947 resultados para 0915 Interdisciplinary Engineering


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In the 20th century, the scholarly study of human relationships both grew dramatically and simultaneously fragmented into various disciplines and subdisciplines. Although diversity of thought is generally considered helpful for the evolution of scientific fields, the value accrued from interdisciplinary discourse depends on the ability of scholars to integrate multiple perspectives and synthesize foundational works in a systematic manner. The goal of this study is to synthesize foundational theories from social and behavioral sciences that have contributed to an understanding of relationship marketing. In seeking to provide a holistic understanding of the field, we incorporate contributions from the disciplines of marketing, management, psychology, and sociology. In building on our analysis, we synthesize our findings into a conceptual model that examines the systematic dimensions of relationship marketing. The article concludes by identifying key themes for contributors to the Journal of Relationship Marketing to consider going forward.

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The UK government is mandating the use of building information modelling (BIM) in large public projects by 2016. As a result, engineering firms are faced with challenges related to embedding new technologies and associated working practices for the digital delivery of major infrastructure projects. Diffusion of innovations theory is used to investigate how digital innovations diffuse across complex firms. A contextualist approach is employed through an in-depth case study of a large, international engineering project-based firm. The analysis of the empirical data, which was collected over a four-year period of close interaction with the firm, reveals parallel paths of diffusion occurring across the firm, where both the innovation and the firm context were continually changing. The diffusion process is traced over three phases: centralization of technology management, standardization of digital working practices, and globalization of digital resources. The findings describe the diffusion of a digital innovation as multiple and partial within a complex social system during times of change and organizational uncertainty, thereby contributing to diffusion of innovations studies in construction by showing a range of activities and dynamics of a non-linear diffusion process.

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This study investigates the child (L1) acquisition of properties at the interfaces of morphosyntax, syntax-semantics and syntax-pragmatics, by focusing on inflected infinitives in European Portuguese (EP). Three child groups were tested, 6–7-year-olds, 9–10-year-olds and 11–12-year-olds, as well as an adult control group. The data demonstrate that children as young as 6 have knowledge of the morpho-syntactic properties of inflected infinitives, although they seem at first glance to show partially insufficient knowledge of their syntax–semantic interface properties (i.e. non-obligatory control properties), differently from children aged 9 and older, who show clearer evidence of knowledge of both types of properties. However, in general, both morpho-syntactic and syntax–semantics interface properties are also accessible to 6–7-year-old children, although these children give preference to a range of interpretations partially different from the adults; in certain cases, they may not appeal to certain pragmatic inferences that permit additional interpretations to adults and older children. Crucially, our data demonstrate that EP children master the two types of properties of inflected infinitives years before Brazilian Portuguese children do (Pires and Rothman, 2009a,b), reasons for and implications of which we discuss in detail.

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A key issue in UK railway history is whether the railway system was an efficient response to the traffic requirements of the economy. The UK railway system was constructed entirely by private enterprise with minimal state subsidies. This chapter considers whether the railway system was 'over-built' because the government ignored the advice of the Railway Committee of the Board of Trade. The chapter suggests that the system was over-built by about 35 per cent. The causes of this over-building are investigated and are found to be mainly social and political failures arising from distrust between MPs and civil servants and public pressure on local MPs to ensure that their constituencies were well served by railways.

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Food industry is critical to any nation’s health and well-being; it is also critical to the economic health of a nation, since it can typically constitute over a fifth of the nation’s manufacturing GDP. Food Engineering is a discipline that ought to be at the heart of the food industry. Unfortunately, this discipline is not playing its rightful role today: engineering has been relegated to play the role of a service provider to the food industry, instead of it being a strategic driver for the very growth of the industry. This paper hypothesises that food engineering discipline, today, seems to be continuing the way it was in the last century, and has not risen to the challenges that it really faces. This paper therefore categorises the challenges as those being posed by: 1. Business dynamics, 2. Market forces, 3. Manufacturing environment and 4. Environmental Considerations, and finds the current scope and subject-knowledge competencies of food engineering to be inadequate in meeting these challenges. The paper identifies: a) health, b) environment and c) security as the three key drivers of the discipline, and proposes a new definition of food engineering. This definition requires food engineering to have a broader science base which includes biophysical, biochemical and health sciences, in addition to engineering sciences. This definition, in turn, leads to the discipline acquiring a new set of subject-knowledge competencies that is fit-for-purpose for this day and age, and hopefully for the foreseeable future. The possibility of this approach leading to the development of a higher education program in food engineering is demonstrated by adopting a theme based curriculum development with five core themes, supplemented by appropriate enabling and knowledge integrating courses. At the heart of this theme based approach is an attempt to combine engineering of process and product in a purposeful way, termed here as Food Product Realisation Engineering. Finally, the paper also recommends future development of two possible niche specialisation programs in Nutrition and Functional Food Engineering and Gastronomic Engineering. It is hoped that this reconceptualization of the discipline will not only make it more purposeful for the food industry, but it will also make the subject more intellectually challenging and attract bright young minds to the discipline.

