cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/x5sxsnprbd.1
title: Emotional link between color and music - Raw dataset

description: Raw data from 60 participants (P#) for the assessment of (A) the music-to-color association, (B) the perceptual characteristics and emotion of color, and (C) the emotion of music. Part A consists on the selection of the three most (+) and the three least (-) representative colors, from the 37 colors based on the Berkeley Color Project (Schloss, Poggesi, & Palmer, 2011), for each of the 16 musical stimuli; colors are labeled with an alphanumeric ID. Part B consists on the evaluation of each of the 37 colors, according to the variables of Red-Green, Yellow-Blue, Saturation, Brightness, Valence, and Arousal, on a scale from -100 to +100. Part C consits on the evaluation of each of the 16 musical stimuli, according to the variables of Valence, Arousal, Pleasure, and Familiarity, on a scale from -100 to +100. All data was anonymously acquired with the informed consent of each of the 60 participants, according to the World Medical Association (2013), for academic, research, and publication purposes. For more information, see Valdés-Alemán, Zamudio-Gurrola, and Téllez-Alanís (on press).

References:
<div class="csl-entry">Schloss, K. B., Poggesi, R. M., &#38; Palmer, S. E. (2011). Effects of university affiliation and “school spirit” on color preferences: Berkeley versus Stanford. <i>Psychonomic Bulletin and Review</i>, <i>18</i>(3), 498–504. https://doi.org/10.3758/s13423-011-0073-1</div>
<div class="csl-entry">Valdés-Alemán, P., Zamudio-Gurrola, A., &#38; Téllez-Alanís, B. (on press). The Emotional Link Between Color and Music: What Happens with Atonal Music? <i>Psychomusicology: Music, Mind, and Brain</i>, 1–35.</div>
<div class="csl-entry">World Medical Association. (2013). World Medical Association Declaration of Helsinki. <i>Journal of American Medical Association</i>, <i>310</i>(20), 2191–2194. https://doi.org/10.1001/jama.2013.281053</div>
DOI: 10.17632/h7pf57cgg9.1
title: Pistachio Image Dataset

description: Citation Request :
1. OZKAN IA., KOKLU M. and SARACOGLU R. (2021). Classification of Pistachio Species Using Improved K-NN Classifier. Progress in Nutrition, Vol. 23, N. 2, pp. DOI:10.23751/pn.v23i2.9686.  (Open Access) 
2. SINGH D, TASPINAR YS, KURSUN R, CINAR I, KOKLU M, OZKAN IA, LEE H-N., (2022). Classification and Analysis of Pistachio Species with Pre-Trained Deep Learning Models, Electronics, 11 (7), 981. https://doi.org/10.3390/electronics11070981. (Open Access) 
DATASET: https://www.muratkoklu.com/datasets/

https://www.mattioli1885journals.com/index.php/progressinnutrition/article/view/9686/9178
ABSTRACT: A computer vision system has been developed to distinguish two different species of pistachios with different characteristics that address different market types. 2148 sample image for these two kinds of pistachios were taken with a high-resolution camera. The image processing techniques, segmentation and feature extraction were applied on the obtained images of the pistachio samples. A pistachio dataset that has sixteen attributes was created. An advanced classifier based on k-NN method, which is a simple and successful classifier, and principal component analysis was designed on the obtained dataset. In this study; a multi-level system including feature extraction, dimension reduction and dimension weighting stages has been proposed. Experimental results showed that the proposed approach achieved a classification success of 94.18%. The presented high-performance classification model provides an important need for the separation of pistachio species and increases the economic value of species. In addition, the developed model is important in terms of its application to similar studies. 
Keywords: Classification, Image processing, k nearest neighbor classifier, Pistachio species

