982 resultados para Capability approach


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International comparison is complicated by the use of different terms, classification methods, policy frameworks and system structures, not to mention different languages and terminology. Multi-case studies can assist in the understanding of the influence wielded by cultural, social, economic, historical and political forces upon educational decisions, policy construction and changes over time. But case studies alone are not enough. In this paper, we argue for an ecological or scaled approach that travels through macro, meso and micro levels to build nested case-studies to allow for more comprehensive analysis of the external and internal factors that shape policy-making and education systems. Such an approach allows for deeper understanding of the relationship between globalizing trends and policy developments.

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Student satisfaction data has been collected on a national basis in Australia since 1972. In recent years this data has been used by federal government agencies to allocate funding, and by students in selecting their universities of choice. The purpose of this paper is to present the findings of an action research project designed to identify and implement unit improvement initiatives over a three year period for an underperforming unit. This research utilises student survey data and teacher reflections to identify areas of unit improvement, with a view to aligning learning experiences, teaching and assessment to learning outcomes and improved student satisfaction. This research concludes that whilst a voluntary student survey system may be imperfect, it nevertheless provides important data that can be utilised to the benefit of the unit, learning outcomes and student satisfaction ratings, as well as wider course related outcomes. Extrapolation of these findings is recommended to other underperforming units.

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The Internet is one of the most significant information and communication technologies to emerge during the end of the last century. It created new and effective means by which individuals and groups communicate. These advances led to marked institutional changes most notably in the realm of commercial exchange: it did not only provide the high-speed communication infrastructure to business enterprises; it also opened them to the global consumer base where they could market their products and services. Commercial interests gradually dominated Internet technology over the past several years and have been a factor in the increase of its user population and enhancement of infrastructure. Such commercial interests fitted comfortably within the structures of the Philippine government. As revealed in the study, state policies and programs make use of Internet technology as an enabler of commercial institutional reforms using traditional economic measures. Yet, despite efforts to maximize the Internet as an enabler for market-driven economic growth, the accrued benefits are yet to come about; it is largely present only in major urban areas and accessible to a small number of social groups. The failure of the Internet’s developmental capability can be traced back to the government’s wholesale adoption of commercial-centered discourse. The Internet’s developmental gains (i.e. instrumental, communicative and emancipatory) and features, which were always there since its inception, have been visibly left out in favor of its commercial value. By employing synchronic and diachronic analysis, it can be shown that the Internet can be a vital technology in promoting genuine social development in the Philippines. In general, the object is to realize a social environment of towards a more inclusive and participatory application of Internet technology, equally aware of the caveats or risks the technology may pose. It is argued further that there is a need for continued social scientific research regarding the social as and developmental implications of Internet technology at local level structures, such social sectors, specific communities and organizations. On the meta-level, such approach employed in this research can be a modest attempt in increasing the calculus of hope especially among the marginalized Filipino sectors, with the use of information and communications technologies. This emerging field of study—tentatively called Progressive Informatics—must emanate from the more enlightened social sectors, namely: the non-government, academic and locally-based organizations.

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A critical step in the dissemination of ovarian cancer is the formation of multicellular spheroids from cells shed from the primary tumour. The objectives of this study were to apply bioengineered three-dimensional (3D) microenvironments for culturing ovarian cancer spheroids in vitro and simultaneously to build on a mathematical model describing the growth of multicellular spheroids in these biomimetic matrices. Cancer cells derived from human epithelial ovarian carcinoma were embedded within biomimetic hydrogels of varying stiffness and grown for up to 4 weeks. Immunohistochemistry, imaging and growth analyses were used to quantify the dependence of cell proliferation and apoptosis on matrix stiffness, long-term culture and treatment with the anti-cancer drug paclitaxel. The mathematical model was formulated as a free boundary problem in which each spheroid was treated as an incompressible porous medium. The functional forms used to describe the rates of cell proliferation and apoptosis were motivated by the experimental work and predictions of the mathematical model compared with the experimental output. This work aimed to establish whether it is possible to simulate solid tumour growth on the basis of data on spheroid size, cell proliferation and cell death within these spheroids. The mathematical model predictions were in agreement with the experimental data set and simulated how the growth of cancer spheroids was influenced by mechanical and biochemical stimuli including matrix stiffness, culture duration and administration of a chemotherapeutic drug. Our computational model provides new perspectives on experimental results and has informed the design of new 3D studies of chemoresistance of multicellular cancer spheroids.

