93 resultados para index model


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A number of mathematical models investigating certain aspects of the complicated process of wound healing are reported in the literature in recent years. However, effective numerical methods and supporting error analysis for the fractional equations which describe the process of wound healing are still limited. In this paper, we consider numerical simulation of fractional model based on the coupled advection-diffusion equations for cell and chemical concentration in a polar coordinate system. The space fractional derivatives are defined in the Left and Right Riemann-Liouville sense. Fractional orders in advection and diffusion terms belong to the intervals (0; 1) or (1; 2], respectively. Some numerical techniques will be used. Firstly, the coupled advection-diffusion equations are decoupled to a single space fractional advection-diffusion equation in a polar coordinate system. Secondly, we propose a new implicit difference method for simulating this equation by using the equivalent of the Riemann-Liouville and Gr¨unwald-Letnikov fractional derivative definitions. Thirdly, its stability and convergence are discussed, respectively. Finally, some numerical results are given to demonstrate the theoretical analysis.

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Many physical processes exhibit fractional order behavior that varies with time or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. In this paper, we consider the time variable fractional order mobile-immobile advection-dispersion model. Numerical methods and analyses of stability and convergence for the fractional partial differential equations are quite limited and difficult to derive. This motivates us to develop efficient numerical methods as well as stability and convergence of the implicit numerical methods for the fractional order mobile immobile advection-dispersion model. In the paper, we use the Coimbra variable time fractional derivative which is more efficient from the numerical standpoint and is preferable for modeling dynamical systems. An implicit Euler approximation for the equation is proposed and then the stability of the approximation are investigated. As for the convergence of the numerical scheme we only consider a special case, i.e. the time fractional derivative is independent of time variable t. The case where the time fractional derivative depends both the time variable t and the space variable x will be considered in the future work. Finally, numerical examples are provided to show that the implicit Euler approximation is computationally efficient.

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Business process management (BPM) is becoming the dominant management paradigm. Business process modelling is central to BPM, and the resultant business process model the core artefact guiding subsequent process change. Thus, model quality is at the centre, mediating between the modelling effort and related growing investment in ultimate process improvements. Nonetheless, though research interest in the properties that differentiate high quality process models is longstanding, there have been no past reports of a valid, operationalised, holistic measure of business process model quality. In attention to this gap, this paper reports validation of a Business Process Model Quality measurement model, conceptualised as a single-order, formative index. Such a measurement model has value as the dependent variable in rigorously researching the drivers of model quality; as antecedent of ultimate process improvements; and potentially as an economical comparator and diagnostic for practice.

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This paper develops a framework for classifying term dependencies in query expansion with respect to the role terms play in structural linguistic associations. The framework is used to classify and compare the query expansion terms produced by the unigram and positional relevance models. As the unigram relevance model does not explicitly model term dependencies in its estimation process it is often thought to ignore dependencies that exist between words in natural language. The framework presented in this paper is underpinned by two types of linguistic association, namely syntagmatic and paradigmatic associations. It was found that syntagmatic associations were a more prevalent form of linguistic association used in query expansion. Paradoxically, it was the unigram model that exhibited this association more than the positional relevance model. This surprising finding has two potential implications for information retrieval models: (1) if linguistic associations underpin query expansion, then a probabilistic term dependence assumption based on position is inadequate for capturing them; (2) the unigram relevance model captures more term dependency information than its underlying theoretical model suggests, so its normative position as a baseline that ignores term dependencies should perhaps be reviewed.

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This paper presents two novel concepts to enhance the accuracy of damage detection using the Modal Strain Energy based Damage Index (MSEDI) with the presence of noise in the mode shape data. Firstly, the paper presents a sequential curve fitting technique that reduces the effect of noise on the calculation process of the MSEDI, more effectively than the two commonly used curve fitting techniques; namely, polynomial and Fourier’s series. Secondly, a probability based Generalized Damage Localization Index (GDLI) is proposed as a viable improvement to the damage detection process. The study uses a validated ABAQUS finite-element model of a reinforced concrete beam to obtain mode shape data in the undamaged and damaged states. Noise is simulated by adding three levels of random noise (1%, 3%, and 5%) to the mode shape data. Results show that damage detection is enhanced with increased number of modes and samples used with the GDLI.

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Approximate clone detection is the process of identifying similar process fragments in business process model collections. The tool presented in this paper can efficiently cluster approximate clones in large process model repositories. Once a repository is clustered, users can filter and browse the clusters using different filtering parameters. Our tool can also visualize clusters in the 2D space, allowing a better understanding of clusters and their member fragments. This demonstration will be useful for researchers and practitioners working on large process model repositories, where process standardization is a critical task for increasing the consistency and reducing the complexity of the repository.

