Ventilation effectiveness measures based on heat removal: Part 1. Definitions

The effectiveness of ventilation flows is considered from the perspective of buoyancy (or heat) removal from a space. This perspective is distinct from the standard in which the effectiveness is based on the concentrations of a neutrally buoyant contaminant/passive tracer. Three new measures of effectiveness are proposed based on the ability of a flow to flush buoyancy from a ventilated space. These measures provide estimates of instantaneous and time-averaged effectiveness for the entire space, and local effectiveness at any height of interest. From a generalisation of the latter, a vertical profile of effectiveness is defined. These measures enable quantitative comparisons to be made between different flows and they are applicable when there is a difference in density (as is typical due to temperature differences) between the interior environment and the replacement air. Applications, therefore, include natural ventilation, hybrid ventilation and a range of forced ventilation flows. Finally, we demonstrate how the ventilation effectiveness of a room may be assessed from simple traces of temperature versus time. © 2006 Elsevier Ltd. All rights reserved.

New ventilation efficiency measures based on buoyancy removal

New measures for estimating the efficiency of transient ventilation flows are proposed. These measures are developed by considering how effectively a ventilation system removes buoyancy from a space. This approach is distinct from standard efficiency measures which are, in general, based on the removal of a neutrally-buoyant passive tracer. Our new measures, based on (active) buoyancy removal, allow both the instantaneous and time-averaged efficiency of the entire space, or of any region within it, to be determined. In addition, expressions for determining vertical profiles of efficiency are proposed. These new measures enable the effectiveness of different flows to be compared directly and are applicable providing density (temperature) differences exist between the interior environment and the replacement air. Thus, they may be used to contrast the effectiveness of a broad range of building ventilation flows including natural, hybrid and forced ventilation.

N-gram posterior probability confidence measures for statistical machine translation: An empirical study

We report an empirical study of n-gram posterior probability confidence measures for statistical machine translation (SMT). We first describe an efficient and practical algorithm for rapidly computing n-gram posterior probabilities from large translation word lattices. These probabilities are shown to be a good predictor of whether or not the n-gram is found in human reference translations, motivating their use as a confidence measure for SMT. Comprehensive n-gram precision and word coverage measurements are presented for a variety of different language pairs, domains and conditions. We analyze the effect on reference precision of using single or multiple references, and compare the precision of posteriors computed from k-best lists to those computed over the full evidence space of the lattice. We also demonstrate improved confidence by combining multiple lattices in a multi-source translation framework. © 2012 The Author(s).

A reversible infinite HMM using normalised random measures

Copyright 2014 by the author(s). We present a nonparametric prior over reversible Markov chains. We use completely random measures, specifically gamma processes, to construct a countably infinite graph with weighted edges. By enforcing symmetry to make the edges undirected we define a prior over random walks on graphs that results in a reversible Markov chain. The resulting prior over infinite transition matrices is closely related to the hierarchical Dirichlet process but enforces reversibility. A reinforcement scheme has recently been proposed with similar properties, but the de Finetti measure is not well characterised. We take the alternative approach of explicitly constructing the mixing measure, which allows more straightforward and efficient inference at the cost of no longer having a closed form predictive distribution. We use our process to construct a reversible infinite HMM which we apply to two real datasets, one from epigenomics and one ion channel recording.

Production planning of multi-stage multi-option seru production systems with sustainable measures

With the concerns over climate change and the escalation in worldwide population, sustainable development attracts more and more attention of academia, policy makers, and businesses in countries. Sustainable manufacturing is an inextricable measure to achieve sustainable development since manufacturing is one of the main energy consumers and greenhouse gas contributors. In the previous researches on production planning of manufacturing systems, environmental factor was rarely considered. This paper investigates the production planning problem under the performance measures of economy and environment with respect to seru production systems, a new manufacturing system praised as Double E (ecology and economy) in Japanese manufacturing industries. We propose a mathematical model with two objectives minimizing carbon dioxide emission and makespan for processing all product types by a seru production system. To solve this mathematical model, we develop an algorithm based on the non-dominated sorting genetic algorithm II. The computation results and analysis of three numeral examples confirm the effectiveness of our proposed algorithm. © 2014 Elsevier Ltd. All rights reserved.