Development of raised access floor panel by optimisation techniques

Raised access floor panels currently have a chipboard core and are encapsulated within thin layer of galvanised steel. Two key problems with these raised access floor panels are that they are heavy because of the chipboard and expensive, as the cost of steel has increased significantly over the past few years. The consequence of the raised access floor panel’s mass is that they are difficult to handle, they are expensive to transport and they add considerably to the load on a structures foundation. Glass fibre filled epoxy of floor panels were designed and optimised to achieve lighter weights without compromising their strength using Altair Hypermesh software. A material weight reduction of the glass fibre filled epoxy floor panel was achieved by optimised design of the panes using an evolutionary structural optimisation (ESO) method and the introduction of panel ribs. The lighter weight of new raised floors panel would have a significant impact on the loadings of buildings foundation and allow architects to reduce the carbon footprint of a building resulting in reduced construction costs. In addition, a reduction in the weight of the new raised access floor panels would reduce the transportation costs of the panels

Experiences Migrating Microcosm Learning Materials

Microcosm was an open hypertext system that evolved in the early 1990s, before the advent of the Web. Apart from its success as a research platform it was widely used for presenting interactive educational materials. Since the commercial version of the product ceased to be supported it became necessary for users to migrate their educational materials, generally to the Web. However, the SToMP consortium chose to implement their own environment copying parts of the functionality of Microcosm in order to achieve their educational objectives. This paper examines the motivations of this work in order to understand whether there were features that were available in Microcosm that were not replicated in current Web based solutions

An approximation method for the solution of nonlinear integral equations

A Chebyshev collocation method has been presented to solve nonlinear integral equations in terms of Chebyshev polynomials. This method transforms the integral equation to a matrix equation which corresponds to a system of nonlinear algebraic equations with unknown Chebyshev coefficients. Finally, some examples are presented to illustrate the method and results discussed. (c) 2005 Elsevier Inc. All rights reserved

Relationships between human auditory cortical structure and function

The human auditory cortex comprises multiple areas, largely distributed across the supratemporal plane, but the precise number and configuration of auditory areas and their functional significance have not yet been clearly established. In this paper, we discuss recent research concerning architectonic and functional organisation within the human auditory cortex, as well as architectonic and neurophysiological studies in non-human species, which can provide a broad conceptual framework for interpreting functional specialisation in humans. We review the pattern in human auditory cortex of the functional responses to various acoustic cues, such as frequency, pitch, sound level, temporal variation, motion and spatial location, and we discuss their correspondence to what is known about the organisation of the auditory cortex in other primates. There is some neuroimaging evidence of multiple tonotopically organised fields in humans and of functional specialisations of the fields in the processing of different sound features. It is thought that the primary area, on Heschl's gyrus, may have a larger involvement in processing basic sound features, such as frequency and level, and that posterior non-primary areas on the planum temporale may play a larger role in processing more spectrotemporally complex sounds. Ways in which current knowledge of auditory cortical organisation and different data analysis approaches may benefit future functional neuroimaging studies which seek to link auditory cortical structure and function are discussed

Nucleus accumbens core lesions retard instrumental learning and performance with delayed reinforcement in the rat.

BACKGROUND: Delays between actions and their outcomes severely hinder reinforcement learning systems, but little is known of the neural mechanism by which animals overcome this problem and bridge such delays. The nucleus accumbens core (AcbC), part of the ventral striatum, is required for normal preference for a large, delayed reward over a small, immediate reward (self-controlled choice) in rats, but the reason for this is unclear. We investigated the role of the AcbC in learning a free-operant instrumental response using delayed reinforcement, performance of a previously-learned response for delayed reinforcement, and assessment of the relative magnitudes of two different rewards. RESULTS: Groups of rats with excitotoxic or sham lesions of the AcbC acquired an instrumental response with different delays (0, 10, or 20 s) between the lever-press response and reinforcer delivery. A second (inactive) lever was also present, but responding on it was never reinforced. As expected, the delays retarded learning in normal rats. AcbC lesions did not hinder learning in the absence of delays, but AcbC-lesioned rats were impaired in learning when there was a delay, relative to sham-operated controls. All groups eventually acquired the response and discriminated the active lever from the inactive lever to some degree. Rats were subsequently trained to discriminate reinforcers of different magnitudes. AcbC-lesioned rats were more sensitive to differences in reinforcer magnitude than sham-operated controls, suggesting that the deficit in self-controlled choice previously observed in such rats was a consequence of reduced preference for delayed rewards relative to immediate rewards, not of reduced preference for large rewards relative to small rewards. AcbC lesions also impaired the performance of a previously-learned instrumental response in a delay-dependent fashion. CONCLUSIONS: These results demonstrate that the AcbC contributes to instrumental learning and performance by bridging delays between subjects' actions and the ensuing outcomes that reinforce behaviour