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Purpose: There is a lack of theory relating to destination brand performance measurement in the destination branding literature, which emerged in the late 1990s (see for example Dosen, Vransevic, & Prebezac, 1998). Additionally, there is a lack of research about the importance of travel context in consumers’ destination decision making (Hu & Ritchie, 1993). This study develops a structural model to measure destination brand performance across different travel situations. The theory of planned behaviour (TpB) was utilised as a framework to underpin the consumer-based brand equity (CBBE) hierarchy to develop a model of destination brand performance. Research approach: A proposed model of destination brand performance was developed through a review of the literature. The first study was used to identify destination image attributes (the core construct) using an analysis of the literature, a document analysis, and personal interviews using the Repertory Test qualitative technique. Underpinned by Personal Construct Theory (PCT), the Repertory Test enables the elicitation of attributes consumers use to evaluate destinations when considering travel. Data was examined in the first study to i) identify any attribute differences in travel contexts and ii) create a scale for use in a questionnaire. A second study was conducted to test the proposed model using a questionnaire with eight groups of participants to assess four destinations across two travel contexts. The model was tested utilising structural equation modelling. Findings: The first study resulted in a list of 29 destination image attributes for use in a scale index. Attributes were assessed across travel contexts and few differences were identified. The second study assessed the congruence of destination brand identity (the destination marketing organisation’s desired image) and destination brand image (the actual perceptions held by consumers) using importance-performance analyses. Finally, the proposed model of destination brand performance was tested. Overall the data supported the model of destination brand performance across travel contexts and destinations. Additionally, this was compared to consumers’ decision sets, further supporting the model. Value: This research provides a contribution to the destination marketing literature through the development of a measurement of destination brand performance underpinned by TpB. Practically; it will provide destination marketing organisations with a tool to track destination brand performance, relative to key competing places, over time. This is important given the development of a destination brand is a long term endeavour.

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Abstract Purpose – The purpose of this paper is to identify stakeholders’ expectations of information to be conveyed in local authorities’ annual reports and to develop an index of best practice performance reporting. Design/methodology/approach – The paper describes the development of a disclosure index emphasizing the public interest aspect of reporting and the need to provide relevant and meaningful information to stakeholders. The index was crafted from a public accountability perspective and based on the expectations of stakeholders as reconciled and validated by a Delphi panel of experts. Findings – The wide scope of information that was dentified as being important for disclosure by local authorities is consistent with the public accountability paradigm which requires the reporting of comprehensive information (both financial and non financial), about the condition, performance, activities and progress of the entity. Originality/value – The research posits a model of best practice performance reporting for Malaysian, and other, local authorities to meet the need for greater accountability by these entities.

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The CCI-Creative City Index was commissioned in 2010 by the Beijing Academy of Science & Technology's Beijing Research Center for the Science of Science. John Hartley was asked to develop a new creative global city index. The brief was to improve on the existing indexes with a specific focus on creative industries and the sources of creative development. This report, by John Hartley, Jason Potts, Trent MacDonald, with Chris Erkunt and Carl Kufleitner, sets out the new model we have developed, which we call the CCI Creative City Index (CCI-CCI). It presents the results of a pilot application of the index to six cities: London, Cardiff, Berlin, Bremen, Melbourne and Brisbane. The index incorporates many elements from other global and creative city indexes, but also adds several new dimensions relating to creative industries scope, micro-productivity, and the economy of attention. The report and Excel spreadsheets of index calculations can be found on this site.