https://doi.org/10.3390/electronics11070981 
Within the scope of the study, images of Kirmizi and Siirt pistachio types were obtained through the computer vision system. The pre-trained dataset includes a total of 2148 images, 1232 of Kirmizi type and 916 of Siirt type. Three different convolutional neural network models were used to classify these images. Models were trained by using the transfer learning method, with AlexNet and the pre-trained models VGG16 and VGG19. The dataset is divided as 80% training and 20% test. As a result of the performed classifications, the success rates obtained from the AlexNet, VGG16, and VGG19 models are 94.42%, 98.84%, and 98.14%, respectively. Models’ performances were evaluated through sensitivity, specificity, precision, and F-1 score metrics. In addition, ROC curves and AUC values were used in the performance evaluation. The highest classification success was achieved with the VGG16 model. The obtained results reveal that these methods can be used successfully in the determination of pistachio types. View Full-Text
Keywords: pistachio; genetic varieties; machine learning; deep learning; food recognition
DOI: 10.17632/hp6y7cj9r2.1
title: Relationship between postnatal depression of mental health patients and the psychological health of their offspring

description: Postnatal depression is a major illness affecting the health of a mother and her family. The rate of postnatal depression among mental health clients is postulated to be higher than in the community due to the added brain assault. Children of parents who are mental health clients are more likely to have psychological problems compared to children from other parents in the community. This study investigates the rate of postnatal depression among mental health clients and their offspring's psychological health. A total of 140 mental health clients were assessed using the Edinburgh Postnatal Depression Scale. They subsequently completed the Strength and Difficulties Questionnaire regarding their children. The majority ethnicity was the Kadazan (40.7%). The mean age of mothers was 38.6 (7) years with most having a secondary education (53.6%) and a household income per month of less than RM1000 per month (27.1%). The postnatal depression rate was 47.8 %. Higher EPDS scores were associated with higher total SDQ scores in their offspring. Model 1 was unadjusted, giving an OR of 5.65 (95% CI (3.74, 7.55)), p<0.001. After adjustment for confounders, Model 2 had an OR of 5.51 (95% CI (3.57, 7.46)), p<0.001. More efforts need to be given to the early detection of maternal depression and its prompt treatment in mental health clients because of the relationship with the psychological health of the offspring.
DOI: 10.17632/yyt22prsr3.1
title: Designing Effective Awareness-raising Interventions for Sustainable Plastic Usages and Disposal

description: This is a coded dataset which I used for students behavioral diagnosis and designing effective intervention.
DOI: 10.17632/9v76rdd4gz.2
title: Data for: Contextual Music Rating Prediction

description: Within the .xlsx:
Sheet 1: Users vs Items Rating Table on Musical information 
Sheet 2: Hybrid Matrix Factorisation based Predicted rating 
Sheet 3 and Sheet 4: Generalised Rating Analysis
In .pdf
Implementation Code for Performance evaluation metrics
DOI: 10.17632/jrh8jxwv2t.2
title: Moroccan Aircraft Emergency Landing Sites Semantic Segmentation Dataset

description: The emergency landing sites dataset comprises two primary folders: the raw images folder and the annotation folder. Both the raw images and their annotated counterparts are sized at 256x256 pixels and are stored in PNG format.
DOI: 10.17632/n56pn9fncw.2
title: Malabar Spinach dataset for diseases classification using deep learning approach

description: (1) Malabar Spinach disease is a widespread problem affecting the productivity and quality of agricultural production. It has a detrimental impact on the quality of Malabar Spinach crops. Malabar Spinach is a leafy green vegetable frequently grown for its nutritional value and taste. However, under certain non-biological circumstances, diseases can severely harm the yield and quality of Malabar Spinach, resulting in significant economic losses for farmers. Traditional methods of diagnosing these diseases are often time-consuming, labor-intensive, ineffective, and subjective. (2) In recent years, computer vision approaches have shown great promise in addressing the challenges of disease classification and detection in Malabar Spinach crops. (3) To develop machine vision-based algorithms for detecting Malabar Spinach diseases, a comprehensive dataset has been curated. This dataset comprises images representing various Malabar Spinach diseases, including Anthracnose_leaf_spot, Straw_mite, and Healthy Malabar Spinach. The classification of Malabar Spinach diseases was accomplished with the collaboration of experts from agricultural research institutes. (4) A total of 603 images of Malabar Spinach plants were collected from real fields. Additionally, to expand the dataset, 5868 augmented images were generated from the original ones using techniques such as flipping, shearing, zooming, and rotation. This augmentation is crucial for enhancing the accuracy and robustness of the machine vision algorithms for detecting and classifying Malabar Spinach diseases.
DOI: 10.17632/f6d39287km.2
title: Visual LED Status Dataset for Machine Learning Applications

