cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.17632/wrg5fmt35d.2
title: A nationwide dataset of advisor-advisee relationships

description: This dataset contains pairs of advisor-advisee relationships about the academic genealogy in Brazil. We generated it through the application of an updated version of the algorithm described in [1], based on 7,300,000 academic curricula.

The dataset is represented by a directed graph where each vertex is an Academic and each edge is a relationship between two Academics (a master's, doctorate, or post-doctorate). The edge's source is the advisor (professor), and the edges' target is the advisee (student).  The graph contains 1,463,190 vertices and 1.633.248 edges; these are available in two comma-separated values files.

A vertex is composed of the vertex's code, the researcher's abbreviated full name, the major area of knowledge, area of knowledge, and values of seven topological metrics (descendants, fecundity, fertility, cousins, generations, relations, and genealogical index) - see [2,3] for more details.

An edge contains the source and target vertices codes, the academic degree  (i.e., master, doctorate, or post-doctorate), the start and conclusion years of this degree, the course and institution where the degree was received, the thesis, the major area of knowledge and area of knowledge.

References:

[1]. Damaceno, R.J.P., Rossi, L., Mugnaini, R., Mena-Chalco, J.P. The Brazilian academic genealogy: evidence of advisor-advisee relationships through quantitative analysis. Scientometrics (2019) 119, 303-333. https://doi.org/10.1007/s11192-019-03023-0.

[2] Rossi, L., Damaceno, R.J.P., Freire, I.L., Bechara, E.J.H., Mena-Chalco, J.P. Topological metrics in academic genealogy graphs. Journal of Informetrics (2018). 12, 1042-1058. https://doi.org/10.1016/j.joi.2018.08.004.

[3] Rossi, L., Freire, I.L., Mena-Chalco, J.P. Genealogical index: A metric to analyze advisor-advisee relationship. Journal of Informetrics (2017) 11, 564-582. https://doi.org/10.1016/j.joi.2017.04.001.
DOI: 10.17632/m5nwp6cffn.1
title: DIGITAL BASE MARKETING STRATEGIES: REVIEW INFLUENCER AND THEIR IMPACT BRAND AWARENESS

description: This research explores the impact of influencer marketing on brand awareness in the digital era. This study integrates findings from various articles discussing the influence of social media influencers on brand awareness, brand image, and trust in sponsored content. The research results show that social media influencers have a significant influence in increasing brand awareness and image, as well as building consumer trust in the content they promote. Influencers who have high credibility are able to form stronger relationships with their audience, which in turn increases consumer purchase intentions. Brand awareness acts as an important mediator in influencing purchase intentions, which shows that an effective influencer marketing strategy can increase consumers' desire to purchase promoted products. These findings emphasize the importance of selecting the right influencers and effective communication strategies to maximize marketing impact in today's social media era.
DOI: 10.17632/s6gyxb2cg9.1
title: SeasVeg: An Image Dataset of Bangladeshi Seasonal Vegetables

description: This dataset introduces a newly developed dataset named "SeasVeg," which includes Ten different types of seasonal vegetables from various regions in Pabna and Dhaka, Bangladesh. The ten different categories are Carica Papaya, Momordica dioica, Abelmoschus esculentus, Lablab purpureus, Trichosanthes cucumerina, Trichosanthes dioica, Solanum Iycopersicum, Brassica oleracea, Momordica charantia, Raphanus sativus. The dataset contains a total of 1,500 original images, along with an additional 3000 augmented images. We meticulously captured each original image under natural lighting conditions with an appropriate background. This comprehensive dataset holds immense potential for researchers in utilizing various ML and DL methods to advance the healthcare sector significantly. It is a valuable resource for future investigations, laying the foundation for crucial developments in these domains.
DOI: 10.17632/ptt8zxzx92.1
title: Experiment of chocolate consumption

description: This study investigates the unit size effect, a behaviorally-oriented nudge, on chocolate consumption. In particular, it examines how different unit sizes and the presence or absence of packaging influence the quantity of chocolate consumed and the perceived energy intake in grams and calories. The methodology involved an experiment with four focus groups, differentiated by health-consciousness, who were provided with chocolate in varying unit sizes and packaging conditions.
DOI: 10.17632/xpb4nmdnfy.1
title: Parental Influence, Socioeconomic factors and School Environment and Career Choice amongst Secondary School Students in Kabale District, Uganda

