Real-time application of a constrained predictive controller based on dynamic neural networks with feedback linearization

This paper describes an experimental application of constrained predictive control and feedback linearisation based on dynamic neural networks. It also verifies experimentally a method for handling input constraints, which are transformed by the feedback linearisation mappings. A performance comparison with a PID controller is also provided. The experimental system consists of a laboratory based single link manipulator arm, which is controlled in real time using MATLAB/SIMULINK together with data acquisition equipment.

Predictive computed-torque control of a PUMA 560 manipulator robot

This paper describes the integration of constrained predictive control and computed-torque control, and its application on a six degree-of-freedom PUMA 560 manipulator arm. The real-time implementation was based on SIMULINK, with the predictive controller and the computed-torque control law implemented in the C programming language. The constrained predictive controller solved a quadratic programming problem at every sampling interval, which was as short as 10 ms, using a prediction horizon of 150 steps and an 18th order state space model.

Public leisure provision under Compulsory Competitive Tendering: the maintenance of ideological dominance?

Although much has been written about the effect on services of public sector restructuring, little is yet available on public leisure provision. This omission is addressed by considering how the delivery of public leisure services in Britain has been affected by the imposition of Compulsory Competitive Tendering (CCT). In particular, it focuses on the changing relationship between the central and local levels of government recognising, on the part of local government, a continuum of structural responses to central initiatives which have, in some cases, conspired to reduce the impact of CCT on public leisure provision. The paper concludes that although attempts have been made to protect local services, the outcome of the CCT process has been the regeneration of public leisure provision away from its service roots, but within an enduring ideological paradigm of conservative professionalism.

A Real-time, Predictive Architecture for Distributed Virtual Reality

User interaction within a virtual environment may take various forms: a teleconferencing application will require users to speak to each other (Geak, 1993), with computer supported co-operative working; an Engineer may wish to pass an object to another user for examination; in a battle field simulation (McDonough, 1992), users might exchange fire. In all cases it is necessary for the actions of one user to be presented to the others sufficiently quickly to allow realistic interaction. In this paper we take a fresh look at the approach of virtual reality operating systems by tackling the underlying issues of creating real-time multi-user environments.

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.

Phylogenies reveal predictive power of traditional medicine in bioprospecting

There is controversy about whether traditional medicine can guide drug discovery, and investment in ethnobotanically led research has fluctuated. One view is that traditionally used plants are not necessarily efficacious and there are no robust methods for distinguishing the ones that are most likely to be bioactive when selecting species for further testing. Here, we reconstruct a genus-level molecular phylogeny representing the 20,000 species found in the floras of three disparate biodiversity hotspots: Nepal, New Zealand and the Cape of South Africa. Borrowing phylogenetic methods from community ecology, we reveal significant clustering of the 1,500 traditionally used species, and provide a direct measure of the relatedness of the three medicinal floras. We demonstrate shared phylogenetic patterns across the floras: related plants from these regions are used to treat medical conditions in the same therapeutic areas. This strongly suggests independent discovery of plant efficacy, an interpretation corroborated by the presence of a significantly greater proportion of known bioactive species in these plant groups than in a random sample. Phylogenetic cross-cultural comparison can focus screening efforts on a subset of traditionally used plants that are richer in bioactive compounds, and could revitalise the use of traditional knowledge in bioprospecting.

