Numerical simulation of a fractional mathematical model for epidermal wound healing

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.

Relative entropy rate based model selection for linear hybrid system filters of uncertain nonlinear systems

Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.

A holistic blended design studio model : a basis for exploring and expanding learning opportunities

While the studio environment has been promoted as an ideal educational setting for project-based disciplines, few qualitative studies have been undertaken in a comprehensive way (Bose, 2007). This study responds to this need by adopting Grounded Theory methodology in a qualitative comparative approach. The research aims to explore the limitations and benefits of a face-to-face (f2f) design studio as well as a virtual design studio (VDS) as experienced by architecture students and educators at an Australian university in order to find the optimal combination for a blended environment to maximize learning. The main outcome is a holistic multidimensional blended model being sufficiently flexible to adapt to various setting, in the process, facilitating constructivist learning through self-determination, self-management, and personalization of the learning environment.

Towards a comprehensive and integrated knowledge-based urban development model : status quo and directions

Incorporating knowledge based urban development (KBUD) strategies in the urban planning and development process is a challenging and complex task due to the fragmented and incoherent nature of the existing KBUD models. This paper scrutinizes and compares these KBUD models with an aim of identifying key and common features that help in developing a new comprehensive and integrated KBUD model. The features and characteristics of the existing KBUD models are determined through a thorough literature review and the analysis reveals that while these models are invaluable and useful in some cases, lack of a comprehensive perspective and absence of full integration of all necessary development domains render them incomplete as a generic model. The proposed KBUD model considers all central elements of urban development and sets an effective platform for planners and developers to achieve more holistic development outcomes. The proposed model, when developed further, has a high potential to support researchers, practitioners and particularly city and state administrations that are aiming to a knowledge-based development.

g4c2c: A model for citizen engagement at arms' length from government

The recognition that Web 2.0 applications and social media sites will strengthen and improve interaction between governments and citizens has resulted in a global push into new e-democracy or Government 2.0 spaces. These typically follow government-to-citizen (g2c) or citizen-to-citizen (c2c) models, but both these approaches are problematic: g2c is often concerned more with service delivery to citizens as clients, or exists to make a show of ‘listening to the public’ rather than to genuinely source citizen ideas for government policy, while c2c often takes place without direct government participation and therefore cannot ensure that the outcomes of citizen deliberations are accepted into the government policy-making process. Building on recent examples of Australian Government 2.0 initiatives, we suggest a new approach based on government support for citizen-to-citizen engagement, or g4c2c, as a workable compromise, and suggest that public service broadcasters should play a key role in facilitating this model of citizen engagement.

Study of mechanical deformations on tough skinned vegetables during mechanical peeling process

Peeling is an essential phase of post harvesting and processing industry; however undesirable processing losses are unavoidable and always have been the main concern of food processing sector. There are three methods of peeling fruits and vegetables including mechanical, chemical and thermal, depending on the class and type of fruit. By comparison, the mechanical methods are the most preferred; mechanical peeling methods do not create any harmful effects on the tissue and they keep edible portions of produce fresh. The main disadvantage of mechanical peeling is the rate of material loss and deformations. Obviously reducing material losses and increasing the quality of the process has a direct effect on the whole efficiency of food processing industry, this needs more study on technological aspects of these operations. In order to enhance the effectiveness of food industrial practices it is essential to have a clear understanding of material properties and behaviour of tissues under industrial processes. This paper presents the scheme of research that seeks to examine tissue damage of tough skinned vegetables under mechanical peeling process by developing a novel FE model of the process using explicit dynamic finite element analysis approach. A computer model of mechanical peeling process will be developed in this study to stimulate the energy consumption and stress strain interactions of cutter and tissue. The available Finite Element softwares and methods will be applied to establish the model. Improving the knowledge of interactions and involves variables in food operation particularly in peeling process is the main objectives of the proposed study. Understanding of these interrelationships will help researchers and designer of food processing equipments to develop new and more efficient technologies. Presented work intends to review available literature and previous works has been done in this area of research and identify current gap in modelling and simulation of food processes.

