317 resultados para Process models


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In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

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Computational models in physiology often integrate functional and structural information from a large range of spatio-temporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and scepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace and refine animal experiments. A fundamental requirement to fulfil these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations between experiments, models and simulations in cardiac electrophysiology. We describe the processes, data and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. Validation must therefore take into account the complex interplay between models, simulations and experiments. Key points for developing strategies for validation are: 1) understanding sources of bio-variability is crucial to the comparison between simulation and experimental results; 2) robustness of techniques and tools is a pre-requisite to conducting physiological investigations using the MSE system; 3) definition and adoption of standards facilitates interoperability of experiments, models and simulations; 4) physiological validation must be understood as an iterative process that defines the specific aspects of electrophysiology the MSE system targets, and is driven by advancements in experimental and computational methods and the combination of both.

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Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

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Existing crowd counting algorithms rely on holistic, local or histogram based features to capture crowd properties. Regression is then employed to estimate the crowd size. Insufficient testing across multiple datasets has made it difficult to compare and contrast different methodologies. This paper presents an evaluation across multiple datasets to compare holistic, local and histogram based methods, and to compare various image features and regression models. A K-fold cross validation protocol is followed to evaluate the performance across five public datasets: UCSD, PETS 2009, Fudan, Mall and Grand Central datasets. Image features are categorised into five types: size, shape, edges, keypoints and textures. The regression models evaluated are: Gaussian process regression (GPR), linear regression, K nearest neighbours (KNN) and neural networks (NN). The results demonstrate that local features outperform equivalent holistic and histogram based features; optimal performance is observed using all image features except for textures; and that GPR outperforms linear, KNN and NN regression

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Finite element (FE) model studies have made important contributions to our understanding of functional biomechanics of the lumbar spine. However, if a model is used to answer clinical and biomechanical questions over a certain population, their inherently large inter-subject variability has to be considered. Current FE model studies, however, generally account only for a single distinct spinal geometry with one set of material properties. This raises questions concerning their predictive power, their range of results and on their agreement with in vitro and in vivo values. Eight well-established FE models of the lumbar spine (L1-5) of different research centres around the globe were subjected to pure and combined loading modes and compared to in vitro and in vivo measurements for intervertebral rotations, disc pressures and facet joint forces. Under pure moment loading, the predicted L1-5 rotations of almost all models fell within the reported in vitro ranges, and their median values differed on average by only 2° for flexion-extension, 1° for lateral bending and 5° for axial rotation. Predicted median facet joint forces and disc pressures were also in good agreement with published median in vitro values. However, the ranges of predictions were larger and exceeded those reported in vitro, especially for the facet joint forces. For all combined loading modes, except for flexion, predicted median segmental intervertebral rotations and disc pressures were in good agreement with measured in vivo values. In light of high inter-subject variability, the generalization of results of a single model to a population remains a concern. This study demonstrated that the pooled median of individual model results, similar to a probabilistic approach, can be used as an improved predictive tool in order to estimate the response of the lumbar spine.

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It is often said that Australia is a world leader in rates of copyright infringement for entertainment goods. In 2012, the hit television show, Game of Thrones, was the most downloaded television show over bitorrent, and estimates suggest that Australians accounted for a plurality of nearly 10% of the 3-4 million downloads each week. The season finale of 2013 was downloaded over a million times within 24 hours of its release, and again Australians were the largest block of illicit downloaders over BitTorrent, despite our relatively small population. This trend has led the former US Ambassador to Australia to implore Australians to stop 'stealing' digital content, and rightsholders to push for increasing sanctions on copyright infringers. The Australian Government is looking to respond by requiring Internet Service Providers to issue warnings and potentially punish consumers who are alleged by industry groups to have infringed copyright. This is the logical next step in deterring infringement, given that the operators of infringing networks (like The Pirate Bay, for example) are out of regulatory reach. This steady ratcheting up of the strength of copyright, however, comes at a significant cost to user privacy and autonomy, and while the decentralisation of enforcement reduces costs, it also reduces the due process safeguards provided by the judicial process. This article presents qualitative evidence that substantiates a common intuition: one of the major reasons that Australians seek out illicit downloads of content like Game of Thrones in such numbers is that it is more difficult to access legitimately in Australia. The geographically segmented way in which copyright is exploited at an international level has given rise to a ‘tyranny of digital distance’, where Australians have less access to copyright goods than consumers in other countries. Compared to consumers in the US and the EU, Australians pay more for digital goods, have less choice in distribution channels, are exposed to substantial delays in access, and are sometimes denied access completely. In this article we focus our analysis on premium film and television offerings, like Game of Thrones, and through semi-structured interviews, explore how choices in distribution impact on the willingness of Australian consumers to seek out infringing copies of copyright material. Game of Thrones provides an excellent case study through which to frame this analysis: it is both one of the least legally accessible television offerings and one of the most downloaded through filesharing networks of recent times. Our analysis shows that at the same time as rightsholder groups, particularly in the film and television industries, are lobbying for stronger laws to counter illicit distribution, the business practices of their member organisations are counter-productively increasing incentives for consumers to infringe. The lack of accessibility and high prices of copyright goods in Australia leads to substantial economic waste. The unmet consumer demand means that Australian consumers are harmed by lower access to information and entertainment goods than consumers in other jurisdictions. The higher rates of infringement that fulfils some of this unmet demand increases enforcement costs for copyright owners and imposes burdens either on our judicial system or on private entities – like ISPs – who may be tasked with enforcing the rights of third parties. Most worryingly, the lack of convenient and cheap legitimate digital distribution channels risks undermining public support for copyright law. Our research shows that consumers blame rightsholders for failing to meet market demand, and this encourages a social norm that infringing copyright, while illegal, is not morally wrongful. The implications are as simple as they are profound: Australia should not take steps to increase the strength of copyright law at this time. The interests of the public and those of rightsholders align better when there is effective competition in distribution channels and consumers can legitimately get access to content. While foreign rightsholders are seeking enhanced protection for their interests, increasing enforcement is likely to increase their ability to engage in lucrative geographical price-discrimination, particularly for premium content. This is only likely to increase the degree to which Australian consumers feel that their interests are not being met and, consequently, to further undermine the legitimacy of copyright law. If consumers are to respect copyright law, increasing sanctions for infringement without enhancing access and competition in legitimate distribution channels could be dangerously counter-productive. We suggest that rightsholders’ best strategy for addressing infringement in Australia at this time is to ensure that Australians can access copyright goods in a timely, affordable, convenient, and fair lawful manner.

