cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/th7fztbrv9.11
title: Data for: USING MACHINE LEARNING TO PREDICT OVARIAN CANCER

description: Supplementary data 1: It contains the original raw data. Supplementary data 2: It contains a list of biomarkers, their abbreviations, and their descriptions used in the study. Supplementary data 3: It contains the imputed version of the training data without the biomarker CA72-4. Supplementary data 4: It contains the raw training data. Supplementary data 5: It contains the raw test data.
DOI: 10.17632/6ns4xkbnf3.2
title: Data set for the ANN prediction of landslide coverage area

description: This is data set for the ANN prediction of landslide coverage area , associated with the submission of Paper "Prediction on coverage area of flow-like landslides considering the influence of random strength parameters based on artificial neural network model".
DOI: 10.17632/y8g64m2v52.1
title: Data for: A global erosivity index to represent sevgroduction potential of different rock types

description: A gridded representation of the global erodibility index described in the linked paper. This erodibility index is the first estimate of sediment production potential of different rock types at given environmental conditions aimed at regional to global scale application. The index is 1.0 for acid plutonic rocks, metamorphic rocks, and carbonate sedimentary rocks; medium erodibility: 1.1 for acid volcanic rocks; 1.2 for mixed sedimentary rocks; medium erodibility - 1.5 for basic plutonic rocks, siliciclastic rocks of all grain sizes; 1.4 for basic volcanic rocks; high erodibility – 3.2 for unconsolidated sediments. The gridding of 0.1 degrees to align with the gridding of the BQUART model.
DOI: 10.17632/574v66hf2v.1
title: Product Reviews Dataset for Emotions Classification Tasks - Indonesian (PRDECT-ID) Dataset

description: PRDECT-ID Dataset is a collection of Indonesian product review data annotated with emotion and sentiment labels. The data were collected from one of the giant e-commerce in Indonesia named Tokopedia. The dataset contains product reviews from 29 product categories on Tokopedia that use the Indonesian language. Each product review is annotated with a single emotion, i.e., love, happiness, anger, fear, or sadness. The group of annotators does the annotation process to provide emotion labels by following the emotions annotation criteria created by an expert in clinical psychology. Other attributes related to the product review are also extracted, such as Location, Price, Overall Rating, Number Sold, Total Review, and Customer Rating, to support further research.
DOI: 10.17632/rnbsw72zb5.1
title: Tomato Leaf Image Dataset for Disease Analysis in Real-World Environment

description: The dataset comprises a total of 1,028 images of tomato leaves collected in Bangladesh, with 486 images depicting healthy leaves and 546 images showing diseased leaves. Each image has been carefully annotated to indicate specific regions as either healthy or diseased, given that each image includes a complex background. The annotations are provided as text files, where each image file has a corresponding text file with the same name to facilitate model implementation. Healthy images are labelled with "H," while diseased images are labeled with "D." For structured model development, the dataset is divided into two folders: a validation folder and a training folder. The validation folder contains 160 images, equally split between 80 healthy and 80 diseased leaves, while the training folder includes the remaining 868 images. This dataset is particularly valuable for training and validating deep learning and machine learning algorithms aimed at detecting diseases in tomato leaves. It offers researchers and learners a robust resource for analysing and improving the health management of tomato plants through the development of advanced computational models.
DOI: 10.17632/fk29shm2kn.2
title: Dataset Of Animal Images

description: The Animal Image Dataset is a curated collection of high-resolution images of eight animals, including rabbits, goats, sheep, dogs, cows, hens, cats, and deer. This dataset focuses on night vision skills and includes photos taken in low-light circumstances to replicate nighttime driving scenarios. This focus assures that the dataset is particularly valuable for vehicles to detect and respond to animals in the dark, improving safety and lowering the chance of collisions while driving at night.
DOI: 10.17632/8gx2fvg2k6.1
title: DataCo SMART SUPPLY CHAIN FOR BIG DATA ANALYSIS

description: A DataSet of Supply Chains used by the company DataCo Global was used for the analysis. Dataset of Supply Chain , which allows the use of Machine Learning Algorithms and R Software. Areas of important registered activities : Provisioning , Production , Sales , Commercial Distribution.It also allows the correlation of Structured Data with Unstructured Data for knowledge generation. Types of Products : Clothing , Sports , and Electronic Supplies Additionally it is attached in another file called DescriptionDataCoSupplyChain.csv, the description of each of the variables of the DataCoSupplyChainDatasetc.csv.
DOI: 10.17632/96pv72nj83.1
title: Table 1: ChatGPT Inputs, Outputs, and Categories of Suggested Diagnoses for Malignant and Benign Skin Neoplasms.