description: Visual LED Status Dataset is a collection of high-quality images of LEDs captured in different environments and under various lighting conditions. The dataset includes images of normal LEDs, bike and car lights, signal lights, and LEDs of different colors. The images were captured using a high-end resolution camera to ensure high-quality images suitable for machine learning applications. The dataset is divided into five sub-folders containing images of normal LEDs, coloured LEDs, bike lights, car lights and signal lights labelled accordingly. The purpose of this dataset is to develop an image classification model that can accurately determine whether an LED is on or off based on its visual appearance. It is designed to support the development of machine learning models for LED status classification and recognition. The dataset can be used for training, testing, and validation of machine learning models, as well as for research and educational purposes. The proposed dataset provides a valuable resource for industries that use LED technology, particularly in quality control and manufacturing settings. The dataset could be used to develop automated inspection systems for vehicles, electronic devices, or other products that incorporate LEDs. Overall, the LED Status Classification Dataset can be used to improve quality control and efficiency in various industries that use LED technology.
DOI: 10.17632/hm25f9zpry.1
title: Journal Data

description: Background: As the number of coronavirus infection cases increases, interactions become more limited, and life ceases to function normally. The insecurity of family life during the COVID-19 pandemic affects family life quality, which can be seen in various ways, including schooling, jobs, the economy, and social support. Objective: To analyzes family typology based on stress levels, economic stress, and family quality of life, and the influence of religiosity, economic pressure, stress levels, and financial management on family quality of life during the COVID-19 pandemic. Methods: Using cross-sectional study design with 270 respondents, all of whom were pre-selected based on the criterion of working mothers or homemakers with husbands. Results: Economic pressure, stress levels, and financial management are categorized as low and moderately organized religiosity levels, but the quality of life is relatively high. Religiosity harmed stress levels, whereas economic pressure had a strong positive impact. Furthermore, family stress levels and economic pressure directly negatively impact, and financial management positively impacts the family's quality of life. On the other hand, religiosity indirectly affects the quality of life through stress levels. A family typology based on stress levels and quality of life tend to be type I (best) and type IV (equivalent). Type IV (equivalent) with low economic pressure and quality of life dominates a family typology based on economic pressure and quality of life. Conclusions: The results show the importance of improving the family's quality of life through the reduction of economic pressure, enhancing the way of managing finances, and managing stress properly.
DOI: 10.17632/nj4vtk4tt6.1
title: Data for: Dataset of annotated food crops and weed images for robotic computer vision control

description: The dataset is composed of 1176 images (folder "raw images") in which 6 food crops and 8 weed species are identified, altogether 7853 annotations were made in total. Three RGB digital cameras were used for image capturing: Intel RealSense D435, Canon EOS 800D, and Sony W800. The images were taken on food crops and weeds grown in controlled environment and field conditions at different growth stages. Folder "annotations" consists of annotated XML files related to each raw image.
DOI: 10.17632/r47847kcb6.1
title: Oversampling techniques for diabetes classification: A comparative study

description: Supplementary Material: In this study, several tests were conducted to evaluate the occurrence of overfitting when applying different oversampling variants and machine learning algorithms. Therefore, we have compared the results obtained in the test dataset with the results obtained in the training dataset.
Table S[1 - 3] show the F1-Score results obtained for each oversampling variant. The results concerning the application of different machine learning algorithms to training data are presented for each fold (K=10) dataset, as well as the mean of these values.
DOI: 10.17632/8nvgtrkzdm.2
title: SARS-CoV-2 Intra-host Mutational Landscape: A Curated Dataset of iSNVs

