Artificial Intelligence

A dataset of simulated resistive drift series for an illustrative stochastic memristor.

Dataset Description

The memristor has an equilibrium resistance of approximately 500kΩ.

5000 series are generated with starting resistances sampled uniformly from the range [100Ω, 750kΩ].

Each series consists of 1001 datapoints, with the first (zeroth) point corresponding to the initial resistance, and subsequent points sampled at subsequent timesteps.

Dataset Creation

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IITP-VDLand is a comprehensive dataset of Decentraland parcels sourced from diverse platforms such as Decentraland, OpenSea, Etherscan, Google BigQuery, and various Social Media Platforms. Unlike existing datasets which have limited attributes and records, IITP-VDLand offers a rich array of attributes, encompassing parcel characteristics, trading history, past activities, transactions, and social media interactions. Alongside, we introduce a key attribute in the dataset, namely Rarity score, which measures the uniqueness of each parcel within the virtual world.

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177 Views

A multimodal dataset is presented for the cognitive fatigue assessment of physiological minimally invasive sensory data of Electrocardiography (ECG) and Electrodermal Activity (EDA) and self-reporting scores of cognitive fatigue during HRI. Data were collected from 16 non-STEM participants, up to three visits each, during which the subjects interacted with a robot to prepare a meal and get ready for work. For some of the visits, a well-established cognitive test was used to induce cognitive fatigue.

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39 Views

Data were generated from ChatGPT’s responses to 80 counseling questions that college students asked during a school counseling setting. All the responses generated during these simulated counseling sessions were then analyzed using three primary metrics—warmth, empathy, and acceptance—following APA guidelines. The analysis adopted several natural language processing methodologies for emotion detection and empathy measurement to quantify ChatGPT’s high efficacy in presenting the appropriate emotions and reactions for counseling. 

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23 Views

The 5G cellular technology has introduced advanced radio communication protocols and new frequency bands and enabled faster data exchange. These improvements increase network capacity and establish a foundation for high-bandwidth, low-latency services, helping the development of applications like the Internet of Things (IoT). However, information security poses significant challenges, particularly concerning attacks such as Fake Base Stations (FBS) and Stream Control Transmission Protocol (SCTP) Session Hijacking.

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117 Views

General video captioning datasets are not suitable for challenges of fast moving camera, highly overlapping vocabulary and caption for camera-carrier in driving scenes. To address this issue, we develop the Traffic Scenarios Event Caption (TSEC) Dataset to describe the key events of ego vehicle, road environment and other traffic participants. To acquire diverse types of traffic scenarios, we select the videos that we take with our on-board camera and other public dataset videos. We also download from BiliBili and Youtube to get the traffic accident videos.

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the dataset is related to an app-based framework for multivariate next-day price prediction using
GRU attention networks with rolling averages.

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Decentralized Collaborative Simultaneous Localization and Mapping (C-SLAM) is essential to enable multi-robot missions in unknown environments without relying on pre-existing localization and communication infrastructure. This technology is anticipated to play a key role in the exploration of the Moon, Mars, and other planets. In this work, we introduce a novel dataset collected during C-SLAM experiments involving three robots operating on a Mars analogue terrain.

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195 Views

The benchmarking dataset, GenAI on the Edge, contains performance metrics from evaluating Large Language Models (LLMs) on edge devices, utilizing a distributed testbed of Raspberry Pi devices orchestrated by Kubernetes (K3s). It includes performance data collected from multiple runs of prompt-based evaluations with various LLMs, leveraging Prometheus and the Llama.cpp framework. The dataset captures key metrics such as resource utilization, token generation rates/throughput, and detailed inference timing for stages such as Sample, Prefill, and Decode.

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This study introduces a multimodal dataset collected to investigate the psychophysiological relationship between perceived fear and muscle activity in climbers. The dataset includes physiological, motion, and subjective data from 19 climbers during \textit{lead} and \textit{top rope climbing} ascent styles, which differ in perceived risk due to varying fall distances. Physiological data were recorded using EMG, ECG, and IMU sensors. Additionally, subjective fear ratings were collected at distinct phases of the climb.

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