Compression techniques applied to multiple speech recognition systems

Speech recognition systems typically contain many Gaussian distributions, and hence a large number of parameters. This makes them both slow to decode speech, and large to store. Techniques have been proposed to decrease the number of parameters. One approach is to share parameters between multiple Gaussians, thus reducing the total number of parameters and allowing for shared likelihood calculation. Gaussian tying and subspace clustering are two related techniques which take this approach to system compression. These techniques can decrease the number of parameters with no noticeable drop in performance for single systems. However, multiple acoustic models are often used in real speech recognition systems. This paper considers the application of Gaussian tying and subspace compression to multiple systems. Results show that two speech recognition systems can be modelled using the same number of Gaussians as just one system, with little effect on individual system performance. Copyright © 2009 ISCA.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Comparison of Civil Infrastructure Optical-based Spatial Data Acquisition Techniques

Infrastructure spatial data, such as the orientation and the location of in place structures and these structures' boundaries and areas, play a very important role for many civil infrastructure development and rehabilitation applications, such as defect detection, site planning, on-site safety assistance and others. In order to acquire these data, a number of modern optical-based spatial data acquisition techniques can be used. These techniques are based on stereo vision, optics, time of flight, etc., and have distinct characteristics, benefits and limitations. The main purpose of this paper is to compare these infrastructure optical-based spatial data acquisition techniques based on civil infrastructure application requirements. In order to achieve this goal, the benefits and limitations of these techniques were identified. Subsequently, these techniques were compared according to applications' requirements, such as spatial accuracy, the automation of acquisition, the portability of devices and others. With the help of this comparison, unique characteristics of these techniques were identified so that practitioners will be able to select an appropriate technique for their own applications.

Experimental investigation of stratified combustion: Application of laser diagnostic techniques

In order to better understand the stratified combustion, the propagation of flame through stratified mixture field in laminar and turbulent flow conditions has been studied by using combined PIV/PLIF techniques. A great emphasis was placed on developing methods to improve the accuracy of local measurements of flame propagation. In particular, a new PIV approach has been developed to measure the local fresh gas velocity near preheat zone of flame front. To improve the resolution of measurement, the shape of interrogation window has been continuously modified based on the local flame topology and gas expansion effect. Statistical analysis of conditioned local measurements by the local equivalence ratio of flames allows the characterization of the properties of flame propagation subjected to the mixture stratification in laminar and turbulent flows, especially the highlight of the memory effect.

Fibre optic installation techniques for pile instrumentation

An innovative technique based on optical fibre sensing that allows continuous strain measurement has recently been introduced in structural health monitoring. Known as Brillouin Optical Time-Domain Reflectometry (BOTDR), this distributed optical fibre sensing technique allows measurement of strain along the full length (up to 10km) of a suitably installed optical fibre. Examples of recent implementations of BOTDR fibre optic sensing in piles are described in this paper. Two examples of distributed optical fibre sensing in piles are demonstrated using different installation techniques. In a load bearing pile, optical cables were attached along the reinforcing bars by equally spaced spot gluing to measure the axial response of pile to ground excavation induced heave and construction loading. Measurement of flexural behaviour of piles is demonstrated in the instrumentation of a secant piled wall where optical fibres were embedded in the concrete by simple endpoint clamping. Both methods have been verified via laboratory works. © 2009 IOS Press.

Experimental investigation of turbine stator well rim seal, reingestion and interstage seal flows using gas concentration techniques and displacement measurements

Gas turbine engine performance requires effective and reliable internal cooling over the duty cycle of the engine. Life predictions for rotating components subject to the main gas path temperatures are vital. This demands increased precision in the specification of the internal air system flows which provide turbine stator well cooling and sealing. This in turn requires detailed knowledge of the flow rates through rim seals and interstage labyrinth seals. Knowledge of seal movement and clearances at operating temperatures is of great importance when prescribing these flows. A test facility has been developed at the University of Sussex, incorporating a two stage turbine rated at 400 kW with an individual stage pressure ratio of 1.7:1. The mechanical design of the test facility allows internal cooling geometry to be rapidly re-configured, while cooling flow rates of between 0.71 CW, ENT and 1.46 C W, ENT, may be set to allow ingress or egress dominated cavity flows. The main annulus and cavity conditions correspond to in cavity rotational Reynolds numbers of 1.71×106< Reφ <1.93×106. Displacement sensors have been used to establish hot running seal clearances over a range of stator well flow conditions, allowing realistic flow rates to be calculated. Additionally, gas seeding techniques have been developed, where stator well and main annulus flow interactions are evaluated by measuring changes in gas concentration. Experiments have been performed which allow rim seal and re-ingestion flows to be quantified. It will be shown that this work develops the measurement of stator well cooling flows and provides data suitable for the validation of improved thermo-mechanical and CFD codes, beneficial to the engine design process. Copyright © 2011 by Rolls-Royce plc.