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Agent-based modeling and simulation (ABMS) may fit well with entrepreneurship research and practice because the core concepts and basic premises of entrepreneurship coincide with the characteristics of ABMS. However, it is difficult to find cases where ABMS is applied to entrepreneurship research. To apply ABMS to entrepreneurship and organization studies, designing a conceptual model is important; thus to effectively design a conceptual model, various mixed method approaches are being attempted. As a new mixed method approach to ABMS, this study proposes a bibliometric approach to designing agent based models, which establishes and analyzes a domain corpus. This study presents an example on the venture creation process using the bibliometric approach. This example shows us that the results of the multi-agent simulations on the venturing process based on the bibliometric approach are close to each nation’s surveyed data on the venturing activities. In conclusion, by the bibliometric approach proposed in this study, all the agents and the agents’ behaviors related to a phenomenon can be extracted effectively, and a conceptual model for ABMS can be designed with the agents and their behaviors. This study contributes to the entrepreneurship and organization studies by promoting the application of ABMS.

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Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams. It is necessary to consider human-factors in {CF} modeling for a more realistic representation of {CF} behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of {CF} models available in the literature, none of these specifically focuses on the human factors in these models. This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.

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Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.

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Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

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Rodent (mouse and rat) models have been crucial in developing our understanding of human neurogenesis and neural stem cell (NSC) biology. The study of neurogenesis in rodents has allowed us to begin to understand adult human neurogenesis and in particular, protocols established for isolation and in vitro propagation of rodent NSCs have successfully been applied to the expansion of human NSCs. Furthermore, rodent models have played a central role in studying NSC function in vivo and in the development of NSC transplantation strategies for cell therapy applications. Rodents and humans share many similarities in the process of neurogenesis and NSC biology however distinct species differences are important considerations for the development of more efficient human NSC therapeutic applications. Here we review the important contributions rodent studies have had to our understanding of human neurogenesis and to the development of in vitro and in vivo NSC research. Species differences will be discussed to identify key areas in need of further development for human NSC therapy applications.

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Angiogenesis is indispensable for solid tumor expansion, and thus it has become a major target of cancer research and anti-cancer therapies. Deciphering the arcane actions of various cell populations during tumor angiogenesis requires sophisticated research models, which could capture the dynamics and complexity of the process. There is a continuous need for improvement of existing research models, which engages interdisciplinary approaches of tissue engineering with life sciences. Tireless efforts to develop a new model to study tumor angiogenesis result in innovative solutions, which bring us one step closer to decipher the dubious nature of cancer. This review aims to overview the recent developments, current limitations and future challenges in three-dimensional tissue-engineered models for the study of tumor angiogenesis and for the purpose of elucidating novel targets aimed at anti-cancer drug discovery.

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We learn from the past that invasive species have caused tremendous damage to native species and serious disruption to agricultural industries. It is crucial for us to prevent this in the future. The first step of this process is to identify correctly an invasive species from native ones. Current identification methods, relying on mainly 2D images, can result in low accuracy and be time consuming. Such methods provide little help to a quarantine officer who has time constraints to response when on duty. To deal with this problem, we propose new solutions using 3D virtual models of insects. We explain how working with insects in the 3D domain can be much better than the 2D domain. We also describe how to create true-color 3D models of insects using an image-based 3D reconstruction method. This method is ideal for quarantine control and inspection tasks that involve the verification of a physical specimen against known invasive species. Finally we show that these insect models provide valuable material for other applications such as research, education, arts and entertainment. © 2013 IEEE.

