cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.57745/bc1efa
title: PASHA (PedAgogic StocHastic data Assimilation)

description: The global structure of the package is mainly composed of a model class which implements the model and a DAscheme class which implements the data assimilation method that is used. The model class is composed of a set of methods allowing to initialize the model, to propagate it on one or several consecutive time steps and to update the initial conditions and/or the parameters for the next assimilation cycle. The DAscheme class allows to drive the whole assimilation experiment by performing alternating prediction and analysis steps. Different variants of the Kalman filter are integrated in the form of classes inheriting from DAscheme: EnKF (two integrated variants: Ensemble Transform Kalman Filter (Bishop et al. 2001) and stochastic version of EnKF as proposed in Burgers et al. 1998), ES ES-MDA iEnKS For each of them, the analysis and DAfull methods are redefined according to the strategy used for the analysis and according to the type of assimilation considered (filter or fixed point smoother or fixed interval smoother with fixed interval). No numerical optimization has been done and the algorithms have been kept as compact and transparent as possible, which allows a better overview of the mathematical theory they implement. Moreover, an ObsInfo class allows to provide all the information related to the observations (values, frequency, observation operator, error covariance matrix,) and a Trajectory class allows to extract some values from the state vector to constitute temporal trajectories. The ObsInfo and Trajectory classes also include a set of methods facilitating the visualization of the temporal evolution of the set of observations and their errors. Finally, the PerfStudy class allows to compute a set of of metrics allowing to evaluate the quality of the assimilation results in relation to a reference trajectory (bias, RMSE, dispersion, CRPS).
DOI: 10.15468/dl.h2maam
title: Occurrence Download

description: A dataset containing 132055 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Spain",
 "OccurrenceStatus is Present",
 "TaxonKey is Vulpes",
 "Year 2020-2025"
 ]
}

 The dataset includes 132055 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007529-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kmgv5s
title: Occurrence Download

description: A dataset containing 1395 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cerastes cerastes"
 ]
}

 The dataset includes 1395 records from 63 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007546-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vpjmgd
title: Occurrence Download

description: A dataset containing 132 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-78.18005 -7.02761,-78.05957 -7.02761,-78.06314 -6.8867,-78.06136 -6.88521,-78.18028 -6.88521,-78.18005 -7.02761))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "IucnRedListCategory is one of (NT, VU)",
 "OccurrenceStatus is Present",
 "TaxonKey is Animalia",
 "Year 2010-2025"
 ]
}

 The dataset includes 132 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007547-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.30705179
title: <b>Multi-dimensional Resource Synergy and Coded Computation Theory for 6G Satellite-Terrestrial Integrated Networks</b>

description: <b>Multi-dimensional Resource Synergy and Coded Computation Theory for 6G Satellite-Terrestrial Integrated Networks</b>
DOI: 10.6084/m9.figshare.30705179.v1
title: <b>Multi-dimensional Resource Synergy and Coded Computation Theory for 6G Satellite-Terrestrial Integrated Networks</b>

description: <b>Multi-dimensional Resource Synergy and Coded Computation Theory for 6G Satellite-Terrestrial Integrated Networks</b>
DOI: 10.5281/zenodo.17710691
title: Raw Data: Google Trends Search Interest and Related Queries for 'Janda' and 'Duda' in Indonesia (2024-2025)

description: This repository contains the raw dataset extracted from Google Trends to support a research article titled "Digital Search Trend Disparity: A Comparative Analysis of 'Janda' and 'Duda' Keywords on Google Trends Indonesia from a Muted Group Theory Perspective."

The dataset provides empirical evidence of gender disparity in digital search behaviors. It includes comparative data on search interest volume (0-100 index) and related queries (top and rising keywords) for the terms 'Janda' (Widow) and 'Duda' (Widower).
DOI: 10.15468/dl.c3chj4
title: Occurrence Download

description: A dataset containing 694 species occurrences available in GBIF matching the query:
{
 "InstitutionCode" : [
 "is one of (Glasgow Art Gallery and Museum, UK, GLAM)"
 ]
}

 The dataset includes 694 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007549-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.34740/kaggle/dsv/13863542
title: Peer-to-Peer Boliviano (BOB) Exchange Data
DOI: 10.57745/5tdka4
title: Transcriptome assembly, open reading frames (ORF) predictions and protein catalogues of two aquatic sentinel species : Palaemon serratus and Dreissena polymorpha

description: This dataset comprises RNA sequences from two well-established aquatic sentinel species, Dreissena polymorpha (a mollusk bivalve) and Palaemon serratus (a crustacean decapod), which are commonly used as bioindicators of environmental health. In addition, the dataset included the prediction of open reading frames (ORFs) of these reference transcriptomes, which can aid in the interpretation of mass spectra during proteogenomic analyses.
DOI: 10.15468/dl.hqqsya
title: Occurrence Download

description: A dataset containing 921 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cerastes vipera"
 ]
}

