cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/chvz7vh2dc
title: Annotated Drowsiness Detection Dataset Captured Using Raspberry Pi 5

description: Research Hypothesis:
This study hypothesizes that drowsiness can be accurately detected in real-time through computer vision analysis of facial features, specifically eye closure patterns and yawning behavior, using affordable edge computing devices like the Raspberry Pi 5.

Data Collection Methodology:
The dataset was recorded using a Raspberry Pi 5 equipped with a Camera Module 3. All recordings were captured at a consistent frame rate of 30 frames per second (FPS) and a resolution of 640×480 pixels, utilizing H.264 compression for video encoding. The recordings cover various lighting conditions with differing lux levels to simulate real-world scenarios ranging from low-light conditions (e.g., nighttime environments) to bright daylight settings.

Dataset Composition and Labeling:
The dataset includes labeled categories essential for training and testing machine learning models. Labeling was performed using Edge Impulse, with the following categories:

Open Eyes: 968 training samples, 225 testing samples (Total: 1,193)
Closed Eyes: 158 training samples, 49 testing samples (Total: 207)
No Yawning: 496 training samples, 124 testing samples (Total: 620)
Yawning: 60 training samples, 12 testing samples (Total: 72)
Video-wise Annotation Data:
The dataset also contains detailed video-wise annotations for testing purposes:

Open Eyes (mata_terbuka): 30,922 testing samples
Closed Eyes (mata_tertutup): 4,662 testing samples
No Yawning (tidak_menguap): 16,877 testing samples
Yawning (menguap): 1,019 testing samples

Notable Findings:
The data reveals a significant class imbalance, with open eyes representing 85.4% of image samples and 86.9% of video samples, while yawning behavior accounts for only 5.2% of image samples and 5.7% of video samples. This distribution reflects natural human behavior patterns where drowsiness indicators occur less frequently than alert states.

Data Interpretation and Usage:
This dataset can be used to train machine learning models for drowsiness detection applications, particularly in automotive safety systems or workplace monitoring. The class imbalance should be addressed through appropriate sampling techniques or weighted loss functions during model training. The multi-modal nature of the data (both image-based and video-based annotations) allows for both static image classification and temporal sequence analysis approaches. Researchers should consider the lighting condition variations when evaluating model performance across different deployment scenarios.
DOI: 10.17632/chvz7vh2dc.1
title: Annotated Drowsiness Detection Dataset Captured Using Raspberry Pi 5

description: Research Hypothesis:
This study hypothesizes that drowsiness can be accurately detected in real-time through computer vision analysis of facial features, specifically eye closure patterns and yawning behavior, using affordable edge computing devices like the Raspberry Pi 5.

Data Collection Methodology:
The dataset was recorded using a Raspberry Pi 5 equipped with a Camera Module 3. All recordings were captured at a consistent frame rate of 30 frames per second (FPS) and a resolution of 640×480 pixels, utilizing H.264 compression for video encoding. The recordings cover various lighting conditions with differing lux levels to simulate real-world scenarios ranging from low-light conditions (e.g., nighttime environments) to bright daylight settings.

Dataset Composition and Labeling:
The dataset includes labeled categories essential for training and testing machine learning models. Labeling was performed using Edge Impulse, with the following categories:

Open Eyes: 968 training samples, 225 testing samples (Total: 1,193)
Closed Eyes: 158 training samples, 49 testing samples (Total: 207)
No Yawning: 496 training samples, 124 testing samples (Total: 620)
Yawning: 60 training samples, 12 testing samples (Total: 72)
Video-wise Annotation Data:
The dataset also contains detailed video-wise annotations for testing purposes:

Open Eyes (mata_terbuka): 30,922 testing samples
Closed Eyes (mata_tertutup): 4,662 testing samples
No Yawning (tidak_menguap): 16,877 testing samples
Yawning (menguap): 1,019 testing samples

Notable Findings:
The data reveals a significant class imbalance, with open eyes representing 85.4% of image samples and 86.9% of video samples, while yawning behavior accounts for only 5.2% of image samples and 5.7% of video samples. This distribution reflects natural human behavior patterns where drowsiness indicators occur less frequently than alert states.