Analysis of document-mining techniques and tools for technology intelligence: Discovering knowledge from technical documents

This research proposes a method for extracting technology intelligence (TI) systematically from a large set of document data. To do this, the internal and external sources in the form of documents, which might be valuable for TI, are first identified. Then the existing techniques and software systems applicable to document analysis are examined. Finally, based on the reviews, a document-mining framework designed for TI is suggested and guidelines for software selection are proposed. The research output is expected to support intelligence operatives in finding suitable techniques and software systems for getting value from document-mining and thus facilitate effective knowledge management. Copyright © 2012 Inderscience Enterprises Ltd.

The design of multi-element airfoils through multi-objective optimization techniques

This paper presents the development and the application of a multi-objective optimization framework for the design of two-dimensional multi-element high-lift airfoils. An innovative and efficient optimization algorithm, namely Multi-Objective Tabu Search (MOTS), has been selected as core of the framework. The flow-field around the multi-element configuration is simulated using the commercial computational fluid dynamics (cfd) suite Ansys cfx. Elements shape and deployment settings have been considered as design variables in the optimization of the Garteur A310 airfoil, as presented here. A validation and verification process of the cfd simulation for the Garteur airfoil is performed using available wind tunnel data. Two design examples are presented in this study: a single-point optimization aiming at concurrently increasing the lift and drag performance of the test case at a fixed angle of attack and a multi-point optimization. The latter aims at introducing operational robustness and off-design performance into the design process. Finally, the performance of the MOTS algorithm is assessed by comparison with the leading NSGA-II (Non-dominated Sorting Genetic Algorithm) optimization strategy. An equivalent framework developed by the authors within the industrial sponsor environment is used for the comparison. To eliminate cfd solver dependencies three optimum solutions from the Pareto optimal set have been cross-validated. As a result of this study MOTS has been demonstrated to be an efficient and effective algorithm for aerodynamic optimizations. Copyright © 2012 Tech Science Press.

Predictive techniques for turbulent oscillatory flows

The prediction of turbulent oscillatory flow at around transitional Reynolds numbers is considered for an idealized electronics system. To assess the accuracy of turbulence models, comparison is made with measurements. A stochastic procedure is used to recover instantaneous velocity time traces from predictions. This procedure enables more direct comparison with turbulence intensity measurements which have not been filtered to remove the oscillatory flow component. Normal wall distances, required in some turbulence models, are evaluated using a modified Poisson equation based technique. A range of zero, one and two equation turbulence models are tested, including zonal and a non-linear eddy viscosity models. The non-linear and zonal models showed potential for accuracy improvements.

The incentives for supply chain collaboration to improve material efficiency in the use of steel: An analysis using input output techniques

In the face of increasing demand and limited emission reduction opportunities, the steel industry will have to look beyond its process emissions to bear its share of emission reduction targets. One option is to improve material efficiency - reducing the amount of metal required to meet services. In this context, the purpose of this paper is to explore why opportunities to improve material efficiency through upstream measures such as yield improvement and lightweighting might remain underexploited by industry. Established input-output techniques are applied to the GTAP 7 multi-regional input-output model to quantify the incentives for companies in key steel-using sectors (such as property developers and automotive companies) to seek opportunities to improve material efficiency in their upstream supply chains under different short-run carbon price scenarios. Because of the underlying assumptions, the incentives are interpreted as overestimates. The principal result of the paper is that these generous estimates of the incentives for material efficiency caused by a carbon price are offset by the disincentives to material efficiency caused by labour taxes. Reliance on a carbon price alone to deliver material efficiency would therefore be misguided and additional policy interventions to support material efficiency should be considered. © 2013 Elsevier B.V.