description: Table 1: ChatGPT Inputs, Outputs, and Categories of Suggested Diagnoses for Malignant and Benign Skin Neoplasms.
DOI: 10.17632/sf74hptxht.1
title: Table 1- A list of interacting proteins for AURKB

description: Table 1- A list of interacting proteins for AURKB.
DOI: 10.17632/83ht2kc8xt.1
title: First-principles calculations of specular reflection of high-energy electrons during the two-dimensional crystal growth

description: RHEED_DIFF_2D is an open-source software capable of performing qualitative numerical simulations of changes to the intensity of RHEED oscillations in the function of the layer deposited, employing various models of scattering crystal potential for heteroepitaxial structures of bcc (001) films nucleated on a fcc (001) surface, including the possible existence of various diffuse scattering models through the layer parallel to the surface. This model can be used for interpreting data weakly dependent on the azimuth of the incident electron beam direction and for 2D monolayer-by-monolayer growth modes. The program does not use any external data sources.
DOI: 10.17632/jg8tr5cw8g.1
title: Nutrient budget and biogeochemical dynamics in Sansha Bay, China: a coastal bay affected by intensive mariculture

description: This file provides the detailed dataset on the hydrological characteristics and nutrient concentrations collected in each station in Sansha Bay during the investigation period. This dataset is used to generate Tables and Figures in the manuscript.
DOI: 10.17632/ns87rtkv58.2
title: Dataset on Academic Performance of Computer Science Students at Selected Universities in Bangladesh

description: The dataset comprises a comprehensive survey of 894 Computer Science students from IUBAT University in Bangladesh, detailing various aspects of student performance. It includes demographic information such as University Admission Year, Gender, Age, and H.S.C Passing Year. Academic details cover the Program, Current Semester, Meritorious Scholarship, SGPA, Current CGPA, and Credits Completed. Study habits and learning preferences are assessed through Daily Study Hours, Number of Study Sessions per Day, Preferred Learning Mode, Average Class Attendance, and Attendance at Teacher Consultancy. Technology usage is evaluated by Smartphone Use, Possession of a Personal Computer, and Time Spent on Social Media. Language proficiency is indicated by the Status of English Language Proficiency. Behavioral and risk factors include incidents of Probation, Suspension, Health Issues, and Physical Disabilities. Finally, Skill Development and Interests are measured by Skills, Hours Spent Daily on Skill Development, Areas of Interest, and Participation in Co-curricular Activities, while Personal and Social Life is represented by Relationship Status and Living Arrangements, and Financial Information is captured by Monthly Family Income.
DOI: 10.17632/vfn2g8xg36.1
title: Comparison of Design Approaches for Low-Cost Sampling Mechanisms in Open-Source Chemical Instrumentation

description: Robotic positioning systems are used in a variety of chemical instruments, primarily for liquid handling purposes, such as autosamplers from vials or well plates. Here, two approaches to the design of open-source autosampler positioning systems for use with 96-well plates are described and compared. The first system, a 3-axis design similar to many low-cost 3D printers that are available on the market, is constructed using an aluminum design and stepper motors. The other system relies upon a series of 3D printed parts to achieve movement with a series of linker arms based on Selective Compliance Assembly Robot Arm (SCARA) design principles. Full design files and software are included for both samplers in this repository. The positioning precision of the 3-axis system is better than the SCARA mechanism due to finer motor control, albeit with a slightly higher cost of materials. Based on the improved precision of this approach, the 3-axis autosampler system was used to demonstrate the generation of a segmented flow droplet stream from adjacent wells within a 96-well plate. Build instructions and other information is available in the associated HardwareX article.
DOI: 10.17632/j5zdrhr9bf.2
title: wPCC manoeuvring model tests

