or qualitative) or m...
Recently, local governments have been using transportation card data to monitor the use of public transport and improve the service. However, local governments that are applying a single-fare scheme are experiencing difficulties in using data for acc...
Land cover (LC) products, derived primarily from satellite spectral imagery, are essential inputs for environmental studies because LC is a critical driver of processes involved in hydrology, ecology, and climatology, among others. However, existing...
A new tool is presented for facilitating greater objectivity in the chaotic field of genocide studies: first, assembling the available factual data about any event of mass murder systematically; second, contextualizing each of our judgments of the na...
Classification and clustering problems are closely connected with pattern recognition where many general algorithms have been developed and used in various fields. Depending on the complexity of patterns in data, classification and clustering procedu...
Standardization of radiotherapy structure names is essential for developing data-driven personalized radiotherapy treatment plans. Different types of data are associated with radiotherapy structures, such as the physician-given text labels, geometric...
Scale effects are inherent in spatial analysis. Quantitative knowledge about them is necessary for properly interpreting and scaling analysis results. The objective of this study was to systematically model patch area scaling and the associated uncer...
In this paper, we propose a general mathematical model for analyzing yield data. The data analyzed in this paper come from a characteristic corn field in the upper midwestern United States. We derive expressions for statistical moments from the under...
The so-called proportional odds assumption is popular in cumulative, ordinal regression. In practice, however, such an assumption is sometimes too restrictive. For instance, when modeling the perception of boar taint on an individual level, it turns...
This paper describes a new method for testing randomized clinical trials with binary outcomes, which combines the O’Brien and Fleming (1979) multiple-testing procedure with optimal allocations and unequal weighted samples simultaneously. The O&...
In square contingency table analysis, we consider a partial measure that represents the degree of departure from symmetry for each of several pairs. It may be useful to pool the values of the measure into a single summary measure of partial asymmetry...
With the increasing importance of offshore wind turbines, a critical issue in their construction is the high-performance concrete (HPC) used for grouting underwater foundations, as such materials must be better able to withstand the extremes of the s...
International agreements require reducing and eliminating the exclusion faced by persons with disabilities. Achieving this goal depends on having reliable data on persons with disabilities, yet a wide variety of instruments are used to identify who i...
Background: The Hungarian Science Bibliography applies the OECD Frascati Fields of Science and Technology taxonomy for subject classification; however, approximately 80% of its records lack assigned categories. Automated large-scale classification co...
Background/Objectives: Childhood interstitial lung disease (chILD) represents a heterogeneous group of rare pulmonary disorders. Practical diagnostic approaches tested for feasibility and impact in comprehensive cohorts are lacking. We aimed to asses...
Type 2 diabetes, prediabetes, and insulin resistance (IR) are widespread yet often undetected in their early stages, contributing to a silent epidemic. Metabolic Syndrome (MetS) is also highly prevalent, increasing the chronic disease burden. Annual...
This data descriptor documents a two-level genre classification scheme for metal-music corpus studies derived from Encyclopaedia Metallum’s multi-label genre strings. The scheme assigns each band to one of eleven mutually exclusive primary buck...
This work combines the Urn allocation and O’Brien and Fleming multiple testing procedure to compare two treatments in clinical trials in a novel way. It is shown that this approach overcomes the constraints that previously made it challenging t...
Nowadays, with the rapid growth of the internet of things (IoT), massive amounts of time series data are being generated. Time series data play an important role in scientific and technological research for conducting experiments and studies to obtai...
This study introduces a new method that combines three distinct approaches for comparing two treatments: Neyman allocation, the O’Brien and Fleming multiple testing procedure, and a system of different sample weights at different stages. This n...
The quality of teacher education represents a fundamental pillar for effective educational systems. European and Czech educational policies emphasise alignment with labour market demands and continuous professional development of teachers. This study...
According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) syste...
According to literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) systems, where...
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