907 resultados para Link variables method


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Collaborative contracting has emerged over the past 15 years as an innovative project delivery framework that is particularly suited to infrastructure projects. Australia leads the world in the development of project and program alliance approaches to collaborative delivery. These approaches are considered to promise superior project results. However, very little is known about the learning routines that are most widely used in support of collaborative projects in general and alliance projects in particular. The literature on absorptive capacity and dynamic capabilities indicates that such learning enhances project performance. The learning routines employed at corporate level during the operation of collaborative infrastructure projects in Australia were examined through a large survey conducted in 2013. This paper presents a descriptive summary of the preliminary findings. The survey captured the experiences of 320 practitioners of collaborative construction projects, including public and private sector clients, contractors, consultants and suppliers (three per cent of projects were located in New Zealand, but for brevity’s sake the sample is referred to as Australian). The majority of projects identified used alliances (78.6%); whilst 9% used Early Contractor Involvement (ECI) contracts and 2.7% used Early Tender Involvement contracts, which are ‘slimmer’ types of collaborative contract. The remaining 9.7% of respondents used traditional contracts that employed some collaborative elements. The majority of projects were delivered for public sector clients (86.3%), and/or clients experienced with asset procurement (89.6%). All of the projects delivered infrastructure assets; one third in the road sector, one third in the water sector, one fifth in the rail sector, and the rest spread across energy, building and mining. Learning routines were explored within three interconnected phases: knowledge exploration, transformation and exploitation. The results show that explorative and exploitative learning routines were applied to a similar extent. Transformative routines were applied to a relatively low extent. It was also found that the most highly applied routine is ‘regularly applying new knowledge to collaborative projects’; and the least popular routine was ‘staff incentives to encourage information sharing about collaborative projects’. Future research planned by the authors will examine the impact of these routines on project performance.

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Guaranteeing the quality of extracted features that describe relevant knowledge to users or topics is a challenge because of the large number of extracted features. Most popular existing term-based feature selection methods suffer from noisy feature extraction, which is irrelevant to the user needs (noisy). One popular method is to extract phrases or n-grams to describe the relevant knowledge. However, extracted n-grams and phrases usually contain a lot of noise. This paper proposes a method for reducing the noise in n-grams. The method first extracts more specific features (terms) to remove noisy features. The method then uses an extended random set to accurately weight n-grams based on their distribution in the documents and their terms distribution in n-grams. The proposed approach not only reduces the number of extracted n-grams but also improves the performance. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms the state-of-art methods underpinned by Okapi BM25, tf*idf and Rocchio.

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Developer paid charges or contributions are a commonly used infrastructure funding mechanism for local governments. However, developers claim that these costs are merely passed on to home buyers, with adverse effects to housing affordability. Despite a plethora of government reports and industry advocacy, there remains no empirical evidence in Australia to confirm or quantify this passing on effect to home buyers and hence no data for which governments to base policy decision upon. This paper examines the question of who really pays for urban infrastructure and the impact of infrastructure charges on housing affordability. It presents the findings of a number of international empirical studies that provide evidence that infrastructure charges do increase house prices. Based on international findings, and in the absence of any Australian research, then these findings suggest that if the international findings are transferable, then there is empirical evidence to support the proposition that developer paid infrastructure charges are a significant contributor to increasing house prices.

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Dengue virus (DENV) transmission in Australia is driven by weather factors and imported dengue fever (DF) cases. However, uncertainty remains regarding the threshold effects of high-order interactions among weather factors and imported DF cases and the impact of these factors on autochthonous DF. A time-series regression tree model was used to assess the threshold effects of natural temporal variations of weekly weather factors and weekly imported DF cases in relation to incidence of weekly autochthonous DF from 1 January 2000 to 31 December 2009 in Townsville and Cairns, Australia. In Cairns, mean weekly autochthonous DF incidence increased 16.3-fold when the 3-week lagged moving average maximum temperature was <32 °C, the 4-week lagged moving average minimum temperature was ≥24 °C and the sum of imported DF cases in the previous 2 weeks was >0. When the 3-week lagged moving average maximum temperature was ≥32 °C and the other two conditions mentioned above remained the same, mean weekly autochthonous DF incidence only increased 4.6-fold. In Townsville, the mean weekly incidence of autochthonous DF increased 10-fold when 3-week lagged moving average rainfall was ≥27 mm, but it only increased 1.8-fold when rainfall was <27 mm during January to June. Thus, we found different responses of autochthonous DF incidence to weather factors and imported DF cases in Townsville and Cairns. Imported DF cases may also trigger and enhance local outbreaks under favorable climate conditions.

