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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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167 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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139 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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188 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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407 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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190 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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68 Views
This is an example of a signal from an RCD reading from a 7W Led Lamp load. The data is titled with two status: 0 for normal condition (NC) and 1 for single fault condition (SFC). From the signal, It was evident that the peak voltage fluctuated over a certain time. The signal waveform displayed a positive peak and a negative peak alternatively in a comparable amount of time, while lacking any distinct cosine form or fixed values for the peak voltages. It was discovered through measuring that time period that it had the same frequency of 50 Hz as the source of the input.
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27 Views
The TiHAN-V2X Dataset was collected in Hyderabad, India, across various Vehicle-to-Everything (V2X) communication types, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Infrastructure-to-Vehicle (I2V), and Vehicle-to-Cloud (V2C). The dataset offers comprehensive data for evaluating communication performance under different environmental and road conditions, including urban, rural, and highway scenarios.
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683 Views
Endemic fish species are key components in seafood culinary excursions. Despite the increasing interest in leveraging technology to enhance various seafood culinary activities, there is a shortage of comprehensive datasets containing images of seafood used in artificial intelligence research, mainly those showcasing endemic fish. This research endeavors to bridge this gap by increasing the accuracy of fish recognition and introducing a new dataset comprising images of native fish for application in various machine-learning investigations.
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173 Views