cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.24242956.v1
title: Spatial analysis of Asian protected areas for transboundary conservation

description: This is a data related to the spatial proximity of protected areas across borderlands in Asian countries, developed by Vignesh et al (under review)
DOI: 10.5281/zenodo.8266456
title: ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2017)

description: The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn). This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively. This is the ELITE seamless LST product in 2017. Please <strong><em>click here</em></strong> to download the ELITE LST product in 2016 and <strong><em>click here</em></strong> to download the ELITE LST product in 2018. <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia (0-60°N, 80°E-140°E) Temporal Coverage: 2017 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Data Format: Geotiff Scale: 0.01 <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170 Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124. If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
description: {"references": ["Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170", "Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124"]}
DOI: 10.5281/zenodo.7316883
title: ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2017)

description: The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn). This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively. This is the ELITE seamless LST product in 2017. Please <strong><em>click here</em></strong> to download the ELITE LST product in 2016 and <strong><em>click here</em></strong> to download the ELITE LST product in 2018. <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia (0-60°N, 80°E-140°E) Temporal Coverage: 2017 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Data Format: Geotiff Scale: 0.01 <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170 Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124. If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
description: {"references": ["Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170", "Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124"]}
DOI: 10.5281/zenodo.8375656
title: Datasets of Man-in-the-middle Attacks Targeting Modbus TCP/IP and MMS protocols in the Smart Grid

description: The sustainable development of smart grids requires the massive deployment of renewable energy, in a highly distributed manner, introducing new challenges for the system operation. Therefore, the integration of information and communication technologies in sites with Distributed Energy Resources (DERs) is needed to monitor and control the DERs operation. In this scheme, a local controller is installed at each DER site to interact with the centralized applications at the grid level and the power equipment at the site level. This local controller uses client–server protocols (e.g., Modbus TCP/IP and IEC 61850 Manufacturing Message Specification (MMS)) to communicate with different power equipment in the Private Area Network (PAN) of the site. Such protocols often lack information confidentiality and integrity mechanisms. As a result, the smart grids become vulnerable to cyber-attacks. This repository contains datasets created to evaluate the detection and classification of man-in-the-middle attacks, operating in eavesdropping mode, targeting MMS and Modbus TCP/IP protocols in the PAN of the smart grid. Five Flow-based features were used to create these datasets, as shown in Table 1, in addition to the ARP poisoning indicator feature: Table 1 Feature Description IRTT Time for establishing one connection TTOC Time for receiving all responses in one connection MITR Minimum time between requests in one connection MATR Maximum time between requests in one connection NROC Number of requests in one connection **NOTE** If you use this dataset in your research/publication please cite us using the following:<br> Mohamed Faisal Elrawy, Lenos Hadjidemetriou, Christos Laoudias, Maria K. Michael,<br> Detecting and classifying man-in-the-middle attacks in the private area network of smart grids,<br> Sustainable Energy, Grids and Networks,2023,pp.1-13, https://doi.org/10.1016/j.segan.2023.101167
DOI: 10.5281/zenodo.8375657
title: Datasets of Man-in-the-middle Attacks Targeting Modbus TCP/IP and MMS protocols in the Smart Grid

description: The sustainable development of smart grids requires the massive deployment of renewable energy, in a highly distributed manner, introducing new challenges for the system operation. Therefore, the integration of information and communication technologies in sites with Distributed Energy Resources (DERs) is needed to monitor and control the DERs operation. In this scheme, a local controller is installed at each DER site to interact with the centralized applications at the grid level and the power equipment at the site level. This local controller uses client–server protocols (e.g., Modbus TCP/IP and IEC 61850 Manufacturing Message Specification (MMS)) to communicate with different power equipment in the Private Area Network (PAN) of the site. Such protocols often lack information confidentiality and integrity mechanisms. As a result, the smart grids become vulnerable to cyber-attacks. This repository contains datasets created to evaluate the detection and classification of man-in-the-middle attacks, operating in eavesdropping mode, targeting MMS and Modbus TCP/IP protocols in the PAN of the smart grid. Five Flow-based features were used to create these datasets, as shown in Table 1, in addition to the ARP poisoning indicator feature: Table 1 Feature Description IRTT Time for establishing one connection TTOC Time for receiving all responses in one connection MITR Minimum time between requests in one connection MATR Maximum time between requests in one connection NROC Number of requests in one connection **NOTE** If you use this dataset in your research/publication please cite us using the following:<br> Mohamed Faisal Elrawy, Lenos Hadjidemetriou, Christos Laoudias, Maria K. Michael,<br> Detecting and classifying man-in-the-middle attacks in the private area network of smart grids,<br> Sustainable Energy, Grids and Networks,2023,pp.1-13, https://doi.org/10.1016/j.segan.2023.101167
DOI: 10.5281/zenodo.7316884
title: ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2017)

