997 resultados para Effective Modulus
Resumo:
Drying has been extensively used as a food preservation procedure. The longer life attained by drying is however accompanied by huge energy consumption and deterioration of quality. Moisture diffusivity is an important factor that is considered essential to understand for design, analysis, and optimization of drying processes for food and other materials. Without an accurate value of moisture diffusivity, drying kinetics, energy consumption, quality attributes such as shrinkage, texture, and microstructure cannot be predicted properly. However, moisture diffusivities differ due to variation of composition and microstructure of foodstuff and drying variables. For a particular food, it changes with many factors including moisture content, water holding capacity, process variables and physiochemical attributes of food. Published information on moisture diffusivities of banana is inadequate and sometimes inconsistent due to lack of precise repeatable analysis techniques. In this work, the effective moisture diffusivity of banana was determined by Thermogravimetric Analysis (TGA), which ensures precise measurements and reproduction of experiments. A TGA Q500 V20.13 Build 39 was deployed to obtain the drying curve of the food material. It was found that effective moisture diffusivity ranged from 6.63 x10-10 to 1.03 x10-9 and 1.34 x10-10 to 6.60 x10-10 for isothermal at 70 0C and non-isothermal process respectively.These values are consistent with the value of moisture diffusivity found in the literature.
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The definition of tourism “is the travel for recreational, leisure, family or business purposes, usually of a limited duration. Tourism is commonly associated with trans-national travel, but may also refer to travel to another location within the same country”. Tourism as an industry, in today’s modern language is a means of global communication between nations and travelers of all countries, introducing them to the various cultures and societies abroad, as well there history, ancient, historical sites, and languages. Hence, advertising overall has become a tool of necessity in this ever-growing global industry. Given that, tourism is a part of the infrastructure of any country’s economy the growth and development of tourism is of great importance. Advertising plays a vital and is a crucial tool in developing the countries tourism by attractively presenting the nations points-of-interests, historical and cultural. Advertising has a central role in expanding this industry, generating economic growth in this area, as well as creating direct and indirect employment, but most importantly a creative innovating competition in the national and international travel industry. Importantly, to achieve a successful tourist industry, the Travel Agencies and governmental offices of the Ministry’s of Tourism and Business must work hand-in-hand to attain these goals. This article shows the impact of the various media and advertising methods used in tourism, which assisted in identifying the correct tool for expanding the country’s industry of tourism. The results of this study illustrated that the appropriate tools for promotional strategies to attract domestic and foreign traveler’s, found to be the most effective were, handbook, internet advertising, TV, brochures, newspapers
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In recent times a widespread consensus on the reality and gravity of anthropogenic climate change has emerged. Perceived inadequacies in the Australian government’s legal and policy responses to climate change issues have resulted in environmental activists increasingly turning to the courts as a strategy to promote greater action to address adverse climate impacts. The efficacy of this strategy for achieving climate goals is limited by the time and expense of litigating, the restrictions inherent in environmental law administrative challenges, and the possibility that judicial decisions may be overruled by the legislature. To date, climate change litigation in Australia has met with varied success, yet its significance extends beyond the court room as an important mechanism for raising public, political and commercial awareness about climate change issues. Ultimately, however, the types of far-reaching changes needed to mitigate and manage adverse climate impacts require strong regulatory backing. The most effective approach to addressing the complex challenges posed by climate change is a coordinated suite of regulatory measures spearheaded by the Federal Government.
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It is argued that the smart cities model promise solutions to fuel sustainable development and a high quality of life with a wise management of natural resources, through participatory action and engagement. The paper provides a critical review of this model and application attempts of smart urban technologies in contemporary cities by particularly looking into emerging practices of ubiquitous eco-cities as exemplar smart cities initiatives. Through a thorough review of literature and best practices on the smart cities model, this paper attempts to address the research question of whether smart cities model is just another fashionable city brand or an effective urban development and management model to solve the problems of our cities. The findings shed light on urban planning and development considerations for the integration of smart urban technologies and their possible implications in shaping up of the built environment to produce prosperous and sustainable urban futures.
