cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/xtvvkfvycr.1
title: Dataset of Tropical Cyclone in a High-Resolution Global Nonhydrostatic Atmospheric Simulation

description: This dataset comprises a time series of tropical cyclones that were simulated using the high-resolution Nonhydrostatic Icosahedral Atmospheric Model (NICAM). By tracking tropical cyclones over a period of 30 years of climate simulation data, 2463 tracks that encompass the life stages of precursors (pre-TCs), tropical cyclones (TCs), and post-tropical cyclones (post-TCs) were extracted. Each data in the track contains information about the time, longitude, latitude, maximum wind speed at 10m, minimum central pressure, elapsed time since onset, and life-stage label of the tropical cyclone. The number of steps for pre-TCs, TCs, and post-TCs were 45288, 55206, and 37312, respectively. The dataset for each step also consists of atmospheric field data of various physical quantities, including outgoing longwave radiation (OLR) at the top-of-the-atmosphere, sea level pressure (SLP), sea surface temperature (SST), specific humidity at 600 hPa, and zonal and meridional winds at 850 and 200 hPa over a 1000 km square area that encompasses a tropical cyclone at its center. This dataset holds immense potential for developing machine learning models for detecting, predicting the intensity, and predicting the cyclogenesis of tropical cyclones.
DOI: 10.17632/63vhbkndns.3
title: The dataset for bibliometric analysis of economics and business research trends in Vietnam

description: All scientiﬁc publications of Vietnam were refined by Scopus to the “Economics, Econometrics and Finance” and “Business, Management and Accounting” categories.
DOI: 10.17632/6f8j3m7868.1
title: Data for: Accurate Transmission Performance Evaluation of Servo-Mechanisms for Robots

description: This folder contains the Matlab files related to the study presented in the paper:

Title: "Accurate Transmission Performance Evaluation of Servo-Mechanisms for Robots"
Authors: P. Bilancia, L. Monari, R. Raffaeli, M. Peruzzini and M. Pellicciari
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**FILES**

- "TEModeling.m" --> it evaluates the TE experimental model by elaborating the acquired data (DOE approach)


- "GetDataFromExp.m" file --> it calculates the reducer performance indices


- "FileListForModel.m" file --> it comprises the list of files (experiments) to be processed



**FOLDER**

-Functions --> it contains matlab functions utilized during the data processing

-Test_30deg --> Experimental data acquired at T_lubricant = 30°C

-Test_35deg --> "	"	"	"	"	" = 35°C

-Test_40deg --> "	"	"	"	"	" = 30°C

-Test_45deg --> "	"	"	"	"	" = 45°C
DOI: 10.17632/fr9t5fkkvz.3
title: Olive oil geography by GC-IMS analysis

description: 53 olive oils from Spain (20), Italy (20) and Greece (13) of extra virgin quality, harvested during the 2014/2015 season, were kindly supplied by Coop Switzerland (Basel, Switzerland). Authenticity was verified by the supplier by chemical and isotope analysis.
Olive oil samples were analysed by headspace GC-IMS. The setup includes an Agilent 6890N gas chromatograph (Agilent Technologies, Palo Alto, USA), coupled with a standalone ion mobility spectrometer (Gesellschaft für Analytische Sensorsysteme mbH, Dortmund, Germany). Measurements were carried out in triplicates.
Binary files (*.mea format G.A.S. Sensorsysteme m.b.H., Dortmund, Germany)
DOI: 10.17632/xdy27vc3s8.1
title: Data for: Effect of Hypnotic Suggestion on Cognition and Craving in Smokers

description: Raw data for examining effect of hypnotic suggestion on cognition and craving
DOI: 10.17632/y92b2h27jv.1
title: Data for: Revised and extended benchmark results for Rayleigh scattering of sunlight in spherical atmospheres

description: Tables from the paper in Excel
DOI: 10.17632/cj5d332zyv.2
title: Bridge failures/collapses
DOI: 10.17632/sf628sb2cn.1
title: Refining rates of active crustal deformation in the upper plate of subduction zones, implied by geological and geodetic data: The E-dipping West Crati Fault, southern Italy.