description: Model test data from research project at SSPA Maritime Dynamics Laboratory.
Used in paper: System identification of Vessel Manoeuvring Models
DOI: 10.17632/w7t33r49yx.2
title: Dial-a-Ride Problem (DARP) data set from Ouro Preto-MG, Basil

description: The data was used on a dissertation to obtain a Master degree. The research is "A based-VNS algorithm to solve the Dial-a-RIde Problem". The data set was created based on the data given by the transportation sector of the Health System of the Ouro Preto City Hall. The archive README.txt has all information about the instances created.
DOI: 10.17632/t9h6p943xy.4
title: B-SER: A Bangla speech emotion recognition dataset

description: B-SER is an audio-speech emotion recognition dataset for the Bangla language. The developed dataset consists of voice data from 34 speakers from diverse age groups between 19 to 47 (mean = 28.75 and Standard deviation = 9.346), equally balanced with 17 males and 17 females. This dataset contains 1224 speech-audio data recordings.  There are 4 emotional states recorded for three sentences. The 3 sentences are i. ‘বারোটা বেজে গেছে,’ ii. ‘আমি জানতাম এমন কিছু হবে’, and iii. ‘এ কেমন উপহার’. These emotional states are Angry, Happy, Sad, and Surprise. The format of the audio file is a . WAV format.  The data files are divided into 34 individual folders. Each folder contains 36 audio recordings of each participating actor. The size of the B-SER dataset is 619 MB. While most of the existing datasets of different languages are recorded inside a closed studio or cover a single sentence, this dataset is collected by recording through smartphones, hence preserving the slightly noisy real-life environment. B-SER is compatible with various shallow machine learning and deep learning architectures such CNN, LSTM, HMM, Transformer, etc.  The naming of each audio file of the B-SER dataset is inspired by the RAVDESS dataset. The filename consists of seven two-digit numerical identifiers, separated by hyphens (e.g., 03-01-01-01-02-02-02.wav). Each two-digit numerical identifier defines the level of a different experimental factor. The identifiers are ordered: Modality - Scripted - Name of emotion - Intensity - Statement number - Number of repetition - Actor.wav. For example, the filename “03-01-02-01-03-03-02.wav” refers to: Audio only (03) - Scripted (01) - Sad (02) - Normal intensity (01) - 3rd Statement (03) - 3rd Repetition (03) - 2nd Actor (even number-female actor, odd number-male actor) (02).
DOI: 10.17632/xs5kp2v4tr.2
title: Replication Material for "Credit Growth, the Yield Curve and Financial Crisis Prediction: Evidence from a Machine Learning Approach"

description: This archive contains the replication material for the research paper "Credit Growth, the Yield Curve and Financial Crisis Prediction: Evidence from a Machine Learning Approach" in the Journal of International Economics. A detailed description of the code and data is provided in readme/readme.pdf
Should you have any questions or spot a bug in the code, please send an email to marcus.buckmann@bankofengland.co.uk.
DOI: 10.17632/9h4xyfnvny.1
title: Manzano, Günther et al. 2020

description: Supplemental Tables Describing Analyzed Datasets for Manzano, Günther et al. 2020
DOI: 10.17632/hwb9rn9w9h.3
title: SCARED-C

description: The dataset SCARED-C is introduced in the context of assessing robustness in endoscopic depth prediction models. It is part of the EndoDepth benchmark, which is designed to evaluate the performance of monocular depth prediction models specifically for endoscopic scenarios. The dataset features 16 different types of image corruptions, each with five levels of severity, encompassing challenges like lens distortion, resolution alterations, specular reflection, and color changes that are typical in endoscopic imaging. The ground truth is on the original testing set of SCARED. 
The purpose of SCARED-C is to test the robustness of depth estimation models by exposing them to various common endoscopic corruptions. This dataset is a valuable tool for developing and evaluating depth prediction algorithms that can handle the unique challenges presented by endoscopic procedures, ensuring more accurate and reliable outcomes in medical imaging.
DOI: 10.17632/dv3yxsnhcg.5
title: Environmental and Social Disclosures of Public Listed Companies in Malaysia: A Dataset

