976 resultados para HIERARCHICAL CONTROL


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A exhibition of sculptural assemblages that continue my exploration of self-portraiture and the sculptural object. The work specifically extends the formal vocabulary of my studio to incorporate smaller composite arrangements with an emphasis on the sculptural support. Small objects that are either modelled or cast from life are assembled into four tableaux that respond to the object-relations that arise through the production process. The resulting exhibiton thus acts a meditation on the ontology of art practice, conceived as a topology of objects.

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Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

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Purpose: Young adults regularly experience restricted sleep due to a range of social, educational and vocational commitments. Evidence suggests that extended periods of sleep deprivation negatively impact affective and inhibitory control mechanisms leading to behavioural consequences such as increased emotional reactivity and impulsive behaviour. It is less clear whether acute periods of restricted sleep produce the same behavioural consequences. Methods: Nineteen young adults (m = 8, f = 12) with habitual late bed-time (after 22:30 h) and wake-time (after 06:30 h) completed a range of objective and subjective measures assessing sleepiness (Psychomotor Vigilance Task, Karolinska Sleepiness Scale), inhibitory control (Emotional Go/No-go Task and a Balloon Analog Risk Task) and affect (Positive and Negative Affective Schedule). Testing was counterbalanced across participants, and occurred on two occasions once following restricted sleep and once following habitual sleep one week apart. Results: Compared to habitual sleep, sleep restriction produced significantly slower performance on the Psychomotor Vigilance Task, and higher subjective ratings of sleepiness on the Karolinska Sleepiness Scale. Sleep restriction also caused a significant decrease in positive affect, but no change in negative affect on the Affective Schedule. Inhibitory control efficiency was significantly differentiated, with participants showing an increase in risk taking on the Balloon Analog Risk Task, but there was no evidence of increased reactivity to negative stimuli on the Emotional Go/No-go task. Conclusions: Results suggest that even acute periods of sleep loss may cause deficits in affective experiences and increase impulsive and potentially high risk behaviour in young adults.

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We present a novel method for improving hierarchical speaker clustering in the tasks of speaker diarization and speaker linking. In hierarchical clustering, a tree can be formed that demonstrates various levels of clustering. We propose a ratio that expresses the impact of each cluster on the formation of this tree and use this to rescale cluster scores. This provides score normalisation based on the impact of each cluster. We use a state-of-the-art speaker diarization and linking system across the SAIVT-BNEWS corpus to show that our proposed impact ratio can provide a relative improvement of 16% in diarization error rate (DER).

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Hypsipyla grandella and Hypsipyla robusta are serious pests of species of the subfamily Swietenioideae of the family Meliaceae in virtually every moist tropical region of the world. An international workshop reviewed the ecology and control of Hypsipyla shoot borers of Meliaceae, identified promising control methods, and set priorities for future research. The conclusions of the workshop are presented with specific recommendations for research in aspects of the taxonomy, biology, and ecology of Hypsipyla, and pest management options that use host plant resistance and chemical, biological, and silvicultural control

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Published information on the incidence of pathogens in the field and laboratory infections of Hypsipyla spp. with entomopathogens is reviewed. In addition, some preliminary results of field collections from Ghana and Costa Rica are presented. Fungal pathogens from the Deuteromycetes have been isolated from both H. robusta Moore and H. grandella Zeller. Mermithid nematodes, Hexamermis spp., have been frequently isolated from larvae in the field and incidence of infection with these pathogens can reach significant levels. Microsporidia have been found in cadavers of larvae collected in the field but none have been identified so far. A number of pathogens of other Lepidoptera have been shown to be infectious to H. grandella , including Bacillus thuringiensis , Deuteromycete fungi and a nucleopolyhedrovirus (NPV) from Autographa californica . Hypsipyla spp. are difficult targets for microbial control, since the larvae are cryptic, occur at low density and occur sporadically. In addition, there is a low damage threshold, the plant is susceptible for a number of years and the susceptible part of the plant will rapidly outgrow any surface application. Key features of the biology of entomopathogens with relevance to the control of low density and cryptic pests are discussed. In the light of this experience, we discuss strategies to improve the possibilities of microbial control of this pest and suggest areas for research.

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Hypsipyla grandella (Zeller) is the most important insect pest of the Meliaceae in the Neotropics. This paper reviews the information on H. grandella parasitoids in Latin America and the Caribbean. Preliminary data on the parasitoid complex in Turrialba, Costa Rica, are presented, where apparent parasitisation of H. grandella during 1995–1996 reached 36%. The lowest level of parasitisation occurred during the dry season. The parasitoid Apanteles sp. (= Hypomicrogaster hypsipylae de Santis?) (Hymenoptera: Braconidae) was the most abundant larval parasitoid with a mean of 22 parasitoids per parasitised larva and a sex ratio of 3:1 females to males. Brachymeria conica Ashmead (Hymenoptera: Chalcididae) was found parasitising pupae, but at low frequency

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Synthesis of high quality boron carbide (B4C) powder is achieved by carbothermal reduction of boron oxide (B2O3) from a condensed boric acid (H3BO3) / polyvinyl acetate (PVAc) product. Precursor solutions are prepared via polymerisation of vinyl acetate (VA) in methanol in the presence of dissolved H3BO3. With excess VA monomer being removed during evaporation of the solvent, the polymerisation time is then used to manage availability of carbon for reaction.

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A field oriented control (FOC) algorithm is simulated and implemented for use with a permanent magnet synchronous motor (PMSM). Rotor position is sensed using Hall effect switches on the stator because other hardware position sensors attached to the rotor may not be desirable or cost effective for certain applications. This places a limit on the resolution of position sensing – only a few Hall effect switches can be placed. In this simulation, three sensors are used and the position information is obtained at higher resolution by estimating it from the rotor dynamics, as shown in literature previously. This study compares the performance of the method with an incremental encoder using simulations. The FOC algorithm is implemented using Digital Motor Control (DMC) and IQ Texas Instruments libraries from a Simulink toolbox called Embedded Coder, and downloaded into a TI microcontroller (TMS320F28335) known as the Piccolo via Code Composer Studio (CCS).

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Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.

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Building information models have created a paradigm shift in how buildings are built and managed by providing a dynamic repository for building data that is useful in many new operational scenarios. This change has also created an opportunity to use building information models as an integral part of security operations and especially as a tool to facilitate fine-grained access control to building spaces in smart buildings and critical infrastructure environments. In this paper, we identify the requirements for a security policy model for such an access control system and discuss why the existing policy models are not suitable for this application. We propose a new policy language extension to XACML, with BIM specific data types and functions based on the IFC specification, which we call BIM-XACML.

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Building information models are increasingly being utilised for facility management of large facilities such as critical infrastructures. In such environments, it is valuable to utilise the vast amount of data contained within the building information models to improve access control administration. The use of building information models in access control scenarios can provide 3D visualisation of buildings as well as many other advantages such as automation of essential tasks including path finding, consistency detection, and accessibility verification. However, there is no mathematical model for building information models that can be used to describe and compute these functions. In this paper, we show how graph theory can be utilised as a representation language of building information models and the proposed security related functions. This graph-theoretic representation allows for mathematically representing building information models and performing computations using these functions.