description: We investigate crustal deformation within the upper plate of the Ionian Subduction Zone (ISZ) at different time scales by (i) refining geodetic rates of crustal extension from continuous Global Navigation Satellite System (GNSS) measurements and (ii) mapping sequence of Late Quaternary raised marine terraces tectonically deformed by the West Crati normal fault, in northern Ca-labria. This region experienced damaging earthquakes in 1184 (M 6.75) and 1854 (M 6.3), possi-bly on the E-dipping West Crati fault (WCF) which, however, is not unanimously considered to be a seismogenic source. We report geodetic measurements of extension and strain rates across-strike the E-dipping WCF and throughout the northern Calabria obtained by using veloci-ties from 18 permanent GNSS stations with series length longer than 4.5 years. These results sug-gest that crustal extension may be seismically accommodated in this region by a few normal faults. Furthermore, by applying a synchronous correlation approach we refine the chronology of understudied tectonically-deformed palaeoshorelines mapped on the footwall and along the strike of the WCF, facilitating calculation of the associated fault-controlled uplift rates. Raised Late Quaternary palaeoshorelines are preserved on the footwall of the WCF indicating that “re-gional” uplift, likely related to the deformation associated either with the subduction or mantle upwelling processes, is affected by local footwall uplift. We show that GIS-based elevations of Late Quaternary palaeoshorelines, as well as temporally constant uplift rates, vary along the strike of the WCF, implying normal faulting activity through time. This suggests that (i) the fault slip-rate governing seismic hazard has also been constant over the Late Quaternary, over multiple earthquake cycles and (ii) our geodetically-derived fault throw-rate for the WCF is likely a more than reasonable value to be used over longer time scales for an improved seismic hazard assess-ment. Overall, we emphasize the importance of mapping crustal deformation within the upper plate above subduction zones to avoid unreliable interpretations relating to the mechanism controlling regional uplift.
DOI: 10.17632/fy7c4z4vbn.1
title: ELC Software and Tutorial

description: The files presented here are part of a long-term effort in developing stable and tractable simulation tools for modeling desalination by capacitive deionization (CDI). Recently, we presented an electrolytic-capacitor (ELC) model, which blends CDI modeling with existing tools in battery and supercapacitor simulations. Here, we present a comprehensive COMSOL file for implementing the model. There is also a video tutorial showing how to use the model.

The model can simulate time-dependent CDI processes in 2D. The model generates trends for the internal concentration, the current, the adsorption, the cumulative adsorption and current, and the cell voltage. It also stimulates the internal flow distribution. Optional features that are covered include CV/CC charging, continuous/batch flow mode, and options to include leakage reactions. The physics are set up so that the geometry can be independently changed to simulate new devices.

In short, we present a versatile software for simulating a broad range of CDI processes.
DOI: 10.17632/vz8pyyfjyy.1
title: Data for: Impact of female students’ perceptions on behavioral intention to use video conferencing tools in COVID-19: Data of Vietnam

description: The data set shows 254 valid records about behavioural intention on selecting conferencing tools (VCTs; e.g. Zoom, Microsoft Teams or Google Hangout) of Vietnam female students in the context of the COVID-19 pandemic. The survey was conducted on an online platform and the questionnaire consists of 21 items to collect the respondents’ characteristics, their perception on computer self-efficacy, computer playfulness, COVID-19 context, behavioural intention to Use VCTs.
DOI: 10.17632/29b5dzk6tf.2
title: Effects of Defects on Laminate Quality and Mechanical Performance in Thermoplastic Automated Fiber Placement-based Process Chains