From ensemble forecasts to predictive distribution functions

The translation of an ensemble of model runs into a probability distribution is a common task in model-based prediction. Common methods for such ensemble interpretations proceed as if verification and ensemble were draws from the same underlying distribution, an assumption not viable for most, if any, real world ensembles. An alternative is to consider an ensemble as merely a source of information rather than the possible scenarios of reality. This approach, which looks for maps between ensembles and probabilistic distributions, is investigated and extended. Common methods are revisited, and an improvement to standard kernel dressing, called ‘affine kernel dressing’ (AKD), is introduced. AKD assumes an affine mapping between ensemble and verification, typically not acting on individual ensemble members but on the entire ensemble as a whole, the parameters of this mapping are determined in parallel with the other dressing parameters, including a weight assigned to the unconditioned (climatological) distribution. These amendments to standard kernel dressing, albeit simple, can improve performance significantly and are shown to be appropriate for both overdispersive and underdispersive ensembles, unlike standard kernel dressing which exacerbates over dispersion. Studies are presented using operational numerical weather predictions for two locations and data from the Lorenz63 system, demonstrating both effectiveness given operational constraints and statistical significance given a large sample.

Intermittently-visual tracking experiments reveal the roles of error-correction and predictive mechanisms in the human visual-motor control system

Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

Response to zinc deficiency of two rice lines with contrasting tolerance is determined by root growth maintenance and organic acid exudation rates, and not by zinc-transporter activity

Zinc (Zn)-deficient soils constrain rice (Oryza sativa) production and cause Zn malnutrition. The identification of Zn-deficiency-tolerant rice lines indicates that breeding might overcome these constraints. Here, we seek to identify processes underlying Zn-deficiency tolerance in rice at the physiological and transcriptional levels. A Zn-deficiency-tolerant line RIL46 acquires Zn more efficiently and produces more biomass than its nontolerant maternal line (IR74) at low Zn(ext) under field conditions. We tested if this was the result of increased expression of Zn(2+) transporters; increased root exudation of deoxymugineic acid (DMA) or low-molecular-weight organic acids (LMWOAs); and/or increased root production. Experiments were performed in field and controlled environment conditions. There was little genotypic variation in transcript abundance of Zn-responsive root Zn(2+)-transporters between the RIL46 and IR74. However, root exudation of DMA and LMWOA was greater in RIL46, coinciding with increased root expression of putative ligand-efflux genes. Adventitious root production was maintained in RIL46 at low Zn(ext), correlating with altered expression of root-specific auxin-responsive genes. Zinc-deficiency tolerance in RIL46 is most likely the result of maintenance of root growth, increased efflux of Zn ligands, and increased uptake of Zn-ligand complexes at low Zn(ext); these traits are potential breeding targets.

Maintenance of the African easterly jet

The maintenance of the African easterly jet (AEJ) has been examined using a zonally symmetric general circulation model with simple parametrizations. It is shown that the AEJ is maintained in association with two diabatically forced meridional circulations: one associated with surface fluxes and dry convection in the Saharan heat-low region and one associated with deep moist convection in the intertropical convergence zone equatorward of this. the heat-low heating, which reaches the height of the AEJ around 700 mb, is particularly important in maintaining the AEJ and its associated meridional gradients in potential vorticity. It is concluded that the mean observed AEJ results from a combination of the diabatically forced meridional circulations which maintain it and easterly waves which weaken it.

Interpretation of ageostrophic winds and implications for jet stream maintenance

The use of ageostrophic flow to infer the presence of vertical circulations in the entrances and exits of the climatological jet streams is questioned. Problems of interpretation arise because of the use of different definitions of geostrophy in theoretical studies and in analyses of atmospheric data. The nature and role of the ageostrophic flow based on constant and variable Coriolis parameter definitions of geostrophy vary. In the latter the geostrophic divergence cannot be neglected, so the vertical motion is not associated solely with the ageostrophic flow. Evidence is presented suggesting that ageostrophic flow in the climatological jet streams is primarily determined by the kinematic requirements of wave retrogression rather than by a forcing process. These requirements are largely met by the rotational flow, with the divergent circulations present being geostrophically forced, and so playing a secondary, restoring role.

