939 resultados para connection weight approach


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Retrieving information from Twitter is always challenging due to its large volume, inconsistent writing and noise. Most existing information retrieval (IR) and text mining methods focus on term-based approach, but suffers from the problems of terms variation such as polysemy and synonymy. This problem deteriorates when such methods are applied on Twitter due to the length limit. Over the years, people have held the hypothesis that pattern-based methods should perform better than term-based methods as it provides more context, but limited studies have been conducted to support such hypothesis especially in Twitter. This paper presents an innovative framework to address the issue of performing IR in microblog. The proposed framework discover patterns in tweets as higher level feature to assign weight for low-level features (i.e. terms) based on their distributions in higher level features. We present the experiment results based on TREC11 microblog dataset and shows that our proposed approach significantly outperforms term-based methods Okapi BM25, TF-IDF and pattern based methods, using precision, recall and F measures.

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To protect the health information security, cryptography plays an important role to establish confidentiality, authentication, integrity and non-repudiation. Keys used for encryption/decryption and digital signing must be managed in a safe, secure, effective and efficient fashion. The certificate-based Public Key Infrastructure (PKI) scheme may seem to be a common way to support information security; however, so far, there is still a lack of successful large-scale certificate-based PKI deployment in the world. In addressing the limitations of the certificate-based PKI scheme, this paper proposes a non-certificate-based key management scheme for a national e-health implementation. The proposed scheme eliminates certificate management and complex certificate validation procedures while still maintaining security. It is also believed that this study will create a new dimension to the provision of security for the protection of health information in a national e-health environment.

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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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Incorporating design thinking as a generic capability at a school level is needed to ensure future generations are empowered for business innovation and active citizenship. This paper describes the methodology of an investigation into modelling design led innovation approaches from the business sector to secondary education, as part of a larger study. It builds on a previously discussed research agenda by outlining the scope, significance and limitations of currently available research in this area, examining an action research methodology utilising an Australian design immersion program case study, and discussing implications and future work. It employs a triangulated approach encompassing thematic analysis of qualitative data collection from student focus groups, semi-structured convergent interviews with teachers and facilitators, and student journals. Eventual outcomes will be reviewed and analysed within the framework of a proposed innovation matrix model for educational growth, synthesising principles responding to 21st century student outcomes. It is anticipated this research will inform a successful design led secondary education innovation model, facilitating new engagement frameworks between tertiary and secondary education sectors, as well as providing new insight into the suitability of action research in prototyping social innovation in Australia.

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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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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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The dynamic capabilities view (DCV) focuses on renewal of firms’ strategic knowledge resources so as to sustain competitive advantage within turbulent markets. Within the context of the DCV, the focus of knowledge management (KM) is to develop the KMC through deploying knowledge governance mechanisms that are conducive to facilitating knowledge processes so as to produce superior business performance over time. The essence of KM performance evaluation is to assess how well the KMC is configured with knowledge governance mechanisms and processes that enable a firm to achieve superior performance through matching its knowledge base with market needs. However, little research has been undertaken to evaluate KM performance from the DCV perspective. This study employed a survey study design and adopted hypothesis-testing approaches to develop a capability-based KM evaluation framework (CKMEF) that upholds the basic assertions of the DCV. Under the governance of the framework, a KM index (KMI) and a KM maturity model (KMMM) were derived not only to indicate the extent to which a firm’s KM implementations fulfill its strategic objectives, and to identify the evolutionary phase of its KMC, but also to bench-mark the KMC in the research population. The research design ensured that the evaluation framework and instruments have statistical significance and good generalizabilty to be applied in the research population, namely construction firms operating in the dynamic Hong Kong construction market. The study demonstrated the feasibility of quantitatively evaluating the development of the KMC and revealing the performance heterogeneity associated with the development.

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A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that "the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy". However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.

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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.