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This paper develops a dynamic model for cost-effective selection of sites for restoring biodiversity when habitat quality develops over time and is uncertain. A safety-first decision criterion is used for ensuring a minimum level of habitats, and this is formulated in a chance-constrained programming framework. The theoretical results show; (i) inclusion of quality growth reduces overall cost for achieving a future biodiversity target from relatively early establishment of habitats, but (ii) consideration of uncertainty in growth increases total cost and delays establishment, and (iii) cost-effective trading of habitat requires exchange rate between sites that varies over time. An empirical application to the red listed umbrella species - white-backed woodpecker - shows that the total cost of achieving habitat targets specified in the Swedish recovery plan is doubled if the target is to be achieved with high reliability, and that equilibrating price on a habitat trading market differs considerably between different quality growth combinations. © 2013 Elsevier GmbH.
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Introduced predators can have pronounced effects on naïve prey species; thus, predator control is often essential for conservation of threatened native species. Complete eradication of the predator, although desirable, may be elusive in budget-limited situations, whereas predator suppression is more feasible and may still achieve conservation goals. We used a stochastic predator-prey model based on a Lotka-Volterra system to investigate the cost-effectiveness of predator control to achieve prey conservation. We compared five control strategies: immediate eradication, removal of a constant number of predators (fixed-number control), removal of a constant proportion of predators (fixed-rate control), removal of predators that exceed a predetermined threshold (upper-trigger harvest), and removal of predators whenever their population falls below a lower predetermined threshold (lower-trigger harvest). We looked at the performance of these strategies when managers could always remove the full number of predators targeted by each strategy, subject to budget availability. Under this assumption immediate eradication reduced the threat to the prey population the most. We then examined the effect of reduced management success in meeting removal targets, assuming removal is more difficult at low predator densities. In this case there was a pronounced reduction in performance of the immediate eradication, fixed-number, and lower-trigger strategies. Although immediate eradication still yielded the highest expected minimum prey population size, upper-trigger harvest yielded the lowest probability of prey extinction and the greatest return on investment (as measured by improvement in expected minimum population size per amount spent). Upper-trigger harvest was relatively successful because it operated when predator density was highest, which is when predator removal targets can be more easily met and the effect of predators on the prey is most damaging. This suggests that controlling predators only when they are most abundant is the "best" strategy when financial resources are limited and eradication is unlikely. © 2008 Society for Conservation Biology.
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This paper critically evaluates the empirical evidence of 36 studies regarding the comparative cost-effectiveness of group and individual cognitive behaviour therapy (CBT) as a whole, and also for specific mental disorders (e.g. depression, anxiety, substance abuse) or populations (e.g. children). Methods of calculating costs, as well as methods of comparing treatment outcomes were appraised and criticized. Overall, the evidence that group CBT is more cost-effective than individual CBT is mixed, with group CBT appearing to be more cost effective in treating depression and children, but less cost effective in treating drugs and alcohol dependence, anxiety and social phobias. In addition, methodological weaknesses in the studies assessed are noted. There is a need to improve cost calculation methodology, as well as more solid and a greater number of empirical cost-effectiveness studies before a firm conclusion can be reached that group CBT is more cost effective then individual CBT.
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Alcohol-related mortality and morbidity represents a substantial financial burden on communities across the world. Adolescence and young adulthood is a peak period for heavy episodic alcohol consumption, with over a third of all people aged 14-19 years having been at risk of acute alcoholrelated harm at least once in the previous 12 months (Australian Institute of Health and Welfare [AIHW], 2011). Excessive alcohol consumption has long been seen as a male problem; however, a gradual shift towards a social acceptance of female drunkenness has narrowed the gap in drinking quantity and style between men and women (Grucza, Bucholz, Rice, & Bierut, 2008). The presented data point to the vulnerability of women to the consequences of acute alcohol intoxication and indicate that alcohol-related offending by women is on the rise. Taken together, these findings reveal that alcohol-related harms and aggression for young women are becoming more prevalent and problematic. This report addressed these issues from a policing perspective...