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The degradation efficiencies and behaviors of caffeic acid (CaA), p-coumaric acid (pCoA) and ferulic acid (FeA) in aqueous sucrose solutions containing the mixture of these hydroxycinnamic acids (HCAs) mixtures were studied by the Fenton oxidation process. Central composite design and multi-response surface methodology were used to evaluate and optimize the interactive effects of process parameters. Four quadratic polynomial models were developed for the degradation of each individual acid in the mixture and the total HCAs degraded. Sucrose was the most influential parameter that significantly affected the total amount of HCA degraded. Under the conditions studied there was < 0.01% loss of sucrose in all reactions. The optimal values of the process parameters for a 200 mg/L HCA mixture in water (pH 4.73, 25.15 °C) and sucrose solution (13 mass%, pH 5.39, 35.98 °C) were 77% and 57% respectively. Regression analysis showed goodness of fit between the experimental results and the predicted values. The degradation behavior of CaA differed from those of pCoA and FeA, where further CaA degradation is observed at increasing sucrose and decreasing solution pH. The differences (established using UV/Vis and ATR-FTIR spectroscopy) were because, unlike the other acids, CaA formed a complex with Fe(III) or with Fe(III) hydrogen-bonded to sucrose, and coprecipitated with lepidocrocite, an iron oxyhydroxide.

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1.Description of the Work The Fleet Store was devised as a creative output to establish an exhibition linked to a fashion business model where emerging designers were encouraged to research new and innovative strategies for creating design-driven and commercial collections for a public consumer. This was a project that was devised to break down the perceptions of emerging fashion designers that designing commercial collections linked to a sustainable business model is a boring and unnecessary process. The focus was to demystify the business of fashion and to link its importance to a design-driven and public outcome that is more familiar to fashion designers. The criterion for participation was that all designers had to be registered as a business with the Australian Taxation Office. Designers were chosen from the Creative Enterprise Australia Fashion Business Incubator, the QUT fashion graduate alumni and current QUT fashion design and double degree (fashion and business) students with existing businesses. The project evolved from a series of collaborative workshops where designers were introduced to new and innovative creative industries’ business models and the processes, costings and timings involved to create a niche, sustainable business for a public exhibition of design-driven commercial collections. All designers initiated their own business infra-structure but were then introduced to the concept of collaboration for successful and profitable exhibition and business outcomes. Collaborative strategies such as crowd funding, crowd sourcing, peer to peer mentoring and manufacturing were all researched, and strategies for the establishment of the retail exhibition were all devised in a collaborative environment. All participants also took on roles outside their ‘designer’ background to create a retail exhibition that was creative but also had critical mass and aesthetic for the consumer. The Fleet Store ‘popped up’ for 2 weeks (10 days), in a heritage-listed building in an inner city location. Passers-by were important, but the main consumer was enlisted by the use of interest and investment from crowd sourcing, crowd funding, ethical marketing, corporate social responsibility projects and collaborative public relations and social media strategies. The research has furthered discussion on innovative strategies for emerging fashion designers to initiate and maintain sustainable businesses and suggests that collaboration combined with a design-driven and business focus can create a sustainable and economically viable retail exhibition. 2. Research Statement Research Background The research field involved developing a new ethical, design-driven, collaborative and sustainable model for fashion design practice and management. The research asked can a public, design-driven, collaborative retail exhibition create a platform for promoting creative, innovative and sustainable business models for emerging fashion designers. The methodology was primarily practice-led as all participants were designers in their own right and the project manager acted as a mentor and curator to guide the process and analyse the potential of the research question. The Fleet Store offers new knowledge in design practice and management; with the creation of a model where design outcomes and business models are inextricably linked to the success of the creative output. Key innovations include extending the commercialisation of emerging fashion businesses by creating a curated retail gallery for collaborative and sustainable strategies to support niche fashion designer labels. This has contributed to a broader conversation on how to nurture and sustain competitive Australian fashion designers/labels. Research Contribution and Significance The Fleet Store has contributed to a growing body of research into innovative and sustainable business models for niche fashion and creative industries’ practitioners. All participants have maintained their business infra-structure and many are currently growing their businesses, using the strategies tested for the Fleet Store. The exhibition space was visited by over 1,000 people and sales of $27,000 were made in 10 days of opening. (Follow up sales of $3,000 has also been reported.) Three of the designers were ‘discovered’ from the exhibition and have received substantial orders from high profile national buyers and retailers for next season delivery. Several participants have since collaborated to create other pop up retail environments and are now mentoring other emerging designers on the significance of a collaborative retail exhibition to consolidate niche business models for emerging fashion designers.