Data Interpretation and Usage:
This dataset can be used to train machine learning models for drowsiness detection applications, particularly in automotive safety systems or workplace monitoring. The class imbalance should be addressed through appropriate sampling techniques or weighted loss functions during model training. The multi-modal nature of the data (both image-based and video-based annotations) allows for both static image classification and temporal sequence analysis approaches. Researchers should consider the lighting condition variations when evaluating model performance across different deployment scenarios.
DOI: 10.5281/zenodo.15641336
title: Dataset of "Cobalt and nickel doped WSe2 as efficient electrocatalysts for water splitting and as cathodes in hydrogen evolution reaction PEM water electrolysis"

description: Efficient electrocatalysts are crucial for water splitting and fuel cells. Using cheap alternatives that can improve reaction kinetics is essntial for advancing fuel cell technology. Although, tungsten diselinide (WSe2) is promising for electrocatalysis is not fully explored, especially in oxygen evolution and in applications such as polymer electrolyte membrane water electrolyzer.In this work, we used a simple approach to dope WSe2 with cobalt and/or nickel atoms. The doped material was subsequently tested for hydrogen evolution reaction and oxygen evolution reaction. Accordingly, the two electrocatalysts are highly active and stable, affording low overpotentials comparable to those of noble metals. The effective introduction of heteroatoms causes the retention of coordination vacancies, furnishing active catalytic sites that enhanced electrocatalytic performance both in activity and charge transfer. Moreover, both doped materials show excellent performance and stability as cathode electrocatalysts in the polymer electrolyte membrane water electrolyzer with great promise for real-world applications.
DOI: 10.17632/3fgvzfkdg9
title: Keleghai data

description: VES data
DOI: 10.17632/3fgvzfkdg9.1
title: Keleghai data

description: VES data
DOI: 10.15468/dl.syxhrq
title: Occurrence Download

description: A dataset listing the 9 species recorded in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is one of (Allonais inaequalis (Stephenson, 1911), Allonais paraguayensis (Michaelsen, 1905))"
 ]
}

 The dataset's 9 records were derived from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036273-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57701/suf.rtzn.2017.1-0
title: Versichertenrentenzugang 2017
title: SUF
title: RTZN

description: Scientific Use File Versichertenrentenzugang (SUF.RTZN):Grundlage des Querschnittsdatensatzes SUF.RTZN ist die Rentenzugangsstatistik (§ 6 RSVwV, SK90). Die Grundgesamtheit des SUF.RTZN bilden Alters- und Erwerbsminderungsrenten, deren Rentenbeginn im Berichtjahr liegt. Die Größe der Zufallsstichprobe beträgt 20 Prozent. Berichtet wird neben demographischen Angaben über wichtige rentenrechtliche Sachverhalte wie beispielsweise Rentenhöhe, Komponenten des Rentenzahlbetrages, Entgeltpunkte sowie angerechnete versicherungsrechtliche Zeiten.
DOI: 10.15468/dl.ep2a2u
title: Occurrence Download

description: A dataset containing 15 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is China",
 "Geometry POLYGON((80 40,92 40,92 50,80 50,80 40))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Pterocles orientalis (Linnaeus, 1758)",
 "Year 2023-2025"
 ]
}

 The dataset includes 15 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036287-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13889801
title: Dataset of "Cobalt and nickel doped WSe2 as efficient electrocatalysts for water splitting and as cathodes in hydrogen evolution reaction PEM water electrolysis"

description: Efficient electrocatalysts are crucial for water splitting and fuel cells. Using cheap alternatives that can improve reaction kinetics is essntial for advancing fuel cell technology. Although, tungsten diselinide (WSe2) is promising for electrocatalysis is not fully explored, especially in oxygen evolution and in applications such as polymer electrolyte membrane water electrolyzer.In this work, we used a simple approach to dope WSe2 with cobalt and/or nickel atoms. The doped material was subsequently tested for hydrogen evolution reaction and oxygen evolution reaction. Accordingly, the two electrocatalysts are highly active and stable, affording low overpotentials comparable to those of noble metals. The effective introduction of heteroatoms causes the retention of coordination vacancies, furnishing active catalytic sites that enhanced electrocatalytic performance both in activity and charge transfer. Moreover, both doped materials show excellent performance and stability as cathode electrocatalysts in the polymer electrolyte membrane water electrolyzer with great promise for real-world applications.
DOI: 10.5281/zenodo.13889802
title: Dataset of "Cobalt and nickel doped WSe2 as efficient electrocatalysts for water splitting and as cathodes in hydrogen evolution reaction PEM water electrolysis"

