HTTP and DNS sample traffic traces for experimenting of protocol reverse engineering methods.
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Displaying 7849 - 7872 of 8281 results
Our state of arousal can significantly affect our ability to make optimal decisions, judgments, and actions in real-world dynamic environments. The Yerkes-Dodson law, which posits an inverse-U relationship between arousal and task performance, suggests that there is a state of arousal that is optimal for behavioral performance in a given task. Here we show that we can use on-line neurofeedback to shift an individual's arousal from the right side of the Yerkes-Dodson curve to the left toward a state of improved performance.
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The dataset is used in the paper entitled "A distributed Fog node assessment model by using Fuzzy rules learned by XGBoost" as fuzzy rules extracted by XGboost
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In this paper, the effects of input power of microwave antenna (MWAN) on liver cancerous tissue at injection of Magnetic Nanoparticles (MNPs) are investigated. At first for base simulation, we validate our results by a comparison with other literature reports. After that, we used a 1.8-cm hepatocellular carcinoma (HCC) tumor that was treated in experiment during a 3-min ablation by using MWAN operating on 2.45 GHz frequency with 90 W power. In the next step of the simulation, the obtained results were compared with experimental results.
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Our goal is to find whether a convolutional neural network (CNN) performs better than the existing blind algorithms for image denoising, and, if yes, whether the noise statistics has an effect on the performance gap. We performed automatic identification of noise distribution, over a set of nine possible distributions, namely, Gaussian, log-normal, uniform, exponential, Poisson, salt and pepper, Rayleigh, speckle and Erlang. Next, for each of these noisy image sets, we compared the performance of FFDNet, a CNN based denoising method, with noise clinic, a blind denoising algorithm.
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Data for the article in the Transactions on Industrial Informatics
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Full Duplex Sensor array
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AoT for Smart Society provides solutions of industry 4.0 standards in which contains custom-built multisensory wearable suit with cloud connectivity interfaced Artificial Intelligent techniques and Machine Learning algorithms in order to detect, to monitor and to analyze biofeedback control and visualization during human daily activities.
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Dataset for journal manuscript titled: 'Cardiac Motion Estimation from Noisy Medical Images: A Regularisation Framework Applied on Pairwise Image Registration Displacement Fields'
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The MovieLens 1M dataset has been extended introducing diverse shilling profiles to push or nuke a target item. Shilling profiles has been generated using different shilling attack methods: random, average, bandwagon, reverse-bandwagon, love-hate and perfect-knowledge. Each file contains the 1M original MovieLens ratings plus the added votes for the shilling profiles. Each shilling profile rates as many items as the mean number of ratings from each user in the original dataset. The dataset is divided in four quartiles based on the number of rating for the target item.
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Indoor location systems based on ultra-wideband (UWB) technology have become very popular in recent years following the introduction of a number of low-cost devices on the market capable of providing accurate distance measurements. Although promising, UWB devices also suffer from the classic problems found when working in indoor scenarios, especially when there is no a clear line-of-sight (LOS) between the emitter and the receiver, causing the estimation error to increase up to several meters.
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It gives the test results of a few typical samples to analyze the difference in the effect of moisture and aging on FDS curves. (a) and (b) take A1 and A4 samples as examples, respectively, to show the effect of moisture on frequency domain dielectric spectra. It can be seen that the frequency-domain response curves of dielectric loss increase with increase in the moisture content for both unaged and severely aged samples, and there is a difference of nearly two orders of magnitude between dry samples and severely damped samples.
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The DualModal2019 is a dual-modal fundus image dataset. It is for vessel, arteriole, and venule segmentation tasks. The dataset consists of five types of images: RGB color images, the 570 nm and 610 nm monochromic images, and the corresponding manually annotated ground truth images of the arterioles and venules.
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privacy location data
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We introduced the task of acoustic question answering (AQA) in https://arxiv.org/abs/1811.10561.
A second version of the dataset was introduced in https://arxiv.org/abs/2106.06147
This dataset aim to promote research in the acoustic reasoning area.
It comprise Acoustic Scenes and multiple questions/answers for each of them.
Each question is accompanied by a functional program which describe the reasoning steps needed in order to answer it.
The dataset is constitued is separated in 3 sets :
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Date fruit data sets are not publicly available. Previous studies have collected and used their own data set. Almost all these studies have few hundred images per class. As our motive was robust date fruit classification, we did not use the camera to take images of a particular size, angle or images with a particular background, instead to add robustness, we built our date fruit database using Google search engine. Hence the images had the multi-background, noise, different lighting condition, other objects, different packaging and sometimes even partial covering.
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These videos show bottom and side views of the treatment by a He/O2 plasma jet of a solution containing ultra-pure water, potassium iodide and starch. As the plasma reaches the liquid, a purple filament characteristic of the triiodide ion/starch complex appears. This complex is formed by the reaction between iodide ion and a reactive oxygen and nitrogen species (RONS) such as ozone, hydrogen peroxide, hydroxide ion, nitric oxyde or nitrate. Therefore, the formation of these RONS in the liquid phase is temporally and spatially quantified.
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Our Signing in the Wild dataset consists of various videos harvested from YouTube containing people signing in various sign languages and doing so in diverse settings, environments, under complex signer and camera motion, and even group signing. This dataset is intended to be used for sign language detection.
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A two-year electricity consumption data of a hotel building in Shanghai, China and and corresponding outdoor weather data.
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These tables provide proof of the authenticity and reliability of the article.
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The proposed signals are used for electromagnetic-based stroke classification. Six realistic head phantom computed from MRI scans, is surrounded by an antenna array of 16 dipole antennas distributed uniformly around the head. These antennas are deployed in a fixed circular array around the head, at a distance of approximately 2-3 mm from the head.
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The database was created with records of psychosocial risk level colombian teachers school using physiological variables from May 2016 to December 2017 in five municipalities of a metropolitan area of city in Colombia. The application of physiological variables was made to the people who voluntarily participated in the study. The names and personal data were kept by the researcher.
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The date fruit dataset was created to address the requirements of many applications in the pre-harvesting and harvesting stages. The two most important applications are automatic harvesting and visual yield estimation. The dataset is divided into two subsets and each of them is oriented into one of these two applications. The first dataset consists of 8079 images of more than 350 date bunches captured from 29 date palms. The date bunches belong to five date types: Naboot Saif, Khalas, Barhi, Meneifi, and Sullaj.
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The dataset comprises motion sensor data of 19 daily and sports activities each performed by 8 subjects in their own style for 5 minutes. Five Xsens MTx units are used on the torso, arms, and legs.
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