description: The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn). This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively. This is the ELITE seamless LST product in 2017. Please <strong><em>click here</em></strong> to download the ELITE LST product in 2016 and <strong><em>click here</em></strong> to download the ELITE LST product in 2018. <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia (0-60°N, 80°E-140°E) Temporal Coverage: 2017 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Data Format: Geotiff Scale: 0.01 <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170 Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124. If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
description: {"references": ["Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170", "Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124"]}
DOI: 10.34740/kaggle/dsv/6609422
title: COVID Vaccination in World (updated daily)
DOI: 10.5281/zenodo.8256087
title: ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2018)

description: The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn). This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively. This is the ELITE seamless LST product in 2018. Please <strong><em>click here</em></strong> to download the ELITE LST product in 2017 and <strong><em>click here</em></strong> to download the ELITE LST product in 2019. <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia (0-60°N, 80°E-140°E) Temporal Coverage: 2018 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Data Format: Geotiff Scale: 0.01 <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170 Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124. If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
description: {"references": ["Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170", "Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124"]}
DOI: 10.5281/zenodo.7316872
title: ELITE land surface temperature: hourly seamless 0.02° LST over East Asia (2018)

description: The <strong>E</strong>ssential therma<strong>L</strong> <strong>I</strong>nfrared remo<strong>T</strong>e s<strong>E</strong>nsing (<strong>ELITE</strong>) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth’s radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn). This dataset is the 0.02 ° hourly seamless LST dataset over East Asia (2016-2021). Firstly, the iTES algorithm is employed to retrieve the Himawari-8/AHI LST. Secondly, the CLDAS LST is corrected to eliminate its system deviation. Finally, the multi-scale Kalman filter is employed to fuse Himawari-8/AHI LST and the bias-corrected CLDAS LST to generate 0.02 ° hourly seamless LST. The in situ validation results show that the root mean square error (RMSE) of the seamless LST is about 3k. The temporal resolution and spatial resolution of this dataset are 1 hour and 0.02°, respectively. This is the ELITE seamless LST product in 2018. Please <strong><em>click here</em></strong> to download the ELITE LST product in 2017 and <strong><em>click here</em></strong> to download the ELITE LST product in 2019. <strong>Dataset Characteristics:</strong> Spatial Coverage: East Asia (0-60°N, 80°E-140°E) Temporal Coverage: 2018 Spatial Resolution: 0.02 ° Temporal Resolution: one hour Data Format: Geotiff Scale: 0.01 <strong>Citation </strong>(Please cite these papers when using the data)<strong>:</strong> Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170 Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124. If you have any questions, please contact Prof. Jie Cheng (Jie_Cheng@bnu.edu.cn).
description: {"references": ["Dong, S., Cheng, J., Shi, J., Shi, C., Sun, S., & Liu, W. (2022). A Data Fusion Method for Generating Hourly Seamless Land Surface Temperature from Himawari-8 AHI Data. Remote Sensing, 14, 5170", "Zhou, S., & Cheng, J. (2020). An Improved Temperature and Emissivity Separation Algorithm for the Advanced Himawari Imager. IEEE Transactions on Geoscience and Remote Sensing, 58(10), 7105-7124"]}
DOI: 10.21223/jmrqmo/akgyxc
title: 09_Datadictionary.txt

description: :unav
DOI: 10.21223/jmrqmo/0izlwk
title: 08_Material_list.txt

description: :unav
DOI: 10.21223/jmrqmo/j7mcdr
title: 01_Fieldbook_PTYL200605_COMAS_Phureja_Collection_.txt

