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This dataset contains a comprehensive V2X misbehavior dataset simulated using VASP, an open-source framework. VASP allows the simulation of diverse types of V2X attacks and works as a sub-module for Veins, a well-established open-source framework for running vehicular network simulations. Veins runs on an event-based network simulator OMNeT ++, and road traffic simulator SUMO. Data are collected from the Boston traffic network, which is a good candidate to represent real-world traffic mobility. We run VASP simulation for 3,000 simulated seconds to collect benign traces without any attacks.
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223 Views
This is a test case for a talent intelligence evaluation benchmark dataset with rich attributes (Attributes: 11, 909, Samples: 244, 610), containing information on honors, masterpieces, projects, rankings, and other attributes. Please note that we are providing this for scientific research use only; to use the full dataset, please contact liuying.void@gmail.com.
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38 Views
The Deenz Psychopathy Spectrum Scale (DPSS-24) is a newly developed psychometric instrument aimed at assessing psychopathy traits across diverse adult populations. This study presents preliminary data collected from two distinct samples—a group of 21 participants from an initial testing phase and a German sample of 31 participants. Each participant completed the DPSS-24, a 24-item scale designed to measure various psychopathy-related behaviors, including impulsivity, emotional detachment, and interpersonal difficulties, using a Likert scale ranging from 1 to 5.
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80 Views
With the development of recommender systems (RSs), several promising systems have emerged, such as context-aware RS, multi-criteria RS, and group RS. Multi-criteria recommender systems (MCRSs) are designed to provide personalized recommendations by considering user preferences in multiple attributes or criteria simultaneously. Unlike traditional RSs that typically focus on a single rating, these systems help users make more informed decisions by considering their diverse preferences and needs across various dimensions.
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163 Views
A number of disruptive technologies are expected to impact on future power systems (PS). Electric vehicles (EV), photovoltaic systems (PV), wind turbines (WT), energy storage systems (ESS), vehicle to grid (V2G), and demand response (DR) are seen as those with the most significant potential impact on the PS. Whereas various aspects of the integration of these six technologies into PS are well researched, the technologies are often studied in isolation from each other or in small subsets (e.g. PV and ESS).
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136 Views
This dataset used in the research paper "JamShield: A Machine Learning Detection System for Over-the-Air Jamming Attacks." The research was conducted by Ioannis Panitsas, Yagmur Yigit, Leandros Tassiulas, Leandros Maglaras, and Berk Canberk from Yale University and Edinburgh Napier University.
For any inquiries, please contact Ioannis Panitsas at ioannis.panitsas@yale.edu.
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182 Views
We used the broad group of 47,692 tweets from the Cyberbullying Classification dataset. This worldwide sourced dataset offers a broad range of examples of cyberbullying, guaranteeing a thorough viewpoint. Our thorough translation and modification procedure guaranteed the dataset's contextual and cultural relevance for the Tamil-speaking population, even though it is not solely from South Asia. These tweets were carefully divided into six classes, each of which represented a different facet of cyberbullying, as well as cases that weren't considered cyberbullying.
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397 Views
A crucial requirement for effective human-AI teaming is the ability to form mutually compatible mental models that help humans discern when the AI can be relied upon and how to best complement each other. To understand the impact of having this mutual understanding, we conducted an experiment where participants (N=125), tasked as disaster relief planners, were assisted by an AI agent that recommends optimal allocation of a resource based on several information sources. The interaction effects of mental models between the human and the AI were studied.
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74 Views
In the domain of gait recognition, the scarcity of non-simulated, real-world data significantly hampers the performance and applicability of recognition systems. To address this limitation, we present a comprehensive gait recognition dataset - GaitMotion- collected using built-in sensors of Android smartphones in an uncontrolled, real-world environment. This dataset captures the walking activity of 24 subjects (14 females and 10 males) above 18 years old and weighing at least 50 kg.
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178 Views
SynGen6 is a synthetic genomic dataset that encompasses six distinct populations. We utilized Principal Component Analysis (PCA) and ϵ-local differential privacy (LDP) to generate synthetic samples. We then simulated phenotype vectors associated with significant SNPs, mirroring real-world gene-disease associations. We also generated synthetic SNPs to watermark the dataset enabling verification of outsourced computations. Lastly, synthetic relatives were created to support research on kinship inference and family-based genomic analyses.
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65 Views