description: This dataset comprises the level of environmental and social information disclosure of the top 100 Malaysian companies from 2018 to 2020.
DOI: 10.17632/phybjpxg63.1
title: Guidelines to teach Present Perfect

description: Teaching the present perfect tense effectively requires a clear structure, relavant examplesn and plenty of opportunities for practice. Here is a step-by-step guide that outlines an approach to introducing and practicing the present perfect tense in a communicative approach which is the methodoly used by Universidad Cooperativa de Colombia
DOI: 10.17632/43y5zssf4k.2
title: Riverine Bridges: A Hydrological Vulnerability Appraisal

description: Recent studies on the recurrence and severity of meteorological phenomena suggest that these indicators have increased considerably due to several factors, including climate change. Important infrastructure such as riverine bridges have demonstrated a lack of resilience to the consequences of these phenomena. It is important, then, to analyze their vulnerability for future interventions and thus mitigate the risk to users. Through the case study of the Bajo Grau Bridge in Peru, which crosses the Chili River, a methodology is proposed to identify the most relevant parameters for diagnosing the condition of riverine bridges in order to determine their hydrological vulnerability.

A fundamental aspect of achieving the research objective is data collection and analysis. Since the analysis is interdisciplinary, it is important to manage information from all areas in an optimal way. That is why this dataset presents six folders with information used as primary source in the case study of the Bajo Grau Bridge. First, the Hydrological Data is presented in XLS file, which contains the record of maximum monthly flows since 1960, provided by Autodema. Second, the Soil Data folder is included in XLS file, which shows the granulometry of the soil and the roughness of the channel, this information was obtained through a test pit in the riverbed. Third, the Topological Data in DWG file format, which contains the contour lines every one meter, this information was obtained through a topographic survey. Fourth, photos of the bridge are presented in JPG format, as part of the field visit. Fifth, photos of the granulometric study are included in JPG. Sixth, the hydraulic model in HEC-RAS is presented. Seventh, JPG photographs of the hydraulic models for the proposed scenarios are included.

The processing of the information, presented in detail in the scientific article "Hydrological Vulnerability Assessment of Riverine Bridges: The Bajo Grau Bridge Case Study", made it possible to determine the hydrological vulnerability of the Bajo Grau bridge as a high vulnerability, based on 10 criteria subdivided into physical and environmental vulnerabilities. The methodology used for this case study can be replicated in other riverbed bridges. The information contained in this dataset is intended to contribute to a better understanding of hydrological evaluations in river channels and their possible future implementation.
DOI: 10.17632/bzk9zbyvv7.1
title: Online Education System - Review

description: Pandemic has influenced all spheres of the humanity.  COVID-19 impacted the education vertical in larger manner. Traditional classroom environment plays a very vital role in molding the life of an individual. Bond nurtured in the early ages of the life acts as the great moral support in the latter stages of the journey. As the pandemic has forced us into online education, this data collection aims to analyze the impact of online education. To check out the satisfactory level of the learners, review was conducted.

Gender – Male, Female
Home Location – Rural, Urban
Level of Education – Post Graduate, School, Under Graduate
Age – Years
Number of Subjects – 1- 20 
Device type used to attend classes – Desktop, Laptop, Mobile
Economic status – Middle Class, Poor, Rich
Family size – 1 -10
Internet facility in your locality – Number scale (Very Bad to Very Good)
Are you involved in any sports? – Yes, No
Do elderly people monitor you? – Yes, No
Study time – Hours
Sleep time – Hours
Time spent on social media – Hours
Interested in Gaming? – Yes, No
Have separate room for studying? – Yes, No
Engaged in group studies? – Yes, No
Average marks scored before pandemic in traditional classroom – range
Your interaction in online mode - Number scale (Very Bad to Very Good)
Clearing doubts with faculties in online mode - Number scale (Very Bad to Very Good)
Interested in? – Practical, Theory, Both
Performance in online - Number scale (Very Bad to Very Good)
Your level of satisfaction in Online Education – Average, Bad, Good
DOI: 10.15468/dl.t8nvh6
title: Occurrence Download

description: A dataset containing 35 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Melocanna Trin."
 ]
}

 The dataset includes 35 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0009346-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/9ygs9vhnpw.1
title: Allergen30

description: Allergen30 is created with the goal of building a robust detection model that can assist people in avoiding possible allergic reactions. It contains images of 30 commonly used food items that can cause an adverse reaction within a human body. These food items pertain to specific food intolerances which can trigger an allergic reaction. Such food intolerance primarily includes Lactose, Histamine, Gluten, Salicylate, Caffeine, and Ovomucoid intolerance.

