976 resultados para HIERARCHICAL CONTROL
Resumo:
In this study we set out to dissociate the developmental time course of automatic symbolic number processing and cognitive control functions in grade 1-3 British primary school children. Event-related potential (ERP) and behavioral data were collected in a physical size discrimination numerical Stroop task. Task-irrelevant numerical information was processed automatically already in grade 1. Weakening interference and strengthening facilitation indicated the parallel development of general cognitive control and automatic number processing. Relationships among ERP and behavioral effects suggest that control functions play a larger role in younger children and that automaticity of number processing increases from grade 1 to 3.
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Networked control systems (NCSs) offer many advantages over conventional control; however, they also demonstrate challenging problems such as network-induced delay and packet losses. This paper proposes an approach of predictive compensation for simultaneous network-induced delays and packet losses. Different from the majority of existing NCS control methods, the proposed approach addresses co-design of both network and controller. It also alleviates the requirements of precise process models and full understanding of NCS network dynamics. For a series of possible sensor-to-actuator delays, the controller computes a series of corresponding redundant control values. Then, it sends out those control values in a single packet to the actuator. Once receiving the control packet, the actuator measures the actual sensor-to-actuator delay and computes the control signals from the control packet. When packet dropout occurs, the actuator utilizes past control packets to generate an appropriate control signal. The effectiveness of the approach is demonstrated through examples.
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Is it possible to control identities using performance management systems (PMSs)? This paper explores the theoretical fusion of management accounting and identity studies, providing a synthesised view of control, PMSs and identification processes. It argues that the effective use of PMSs generates a range of obtrusive mechanistic and unobtrusive organic controls that mediate identification processes to achieve a high level of identity congruency between individuals and collectives—groups and organisations. This paper contends that mechanistic control of PMSs provides sensebreaking effects and also creates structural conditions for sensegiving in top-down identification processes. These processes encourage individuals to continue the bottom-up processes of sensemaking, enacting identity and constructing identity narratives. Over time, PMS activities and conversations periodically mediate several episode(s) of identification to connect past, current and future identities. To explore this relationship, the dual locus of control—collectives and individuals—is emphasised to explicate their interplay. This multidisciplinary approach contributes to explaining the multidirectional effects of PMSs in obtrusive as well as unobtrusive ways, in order to control the nature of collectives and individuals in organisations.
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Is it possible to control identities using performance management systems (PMSs)? This paper explores the theoretical fusion of management accounting and identity studies, providing a synthesised view of control, PMSs and identification processes. It argues that the effective use of PMSs generates a range of obtrusive mechanistic and unobtrusive organic controls that mediate identification processes to achieve a high level of identity congruency between individuals and collectives—groups and organisations. This paper contends that mechanistic control of PMSs provides sensebreaking effects and also creates structural conditions for sensegiving in top-down identification processes. These processes encourage individuals to continue the bottom-up processes of sensemaking, enacting identity and constructing identity narratives. Over time, PMS activities and conversations periodically mediate several episode(s) of identification to connect past, current and future identities. To explore this relationship, the dual locus of control—collectives and individuals—is emphasised to explicate their interplay. This multidisciplinary approach contributes to explaining the multidirectional effects of PMSs in obtrusive as well as unobtrusive ways, in order to control the nature of collectives and individuals in organisations.
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The compressed gas industry and government agencies worldwide utilize "adiabatic compression" testing for qualifying high-pressure valves, regulators, and other related flow control equipment for gaseous oxygen service. This test methodology is known by various terms including adiabatic compression testing, gaseous fluid impact testing, pneumatic impact testing, and BAM testing as the most common terms. The test methodology will be described in greater detail throughout this document but in summary it consists of pressurizing a test article (valve, regulator, etc.) with gaseous oxygen within 15 to 20 milliseconds (ms). Because the driven gas1 and the driving gas2 are rapidly compressed to the final test pressure at the inlet of the test article, they are rapidly heated by the sudden increase in pressure to sufficient temperatures (thermal energies) to sometimes result in ignition of the nonmetallic materials (seals and seats) used within the test article. In general, the more rapid the compression process the more "adiabatic" the pressure surge is presumed to be and the more like an isentropic process the pressure surge has been argued to simulate. Generally speaking, adiabatic compression is widely considered the most efficient ignition mechanism for directly kindling a nonmetallic material in gaseous oxygen and has been implicated in many fire investigations. Because of the ease of ignition of many nonmetallic materials by this heating mechanism, many industry standards prescribe this testing. However, the results between various laboratories conducting the testing have not always been consistent. Research into the test method indicated that the thermal profile achieved (i.e., temperature/time history of the gas) during adiabatic compression testing as required by the prevailing industry standards has not been fully modeled or empirically verified, although attempts have been made. This research evaluated the following questions: 1) Can the rapid compression process required by the industry standards be thermodynamically and fluid dynamically modeled so that predictions of the thermal profiles be made, 2) Can the thermal profiles produced by the rapid compression process be measured in order to validate the thermodynamic and fluid dynamic models; and, estimate the severity of the test, and, 3) Can controlling parameters be recommended so that new guidelines may be established for the industry standards to resolve inconsistencies between various test laboratories conducting tests according to the present standards?
