Gaming consoles are very common connected devices which have evolved in functionality and applications (games and beyond) they support. This diversity of traffic generated from these consoles has diverse quality of service (QoS) requirements. However, in order to offer diverse QoS, ISPs and operators must be able to classify this traffic. To enable research in traffic classification (Machine Learning based or other), we have generated and collected this dataset. This is a labelled dataset collected from a gaming console, PlayStation 4.

Instructions: 

Download Microsoft Network Monitor (at the following link: https://www.microsoft.com/en-us/download/details.aspx?id=4865) to be able to access the data. Open the capture file and then wait for all the collected frames to be loaded. The data set was collected using Microsoft Network Monitor 3.4. The traffic is Labelled by number, time and day, Source and Destination IP, Protocol, length and description. Using Microsoft Network Monitor, there is a way to Filter by Media type (check the following link: https://docs.microsoft.com/en-us/archive/blogs/netmon/intro-to-filtering...). To navigate the data easily, you can apply a filter on the media type by putting it Ethernet meaning that only the data exchanged between the Laptop and the PlayStation will show. The Excel sheet included with the dataset contains the date and the time of each capture and also when each activity was running and when it was stopped making it easy to identify the data. Refer to the time delay report attached for more information about the time synchronization aspects between the data capture and the PlayStation.

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The demo data set consists the propagation path distances of AT & T North America Netowork Topology. The geographical node positions (latitude and longitude) along with the adjacency matrix has been found out from International Topology Zoo and the data set has been formed using the available data. This set has been used in Joint localization prolem of Controller and Hypervisor instances in vSDN enebled 5G Network. 

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This article describes the possible design of the electron-ion trap combined density sensor and the composition of the upper atmosphere and simulation of the processes occurring in it. The simulation of the electric field between the electrodes of the trap and the motion of charged particles in it is carried out. The calculation of the maximum speed and energy of the particles below which the trap holds all charged particles, even in the case of the most unfavorable direction of their speed – along the gap between the electrodes.

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open access

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This dataset present the traffic volume (i.e., the bandwidth usage) of a university campus to the Internet during 6 months.

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2D geometrically shaped constellations that are simultaneously robust to both residual phase noise and AWGN (GS-RPN) for 8, 16, 32 and 64-ary formats. The presented formats are optimised at the generalised mutual information (GMI) threshold of 0.96m bits/symbol, where m is the number of bits per symbol. Additionally, we added AWGN-only constellations (GS-AWGN) to serve as a reference.

 

Note: This is a supplementary dataset for a journal submission.

Instructions: 

Each modulation order is placed in a separate folder, in which, every text file has the coordinates for the in-phase and quadrature components of each symbol in the first and the second column, respectively. The bit mapping for each symbol is natural mapping for the line number, i.e., 000 001 010 011 100 etc.

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The NSI-MI measurement setup of the 140-220 GHz corrugated horn D-plane radiation pattern. It is a short movie.

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The project is conceptualized to 'Geo Web-Based Facility Mapping for Zone-2 in Greater Visakhapatnam Municipal Corporation- GVMC in Visakhapatnam, India'. The main objective is to share the spatial data to the public to help them find the information about the nearest Hospital, ATM, Educational institutions, petrol filling stations, and supermarkets by providing both web map services and web coverage services using QGIS Cloud.

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We test the consumed time of the three steps of the exchange model in order to show that our scheme is feasible.

 

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The data set are images taken from the Particle Image Velocimetry (PIV) method and the Planar Laser-Induced Fluorescence (PLIF) method. These methods set out the macro-scale experimental techniques that can enable fluid dynamic knowledge to inform molecular communication performance and design. Fluid dynamic experiments can capture latent features that allow the receiver to detect coherent signal structures and infer transmit parameters for optimal decoding.

Instructions: 

They are in 22 zip files, the first two files are related to the PIV test and the other are for the PLIF test. PIV test files contain 654 and 1392 images for frame rates of 15 and 90 fps, respectively. The image format is .bmp, and the first image in each set is the calibration image. There are 20 zip files named PLIF-1 to PLIF-20. Each file contains approximately 150 images in .tif format. The first 25 images in each file are calibration images and the rest are images of the laser plane after injection of the fluorescence. All images are recorded with a frame rate of 2 fps so one can calculate the total recording time according to the number of images per file. The MATLAB code has also provided in each file that can help in image processing.

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In the fifth generation (5G) wireless communication, high-speed railway (HSR) communication is one of the most challenging scenarios. By adopting massive multi-input multi-output (mMIMO) technology in HSR communication, the design of the underlying communication system becomes more challenging. Some new channel characteristics must be studied, such as non-stationarity in space, time and frequency domains. In this paper, two models are established for the two states of HSR at rest or in motion.

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