The mirror neuron system as revealed through neonatal imitation: presence from birth, predictive power, and evidence of plasticity

There is strong evidence that neonates imitate previously unseen behaviors. These behaviors are predominantly used in social interactions, demonstrating neonates’ ability and motivation to engage with others. Research on neonatal imitation can provide a wealth of information about the early mirror neuron system (MNS): namely, its functional characteristics, its plasticity from birth, and its relation to skills later in development. Though numerous studies document the existence of neonatal imitation in the laboratory, little is known about its natural occurrence during parent-infant interactions and its plasticity as a consequence of experience. We review these critical aspects of imitation, which we argue are necessary for understanding the early action-perception system. We address common criticisms and misunderstandings about neonatal imitation and discuss methodological differences among studies. Recent work reveals that individual differences in neonatal imitation positively correlate with later social, cognitive, and motor development. We propose that such variation in neonatal imitation could reflect important individual differences of the MNS. Although postnatal experience is not necessary for imitation, we present evidence that neonatal imitation is influenced by experience in the first week of life.

Humans use predictive kinematic models to calibrate visual cues to three-dimensional surface slant

When the sensory consequences of an action are systematically altered our brain can recalibrate the mappings between sensory cues and properties of our environment. This recalibration can be driven by both cue conflicts and altered sensory statistics, but neither mechanism offers a way for cues to be calibrated so they provide accurate information about the world, as sensory cues carry no information as to their own accuracy. Here, we explored whether sensory predictions based on internal physical models could be used to accurately calibrate visual cues to 3D surface slant. Human observers played a 3D kinematic game in which they adjusted the slant of a surface so that a moving ball would bounce off the surface and through a target hoop. In one group, the ball’s bounce was manipulated so that the surface behaved as if it had a different slant to that signaled by visual cues. With experience of this altered bounce, observers recalibrated their perception of slant so that it was more consistent with the assumed laws of kinematics and physical behavior of the surface. In another group, making the ball spin in a way that could physically explain its altered bounce eliminated this pattern of recalibration. Importantly, both groups adjusted their behavior in the kinematic game in the same way, experienced the same set of slants and were not presented with low-level cue conflicts that could drive the recalibration. We conclude that observers use predictive kinematic models to accurately calibrate visual cues to 3D properties of world.

Towards cost-sensitive adaptation: when is it worth updating your predictive model?

Our digital universe is rapidly expanding,more and more daily activities are digitally recorded, data arrives in streams, it needs to be analyzed in real time and may evolve over time. In the last decade many adaptive learning algorithms and prediction systems, which can automatically update themselves with the new incoming data, have been developed. The majority of those algorithms focus on improving the predictive performance and assume that model update is always desired as soon as possible and as frequently as possible. In this study we consider potential model update as an investment decision, which, as in the financial markets, should be taken only if a certain return on investment is expected. We introduce and motivate a new research problem for data streams ? cost-sensitive adaptation. We propose a reference framework for analyzing adaptation strategies in terms of costs and benefits. Our framework allows to characterize and decompose the costs of model updates, and to asses and interpret the gains in performance due to model adaptation for a given learning algorithm on a given prediction task. Our proof-of-concept experiment demonstrates how the framework can aid in analyzing and managing adaptation decisions in the chemical industry.

Case study on the maintenance of a construction monitoring using USN-based data acquisition

In recent years, there has been an increasing interest in the adoption of emerging ubiquitous sensor network (USN) technologies for instrumentation within a variety of sustainability systems. USN is emerging as a sensing paradigm that is being newly considered by the sustainability management field as an alternative to traditional tethered monitoring systems. Researchers have been discovering that USN is an exciting technology that should not be viewed simply as a substitute for traditional tethered monitoring systems. In this study, we investigate how a movement monitoring measurement system of a complex building is developed as a research environment for USN and related decision-supportive technologies. To address the apparent danger of building movement, agent-mediated communication concepts have been designed to autonomously manage large volumes of exchanged information. In this study, we additionally detail the design of the proposed system, including its principles, data processing algorithms, system architecture, and user interface specifics. Results of the test and case study demonstrate the effectiveness of the USN-based data acquisition system for real-time monitoring of movement operations.