Reprint: R0411J In the classroom, activity-based costing (ABC) looks like a great way to manage a company’s limited resources. But executives who have tried to implement ABC in their ...

For decades, Activity-Based Costing (ABC) has been an important tool for analysts and business leaders to assess their production and make course corrections necessary for survival and success. Today, ...

Introduction Osteoarthritis of the knee has been identified as the most common disability in Pakistan. Total knee replacement (TKR) surgery is the curative treatment for advanced osteoarthritis of the ...

Human activity recognition is an emerging technology for many security, surveillance, and health service applications utilizing wireless sensor networks (WSNs). However, the exploitation of radar in ...

Full Economic Costing (FEC) is a government-directed standard costing methodology used across the UK Higher Education sector for the production of consistent and transparent research project costs.

The progress of the pillar[5]arene chemistry allowed us to set out a new concept on application of the supramolecular assemblies to create antimicrobial films with variable surface morphologies and ...

The face-centered cubic (fcc) Ru exhibits great potential for the alkaline hydrogen oxidation reaction (HOR), while achieving high HOR activity and CO tolerance poses a formidable challenge for Ru ...

Key Features of RobustBenchHAR: The first large-scale benchmark for evaluating adversarial robustness in Human Activity Recognition (HAR): RobustBenchHAR ensembles existing adversarial attacks ...

Citation: Kobayashi H, Song C, Ikei H, Park B-J, Lee J, Kagawa T and Miyazaki Y (2018) Forest Walking Affects Autonomic Nervous Activity: A Population-Based Study. Front. Public Health 6:278. doi: ...

Objective To describe changing use of primary care in relation to use of urgent care and planned hospital services by children aged less than 15 years in England in the decade following major primary ...

This project focuses on Human Activity Recognition (HAR) using time-series sensor data collected from mobile devices. The goal is to build a deep learning model specifically an (LSTM-based neural ...