Artificial Intelligence
The dataset used in this study is a comprehensive, publicly available dataset designed for research purposes, encompassing various features related to the public sector. It includes data on all genders (male and female) from diverse regions, age groups, and educational levels. The dataset was sourced from CAPMAS reports (2018-2023), which provide quarterly updates on the labor force, including details on unemployment assessments categorized by geographical distribution.
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Dig21000 is a comprehensive dataset consisting of 21,000 images of digit-based rotary meters photographed in uncontrolled environments.
It integrates images from open datasets on the Roboflow platform and those independently collected.
After undergoing cleaning, the images are randomly divided into training and testing sets at a ratio of 6:1.
It contains 10 digit categories. The images are affected by multiple factors and can be used for research on digital dial recognition. It is publicly available and citation is required when using it.
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To further evaluate the practical performance of HPDM, we apply it to detect defects in actual industrial circuit boards. Various defects, such as board, lifting, and ffipping defects, occur on the circuit board because of external forces imposed during the placement and soldering processes .A real industrial circuit board defect detection dataset is collected and presented. This dataset includes five different categories of components with various real multiscale defects.
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To ensure reproducible experiments and prevent overburdening the server, we construct an SQL-based database dubbed RiPAMI (Reviews in Pattern Analysis and Machine Intelligence, pronounced as \textipa{/ri:p\ae mi/}). This database stores information related to the paper such as title, abstract, date of publication, venue, citation counts, and reference details, etc. From initial keyword selection to the final SQL-based RiPAMI snapshot, three key steps are implemented to ensure the data in RiPAMI is clean, accurate, and reliable.
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Large vision-language models (LVLMs) have demonstrated remarkable capabilities in multimodal understanding and generation tasks. However, these models occasionally generate hallucinatory texts, resulting in descriptions that seem reasonable but do not correspond to the image. This phenomenon can lead to wrong driving decisions of the autonomous driving system.
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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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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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22 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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113 Views