Pragmatics, perceptions and strategies in Chinese college English learning

This study investigated Chinese College English students. perceptions of pragmatics, their pragmatic competence in selected speech acts, strategies they employed in acquiring pragmatic knowledge, as well as their general approach to learning English as a foreign language. The research was triggered by a national curriculum initiative that prioritizes the need for College English students to enhance their ability to use English effectively in different social interactions (Chinese College English Education and Supervisory Committee, 2007). The traditional "grammar-translation" and "examination-oriented" method is believed to have reduced Chinese College English students to what is dubbed "mute" and "deaf" language learners (Zhang, 2008; Zhao, 2009). Many students lack pragmatic knowledge on how to interpret discourse by relating utterances to their meanings, understanding the intention of language users, and how language is used in specific settings (Bachman & Palmer, 1996, 2010). There is an increasing body of literature on awareness-raising of the importance of pragmatic knowledge and strategies for classroom instruction. However, to date, researchers have tended to focus largely on the teaching of pragmatics, rather than on how students acquire pragmatic competence (Bardovi-Harlig & Dornyei, 1998; Du, 2004; Hou, 2007; Ruan, 2007; Schauer, 2009). It is this gap in the research that this study fills, with a focus on different types of pragmatic knowledge, learner perceptions of such knowledge, and learning strategies that College English students employ in the process of learning English in general, and pragmatics in particular. Three strands of theories of second language acquisition (Ellis, 1985, 1994): pragmatics (Levinson, 1983; Mey, 2001; Yule, 1996), intercultural communications (Kramsch, 1998; Samovar & Porter, 1997; Samovar, Porter & McDaniel, 2009) and English as a lingua franca (ELF) (Canagarajah, 2006; Firth, 1996; Pennycook, 2010) were employed to establish a conceptual framework for data collection and analyses. Key constructs derived from the three related theories helped to form a typology for a detailed examination and theorization of the empirical evidence gathered from different sources. Four research instruments: a questionnaire (N=237), Discourse Completion Tasks (DCTs) (N=55), focus group interviews (N=18), and a textbook tasks analysis were employed to collect data for this systematic inquiry. Data collected by different instruments were analyzed and compared by way of a triangulation to enhance its validity and reliability. Major findings derived from different sources highlighted that, although College English students were grammatically advanced language learners, they displayed limited pragmatic knowledge and a highly restricted repertoire of language learning strategies. The majority of the respondents, however, believed that pragmatic knowledge was as important as linguistic knowledge in the process of developing communicative competence for interaction in different contexts. It was argued that a combination of a less than sufficient English proficiency, limited knowledge of pragmatics, inadequate language materials and tasks, and a small stock of language learning strategies, were a major hindrance to effective learning and communication, resulting in pragmatic failures in many intercultural communication situations. As the first systematic study of how Chinese College English students learned pragmatics, the research provided a solid empirical base for developing a tentative model for the learning of pragmatics in a College English classroom in China and similar educational contexts. The model was strengthened by a unique combination of theories of pragmatics, intercultural communication and ELF. Findings from this research provided insights into how Chinese College English students perceived pragmatics in the English as foreign language (EFL) curriculum, the processes of learning, as well as strategies they utilized in developing linguistic and pragmatic knowledge and competence.

Is the unigram relevance model term independent? Classifying term dependencies in query expansion

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.

An interpretation of current progress towards an industry model for Queensland's surveying and mapping industry

A strongly progressive surveying and mapping industry depends on a shared understanding of the industry as it exists, some shared vision or imagination of what the industry might become, and some shared action plan capable of bringing about a realisation of that vision. The emphasis on sharing implies a need for consensus reached through widespread discussion and mutual understanding. Unless this occurs, concerted action is unlikely. A more likely outcome is that industry representatives will negate each other's efforts in their separate bids for progress. The process of bringing about consensual viewpoints is essentially one of establishing an industry identity. Establishing the industry's identity and purpose is a prerequisite for rational development of the industry's education and training, its promotion and marketing, and operational research that can deal .with industry potential and efficiency. This paper interprets evolutionary developments occurring within Queensland's surveying and mapping industry within a framework that sets out logical requirements for a viable industry.

Leadership practices of Kuwaiti Secondary School Principals for embedding ICT

Globalisation and the emergence of knowledge-based economies have forced many countries to reform their education system. The enhancement of human capital to meet modern day demands of a knowledge economy, and equip the new generation with the capacity to meet the challenges of the 21st Century has become a priority. This change is particularly necessary in economies typical of countries, such as Kuwait, which have been dependent on the exploitation of non-renewable natural resources. Transiting from a resource-based economy to an economy based on knowledge and intellectual skills poses a key challenge for an education system. Significant in the development of this new economy has been the expansion of Information Communication Technology (ICT). In education, in particular, ICT is a tool for transforming the education setting. However, transformation is only successful where there are effective change management strategies and appropriate leadership. At the school level, rapid changes have affected the role that principals take particularly in relation to leading the change process. Therefore, this study investigated the leadership practices of school principals for embedding ICT into schools. The case study assessed two Kuwaiti secondary schools; both schools had well established ICT programs. The mode of data collection used a mixed-methods design, to address the purpose of the study, namely, to examine the leadership practices of school principals when managing the change processes associated with embedding ICT in the context of Kuwait. A theoretical model of principal leadership, developed, from the literature, documented and analysed the practices of the respective school principals. The study used the following five data sources: (a) face to face interviews (with each school principal), and two focus group interviews (with five teachers and five students, from each school); (b) school documents (related to the implementation and embedding of ICT); (c) one survey (of all teachers in each school); (d) an open-ended questionnaire (of participating principals and teachers); and (e) the observation of ICT activities (PD ICT activities and instruction meetings). The study revealed a range of strategies used by the principals and aligned with the theoretical perspective. However, these strategies needed to be refined and selectively used to fit the Kuwait context, both culturally and organisationally. The principals of Schools A and B employed three key strategies to maximise the impact on the teaching staff incorporating ICT into their teaching and learning practices. These strategies were: (a) encouragement for teaching staff to implement ICT in their teaching; (b) support to meet the material and human needs of teaching staff using ICT; and (c) provision of instructions and guidance for teaching staff in how and why such behaviours and practices should be performed. The strategies provided the basic leadership practices required to construct a successful ICT embedded implementation process. Hence, a revised model of leadership that has applicability in the adoption of ICT in Kuwait was developed. The findings provide a better understanding of how a school principal’s leadership practices impact upon the ICT embedding process. Hence, the outcome of this study informs emerging countries, which are also undergoing major change related to ICT, for example, other members of the Cooperation Council for the Arab States of the Gulf. From an educational perspective, this knowledge has the potential to support ICT-based learning environments that will help educational practitioners to effectively integrate ICT into teaching and learning that will facilitate students’ ICT engagement, and prepare them for the ICT development challenges that are associated with the new economy; this is achieved by increasing students’ knowledge and performance. Further, the study offers practical strategies that have been shown to work for school principals leading ICT implementation in Kuwait. These strategies include how to deal with the shortage in schools’ budgets, and the promotion of the ICT vision, as well as developing approaches to build collaborative culture in the schools.

Dirichlet process mixture models for unsupervised clustering of symptoms in Parkinson's disease

In this paper, the goal of identifying disease subgroups based on differences in observed symptom profile is considered. Commonly referred to as phenotype identification, solutions to this task often involve the application of unsupervised clustering techniques. In this paper, we investigate the application of a Dirichlet Process mixture (DPM) model for this task. This model is defined by the placement of the Dirichlet Process (DP) on the unknown components of a mixture model, allowing for the expression of uncertainty about the partitioning of observed data into homogeneous subgroups. To exemplify this approach, an application to phenotype identification in Parkinson’s disease (PD) is considered, with symptom profiles collected using the Unified Parkinson’s Disease Rating Scale (UPDRS). Clustering, Dirichlet Process mixture, Parkinson’s disease, UPDRS.

Modelling the flow of cane constituents in the milling process

A model has been developed to track the flow of cane constituents through the milling process. While previous models have tracked the flow of fibre, brix and water through the process, this model tracks the soluble and insoluble solid cane components using modelling theory and experiment data, assisting in further understanding the flow of constituents into mixed juice and final bagasse. The work provided an opportunity to understand the factors which affect the distribution of the cane constituents in juice and bagasse. Application of the model should lead to improvements in the overall performance of the milling train.