description: This study aims to see if there was a relationship between parental influence, socioeconomic factors, school environment and career choice among senior three and senior five students among 10 secondary schools in the Kabale district. For the year 2017, the study’s target population was all 1005 students from senior three and senior five, with a sample of 300 students. A cross-sectional survey research design was followed and a multistage sampling technique was used for selecting schools and students. The instrument for data collection was the Career choice questionnaire. Data were analysed using Statistical Package for social sciences (IBM SPSS) software, to produce frequencies, percentages and correlation coefficients. The findings indicate that students considered their family's socioeconomic status to be low based on their parent’s monthly income. The study findings further indicate that there is a significant positive relationship between parental influence, socioeconomic factors, school environment and career choice (r = .162, .228, .254, ρ < .01). Teachers and parents should always consider the influence of parents, socioeconomic factors and school environment when guiding their students on issues related to careers, this study recommend. This will allow students to make the best career decisions possible based on their educational achievements and career goals.
DOI: 10.17632/s3bw2vksx6.1
title: Goldene: An anisotropic metallic monolayer with remarkable stability and rigidity and low lattice thermal conductivity

description: The "p.mtp" is the trained MTP, and "AIMD-Train.cfg" and "AIMD-Train.xyz" are the complete dataset in the "cfg" and "xyz" formats, respectively. 
"POSCAR" and "LAMMPS-input.xyz" are the stress-free monolayer in the VASP and LAMMPS input format, respectively.
DOI: 10.17632/xw7r4tt54g.1
title: Encrypted Traffic Feature Dataset for Machine Learning and Deep Learning based Encrypted Traffic Analysis

description: This traffic dataset contains a balance size of encrypted malicious and legitimate traffic for encrypted malicious traffic detection and analysis. The dataset is a secondary csv feature data that is composed of six public traffic datasets. 

Our dataset is curated based on two criteria: The first criterion is to combine widely considered public datasets which contain enough encrypted malicious or encrypted legitimate traffic in existing works, such as Malware Capture Facility Project datasets. The second criterion is to ensure the final dataset balance of encrypted malicious and legitimate network traffic. 

Based on the criteria, 6 public datasets are selected. After data pre-processing, details of each selected public dataset and the size of different encrypted traffic are shown in the “Dataset Statistic Analysis Document”. The document summarized the malicious and legitimate traffic size we selected from each selected public dataset, the traffic size of each malicious traffic type, and the total traffic size of the composed dataset. From the table, we are able to observe that encrypted malicious and legitimate traffic equally contributes to approximately 50% of the final composed dataset. 
 
The datasets now made available were prepared to aim at encrypted malicious traffic detection. Since the dataset is used for machine learning or deep learning model training, a sample of train and test sets are also provided. The train and test datasets are separated based on 1:4. Such datasets can be used for machine learning or deep learning model training and testing based on selected features or after processing further data pre-processing.
DOI: 10.17632/kdzsg62whg.1
title: Skin of Colour Delphi Consensus Supplement

description: Supplementary materials relating to the manuscript "Optimizing the management of psoriasis in patients with Skin of Colour: A Canadian Delphi Consensus."
DOI: 10.17632/wz93p38svm.1
title: Inclusive Governance

description: “inclusive governance” was first used in 2000 and has continued to increase significantly since 2013. This data shows the authors of inclusive governance emphasized more on principles: participation, accessibility, power, structure, empowerment, accountability, social justice, collaboration, capacity, and decision-making..
DOI: 10.17632/2xf5v5pwkr.2
title: SAR despeckling filters dataset

description: The dataset consists of images downloaded from https://search.asf.alaska.edu/#/, without taking georeferencing into account. Specifically, 10 SAR images were taken from Sentinel-1 in Level 1 Detected High-Res Dual-Pol (GRD-HD), polarization VV. With this set of images provided by ASF DATA SEARCH, a rescaling to 8-bit integer images was performed, all of them were registered (aligned) with respect to one reference image, and then a multitemporal fusion was performed by averaging all of them. The averaging process integrates all ten images, pixel by pixel in a single one, resulting in one single image. Finally, one of the 10 downloaded images (noisy) is taken and split into 1600 data with dimensions of 512x512 pixels, and then this data set is separated into 1500 images (training) and 100 (validation). This process is also performed for the image resulting from the fusion of 10 images (noiseless), generating another 1600 images.

