39 resultados para Associative network theory


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As the field of international business has matured, there have been shifts in the core unit of analysis. First, there was analysis at country level, using national statistics on trade and foreign direct investment (FDI). Next, the focus shifted to the multinational enterprise (MNE) and the parent’s firm specific advantages (FSAs). Eventually the MNE was analysed as a network and the subsidiary became a unit of analysis. We untangle the last fifty years of international business theory using a classification by these three units of analysis. This is the country-specific advantage (CSA) and firm-specific advantage (FSA) matrix. Will this integrative framework continue to be useful in the future? We demonstrate that this is likely as the CSA/FSA matrix permits integration of potentially useful alternative units of analysis, including the broad region of the triad. Looking forward, we develop a new framework, visualized in two matrices, to show how distance really matters and how FSAs function in international business. Key to this are the concepts of compounded distance and resource recombination barriers facing MNEs when operating across national borders.

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The general stability theory of nonlinear receding horizon controllers has attracted much attention over the last fifteen years, and many algorithms have been proposed to ensure closed-loop stability. On the other hand many reports exist regarding the use of artificial neural network models in nonlinear receding horizon control. However, little attention has been given to the stability issue of these specific controllers. This paper addresses this problem and proposes to cast the nonlinear receding horizon control based on neural network models within the framework of an existing stabilising algorithm.

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The construction industry has become a truly global network of interconnected stakeholders making demands which require the involvement of skilled workforces from all over the world. Construction Management Strategies sets the foundations for understanding and managing construction’s inherent complexity and uniqueness. It establishes clear definitions of commonly accepted terms like built environment, construction, civil engineering, etc. which are often given confusing and conflicting interpretations. It cuts through the plethora of overlapping role titles currently used in the construction sector that make it difficult to establish how projects are actually managed.

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This contribution introduces a new digital predistorter to compensate serious distortions caused by memory high power amplifiers (HPAs) which exhibit output saturation characteristics. The proposed design is based on direct learning using a data-driven B-spline Wiener system modeling approach. The nonlinear HPA with memory is first identified based on the B-spline neural network model using the Gauss-Newton algorithm, which incorporates the efficient De Boor algorithm with both B-spline curve and first derivative recursions. The estimated Wiener HPA model is then used to design the Hammerstein predistorter. In particular, the inverse of the amplitude distortion of the HPA's static nonlinearity can be calculated effectively using the Newton-Raphson formula based on the inverse of De Boor algorithm. A major advantage of this approach is that both the Wiener HPA identification and the Hammerstein predistorter inverse can be achieved very efficiently and accurately. Simulation results obtained are presented to demonstrate the effectiveness of this novel digital predistorter design.

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The functional networks of cultured neurons exhibit complex network properties similar to those found in vivo. Starting from random seeding, cultures undergo significant reorganization during the initial period in vitro, yet despite providing an ideal platform for observing developmental changes in neuronal connectivity, little is known about how a complex functional network evolves from isolated neurons. In the present study, evolution of functional connectivity was estimated from correlations of spontaneous activity. Network properties were quantified using complex measures from graph theory and used to compare cultures at different stages of development during the first 5 weeks in vitro. Networks obtained from young cultures (14 days in vitro) exhibited a random topology, which evolved to a small-world topology during maturation. The topology change was accompanied by an increased presence of highly connected areas (hubs) and network efficiency increased with age. The small-world topology balances integration of network areas with segregation of specialized processing units. The emergence of such network structure in cultured neurons, despite a lack of external input, points to complex intrinsic biological mechanisms. Moreover, the functional network of cultures at mature ages is efficient and highly suited to complex processing tasks.

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This paper aims to develop a mathematical model based on semi-group theory, which allows to improve quality of service (QoS), including the reduction of the carbon path, in a pervasive environment of a Mobile Virtual Network Operator (MVNO). This paper generalise an interrelationship Machine to Machine (M2M) mathematical model, based on semi-group theory. This paper demonstrates that using available technology and with a solid mathematical model, is possible to streamline relationships between building agents, to control pervasive spaces so as to reduce the impact in carbon footprint through the reduction of GHG.

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Last fall, a network of the European Cooperation in Science and Technology (COST), called “Basic Concepts for Convection Parameterization in Weather Forecast and Climate Models” (COST Action ES0905; see http://w3.cost.esf.org/index.php?id=205&action_number=ES0905), organized a 10-day training course on atmospheric convection and its parameterization. The aim of the workshop, held on the island of Brac, Croatia, was to help young scientists develop an in-depth understanding of the core theory underpinning convection parameterizations. The speakers also sought to impart an appreciation of the various approximations, compromises, and ansatz necessary to translate theory into operational practice for numerical models.

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It has been years since the introduction of the Dynamic Network Optimization (DNO) concept, yet the DNO development is still at its infant stage, largely due to a lack of breakthrough in minimizing the lengthy optimization runtime. Our previous work, a distributed parallel solution, has achieved a significant speed gain. To cater for the increased optimization complexity pressed by the uptake of smartphones and tablets, however, this paper examines the potential areas for further improvement and presents a novel asynchronous distributed parallel design that minimizes the inter-process communications. The new approach is implemented and applied to real-life projects whose results demonstrate an augmented acceleration of 7.5 times on a 16-core distributed system compared to 6.1 of our previous solution. Moreover, there is no degradation in the optimization outcome. This is a solid sprint towards the realization of DNO.

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This perspectives paper and its associated commentaries examine Alan Rugman's conceptual contribution to international business scholarship. Most significantly, we highlight Rugman's version of internalization theory as an approach that integrates transaction cost economics and ‘classical’ internalization theory with elements from the resource-based view, such that it is especially relevant to strategic management. In reviewing his oeuvre, we also offer observations on his ideas for ‘new internalization theory’. We classify his other novel insights into four categories: Network Multinationals; National competitiveness; Development and public policy; and Emerging Economy MNEs. This special section offers multiple views on how his work informed the larger academic debate and considers how these ideas might evolve in the longer term.