description: The corresponding paper (open-access gold) investigates the effects of process specific defects on the laminate quality and mechanical performance for the Thermoplastic Automated Fiber Placement (TAFP) process. The coupon panels were made of polyphenylene sulfide with 60 %wt. continous carbon fiber reinforcment. Subsequent to TAFP layup, three different consolidation processes were applied. Furthermore, stacking sequence, defect type and defect size were varied. Tensile testing of the specimens was conducted according to DIN ISO 527. A GOM Aramis digital extensiometer was used for strain recording. Compression testing was conducted in reference to ASTM-6484. The data provided contains the raw data from the testing machine for both compression and tensile testing. For the latter, the export of the ARAMIS strain concantration measurements is provided as well. Within all data sets, the specimens are refered to with the same nomenclature that is used in the paper. Each parameter set is addressed by XX-Y-Z-S, where XX is the consolidation process, Y is the stacking sequence, Z is the type of defect and S is the defects size. Each testing machine data file contains all five specimen tested as seperate tab. The tabe are named with an internal testing number followed by the specimen index. The ARAMIS strain data is only provieded for the specimen that was considered for the plot and image generation. The authors did ensure that the selected specimen is representative for the corresponding group by subjective comparison of the strain measurements and plots.
DOI: 10.17632/dkf65jd9fc.1
title: Data on A Goal Programming Model for Optimizing the Reverse Logistics Network of Glass Containers, and an Application in Turkey

description: Since there is no data available in the literature or through internet, we really made an effort to find real data and try to estimate non-available data through available ones, correctly. Scalar and parameters of the mathematical model in the study are estimated according to assumptions shown as below, and are given in folders. Assumptions • There are 3 source of glass containers. These are from recycle bins, HORECA and other waste recyclers, and those amounts are estimated according to some past data. • All cost parameters are foreknown which are calculated from real data, and will be shown in detail. • Cost parameters will be determined with estimated inflation rate for the future periods and revenue parameters will be determined according to government payments per ton of recycled glass. • Glass container consumption is directly proportional with the population of a town. So, for districts in which this data does not exist, the amount of glass can be collected through recycle bins is estimated according to their populations. • The glass container source from other recyclers are assumed as 10% of total amount of glass containers available through recycle bins in each period. • At the beginning of first period, 10 million Turkish Liras (TL) budget is available. Thereby, Bp parameter becomes 10,000,000 for the first period and 0 for the rest of periods. • For operational side of glass recycling facility, we have stayed in touch with a real firm named “Cam Kırığı” located in Gebze/Istanbul through telephone interviews to get data (telephone interview, March 2019). • The information about the glass manufacturer belongs to Sisecam Company, which is biggest glass manufacturer in Turkey. • Equivalent cost parameters for future periods will be adjusted according to official price increases and inflation expectations. • 1 year consists of 250 workdays. So, WD scalar becomes 250. • Distances between facilities and glass container sources are based on highway routes. • One driver and one assistant are required for each truck type 1 whereas only a driver is needed for truck type 2. So, these are summed with the required number of workers in the facility in order to find total number of personnel.
DOI: 10.17632/bs2j56pn7y.3
title: Graphite//LFP synthetic V vs. Q dataset (&gt;700,000 unique curves)

description: This dataset contains more than 700,000 unique voltage vs. capacity curves. It was calculated using the mechanistic modeling approach. See “Big data training data for artificial intelligence-based Li-ion diagnosis and prognosis“ (Journal of Power Sources, Volume 479, 15 December 2020, 228806) and "Analysis of Synthetic Voltage vs. Capacity Datasets for Big Data Li-ion Diagnosis and Prognosis" (Energies, under review) for more details. This dataset was compiled with a resolution of 0.01 for the triplets and C/25 charges. This accounts for more than 5,000 different paths. Each path was simulated with at most 0.85% increases for each degradation mode. 4 Variables are included, see read me file for details and example how to use.
DOI: 10.17632/jxzgfw47wg.2
title: Data and Code for 'Machine-Learning the Skill of Mutual Fund Managers'

description: Data and Code for 'Machine-Learning the Skill of Mutual Fund Managers'
DOI: 10.17632/4hh45vkp38.5
title: Data for: Deep learning-based early weed segmentation using motion blurred UAV images of sorghum fields

description: Weeds are undesired plants in agricultural fields that affect crop yield and quality by competing for nutrients, water, sunlight and space. Site-specific weed management (SSWM) through variable rate herbicide application and mechanical weed control have long been recommended in order to reduce the amount of herbicide and impact caused by uniform spraying. Accurate detection and classification of weeds in crop fields is a crucial first step for implementing such precise strategies. Drones are commonly used for image capturing but high wind pressure and different drone settings have a severe effect on the image quality, which potentially results in degraded images, e.g. due to motion blur. 
We publish a manually annotated and expert curated drone image dataset for weed detection in sorghum fields under challenging conditions. Our results show that our trained models generalize well regarding the detection of weeds, even for degraded captures due to motion blur. An UNet-like architecture with ResNet-34 as feature extractor achieved an F1-score of over 89 % on a hold-out test-set. Further analysis indicate that the trained model performed well in predicting the general plant shape, while most mis-classifications appeared at borders of the plants. Beyond that, our approach can detect intra-row weeds without additional information as well as partly occluded plants in contrast to existing research.

