cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/88rpmmnmkm.8
title: HEVC-SVS: Low-level HEVC features and CNN features for TVSum, SumMe, OVP and VSUMM datasets

description: Proposed HEVC feature sets along with CNN features from GoogleNet, AlexNet, Inception-ResNet-V2, and VGG16 for TVSum, SumMe, OVP and VSUMM datasets. The new modified datasets names are "HEVC-SVS-TVSum", "HEVC-SVS-SumMe", "HEVC-SVS-OVP" and "HEVC-SVS-VSUMM", respectively.

The datasets contain the original ground truth data they came with, and these stayed unmodified.

Upon using any of these datasets, please do cite our publications where we proposed the HEVC feature set for the first time:

If you are using (HEVC-SVS-OVP) and/or (HEVC-SVS-VSUMM) datasets: https://ieeexplore.ieee.org/document/9815254/

@article{issa_cnn_2022,
	title = {{CNN} and {HEVC} {Video} {Coding} {Features} for {Static} {Video} {Summarization}},
	volume = {10},
	issn = {2169-3536},
	url = {https://ieeexplore.ieee.org/document/9815254/},
	doi = {10.1109/ACCESS.2022.3188638},
	urldate = {2022-09-29},
	journal = {IEEE Access},
	author = {Issa, Obada and Shanableh, Tamer},
	year = {2022},
	pages = {72080--72091},
}

If you are using (HEVC-SVS-TVSum) and/or (HEVC-SVS-SumMe) datasets: https://www.mdpi.com/2076-3417/13/10/6065

@article{issa_static_2023,
	title = {Static {Video} {Summarization} {Using} {Video} {Coding} {Features} with {Frame}-{Level} {Temporal} {Subsampling} and {Deep} {Learning}},
	volume = {13},
	issn = {2076-3417},
	url = {https://www.mdpi.com/2076-3417/13/10/6065},
	doi = {10.3390/app13106065},
	number = {10},
	journal = {Applied Sciences},
	author = {Issa, Obada and Shanableh, Tamer},
	month = may,
	year = {2023},
	pages = {6065},
}

Make sure to also cite the original authors for each of the datasets:

TVSum (https://people.csail.mit.edu/yalesong/tvsum/)
SumMe (https://gyglim.github.io/me/vsum/index.html)
OVP and VSUMM (https://www.sites.google.com/site/vsummsite/download)


Acknowledgement:
The work in this research project is supported by the American University of Sharjah under research grant number FRG22-E-E44. This research work represents the opinions of the author(s) and does not mean to represent the position or opinions of the American University of Sharjah.
DOI: 10.17632/88rpmmnmkm.1
title: HEVC-SVS: Low-level HEVC features and CNN features for OVP and SUMME datasets 

description: Proposed HEVC feature sets along with CNN features from GoogleNet, AlexNet, Inception-ResNet-V2, and VGG16 for OVP and SUMME datasets.
The new modified datasets are names "HEVC-SVS-OVP" and "HEVC-SVS-SUMME".

The datasets contain the original ground truth data they came with, and these stayed unmodified.

Feature ID	Feature variable
Averaged per frame
	1	Number of CU parts
	2	MVD bits per CU
	3	CU bits excluding MVD bits
	4	Percentage of intra CU parts
	5	Percentage of skipped CU parts
	6	Number of CUs with depth 0 (i.e 64x64)
	7	Number of parts with depth 1 (i.e 32x32)
	8	Number of CUs with depth 2 (i.e 16x16)
	9	Number of parts with depth 3 (i.e 8x8)
10-18	Standard deviation of feature IDs 1-9 per frame
19	Max CU depth per frame
20	For CUs with depth > 0, log_2⁡〖(|sum of MVD|)〗?
21	For CUs with depth = 0, log_2⁡〖(|sum of MVD|)〗?
Averaged per frame
	22	Row-wise SAD of the CU prediction error
	23	Column-wise SAD of the CU prediction error
	24	Ratio of gradients (i.e feature 22 divided by feature 23) per CU
	25	Total distortion per CU as computed by the HEVC encoder
26-29	Standard deviation of feature IDs 22-25 per frame
30	Per frame: Summation of variance of the x and y components of all MVs
31-47	Histogram of x-component of all MVs per frame (using 16 pins)
48-64	Histogram of y-component of all MVs per frame (using 16 pins)

Upon using any of these datasets, please do cite our publication where we proposed the HEVC 64 feature set for the first time:
[[Place holder for our publication reference]].

Along with the original authors for each of the datasets:

OVP:

@article{Avila,
title = "VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method",
journal = "Pattern Recognition Letters",
volume = "32",
number = "1",
pages = "56 - 68",
year = "2011",
note = "<ce:title>Image Processing, Computer Vision and Pattern Recognition in Latin America</ce:title>",
issn = "0167-8655",
doi = "10.1016/j.patrec.2010.08.004",
author = "Sandra Eliza Fontes de Avila and Ana Paula Brand„o Lopes and Antonio da Luz Jr. and Arnaldo de Albuquerque Ara˙jo",
}

SUMME:

@inproceedings{GygliECCV14,
   author ={Gygli, Michael and Grabner, Helmut and Riemenschneider, Hayko and Van Gool, Luc},
   title = {Creating Summaries from User Videos},
   booktitle = {ECCV},
   year = {2014}
}
DOI: 10.17632/88rpmmnmkm.2
title: HEVC-SVS: Low-level HEVC features and CNN features for OVP and SUMME datasets 

description: Proposed HEVC feature sets along with CNN features from GoogleNet, AlexNet, Inception-ResNet-V2, and VGG16 for OVP and SUMME datasets.
The new modified datasets are names "HEVC-SVS-OVP" and "HEVC-SVS-SUMME".

The datasets contain the original ground truth data they came with, and these stayed unmodified.

Feature ID	Feature variable
Averaged per frame
	1	Number of CU parts
	2	MVD bits per CU
	3	CU bits excluding MVD bits
	4	Percentage of intra CU parts
	5	Percentage of skipped CU parts
	6	Number of CUs with depth 0 (i.e 64x64)
	7	Number of parts with depth 1 (i.e 32x32)
	8	Number of CUs with depth 2 (i.e 16x16)
	9	Number of parts with depth 3 (i.e 8x8)
10-18	Standard deviation of feature IDs 1-9 per frame
19	Max CU depth per frame
20	For CUs with depth > 0, log_2⁡〖(|sum of MVD|)〗?
21	For CUs with depth = 0, log_2⁡〖(|sum of MVD|)〗?
Averaged per frame
	22	Row-wise SAD of the CU prediction error
	23	Column-wise SAD of the CU prediction error
	24	Ratio of gradients (i.e feature 22 divided by feature 23) per CU
	25	Total distortion per CU as computed by the HEVC encoder
26-29	Standard deviation of feature IDs 22-25 per frame
30	Per frame: Summation of variance of the x and y components of all MVs
31-47	Histogram of x-component of all MVs per frame (using 16 pins)
48-64	Histogram of y-component of all MVs per frame (using 16 pins)

Upon using any of these datasets, please do cite our publication where we proposed the HEVC 64 feature set for the first time:
[[Place holder for our publication reference]].

Along with the original authors for each of the datasets:

OVP:

@article{Avila,
title = "VSUMM: A mechanism designed to produce static video summaries and a novel evaluation method",
journal = "Pattern Recognition Letters",
volume = "32",
number = "1",
pages = "56 - 68",
year = "2011",
note = "<ce:title>Image Processing, Computer Vision and Pattern Recognition in Latin America</ce:title>",
issn = "0167-8655",
doi = "10.1016/j.patrec.2010.08.004",
author = "Sandra Eliza Fontes de Avila and Ana Paula Brand„o Lopes and Antonio da Luz Jr. and Arnaldo de Albuquerque Ara˙jo",
}

SUMME:

@inproceedings{GygliECCV14,
   author ={Gygli, Michael and Grabner, Helmut and Riemenschneider, Hayko and Van Gool, Luc},
   title = {Creating Summaries from User Videos},
   booktitle = {ECCV},
   year = {2014}
}
DOI: 10.17632/sygn59mm7h.1
title: PAHTEI-Proceedings of Azerbaijan High Technical Educational Institutions

description: Referred & Reviewed Journal

DOI PREFIX: 10.36962/PAHTEI

ISSN: 1609-1620 (Print); ISSN: 2674-5224 (Online); UDC: 62 (051) (0.034)

