866 resultados para random number generation
Resumo:
The future of the HRM profession depends to at least some extent on the quality of preparation of the next generation of HR professionals. This paper examines bachelor degree programs in HRM and the role of professional associations as influencers of curricula. Some 39% of the 599 AACSB and EQUIS-accredited institutions sampled offer undergraduate degrees in HRM. The programs vary in emphasis on HRM competencies. Unsurprisingly, all include foundation work (perhaps a third of the content) in business management. Grouping degree content by regions globally allows benchmarking of degrees against international trends, along with consideration of the increasingly significant influence on curricula by professional bodies, in preparing the next generation of HRM practitioners to manage in organisations that will require strategic thinking, specialist technical skills, and interpersonal competence.
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The use of Bayesian methodologies for solving optimal experimental design problems has increased. Many of these methods have been found to be computationally intensive for design problems that require a large number of design points. A simulation-based approach that can be used to solve optimal design problems in which one is interested in finding a large number of (near) optimal design points for a small number of design variables is presented. The approach involves the use of lower dimensional parameterisations that consist of a few design variables, which generate multiple design points. Using this approach, one simply has to search over a few design variables, rather than searching over a large number of optimal design points, thus providing substantial computational savings. The methodologies are demonstrated on four applications, including the selection of sampling times for pharmacokinetic and heat transfer studies, and involve nonlinear models. Several Bayesian design criteria are also compared and contrasted, as well as several different lower dimensional parameterisation schemes for generating the many design points.
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Preventive Maintenance (PM) is often applied to improve the reliability of production lines. A Split System Approach (SSA) based methodology is presented to assist in making optimal PM decisions for serial production lines. The methodology treats a production line as a complex series system with multiple (imperfect) PM actions over multiple intervals. The conditional and overall reliability of the entire production line over these multiple PM intervals are hierarchically calculated using SSA, and provide a foundation for cost analysis. Both risk-related cost and maintenance-related cost are factored into the methodology as either deterministic or random variables. This SSA based methodology enables Asset Management (AM) decisions to be optimised considering a variety of factors including failure probability, failure cost, maintenance cost, PM performance, and the type of PM strategy. The application of this new methodology and an evaluation of the effects of these factors on PM decisions are demonstrated using an example. The results of this work show that the performance of a PM strategy can be measured by its Total Expected Cost Index (TECI). The optimal PM interval is dependent on TECI, PM performance and types of PM strategies. These factors are interrelated. Generally, it was found that a trade-off between reliability and the number of PM actions needs to be made so that one can minimise Total Expected Cost (TEC) for asset maintenance.
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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.
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Purpose: Generation Y (Gen Y) is the newest and largest generation entering the workforce. Gen Y may differ from previous generations in work-related characteristics which may have recruitment and retention repercussions. Currently, limited theoretically-based research exists regarding Gen Y’s work expectations and goals in relation to undergraduate students and graduates. Design/methodology/approach: This study conducted a theoretically-based investigation of the work expectations and goals of student- and working-Gen Y individuals based within a framework incorporating both expectancy-value and goal setting theories. N = 398 provided useable data via an on-line survey. Findings: Overall, some support was found for predictions with career goals loading on a separate component to daily work expectations and significant differences between student- and working- Gen Y on career goals. No significant differences were found, however, between the two groups in daily work expectations. Research limitations/implications: Future research may benefit from adopting a theoretical framework which assesses both daily work expectations and career goals when examining the factors which motivate Gen Y’s decisions to join and remain at a particular organisation. Practical implications: At a practical level, based on the findings, some examples are provided of the means by which organisations may draw upon daily work expectations and career goals of importance to Gen Y and, in doing so, influence the likelihood that a Gen Y individual will join and remain at their particular organisation. Originality/value: This research has demonstrated the utility of adopting a sound theoretical framework in furthering understanding about the motivations which influence organisations’ ability to recruit and retain Gen Y, among both student Gen Y as well as those Gen Y individuals who are already working.