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Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

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On average, 560 fatal run-off-road crashes occur annually in Australia and 135 in New Zealand. In addition, there are more than 14,000 run-off-road crashes causing injuries each year across both countries. In rural areas, run-off-road casualty crashes constitute 50-60% of all casualty crashes. Their severity is particularly high with more than half of those involved sustaining fatal or serious injuries. This paper reviews the existing approach to roadside hazard risk assessment, selection of clear zones and hazard treatments. It proposes a modified approach to roadside safety evaluation and management. It is a methodology based on statistical modelling of run-off-road casualty crashes, and application of locally developed crash modification factors and severity indices. Clear zones, safety barriers and other roadside design/treatment options are evaluated with a view to minimise fatal and serious injuries – the key Safe System objective. The paper concludes with a practical demonstration of the proposed approach. The paper is based on findings from a four-year Austroads research project into improving roadside safety in the Safe System context.

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In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge-Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E coli, and conclude with a discussion on the significance of this work. (C) 2004 Elsevier Ltd. All rights reserved.

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This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are generally difficult to learn to control due to their elastic properties preventing standard model learning techniques from being used, such as learning computed torque control. This paper demonstrates the capability of LWL-MPC to perform online and incremental learning while controlling the joint positions of a real three Degree of Freedom (DoF) EJR. An experiment on a real EJR is presented and LWL-MPC is shown to successfully learn to control the system to follow two different figure of eight trajectories.

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The selection of optimal camera configurations (camera locations, orientations etc.) for multi-camera networks remains an unsolved problem. Previous approaches largely focus on proposing various objective functions to achieve different tasks. Most of them, however, do not generalize well to large scale networks. To tackle this, we introduce a statistical formulation of the optimal selection of camera configurations as well as propose a Trans-Dimensional Simulated Annealing (TDSA) algorithm to effectively solve the problem. We compare our approach with a state-of-the-art method based on Binary Integer Programming (BIP) and show that our approach offers similar performance on small scale problems. However, we also demonstrate the capability of our approach in dealing with large scale problems and show that our approach produces better results than 2 alternative heuristics designed to deal with the scalability issue of BIP.

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A firm, as a dynamic, evolving, and quasi-autonomous system of knowledge production and application, develops knowledge management capability (KMC) through strategic learning in order to sustain competitive advantages in a dynamic environment. Knowledge governance mechanisms and knowledge processes connect and interact with each other forming learning mechanisms, which carry out double loop learning that drives genesis and evolution of KMC to modify operating routines that effect desired performance. This paper reports a study that was carried out within a context of construction contractors, a type of project-based firms, operating within the dynamic Hong Kong construction market. A multiple-case design was used to incorporate evidence from the literature and interviews, with the help of system dynamics modeling, to visualize the evolution of KMC. The study demonstrates the feasibility to visualize how a firm's KMC matches its operating environment over time. The findings imply that knowledge management (KM) applications can be better planned and controlled through evaluation of KM performance over time from a capability perspective.

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Recent literature has argued that environmental efficiency (EE), which is built on the materials balance (MB) principle, is more suitable than other EE measures in situations where the law of mass conversation regulates production processes. In addition, the MB-based EE method is particularly useful in analysing possible trade-offs between cost and environmental performance. Identifying determinants of MB-based EE can provide useful information to decision makers but there are very few empirical investigations into this issue. This article proposes the use of data envelopment analysis and stochastic frontier analysis techniques to analyse variation in MB-based EE. Specifically, the article develops a stochastic nutrient frontier and nutrient inefficiency model to analyse determinants of MB-based EE. The empirical study applies both techniques to investigate MB-based EE of 96 rice farms in South Korea. The size of land, fertiliser consumption intensity, cost allocative efficiency, and the share of owned land out of total land are found to be correlated with MB-based EE. The results confirm the presence of a trade-off between MB-based EE and cost allocative efficiency and this finding, favouring policy interventions to help farms simultaneously achieve cost efficiency and MP-based EE.