Web-site: https://bsj.fisdd.org/index.php/pahtei/
DOI: 10.17632/bjs5wghsmv.1
title: Supplemental Data - Incidence and melanoma-specific mortality of second primary melanomas: a population-based retrospective cohort study

description: Supplemental methods and data
DOI: 10.17632/zgh553by5n.1
title: Progress and setbacks in rural women's poverty reduction data set for a systematic literature review.

description: This database focuses on poverty reduction in rural women. We are sharing the data in RIS format for articles that meet the search strategy in rural women, along with the search strategy in WoS, PubMed, and Scopus. TITLE-ABS-KEY ( "Rural Women"  OR  "Rural Population*"  OR  "Rural Area"  OR  "Rural"  OR  "Urban Rural Difference"  OR  "Rural Workers"  OR  "Internal Migration"  OR  "Rural Areas" )  AND  TITLE-ABS-KEY ( ( {extreme poverty}  OR  {poverty alleviation}  OR  {poverty eradication}  OR  {poverty reduction}  OR  {international poverty line}  OR  ( {financial aid}  AND  {poverty} )  OR  ( {financial aid}  AND  {poor} )  OR  ( {financial aid}  AND  {north-south divide} )  OR  ( {financial development}  AND  {poverty} )  OR  {financial empowerment}  OR  {distributional effect}  OR  {distributional effects}  OR  {child labor}  OR  {child labour}  OR  {development aid}  OR  {social protection}  OR  {social protection system}  OR  ( {social protection}  AND  access )  OR  microfinanc*  OR  micro-financ*  OR  {resilience of the poor}  OR  ( {safety net}  AND  {poor}  OR  {vulnerable} )  OR  ( {economic resource}  AND  access )  OR  ( {economic resources}  AND  access )  OR  {food bank}  OR  {food banks} ) )
DOI: 10.34740/kaggle/dsv/5811140
title: "Futureidea_3K+_AI_Tools_Dataset"
DOI: 10.25625/hooaj4/dnhh2e
title: read me.txt

description: :unav
DOI: 10.25625/hooaj4/gpcqdj
title: Jambi_UCI_SingleScans.tab

description: :unav
DOI: 10.25625/hooaj4/lylqli
title: B11_SSC_ENL_central_scans.tab

description: :unav
DOI: 10.25625/hooaj4/2l3hrg
title: B11_FD_tree_species-1.tab

description: :unav
DOI: 10.25625/hooaj4/31awcf
title: laser-scan-position-B11plot.pptx

description: :unav
DOI: 10.25625/hooaj4/6dbcnd
title: Jambi_SSC_SingleScans.tab

description: :unav
DOI: 10.25625/hooaj4/rops9e
title: B11_FD_tree_species.tab
DOI: 10.25625/hooaj4/roz4hq
title: SSCI Algorithm.r

description: :unav
DOI: 10.25625/hooaj4/xgokmg
title: CRC990_CorePlots_SSC_ENL.xls

description: :unav
DOI: 10.25625/hooaj4
title: EFForTS-BEE Stand structural complexity from terrestrial laser scanning

description: Stand structural complexity of the B11 plots and box dimensions of the planted tree species
DOI: 10.25625/hooaj4/hgpigj
title: read me.txt

description: :unav
DOI: 10.25625/hooaj4/mywx4z
title: B11_SSC_ENL_all_scans.tab

description: :unav
DOI: 10.5281/zenodo.7987075
title: corambe_burchi_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7987074
title: corambe_burchi_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.6407330
title: Supplementary material for: L. Coltofean-Arizancu, B. Gaydarska, S. Plutniak, L. Mary, M. Hlad, I. Algrain, B. Pasquini, S. Vandevelde, E. Stamataki, P. Janežič, B. Wouters, A. Sengeløv. "Harassment, Assault, Bullying and Intimidation (HABI) in Archaeology: Europe-wide Survey", DOI: 10.15184/aqy.2023.58

description: Supplementary material for: L. Coltofean-Arizancu, B. Gaydarska, S. Plutniak, L. Mary, M. Hlad, I. Algrain, B. Pasquini, S. Vandevelde, E. Stamataki, P. Janežič, B. Wouter, A. Sengeløv. “Harassment, Assault, Bullying and Intimidation (HABI) in Archaeology: Europe-wide Survey”, <em>Antiquity</em>. DOI: 10.15184/aqy.2023.58.
DOI: 10.5281/zenodo.6407331
title: Supplementary material for: L. Coltofean-Arizancu, B. Gaydarska, S. Plutniak, L. Mary, M. Hlad, I. Algrain, B. Pasquini, S. Vandevelde, E. Stamataki, P. Janežič, B. Wouters, A. Sengeløv. "Harassment, Assault, Bullying and Intimidation (HABI) in Archaeology: Europe-wide Survey", DOI: 10.15184/aqy.2023.58

description: Supplementary material for: L. Coltofean-Arizancu, B. Gaydarska, S. Plutniak, L. Mary, M. Hlad, I. Algrain, B. Pasquini, S. Vandevelde, E. Stamataki, P. Janežič, B. Wouter, A. Sengeløv. “Harassment, Assault, Bullying and Intimidation (HABI) in Archaeology: Europe-wide Survey”, <em>Antiquity</em>. DOI: 10.15184/aqy.2023.58.
DOI: 10.17632/7s6zjz62v2.1
title: Data for: Environmental effects on ammonium adsorption onto clay minerals: Experimental constraints and applications

description: Data for all figures in the manuscript by Yu et al. to be submitted by Geochimica et Cosmochimica Acta as "Environmental effects on ammonium adsorption onto clay minerals: Experimental constraints and applications". Excel file 'Characterization' contains all characterization data (i.e., XRD, grain size, zeta potential) of studied clay minerals. Word file 'NH4 onto clays_tables' contains all data tabulated in tables in the manuscript.
DOI: 10.17632/7s6zjz62v2.2
title: Data for: Environmental effects on ammonium adsorption onto clay minerals: Experimental constraints and applications

description: Data for all figures in the manuscript by Yu et al. to be submitted to Geochimica et Cosmochimica Acta entitled "Environmental effects on ammonium adsorption onto clay minerals: Experimental constraints and applications".  Excel file 'Sample Characterization' contains all characterization data (i.e., XRD, grain size, zeta potential) of the studied clay minerals. Word file 'NH4 adsorption data tables' contains all data tabulated in tables in the manuscript.
DOI: 10.17632/7s6zjz62v2.3
title: Data for: Environmental effects on ammonium adsorption onto clay minerals: Experimental constraints and applications

description: Data for all figures in the manuscript entitled "Environmental effects on ammonium adsorption onto clay minerals: Experimental constraints and applications" by Yu et al. Excel file 'Sample Characterization' contains all characterization data (i.e., XRD, grain size, zeta potential) of the studied clay minerals. Word file 'NH4 adsorption data tables' contains all data tabulated in tables in the manuscript.
DOI: 10.5281/zenodo.7987079
title: ancula_gibbosa_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7987078
title: ancula_gibbosa_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.6696869
title: Secondary screening MPRA dataset (3 replicates)

description: Secondary screening MPRA dataset (3 replicates)
DOI: 10.5281/zenodo.6696870
title: Secondary screening MPRA dataset (3 replicates)

description: Secondary screening MPRA dataset (3 replicates)
DOI: 10.5519/qd.s3q9vdks
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (20 records)
DOI: 10.6084/m9.figshare.23262005
title: Linsenmeier_hnRNPA1-interface_SourceData_main.xlsx

description: Source data - main text of Linsenmeier M. et al., Nat Chem, 2023
DOI: 10.6084/m9.figshare.23262005.v1
title: Linsenmeier_hnRNPA1-interface_SourceData_main.xlsx

description: Source data - main text of Linsenmeier M. et al., Nat Chem, 2023
DOI: 10.17632/t3tyvpbnj9.1
title: An Archean lower crustal cross-section: constraints from granulite terrains and xenoliths (GCA)