Github link: https://github.com/grimmlab/UAVWeedSegmentation

Please cite our original publication if you have used the data in your project or in any follow-up analysis (https://doi.org/10.1016/j.compag.2022.107388): 

@article{GENZE2022107388,
title = {Deep learning-based early weed segmentation using motion blurred UAV images of sorghum fields},
journal = {Computers and Electronics in Agriculture},
volume = {202},
pages = {107388},
year = {2022},
issn = {0168-1699},
doi = {https://doi.org/10.1016/j.compag.2022.107388},
url = {https://www.sciencedirect.com/science/article/pii/S0168169922006962},
author = {Nikita Genze and Raymond Ajekwe and Zeynep Güreli and Florian Haselbeck and Michael Grieb and Dominik G. Grimm},
keywords = {Deep learning, Weed detection, Weed segmentation, UAV, Precision agriculture},
}
DOI: 10.17632/nc995wjbmm.1
title: Exploring Synthetic Routes to Heteroleptic UIII, UIV and ThIV Bulky Bis(silyl)amide Complexes

description: Research support data for paper.
DOI: 10.17632/5c723rpwz2.2
title: HiSBreast

description: This is a dataset of breast ultrasound images of patients collected from Ca Mau province general hospital - Vietnam. This data set includes 972 samples, and each sample has 03 parts: ultrasound image, description of signs and characteristics of breast tumors based on that image, and diagnosis results of doctors. All information is presented in Vietnamese.
The data set is organized into 04 folders:
- The "json" folder contains original information about the data such as: images in based64 format, descriptions, diagnoses, patient codes,...
- The "image" folder contains images that have been decoded from base64 format in json file.
- The "diagnoses" folder contains doctor's diagnoses corresponding to the images in the image folder.
- "descriptions" folder: contains descriptions of signs and disease characteristics corresponding to the images in the image folder.
DOI: 10.17632/9kxpndx6xg
title: Article Trichoscopic Features and Measurable Hair Shaft Parameters for the Healthy Female Dark Scalp: A Cross Sectional Study.

description: This data contains supplementary tables of the article Trichoscopic Features and Measurable Hair Shaft Parameters for the Healthy Female Dark Scalp: A Cross Sectional Study.
DOI: 10.17632/9jy9j7zgkc.1
title: Examining Academic Performance: A Holistic Approach to Identifying Influential Factors in Higher Education

description: In an increasingly competitive educational landscape, understanding the dynamics that affect student performance is crucial. Our research focuses on eight key independent variables: study habits, motivation, health and well-being, learning environment, teaching quality, peer influence, background knowledge, and exam anxiety. By employing a mixed-methods approach, we gathered quantitative data through a structured questionnaire that employed a Likert scale, allowing for a nuanced measurement of each variable's impact.
This research contributes to the growing body of literature emphasizing the need for holistic educational interventions that address both cognitive and emotional factors affecting student success. The insights gained from this study can inform educators, policymakers, and institutions in developing effective strategies to enhance academic outcomes in higher education.
DOI: 10.17632/5tj2yr7fs3.1
title: Classification, structure and key performance indicators of business channels

description: The purpose of this article is to clarify and supplement the theory and methodology of creating business channels as components of business systems in statics and dynamics, including design, digitalization, optimality assessment and balancing of their objects and components.
Methods of classification, synthesis, analysis, induction and deduction were chosen as re-search methods, and binary matrices formed on the basis of classification attributes of objects and components of business channel management, as well as their dichotomies, were used as a research tool.
The article develops the classification of business channels as components of business systems and their links, as well as the business processes performed by them; the structure of business channels is defined; the sequences of their creation are formed; a system of balanced criteria for the optimality of business channels is created; a sequence of balancing objects and components of a business channel is developed, and creating prerequisites for design and the formation of business systems of a more complex type.
DOI: 10.17632/rdj594v745.2
title: Data for: Fertilizer adoption by smallholders in the Brazilian Amazon: farm-level evidence

description: STATA(r) dataset and do file
DOI: 10.17632/rxr4rr9bw3.2
title: CTI and APT Related Dataset and Source Code for the Paper in Short: DEVIL

description: Here are the data set and source code related to the paper: "DEVIL: A Framework for Discovering and Evaluating Insidious Advanced Persistent Threats Leveraging Graph-Based Algorithms"

