40 resultados para ecological dynamics, performance contexts

em Aston University Research Archive


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As the world’s natural resources dwindle and critical levels of environmental pollution are approached, sustainability becomes a key issue for governments, organisations and individuals. With the consequences of such an issue in mind, this paper introduces a unifying approach to measure the sustainability performance of socio-economic systems based on the interplay between two key variables: essentiality of consumption and environmental impact. This measure attributes to every system a ‘fitness’ value i.e. a quantity that reflects its ability to remain resilient/healthy by avoiding ecological, social and economic collapse as it consumes the available resources. This new measure is tested on a system where there is a limited supply of resources and four basic consumption types. The analysis has theoretical implications as well as practical importance as it can help countries, organisations or even individuals, in finding better ways to measure sustainability performance.

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The amplification of demand variation up a supply chain widely termed ‘the Bullwhip Effect’ is disruptive, costly and something that supply chain management generally seeks to minimise. Originally attributed to poor system design; deficiencies in policies, organisation structure and delays in material and information flow all lead to sub-optimal reorder point calculation. It has since been attributed to exogenous random factors such as: uncertainties in demand, supply and distribution lead time but these causes are not exclusive as academic and operational studies since have shown that orders and/or inventories can exhibit significant variability even if customer demand and lead time are deterministic. This increase in the range of possible causes of dynamic behaviour indicates that our understanding of the phenomenon is far from complete. One possible, yet previously unexplored, factor that may influence dynamic behaviour in supply chains is the application and operation of supply chain performance measures. Organisations monitoring and responding to their adopted key performance metrics will make operational changes and this action may influence the level of dynamics within the supply chain, possibly degrading the performance of the very system they were intended to measure. In order to explore this a plausible abstraction of the operational responses to the Supply Chain Council’s SCOR® (Supply Chain Operations Reference) model was incorporated into a classic Beer Game distribution representation, using the dynamic discrete event simulation software Simul8. During the simulation the five SCOR Supply Chain Performance Attributes: Reliability, Responsiveness, Flexibility, Cost and Utilisation were continuously monitored and compared to established targets. Operational adjustments to the; reorder point, transportation modes and production capacity (where appropriate) for three independent supply chain roles were made and the degree of dynamic behaviour in the Supply Chain measured, using the ratio of the standard deviation of upstream demand relative to the standard deviation of the downstream demand. Factors employed to build the detailed model include: variable retail demand, order transmission, transportation delays, production delays, capacity constraints demand multipliers and demand averaging periods. Five dimensions of supply chain performance were monitored independently in three autonomous supply chain roles and operational settings adjusted accordingly. Uniqueness of this research stems from the application of the five SCOR performance attributes with modelled operational responses in a dynamic discrete event simulation model. This project makes its primary contribution to knowledge by measuring the impact, on supply chain dynamics, of applying a representative performance measurement system.

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We analyse the matrix momentum algorithm, which provides an efficient approximation to on-line Newton's method, by extending a recent statistical mechanics framework to include second order algorithms. We study the efficacy of this method when the Hessian is available and also consider a practical implementation which uses a single example estimate of the Hessian. The method is shown to provide excellent asymptotic performance, although the single example implementation is sensitive to the choice of training parameters. We conjecture that matrix momentum could provide efficient matrix inversion for other second order algorithms.

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The dynamics of supervised learning in layered neural networks were studied in the regime where the size of the training set is proportional to the number of inputs. The evolution of macroscopic observables, including the two relevant performance measures can be predicted by using the dynamical replica theory. Three approximation schemes aimed at eliminating the need to solve a functional saddle-point equation at each time step have been derived.

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This paper highlights the context within which business process outsourcing (BPO) has rapidly grown in India and the critical need to investigate the dynamics of human resource management (HRM) practices and systems in this sector. Using a mixed-method approach involving both in-depth interviews and self-completing questionnaires, we analyze the nature of HRM systems in BPO organizations operating in India. The analysis is based on a sample of 51 BPO companies, a majority of which are located near the capital of New Delhi. The results focus on the nature and structure of work and organization of Indian BPOs, as well as the strategic role played by HRM in such organizations. Furthermore, the findings highlight the way specific HRM practices such as recruitment, performance appraisal, training and development, and compensations are implemented. Our study suggests the existence of formal, structured, and rationalized HRM systems in Indian BPOs. A number of insights related to HRM policies and practices are shared by the HR managers interviewed shedding more light on the inner workings of the Indian BPO companies and their challenges. The analysis provides original and useful information to both academics and practitioners and opens avenues for future research on the nature of HRM systems and practices in the Indian BPO industry.