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Organizations from every industry sector seek to enhance their business performance and competitiveness through the deployment of contemporary information systems (IS), such as Enterprise Systems (ERP). Investments in ERP are complex and costly, attracting scrutiny and pressure to justify their cost. Thus, IS researchers highlight the need for systematic evaluation of information system success, or impact, which has resulted in the introduction of varied models for evaluating information systems. One of these systematic measurement approaches is the IS-Impact Model introduced by a team of researchers at Queensland University of technology (QUT) (Gable, Sedera, & Chan, 2008). The IS-Impact Model is conceptualized as a formative, multidimensional index that consists of four dimensions. Gable et al. (2008) define IS-Impact as "a measure at a point in time, of the stream of net benefits from the IS, to date and anticipated, as perceived by all key-user-groups" (p.381). The IT Evaluation Research Program (ITE-Program) at QUT has grown the IS-Impact Research Track with the central goal of conducting further studies to enhance and extend the IS-Impact Model. The overall goal of the IS-Impact research track at QUT is "to develop the most widely employed model for benchmarking information systems in organizations for the joint benefit of both research and practice" (Gable, 2009). In order to achieve that, the IS-Impact research track advocates programmatic research having the principles of tenacity, holism, and generalizability through extension research strategies. This study was conducted within the IS-Impact Research Track, to further generalize the IS-Impact Model by extending it to the Saudi Arabian context. According to Hofsted (2012), the national culture of Saudi Arabia is significantly different from the Australian national culture making the Saudi Arabian culture an interesting context for testing the external validity of the IS-Impact Model. The study re-visits the IS-Impact Model from the ground up. Rather than assume the existing instrument is valid in the new context, or simply assess its validity through quantitative data collection, the study takes a qualitative, inductive approach to re-assessing the necessity and completeness of existing dimensions and measures. This is done in two phases: Exploratory Phase and Confirmatory Phase. The exploratory phase addresses the first research question of the study "Is the IS-Impact Model complete and able to capture the impact of information systems in Saudi Arabian Organization?". The content analysis, used to analyze the Identification Survey data, indicated that 2 of the 37 measures of the IS-Impact Model are not applicable for the Saudi Arabian Context. Moreover, no new measures or dimensions were identified, evidencing the completeness and content validity of the IS-Impact Model. In addition, the Identification Survey data suggested several concepts related to IS-Impact, the most prominent of which was "Computer Network Quality" (CNQ). The literature supported the existence of a theoretical link between IS-Impact and CNQ (CNQ is viewed as an antecedent of IS-Impact). With the primary goal of validating the IS-Impact model within its extended nomological network, CNQ was introduced to the research model. The Confirmatory Phase addresses the second research question of the study "Is the Extended IS-Impact Model Valid as a Hierarchical Multidimensional Formative Measurement Model?". The objective of the Confirmatory Phase was to test the validity of IS-Impact Model and CNQ Model. To achieve that, IS-Impact, CNQ, and IS-Satisfaction were operationalized in a survey instrument, and then the research model was assessed by employing the Partial Least Squares (PLS) approach. The CNQ model was validated as a formative model. Similarly, the IS-Impact Model was validated as a hierarchical multidimensional formative construct. However, the analysis indicated that one of the IS-Impact Model indicators was insignificant and can be removed from the model. Thus, the resulting Extended IS-Impact Model consists of 4 dimensions and 34 measures. Finally, the structural model was also assessed against two aspects: explanatory and predictive power. The analysis revealed that the path coefficient between CNQ and IS-Impact is significant with t-value= (4.826) and relatively strong with â = (0.426) with CNQ explaining 18% of the variance in IS-Impact. These results supported the hypothesis that CNQ is antecedent of IS-Impact. The study demonstrates that the quality of Computer Network affects the quality of the Enterprise System (ERP) and consequently the impacts of the system. Therefore, practitioners should pay attention to the Computer Network quality. Similarly, the path coefficient between IS-Impact and IS-Satisfaction was significant t-value = (17.79) and strong â = (0.744), with IS-Impact alone explaining 55% of the variance in Satisfaction, consistent with results of the original IS-Impact study (Gable et al., 2008). The research contributions include: (a) supporting the completeness and validity of IS-Impact Model as a Hierarchical Multi-dimensional Formative Measurement Model in the Saudi Arabian context, (b) operationalizing Computer Network Quality as conceptualized in the ITU-T Recommendation E.800 (ITU-T, 1993), (c) validating CNQ as a formative measurement model and as an antecedent of IS Impact, and (d) conceptualizing and validating IS-Satisfaction as a reflective measurement model and as an immediate consequence of IS Impact. The CNQ model provides a framework to perceptually measure Computer Network Quality from multiple perspectives. The CNQ model features an easy-to-understand, easy-to-use, and economical survey instrument.

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Objective: Menopause is the consequence of exhaustion of the ovarian follicular pool. AMH, an indirect hormonal marker of ovarian reserve, has been recently proposed as a predictor for age at menopause. Since BMI and smoking status are relevant independent factors associated with age at menopause we evaluated whether a model including all three of these variables could improve AMH-based prediction of age at menopause. Methods: In the present cohort study, participants were 375 eumenorrheic women aged 19–44 years and a sample of 2,635 Italian menopausal women. AMH values were obtained from the eumenorrheic women. Results: Regression analysis of the AMH data showed that a quadratic function of age provided a good description of these data plotted on a logarithmic scale, with a distribution of residual deviates that was not normal but showed significant leftskewness. Under the hypothesis that menopause can be predicted by AMH dropping below a critical threshold, a model predicting menopausal age was constructed from the AMH regression model and applied to the data on menopause. With the AMH threshold dependent on the covariates BMI and smoking status, the effects of these covariates were shown to be highly significant. Conclusions: In the present study we confirmed the good level of conformity between the distributions of observed and AMH-predicted ages at menopause, and showed that using BMI and smoking status as additional variables improves AMH-based prediction of age at menopause.