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Modern technology now has the ability to generate large datasets over space and time. Such data typically exhibit high autocorrelations over all dimensions. The field trial data motivating the methods of this paper were collected to examine the behaviour of traditional cropping and to determine a cropping system which could maximise water use for grain production while minimising leakage below the crop root zone. They consist of moisture measurements made at 15 depths across 3 rows and 18 columns, in the lattice framework of an agricultural field. Bayesian conditional autoregressive (CAR) models are used to account for local site correlations. Conditional autoregressive models have not been widely used in analyses of agricultural data. This paper serves to illustrate the usefulness of these models in this field, along with the ease of implementation in WinBUGS, a freely available software package. The innovation is the fitting of separate conditional autoregressive models for each depth layer, the ‘layered CAR model’, while simultaneously estimating depth profile functions for each site treatment. Modelling interest also lay in how best to model the treatment effect depth profiles, and in the choice of neighbourhood structure for the spatial autocorrelation model. The favoured model fitted the treatment effects as splines over depth, and treated depth, the basis for the regression model, as measured with error, while fitting CAR neighbourhood models by depth layer. It is hierarchical, with separate onditional autoregressive spatial variance components at each depth, and the fixed terms which involve an errors-in-measurement model treat depth errors as interval-censored measurement error. The Bayesian framework permits transparent specification and easy comparison of the various complex models compared.
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The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.
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We present an iterative hierarchical algorithm for multi-view stereo. The algorithm attempts to utilise as much contextual information as is available to compute highly accurate and robust depth maps. There are three novel aspects to the approach: 1) firstly we incrementally improve the depth fidelity as the algorithm progresses through the image pyramid; 2) secondly we show how to incorporate visual hull information (when available) to constrain depth searches; and 3) we show how to simultaneously enforce the consistency of the depth-map by continual comparison with neighbouring depth-maps. We show that this approach produces highly accurate depth-maps and, since it is essentially a local method, is both extremely fast and simple to implement.
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Bauxite refinery residues (red mud) are derived from the Bayer process by the digestion of crushed bauxite in concentrated sodium hydroxide at elevated temperatures and pressures. This slurry residue, if untreated, is unsuitable for discharge directly into the environment and is usually stored in tailing dams. The liquid portion has the potential for discharge, but requires pre-treatment before this can occur. The seawater neutralisation treatment facilitates a significant reduction in pH and dissolved metal concentrations, through the precipitation of hydrotalcite-like compounds and some other Mg, Ca, and Al hydroxide and carbonate minerals. The hydrotalcite-like compounds, precipitated during seawater neutralisation, also remove a range of transition metals, oxy-anions and other anionic species through a combination of intercalation and adsorption reactions: smaller anions are intercalated into the hydrotalcite matrix, while larger molecules are adsorbed on the particle surfaces. A phenomenon known as ‘reversion’ can occur if the seawater neutralisation process is not properly controlled. Reversion causes an increase in the pH and dissolved impurity levels of the neutralised effluent, rendering it unsuitable for discharge. It is believed that slow dissolution of components of the red mud residue and compounds formed during the neutralisation process are responsible for reversion. This investigation looked at characterising natural hydrotalcite (Mg6Al2(OH)16(CO3)∙4H2O) and ‘Bayer’ hydrotalcite (synthesised using the seawater neutralisation process) using a variety of techniques including X-ray diffraction, infrared and Raman spectroscopy, and thermogravimetric analysis. This investigation showed that Bayer hydrotalcite is comprised of a mixture of 3:1 and 4:1 hydrotalcite structures and exhibited similar chemical characteristic to the 4:1 synthetic hydrotalcite. Hydrotalcite formed from the seawater neutralisation of Bauxite refinery residues has been found not to cause reversion. Other components in red mud were investigated to determine the cause of reversion and this investigation found three components that contributed to reversion: 1) tricalcium aluminate, 2) hydrocalumite and 3) calcium hydroxide. Increasing the amount of magnesium in the neutralisation process has been found to be successful in reducing reversion.
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We develop and test a theoretically-based integrative framework of key proximal factors (orientation, pressure, and control) that helps to explain the effects of more general factors (the organisation's strategy, structure, and environment) on intentions to adopt an innovation one year later. Senior managers from 134 organizations were surveyed and confirmatory factor analyses showed that these hypothesized core factors provided a good fit to the data, indicating that our framework can provide a theoretical base to the previous, largely a theoretical, literature. Moreover, in a subgroup of 63 organizations, control mediated the effects of organizational strategy and centralisation on organizational innovation adoption intentions one year later. We suggest this model of core factors enables researchers to understand why certain variables are important to organisational innovation adoption and promotes identification of fertile research areas around orientation, pressure and control, and it enables managers to focus on the most proximal triggers for increasing innovation adoption.