Bayesian hierarchical models in statistical quality control methods to improve healthcare in hospitals

Quality oriented management systems and methods have become the dominant business and governance paradigm. From this perspective, satisfying customers’ expectations by supplying reliable, good quality products and services is the key factor for an organization and even government. During recent decades, Statistical Quality Control (SQC) methods have been developed as the technical core of quality management and continuous improvement philosophy and now are being applied widely to improve the quality of products and services in industrial and business sectors. Recently SQC tools, in particular quality control charts, have been used in healthcare surveillance. In some cases, these tools have been modified and developed to better suit the health sector characteristics and needs. It seems that some of the work in the healthcare area has evolved independently of the development of industrial statistical process control methods. Therefore analysing and comparing paradigms and the characteristics of quality control charts and techniques across the different sectors presents some opportunities for transferring knowledge and future development in each sectors. Meanwhile considering capabilities of Bayesian approach particularly Bayesian hierarchical models and computational techniques in which all uncertainty are expressed as a structure of probability, facilitates decision making and cost-effectiveness analyses. Therefore, this research investigates the use of quality improvement cycle in a health vii setting using clinical data from a hospital. The need of clinical data for monitoring purposes is investigated in two aspects. A framework and appropriate tools from the industrial context are proposed and applied to evaluate and improve data quality in available datasets and data flow; then a data capturing algorithm using Bayesian decision making methods is developed to determine economical sample size for statistical analyses within the quality improvement cycle. Following ensuring clinical data quality, some characteristics of control charts in the health context including the necessity of monitoring attribute data and correlated quality characteristics are considered. To this end, multivariate control charts from an industrial context are adapted to monitor radiation delivered to patients undergoing diagnostic coronary angiogram and various risk-adjusted control charts are constructed and investigated in monitoring binary outcomes of clinical interventions as well as postintervention survival time. Meanwhile, adoption of a Bayesian approach is proposed as a new framework in estimation of change point following control chart’s signal. This estimate aims to facilitate root causes efforts in quality improvement cycle since it cuts the search for the potential causes of detected changes to a tighter time-frame prior to the signal. This approach enables us to obtain highly informative estimates for change point parameters since probability distribution based results are obtained. Using Bayesian hierarchical models and Markov chain Monte Carlo computational methods, Bayesian estimators of the time and the magnitude of various change scenarios including step change, linear trend and multiple change in a Poisson process are developed and investigated. The benefits of change point investigation is revisited and promoted in monitoring hospital outcomes where the developed Bayesian estimator reports the true time of the shifts, compared to priori known causes, detected by control charts in monitoring rate of excess usage of blood products and major adverse events during and after cardiac surgery in a local hospital. The development of the Bayesian change point estimators are then followed in a healthcare surveillances for processes in which pre-intervention characteristics of patients are viii affecting the outcomes. In this setting, at first, the Bayesian estimator is extended to capture the patient mix, covariates, through risk models underlying risk-adjusted control charts. Variations of the estimator are developed to estimate the true time of step changes and linear trends in odds ratio of intensive care unit outcomes in a local hospital. Secondly, the Bayesian estimator is extended to identify the time of a shift in mean survival time after a clinical intervention which is being monitored by riskadjusted survival time control charts. In this context, the survival time after a clinical intervention is also affected by patient mix and the survival function is constructed using survival prediction model. The simulation study undertaken in each research component and obtained results highly recommend the developed Bayesian estimators as a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances as well as industrial and business contexts. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The empirical results and simulations indicate that the Bayesian estimators are a strong alternative in change point estimation within quality improvement cycle in healthcare surveillances. The superiority of the proposed Bayesian framework and estimators are enhanced when probability quantification, flexibility and generalizability of the developed model are also considered. The advantages of the Bayesian approach seen in general context of quality control may also be extended in the industrial and business domains where quality monitoring was initially developed.

A hybrid model for studying spatial aspects of infectious diseases

We consider a hybrid model, created by coupling a continuum and an agent-based model of infectious disease. The framework of the hybrid model provides a mechanism to study the spread of infection at both the individual and population levels. This approach captures the stochastic spatial heterogeneity at the individual level, which is directly related to deterministic population level properties. This facilitates the study of spatial aspects of the epidemic process. A spatial analysis, involving counting the number of infectious agents in equally sized bins, reveals when the spatial domain is nonhomogeneous.

Practical stability of approximating discrete-time filters with respect to model mismatch

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Practical stability is established in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.