Resumo:
Issues addressed: Hand hygiene in hospitals is vital to limit the spread of infections. This study aimed to identify key beliefs underlying hospital nurses’ hand-hygiene decisions to consolidate strategies that encourage compliance. Methods: Informed by a theory of planned behaviour belief framework, nurses from 50 Australian hospitals (n = 797) responded to how likely behavioural beliefs (advantages and disadvantages), normative beliefs (important referents) and control beliefs (barriers) impacted on their hand-hygiene decisions following the introduction of a national ‘5 moments for hand hygiene’ initiative. Two weeks after completing the survey, they reported their hand-hygiene adherence. Stepwise regression analyses identified key beliefs that determined nurses’ hand-hygiene behaviour. Results: Reducing the chance of infection for co-workers influenced nurses’ hygiene behaviour, with lack of time and forgetfulness identified as barriers. Conclusions: Future efforts to improve hand hygiene should highlight the potential impact on colleagues and consider strategies to combat time constraints, as well as implementing workplace reminders to prompt greater hand-hygiene compliance. So what? Rather than emphasising the health of self and patients in efforts to encourage hand-hygiene practices, a focus on peer protection should be adopted and more effective workplace reminders should be implemented to combat forgetting.
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This thesis investigates the design of motivating and engaging software experiences. In particular it examines the use of video game elements in non-game contexts, known as gamification, and how to effectively design gamification experiences for smartphone applications. The original contribution of this thesis is a novel framework for designing gamification, derived from an iterative process of evaluating gamified prototypes. The outcomes of this research can help us to better understand the impact of gamification in today's society and how it can be used to design more effective software.
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This paper investigates a five-factor model of mentoring for effective teaching. A survey was administered to 218 student teachers after student teaching to provide insights into their mentoring experience. Results indicated the five factors, namely, personal attributes, system requirements, pedagogical knowledge, modeling, and feedback, had Cronbach alpha scores of .93, .81, .95, .91, and .91, respectively with mean scale scores ranging from 4.20 to 4.60 (p< .001). Items associated with each factor were analyzed; the lowest percentage response was reviewing lesson plans (71%) and the highest percentage was modeling effective teaching practices (96%). Triangulated data from the survey results suggested that the practices implemented by the mentor teachers were perceived to have supported the student teachers’ development during student teaching. Implications of this study suggest that actively engaging mentor teachers who apply the principles outlined by the five factor areas will serve to ensure highly effective support for the development of student teachers.
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Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.
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In the structural health monitoring (SHM) field, long-term continuous vibration-based monitoring is becoming increasingly popular as this could keep track of the health status of structures during their service lives. However, implementing such a system is not always feasible due to on-going conflicts between budget constraints and the need of sophisticated systems to monitor real-world structures under their demanding in-service conditions. To address this problem, this paper presents a comprehensive development of a cost-effective and flexible vibration DAQ system for long-term continuous SHM of a newly constructed institutional complex with a special focus on the main building. First, selections of sensor type and sensor positions are scrutinized to overcome adversities such as low-frequency and low-level vibration measurements. In order to economically tackle the sparse measurement problem, a cost-optimized Ethernet-based peripheral DAQ model is first adopted to form the system skeleton. A combination of a high-resolution timing coordination method based on the TCP/IP command communication medium and a periodic system resynchronization strategy is then proposed to synchronize data from multiple distributed DAQ units. The results of both experimental evaluations and experimental–numerical verifications show that the proposed DAQ system in general and the data synchronization solution in particular work well and they can provide a promising cost-effective and flexible alternative for use in real-world SHM projects. Finally, the paper demonstrates simple but effective ways to make use of the developed monitoring system for long-term continuous structural health evaluation as well as to use the instrumented building herein as a multi-purpose benchmark structure for studying not only practical SHM problems but also synchronization related issues.