This dataset is the supplementary material of an IEEE RAL paper named "Design of Fully Controllable and Continuous Programmable Surface Based on Machine Learning". It includes the z-displacement data derived from the FEA simulation, voltage input data derived from Matlab, and dataset for inverse application. The detailed description can be found in that paper.

Biomechanics has predominantly relied upon the trajectory optimization method for the analysis and prediction of the movement of the limbs. Such approaches have paved the way for the motion planning of biped and quadruped robots as well. Most of these methods are deterministic, utilizing first-order iterative gradient-based algorithms incorporating the constrained differentiable objective functions.

In this data file are the ratings made by 36 subjects during an experiment evaluating 3 different products (desktop telephones) in three different media: photorealistic renders, augmented reality and virtual reality. In addition, their opinion about the overall evaluation of the product ("Like"), security in response and purchase decision was collected. The presence data collected is equivalent to the application of the SUS presence test.

CONTENTS OF THIS FILE

•  Data Analysis
•  Experimental Design

Data Analysis

This folder consists of data obtained from the experiments and the materials we use for analysis. Here we provide the following documents:

01-The folder "Class diagrams"

      This folder contains class diagrams realized by participants in three experiments.

02-Code.R 

Abstract—Chipless RFID tag decoding has some inherent degrees of uncertainty because there is no handshake protocol between chipless tags and readers. This paper initially compares the outcome of different pattern recognition methods to decode some frequency-based tags in the mm-wave spectrum. It will be shown that these pattern recognition methods suffer from almost 2 to 5% false decoding rate. To overcome this mis-decoding problem, two novel methods of making images of the chipless tags are presented.

This sheet contains the answers from our european Cyber Security MSc Education Survey. The data shows which knowledge units various educations in Europe cover and to which extend. We drew conclusions in the paper "Are We Preparing Students to Build Security In? A Survey of European Cybersecurity in Higher Education Programs". The present dataset is newer and therefore extends the one we based our paper on.

Mother’s Significant Feature (MSF) Dataset has been designed to provide data to researchers working towards woman and child health betterment. MSF dataset records are collected from the Mumbai metropolitan region in Maharashtra, India. Women were interviewed just after childbirth between February 2018 to March 2021. MSF comprise of 450 records with a total of 130 attributes consisting of mother’s features, father’s features and health outcomes. A detailed dataset is created to understand the mother’s features spread across three phases of her reproductive age i.e.

 The dataset consists of results of 10 different tests conducted on 8 different types of battery cells. All batteries are designed in 18650, but they differ in manufacturer and composition. The measurements can be divided into three groups: constant load tests, WLTP tests at different temperatures and transient tests. Constant load tests are performed at 0.1C and 1C as a function of battery capacity, both during charging and discharging. During transient tests, a 360s load/charge is followed by a 60s relaxation.

Silk fibroin is the structural fiber of the silk filament and it is usually separated from the external fibroin by a chemical process called degumming. This process consists in an alkali bath in which the silk cocoons are boiled for a determined time. It is also known that the degumming process impacts the property of the outcoming silk fibroin fibers.

Data Analysis

This folder consists of data obtained from the experiments and the materials we use for analysis. Here we provide the following documents: