252 resultados para Resource Dependence


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In this paper we report a new neutron Compton scattering (NCS) measurement of the ground state single atom kinetic energy of polycrystalline beryllium at momentum transfers in the range 27}104 As ~1 and temperatures in the range 110}1150 K. The measurements have been made with the electron Volt spectrometer (eVS) at the ISIS facility and the measured kinetic energies are shown to be &10% higher than calculations made in the harmonic approximation.

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In this paper, the influence of the impact energy on the initial fabrication of thin films formed by low energy cluster deposition was investigated by molecular dynamics simulation of All 3 clusters depositing on Ni(0 0 1) substrate. In the case of soft-landing, (0.01 eV/atom), clusters are rearranged from I-h symmetry into fcc-like clusters on the surface. Then they aggregate each other, which result in thin film growing in 3D island mode. While, growth will be in layer-by-layer mode at the impact energy of a few electron volt due to the transient lateral spread of cluster atoms induced by dense collision cascade. This effect has been traced to collision cascade inside the cluster. which is enhanced by collision with a hard Ni substrate. (C) 2002 Elsevier Science B.V. All rights reserved.

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The deposition of hyperthermal CH3 on diamond (001)-(2×1) surface at room temperature has been studied by means of molecular dynamics simulation using the many-body hydrocarbon potential. The energy threshold effect has been observed. That is, with fixed collision geometry, chemisorption can occur only when the incident energy of CH3 is above a critical value (Eth). Increasing the incident energy, dissociation of hydrogen atoms from the incident molecule was observed. The chemisorption probability of CH3 as a function of its incident energy was calculated and compared with that of C2H2. We found that below 10 eV, the chemisorption probability of C2H2 is much lower than that of CH3 on the same surface. The interesting thing is that it is even lower than that of CH3 on a hydrogen covered surface at the same impact energy. It indicates that the reactive CH3 molecule is the more important species than C2H2 in diamond synthesis at low energy, which is in good agreement with the experimental observation.

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This thesis studied the source of instability in optical phase modulators used in high accuracy laser measurement systems. The nonlinear origin of the amplitude noise helped further reducing this instability in applications that rely on phase modulators to function. This outcome will have positive impacts on the development of new methods in the amplitude noise suppression.

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This study aimed to investigate drink driving in a sample of general drivers and convicted drunk driving offenders in Guangzhou, China. The study also aimed to explore some potential factors that impact on alcohol-related driving behaviour. Samples of 406 general drivers and 101 drunk driving offenders were recruited between May and October 2012. A survey was used to collect information about demographic characteristics, knowledge, attitudes and practices related to drink driving. The Alcohol Use Disorders Identification Test (AUDIT) was used to assess possible drinking problems. The average age reported for starting to drink alcohol for both groups of participants was around 19 years old. The mean AUDIT score of general drivers was 7.4 (SD = 5.4) representing a low level of alcohol problems, and for convicted drunk driving offenders was 11.1 (SD = 5.9) representing a medium level of alcohol problems (significant difference between means, t = 5.75, p < 0.001). AUDIT scores indicated that a substantial proportion (65%) of the offenders had medium to high levels of alcohol use disorders, compared with 38.5% among general drivers. Offenders who knew the drunk driving legal limit had a lower AUDIT score (M = 9.8, SD = 5.16) than those who did not know it (M = 12.2, SD = 6.257, t = -1.987. p = 0.05). In addition, offenders who were novice drivers (licensed less than 2 years) had a higher AUDIT score (M = 16.4, SD = 7.6) than the other three driver experience categories used.

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Evidence suggests that both nascent and young firms (henceforth: “new firms”)—despite typically being small and resource-constrained—are sometimes able to innovate effectively. Such firms are seldom able to invest in lengthy and expensive development processes, which suggests that they may frequently rely instead on other pathways to generate innovativeness within the firm. In this paper, we develop and test arguments that “bricolage,” defined as making do by applying combinations of the resources at hand to new problems and opportunities, provides an important pathway to achieve innovation for new resource-constrained firms. Through bricolage, resource-constrained firms engage in the processes of “recombination” that are core to creating innovative outcomes. Based on a large longitudinal dataset, our results suggest that variations in the degree to which firms engage in bricolage behaviors can provide a broadly applicable explanation of innovativeness under resource constraints by new firms. We find no general support for our competing hypothesis that the positive effects may level off or even turn negative at high levels of bricolage..

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Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.

