Digital Dissemination Platform of Transportation Engineering Education Materials Founded in Adoption Research

INE/AUTC 14.0

Lean implementation to improve scheduling for a multi-cell manufacturing facility

Includes bibliographical references

Information Technology, Organisational Change and Productivity Growth: Evidence from UK Firms

We examine the relationships between productivity growth, IT investment and organisational change (Δ O) using UK firm panel data. Consistent with the small number of other micro studies we find (a) IT appears to have high returns in a growth accounting sense when Δ O is omitted; when Δ O is included the IT returns are greatly reduced, (b) IT and Δ O interact in their effect on productivity growth, (c) non-IT investment and Δ O do not interact in their effect on productivity growth. Some new findings are (a) Δ O is affected by competition and (b) we also find strong effects on the probability of introducing Δ O from ownership. US-owned firms are much more likely to introduce Δ O relative to foreign owned firms who are more likely still relative to UK firms.Information technology, Productivity growth, Organisational change

Subtask Gated Networks for Non-Intrusive Load Monitoring

Non-intrusive load monitoring (NILM), also known as energy disaggregation, is a blind source separation problem where a household's aggregate electricity consumption is broken down into electricity usages of individual appliances. In this way, the cost and trouble of installing many measurement devices over numerous household appliances can be avoided, and only one device needs to be installed. The problem has been well-known since Hart's seminal paper in 1992, and recently significant performance improvements have been achieved by adopting deep networks. In this work, we focus on the idea that appliances have on/off states, and develop a deep network for further performance improvements. Specifically, we propose a subtask gated network that combines the main regression network with an on/off classification subtask network. Unlike typical multitask learning algorithms where multiple tasks simply share the network parameters to take advantage of the relevance among tasks, the subtask gated network multiply the main network's regression output with the subtask's classification probability. When standby-power is additionally learned, the proposed solution surpasses the state-of-the-art performance for most of the benchmark cases. The subtask gated network can be very effective for any problem that inherently has on/off states

Monte Carlo Planning method estimates planning horizons during interactive social exchange

Reciprocating interactions represent a central feature of all human exchanges. They have been the target of various recent experiments, with healthy participants and psychiatric populations engaging as dyads in multi-round exchanges such as a repeated trust task. Behaviour in such exchanges involves complexities related to each agent's preference for equity with their partner, beliefs about the partner's appetite for equity, beliefs about the partner's model of their partner, and so on. Agents may also plan different numbers of steps into the future. Providing a computationally precise account of the behaviour is an essential step towards understanding what underlies choices. A natural framework for this is that of an interactive partially observable Markov decision process (IPOMDP). However, the various complexities make IPOMDPs inordinately computationally challenging. Here, we show how to approximate the solution for the multi-round trust task using a variant of the Monte-Carlo tree search algorithm. We demonstrate that the algorithm is efficient and effective, and therefore can be used to invert observations of behavioural choices. We use generated behaviour to elucidate the richness and sophistication of interactive inference

The thirty-hour week: its social and economic significance

This item was digitized by the Internet Archive

Moment-Based Order-Independent Transparency

Compositing transparent surfaces rendered in an arbitrary order requires techniques for order-independent transparency. Each surface color needs to be multiplied by the appropriate transmittance to the eye to incorporate occlusion. Building upon moment shadow mapping, we present a moment-based method for compact storage and fast reconstruction of this depth-dependent function per pixel. We work with the logarithm of the transmittance such that the function may be accumulated additively rather than multiplicatively. Then an additive rendering pass for all transparent surfaces yields moments. Moment-based reconstruction algorithms provide approximations to the original function, which are used for compositing in a second additive pass. We utilize existing algorithms with four or six power moments and develop new algorithms using eight power moments or up to four trigonometric moments. The resulting techniques are completely order-independent, work well for participating media as well as transparent surfaces and come in many variants providing different tradeoffs. We also utilize the same approach for the closely related problem of computing shadows for transparent surfaces

The Government Service Technological Revolution: Challenges and Opportunities to Local Governments in Regard to E- Government Implementation and Advancement

This analysis addreses the various issues that affect local government\u27s ability to provide services via the web. The focus will be on e government services provided through local town websites. Discussed are various obstacles and opportunities that local municipalities and small government entities face with the adoption of e government services