A sensor based intelligent building assessment model

While building provides shelter for human being, the previous models for assessing the intelligence of a building seldom consider the responses of occupants. In addition, the assessment is usually conducted by an authority organization on a yearly basis, thus can seldom provide timely assistance for facility manager to improve his daily facility maintenance performance. By the extending the law of entropy into the area of intelligent building, this paper demonstrate that both energy consumption and the response of occupants are important when partially assessing the intelligence of a building. This study then develops a sensor based real time building intelligence (BI) assessment model. An experimental case study demonstrates how the model can be implemented. The developed model can address the two demerits of the previous BI assessment model.

Neural network based control in food processing

A number of commonly encountered simple neural network types are discussed, with particular attention being paid to their applicability in automation and control when applied to food processing. In the first instance n-tuple networks are considered, these being particularly useful for high speed production checking operations. Subsequently backpropagation networks are discussed, these being useful both in a more familiar feedback control arrangement and also for such things as recipe prediction.

Remote control systems laboratory

Control systems theory can be a discipline difficult to learn without some laboratory help. With the help of focused laboratories this discipline turns to be very interesting to the students involved. The main problem is that laboratories aren't always available to students, and sometimes, when they are available, aren't big enough to a growing student population. Thus, with computer networks growing so fast, why don't create remote control labs that can be used by a large number of students? Why don't create remote control labs using Internetⓒ Copyright ?2001 IFAC Keywords: Remote Control, Computer Networks, Database, Educational Aids, Laboratory Education, Communication Control Applications.

Prefrontal control of familiarity and recollection in working memory

Left inferior frontal gyrus (IFG) is a critical neural substrate for the resolution of proactive interference (PI) in working memory. We hypothesized that left IFG achieves this by controlling the influence of familiarity- versus recollection-based information about memory probes. Consistent with this idea, we observed evidence for an early (200 msec)-peaking signal corresponding to memory probe familiarity and a late (500 msec)-resolving signal corresponding to full accrual of trial-related contextual ("recollection-based") information. Next, we applied brief trains of repetitive transcranial magnetic stimulation (rTMS) time locked to these mnemonic signals, to left IFG and to a control region. Only early rTMS of left IFG produced a modulation of the false alarm rate for high-PI probes. Additionally, the magnitude of this effect was predicted by individual differences in susceptibility to PI. These results suggest that left IFG-based control may bias the influence of familiarity- and recollection-based signals on recognition decisions.

Body-centric modelling, identification, and acceleration tracking control of a quadrotor UAV

This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

Can wavelets improve the representation of forecast error covariances in variational data assimilation?

Two wavelet-based control variable transform schemes are described and are used to model some important features of forecast error statistics for use in variational data assimilation. The first is a conventional wavelet scheme and the other is an approximation of it. Their ability to capture the position and scale-dependent aspects of covariance structures is tested in a two-dimensional latitude-height context. This is done by comparing the covariance structures implied by the wavelet schemes with those found from the explicit forecast error covariance matrix, and with a non-wavelet- based covariance scheme used currently in an operational assimilation scheme. Qualitatively, the wavelet-based schemes show potential at modeling forecast error statistics well without giving preference to either position or scale-dependent aspects. The degree of spectral representation can be controlled by changing the number of spectral bands in the schemes, and the least number of bands that achieves adequate results is found for the model domain used. Evidence is found of a trade-off between the localization of features in positional and spectral spaces when the number of bands is changed. By examining implied covariance diagnostics, the wavelet-based schemes are found, on the whole, to give results that are closer to diagnostics found from the explicit matrix than from the nonwavelet scheme. Even though the nature of the covariances has the right qualities in spectral space, variances are found to be too low at some wavenumbers and vertical correlation length scales are found to be too long at most scales. The wavelet schemes are found to be good at resolving variations in position and scale-dependent horizontal length scales, although the length scales reproduced are usually too short. The second of the wavelet-based schemes is often found to be better than the first in some important respects, but, unlike the first, it has no exact inverse transform.