1- aptnotes-downloader.zip : contains source code that downloads all APT reports listed in https://github.com/aptnotes/data and https://github.com/CyberMonitor/APT_CyberCriminal_Campagin_Collections

2- apt-groups.zip : contains all APT group names gathered from https://docs.google.com/spreadsheets/d/1H9_xaxQHpWaa4O_Son4Gx0YOIzlcBWMsdvePFX68EKU/edit?gid=1864660085#gid=1864660085 
and https://malpedia.caad.fkie.fraunhofer.de/actors

3- apt-reports.zip : contains all deduplicated APT reports gathered from https://github.com/aptnotes/data and https://github.com/CyberMonitor/APT_CyberCriminal_Campagin_Collections

4- countries.zip : contains country name list. 

5- ttps.zip : contains all MITRE techniques gathered from https://attack.mitre.org/resources/attack-data-and-tools/

6- malware-families.zip : contains all malware family names gathered from https://malpedia.caad.fkie.fraunhofer.de/families

7- ioc-searcher-app.zip : contains source code that extracts IoCs from APT reports. Extracted IoC files are provided in report-analyser.zip. Original code repo can be found at https://github.com/malicialab/iocsearcher

8- extracted-iocs.zip : contains extracted IoCs by ioc-searcher-app.zip

9- report-analyser.zip : contains source code that searchs APT reports, malware families, countries and TTPs. I case of a match, it updates files in extracted-iocs.zip. 

10- cti-transformation-app.zip : contains source code that transforms files in extracted-iocs.zip to CTI triples and saves into Neo4j graph database.

11- graph-db-backup.zip : contains volume folder of Neo4j Docker container. When it is mounted to a Docker container, all CTI database becomes reachable from Neo4j web interface. Here is how to run a Neo4j Docker container that mounts folder in the zip:

docker run -d --publish=7474:7474 --publish=7687:7687 --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/data:/data --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/plugins:/plugins --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/logs:/logs --volume={PATH_TO_VOLUME}/DEVIL_NEO4J_VOLUME/neo4j/conf:/conf --env 'NEO4J_PLUGINS=["apoc","graph-data-science"]' --env NEO4J_apoc_export_file_enabled=true --env NEO4J_apoc_import_file_enabled=true --env NEO4J_apoc_import_file_use__neo4j__config=true --env=NEO4J_AUTH=none neo4j:5.13.0

web interface: http://localhost:7474
username: neo4j
password: neo4j
DOI: 10.17632/ynmxmgk7mk.1
title: Artificial_Voice_Assistant_for_COVID_19_Suspects

description: COVID-19 outbreak occurred from China which spreads between people through close contact of the infected person. In this pandemic, managing such a high number of patients is difficult. Already, 5.3 million people have died. For this disease, people from all over the world became interested on telemedicine. Till now lots of people solved many problems using telemedicine that’s why we are proposing Artificial intelligence voice assistant that can help whether a particular person is COVID-19 suspected or not. Our artificial voice Assistant to help people deal with this type of circumstance. We design some questionnaires that will be asked by the machine and user will answer accordingly. Then based on their answer machine will analysis and predict, whether that particular user might have COVID or not. We took a survey and collected data from different 513 peoples. We applied several machine learning algorithms like Gini Index, Random Forest, Entropy, KNN, Decision Tree. Out of that random forest provide us the highest accuracy. Throughout the research, using random forest algorithm, we had a 92.85% prediction accuracy, which was reasonable. So, our ultimate goal is during this kind of epidemic, medical voice assistant, assists people in overcoming any problems they may be experiencing.