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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.

This document shows time-domain thermoreflectance (TDTR) measurements on blanket phase change multilayers [Fig. S1] and electro-thermal simulations of confined PCM cells [Fig. S2]. The extracted thermal resistance per unit area obtained from our measured TDTR signal ratio vs. time delay in Fig. S1 reveals that Bi2Te3 layer only introduces ~13% additional thermal resistance in the PCM stack. On the other hand, Fig. S2 shows the electro-thermal simulation of confined cells with 4 nm Bi2Te3 and 50 nm GST layer with a BE (TiN) diameter of 150 nm in Fig.

The following pages show axial T2-weighted MRI obtained at 24 hours and at 3-15 months after MRgFUS. The images shown here were registered to the same reference frame that was used in the thermal simulations; every third image is shown. To segment the bone marrow lesions, the registered images were toggled back and forth between the two time points to detect obvious changes. The lesion segmentations were completed before the acoustic and thermal simulations were performed. They were originally done on the native T2-weighted images acquired at 3-15 months after FUS.

This data set containts the detailed parameters of the modified Kundur's two-area system that is used in the manuscript "Hybrid Symbolic-Numeric Library for Power System Modeling and Analysis"