description: Efficient electrocatalysts are crucial for water splitting and fuel cells. Using cheap alternatives that can improve reaction kinetics is essntial for advancing fuel cell technology. Although, tungsten diselinide (WSe2) is promising for electrocatalysis is not fully explored, especially in oxygen evolution and in applications such as polymer electrolyte membrane water electrolyzer.In this work, we used a simple approach to dope WSe2 with cobalt and/or nickel atoms. The doped material was subsequently tested for hydrogen evolution reaction and oxygen evolution reaction. Accordingly, the two electrocatalysts are highly active and stable, affording low overpotentials comparable to those of noble metals. The effective introduction of heteroatoms causes the retention of coordination vacancies, furnishing active catalytic sites that enhanced electrocatalytic performance both in activity and charge transfer. Moreover, both doped materials show excellent performance and stability as cathode electrocatalysts in the polymer electrolyte membrane water electrolyzer with great promise for real-world applications.
DOI: 10.15468/dl.v2rk99
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Strongylopus bonaespei (Dubois, 1981)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.628 -23.023,35.6007 -22.9702,35.6007 -23.165,35.628 -23.023))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036286-250525065834625/datasets/export for details.
DOI: 10.17632/p7nw36tbbf
title: Transfer function

description: Original transfer function data for the manuscript "Estimation of temporal variation in seismic wave velocity using coda wave interferometry with an accurately controlled seismic source"
This dataset contains transfer function data obtained through the ACROSS (Accurately Controlled Routinely Operated Signal System). The dataset consists of transfer function data processed according to the methodology described in Section 2.2. Each seismometer in the array provides six-component transfer functions. Each .mat file contains transfer function data derived from two-hour continuous recordings. Considering the large volume of content, I have uploaded one month of data from October 14 to November 13, 2020.
DOI: 10.15468/dl.673upg
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is one of (India, China, Myanmar, Nepal, Bhutan, Bangladesh, Pakistan, Afghanistan)",
 "TaxonKey is Colias alpherakii Staudinger, 1882"
 ]
}

 The dataset includes 5 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036289-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/p7nw36tbbf.2
title: Transfer function

description: Original transfer function data for the manuscript "Estimation of temporal variation in seismic wave velocity using coda wave interferometry with an accurately controlled seismic source"
This dataset contains transfer function data obtained through the ACROSS (Accurately Controlled Routinely Operated Signal System). The dataset consists of transfer function data processed according to the methodology described in Section 2.2. Each seismometer in the array provides six-component transfer functions. Each .mat file contains transfer function data derived from two-hour continuous recordings. Considering the large volume of content, I have uploaded one month of data from October 14 to November 13, 2020.
DOI: 10.17632/5wchkgbv3v.1
title: Exploring the Impact of Virtual Reality on Modern Commerce Business: A Bibliometric Study

description: Exploring the Impact of Virtual Reality on Modern Commerce Business: A Bibliometric Study
DOI: 10.15468/dl.2jgds4
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Strongylopus bonaespei (Dubois, 1981)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "BasisOfRecord is one of (Specimen, Living Specimen, Observation, Human Observation, Machine Observation, Material sample, Literature Occurrence, Material citation, Occurrence evidence)",
 "Geometry POLYGON ((35.6306 -23.844,35.6007 -23.8125,35.6007 -24.0157,35.6306 -23.844))"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036291-250525065834625/datasets/export for details.
DOI: 10.25824/redu/w8hzzw
title: Inventaire iconographique de Mesdames, filles de Louis XV (1727–1802)