description: :unav
DOI: 10.21223/jmrqmo/tlk9i2
title: 04_Fieldbook_TCAR200605_COMAS_Phureja_Collection_.txt

description: :unav
DOI: 10.21223/jmrqmo/zqlaiu
title: TVIT200605_COMAS_Phureja_Collection_Field.xls

description: :unav
DOI: 10.21223/jmrqmo/a6vygz
title: TMIN200605_COMAS_Phureja_Collection_Field.xls

description: :unav
DOI: 10.5281/zenodo.8406719
title: NOT JUST MOTIVATION, BUT ALSO SELF-REGULATED LEARNING AFFECTED THE ACADEMIC ACHIEVEMENT OF INDONESIAN MEDICAL STUDENTS

description: Introduction. Medical education is regarded as difficult college degrees and a stressful academic journey. This study aimed to elaborate the correlation between several internal factors that affect academic performance. Methods. 211 active students in UPN Veteran Jakarta Indonesia was filled the four questionnaires to measure SRL (self regulated learning), motivation, self-efficacy, and emotional intelligence. GPA was considered as the academic performance of students. Correlation tests were analysed by Pearson correlation test and multiple linear regression. Results. SRL scores were higher in the medium level than high or low level, on contrast, the other variables showed different trends. The variables showed significant correlation with GPA were SRL and motivation. Conclusion. This study examined several intrinsic factors affected GPA, with predominantly SRL and motivation influencing GPA more. Strengthening the self-efficacy and Emotional Intelligence might improve the academic performance of medical students
DOI: 10.21223/jmrqmo/kjhroq
title: 06_Fieldbook_TMORP200605_COMAS_Phureja_Collection_.txt

description: :unav
DOI: 10.5281/zenodo.8406718
title: NOT JUST MOTIVATION, BUT ALSO SELF-REGULATED LEARNING AFFECTED THE ACADEMIC ACHIEVEMENT OF INDONESIAN MEDICAL STUDENTS

description: Introduction. Medical education is regarded as difficult college degrees and a stressful academic journey. This study aimed to elaborate the correlation between several internal factors that affect academic performance. Methods. 211 active students in UPN Veteran Jakarta Indonesia was filled the four questionnaires to measure SRL (self regulated learning), motivation, self-efficacy, and emotional intelligence. GPA was considered as the academic performance of students. Correlation tests were analysed by Pearson correlation test and multiple linear regression. Results. SRL scores were higher in the medium level than high or low level, on contrast, the other variables showed different trends. The variables showed significant correlation with GPA were SRL and motivation. Conclusion. This study examined several intrinsic factors affected GPA, with predominantly SRL and motivation influencing GPA more. Strengthening the self-efficacy and Emotional Intelligence might improve the academic performance of medical students
DOI: 10.21223/jmrqmo/nurn7k
title: TCAR200605_COMAS_Phureja_Collection_Field.xls

description: :unav
DOI: 10.21223/jmrqmo/4jg3gg
title: 05_Fieldbook_TPHEN200605_COMAS_Phureja_Collection_.txt

description: :unav
DOI: 10.21223/jmrqmo/bmow0v
title: PTYL200605_COMAS_Phureja_Collection_Field.xls

description: :unav
DOI: 10.21223/jmrqmo/8csf7y
title: TPHEN200605_COMAS_Phureja_Collection_Field.xls

description: :unav
DOI: 10.21223/jmrqmo/maresg
title: TMORP200605_COMAS_Phureja_Collection.xls

description: :unav
DOI: 10.21223/jmrqmo/bgjdr8
title: 02_Fieldbook_TMIN200605_COMAS_Phureja_Collection_.txt

description: :unav
DOI: 10.21223/jmrqmo
title: Dataset for: Field Evaluation and Nutritional Analysis of Phureja Collection Native Potatoes in Comas - Junin, 2006

description: An evaluation was carried out on 192 varieties from the Phureja potato collection. The assessment took place in the Comas locality in Junin during the 2006 growing season. Additionally, nutritional analyses were conducted for micronutrients, vitamin C, carotenoids, polyphenols, and a morphological characterization.
DOI: 10.21223/jmrqmo/no2qs5
title: 03_Fieldbook_TVIT200605_COMAS_Phureja_Collection_.txt

description: :unav