GRSS SAR/PolSAR DATABASE

The distributed generation, along with the deregulation of the Smart Grid, have created a great concern on Power Quality (PQ), as it has a direct impact on utilities and customers, as well as effects on the sinusoidal signal of the power line. The a priori unknown features of the distributed energy resources (DER) introduce non-linear behaviours in loads associated to a variety of PQ disturbances.

This data content is the relevant data information in the paper "Research of the Scraper Bucket Motion Based on the Mathematical Model of Loader’s Working Device".

This is a compressed archive containing a Docker image with a software development kit (SDK) for HEROv2 (see https://github.com/pulp-platform/hero). This SDK currently contains:

This dataset complies 172 chipless RFID measurements that have been reported in the literature from 2005-2022. The dataset contain the year, reading distance, frequency range, tag type, reader setup, and reference for each entry.

The article presented a synthesis of expert opinions about open research remarked as a substantial influence on knowledge and innovation of concepts dissemination contained in published and unpublished manuscripts. The practise of open science reach increased in acceptance in recent years due to the challenging effort of the researchers who have written scientific articles.

Task prioritization is one of the most researched areas in software development. Given the huge amount of papers written on the topic, it might be challenging for IT practitioners to find the most appropriate tools or methods developed to date to deal with this important issue. To overcome this problem, we conducted a systematic literature review. The main goal of this work is to review the current state of research and practice on task prioritization among IT practitioners and to individuate the most effective ranking tools and techniques used in the industry.

This dataset consists of a simulated normal distribution data having n = 500 data points and mean = 80 and standard deviation = 2.

This is the supplementary file of "Fast Algorithms for Exact IR Drop De-embedding in Analog Multiply-Accumulate Computing". Mathematical derivation and supporting data is provided.

Dataset