903 resultados para COMPOSITES MANUFACTURING APPLICATIONS


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Most social network users hold more than one social network account and utilize them in different ways depending on the digital context. For example, friendly chat on Facebook, professional discussion on LinkedIn, and health information exchange on PatientsLikeMe. Thus many web users need to manage many disparate profiles across many distributed online sources. Maintaining these profiles is cumbersome, time consuming, inefficient, and leads to lost opportunity. In this paper we propose a framework for multiple profile management of online social networks and showcase a demonstrator utilising an open source platform. The result of the research enables a user to create and manage an integrated profile and share/synchronise their profiles with their social networks. A number of use cases were created to capture the functional requirements and describe the interactions between users and the online services. An innovative application of this project is in public health informatics. We utilize the prototype to examine how the framework can benefit patients and physicians. The framework can greatly enhance health information management for patients and more importantly offer a more comprehensive personal health overview of patients to physicians.

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Today’s highly competitive market influences the manufacturing industry to improve their production systems to become the optimal system in the shortest cycle time as possible. One of most common problems in manufacturing systems is the assembly line balancing problem. The assembly line balancing problem involves task assignments to workstations with optimum line efficiency. The line balancing technique, namely “COMSOAL”, is an abbreviation of “Computer Method for Sequencing Operations for Assembly Lines”. Arcus initially developed the COMSOAL technique in 1966 [1], and it has been mainly applied to solve assembly line balancing problems [6]. The most common purposes of COMSOAL are to minimise idle time, optimise production line efficiency, and minimise the number of workstations. Therefore, this project will implement COMSOAL to balance an assembly line in the motorcycle industry. The new solution by COMSOAL will be used to compare with the previous solution that was developed by Multi‐Started Neighborhood Search Heuristic (MSNSH), which will result in five aspects including cycle time, total idle time, line efficiency, average daily productivity rate, and the workload balance. The journal name “Optimising and simulating the assembly line balancing problem in a motorcycle manufacturing company: a case study” will be used as the case study for this project [5].

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Building prefabrication is known as Industrialised Building Systems (IBS) in Malaysia. This construction method possesses unique characteristics that are central to sustainable construction. For example, offsite construction enables efficient management of construction wastage by identifying major causes of waste arising during both the design and construction stages. These causes may then be eliminated by the improvement process in IBS component's manufacturing. However, current decisions on using IBS are typically financial driven and hinder the wider ranged adoption. In addition, current IBS misconceptions and the failure of rating schemes in evaluating the sustainability of IBS affect its implementation. A new approach is required to provide better understanding on the sustainability potential of IBS among stakeholders. Such approach should also help project the outcomes of each levels of decision-making to respond to social, economy and environmental challenges. This paper presents interim findings of research aimed at developing a framework for sustainable IBS development and suggests a more holistic approach to achieve sustainability. A framework of embedding sustainability factors is considered in three main phases of IBS construction; 1) Pre-construction, 2) Construction and 3) Post-construction phase. SWOT analysis was used to evaluate the strengths, weaknesses, opportunities and threats involved in the IBS implementations. The action plans are formulated from the analysis of sustainable objectives. This approach will show where and how sustainability should be integrated to improve IBS construction. A mix of quantitative and qualitative methodology was used in this research to explore the potential of IBS in integrating sustainability. The tools used in the study are questionnaires and semi-structured interviews. Outcomes from these tools lead to the identification of viable approaches involving 18 critical factors to improve sustainability in IBS constructions. Finally, guidelines for decision-making are being developed to provide a useful source of information and support to mutual benefit of the stakeholders in integrating sustainability issues and concepts into IBS applications.

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A contentious issue in the field of destination marketing has been the recent tendency by some authors to refer to destination marketing organisations (DMOs) as destination management organisations. This nomenclature infers control over destination resources, a level of influence that is in reality held by few DMOs. This issue of a lack of control over the destination ‘amalgam’ is acknowledged by a number of the contributors, including the editors and the discussion on destination competitiveness by J.R. Brent Ritchie and Geoffrey Crouch, and is perhaps best summed up by Alan Fyall in the concluding chapter: “...unless all elements are owned by the same body, then the ability to control and influence the direction, quality and development of the destination pose very real challenges’ (p. 343). The title of the text acknowledges both marketing and management, in relation to theories and applications. While there are insightful propositions about ideals of destination management, readers will find there is a lack of coverage of destination management in practise by DMOs. This represents fertile ground for future research.

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The development and design of electric high power devices with electromagnetic computer-aided engineering (EM-CAE) software such as the Finite Element Method (FEM) and Boundary Element Method (BEM) has been widely adopted. This paper presents the analysis of a Fault Current Limiter (FCL), which acts as a high-voltage surge protector for power grids. A prototype FCL was built. The magnetic flux in the core and the resulting electromagnetic forces in the winding of the FCL were analyzed using both FEM and BEM. An experiment on the prototype was conducted in a laboratory. The data obtained from the experiment is compared to the numerical solutions to determine the suitability and accuracy of the two methods.