description: This dataset, derived from 128,423 high-quality SARS-CoV-2 NGS libraries, represents a comprehensive and precise collection of intra-host single nucleotide variants (iSNVs) processed through a rigorous workflow to ensure accuracy and reliability. Key steps include stringent quality control, variant calling, application of metrics like Strand Bias Likelihood (S) and Alternative Allele Frequency (AAF) for artifact removal. This iSNV dataset, refined to exclude sequencing artifacts, offers a valuable resource for understanding SARS-CoV-2 intra-host mutational dynamics. We also provide a file with the recommended genomic positions to mask for accurate iSNVs calling. The 477 genomic positions are highly recurrent strand bias artifacts.
DOI: 10.17632/xh9pgb3w8c.1
title: Human Behavior dataset (HBD21)

description: HBD21 dataset comprised of video files. This video dataset is divided into four categories i) Assault violence, ii) Gun violence, iii) Sabotage violence, and iv) Normal actions. This dataset consists of 463 videos. Each category has contained more than 100 video files. Each video's length is 9 seconds, and it is observed that this length is sufficient to represent the real action. There are three separate folders attached in HBD21 dataset.rar file. The first folder represents the entire original dataset files, while in the second folder, the train_split and test_split datasets are present. The training and testing video files are in the ratio of 7:3, i.e., 70% training and 30% testing videos of the original dataset. Further, the third folder consists of a pre-processed enhanced version of the training and testing dataset. In this improved version, each video's brightness is increased at a suitable threshold value, which helps in achieving achieve better performance in the training and testing stages. HBD21 dataset is collected from a mobile camera of about 16MP, placed at a tripod with a 5m to 12m distance. The resolution of each video is 640*480. This dataset is captured at various locations in different lighting conditions using multiple objects(bat, badminton, gun, stick, axes, chairs, bottles, and many more).
DOI: 10.17632/hh4ncp9hy6.2
title: Seismic performance evaluation of Unconnected Fiber Reinforced Elastomeric Isolators (U-FREI) as base isolation in a Reinforced Concrete Thin Wall building using Real-Time Hybrid Simulations

description: This data present the seismic performance and behavior of Unconnected Fiber Reinforced Elastomeric Isolators (U-FREI) devices as base isolator in Reinforced Concrete Thin Walls (RCTW) buildings using the Real-Time Hybrid Simulation (RTHS) technique. RTHS is a physical-cybernetic testing methodology that allows a dynamic system to be substructured into numerical and experimental components. In this data, isolated RCTW buildings are evaluated under four seismic events (El Centro, Kobe, Loma Prieta, and Morgan) with a maximum acceleration of 0.70 g.
DOI: 10.17632/46htwnp833.1
title: Mango DMC and spectra Anderson et al. 2020

description: This data set contains NIR absorbance spectra of the wavelength range 309 - 1149 nm of mango mesocarp with corresponding dry matter content values. This was the data set used in Anderson et al. 2020 "Achieving robustness across season, location and cultivar for a NIRS model for intact mango fruit dry matter content"
DOI: 10.17632/gpr2phd9mk.1
title: Digital Innovation Research Dataset (1983-2019)

description: The Digital Innovation research & publication dataset, which was indexed by Scopus from 1983 to 2019. The dataset contains data authors, authors ID Scopus, title, year, source title, volume, issue, article number in Scopus, DOI, link, affiliation, abstract, index keywords, references, Correspondence Address, editors, publisher, conference name, conference date, conference code, ISSN, language, document type, access type, and EID.
DOI: 10.17632/fdn8yy2npn.1
title: A Complex Hierarchy of Avoidance Behaviors in a Single-Cell Eukaryote, Dexter et al. (Day 17)

description: Videos for Dexter et al. (Day 17)
DOI: 10.17632/9nx6ypbr5n.1
title: Geochemical Dataset of laterite soils in Koubou Gold District (Zone A) East Cameroon: Implication for Identification of Gold Pathfinder Elements.