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In this work, thermodynamic models for fitting the phase equilibrium of binary systems were applied, aiming to predict the high pressure phase equilibrium of multicomponent systems of interest in the food engineering field, comparing the results generated by the models with new experimental data and with those from the literature. Two mixing rules were used with the Peng-Robinson equation of state, one with the mixing rule of van der Waals and the other with the composition-dependent mixing rule of Mathias et al. The systems chosen are of fundamental importance in food industries, such as the binary systems CO(2)-limonene, CO(2)-citral and CO(2)-linalool, and the ternary systems CO(2)-Limonene-Citral and CO(2)-Limonene-Linalool, where high pressure phase equilibrium knowledge is important to extract and fractionate citrus fruit essential oils. For the CO(2)-limonene system, some experimental data were also measured in this work. The results showed the high capability of the model using the composition-dependent mixing rule to model the phase equilibrium behavior of these systems.

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A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

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Document engineering is the computer science discipline that investigates systems for documents in any form and in all media. As with the relationship between software engineering and software, document engineering is concerned with principles, tools and processes that improve our ability to create, manage, and maintain documents (http://www.documentengineering.org). The ACM Symposium on Document Engineering is an annual meeting of researchers active in document engineering: it is sponsored by ACM by means of the ACM SIGWEB Special Interest Group. In this editorial, we first point to work carried out in the context of document engineering, which are directly related to multimedia tools and applications. We conclude with a summary of the papers presented in this special issue.

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Existence of positive solutions for a fourth order equation with nonlinear boundary conditions, which models deformations of beams on elastic supports, is considered using fixed points theorems in cones of ordered Banach spaces. Iterative and numerical solutions are also considered. (C) 2010 IMACS. Published by Elsevier B.V. All rights reserved.

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Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.

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In this paper we present a genetic algorithm with new components to tackle capacitated lot sizing and scheduling problems with sequence dependent setups that appear in a wide range of industries, from soft drink bottling to food manufacturing. Finding a feasible solution to highly constrained problems is often a very difficult task. Various strategies have been applied to deal with infeasible solutions throughout the search. We propose a new scheme of classifying individuals based on nested domains to determine the solutions according to the level of infeasibility, which in our case represents bands of additional production hours (overtime). Within each band, individuals are just differentiated by their fitness function. As iterations are conducted, the widths of the bands are dynamically adjusted to improve the convergence of the individuals into the feasible domain. The numerical experiments on highly capacitated instances show the effectiveness of this computational tractable approach to guide the search toward the feasible domain. Our approach outperforms other state-of-the-art approaches and commercial solvers. (C) 2009 Elsevier Ltd. All rights reserved.

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In this article we address decomposition strategies especially tailored to perform strong coupling of dimensionally heterogeneous models, under the hypothesis that one wants to solve each submodel separately and implement the interaction between subdomains by boundary conditions alone. The novel methodology takes full advantage of the small number of interface unknowns in this kind of problems. Existing algorithms can be viewed as variants of the `natural` staggered algorithm in which each domain transfers function values to the other, and receives fluxes (or forces), and vice versa. This natural algorithm is known as Dirichlet-to-Neumann in the Domain Decomposition literature. Essentially, we propose a framework in which this algorithm is equivalent to applying Gauss-Seidel iterations to a suitably defined (linear or nonlinear) system of equations. It is then immediate to switch to other iterative solvers such as GMRES or other Krylov-based method. which we assess through numerical experiments showing the significant gain that can be achieved. indeed. the benefit is that an extremely flexible, automatic coupling strategy can be developed, which in addition leads to iterative procedures that are parameter-free and rapidly converging. Further, in linear problems they have the finite termination property. Copyright (C) 2009 John Wiley & Sons, Ltd.