 The dataset includes 921 records from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007551-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.c4vprk
title: Occurrence Download

description: A dataset containing 37475 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lycium barbarum"
 ]
}

 The dataset includes 37475 records from 659 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007550-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2me8ny
title: Occurrence Download

description: A dataset containing 2 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Kazakhstan",
 "Geometry POLYGON((55.85277 42.24421,92.14723 42.24421,92.14723 56.75579,55.85277 56.75579,55.85277 42.24421))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Oxytropis subverticillaris"
 ]
}

 The dataset includes 2 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006407-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15480/882.16527
title: Plate separation test results for reconstituted illite and plane metal surfaces

description: This data set contains 144 maximum separation resistance values from plate separation tests of reconstituted illite on plane metal surfaces. Currently, only the peak, maximum values are provided, which lay the groundwork for the statistical evaluation of the full factorial design within the ANOVA framework. This repository will be continuously expanded, providing more information about the soil, the test stand, and sample preparation. Finally, the resulting test curves for time, displacement, and stress will be provided. Publications of interest will be linked, explaining the factorial design and providing further insights into the related project.
DOI: 10.14457/tu.the.2025.47
title: Capacitated vehicle routing problems with heterogeneous fleet

description: This independent study focuses on solving the Capacitated Vehicle Routing Problem for a beverage distributor in Thailand, addressing the challenges posed by heterogeneous fleet vehicles, limited driver working hours, and customer-specific time windows. The study aims to minimize logistics costs by optimizing delivery routes and schedules. The mathematical model formulated in this project considers multiple constraints, such as vehicle capacity, demand at each customer location, and time limitations, and aims to find the optimal routes for a fleet of three types of trucks: small 4-wheelers, big 4-wheelers, and 6-wheelers. The research first applies a mixed-integer linear programming model to small-scale problems to achieve optimal solutions, followed by the development of heuristics for large-scale problems, where exact solutions may not be computationally feasible. The results, derived from data collected from a real beverage distributor’s operations in the Eastern part of Thailand, demonstrate the potential of this approach to reduce operational costs and improve logistical efficiency. The study concludes that the proposed methods can effectively manage complexities of heterogeneous fleets, providing a practical solution to the logistics challenges faced by beverage distributors in the region.
DOI: 10.14457/tu.the.2025.48
title: The essential factors to develop the technological capability and innovation of the Thai manufacturing sector under industry 4.0

description: Industry 4.0 is revolutionizing global industries by integrating advanced information and communication technologies, enabling enhanced interaction among production systems. The integration of emerging technologies, notably the Internet of Things (IoT), robotics, and artificial intelligence (AI), has unlocked unprecedented opportunities for efficiency and innovation. However, these technological transformations also present significant challenges, particularly in workforce preparedness. In Thailand, traditional human resource development (HRD) approaches often fail to meet the demands of this industrial revolution.This thesis undertakes an empirical investigation into the stages of Industry 4.0 adoption and examines the factors influencing the adoption of digital technology. Key factors examined include leadership, business constraints, technological readiness, and workforce preparedness. The limited research on HRD and its role in Industry 4.0 adoption underscores the need to develop a robust framework that supports manufacturers in transitioning to this new industrial paradigm.To address these challenges, this study adopts a mixed-methods approach. The research begins with qualitative case studies of five Thai manufacturing firms, each at different stages of Industry 4.0 adoption. Semi-structured interviews with executives and HR managers offer valuable insights into the challenges and strategies of HRD within this context. These qualitative findings inform the development of a survey distributed to firms in Thailand’s manufacturing sector during the quantitative phase. Partial least squares structural equation modeling (PLS-SEM) is employed to examine the relationships between business constraints, leadership support, human resource development (HRD), and technological readiness. The PLS-SEM results demonstrate a significant impact of business constraints on leadership support and human resource development (HRD). Additionally, leadership and strategic HRD play a crucial role in driving a firm's technological readiness.The findings of this study offer valuable insights into digital transformation in the manufacturing sector. Practical recommendations are provided to enhance Industry 4.0 readiness in Thai industries. The research emphasizes the importance of HRD frameworks that anticipate future challenges, offering targeted training and development resources. These frameworks integrate leadership development, technological training, and employee engagement, ensuring workforce agility and adaptability in the face of rapid technological change. The combination of effective leadership, a prepared workforce, and strategic HRD initiatives is pivotal for achieving successful digital transformation under Industry 4.0.
DOI: 10.14457/tu.the.2025.49
title: Machine learning for retinal health classification of optical coherence tomography images

