2023 September - 10 articles
Conservation management heavily relies on accurate species distribution data. However, distributional information for most species is limited to distributional range maps, which could not have enough resolution to take conservation action and know cu...
In this article, we pioneer a new Burr X distribution using the odd beta prime generalized (OBP-G) family of distributions called the OBP-Burr X (OBPBX) distribution. The density function of this model is symmetric, left-skewed, right-skewed, and rev...
Harmonized composition data for foods and dietary supplements are needed for research and for policy decision making. For a correct assessment of dietary intake, the categorization and the classification of food products and dietary supplements are n...
Sustainable water quality data are important for understanding historical variability and trends in river regimes, as well as the impact of industrial waste on the health of aquatic ecosystems. Sustainable water management practices heavily depend on...
The availability of code snippets in online repositories like GitHub has led to an uptick in code reuse, this way further supporting an open-source component-based development paradigm. The likelihood of code reuse rises when the code components or s...
Nowadays, new branches of research are proposing the use of non-traditional data sources for the study of migration trends in order to find an original methodology to answer open questions about cross-border human mobility. New knowledge extracted fr...
This study investigates the application of various machine learning models for land use and land cover (LULC) classification in the Kerch Peninsula. The study utilizes archival field data, cadastral data, and published scientific literature for model...
At present, the energy landscape of many countries faces transformational challenges driven by sustainable development objectives, supported by the implementation of clean technologies, such as renewable energy sources, to meet the flexibility and di...
This data description introduces a comprehensive knowledge graph (KG) dataset with detailed information about the relevant high-level semantics of visual stimuli used to induce emotional states stored in the Nencki Affective Picture System (NAPS) rep...
This study addressed the challenge of training generative adversarial networks (GANs) on small tabular clinical trial datasets for data augmentation, which are known to pose difficulties in training due to limited sample sizes. To overcome this obsta...
