22 resultados para lightener evaluation system tyrosinaseTYR


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Computational Design has traditionally required a great deal of geometrical and parametric data. This data can only be supplied at stages later than conceptual design, typically the detail stage, and design quality is given by some absolute fitness function. On the other hand, design evaluation offers a relative measure of design quality that requires only a sparse representation. Quality, in this case, is a measure of how well a design will complete its task.

The research intends to address the question: "Is it possible to evaluate a mechanical design at the conceptual design phase and be able to make some prediction of its quality?" Quality can be interpreted as success in the marketplace, success in performing the required task, or some other user requirement. This work aims to determine a minimum level of representation such that conceptual designs can be usefully evaluated without needing to capture detailed geometry. This representation will form the model for the conceptual designs that are being considered for evaluation. The method to be developed will be a case-based evaluation system, that uses a database of previous designs to support design exploration. The method will not be able to support novel design as case-based design implies the model topology must be fixed.

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A multi-disciplinary team based at Heriot-Watt University and other Universities has been set up to tackle the design and manufacturing of lab-on-a-chip for industries as one of the demonstrators of the EPSRC Grand Challenge project "3D-Mintegration". The team focuses on the analysis of foetal genetic material extracted from maternal blood as a smart alternative to invasive prenatal testing such as amniocentesis. The first module of the microsystem envisaged achieves a separation of blood cells from plasma. This system permits the testing of different manufacturing techniques.

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Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

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This paper describes the development of the 2003 CU-HTK large vocabulary speech recognition system for Conversational Telephone Speech (CTS). The system was designed based on a multi-pass, multi-branch structure where the output of all branches is combined using system combination. A number of advanced modelling techniques such as Speaker Adaptive Training, Heteroscedastic Linear Discriminant Analysis, Minimum Phone Error estimation and specially constructed Single Pronunciation dictionaries were employed. The effectiveness of each of these techniques and their potential contribution to the result of system combination was evaluated in the framework of a state-of-the-art LVCSR system with sophisticated adaptation. The final 2003 CU-HTK CTS system constructed from some of these models is described and its performance on the DARPA/NIST 2003 Rich Transcription (RT-03) evaluation test set is discussed.

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State-of-the-art large vocabulary continuous speech recognition (LVCSR) systems often combine outputs from multiple subsystems developed at different sites. Cross system adaptation can be used as an alternative to direct hypothesis level combination schemes such as ROVER. In normal cross adaptation it is assumed that useful diversity among systems exists only at acoustic level. However, complimentary features among complex LVCSR systems also manifest themselves in other layers of modelling hierarchy, e.g., subword and word level. It is thus interesting to also cross adapt language models (LM) to capture them. In this paper cross adaptation of multi-level LMs modelling both syllable and word sequences was investigated to improve LVCSR system combination. Significant error rate gains up to 6.7% rel. were obtained over ROVER and acoustic model only cross adaptation when combining 13 Chinese LVCSR subsystems used in the 2010 DARPA GALE evaluation. © 2010 ISCA.

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The development of an expert system, BRIDEX, for the design of prestressed concrete bridges is discussed in this paper. Design of multi-span continuous pre-stressed concrete bridges pose considerable difficulties to designers because of the large number of parameters involved and their complex interactions. The design is often perceived as an iterative process of generation, evaluation and modification of trial designs. It takes years of experience to develop an understanding of the design process. BRIDEX is aimed at providing guidance to the designers by suggesting appropriate range of values for the design parameters. The knowledge within BRIDEX is mainly based on fundamental principles developed by a careful study of the intricacies involved in the design process, while heuristics are used only to supplement this knowledge. The BRIDEX approach ensures that the whole design evolves sequentially as the design proceeds, module after module.