description: Optical Coherence Tomography (OCT) is an essential imaging technique for diagnosing retinal diseases. While deep learning models offer high accuracy for automated OCT classification, their “black-box” nature limits clinical trust and adoption. Conversely, traditional machine learning methods are more interpretable but often depend on features that can be difficult to extract or are sensitive to image quality. This thesis presents two complementary studies to develop an accurate and interpretable machine learning framework for retinal health classification.The first study introduces a method based on extracting computationally simple and clinically intuitive geometric features—specifically foveal concavity, bilateral symmetry, and layer smoothness—from the Inner Limiting Membrane (ILM) and Retinal Pigment Epithelium (RPE) layers. Using a Light Gradient Boosting Machine (LGBM) classifier, this approach achieved 96% accuracy, 98% precision, and a low false negative rate of 6%, significantly out performing a baseline method using vertical line profile features.The second study expands this analysis by extracting a comprehensive set of 56 features derived from the thickness, area, and inter-layer relationships of seven segmented retinal layers. This layer-wise approach, while achieving a slightly lower binary classification accuracy of 93.5% on the test set, demonstrated robust performance and provided deeper clinical insights. Through interpretable models, this analysis revealed a hierarchical pattern of retinal deterioration. Key predictive features included the area ratio of specific layers to the total retina and thickness ratios between adjacent layers, offering a more granular understanding of disease mechanisms.Together, these studies demonstrate that analyzing retinal layer morphology, from simple geometries to complex inter-layer dynamics, provides a powerful and transparent framework for automated disease detection. The proposed methods support ophthalmologists by improving diagnostic accuracy and efficiency, contributing to the early detection and prevention of vision loss. The initial geometric approach is ideal for rapid pre-screening, while the layer-wise analysis enhances diagnostic insight by uncovering specific, clinically meaningful patterns of pathology.
DOI: 10.5281/zenodo.18228317
title: Data

description: The data provided are as follows:

(1) Overall Frugivory rate for the 11 months

(2) Audio data extraction for Brise Fer and Mare Longue

(3) Detection rate of each species

(4) Acoustic index for each month per site and forest type

(5) Median Acoustic index combined for each site and forest type

(6) Master sheet: Attack rate, canopy cover for each tree, Acoustic indices, overall detection
DOI: 10.5281/zenodo.18228318
title: Data

description: The data provided are as follows:

(1) Overall Frugivory rate for the 11 months

(2) Audio data extraction for Brise Fer and Mare Longue

(3) Detection rate of each species

(4) Acoustic index for each month per site and forest type

(5) Median Acoustic index combined for each site and forest type

(6) Master sheet: Attack rate, canopy cover for each tree, Acoustic indices, overall detection
DOI: 10.15468/dl.ek438s
title: Occurrence Download

description: A dataset containing 2814 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-11.7729 34.89626,43.59189 34.89626,43.59189 71.8535,-11.7729 71.8535,-11.7729 34.89626))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Octolasion lacteum"
 ]
}

 The dataset includes 2814 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0006408-260120142942310/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.2908/prc_hicp_admp
title: Harmonisierter Verbraucherpreisindex - ECOICOP ver.2 - Administrierte Preise Zusammensetzung
title: Indice des prix à la consommation harmonisé (IPCH) - ECOICOP ver.2 – composition des prix administrés
title: Harmonised index of consumer prices (HICP) - ECOICOP ver.2 - administered prices composition
DOI: 10.2908/prc_hicp_cw
title: Harmonisierter Verbraucherpreisindex - ECOICOP ver.2 – Ländergewichte
title: Indice des prix à la consommation harmonisé (IPCH) - ECOICOP ver.2 - pondération des pays
title: Harmonised index of consumer prices (HICP) - ECOICOP ver.2 - country weights
DOI: 10.2908/prc_hicp_iw
title: Harmonised index of consumer prices (HICP) - ECOICOP ver.2 - item weights
title: Indice des prix à la consommation harmonisé (IPCH) - ECOICOP ver.2 - pondération des indices
title: Harmonisierter Verbraucherpreisindex - ECOICOP ver.2 - Gewichte der Indizes
DOI: 10.14457/tu.the.2025.50
title: Warehouse selection: a hybrid fuzzy multi-criteria decision-making approach