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Designers need to consider both the functional and production process requirements at the early stage of product development. A variety of the research works found in the literature has been proposed to assist designers in selecting the most viable manufacturing process chain. However, they do not provide any assistance for designers to evaluate the processes according to the particular circumstances of their company. This paper describes a framework of an Activity and Resource Advisory System (ARAS) that generates advice about the required activities and the possible resources for various manufacturing process chains. The system provides more insight, more flexibility, and a more holistic and suitable approach for designers to evaluate and then select the most viable manufacturing process chain at the early stage of product development.

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Our results demonstrate that photorefractive residual amplitude modulation (RAM) noise in electro-optic modulators (EOMs) can be reduced by modifying the incident beam intensity distribution. Here we report an order of magnitude reduction in RAM when beams with uniform intensity (flat-top) profiles, generated with an LCOS-SLM, are used instead of the usual fundamental Gaussian mode (TEM00). RAM arises from the photorefractive amplified scatter noise off the defects and impurities within the crystal. A reduction in RAM is observed with increasing intensity uniformity (flatness), which is attributed to a reduction in space charge field on the beam axis. The level of RAM reduction that can be achieved is physically limited by clipping at EOM apertures, with the observed results agreeing well with a simple model. These results are particularly important in applications where the reduction of residual amplitude modulation to 10^-6 is essential.

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Lens average and equivalent refractive indices are required for purposes such as lens thickness estimation and optical modeling. We modeled the refractive index gradient as a power function of the normalized distance from lens center. Average index along the lens axis was estimated by integration. Equivalent index was estimated by raytracing through a model eye to establish ocular refraction, and then backward raytracing to determine the constant refractive index yielding the same refraction. Assuming center and edge indices remained constant with age, at 1.415 and 1.37 respectively, average axial refractive index increased (1.408 to 1.411) and equivalent index decreased (1.425 to 1.420) with age increase from 20 to 70 years. These values agree well with experimental estimates based on different techniques, although the latter show considerable scatter. The simple model of index gradient gives reasonable estimates of average and equivalent lens indices, although refinements in modeling and measurements are required.

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Some of Queensland's regions are experiencing rapid changes related to the recent and growing capacity to more effectively exploit significant energy sources. These changes have triggered land-use conflicts between the mining sector and other economic sectors, mainly agriculture. These conflicts fuel existing uncertainty surrounding the current and future economic, social and environmental impacts of extractive industries. This paper explores the concept of uncertainty as it applies to planning for resource-based regions through a scoping analysis of regional stakeholders' perceptions of land-use uncertainty. It then investigates solutions to alleviate such an issue.

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This thesis addresses the process simulation and validation in Business Process Management. It proposes that the hybrid Multi Agent System (MAS) / 3D Virtual World approach is a valid method for better simulating the behaviour of human resources in business processes, supporting a wide range of rich visualization applications that can facilitate communication between business analysts and stakeholders. It is expected that the findings of this thesis may be fruitfully extended from BPM to other application domains, such as social simulation in video games and computer-based training animations.

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Carrying capacity assessments model a population’s potential self-sufficiency. A crucial first step in the development of such modelling is to examine the basic resource-based parameters defining the population’s production and consumption habits. These parameters include basic human needs such as food, water, shelter and energy together with climatic, environmental and behavioural characteristics. Each of these parameters imparts land-usage requirements in different ways and varied degrees so their incorporation into carrying capacity modelling also differs. Given that the availability and values of production parameters may differ between locations, no two carrying capacity models are likely to be exactly alike. However, the essential parameters themselves can remain consistent so one example, the Carrying Capacity Dashboard, is offered as a case study to highlight one way in which these parameters are utilised. While examples exist of findings made from carrying capacity assessment modelling, to date, guidelines for replication of such studies in other regions and scales have largely been overlooked. This paper addresses such shortcomings by describing a process for the inclusion and calibration of the most important resource-based parameters in a way that could be repeated elsewhere.

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This thesis presents an analysis of the resource allocation problem in Orthogonal Frequency Division Multiplexing based multi-hop wireless communications systems. The study analyzed the tractable nature of the problem and designed several heuristic and fairness-aware resource allocation algorithms. These algorithms are fast and efficient and therefore can improve power management in wireless systems significantly.

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This concept paper examines the positioning of Change Management (CM) in relation to IHRM, and suggests that the emerging field of CM should be seen as collaborative with HRM in providing for the dynamic needs of organisations in contemporary international conditions of uncertainty and environmental turbulence.