The root folder includes the "Main folder" which contains four subfolders, namely:
Noisy: 1500 SAR noisy images for training
Noisy_val: 100 SAR noisy images for validation
GTruth: 1500 noiseless images for training
GTruth_val: 100 noiseless images for validation

The images are in TIFF (Tagged Image File Format) with values from 0 to 255 uint8.
DOI: 10.17632/xkt857dsxk.1
title: A dataset of scoliosis, spondylolisthesis, and normal vertebrae X-ray images 

description: The vertebrae X-ray images were collected locally at King Abdullah University Hospital, Jordan University of Science and Technology, Irbid, Jordan. The dataset included 338 subjects (240 females, 98 males) . The number of subjects with normal X-ray images was 71 (40 females, 31 males) . The number of subjects diagnosed with spondylolisthesis was 79 (49 females, 30 males) . The number of subjects diagnosed with scoliosis was 188 (151 females, 37 males). The images are available in their original size as well as sizes suitable for various deep learning models (e.g., [224 224 3])
DOI: 10.17632/fnpsny8km9
title: Expression of STUB1 in testes and sertoli cells

description: Supplement figure 1. Expression of STUB1 in testes and sertoli cells. A, The HPA database shows the mRNA expression levels of STUB1 in various tissues. B, The HPA database shows the mRNA expression levels of STUB1 in various single cell types.
DOI: 10.17632/2h9cxkzj8j.1
title: Dataset of an airline-driven flight rescheduling problem

description: This data was derived from Luo and Yu (1997), Bard and Mohan (2008), and Brunner (2014). The data is from American Airlines’ daily flight schedule at the Dallas/Fort Worth Airport. There are 71 flights in GDP and the GDP spanned three hours in duration. The planning period of the airline-driven flight rescheduling problem is a half day for one specific season. The data was considered as the base scenario on which a GDP had been issued, and there is no change of the GDP. Including the base scenario, some hypothetical scenarios on subsequent GDPs were assumed and then used to attain the solution. The hypothetical scenarios correspond to new situations in which there are changes in GDP due to weather conditions or external restrictions. The minimum turnaround times of plane and crew were fixed with 30 minutes and 20 minutes, respectively. The maximum allowed time for delays was set to 500 minutes. The misconnection cost of crew members and the cancellation cost of a flight were 50 and 500, respectively. For the incremental delay cost function, each interval, in which different unit costs occurred, was fixed by 60 minutes. There were three intervals. The cost per unit delay time is set to 2, 3, and 4, and associated with each interval, respectively. Correspondingly, the constant value of the incremental delay cost function was set to 0, -60, and -180, and associated with each interval, respectively. The initial flight schedule and the schedule revised by a GDP are presented in "base scenario.csv". The current GDP has been issued at 0. The initial flight schedule defines the arrival and departure times of flights. The connections of crews between flights are also described in the initial flight schedule. In the revised schedule, the arrival times represent the scheduled arrival times of slots. For possible scenarios, ten scenarios were randomly generated. The scheduled arrival times revised by the subsequent GDP in each scenario are presented in scenario##.csv". All the constrained flow rates are 1.81, 1.88, 1.58, 1.64, 1.59, 1.46, 1.49, 1.46, 1.4, and 1.45, respectively. All the next time points are 103, 103, 123, 112, 151, 168, 145, 139, 76, and 103, respectively. In each scenario, the starting times of slots was calculated by adding the inverse of the constrained flow rate to the initial arrival times after the time point, cumulatively. The probability of the base scenario, θ, was set to 0.2, and the probability of the other scenarios was set to 0.08.
DOI: 10.17632/r3nzvfrn8z.1
title: Data for: Simple method for determining CO2 loading of partially carbonated aqueous ammonia solutions using pH and density measurements