The 30 food items (labels) in the dataset include 'alcohol', 'alcohol glass', 'almond', 'avocado', 'blackberry', 'blueberry', 'bread', 'bread loaf', 'capsicum', 'cheese', 'chocolate', 'cooked meat', 'dates', 'egg', 'eggplant', 'icecream', 'milk', 'milk based beverage', 'mushroom', 'non milk based beverage', 'pasta', 'pineapple', 'pistachio', 'pizza', 'raw meat', 'roti', 'spinach', 'strawberry', 'tomato' and 'whole egg boiled'.
DOI: 10.17632/2jpy5233nb.1
title: Techno-economic evaluation of CO2 electrolysis Excel tool

description: Attached Excel tool allows for evaluation of the operational and investments cost for CO2 electrolysis (low and high-temperature, C1 and C2 products). Please see the article "Techno-economic assessment of emerging CO2 electrolysis technologies" by Barecka, Ager and Lapkin for the detailed description of the Excel tool use.
DOI: 10.17632/tzyy8gb9x3.1
title: Mitochondrial translational defect extends lifespan in C. elegans by activating UPRmt

description: To study the function of mitochondrial tars-1 (representing the ORF encoding CeThrRS-1), we used CRISPR–Cas9 to generate a mitochondrial tars-1 knockdown strain of C. elegans named tars-1(ora1) Ⅱ by mutating the start codon “ATG1” to “ACG1”, and the stain was confirmed by whole-exome sequencing.To study the mechanism of abnormal phenotypes in tars-1(ora1) Ⅱ, RNA-Seq was performed. We performed quantitative proteomics by LC–MS/MS to detect the protein abundance in N2 and tars-1(ora1) Ⅱ. Mitochondrial and cytosolic translation are dynamically regulated in a synchronized manner .
DOI: 10.17632/gx8bmc3hmz.1
title: ItMRnet

description: An iterative solution for improving the generalization ability of unsupervised skeleton motion retargeting

>>>>>>>>>Downloading  and Preprocessing Data<<<<<<<<<
    All data we use are come from the website of mixamo(https: //www.mixamo.com/ ).  You need to create an account to get the animation files. There is a way to quickly start downloading files.
> *https://github.com/gnuton/mixamo_anims_downloader*
   Once the fbx animation files have been downloaded, run *fbx2bvh* in Blender(note: press *"Shift + F11"* to jump to the script screen). Then, process the bvh files into npy file by *bvh2npy.py*.

>>>>>>>>>Training Phase<<<<<<<<<
  Training ItMRNet by:
  > *./src/ItMRnet_Train.py*
 The model will be saved at  "./models". We also provide pre-trained models to get the help started quickly(models are saved at "./models").

>>>>>>>>>Execution Phase<<<<<<<<<
  Executing ItMRnet by:
  >*./src/ItMRnet_Test.py*
  The details of the four groups of experiments are shown at *https://drive.google.com/file/d/1T0o6kFho96CniyjX7LXV_xgaeHlDJqbV/view?usp=sharing*.
  The experimental data are shown at "./datasets/test/"

>>>>>>>>>Evaluation<<<<<<<<<
> Run* ./result/evaluate.py*

>>>>>>>>Rendering model to generate videos<<<<<<<<<
    Download blender files with character skins -->https://drive.google.com/file/d/1m_n1RzdmOv8o1KQJpH3YDC0Drb7KcH8Z/view?usp=sharing
    >Run  *./result/make_videos.py* to generate videos.	
    The visualization results of ItMRNet are all placed in the video at https://drive.google.com/file/d/15Jv_qdcdsS8Rn26lIZc-o5T8YaKgi17R/view?usp=sharing.

>>>>>>>>>IK processing<<<<<<<<<
Please refer to this work：*https://github.com/DeepMotionEditing/deep-motion-editing*