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The CCI Creative City Index (CCI-CCI) is a new approach to the measurement and ranking of creative global cities. It is constructed over eight principal dimensions, each with multiple distinct elements. Some of these dimensions are familiar from other global city indexes, such as the MORI or GaWC indexes, which account for the size of creative industries, the scale of cultural amenities, or the flows of creative people and global connectedness. In addition to these indicators, the CCI-CCI contributes several new dimensions. These measure the demand side of creative participation, the attention economy, user-created content, and the productivity of socially networked consumers. Global creative cities can often seem alike, in respect of per-capita measures of factors such as public spending on cultural amenities, or the number of hotels and restaurants. This is to be expected when people and capital are relatively free to move, and where economic and political institutions are broadly comparable. However, we find that different cities can register far larger differences at the level of consumer-co-creation and especially digital creative ‘microproductivity’. To explain this finding, we review the logic and rationale of creative and global city index construction and present a review of previous and contemporary indexes. We set out the case for our new model of a creative city index by showing why greater attention to consumer co-creation and microproductivity are important, as well as examining how these factors have been previously overlooked. We show how we have CCI-CCI Creative City Index measured these additional factors and indicate the effect they have on creative and global city indexes. We then present the findings from a pilot study of six cities, two Australian, two German and two from the UK, to indicate how the new index is calculated and applied. Our results indicate much greater variance arising from the new arguments between cities.

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A new optimal control model of the interactions between a growing tumour and the host immune system along with an immunotherapy treatment strategy is presented. The model is based on an ordinary differential equation model of interactions between the growing tu- mour and the natural killer, cytotoxic T lymphocyte and dendritic cells of the host immune system, extended through the addition of a control function representing the application of a dendritic cell treat- ment to the system. The numerical solution of this model, obtained from a multi species Runge–Kutta forward-backward sweep scheme, is described. We investigate the effects of varying the maximum al- lowed amount of dendritic cell vaccine administered to the system and find that control of the tumour cell population is best effected via a high initial vaccine level, followed by reduced treatment and finally cessation of treatment. We also found that increasing the strength of the dendritic cell vaccine causes an increase in the number of natural killer cells and lymphocytes, which in turn reduces the growth of the tumour.

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Background There is growing consensus that a multidisciplinary, comprehensive and standardised process for assessing the fitness of older patients for chemotherapy should be undertaken to determine appropriate cancer treatment. Aim This study tested a model of cancer care for the older patient incorporating Comprehensive Geriatric Assessment (CGA), which aimed to ensure that 'fit' individuals amenable to active treatment were accurately identified; 'vulnerable' patients more suitable for modified or supportive regimens were determined; and 'frail 'individuals who would benefit most from palliative regimens were also identified and offered the appropriate level of care. Methods A consecutive-series n=178 sample of patients >65 years was recruited from a major Australian cancer centre. The following instruments were administered by an oncogeriatric nurse prior to treatment: Vulnerable Elders Survey-13; Cumulative Illness Rating Scale (Geriatric); Malnutrition Screening Tool; Mini-mental State Examination; Geriatric Depression Scale; Barthel Index; and Lawton Instrumental Activities of Daily Living Scale. Scores from these instruments were aggregated to predict patient fitness, vulnerability or frailty for chemotherapy. Physicians provided a concurrent (blinded) prediction of patient fitness, vulnerability or frailty based on their clinical assessment. Data were also collected on actual patient outcomes (eg treatment completed as predicted, treatment reduced) during monthly audits of patient trajectories. Data analysis Data analysis is underway. A sample of 178 is adequate to detect, with 90% power, kappa coefficients of agreement between CGA and physician assessments of K>0.90 ("almost perfect agreement"). Primary endpoints comprise a) whether the nurse-led CGA determination of fit, vulnerable or frail agrees with the oncologist's assessments of fit, vulnerable or frail and b) whether the CGA and physician assessments accurately predict actual patient outcomes. Conclusion An oncogeriatric nurse-led model of care is currently being developed from the results. We conclude with a discussion of the pivotal role of nurses in CGA-based models of care.