description: Supplementary table S1-S5. xlsx
DOI: 10.17632/t3tyvpbnj9.2
title: Layered Archean lower continental crust: constraints from granulite terrains and xenoliths

description: Supplementary table S1-S5. xlsx
DOI: 10.17632/kv79vw86jj.1
title: Heterogeneous slab thermal dehydration driving warm subduction zone earthquakes

description: The data includes the three-dimensional temperature field (degrees Celsius), water content (wt%), dehydration rate (wt%/km), rock phase change distribution, and subduction velocity field (cm/yr) of the subducting plate, as well as the coastline and volcano distribution. The data coordinates are an orthogonal coordinate system, where the origin of the coordinates is (166.3E, 16.4S).The data of the model region have dimensions of 1200×500×400 km (length×width×depth). The geometry of the subducted plate is well constrained by Slab2.0, and the plate ages are provided by EarthByte. The temperature boundary condition agrees with the plate cooling model. The bottom of the slab and the perpendicular plane are prescribed as adiabatic and permeable, and the top surface is set to a fixed temperature (0°C) and is rigid.  The data was acquired through 3-D numerical thermal modeling which was developed from originally code stag3d. An anelastic liquid approximation and the equations of conservation of mass, momentum, and energy are used in this model. Based on a three-dimensional thermomechanical model and the collect earthquake catalog from IRIS, the data of the slab thermal state, water content, and slab dehydration distribution in Vanuatu are calculated. The geophysical calculation is ensured after the subduction thermal regime reaches a steady state. The temperature field error range is ±50 degrees Celsius, and the velocity field error range is ±0.1cm/ yr. This data can be further used analyzing the geophysical field of subduction zone.
DOI: 10.5281/zenodo.7987084
title: amazona_mercenarius_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7987083
title: amazona_mercenarius_decontaminated_gx.fasta.gz

description: .
DOI: 10.5281/zenodo.7773942
title: pan-viral MPRA (NC fractionation)

description: pan-viral MPRA (NC fractionation), 4 replicates
DOI: 10.5281/zenodo.7773943
title: pan-viral MPRA (NC fractionation)

description: pan-viral MPRA (NC fractionation), 4 replicates
DOI: 10.5281/zenodo.6786178
title: K5 Gene-specific TAIL-seq

description: Gene-specific TAIL-seq experiment
DOI: 10.5281/zenodo.6786179
title: K5 Gene-specific TAIL-seq

description: Gene-specific TAIL-seq experiment
DOI: 10.5281/zenodo.6717931
title: Polysome fractionation MPRA (3 replicates)

description: Polysome fractionation MPRA (3 replicates)
DOI: 10.5281/zenodo.6717932
title: Polysome fractionation MPRA (3 replicates)

description: Polysome fractionation MPRA (3 replicates)
DOI: 10.17632/6wdrr5hgtk.1
title: Dataset - Application of biological early warning systems in wastewater treatment plants: Introducing a new approach to monitor changing wastewater composition

description: This data set includes all raw data for the publication  "Application of biological early warning systems in wastewater treatment plants: Introducing a new approach to monitor changing wastewater composition"  in the Journal of Environmental Management
DOI: 10.17632/vkv4cwhh7n.1
title: Face mask use in the city of Chennai, India: Results from three serial cross-sectional surveys, 2021

description: Face mask use in the city of Chennai, India: Results from three serial cross-sectional surveys, 2021. We captured the compliance to face mask usage in outdoors, indoors, and in the malls of Chennai. Three datasets are attached here.
DOI: 10.17632/wwxrpynp37.1
title: M3M Capital Walk Gurgaon | M3M Shop Cum Office Space in Sector 113, Gurugram

description: M3M Capital Walk 113, located in Sector 113, Gurgaon, stands as one of the most promising commercial developments by M3M India. This distinguished project features beautifully designed landscaped gardens, retail shops, office spaces, entertainment areas, restaurants, and much more to offer a remarkable experience for investors. 
more link - https://www.indiapropertydekho.com/show-projects/m3m-capital-walk/1971
DOI: 10.17632/6244h8cn6z.1
title: panel_democ_growth_MENA

