*.csv; *.json;
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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191 Views
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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1166 Views
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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112 Views
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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105 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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29 Views
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?",
"answer": "The development history of ancient Chinese bronzes can be divided into several stages: Xia (2100-1600 BCE), Shang (1600-1046 BCE), Early Western Zhou (1046-771 BCE), Middle Western Zhou (771-720 BCE), Late Western Zhou (720-256 BCE), and Eastern Zhou (256-256 BCE). These stages are marked by technological advancements, stylistic evolution, and cultural significance.",
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16 Views
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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412 Views
We organized and collected two years' worth of complete fault work orders from a wind farm, and structured these work orders into a fault diagnosis event knowledge graph using the proposed algorithm. This graph includes fault modes, fault impacts, fault symptoms, inspection schemes, root cause identification, and maintenance strategies, covering all potential fault information and handling methods for wind turbines. This dataset records the head entity-relation-tail entity information in the form of triples using JSON format.
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1156 Views
This dataset contains information about code smell, which is a very important issue in software engineering.
It is built by collecting the method having code smell from GitHub using the SonarCloud tool.
There are 5 code smells and 1 normal class with 500 examples each.
the metadata: method (function),smellkey, smellid
Smell Type
ID
Description
Reference
java:S100
0
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759 Views
This study investigates the application of advanced machine learning models, specifically Long Short-Term Memory (LSTM) networks and Gradient Booster models, for accurate energy consumption estimation within a Kubernetes cluster environment. It aims to enhance sustainable computing practices by providing precise predictions of energy usage across various computing nodes. Through meticulous analysis of model performance on both master and worker nodes, the research reveals the strengths and potential applications of these models in promoting energy efficiency.
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513 Views