cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.14726641
title: Multi-aspect renewable energy forecasting

description: TUCKER-CLUS: Multi-aspect renewable energy forecasting

A new method based on the Tucker tensor decomposition, capable of extracting a new feature space for the multi-plant energy forecasting task.

For evaluation purposes, we have investigated the performance of predictive clustering trees with the new feature space, compared to the original feature space, in three renewable energy datasets. The results are favorable for the proposed method, also when compared with state-of-the-art algorithms.

The performance of the method has been tested on the 24-hour ahead multi-plant energy forecasting task. Additional details can be found on the research paper referenced below.

 

Publications:

R. Corizzo, M. Ceci, H. Fanaee-T, J. Gama: Multi-aspect renewable energy forecasting, Information Sciences (DOI: 10.1016/j.ins.2020.08.003), https://www.sciencedirect.com/science/article/pii/S0020025520307611

Citation:

@article{corizzo2021multi,  title={Multi-aspect renewable energy forecasting},  author={Corizzo, Roberto and Ceci, Michelangelo and Fanaee-T, Hadi and Gama, Joao},  journal={Information Sciences},  volume={546},  pages={701--722},  year={2021},  publisher={Elsevier}}
DOI: 10.15468/dl.8srwmp
title: Occurrence Download

description: A dataset containing 3233 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Thamnochortus P.J.Bergius)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 3233 records from 31 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002858-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14002502
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.
DOI: 10.5281/zenodo.14002503
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.
DOI: 10.5281/zenodo.14725235
title: Dataset for the article "Ultrathin electrospun nanofibrous membranes based on poly(γ-benzyl-L-glutamate)"
DOI: 10.5281/zenodo.14725236
title: Dataset for the article "Ultrathin electrospun nanofibrous membranes based on poly(γ-benzyl-L-glutamate)"
DOI: 10.15468/dl.bxtrjx
title: Occurrence Download

description: A dataset containing 594472 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Romania",
 "Geometry POLYGON((7.85277 38.74421,44.14723 38.74421,44.14723 53.25579,7.85277 53.25579,7.85277 38.74421))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Year 2000-2023"
 ]
}

 The dataset includes 594472 records from 177 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0048534-231120084113126/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.28264199
title: PPI raw data

description: raw data of PPI feature
DOI: 10.15468/dl.gkvbzr
title: Occurrence Download

description: A dataset containing 50732 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Tetratheca Sm.)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 50732 records from 69 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002856-250121130708018/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14700381
title: Data supporting the paper "Measurement of the Casimir force between superconductors"

description: This dataset supports the publication "Measurement of the Casimir force between superconductors" by 

Matthijs H.J. de Jong, Evren Korkmazgil, Louise Banniard, Mika A. Sillanpää, and Laure Mercier de Lépinay.

This dataset contains all figures, data, measurement and analysis scripts, calculations, simulation models, and designs used in the above publication. It is a single zip file with a 'readme.txt' containing a detailed description of the contents and role of each of the files in the zip, as well as methods to access them. The zip file is organized with folders associated with each of the figures in the mentioned publication. The figure files are present as .png and/or .pdf files. All numerical results are present as .csv (human-readable), .txt (human-readable), .npy (machine-readable), .h5 (machine-readable), .tiff (human-readable), or .mat (machine-readable) files. All simulations are present as .mph (COMSOL 6.3) files. All designs are present as .gds files. All analysis and calculation scripts are present as .py (Python) or .m (Matlab) files, which are readable in most text editors.
DOI: 10.5281/zenodo.14726417
title: Scalable auto-encoders for gravitational waves detection from time series data

description: Additional resources of the paper:

Scalable auto-encoders for gravitational waves detection from time series data

R Corizzo, M Ceci, E Zdravevski, N Japkowicz

Expert Systems with Applications 151, 113378

 

Citation



@article{corizzo2020scalable,
  title={Scalable auto-encoders for gravitational waves detection from time series data},
  author={Corizzo, Roberto and Ceci, Michelangelo and Zdravevski, Eftim and Japkowicz, Nathalie},
  journal={Expert Systems with Applications},
  volume={151},
  pages={113378},
  year={2020},
  publisher={Elsevier}
}
DOI: 10.5281/zenodo.14726418
title: Scalable auto-encoders for gravitational waves detection from time series data

description: Additional resources of the paper:

Scalable auto-encoders for gravitational waves detection from time series data

R Corizzo, M Ceci, E Zdravevski, N Japkowicz

Expert Systems with Applications 151, 113378

 