description: The data set is the geochemistry of laterite soil gotten from 55 different pits. The chemistry of the soils shows the presence of gold and other pathfinder elements in ppm. This work aim to use multivariate statistical analyses such as Pearson's correlation, principal component analyses, factor analyses and cluster analyses to identify the relationship between gold and other pathfinder elements. this relationship will help determine if the sources of the gold and the pathfinder elements are of the same origin or not.
DOI: 10.17632/hv4yzz7vk9.1
title: Contact Pressure on Hands during the Use of Wheelchair

description: Pressure data is in kPa, by hand region and for each subject. Values were obtained by the mean of the peak pressure at each impulse (hand contact to propel the wheelchair) in each segment. The data was collected for both hands with Tekscan Grip Versatek Wireless System at 50Hz. The sensors were attached to a thin textile glove (helanca glove). Only male, adults (18 to 29 years old) and able bodied subjects performed the activities. No one reported MSDs symptoms up to 12 months prior the experiment.
DOI: 10.17632/38j8b6s2mx.1
title: 1000 Movie Reviews (Review + Attached rating + Sentiment polarity) for Reputation Generation

description: We have created manually 10 datasets for 10 different movies, each one contains 100 reviews (comment + rating + sentiment polarity) randomly extracted and we made sure that the datasets are representatives based on IMDb users weighted average vote. For each movie, we have created 100 text files named from 1 to 100, each one contains an opinion towards the target movie expressed in natural language (English). Furthermore, we have created a text file named "rating.txt" that contains an array of numbers, each number represents the rating (numeric scale ranging from 1 to 10) attached to a specific opinion towards the target movie. Also we have created a text file named "polarity.txt" that contains an array of 0 and 1. 0 stands for a negative review and 1 stands for positive review. This is what the rating file looks like: rating = [ 9, 10, 3, ...................] Interpretation: The user that posted the review stored in file "1.txt" has given a 9/10 as rating towards the target movie. The user that posted the review stored in file "2.txt" has given a 10/10 as rating towards the target movie. The user that posted the review stored in file "3.txt" has given a 3/10 as rating towards the target movie. This is what the polarity file looks like: polarity = [1, 1, 0, ...................] Interpretation: The review stored in file "1.txt" holds positive opinion towards the target movie. The review stored in file "2.txt" holds positive opinion towards the target movie. The review stored in file "3.txt" holds negative opinion towards the target movie. We mention that we have annotated manually the sentiment polarity of each review.
DOI: 10.17632/jdvsyzypzk.1
title: Data on the demographic forecast of the Kazakhstan population

description: The data was obtained as a result of a forecast of the population of Kazakhstan for the future. The forecast data includes the total population of Kazakhstan, gender distribution, the age structure of the population, fertility and mortality (including infant mortality) for the period from 2022 to 2100.
DOI: 10.17632/7j7n2r2zcm.2
title: EEG dataset of children with learning disabilities (LD)

description: When using this resource, kindly cite the original publication:

Sase, T., & Othman, M. (2022). Prediction of ADHD from a Small Dataset Using an Adaptive EEG Theta/Beta Ratio and PCA Feature Extraction. In International Conference on Soft Computing and Data Mining (pp. 101-110). Springer, Cham.


Participants
Participants are 4 children with learning disabilities (LD) (boys and girls, aged 5-8 years).  The LD children were diagnosed by health professionals, and none of -them were under medications.  All of the children are right-handed.  

Hardware and dataset
EEG recordings were performed using 19-channels Brainmarker EEG machine with the sampling rate of 250Hz and Pz as the reference electrode. 

The presented dataset is for the following tasks: 1) eyes closed (1 minute), and 2) watching facial expressions for the emotion fear from the Radboud Faces Database (RafD).  The emotionally related facial expressions may help the children to change his/her feelings.  The experimental protocol was approved by the IIUM Research Ethics Committee No 419 (IREC 419).

The file names have the following format: {participant_id}_{task}.csv
DOI: 10.17632/v8s9nz948s.1
title: Human ileum, Visium

description: Visium experiments on a biopsy from the ileum of a human donor. Four adjacent 10 µm sections. Processed sequencing data from 10X Genomics Space Ranger version 1.0.0. The tissue was collected from a patient undergoing colorectal surgery after obtaining informed consent. The study protocol was approved by the Medical Ethics Committee of the University Hospitals Leuven (reference approval number: S62935).