Occupant productivity and office indoor environment quality : a review of the literature

The purpose of this paper is to review the existing literature to draw an understanding of the relationship between indoor environmental quality and occupant productivity in an office environment. The study reviews over 300 papers from 67 journals, conference articles and books focusing on indoor environment, occupant comfort, productivity and green buildings. It limits its focus to the physical aspects of an office environment. The literature outlines eight Indoor Environmental Quality (IEQ) factors that influence occupant productivity in an office environment. It also discusses different physical parameters under each of the IEQ factors. It proposes a conceptual model of different factors affecting occupant productivity. The study also presents a review of the data collection methods utilised by the research studies that aim to investigate the relationship between IEQ and occupant productivity. The study presents a comprehensive discussion and analysis of different IEQ factors that affect occupant productivity. The paper provides a concise starting point for future researchers interested in the area of indoor environmental quality

Interlocking Backpropagation: Improving depthwise model-parallelism

The number of parameters in state of the art neural networks has drastically increased in recent years. This surge of interest in large scale neural networks has motivated the development of new distributed training strategies enabling such models. One such strategy is model-parallel distributed training. Unfortunately, model-parallelism suffers from poor resource utilisation, which leads to wasted resources. In this work, we improve upon recent developments in an idealised model-parallel optimisation setting: local learning. Motivated by poor resource utilisation, we introduce a class of intermediary strategies between local and global learning referred to as interlocking backpropagation. These strategies preserve many of the compute-efficiency advantages of local optimisation, while recovering much of the task performance achieved by global optimisation. We assess our strategies on both image classification ResNets and Transformer language models, finding that our strategy consistently out-performs local learning in terms of task performance, and out-performs global learning in training efficiency

Robotics Education Under COVID-19 Conditions with Educational Modular Robots

The COVID-19 pandemic forces many robotics teachers to rethink their approach to education. Distance rules and the constant threat of a partial or complete lockdown leading to limited access to classroom equipment make it challenging to plan for hands-on education where students experience robotics by experimenting and studying with robotic hardware. On the other hand, this hands-on active learning experience is one of the strengths of robotics education and the ability to handle hardware equipment a substantial learning goal of study programs on robotics. In this paper we present and discuss the approach taken for the course Robotics and Embedded Systems at Maastricht University. The course had been adjusted to meet COVID-19 safety regulations and to allow for a fast seamless transition between onsite education at university and online education where students can work with robotic hardware at home. We share experience, best practice advice as well as educational material to help other teachers benefit from our developments. A key contribution is our custom-made, low-cost, educational modular robotic system for teaching kinematics, locomotion, and PID control that we make publicly available for replication through the website https://www.maastrichtuniversity.nl/edmo

An Unmanned Aerial Carrier and Anchoring Mechanism for Transporting Companion UAVs

This paper demonstrates an unmanned aerial carrier as well as a new anchoring mechanism for connecting and transporting companion unmanned aerial vehicles (UAVs). Establishing this platform presents unique challenges including the requirements of precise localization of the platform, real-time environment mapping system, robust flight control approach, docking safety mechanism, and reliable anchor system for the companion UAV. To obtain the positioning information, a tightly-coupled visual-inertial optimization based odometry is implemented with a fisheye camera and an inertial measurement unit. A 3D map is updated in real-time using an Octomap framework. A nonlinear position model predictive controller cascaded with a DJI attitude controller is implemented for the flight control. Innovatively, we designed a lightweight anchoring mechanism for safe landing and reliable transportation of the companion UAV. Real-world experiments results suggest that the transportation system is a viab le approach to transport the companion UAV, and that the proposed anchoring mechanism allows for reliable operation