Citation



@article{corizzo2020scalable,
  title={Scalable auto-encoders for gravitational waves detection from time series data},
  author={Corizzo, Roberto and Ceci, Michelangelo and Zdravevski, Eftim and Japkowicz, Nathalie},
  journal={Expert Systems with Applications},
  volume={151},
  pages={113378},
  year={2020},
  publisher={Elsevier}
}
DOI: 10.5281/zenodo.14726809
title: dataset bibliography

description: Dataset consulted for drafting https://doi.org/10.1016/j.tifs.2021.06.025
DOI: 10.5281/zenodo.14726808
title: dataset bibliography

description: Dataset consulted for drafting https://doi.org/10.1016/j.tifs.2021.06.025
DOI: 10.5281/zenodo.14031714
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.
DOI: 10.5281/zenodo.14058516
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

## File Overview



**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.

**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).

**Fill_Information.csv** - (2 KB): Fill information records for new patients.

**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.

**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.

**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.

**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.

**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.

**Triage.csv** - (13 KB): Data related to the triage process.

**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.


 

## Common Fields Across Files



**Patient ID** *(Integer)*: Unique identifier for each patient.

**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).

**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.

**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.

**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.

**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.

**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.

**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.

**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.

**Queue Difference** *(Integer)*: Difference between the before and after queue counts.

**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.

**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.

**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.

**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.
DOI: 10.5281/zenodo.14141844
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

## File Overview



**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.

**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).

**Fill_Information.csv** - (2 KB): Fill information records for new patients.

**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.

**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.

**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.

**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.

**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.

**Triage.csv** - (13 KB): Data related to the triage process.

**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.


 

## Common Fields Across Files



**Patient ID** *(Integer)*: Unique identifier for each patient.

**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).

**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.

**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.

**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.

**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.

**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.

**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.

**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.

**Queue Difference** *(Integer)*: Difference between the before and after queue counts.

**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.

**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.

**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.

**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.
DOI: 10.5281/zenodo.14142067
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

## File Overview



**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.

**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).

**Fill_Information.csv** - (2 KB): Fill information records for new patients.

**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.

**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.

**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.

**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.

**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.

**Triage.csv** - (13 KB): Data related to the triage process.

**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.


 

## Common Fields Across Files



**Patient ID** *(Integer)*: Unique identifier for each patient.

**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).

**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.

**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.

**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.

**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.

**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.

**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.

**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.

**Queue Difference** *(Integer)*: Difference between the before and after queue counts.

**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.

**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.

**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.

**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.
DOI: 10.5281/zenodo.14212794
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

## File Overview



**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.

**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).

**Fill_Information.csv** - (2 KB): Fill information records for new patients.

**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.

**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.

**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.

**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.

**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.

**Triage.csv** - (13 KB): Data related to the triage process.

**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.


 

## Common Fields Across Files



**Patient ID** *(Integer)*: Unique identifier for each patient.

**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).

**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.

**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.

**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.

**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.

**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.

**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.

**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.

**Queue Difference** *(Integer)*: Difference between the before and after queue counts.

**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.

**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.

**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.

**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.
DOI: 10.5281/zenodo.14212812
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

## File Overview



**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.

**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).

**Fill_Information.csv** - (2 KB): Fill information records for new patients.

**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.

**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.

**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.

**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.

**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.

**Triage.csv** - (13 KB): Data related to the triage process.

**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.


 

## Common Fields Across Files



**Patient ID** *(Integer)*: Unique identifier for each patient.

**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).

**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.

**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.

**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.

**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.

**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.

**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.

**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.

**Queue Difference** *(Integer)*: Difference between the before and after queue counts.

**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.

**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.

**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.

**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.


Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14212812
DOI: 10.5281/zenodo.14215301
title: Synthetic Dataset of Emergency Healthcare Services

description: Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.

## File Overview



**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.

**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).

**Fill_Information.csv** - (2 KB): Fill information records for new patients.

**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.

**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.

**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.

**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.

**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.

**Triage.csv** - (13 KB): Data related to the triage process.

**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.


 

## Common Fields Across Files



**Patient ID** *(Integer)*: Unique identifier for each patient.

**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).

**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.

**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.

**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.

**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.

**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.

**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.

**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.

**Queue Difference** *(Integer)*: Difference between the before and after queue counts.

**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.

**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.

**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.

**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.


Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14212812