description: Excel file to compute CO2 loading of partially carbonated ammonia solutions using models presented in the paper. For convenience, the file is password protected, to avoid accidental changes. If necessary, the file can be unprotected using password: ichpw.
DOI: 10.17632/ydj9j88dpr.2
title: Code and Data for On Index Investing

description: This code and data recreates the tables in "On Index Investing" by Jeffrey L. Coles, Davidson Heath, and Matthew C. Ringgenberg. Please see the "Read Me" file before using it.
DOI: 10.17632/ftrbvh82f6.1
title: Data for: Evaluation of a sport-specific field test to determine maximal lactate accumulation rate and sprint performance parameters in running

description: Raw date of all participants of the study to examine the raliability of maximal lactate accumulation rate and sprint performance parameters in running.
DOI: 10.17632/frrv2yd9rg.1
title: Data for: Spectra Data Classification with Kernel Extreme Learning

description: Datasets for Spectra Data Classification: "FTIR_Spectra_instant_coffee.csv": contains a collection of 56 mid infrared diffuse reflectance (MIR-DRIFT) spectra of lyophilized coffee produced from two species: arabica (29 samples) and canephora var. robusta (27 samples). The data are described in full in the journal paper "Near- and Mid-Infrared Spectroscopies in Food Authentication: Coffee Varietal Identification" (Downey G. et al, J. Agric. Food Chem. 45 (11) 4357-4361 (1997)). "MIRFreshMeats.csv": Duplicate acquisitions from 60 independent samples. Raw data matrix size [448 x 120]. Obtained using Fourier transform infrared (FTIR) spectroscopy with attenuated total reflectance (ATR) sampling. As described in "Mid-infrared spectroscopy and authenticity problems in selected meats: a feasibility study" Al-Jowder O, Kemsley E K, Wilson R. H.(1997) Food Chemistry 59 195-20. "MIR_Fruit_Purees.csv": contains a collection of 983 Mid-infrared spectra collected from different authenticated fruit purees in one of two classes: "Strawberry" (purees prepared from fresh whole fruits by the researchers) and "NON-Strawberry" (diverse collection of other purees, including: strawberry adulterated with other fruits and sugar solutions; raspberry; apple; blackcurrant; blackberry; plum; cherry; apricot; grape juice and mixtures of these.Spectra were acquired from each puree using attenuated total reflectance (ATR) sampling. The acquisition order was randomized with respect to sample type. The data are described in more detail in the journal paper "Use of Fourier transform infrared spectroscopy and partial least squares regression for the detection of adulteration of strawberry purees" Holland JK, Kemsley EK, Wilson RH. (1998). Journal of the Science of Food and Agriculture, 76, 263-269 "FTIR_Spectra_olive_oils.csv": contains a collection of 120 Mid-infrared spectra collected from 60 different authenticated extra virgin olive oils, supplied to the Institute of Food Research, UK, by the International Olive Oil Council.Spectra were acquired from each oil using attenuated total reflectance (ATR) sampling. The acquisition order was randomized with respect to the country of origin code. Once all the samples had been examined once, a second acquisition session commenced, to produce a second spectrum from each sample. Again the acquisition order was randomized with respect to country of origin. thus, duplicate spectra were collected from all samples. The data are described in full in the journal paper "FTIR spectroscopy and multivariate analysis can distinguish the geographic origin of extra virgin olive oils" (Tapp H.S. et al, J. Agric. Food Chem. 51 (21) 6110-5 (2003)). These data are free to analyse and redistribute for academic purpose; if you do so, please acknowledge the original sources (webpage and/or citation above).
DOI: 10.17632/hppkn5kbg8.1
title: Reddit Cross-Topic Authorship Verification Corpus

description: The "Reddit Cross-Topic Authorship Verification Corpus" consists of comments written between 2010 to 2016 from 1,000 reddit users. Each problem includes 1 unknown and 4 known documents (~ 7 KByte per document), where each document represents an aggregation of reviews coined from the same so-called subreddit. More precisely, all documents within a problem are disjunct regarding the subreddits in order to enable a cross-topic corpus. All subreddits cover exactly 1,388 different topics such as books, news, gaming, music, movies, etc. The corpus follows excatly the same format as the well-known PAN Authorship Identification corpora (http://pan.webis.de/).
DOI: 10.17632/jpp8bsjgrm.1
title: Multiclass Diabetes Dataset

description: This refined dataset is originally based on the "Diabetes Dataset" uploaded by Ahlam Rashid in Mendeley Data. The link to the original dataset is: https://data.mendeley.com/datasets/wj9rwkp9c2/1. The original dataset contains a total of 1000 subjects divided into three classes: diabetic, non-diabetic, and predict-diabetic.