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Security and privacy in electronic health record systems have been hindering the growth of e-health systems since their emergence. The development of policies that satisfy the security and privacy requirements of different stakeholders in healthcare has proven to be difficult. But, these requirements have to be met if the systems developed are to succeed in achieving their intended goals. Access control is a fundamental security barrier for securing data in healthcare information systems. In this paper we present an access control model for electronic health records. We address patient privacy requirements, confidentiality of private information and the need for flexible access for health professionals for electronic health records. We carefully combine three existing access control models and present a novel access control model for EHRs which satisfies requirements of electronic health records.
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This workshop provides an ergonomic framework and design rules for the design of automotive controls, considering anthropometric design, physiologic design, biomechanic design and information design.
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Purpose: Young novice drivers continue to be overrepresented in fatalities and injuries arising from crashes even with the introduction of countermeasures such as graduated driver licensing (GDL). Enhancing countermeasures requires a better understanding of the variables influencing risky driving. One of the most common risky behaviours performed by drivers of all ages is speeding, which is particularly risky for young novice drivers who, due to their driving inexperience, have difficulty in identifying and responding appropriately to road hazards. Psychosocial theory can improve our understanding of contributors to speeding, thereby informing countermeasure development and evaluation. This paper reports an application of Akers’ social learning theory (SLT), augmented by Gerrard and Gibbons’ prototype/willingness model (PWM), in addition to personal characteristics of age, gender, car ownership, and psychological traits/states of anxiety, depression, sensation seeking propensity and reward sensitivity, to examine the influences on self-reported speeding of young novice drivers with a Provisional (intermediate) licence in Queensland, Australia. Method: Young drivers (n = 378) recruited in 2010 for longitudinal research completed two surveys containing the Behaviour of Young Novice Drivers Scale, and reported their attitudes and behaviours as pre-Licence/Learner (Survey 1) and Provisional (Survey 2) drivers and their sociodemographic characteristics. Results: An Akers’ measurement model was created. Hierarchical multiple regressions revealed that (1) personal characteristics (PC) explained 20.3%; (2) the combination of PC and SLT explained 41.1%; and (3) the combination of PC, SLT and PWM explained 53.7% of variance in self-reported speeding. Whilst there appeared to be considerable shared variance, the significant predictors in the final model included gender, car ownership, reward sensitivity, depression, personal attitudes, and Learner speeding. Conclusions: These results highlight the capacity for psychosocial theory to improve our understanding of speeding by young novice drivers, revealing relationships between previous behaviour, attitudes, psychosocial characteristics and speeding. The findings suggest multi-faceted countermeasures should target the risky behaviour of Learners, and Learner supervisors should be encouraged to monitor their Learners’ driving speed. Novice drivers should be discouraged from developing risky attitudes towards speeding.
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A series of one dimensional (1D) zirconia/alumina nanocomposites were prepared by the deposition of zirconium species onto the 3D framework of boehmite nanofibres formed by dispersing boehmite nanofibres into butanol solution. The materials were calcined at 773K and characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscope (TEM), N2 adsorption/desorption, infrared emission spectroscopy (IES). The results demonstrated that when the molar percentage X=100*Zr/(Al+Zr) was > 30 %, extremely long ZrO2/Al2O3 composite nanorods with evenly distributed ZrO2 nanocrystals on the surface were formed. The stacking of such nanorods gave rise to a new kind of macroporous material without the use of any organic space filler\template or other specific technologies. The mechanism for the formation of long ZrO2/Al2O3 composite nanorods was proposed in this work.
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Concerns regarding groundwater contamination with nitrate and the long-term sustainability of groundwater resources have prompted the development of a multi-layered three dimensional (3D) geological model to characterise the aquifer geometry of the Wairau Plain, Marlborough District, New Zealand. The 3D geological model which consists of eight litho-stratigraphic units has been subsequently used to synthesise hydrogeological and hydrogeochemical data for different aquifers in an approach that aims to demonstrate how integration of water chemistry data within the physical framework of a 3D geological model can help to better understand and conceptualise groundwater systems in complex geological settings. Multivariate statistical techniques(e.g. Principal Component Analysis and Hierarchical Cluster Analysis) were applied to groundwater chemistry data to identify hydrochemical facies which are characteristic of distinct evolutionary pathways and a common hydrologic history of groundwaters. Principal Component Analysis on hydrochemical data demonstrated that natural water-rock interactions, redox potential and human agricultural impact are the key controls of groundwater quality in the Wairau Plain. Hierarchical Cluster Analysis revealed distinct hydrochemical water quality groups in the Wairau Plain groundwater system. Visualisation of the results of the multivariate statistical analyses and distribution of groundwater nitrate concentrations in the context of aquifer lithology highlighted the link between groundwater chemistry and the lithology of host aquifers. The methodology followed in this study can be applied in a variety of hydrogeological settings to synthesise geological, hydrogeological and hydrochemical data and present them in a format readily understood by a wide range of stakeholders. This enables a more efficient communication of the results of scientific studies to the wider community.