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We have developed a method to test the cytotoxicity of wound dressings, ointments, creams and gels used in our Burn Centre, by placing them on a permeable Nunc Polycarbonate cell culture insert, incubated with a monolayer of cells (HaCaTs and primary human keratinocytes). METHODS: We performed two different methods to determine the relative toxicity to cells. (1) Photo visualisation: The dressings or compounds were positioned on the insert's membrane which was placed onto the monolayer tissue culture plate. After 24 h the surviving adherent cells were stained with Toluidine Blue and photos of the plates were taken. The acellular area of non-adherent dead cells which had been washed off with buffer was measured as a percentage of the total area of the plate. (2) Cell count of surviving cells: After 24 h incubation with the test material, the remaining cells were detached with trypsin, spun down and counted in a Haemocytometer with Trypan Blue, which differentiates between live and dead cells. RESULTS: Seventeen products were tested. The least cytotoxic products were Melolite, White soft Paraffin and Chlorsig1% Ointment. Some cytotoxicity was shown with Jelonet, Mepitel((R)), PolyMem((R)), DuoDerm((R)) and Xeroform. The most cytotoxic products included those which contained silver or Chlorhexidine and Paraffin Cream a moisturizer which contains the preservative Chlorocresol. CONCLUSION: This in vitro cell culture insert method allows testing of agents without direct cell contact. It is easy and quick to perform, and should help the clinician to determine the relative cytotoxicity of various dressings and the optimal dressing for each individual wound.

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Tobacco use is a major public health concern, and is associated with a number of mental illnesses as well as increased alcohol/other drug (AOD). Research into treatment for individuals experiencing such comorbidities is limited. Participants (n = 447) were those enrolled in the Depression and Alcohol Integrated and Single-focused Interventions project (Baker et al. 2010), and the Self Help for Alcohol/other drugs and DEpression project (Kay-Lambkin et al. Medical Journal of Australia 195:S44-S50, 2011a, Journal of Medical Internet Research 13(1):e11p11, b), who reported current depression and hazardous alcohol use at entry to the study. Smoking cessation was not targeted in, nor a goal of, treatment. After controlling for socioeconomic variables, tobacco use was not associated with higher levels of depressive symptoms at baseline; however heavy smokers (30+ cigarettes per day) consumed significantly more alcohol at baseline than did non-smokers (13 vs. 9 standard drinks per day). Baseline smoking severity did not impact on depression or alcohol use outcomes over a 12-month period. Reductions in tobacco use between baseline and 3-month follow-up were significantly associated with reductions in depression and alcohol consumption over the same time period. The study results suggest that tobacco use does not interfere with treatment for depression and alcohol use problems, and adds weight to the idea of considering specific treatment for tobacco use in the context of treatment for alcohol/other drug use.

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It is widely acknowledged that effective asset management requires an interdisciplinary approach, in which synergies should exist between traditional disciplines such as: accounting, engineering, finance, humanities, logistics, and information systems technologies. Asset management is also an important, yet complex business practice. Business process modelling is proposed as an approach to manage the complexity of asset management through the modelling of asset management processes. A sound foundation for the systematic application and analysis of business process modelling in asset management is, however, yet to be developed. Fundamentally, a business process consists of activities (termed functions), events/states, and control flow logic. As both events/states and control flow logic are somewhat dependent on the functions themselves, it is a logical step to first identify the functions within a process. This research addresses the current gap in knowledge by developing a method to identify functions common to various industry types (termed core functions). This lays the foundation to extract such functions, so as to identify both commonalities and variation points in asset management processes. This method describes the use of a manual text mining and a taxonomy approach. An example is presented.