Application of decarboxylation reactions for improvement of dielectric properties of a methacrylic polymer.

In this work, we present a method based on thermally induced decarboxylation to solve the incompatibility of dielectric properties and the developability in aqueous developer solution of dielectric materials for the application in photodefinable insulating materials. Herein, malonic acid 2-hydroxyethyl methacrylate monoester, a methacrylate monomer with β-keto acid is synthesized phosphotungstic acid catalyzed esterification of 2-hydroxyethyl methacrylate and malonic acid. Further polymerisation is conducted with the obtained monomer to prepare poly(2-hydroxyethyl methacrylate--malonic acid 2-hydroxyethyl acrylate monoester).

Applying neural network to VO2 estimation using 6-axis motion sensing data.

This paper focuses on oxygen consumption (VO2) estimation using 6-axis motion data (3-axis acceleration and 3-axis angular velocity) that are obtained from small motion sensors attached to people playing sports with different intensities. In order to achieve high estimation accuracy over a wide range of intensities of exercises, we apply neural network that is trained by experimental data consisting of the measured VO2 and motion sensing data of people with a wide range of intensities of exercises. We first investigate the gain brought by applying neural network by comparing its accuracy with an approach based on the linear regression model.

VO2 estimation using 6-axis motion sensor with sports activity classification.

In this paper, we focus on oxygen consumption (VO2) estimation using 6-axis motion sensor (3-axis accelerometer and 3-axis gyroscope) for people playing sports with diverse intensities. The VO2 estimated with a small motion sensor can be used to calculate the energy expenditure, however, its accuracy depends on the intensities of various types of activities. In order to achieve high accuracy over a wide range of intensities, we employ an estimation framework that first classifies activities with a simple machine-learning based classification algorithm.