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Capacity probability models of generating units are commonly used in many power system reliability studies, at hierarchical level one (HLI). Analytical modelling of a generating system with many units or generating units with many derated states in a system, can result in an extensive number of states in the capacity model. Limitations on available memory and computational time of present computer facilities can pose difficulties for assessment of such systems in many studies. A cluster procedure using the nearest centroid sorting method was used for IEEE-RTS load model. The application proved to be very effective in producing a highly similar model with substantially fewer states. This paper presents an extended application of the clustering method to include capacity probability representation. A series of sensitivity studies are illustrated using IEEE-RTS generating system and load models. The loss of load and energy expectations (LOLE, LOEE), are used as indicators to evaluate the application
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Vesicular and groundmass phyllosilicates in a hydrothermally altered basalt from the Point Sal ophiolite, California, have been studied using transmission electron microscopy (TEM). Pore-filling phyllosilicates are texturally characterized as having coherent, relatively thick and defect-free crystals of chlorite (14 Å) with occasional 24-Å periodicities. Groundmass phyllosilicates are texturally characterized as 1) randomly oriented crystals up to 200 Å in width and 2) larger, more coherent crystals up to 1000 Å in width. Small crystallites contain predominantly 14-Å layers with some 24-Å units. Large crystals show randomly interlayered chlorite/smectite (C/S), with approximately 50% chlorite on average. Adjacent smectite-like layers are not uncommon in the groundmass phyllosilicates. Electron microprobe analyses show that Fe/Mg ratios of both groundmass and vesicular phyllosilicates are fairly constant. Termination of brucite-like interlayers has been identified in some of the TEM images. The transformation mechanisms represented by these layer terminations are 1) growth of a brucite-like interlayer within smectite interlayer regions and 2) the dissolution and reprecipitation of elements to form chlorite layers. Both mechanisms require an increase in volume as smectite transforms to chlorite. The data, combined with that from previously published reports, suggest that randomly interlayered C/S is a metastable phase formed in microenvironments with low water/rock ratios. Chlorite forms in microenvironments in the same sample dominated by higher water/rock ratios. The relatively constant number of Mg's in the structure (Mg#) of both structures indicates that in both microenvironments the bulk rock composition has influence over the composition of phyllosilicates.
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In his 2007 PESA keynote address, Paul Smeyers discussed the increasing regulation of child-rearing through government intervention and the generation of “experts,” citing particular examples from Europe where cases of childhood obesity and parental neglect have stirred public opinion and political debate. In his paper (this issue), Smeyers touches on a number of tensions before concluding that child rearing qualifies as a practice in which liberal governments should be reluctant to intervene. In response, I draw on recent experiences in Australia and argue that certain tragic events of late are the result of an ethical, moral and social vacuum in which these tensions coalesce. While I agree with Smeyers that governments should be reluctant to “intervene” in the private domain of the family, I argue that there is a difference between intervention and support. In concluding, I maintain that if certain Western liberal democracies did a more comprehensive job of supporting children and their families through active social investment in primary school education, then both families and schools would be better equipped to deal with the challenges they now face.
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This item provides supplementary materials for the paper mentioned in the title, specifically a range of organisms used in the study. The full abstract for the main paper is as follows: Next Generation Sequencing (NGS) technologies have revolutionised molecular biology, allowing clinical sequencing to become a matter of routine. NGS data sets consist of short sequence reads obtained from the machine, given context and meaning through downstream assembly and annotation. For these techniques to operate successfully, the collected reads must be consistent with the assumed species or species group, and not corrupted in some way. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans,with some strains exhibiting antibiotic resistance. In this paper, we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from alternative pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.
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Herein the mechanical properties of graphene, including Young’s modulus, fracture stress and fracture strain have been investigated by molecular dynamics simulations. The simulation results show that the mechanical properties of graphene are sensitive to the temperature changes but insensitive to the layer numbers in the multilayer graphene. Increasing temperature exerts adverse and significant effects on the mechanical properties of graphene. However, the adverse effect produced by the increasing layer number is marginal. On the other hand, isotope substitutions in graphene play a negligible role in modifying the mechanical properties of graphene.
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Large scale sugarcane bagasse storage in uncovered stockpiles has the potential to result in adverse impacts on the environment and surrounding communities through hazards associated with nuisance dust, groundwater seepage, spontaneous combustion and generation of contaminated leachates. Managing these hazards will assist in improved health and safety outcomes for factory staff and reduced potential environmental impacts on surrounding communities. Removal of the smaller fibres (pith) from bagasse prior to stockpiling reduced the dust number of bagasse by 50% and modelling suggests peak ground level PM10 dust emissions would reduce by 70%. Depithed bagasse has much lower water holding capacity (~43%) than whole bagasse. This experimental and modelling study investigated the physical properties of depithed and whole bagasse. Dust dispersion modelling was undertaken to determine the likely effects associated with storage of whole and depithed sugarcane bagasse.