An evaluation of the use of Cottonseed cake in the diet of growing pigs

An experiment was conducted to determine the effects of including cottonseed cake in rations for weaned growing pigs. Thirty-two Landrace x Large White pigs, weighing 20-24 kg, were included in four blocks formed on the basis of initial weight within sex in an otherwise completely randomized block design. The pigs were killed when they reached a live weight of 75.0 +/- 2.0 kg and the half careases were analysed into cuts and the weights of the organs were recorded. An estimate of the productivity of the pigs on each diet was calculated. Cottonseed cake reduced the voluntary feed intake (p < 0.001) and live weight gains (p < 0.001) and increased the heart, kidney and liver weights (p < 0.01). The pigs on the soya bean-based control diet took the shortest time to reach slaughter weight. The result was probably in part due to lysine deficiency and in part to the effect of free gossypol. It was found that it is at present cost-effective to include cottonseed cake in pig weaner grower diets up to 300 g/kg in Cameroon.

Muscle hypertrophy driven by myostatin blockade does not require stem/precursor-cell activity

Myostatin, a member of the TGF-beta family, has been identified as a powerful inhibitor of muscle growth. Absence or blockade of myostatin induces massive skeletal muscle hypertrophy that is widely attributed to proliferation of the population of muscle fiber-associated satellite cells that have been identified as the principle source of new muscle tissue during growth and regeneration. Postnatal blockade of myostatin has been proposed as a basis for therapeutic strategies to combat muscle loss in genetic and acquired myopathies. But this approach, according to the accepted mechanism, would raise the threat of premature exhaustion of the pool of satellite cells and eventual failure of muscle regeneration. Here, we show that hypertrophy in the absence of myostatin involves little or no input from satellite cells. Hypertrophic fibers contain no more myonuclei or satellite cells and myostatin had no significant effect on satellite cell proliferation in vitro, while expression of myostatin receptors dropped to the limits of detectability in postnatal satellite cells. Moreover, hypertrophy of dystrophic muscle arising from myostatin blockade was achieved without any apparent enhancement of contribution of myonuclei from satellite cells. These findings contradict the accepted model of myostatin-based control of size of postnatal muscle and reorient fundamental investigations away from the mechanisms that control satellite cell proliferation and toward those that increase myonuclear domain, by modulating synthesis and turnover of structural muscle fiber proteins. It predicts too that any benefits of myostatin blockade in chronic myopathies are unlikely to impose any extra stress on the satellite cells.

Coordinated management of intelligent pervasive spaces

The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises workspaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.

Co-ordinated management of intelligent pervasive spaces

The content of this paper is a snapshot of a current project looking at producing a real-time sensor-based building assessment tool, and a system that personalises work-spaces using multi-agent technology. Both systems derive physical environment information from a wireless sensor network that allows clients to subscribe to real-time sensed data. The principal ideologies behind this project are energy efficiency and well-being of occupants; in the context of leveraging the current state-of-the-art in agent technology, wireless sensor networks and building assessment systems to enable the optimisation and assessment of buildings. Participants of this project are from both industry (construction and research) and academia.

The relative order and inverses of recurrent networks

Differential geometry is used to investigate the structure of neural-network-based control systems. The key aspect is relative order—an invariant property of dynamic systems. Finite relative order allows the specification of a minimal architecture for a recurrent network. Any system with finite relative order has a left inverse. It is shown that a recurrent network with finite relative order has a local inverse that is also a recurrent network with the same weights. The results have implications for the use of recurrent networks in the inverse-model-based control of nonlinear systems.

Causal evidence for frontal involvement in memory target maintenance by posterior brain areas during distracter interference of visual working memory

Dorsolateral prefrontal cortex (DLPFC) is recruited during visual working memory (WM) when relevant information must be maintained in the presence of distracting information. The mechanism by which DLPFC might ensure successful maintenance of the contents of WM is, however, unclear; it might enhance neural maintenance of memory targets or suppress processing of distracters. To adjudicate between these possibilities, we applied time-locked transcranial magnetic stimulation (TMS) during functional MRI, an approach that permits causal assessment of a stimulated brain region's influence on connected brain regions, and evaluated how this influence may change under different task conditions. Participants performed a visual WM task requiring retention of visual stimuli (faces or houses) across a delay during which visual distracters could be present or absent. When distracters were present, they were always from the opposite stimulus category, so that targets and distracters were represented in distinct posterior cortical areas. We then measured whether DLPFC-TMS, administered in the delay at the time point when distracters could appear, would modulate posterior regions representing memory targets or distracters. We found that DLPFC-TMS influenced posterior areas only when distracters were present and, critically, that this influence consisted of increased activity in regions representing the current memory targets. DLPFC-TMS did not affect regions representing current distracters. These results provide a new line of causal evidence for a top-down DLPFC-based control mechanism that promotes successful maintenance of relevant information in WM in the presence of distraction.