description: Warehouse location selection requires the consideration of multiple, often conflicting criteria such as cost, space availability, and accessibility, as the warehouse itself plays a critical role in optimizing logistics costs and enhancing customer service. To accommodate the selection efforts, this study presents an integrated fuzzy multi-criteria decision-making approach that combines the Fuzzy Best-Worst Method (FBWM) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to identify the most suitable warehouse location. The former is employed to determine the relative weights of criteria, taking into account the uncertainty inherent in expert judgments, while the later is used to rank the alternative locations with respective to the criteria and its weights.A case study, which involves three warehouse alternatives evaluated based on area, rental rate, and distance to the airport is conducted to demonstrate the effectiveness of the proposed method. Closeness coefficients were calculated across multiple methodological configurations using three normalization techniques (linear vector, linear sum, and max) and two distance metrics (Euclidean and Manhattan). To further explore the robustness of the rankings, combinations of weight generated using a complementary weighting strategy was experimented. From a discrete set of weights ranging from 0.05 to 0.90, a total of 5,832 possible combinations were generated. Two filtering conditions were applied to eliminate invalid weight combinations: all the weights must sum to one, and the weight for the rental cost criterion must be the largest one. This process yielded 45 valid weight combinations. These combinations of weight were later put into usage to evaluate the consistency of ranking outcomes.Sensitivity and robustness analyses reveal that the top-ranked warehouse (Alternative S2) consistently outperforms others regardless of methodological configurations and weights combinations. This confirms the reliability of the decision. In addition, Analysis of variance (ANOVA) results indicate that both weight combinations and distance metrics significantly affect the closeness coefficient (〖CC〗_i), while the normalization method shows minimal impact. Moreover, Manhattan distance provides higher discrimination among alternatives, whereas Euclidean distance offers more stable and consistent rankings. Overall, the proposed approach is robust and practical, providing decision-makers with a clear and reliable framework for selecting warehouse locations.
DOI: 10.14457/tu.the.2025.51
title: Demand forecasting in the supply chain: case study of a Bangladeshi retailer

description: This study aims to forecast daily sales using time series analysis through two models: Holt-Winters and ARIMA. A real dataset containing 1,826 consecutive days of sales data was used as the basis for analysis. The first model, Holt-Winters, was optimized by adjusting parameters for level, trend, and seasonality to achieve the lowest possible MAPE. Subsequently, ARIMA (4,1,1) models were developed using Minitab software. Forecasted values from each model were compared against the actual sales values to compute the Mean Absolute Percentage Error (MAPE), which was used as the main metric for evaluating forecasting accuracy. The results showed that the Holt-Winters model achieved the lowest MAPE of 22.04, indicating the highest accuracy among the two models. These findings suggest that the Holt-Winters method is a suitable approach for short-term sales forecasting in daily time series data. This study provides useful insights for improving forecasting in business operations, especially for production planning and inventory management.
DOI: 10.14457/tu.the.2025.52
title: Fuzzy optimization for supply chain planning under uncertain environments

description: This thesis develops advanced fuzzy optimization models to strengthen resilience in Supply Chain Aggregate Production Planning (SCAPP) by addressing uncertainties inherent in modern supply chains. Utilizing fuzzy logic, the model integrates uncertain parameters such as fluctuating demand, variable supplier reliability, and operational disruptions, providing approaches to managing unpredictability. This innovative framework is designed to tackle multiple conflicting objectives simultaneously, including cost minimization, resource allocation optimization, and risk mitigation, thereby enabling decision-makers to achieve balanced and efficient SCAPP. This advancement marks a departure from conventional approaches, which frequently focus on static assumptions and single-objective optimization. By systematically quantifying uncertainties, the model ensures that supply chain strategies remain robust against external shocks and internal variabilities. Its ability to provide adaptive solutions to unexpected scenarios demonstrates its relevance in industries where supply chains face frequent disruptions due to market volatility, global uncertainties, and rapid technological changes. The empirical results confirm that the proposed models enhance operational efficiency, reduce the risk of cost fluctuations, and improve resource utilization, making it a valuable tool for businesses aiming to maintain stability in volatile environments. By bridging the gap between theoretical advancements and practical applications, this study contributes to both scholarly discourse and industry practice, emphasizing the importance of adaptable and scalable solutions in dynamic supply chain environments.The findings of this thesis go beyond theoretical advancements, offering practical insights that empower supply chain managers to make more informed and effective decisions. By addressing real-world complexities, the model demonstrates its versatility and applicability across various industries, serving as a crucial tool for organizations aiming to achieve both operational efficiency and long-term sustainability. Additionally, this research lays a strong foundation for future studies, encouraging the exploration of more advanced fuzzy optimization models and further integration of risk mitigation strategies into SCAPP frameworks.