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Product rating systems are very popular on the web, and users are increasingly depending on the overall product ratings provided by websites to make purchase decisions or to compare various products. Currently most of these systems directly depend on users’ ratings and aggregate the ratings using simple aggregating methods such as mean or median [1]. In fact, many websites also allow users to express their opinions in the form of textual product reviews. In this paper, we propose a new product reputation model that uses opinion mining techniques in order to extract sentiments about product’s features, and then provide a method to generate a more realistic reputation value for every feature of the product and the product itself. We considered the strength of the opinion rather than its orientation only. We do not treat all product features equally when we calculate the overall product reputation, as some features are more important to customers than others, and consequently have more impact on customers buying decisions. Our method provides helpful details about the product features for customers rather than only representing reputation as a number only.

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We present a virtual test bed for network security evaluation in mid-scale telecommunication networks. Migration from simulation scenarios towards the test bed is supported and enables researchers to evaluate experiments in a more realistic environment. We provide a comprehensive interface to manage, run and evaluate experiments. On basis of a concrete example we show how the proposed test bed can be utilized.

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Decades of research has now produced a rich description of the destruction child sexual assault (CSA) can cause in an individual’s life. Post-Traumatic Stress Disorder (PTSD), Dissociative Identity Disorder, Borderline Personality Disorder, depression, anxiety, Panic Disorder, intimacy issues, substance abuse, self-harm, and suicidal ideation and attempts, are some of the negative outcomes that have been attributed to this type of traumatic experience. Psychology's tendency to dwell within a pathological paradigm, along with popular media who espouse a similar rhetoric, would lead to the belief that once exposed to CSA, an individual is forever at the mercy of dealing with a massive array of accompanying negative effects. While the possibility of these outcomes in those who have experienced CSA is not at all denied, it is also timely to consider an alternative paradigm that up until now has received a paucity of attention in the sexual assault literature. That is to say, not only do people have the ability to work through the painful and personal impacts of CSA, but for some people the process of recovery may provide a catalyst for positive life changes that have been termed post-traumatic growth (Tedeschi & Calhoun, 1995). To begin with in this chapter, the negative sequale’ of childhood sexual assault it discussed initially. Inherent to this discussion are questions of measurement and definitions of sexual assault. The chapter highlights ways in which the term CSA has been defined and hence operationalised in research, and the myriad problems, confusions, and inconclusive findings that have plagued the sexual assault literature. Following this is a review of the sparse literature that has conceptualised CSA from a more salutogenic (Antonovsky, 1979) theoretical orientation. It is argued that a salutogenic approach to intervention and to research in this area, provides a more useful way of promoting healing and the gaining of wisdom, but importantly does not negate the very real distress that may accompany growth. This chapter will then present a case study to elucidate the theoretical and empirical literature discussed using the words of a survivor. Finally, the chapter concludes with implications for therapeutic practice, which includes some practical ways in which to promote adaptation to life within the context of having survived this insidious crime.

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Childhood sexual assault (CSA) is one of the most devastating of all traumatic experiences with population studies documenting survivors experiencing higher levels of pathology than general trends in survivors of other traumatic experiences. Yet recent research has demonstrated that far from being permanently crippled by their experiences, many adult survivors of CSA manage to heal and move forward in their lives to experience a rich and fulfilling existence. In this paper two case studies are presented to provide a detailed account of how a person who has experienced CSA may find a pathway to healing. Moreover, data demonstrates that meaning making, spiritual or otherwise, is a pivotal part of acceptance of CSA and ensuing growth. The case studies highlight the unique journeys of two women and the underlying similarities in their pathway to healing. Clinical implications of the research are discussed and specific strategies for encouraging healing and growth are outlined.