28 resultados para Project 2002-005-C : Decision Support Tools for Concrete Infrastructure rehabilitation


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The Moreton Bay Waterways and Catchments Partnership, now branded the Healthy Waterways Partnership, has built on the experience of the past 15 years here in South East Queensland (SEQ). It focuses on water quality and the ecosystem health of our freshwater, estuarine and marine systems through the implementation of actions by individual partners and the collective oversight of a regional work program that assists partners to prioritise their investments and address emerging issues. This regional program includes monitoring, reporting, marketing and communication, development of decision support tools, research that is directed to problem solving, and maintaining extensive consultative and engagement arrangements. The Partnership has produced information-based outcomes which have led to significant cost savings in the protection of water quality and ecosystem resources by its stakeholders. This has been achieved by: – providing a clear focus for management actions that has ownership of governments, industry and community; – targeted scientific research to address issues requiring appropriate management actions; – management actions based on a sound understanding of the waterways and rigorous public consultation; and, – development and implementation of a strategy that incorporates commitments from all levels of stakeholders. While focusing on our waterways, the Partnership’s approach includes addressing catchment management issues particularly relating to the management of diffuse pollution sources in both urban and rural landscapes as well as point source loads. We are now working with other stakeholders to develop a framework for integrated water management that will link water quality and water quantity goals and priorities.

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In patients hospitalised with acute coronary syndromes (ACS) and congestive heart failure (CHF), evidence suggests opportunities for improving in-hospital and after hospital care, patient self-care, and hospital-community integration. A multidisciplinary quality improvement program was designed and instigated in Brisbane in October 2000 involving 250 clinicians at three teaching hospitals, 1080 general practitioners (GPs) from five Divisions of General Practice, 1594 patients with ACS and 904 patients with CHF. Quality improvement interventions were implemented over 17 months after a 6-month baseline period and included: clinical decision support (clinical practice guidelines, reminders, checklists, clinical pathways); educational interventions (seminars, academic detailing); regular performance feedback; patient self-management strategies; and hospital-community integration (discharge referral summaries; community pharmacist liaison; patient prompts to attend GPs). Using a before-after study design to assess program impact, significantly more program patients compared with historical controls received: ACS: Angiotensin-converting enzyme (ACE) inhibitors and lipid-lowering agents at discharge, aspirin and beta-blockers at 3 months after discharge, inpatient cardiac counselling, and referral to outpatient cardiac rehabilitation. CHF. Assessment for reversible precipitants, use of prophylaxis for deep-venous thrombosis, beta-blockers at discharge, ACE inhibitors at 6 months after discharge, imaging of left ventricular function, and optimal management of blood pressure levels. Risk-adjusted mortality rates at 6 and 12 months decreased, respectively, from 9.8% to 7.4% (P=0.06) and from 13.4% to 10.1% (P= 0.06) for patients with ACS and from 22.8% to 15.2% (P < 0.001) and from 32.8% to 22.4% (P= 0.005) for patients with CHF. Quality improvement programs that feature multifaceted interventions across the continuum of care can change clinical culture, optimise care and improve clinical outcomes.

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This paper investigates how demographic (socioeconomic) and land-use (physical and environmental) data can be integrated within a decision support framework to formulate and evaluate land-use planning scenarios. A case-study approach is undertaken with land-use planning scenarios for a rapidly growing coastal area in Australia, the Shire of Hervey Bay. The town and surrounding area require careful planning of the future urban growth between competing land uses. Three potential urban growth scenarios are put forth to address this issue. Scenario A ('continued growth') is based on existing socioeconomic trends. Scenario B ('maximising rates base') is derived using optimisation modelling of land-valuation data. Scenario C ('sustainable development') is derived using a number of social, economic, and environmental factors and assigning weightings of importance to each factor using a multiple criteria analysis approach. The land-use planning scenarios are presented through the use of maps and tables within a geographical information system, which delineate future possible land-use allocations up until 2021. The planning scenarios are evaluated by using a goal-achievement matrix approach. The matrix is constructed with a number of criteria derived from key policy objectives outlined in the regional growth management framework and town planning schemes. The authors of this paper examine the final efficiency scores calculated for each of the three planning scenarios and discuss the advantages and disadvantages of the three land-use modelling approaches used to formulate the final scenarios.

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Community-based coastal resource management has been widely applied within the Philippines. However, small-scale community-based reserves are often inefficient owing to management inadequacies arising because of a lack of local support or enforcement or poor design. Because there are many potential pitfalls during the establishment of even small community-based reserves, it is important for coastal managers, communities, and facilitating institutions to have access to a summary of the key factors for success. Reviewing relevant literature, we present a framework of lessons learned during the establishment of protected areas, mainly in the Philippines. The framework contains summary guidance on the importance of (1) an island location, (2) small community population size, (3) minimal effect of land-based development, (4) application of a bottom-up approach, (5) an external facilitating institution, (6) acquisition of title, (7) use of a scientific information database, (8) stakeholder involvement, (9) the establishment of legislation, (10) community empowerment, (11) alternative livelihood schemes, (12) surveillance, (13) tangible management results, (14) continued involvement of external groups after reserve establishment, and (15) small-scale project expansion. These framework components guided the establishment of a community-based protected area at Danjugan Island, Negros Occidental, Philippines. This case study showed that the framework was a useful guide that led to establishing and implementing a community-based marine reserve. Evaluation of the reserve using standard criteria developed for the Philippines shows that the Danjugan Island protected area can be considered successful and sustainable. At Danjugan Island, all of the lessons synthesized in the framework were important and should be considered elsewhere, even for relatively small projects. As shown in previous projects in the Philippines, local involvement and stewardship of the protected area appeared particularly important for its successful implementation. The involvement of external organizations also seemed to have a key role in the success of the Danjugan Island project by guiding local decision-makers in the sociobiological principles of establishing protected areas. However, the relative importance of each component of the framework will vary between coastal management initiatives both within the Philippines and across the wider Asian region.

