Artificial Intelligence
This dataset is used for the automated assessment of open-ended exam questions in the online course Introduction to Software Engineering at Constantine the Philosopher University in Nitra. The dataset originates from the Moodle Learning Management System (LMS) and includes responses to eight open-ended questions centered on fundamental terminology related to the Scrum framework, a key methodology in agile software development.
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The constructed dataset comprises two representative scene types. The open-pit coal mining scenes (OCMS) include 201 original samples, which yielded 3247 standardized 224×224-pixel samples after target purification. The dataset is split 8:1:1 into training (2597 samples), validation (349 samples), and testing (301 samples). The composite coal-related scenes (CCS) include 272 original samples, which yielded 1531 standardized samples, also divided 8:1:1 into training (1223), validation (154), and testing (154).
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25 Views
With the continuous improvement in the computational capabilities of edge devices such as intelligent sensors in the Industrial Internet of Things, these sensors are no longer limited to mere data collection but are increasingly capable of performing complex computational tasks. This advancement provides both the motivation and the foundation for adopting distributed learning approaches. This study focuses on an industrial assembly line scenario where multiple sensors, distributed across various locations, sequentially collect real-time data characterized by distinct feature spaces.
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18 Views
A fact-checking dataset focused exclusively on quantitative claims. It includes 33,422 fact-checked claims featuring comparative, statistical, interval, and temporal entities. Each claim is accompanied by detailed metadata and supporting evidence, providing a robust foundation for automated verification. This dataset contains claims and their corresponding fact-checking details. It is provided in JSON format, with each entry containing information about a claim, its processed version, fact-checking results, and relevant metadata.
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23 Views
This dataset extends the standard Myers-Briggs Type Indicator (MBTI) dataset, widely available on Kaggle, by incorporating advanced data augmentation techniques leveraging GPT-based Transformers. The augmentation addresses inherent class imbalance and data sparsity issues in the original dataset, significantly enriching the volume and diversity of textual samples while maintaining linguistic and contextual fidelity to the MBTI personality types.
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78 Views
This data examines the evolution of telehealth technologies across three distinct phases: Pre-2010, 2010–2019, and 2020–Present. The timeline highlights the progression from basic video consultations and electronic health records (EHR) to more advanced remote patient monitoring, mobile health applications, and cloud-based platforms. Recent advancements in AI-powered diagnostics, natural language processing (NLP) for clinical documentation, predictive analytics, and virtual health assistants represent a transformative shift in healthcare delivery.
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54 Views
With the continuous advancement of technology, small and portable physiological sensors that can be worn on the body are quietly integrating into our daily lives, and are expected to greatly enhance our quality of life. In order to further enrich and expand the emotional physiological signals captured by portable wearable devices, we utilized the 14-channel portable EEG acquisition device Emotiv EPOC X, and with emotional video clips as the stimulus source, we collected two sets of emotional EEG signals from two groups of 10 participants each, named EmoX1 and EmoX2.
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217 Views
This dataset was developed using the MOBATSim simulator in MATLAB 2020b, designed to mimic real-world autonomous vehicle (AV) environments. It focuses on providing high-quality data for research in anomaly detection and cybersecurity, particularly addressing False Data Injection Attacks (FDIA). The dataset includes comprehensive sensor information, such as speed, rotational movements, positional coordinates, and labelled attack data, enabling supervised learning.
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478 Views
The existing public datasets often suffer from small data volumes, leading to insufficient training processes that result in severe overfitting and poor generalization performance. To address this issue, a radar dataset named RadSet is constructed. During the data acquisition phase, frequency modulated continuous wave (FMCW) radar system IWR1843 Boost manufactured by Texas Instruments (TI) was used.
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164 Views
MaskTIF is collected from different scenarios from ETIF and contains 3,000 thermal infrared face images. The collection time was during the severe COVID-19 epidemic period, and contains a large number of mask-wearing samples.
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27 Views