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Despite the rapidly urbanising population, public transport usage in metropolitan areas is not growing at a level that corresponds to the trend. Many people are reluctant to travel using public transport, as it is commonly associated with unpleasant experiences such as limited services, long wait time, and crowded spaces. This study aims to explore the use of mobile spatial interactions and services, and investigate their potential to increase the enjoyment of our everyday commuting experience. The main goal is to develop and evaluate mobile-mediated design interventions to foster interactions for and among passengers, as well as between passengers and public transport infrastructures, with the aim to positively influence the experience of commuting. Ultimately, this study hopes to generate findings and knowledge towards creating a more enjoyable public transport experience, as well as to explore innovative uses of mobile technologies and context-aware services for the urban lifestyle.

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This paper presents an efficient face detection method suitable for real-time surveillance applications. Improved efficiency is achieved by constraining the search window of an AdaBoost face detector to pre-selected regions. Firstly, the proposed method takes a sparse grid of sample pixels from the image to reduce whole image scan time. A fusion of foreground segmentation and skin colour segmentation is then used to select candidate face regions. Finally, a classifier-based face detector is applied only to selected regions to verify the presence of a face (the Viola-Jones detector is used in this paper). The proposed system is evaluated using 640 x 480 pixels test images and compared with other relevant methods. Experimental results show that the proposed method reduces the detection time to 42 ms, where the Viola-Jones detector alone requires 565 ms (on a desktop processor). This improvement makes the face detector suitable for real-time applications. Furthermore, the proposed method requires 50% of the computation time of the best competing method, while reducing the false positive rate by 3.2% and maintaining the same hit rate.

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Advances in algorithms for approximate sampling from a multivariable target function have led to solutions to challenging statistical inference problems that would otherwise not be considered by the applied scientist. Such sampling algorithms are particularly relevant to Bayesian statistics, since the target function is the posterior distribution of the unobservables given the observables. In this thesis we develop, adapt and apply Bayesian algorithms, whilst addressing substantive applied problems in biology and medicine as well as other applications. For an increasing number of high-impact research problems, the primary models of interest are often sufficiently complex that the likelihood function is computationally intractable. Rather than discard these models in favour of inferior alternatives, a class of Bayesian "likelihoodfree" techniques (often termed approximate Bayesian computation (ABC)) has emerged in the last few years, which avoids direct likelihood computation through repeated sampling of data from the model and comparing observed and simulated summary statistics. In Part I of this thesis we utilise sequential Monte Carlo (SMC) methodology to develop new algorithms for ABC that are more efficient in terms of the number of model simulations required and are almost black-box since very little algorithmic tuning is required. In addition, we address the issue of deriving appropriate summary statistics to use within ABC via a goodness-of-fit statistic and indirect inference. Another important problem in statistics is the design of experiments. That is, how one should select the values of the controllable variables in order to achieve some design goal. The presences of parameter and/or model uncertainty are computational obstacles when designing experiments but can lead to inefficient designs if not accounted for correctly. The Bayesian framework accommodates such uncertainties in a coherent way. If the amount of uncertainty is substantial, it can be of interest to perform adaptive designs in order to accrue information to make better decisions about future design points. This is of particular interest if the data can be collected sequentially. In a sense, the current posterior distribution becomes the new prior distribution for the next design decision. Part II of this thesis creates new algorithms for Bayesian sequential design to accommodate parameter and model uncertainty using SMC. The algorithms are substantially faster than previous approaches allowing the simulation properties of various design utilities to be investigated in a more timely manner. Furthermore the approach offers convenient estimation of Bayesian utilities and other quantities that are particularly relevant in the presence of model uncertainty. Finally, Part III of this thesis tackles a substantive medical problem. A neurological disorder known as motor neuron disease (MND) progressively causes motor neurons to no longer have the ability to innervate the muscle fibres, causing the muscles to eventually waste away. When this occurs the motor unit effectively ‘dies’. There is no cure for MND, and fatality often results from a lack of muscle strength to breathe. The prognosis for many forms of MND (particularly amyotrophic lateral sclerosis (ALS)) is particularly poor, with patients usually only surviving a small number of years after the initial onset of disease. Measuring the progress of diseases of the motor units, such as ALS, is a challenge for clinical neurologists. Motor unit number estimation (MUNE) is an attempt to directly assess underlying motor unit loss rather than indirect techniques such as muscle strength assessment, which generally is unable to detect progressions due to the body’s natural attempts at compensation. Part III of this thesis builds upon a previous Bayesian technique, which develops a sophisticated statistical model that takes into account physiological information about motor unit activation and various sources of uncertainties. More specifically, we develop a more reliable MUNE method by applying marginalisation over latent variables in order to improve the performance of a previously developed reversible jump Markov chain Monte Carlo sampler. We make other subtle changes to the model and algorithm to improve the robustness of the approach.