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Virtual learning environments (VLEs) are computer-based online learning environments, which provide opportunities for online learners to learn at the time and location of their choosing, whilst allowing interactions and encounters with other online learners, as well as affording access to a wide range of resources. They have the capability of reaching learners in remote areas around the country or across country boundaries at very low cost. Personalized VLEs are those VLEs that provide a set of personalization functionalities, such as personalizing learning plans, learning materials, tests, and are capable of initializing the interaction with learners by providing advice, necessary instant messages, etc., to online learners. One of the major challenges involved in developing personalized VLEs is to achieve effective personalization functionalities, such as personalized content management, learner model, learner plan and adaptive instant interaction. Autonomous intelligent agents provide an important technology for accomplishing personalization in VLEs. A number of agents work collaboratively to enable personalization by recognizing an individual's eLeaming pace and reacting correspondingly. In this research, a personalization model has been developed that demonstrates dynamic eLearning processes; secondly, this study proposes an architecture for PVLE by using intelligent decision-making agents' autonomous, pre-active and proactive behaviors. A prototype system has been developed to demonstrate the implementation of this architecture. Furthemore, a field experiment has been conducted to investigate the performance of the prototype by comparing PVLE eLearning effectiveness with a non-personalized VLE. Data regarding participants' final exam scores were collected and analyzed. The results indicate that intelligent agent technology can be employed to achieve personalization in VLEs, and as a consequence to improve eLeaming effectiveness dramatically.

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Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

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This paper highlights challenges in implementing mental health policy at a service delivery level. It describes an attempt to foster greater application of recovery-orientated principles and practices within mental health services. Notwithstanding a highly supportive policy environment, strong support from service administrators, and an enthusiastic staff response to training, application of the training and support tools was weaker than anticipated. This paper evaluates the dissemination trial against key elements to promote sustained adoption of innovations. Organisational and procedural changes are required before mental health policies are systematically implemented in practice.

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The consequences of demographic dissimilarity for group trust in work teams was examined in a virtual (computer-mediated) and a face-to-face (FTF) environment. Demographic dissimilarity (based on age, gender, country of birth, enrolled degree) was predicted to be negatively associated with group trust in the FTF environment but not in the computer-mediated environment. Participants worked in small groups on a creative task for 3 consecutive days. In the computer-mediated environment, participants worked on the task for an hour per day. In the FTF environment, participants worked on the task for 20 minutes per day. Partial support was found for the effectiveness of computer-mediated groups in reducing the negative consequences of dissimilarity. Age dissimilarity was negatively related to trust in FTF groups but not in computer-mediated groups. Birthplace dissimilarity was positively related to trust in computer-mediated groups. Implications for the successful management of virtual teams are discussed.

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Global Software Development (GSD) is an emerging distributive software engineering practice, in which a higher communication overhead due to temporal and geographical separation among developers is traded with gains in reduced development cost, improved flexibility and mobility for developers, increased access to skilled resource-pools and convenience of customer involvements. However, due to its distributive nature, GSD faces many fresh challenges in aspects relating to project coordination, awareness, collaborative coding and effective communication. New software engineering methodologies and processes are required to address these issues. Research has shown that, with adequate support tools, Distributed Extreme Programming (DXP) – a distributive variant of an agile methodology – Extreme Programming (XP) can be both efficient and beneficial to GDS projects. In this paper, we present the design and realization of a collaborative environment, called Moomba, which assists a distributed team in both instantiation and execution of a DXP process in GSD projects.

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Our research described in this paper identifies a three part premise relating to the spyware paradigm. Firstly the data suggests spyware is proliferating at an exponential rate. Secondly ongoing research confirms that spyware produces many security risks – including that of privacy/confidentiality breaches via illicit data collection and reporting. Thirdly, anti-spyware controls are improving but are still considered problematic for several reasons. Our research then concludes that control measures to counter this very significant challenge should merit compliance auditing – and this auditing may effectively target the vital message passing performed by all illicit data collection spyware. Our research then evolves into an experiment involving the design and implementation of a software audit tool to conduct the desired compliance auditing. The software audit tool is positioned at the protected network’s gateway. The software audit tool uses ‘phone-home’ IP addresses as spyware signatures to detect the presence of the offending software. The audit tool also has the capability to differentiate legitimate message passing software from that produced by spyware – and ‘learn’ both new spyware signatures and new legitimate message passing profiles. The testing stage of the software has proven successful – albeit using very limited levels of network message passing variety and frequency.