Among the 1000 subjects, 844 are diabetic, 103 are non-diabetic, and 53 are predict-diabetic, resulting in an extreme class imbalance. We found a total of 174 duplicate subjects in the original dataset, which we subsequently removed. After removing the duplicate subjects, there were 690 diabetic, 96 non-diabetic, and 40 predict-diabetic subjects remaining.

From the 826 unique subjects, we selected 128 diabetic, 96 non-diabetic, and 40 predict-diabetic subjects, resulting in a new dataset with a moderate class imbalance.
DOI: 10.17632/k4rb7xgry9.1
title: Data on mimetic accuracy

description: Myrmecomorphy is the most frequent type of Batesian mimicry. Myrmecomorphic species differ in the accuracy with which they resemble ants, however, the hypothesis of the co-evolution of mimetic traits has been rarely tested. Here, we measured dozens of traits of colour, shape, size, and behaviour, and quantified objectively the resemblance between dozens of arthropod mimics and ants. In all traits, the mimics were more similar to ants than to closely related non-myrmecomorphic species. We found that mimics resemble ants mainly in colour and behaviour, and less in size and body shape. We found that the mimetic accuracy in four trait categories show divergent co-evolutionary patterns. Mimetic accuracy in colour was positively correlated to shape and size in insects but negatively in spiders, presumably reflecting developmental constraints. Accuracy in shape was negatively related to movement in both insects and spiders supporting the motion-limited discrimination hypothesis.
DOI: 10.17632/p63m3jrx9n.1
title: HVAC system - Attack-detection

description: The dataset can be used to study the cybersecurity aspect of the HVAC system by evaluating the different attack detection and mitigation strategies. The dataset was collected from a simulation model of a 3-floor, 12-zone HVAC system for cooling using the Transient System Simulation Tool (TRNSYS), which is a graphical software environment for simulating a dynamical system. It consists of three logs: Dataset log 1 contains normal operational data collected for four months, Dataset log 2 represents normal operational data collected for 20 days. Dataset log 3 consists of the normal and attack data of 16 different attacks. It consists of 65 features: the hour of the year, the hour of the day, the temperature sensor measurements, the control signals, the control system's setpoints, the zones' thermal comfort indices, and the total estimated power usage of the HVAC system. Four files are provided as supplementary materials for training machine learning-based detection models using the Isolation Forest algorithm [1]. The details of the supplementary codes are as follows: File "HVAC - IF Training.ipynb" is for developing an attack detection model using Isolation Forest on the raw data, File "HVAC - PCA-IF Training.ipynb" is for developing an attack detection model using Isolation Forest on the data features extracted using Principal Component Analysis (PCA), File "HVAC - 1D CNN Training.ipynb" is for developing a feature extraction model using 1D Convolutional Neural Network (1D CNN), and File "HVAC - 1D CNN-IF Training.ipynb" is for developing an attack detection model using Isolation Forest on the data features extracted using the 1D CNN model. For more information about the dataset refer to the following publications: [1] Elnour, M., Meskin, N., Khan, K., & Jain, R. (2021). Application of data-driven attack detection framework for secure operation in smart buildings. Sustainable Cities and Society, 69, 102816. https://doi.org/10.1016/j.scs.2021.102816 [2] Elnour, M., Meskin, N., Khan, K., & Jain, R. (2021). HVAC System Attack Detection Dataset. Data in Brief, 107166. https://doi.org/10.1016/j.dib.2021.107166 * This dataset was supported by the Qatar National Research Fund (a member of the Qatar Foundation) under NPRP Grants number 10-0206-170360 and the Open Access funding was provided by the Qatar National Library