Amplitude and frequency-modulated stimuli activate common regions of human auditory cortex

Hall et al. (Hall et al., 2002, Cerebral Cortex 12:140–149) recently showed that pulsed frequency-modulated tones generate considerably higher activation than their unmodulated counterparts in non-primary auditory regions immediately posterior and lateral to Heschl’s gyrus (HG). Here, we use fMRI to explore the type of modulation necessary to evoke such differential activation. Carrier signals were a single tone and a harmonic-complex tone, with a 300 Hz fundamental, that were modulated at a rate of 5 Hz either in frequency, or in amplitude, to create six stimulus conditions (unmodulated, FM, AM). Relative to the silent baseline, the modulated tones, in particular, activated widespread regions of the auditory cortex bilaterally along the supra-temporal plane. When compared with the unmodulated tones, both AM and FM tones generated significantly greater activation in lateral HG and the planum temporale, replicating the previous findings. These activation patterns were largely overlapping, indicating a common sensitivity to both AM and FM. Direct comparisons between AM and FM revealed a higher magnitude of activation in response to the variation in amplitude than in frequency, plus a small part of the posterolateral region in the right hemisphere whose response was specifically AM-, and not FM-, dependent. The dominant pattern of activation was that of co-localized activation by AM and FM, which is consistent with a common neural code for AM and FM within these brain regions

Matrix formulation of fuzzy rule-based systems

In this paper, a matrix formulation of fuzzy rule based systems is introduced. A gradient descent training algorithm for the determination of the unknown parameters can also be expressed in a matrix form for various adaptive fuzzy networks. When converting a rule-based system to the proposed matrix formulation, only three sets of linear/nonlinear equations are required instead of set of rules and an inference mechanism. There are a number of advantages which the matrix formulation has compared with the linguistic approach. Firstly, it obviates the differences among the various architectures; and secondly, it is much easier to organize data in the implementation or simulation of the fuzzy system. The formulation will be illustrated by a number of examples

A new approach to adaptive fuzzy control: the controller output error method

The controller output error method (COEM) is introduced and applied to the design of adaptive fuzzy control systems. The method employs a gradient descent algorithm to minimize a cost function which is based on the error at the controller output. This contrasts with more conventional methods which use the error at the plant output. The cost function is minimized by adapting some or all of the parameters of the fuzzy controller. The proposed adaptive fuzzy controller is applied to the adaptive control of a nonlinear plant and is shown to be capable of providing good overall system performance

Identifying Biomagnetic Sources in the Brain by the Maximum Entropy Approach

Magnetoencephalographic (MEG) measurements record magnetic fields generated from neurons while information is being processed in the brain. The inverse problem of identifying sources of biomagnetic fields and deducing their intensities from MEG measurements is ill-posed when the number of field detectors is far less than the number of sources. This problem is less severe if there is already a reasonable prior knowledge in the form of a distribution in the intensity of source activation. In this case the problem of identifying and deducing source intensities may be transformed to one of using the MEG data to update a prior distribution to a posterior distribution. Here we report on some work done using the maximum entropy method (ME) as an updating tool. Specifically, we propose an implementation of the ME method in cases when the prior contain almost no knowledge of source activation. Two examples are studied, in which part of motor cortex is activated with uniform and varying intensities, respectively.Comment: 8 pages, 8 figures. Presented at 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, San Jose, CA, USA Aug 7-12, 200