description: This panel data set presents information on the impact of democracy and political stability on economic growth in 15 MENA countries for the period 1983–2019. The data are collected from five different sources; the World Bank Development Indicators (WDI), the World Bank Governance Indicators (WGI), the Penn World Table (PWT), Polity5 from the Integrated Network for Societal Conflict Research (INSCR), and the Varieties of Democracy (V-Dem). The data set includes ten variables related to economic growth, democracy, and political stability.
DOI: 10.17632/6244h8cn6z.2
title: panel_democ_growth_MENA

description: This panel data set presents statistics on how democracy and political stability influence economic growth in 15 MENA nations between 1983 and 2019.
DOI: 10.17632/ptyzsw4nxc.1
title: Pathogenicity of fungal isolates from the newly invasive fall armyworm in China against different insect pests.

description: The concentration of fungus in all fungal treatments is 2×108 spores/ml. The mortality caused by the same fungus isolate was compared by one-way analysis of variance (ANOVA) followed by post hoc Tukey tests with insect species as the factor, the data were checked for normality by Shapiro-Wilk tests before analysis. The data represent the mean of five replicates with standard error. Data with different letters indicate significant differences among different insect species with the same fungal treatment.
DOI: 10.17632/ptyzsw4nxc.2
title: Characterization of entomopathogenic fungi from invasive fall armyworm in China and their risk to native pest.

description: The concentration of fungus in all fungal treatments is 2×108 spores/ml. The mortality caused by the same fungus isolate was compared by one-way analysis of variance (ANOVA) followed by post hoc Tukey tests with insect species as the factor, the data were checked for normality by Shapiro-Wilk tests before analysis. The data represent the mean of five replicates with standard error. Data with different letters indicate significant differences among different insect species with the same fungal treatment.
DOI: 10.6084/m9.figshare.13574905
title: Robust Design and Analysis of Clinical Trials With Nonproportional Hazards: A Straw Man Guidance From a Cross-Pharma Working Group

description: Loss of power and clear description of treatment differences are key issues in designing and analyzing a clinical trial where nonproportional hazard (NPH) is a possibility. A log-rank test may be inefficient and interpretation of the hazard ratio estimated using Cox regression is potentially problematic. In this case, the current ICH E9 (R1) addendum would suggest designing a trial with a clinically relevant estimand, for example, expected life gain. This approach considers appropriate analysis methods for supporting the chosen estimand. However, such an approach is case specific and may suffer from lack of power for important choices of the underlying alternate hypothesis distribution. On the other hand, there may be a desire to have robust power under different deviations from proportional hazards. We would contend that no single number adequately describes treatment effect under NPH scenarios. The cross-pharma working group has proposed a combination test to provide robust power under a variety of alternative hypotheses. These can be specified for primary analysis at the design stage and methods appropriately accounting for combination test correlations are efficient for a variety of scenarios. We have provided design and analysis considerations based on a combination test under different NPH types and present a straw man proposal for practitioners. The proposals are illustrated with real life example and simulation.
DOI: 10.6084/m9.figshare.13574905.v2
title: Robust Design and Analysis of Clinical Trials With Nonproportional Hazards: A Straw Man Guidance From a Cross-Pharma Working Group

description: Loss of power and clear description of treatment differences are key issues in designing and analyzing a clinical trial where nonproportional hazard (NPH) is a possibility. A log-rank test may be inefficient and interpretation of the hazard ratio estimated using Cox regression is potentially problematic. In this case, the current ICH E9 (R1) addendum would suggest designing a trial with a clinically relevant estimand, for example, expected life gain. This approach considers appropriate analysis methods for supporting the chosen estimand. However, such an approach is case specific and may suffer from lack of power for important choices of the underlying alternate hypothesis distribution. On the other hand, there may be a desire to have robust power under different deviations from proportional hazards. We would contend that no single number adequately describes treatment effect under NPH scenarios. The cross-pharma working group has proposed a combination test to provide robust power under a variety of alternative hypotheses. These can be specified for primary analysis at the design stage and methods appropriately accounting for combination test correlations are efficient for a variety of scenarios. We have provided design and analysis considerations based on a combination test under different NPH types and present a straw man proposal for practitioners. The proposals are illustrated with real life example and simulation.