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In recent years considerable attention has been paid to the numerical solution of stochastic ordinary differential equations (SODEs), as SODEs are often more appropriate than their deterministic counterparts in many modelling situations. However, unlike the deterministic case numerical methods for SODEs are considerably less sophisticated due to the difficulty in representing the (possibly large number of) random variable approximations to the stochastic integrals. Although Burrage and Burrage [High strong order explicit Runge-Kutta methods for stochastic ordinary differential equations, Applied Numerical Mathematics 22 (1996) 81-101] were able to construct strong local order 1.5 stochastic Runge-Kutta methods for certain cases, it is known that all extant stochastic Runge-Kutta methods suffer an order reduction down to strong order 0.5 if there is non-commutativity between the functions associated with the multiple Wiener processes. This order reduction down to that of the Euler-Maruyama method imposes severe difficulties in obtaining meaningful solutions in a reasonable time frame and this paper attempts to circumvent these difficulties by some new techniques. An additional difficulty in solving SODEs arises even in the Linear case since it is not possible to write the solution analytically in terms of matrix exponentials unless there is a commutativity property between the functions associated with the multiple Wiener processes. Thus in this present paper first the work of Magnus [On the exponential solution of differential equations for a linear operator, Communications on Pure and Applied Mathematics 7 (1954) 649-673] (applied to deterministic non-commutative Linear problems) will be applied to non-commutative linear SODEs and methods of strong order 1.5 for arbitrary, linear, non-commutative SODE systems will be constructed - hence giving an accurate approximation to the general linear problem. Secondly, for general nonlinear non-commutative systems with an arbitrary number (d) of Wiener processes it is shown that strong local order I Runge-Kutta methods with d + 1 stages can be constructed by evaluated a set of Lie brackets as well as the standard function evaluations. A method is then constructed which can be efficiently implemented in a parallel environment for this arbitrary number of Wiener processes. Finally some numerical results are presented which illustrate the efficacy of these approaches. (C) 1999 Elsevier Science B.V. All rights reserved.
Resumo:
Metal and semiconductor nanowires (NWs) have been widely employed as the building blocks of the nanoelectromechanical systems, which usually acted a resonant beam. Recent researches reported that nanowires are often polycrystalline, which contains grain boundaries (GBs) that transect the whole nanowire into a bamboo like structure. Based on the larger-scale molecular dynamics (MD) simulations, a comprehensive investigation of the influence from grain boundaries on the vibrational properties of doubly clamped Ag NWs is conducted. It is found that, the presence of grain boundary will result in significant energy dissipation during the resonance of polycrystalline NWs, which leads a great deterioration to the quality factor. Further investigation reveals that the energy dissipation is originated from the plastic deformation of polycrystalline NWs in the form of the nucleation of partial dislocations or the generation of micro stacking faults around the GBs and the micro stacking faults is found to keep almost intact during the whole vibration process. Moreover, it is observed that the closer of the grain boundary getting to the regions with the highest strain state, the more energy dissipation will be resulted from the plastic deformation. In addition, either the increase of the number of grain boundaries or the decrease of the distance between the grain boundary and the highest strain state region is observed to induce a lower first resonance frequency. This work sheds lights on the better understanding of the mechanical properties of polycrystalline NWs, which benefits the increasing utilities of NWs in diverse nano-electronic devices.
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An online survey was conducted to investigate the views and experiences of Australian traffic and transport professionals about practical problems and issues in terms of trip generation and trip chaining for use in Transport Impact Assessment (TIA). Findings from this survey revealed that there is a shortage of appropriate data related to trip generation estimation for use in TIAs in Australia. Establishing a National Trip Generation Database (NTGD) with a centralised responsible organisation for collecting and publishing trip generation data based on federal and state governments’ contribution was found the most accepted solution for resolving this shortage as well as providing national standards and guidelines associated with trip generation definitions, data collection methodology, and TIA preparation process based on updated research. Finally, the study recognised the importance of the trip chaining effects on trip generation estimation and identified most prevalent land uses subject to trip chaining in terms of TIA.