Brunel University London

About: Brunel University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Large Hadron Collider & Population. The organization has 10918 authors who have published 29515 publications receiving 893330 citations. The organization is also known as: Brunel & University of Brunel.

Fault Detection for Markovian Jump Systems With Sensor Saturations and Randomly Varying Nonlinearities

Abstract: This paper addresses the fault detection problem for discrete-time Markovian jump systems with incomplete knowledge of transition probabilities, randomly varying nonlinearities and sensor saturations. For the Markovian mode jumping, the transition probability matrix is allowed to have partially unknown entries, while the cases with completely known or completely unknown transition probabilities are also investigated as two special cases. The randomly varying nonlinearities and the sensor saturations are introduced to reflect the limited capacity of the communication networks resulting from the noisy environment, probabilistic communication failures, measurements of limited amplitudes, etc. Two energy norm indices are used for the fault detection problem in order to account for, respectively, the restraint of disturbance and the sensitivity of faults. The purpose of the problem addressed is to design an optimized fault detection filter such that 1) the fault detection dynamics is stochastically stable; 2) the effect from the exogenous disturbance on the residual is attenuated with respect to a minimized H∞ -norm; and 3) the sensitivity of the residual to the fault is enhanced by means of a maximized H∞-norm. The characterization of the gains of the desired fault detection filters is derived in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite programme method. Finally, a simulation example is employed to show the effectiveness of the fault detection filtering scheme proposed in this paper.

Structural analysis for lignin characteristics in biomass straw

Abstract: Agricultural by-products are the most promising feedstock for the generation of renewable, carbon neutral substitutes for synthetic materials (e.g. biofuel, building materials). The demand for efficient utilisation of lignin biomass has induced detailed analyses of its fundamental chemical structures and development of analysing technologies. This paper reviews the structural analysis techniques for straw lignin together with the morphology of the lignin biomass and the study of the form and structure of organisms and their specific structural features. The review showed that the studies on lignin could be divided into the qualitative and quantitative analyses; different analytical methods could provide significantly different results that are even sometimes not directly comparable. Among many techniques reviewed, the magnetic resonance techniques have proved to be efficient analytical tools for the structural elucidation of these complex biopolymers. Quantitative and qualitative structural analysis of lignin indicated a great potential for industrial crops optimisation due to in-depth microstructure interpretation, and detailed and accurate chemical composition although the composition and structure of straw lignin have been discovered highly complex and varied considerably within and among plants. The structure of lignin has remained one of the most difficult biopolymers to characterise, however recent advances in analytical chemistry and spectroscopy have dramatically improved the understanding of this natural resource, and further value added utilisations are being expected for the lignin and its related biomass.

Towards a tool for the Subjective Assessment of Speech System Interfaces (SASSI)

Abstract: Applications of speech recognition are now widespread, but user-centred evaluation methods are necessary to ensure their success. Objective evaluation techniques are fairly well established, but previous subjective techniques have been unstructured and unproven. This paper reports on the first stage in the development of a questionnaire measure for the Subjective Assessment of Speech System Interfaces (SASSI). The aim of the research programme is to produce a valid, reliable and sensitive measure of users' subjective experiences with speech recognition systems. Such a technique could make an important contribution to theory and practice in the design and evaluation of speech recognition systems according to best human factors practice. A prototype questionnaire was designed, based on established measures for evaluating the usability of other kinds of user interface, and on a review of the research literature into speech system design. This consisted of 50 statements with which respondents rated their level of agreement. The questionnaire was given to users of four different speech applications, and Exploratory Factor Analysis of 214 completed questionnaires was conducted. This suggested the presence of six main factors in users' perceptions of speech systems: System Response Accuracy, Likeability, Cognitive Demand, Annoyance, Habitability and Speed. The six factors have face validity, and a reasonable level of statistical reliability. The findings form a useful theoretical and practical basis for the subjective evaluation of any speech recognition interface. However, further work is recommended, to establish the validity and sensitivity of the approach, before a final tool can be produced which warrants general use.