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Superconducting composite Bi-2212/Ag tapes and their joints are fabricated by a combination of dip-coating and partial melt processing. The heat treated tapes have a critical current (Ic) between 8 and 26A, depending on tape thickness and the number of Bi-2212 layers. Current transmissions between 80% and 100% have been achieved through the joints of tapes. Different types of HTS joints of Bi-2212/Ag laminated tapes are made and their transport properties during winding operations are investigated. Irreversible strain values (ε irrev) for laminated tapes and their joints are determined and it is found that the degradation of Ic during tape bending depends on the type of joint.

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Chemical treatments of kaolins to produce nanocrystalline or "X-ray amorphous", stable aluminosilicates with variable - but reproducible - types of micro- and meso-porosity have been developed. These materials show cation exchange capacities and surface area values significantly higher (ranging from 10x to 100x) than kaolin and show good acid resistance to pH~3.0. The combination of these properties offers strong potential for many new applications of kaolin-derived materials in large worldwide markets such as environmental remediation and catalysis. Kaolin amorphous derivative (KAD) is well-suited to removal of many toxic metals down to ppb range from acid mine drainage. Engineering development trials of the KAD manufacturing process and the utilisation of KAD in polluted waters such as acid mine drainage indicates that scale-up from bench-scale is not a barrier to market entry.

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Many construction industry decision-makers believe there is a lack of off-site manufacture (OSM) adoption for non-residential construction in Australia. Identification of construction business process was considered imperative in order to assist decision-makers to increase OSM utilisation. The premise that domain knowledge can be re-used to provide an intervention point in the construction process led a team of researchers to construct simple base-line process models for the complete construction process, segmented into six phases. Sixteen domain knowledge industry experts were asked to review the construction phase base-line models to answer the question “Where in the process illustrated by this base-line model phase is an OSM task?”. Through an iterative and generative process a number of off-site manufacture intervention points were identified and integrated into the process models. The re-use of industry expert domain knowledge provided suggestions for new ways to do basic tasks thus facilitating changes to current practice. It is expected that implementation of the new processes will lead to systemic industry change and thus a growth in productivity due to increased adoption of OSM.

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This paper investigates the critical role of knowledge sharing (KS) in leveraging manufacturing activities, namely integrated supplier management (ISM) and new product development (NPD) to improve business performance (BP) within the context of Taiwanese electronic manufacturing companies. The research adopted a sequential mixed method research design, which provided both quantitative empirical evidence as well as qualitative insights, into the moderating effect of KS on the relationships between these two core manufacturing activities and BP. First, a questionnaire survey was administered, which resulted in a sample of 170 managerial and technical professionals providing their opinions on KS, NPD and ISM activities and the BP level within their respective companies. On the basis of the collected data, factor analysis was used to verify the measurement model, followed by correlation analysis to explore factor interrelationships, and finally moderated regression analyses to extract the moderating effects of KS on the relationships of NPD and ISM with BP. Following the quantitative study, six semi-structured interviews were conducted to provide qualitative in-depth insights into the value added from KS practices to the targeted manufacturing activities and the extent of its leveraging power. Results from quantitative statistical analysis indicated that KS, NPD and ISM all have a significant positive impact on BP. Specifically, IT infrastructure and open communication were identified as the two types of KS practices that could facilitate enriched supplier evaluation and selection, empower active employee involvement in the design process, and provide support for product simplification and the modular design process, thereby improving manufacturing performance and strengthening company competitiveness. The interviews authenticated many of the empirical findings, suggesting that in the contemporary manufacturing context KS has become an integral part of many ISM and NPD activities and when embedded properly can lead to an improvement in BP. The paper also highlights a number of useful implications for manufacturing companies seeking to leverage their BP through innovative and sustained KS practices.

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Graphene has attracted considerable interest over recent years due to its intrinsic mechanical, thermal and electrical properties. Incorporation of small quantity of graphene fillers into polymer can create novel nanocomposites with improved structural and functional properties. This review introduced the recent progress in fabrication, properties and potential applications of graphene-polymer composites. Recent research clearly confirmed that graphene-polymer nanocomposites are promising materials with applications ranging from transportation, biomedical systems, sensors, electrodes for solar cells and electromagnetic interference. In addition to graphene-polymer nanocomposites, this article also introduced the synergistic effects of hybrid graphene-carbon nanotubes (CNTs) on the properties of composites. Finally, some technical problems associated with the development of these nanocomposites are discussed.

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CTAC2012 was the 16th biennial Computational Techniques and Applications Conference, and took place at Queensland University of Technology from 23 - 26 September, 2012. The ANZIAM Special Interest Group in Computational Techniques and Applications is responsible for the CTAC meetings, the first of which was held in 1981.