133 resultados para Inverse Methodology


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People are now becoming more environmentally aware and as a consequence of this, industries such as the aviation industry are striving to design more environmentally friendly products. To achieve this, the current design methodologies must be modified to ensure these issues are considered from product conception through to disposal. This paper discusses the environmental problems in relation to the aviation industry and highlights some logic for making the change from the traditional Systems Engineering approach to the recent design paradigm known as Value Driven Design. Preliminary studies have been undertaken to aid in the understanding of this methodology and the existing surplus value objective function. The main results from the work demonstrate that surplus value works well bringing disparate issues such as manufacture and green taxes together to aid decision making. Further, to date studies on surplus value have used simple sensitivity analysis, but deeper consideration shows non-linear interactions between some of the variables and further work will be needed to fully account for complex issues such as environmental impact and taxes.

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Analysis of the acoustical functioning of musical instruments invariably involves the estimation of model parameters. The broad aim of this paper is to develop methods for estimation of clarinet reed parameters that are representative of actual playing conditions. This presents various challenges because of the di?culties of measuring the directly relevant variables without interfering with the control of the instrument. An inverse modelling approach is therefore proposed, in which the equations governing the sound generation mechanism of the clarinet
are employed in an optimisation procedure to determine the reed parameters from the mouthpiece pressure and volume ?ow signals. The underlying physical model captures most of the reed dynamics and is simple enough to be used in an inversion process. The optimisation procedure is ?rst tested by applying it to numerically synthesised signals, and then applied to mouthpiece signals acquired during notes blown by a human player. The proposed inverse modelling approach raises the possibility of revealing information about the way in which the embouchure-related reed parameters are controlled by the player, and also facilitates physics-based re-synthesis of clarinet sounds.

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This work describes a novel method of producing multicomponent fertiliser granules using high shear granulation. The granulation process was optimised using the response surface methodology technique. The variables used in the optimisation process include granulation time, batch size, impeller speed and binder concentration. Granulation time, binder concentration and interaction between the batch size and granulation time were found to be the main factors affecting the granule median size. The product yield is mainly influenced by granulation time and binder concentration. The interaction between the impeller speed and batch size also have a significant influence on the product yield. Product yield (2-4 mm) of approximately 60% could be obtained with high sphericity and granule strength (> 0.5 MPa). A low product recycle ratio of about 2:3 can be obtained at the optimised process conditions, compared to typical recycle rations of 6:1 which are obtained in typical fertiliser plants. © 2012 Elsevier B.V. All rights reserved.

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In this paper, we present a methodology for implementing a complete Digital Signal Processing (DSP) system onto a heterogeneous network including Field Programmable Gate Arrays (FPGAs) automatically. The methodology aims to allow design refinement and real time verification at the system level. The DSP application is constructed in the form of a Data Flow Graph (DFG) which provides an entry point to the methodology. The netlist for parts that are mapped onto the FPGA(s) together with the corresponding software and hardware Application Protocol Interface (API) are also generated. Using a set of case studies, we demonstrate that the design and development time can be significantly reduced using the methodology developed.

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Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

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Q methodology was used to enable the identification of discourses among stakeholders to the environmental and resource dimensions of sustainability policies and to gain an understanding of the usefulness of Q methodology in informing sustainability policy development. The application of Q methodology has been useful in identifying shared discourses between different stakeholder groups, and providing insights into how stakeholders frame or understand policy issues; and recommendations are made for ongoing research priorities. These insights, in turn, informed the choice of scenarios for an in parallel process of policy evaluation using Ecological and Carbon Footprinting.

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Protein interactions play key roles throughout all subcellular compartments. In the present paper, we report the visualization of protein interactions throughout living mammalian cells using two oligomerizing MV (measles virus) transmembrane glycoproteins, the H (haemagglutinin) and the F (fusion) glycoproteins, which mediate MV entry into permissive cells. BiFC (bimolecular fluorescence complementation) has been used to examine the dimerization of these viral glycoproteins. The H glycoprotein is a type II membrane-receptor-binding homodimeric glycoprotein and the F glycoprotein is a type I disulfide-linked membrane glycoprotein which homotrimerizes. Together they co-operate to allow the enveloped virus to enter a cell by fusing the viral and cellular membranes. We generated a pair of chimaeric H glycoproteins linked to complementary fragments of EGFP (enhanced green fluorescent protein)--haptoEGFPs--which, on association, generate fluorescence. Homodimerization of H glycoproteins specifically drives this association, leading to the generation of a fluorescent signal in the ER (endoplasmic reticulum), the Golgi and at the plasma membrane. Similarly, the generation of a pair of corresponding F glycoprotein-haptoEGFP chimaeras also produced a comparable fluorescent signal. Co-expression of H and F glycoprotein chimaeras linked to complementary haptoEGFPs led to the formation of fluorescent fusion complexes at the cell surface which retained their biological activity as evidenced by cell-to-cell fusion.

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A systematic design methodology is described for the rapid derivation of VLSI architectures for implementing high performance recursive digital filters, particularly ones based on most significant digit (msd) first arithmetic. The method has been derived by undertaking theoretical investigations of msd first multiply-accumulate algorithms and by deriving important relationships governing the dependencies between circuit latency, levels of pipe-lining and the range and number representations of filter operands. The techniques described are general and can be applied to both bit parallel and bit serial circuits, including those based on on-line arithmetic. The method is illustrated by applying it to the design of a number of highly pipelined bit parallel IIR and wave digital filter circuits. It is shown that established architectures, which were previously designed using heuristic techniques, can be derived directly from the equations described.