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This study examines climate for innovation as a method by which negative organizational consequences of demanding work may be lessened. It was expected that a climate for innovation would enable employees to develop coping mechanisms or improved work-related processes which counteract negative consequences of work demands. Extending the job demands-resource model (Karasek, 1979), we predicted and found that among the sample of 22,696 respondents from 131 healthcare organizations, organizational climate for innovation alleviated the negative effects of work demands on organizational performance. Thus, this study informs climate theories and guides practitioners' efforts to support the employees. © 2007 The British Psychological Society.

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Purpose - To provide an example of the use of system dynamics within the context of a discrete-event simulation study. Design/methodology/approach - A discrete-event simulation study of a production-planning facility in a gas cylinder-manufacturing plant is presented. The case study evidence incorporates questionnaire responses from sales managers involved in the order-scheduling process. Findings - As the project progressed it became clear that, although the discrete-event simulation would meet the objectives of the study in a technical sense, the organizational problem of "delivery performance" would not be solved by the discrete-event simulation study alone. The case shows how the qualitative outcomes of the discrete-event simulation study led to an analysis using the system dynamics technique. The system dynamics technique was able to model the decision-makers in the sales and production process and provide a deeper understanding of the performance of the system. Research limitations/implications - The case study describes a traditional discrete-event simulation study which incorporated an unplanned investigation using system dynamics. Further, case studies using a planned approach to showing consideration of organizational issues in discrete-event simulation studies are required. Then the role of both qualitative data in a discrete-event simulation study and the use of supplementary tools which incorporate organizational aspects may help generate a methodology for discrete-event simulation that incorporates human aspects and so improve its relevance for decision making. Practical implications - It is argued that system dynamics can provide a useful addition to the toolkit of the discrete-event simulation practitioner in helping them incorporate a human aspect in their analysis. Originality/value - Helps decision makers gain a broader perspective on the tools available to them by showing the use of system dynamics to supplement the use of discrete-event simulation. © Emerald Group Publishing Limited.

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Recently there has been an outburst of interest in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, there is no general consensus as to how best to process sequences using topographicmaps, and this topic remains an active focus of neurocomputational research. The representational capabilities and internal representations of the models are not well understood. Here, we rigorously analyze a generalization of the self-organizingmap (SOM) for processing sequential data, recursive SOM (RecSOM) (Voegtlin, 2002), as a nonautonomous dynamical system consisting of a set of fixed input maps. We argue that contractive fixed-input maps are likely to produce Markovian organizations of receptive fields on the RecSOM map. We derive bounds on parameter β (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed-input maps is guaranteed. Some generalizations of SOM contain a dynamic module responsible for processing temporal contexts as an integral part of the model. We show that Markovian topographic maps of sequential data can be produced using a simple fixed (nonadaptable) dynamic module externally feeding a standard topographic model designed to process static vectorial data of fixed dimensionality (e.g., SOM). However, by allowing trainable feedback connections, one can obtain Markovian maps with superior memory depth and topography preservation. We elaborate on the importance of non-Markovian organizations in topographic maps of sequential data. © 2006 Massachusetts Institute of Technology.

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Using a unique firm level data, this paper analyses the role of political connections in the post-entry performance of private start-up companies in China. It documents robust evidence that political affiliation enhances firms’ survival and growth prospects. But interestingly politically neutral start-ups enjoy faster productivity improvements conditional on survival.. We conclude that the close association between the state and a segment of the business community is leading to sub-optimal resource allocation in the economy by interfering with the process of market selection.

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Vehicle dynamics modelling can provide vehicle designers with vehicle performance data that can assist with the efficient development of more refined cars. However, such models are notoriously complicated requiring the user to have a considerable understanding of vehicle dynamics.

