22 resultados para Preissmann slot
em Cambridge University Engineering Department Publications Database
Resumo:
We present a novel optical routing scheme scalable to greater than 50×50 channels with a potential aggregate bit-rate of 1Tbps. The proof-of-principle experiment demonstrates the feasibility of the router with a de-multiplexed Q-factor of 6.35. © 2004 Optical Society of America.
Resumo:
We present experimental measurements on Silicon-on-insulator (SOI) photonic crystal slabs with an active layer containing Er3+ ions-doped Silicon nanoclusters (Si-nc), showing strong enhancement of 1.54 μm emission at room temperature. We provide a systematic theoretical analysis to interpret such results. In order to get further insight, we discuss experimental data on the guided luminescence of unpatterned SOI planar slot waveguides, which show enhanced light emission in transverse-magnetic (TM) modes over transverse-electric (TE) ones. ©2007 IEEE.
Resumo:
This paper proposes an analytical approach that is generalized for the design of various types of electric machines based on a physical magnetic circuit model. Conventional approaches have been used to predict the behavior of electric machines but have limitations in accurate flux saturation analysis and hence machine dimensioning at the initial design stage. In particular, magnetic saturation is generally ignored or compensated by correction factors in simplified models since it is difficult to determine the flux in each stator tooth for machines with any slot-pole combinations. In this paper, the flux produced by stator winding currents can be calculated accurately and rapidly for each stator tooth using the developed model, taking saturation into account. This aids machine dimensioning without the need for a computationally expensive finite element analysis (FEA). A 48-slot machine operated in induction and doubly-fed modes is used to demonstrate the proposed model. FEA is employed for verification.
Resumo:
Of all laser-based processes, laser machining has received little attention compared with others such as cutting, welding, heat treatment and cleaning. The reasons for this are unclear, although much can be gained from the development of an effcient laser machining process capable of processing diffcult materials such as high-performance steels and aerospace alloys. Existing laser machining processes selectively remove material by melt shearing and evaporation. Removing material by melting and evaporation leads to very low wall plug effciencies, and the process has difficulty competing with conventional mechanical removal methods. Adopting a laser machining solution for some materials offers the best prospects of effcient manufacturing operations. This paper presents a new laser machining process that relies on melt shear removal provided by a vertical high-speed gas vortex. Experimental and theoretical studies of a simple machining geometry have identifed a stable vortex regime that can be used to remove laser-generated melt effectively. The resultant combination of laser and vortex is employed in machining trials on 43A carbon steel. Results have shown that laser slot machining can be performed in a stable regime at speeds up to 150mm/min with slot depths of 4mm at an incident CO2 laser power level of 600 W. Slot forming mechanisms and process variables are discussed for the case of steel. Methods of bulk machining through multislot machining strategies are also presented.
Resumo:
Although partially observable Markov decision processes (POMDPs) have shown great promise as a framework for dialog management in spoken dialog systems, important scalability issues remain. This paper tackles the problem of scaling slot-filling POMDP-based dialog managers to many slots with a novel technique called composite point-based value iteration (CSPBVI). CSPBVI creates a "local" POMDP policy for each slot; at runtime, each slot nominates an action and a heuristic chooses which action to take. Experiments in dialog simulation show that CSPBVI successfully scales POMDP-based dialog managers without compromising performance gains over baseline techniques and preserving robustness to errors in user model estimation. Copyright © 2006, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.
Resumo:
This paper describes a method of improving the cooling of the hub region of high-pressure turbine (HPT) rotor by making better use of the unsteady coolant flows originating from the upstream vane. The study was performed computationally on an engine HPT stage with representative inlet hot streak and vane coolant conditions. An experimental validation study of hot streak migration was undertaken on two low-speed test facilities. The unsteady mechanisms that transport hot and cold fluid within the rotor hub region are first examined. It was found that vortex-blade interaction dominated the unsteady transport of hot and cold fluid in the rotor hub region. This resulted in the transport of hot fluid onto the rotor hub and pressure surface, causing a peak in the surface gas temperatures. The vane film coolant was found to have only a limited effect in cooling this region. A new cooling configuration was thus examined which exploits the unsteadiness in rotor hub to aid transport of coolant towards regions of high rotor surface temperatures. The new coolant was introduced from a slot upstream of the vane. This resulted in the feed of slot coolant at a different phase and location relative to the vane film coolant within the rotor. The slot coolant was entrained into the unsteady rotor secondary flows and transported towards the rotor hub-pressure surface region. The slot coolant reduced the peak time-averaged rotor temperatures by a similar amount as the vane film coolant despite having only a sixth of the coolant mass flow. Copyright © 2008 by ASME.
Resumo:
This paper investigates several approaches to bootstrapping a new spoken language understanding (SLU) component in a target language given a large dataset of semantically-annotated utterances in some other source language. The aim is to reduce the cost associated with porting a spoken dialogue system from one language to another by minimising the amount of data required in the target language. Since word-level semantic annotations are costly, Semantic Tuple Classifiers (STCs) are used in conjunction with statistical machine translation models both of which are trained from unaligned data to further reduce development time. The paper presents experiments in which a French SLU component in the tourist information domain is bootstrapped from English data. Results show that training STCs on automatically translated data produced the best performance for predicting the utterance's dialogue act type, however individual slot/value pairs are best predicted by training STCs on the source language and using them to decode translated utterances. © 2010 ISCA.