This work investigates Industry 4.0 technologies by developing a new key performance
indicator that can determine the energy consumption of machine tools for a more …

Cutting-edge functionalities in embedded systems require the use of parallel architectures to
meet their performance requirements. This imposes the introduction of a new layer in the …

Mobile and wearable sensor technologies have gradually extended their usability into a
wide range of applications, from well-being to healthcare. The amount of collected data can …

The purpose of this work is to develop a new Key Performance Indicator (KPI) that can
quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber …

Python is a popular programming language, and a large part of its appeal comes from
diverse libraries and extension modules. In the bloom of data science and machine learning …

Within the last years, Python became more prominent in the scientific community and is now
used for simulations, machine learning, and data analysis. All these tasks profit from …

Abstract Current Big Data applications are characterized by a heavy use of system
resources (eg, CPU, disk) generally distributed across a cluster. To effectively improve their …

In this paper, we evaluate the performance of parallelism in Python and C++. Parallel
programming can be achieved in Python through the multiprocessing module and in C++ by …

Parallelization is a promising way to improve the performance of Python programs.
Unfortunately, developers may miss parallelization possibilities, because they usually do not …

Many engineering applications require complex frameworks to simulate the intricate and
extensive sub-problems involved. However, performance analysis tools can struggle when …