description: Cet inventaire est issu de la thèse « Portraits de Mesdames : une étude de l’iconographie des filles de Louis XV, suivie de son inventaire » (Retratos de Mesdames : um estudo da iconografia das filhas de Luís XV, seguido de seu inventário), soutenue à l’Université de Campinas le 11 avril 2025, avec le soutien de la FAPESP (nº 2017/14530-2 et 2019/00109-9). Parmi les huit filles de Louis XV, six atteignirent l’âge adulte et formèrent un groupe durablement présent à la cour, inspirant une iconographie abondante qui s'étendit au-delà du XVIIIᵉ siècle. Cet inventaire, aussi complet que possible dans le cadre de la recherche, recense portraits originaux, copies et répliques produits entre 1727 et 1802. La recherche s’est appuyée sur la bibliographie existante et de nombreuses sources primaires, notamment les archives des Bâtiments du roi, des Menus-Plaisirs du roi, des Affaires étrangères et de la Maison de Mesdames. Outre l'inventaire, cet ensemble de données contient une table des portraits des filles de Louis XV commandés par les Menus-Plaisirs du roi, d'après les sources primaires des Archives nationales.
DOI: 10.17632/xsrmpn6ntt
title: LC-MS/MS Raw Files: Anthocyanin identification from mixed flavonoid populations in flowers by positive and negative mode LC-MS/MS

description: This data set includes the raw files for methanolic extracts of Clitoria ternatea and Viola sororia run in LC-MS/MS which we obtained for the purpose of qualitatively identifying anthocyanin and flavonol molecules present in such flowering plants. Anthocyanins are the primary pigments found in flowers and fruits and we aim to develop a rapid and sensitive mass spectrometry-based workflow to identify anthocyanins and their sugar an acyl substituents and differentiate them from a mixed flavonoid population. Targeting anthocyanins and flavonols, we first searched the MS1 data for high-mass (&gt;300 Da) chromatographic peaks in the 5-12.5 minute region of our gradient where we expected such molecules to elute. After identifying potential peaks, we then searched the MS2 spectra associated with these peaks, based on the apparent parent mass in the MS1 domain, looking for obvious signs of anthocyanidin or flavonol aglycone fragments, which appear prominently under our fragmentation scheme below ∼350 Da. Once parent adducts and associated MS2 spectra were assigned, we then manually annotated the fragmentation spectra based on observed losses associated with various sugar or acid moieties being cleaved from the central aglycone structure.
DOI: 10.17632/xsrmpn6ntt.1
title: LC-MS/MS Raw Files: Anthocyanin identification from mixed flavonoid populations in flowers by positive and negative mode LC-MS/MS

description: This data set includes the raw files for methanolic extracts of Clitoria ternatea and Viola sororia run in LC-MS/MS which we obtained for the purpose of qualitatively identifying anthocyanin and flavonol molecules present in such flowering plants. Anthocyanins are the primary pigments found in flowers and fruits and we aim to develop a rapid and sensitive mass spectrometry-based workflow to identify anthocyanins and their sugar an acyl substituents and differentiate them from a mixed flavonoid population. Targeting anthocyanins and flavonols, we first searched the MS1 data for high-mass (&gt;300 Da) chromatographic peaks in the 5-12.5 minute region of our gradient where we expected such molecules to elute. After identifying potential peaks, we then searched the MS2 spectra associated with these peaks, based on the apparent parent mass in the MS1 domain, looking for obvious signs of anthocyanidin or flavonol aglycone fragments, which appear prominently under our fragmentation scheme below ∼350 Da. Once parent adducts and associated MS2 spectra were assigned, we then manually annotated the fragmentation spectra based on observed losses associated with various sugar or acid moieties being cleaved from the central aglycone structure.
DOI: 10.15468/dl.66mtnq
title: Occurrence Download

description: A dataset containing 5 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "Country is China",
 "Geometry POLYGON((80 40,92 40,92 50,80 50,80 40))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Crex crex (Linnaeus, 1758)",
 "Year 2022-2025"
 ]
}

 The dataset includes 5 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0036290-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57701/suf.rtzn.2018.1-0
title: Versichertenrentenzugang 2018
title: SUF
title: RTZN

description: Scientific Use File Versichertenrentenzugang (SUF.RTZN):Grundlage des Querschnittsdatensatzes SUF.RTZN ist die Rentenzugangsstatistik (§ 6 RSVwV, SK90). Die Grundgesamtheit des SUF.RTZN bilden Alters- und Erwerbsminderungsrenten, deren Rentenbeginn im Berichtjahr liegt. Die Größe der Zufallsstichprobe beträgt 20 Prozent. Berichtet wird neben demographischen Angaben über wichtige rentenrechtliche Sachverhalte wie beispielsweise Rentenhöhe, Komponenten des Rentenzahlbetrages, Entgeltpunkte sowie angerechnete versicherungsrechtliche Zeiten.
DOI: 10.17632/kvcfp5y95z
title: Multisensor Dataset for Alcohol Presence Detection (MQ-3, MQ-135, DHT22)

description: This dataset has 1,942 rows of sensor data collected to detect alcohol using MQ-3 and MQ-135 gas sensors and a DHT22 sensor for temperature and humidity. Data were gathered in both lab and indoor environments at East West University, Dhaka (23.7833°N, 90.3833°E). The MQ-3 sensor is sensitive to ethanol, while MQ-135 detects various gases. The DHT22 sensor measures the surrounding temperature and humidity. Alcoholic samples had ethanol levels between 5% and 30%, and non-alcoholic samples included water, tea, coffee, and soft drinks. A fixed process was followed for each test. Sensors were preheated for 24 to 48 hours. Each test began with a 10-second waiting time, followed by sensor readings every 30 seconds for 2.5 minutes. A clean air flush was done between samples to clear leftover gas. Each row in the dataset has values from MQ-3, MQ-135, temperature, humidity, and a label showing if alcohol was present (1) or not (0). Tests show that sensor values from MQ-3 and MQ-135 clearly differ when alcohol is present, while temperature and humidity do not show much change. Graphs such as box plots and PCA also show that the two classes are easy to tell apart based on sensor data. The dataset is balanced with 961 alcohol and 981 non-alcohol samples. It is useful for training machine learning models for alcohol detection in cars, workplaces, and portable devices. No people or animals were involved, and data collection followed research ethics.
Please cite the dataset using the following DOI if you use it in your work: 10.17632/kvcfp5y95z.1.
DOI: 10.17632/kvcfp5y95z.1
title: Multisensor Dataset for Alcohol Presence Detection (MQ-3, MQ-135, DHT22)

description: This dataset has 1,942 rows of sensor data collected to detect alcohol using MQ-3 and MQ-135 gas sensors and a DHT22 sensor for temperature and humidity. Data were gathered in both lab and indoor environments at East West University, Dhaka (23.7833°N, 90.3833°E). The MQ-3 sensor is sensitive to ethanol, while MQ-135 detects various gases. The DHT22 sensor measures the surrounding temperature and humidity. Alcoholic samples had ethanol levels between 5% and 30%, and non-alcoholic samples included water, tea, coffee, and soft drinks. A fixed process was followed for each test. Sensors were preheated for 24 to 48 hours. Each test began with a 10-second waiting time, followed by sensor readings every 30 seconds for 2.5 minutes. A clean air flush was done between samples to clear leftover gas. Each row in the dataset has values from MQ-3, MQ-135, temperature, humidity, and a label showing if alcohol was present (1) or not (0). Tests show that sensor values from MQ-3 and MQ-135 clearly differ when alcohol is present, while temperature and humidity do not show much change. Graphs such as box plots and PCA also show that the two classes are easy to tell apart based on sensor data. The dataset is balanced with 961 alcohol and 981 non-alcohol samples. It is useful for training machine learning models for alcohol detection in cars, workplaces, and portable devices. No people or animals were involved, and data collection followed research ethics.
Please cite the dataset using the following DOI if you use it in your work: 10.17632/kvcfp5y95z.1.
DOI: 10.17632/gk3tk53yv4
title: BOLD TaxonID Tree of water mites from the Balkan peninsula (BOLD Dataset “DS-BALHYD”)

description: The Neighbour-Joining tree of all water mite (Acari, Hydrachnidia) species from the Balkan peninsula based on Kimura 2-parameter distances. The analyses involved 1026 COI nucleotide sequences publicly available through the Barcode of Life Data Systems (BOLD Dataset: https://portal.boldsystems.org/recordset/DS-BALHYD).