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*.csv; *.json;

The scarcity of multimodal datasets in remote sensing, particularly those combining high-resolution imagery with descriptive textual annotations, limits advancements in context-aware analysis. To address this, we introduce a novel dataset comprising 12,473 aerial and satellite images sourced from established benchmarks (RSSCN7, DLRSD, iSAID, LoveDA, and WHU), enriched with automatically generated pseudo-captions and semantic tags.

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Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder affecting children and adolescents, characterized by inattention, hyperactivity, and impulsivity. Current diagnostic methods primarily rely on subjective clinical evaluations, which are prone to bias. Advances in neurophysiological assessment, particularly through electroencephalography (EEG), eye tracking, and electrodermal activity (EDA), offer promising avenues for objective diagnosis and monitoring of ADHD.

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The dataset consists of two primary files: dataset.json and analysis_script.ipynb. The dataset.json file contains structured records of AI-assisted psychological therapy sessions, including emotion recognition, NLP techniques, cognitive behavioral therapy (CBT) patterns, hypnotherapy data, user feedback, and therapy outcomes. The analysis_script.ipynb Jupyter Notebook provides data preprocessing, visualization, and statistical analysis of therapy session outcomes.

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This dataset includes ALVR statistics (.json) and Wireshark packet traces (.csv) for a wide range of single-user and multi-user PCVR configurations. Our configurations are based on ALVR and SteamVR. For each user, we stream a video game from a wired server (desktop or laptop) to a wireless head-mounted display (Meta Quest 2 or 3) over Wi-Fi. In each case, the data was captured on the server.

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The application of large language models (LLMs) in urban planning has gained momentum, with prior research demonstrating their value in participatory planning, process streamlining, and event forecasting. This study focuses on further enhancing urban planning through the integration of more comprehensive datasets. We introduce a newly developed instruction dataset that amalgamates crucial information from several prominent urban datasets, including highD, NGSIM, the Road Networks dataset, TLC Trip data, and the Urban Flow Prediction Survey dataset.

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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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Partial dataset of CHVM-1K dataset for illustration purposes.

    {

        "question": "What stages can be divided into in the development history of ancient Chinese bronzes? Why?",

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This paper introduces the Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) Electrical Simulation Dataset, MESD, an extensive collection of I-V and C-V characteristics data simulated across different foundries' Berkeley Short-channel IGFET Models (BSIMs). The MESD dataset covers a range of bias voltages, temperatures, and MOSFET physical dimensions across several technology nodes from 3 to 350 nm.

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