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Investigations into the modelling techniques that depict the transport of discrete phases (gas bubbles or solid particles) and model biochemical reactions in a bubble column reactor are discussed here. The mixture model was used to calculate gas-liquid, solid-liquid and gasliquid-solid interactions. Multiphase flow is a difficult phenomenon to capture, particularly in bubble columns where the major driving force is caused by the injection of gas bubbles. The gas bubbles cause a large density difference to occur that results in transient multi-dimensional fluid motion. Standard design procedures do not account for the transient motion, due to the simplifying assumptions of steady plug flow. Computational fluid dynamics (CFD) can assist in expanding the understanding of complex flows in bubble columns by characterising the flow phenomena for many geometrical configurations. Therefore, CFD has a role in the education of chemical and biochemical engineers, providing the examples of flow phenomena that many engineers may not experience, even through experimentation. The performance of the mixture model was investigated for three domains (plane, rectangular and cylindrical) and three flow models (laminar, k-e turbulence and the Reynolds stresses). mThis investigation raised many questions about how gas-liquid interactions are captured numerically. To answer some of these questions the analogy between thermal convection in a cavity and gas-liquid flow in bubble columns was invoked. This involved modelling the buoyant motion of air in a narrow cavity for a number of turbulence schemes. The difference in density was caused by a temperature gradient that acted across the width of the cavity. Multiple vortices were obtained when the Reynolds stresses were utilised with the addition of a basic flow profile after each time step. To implement the three-phase models an alternative mixture model was developed and compared against a commercially available mixture model for three turbulence schemes. The scheme where just the Reynolds stresses model was employed, predicted the transient motion of the fluids quite well for both mixture models. Solid-liquid and then alternative formulations of gas-liquid-solid model were compared against one another. The alternative form of the mixture model was found to perform particularly well for both gas and solid phase transport when calculating two and three-phase flow. The improvement in the solutions obtained was a result of the inclusion of the Reynolds stresses model and differences in the mixture models employed. The differences between the alternative mixture models were found in the volume fraction equation (flux and deviatoric stress tensor terms) and the viscosity formulation for the mixture phase.

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The adaptation of profit sharing creates a fundamental change in employee compensation by making a portion of total compensation directly dependent upon the total profits of the firm and the performance of the employee. The major goal of this study is to test for and measure the impact of the independent variable, a profit sharing plan implemented at Shahvand Industrial Company, upon communication behaviour, communication outcomes, and organisational outcomes as dependent variables. A quasi-experimental non-equivalent control group design with pre and posttest was the research design used to test the effects of profit sharing participation on permanent-part-time operative employees implemented by SIC. Several conclusions were reached as a result of the statistical analysis of the data collected in this study. Overall, few of the hypothesised effects of profit sharing participation appeared to have been realised according to the empirical results of this study. The finding that certain communication behaviours were more favourable for profit sharing participants than for non-participants support the general hypothesis of the integrated profit sharing model. The observed changes in communication behaviours indicate that information sharing and idea generation are important components of the profit sharing process. The results of this study did not reveal any changes in either communication or organisational outcomes. A significant finding of this study is that the implementation of profit sharing plans require a relatively long period of time. Patience is required to achieve high levels of success and management must make long-term commitment to profit sharing. Findings of this study should be interpreted with caution, taking into consideration that most of the previo.us researches on profit sharing have been conducted in Western European or American countries, while the current study was based on data collected from an organisation in a developing country. This implies that the findings reported in this thesis may not be comparable in certain respects to results derived from companies in major industrialised economies.

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This collection of papers records a series of studies, carried out over a period of some 50 years, on two aspects of river pollution control - the prevention of pollution by sewage biological filtration and the monitoring of river pollution by biological surveillance. The earlier studies were carried out to develop methods of controlling flies which bred in the filters and caused serious nuisance and possible public health hazard, when they dispersed to surrounding villages. Although the application of insecticides proved effective as an alleviate measure, because it resulted in only a temporary disturbance of the ecological balance, it was considered ecologically unsound as a long-term solution. Subsequent investigations showed that the fly populations in filters were largely determined by the amount of food available to the grazing larval stage in the form of filter film. It was also established that the winter deterioration in filter performance was due to the excessive accumulation of film. Subsequent investigations were therefore carried out to determine the factors responsible for the accumulation of film in different types of filter. Methods of filtration which were considered to control film accumulation by increasing the flushing action of the sewage, were found to control fungal film by creating nutrient limiting conditions. In some filters increasing the hydraulic flushing reduced the grazing fauna population in the surface layers and resulted in an increase in film. The results of these investigations were successfully applied in modifying filters and in the design of a Double Filtration process. These studies on biological filters lead to the conclusion that they should be designed and operated as ecological systems and not merely as hydraulic ones. Studies on the effects of sewage effluents on Birmingham streams confirmed the findings of earlier workers justifying their claim for using biological methods for detecting and assessing river pollution. Further ecological studies showed the sensitivity of benthic riffle communities to organic pollution. Using experimental channels and laboratory studies the different environmental conditions associated with organic pollution were investigated. The degree and duration of the oxygen depletion during the dark hours were found to be a critical factor. The relative tolerance of different taxa to other pollutants, such as ammonia, differed. Although colonisation samplers proved of value in sampling difficult sites, the invertebrate data generated were not suitable for processing as any of the commonly used biotic indexes. Several of the papers, which were written by request for presentation at conferences etc., presented the biological viewpoint on river pollution and water quality issues at the time and advocated the use of biological methods. The information and experiences gained in these investigations was used as the "domain expert" in the development of artificial intelligence systems for use in the biological surveillance of river water quality.

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Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics.