Artificial Intelligence
The picture shows the operation result of image security retrieval. The experiment was validated on five common data sets.
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"128_dim_word_vector" is the word vector that is used in 2.2.1. "86 keywords" is used to extract directive sentences in section 3.1.1. "constructed_KG and source_of_data" contains the constructed API-Task KG and source of data used in constructed KG. ”Experiment RQ_1 and RQ_2" is the experiment data. "Empirical_study" contains the Stack Overflow questions that are used in the empirical study.
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This dataset represents the normal and faulty residual signals for the spacecraft reaction wheel.
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Anonymous network traffic is more pervasive than ever due to the accessibility of services such as virtual private networks (VPN) and The Onion Router (Tor). To address the need to identify and classify this traffic, machine and deep learning solutions have become the standard. However, high-performing classifiers often scale poorly when applied to real-world traffic classification due to the heavily skewed nature of network traffic data.
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Measuring the appearance time slots of characters in videos is still an unsolved problem in computer vision, and the related dataset is insufficient and unextracted. The Character Face In Video (CFIV) dataset provides the labeled appearing time slots for characters of interest for ten video clips on Youtube, two faces per character for training, and a script for downloading each video. Additionally, three videos contain around 100 images per character for evaluating the accuracy of the face recognizer.
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Traffic data set
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637 Views
This dataset accurately models the internal behavior of an IoT spectrum sensor (belonging to the ElectroSense platform and consisting of a Raspberry Pi 3 with a software-defined radio kit) when it is functioning normally and under attack. To accomplish it, the system calls of the IoT sensor are monitored under normal behavior, gathered, cleaned, and stored in a centralized directory. Then, the device is infected with current malware affecting IoT devices, such as the Bashlite botnet, Thetick backdoor, Bdvl rootkit, and a Ransomware proof of concept.
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1104 Views
In this paper, we propose a novel cooperative resource sharing in a multi-tier edge slicing networks which is
robust to imperfect channel state information (CSI) caused by user equipments’ (UEs) mobility. Due to the mobility
of UEs, the dynamic requirements of their tasks, and the limited resources of the network, we propose a smart joint
dynamic pricing and resources sharing (SJDPRS) scenario that can incentivize the infrastructure provider (InP) and
mobile network operators (MNOs). Aiming to maximize the profits of UEs, MNOs and the InP under the task
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357 Views
This is the market data of Bitcoin in terms of price and volume from August 2015 to August 2021. The time interval of sampling is selected as four-hour, that is to say, we choose every kind of price and volume every of four-hour as the original data. The original market data of Bitcoin are obtained from Poloniex, one of the most active crypto-asset exchanges.
Download link on XBlock: http://xblock.pro/#/dataset/5
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1243 Views
The near infrard spectra of 80 corns
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64 Views