14,244 research outputs found
SPIDA: Abstracting and generalizing layout design cases
Abstraction and generalization of layout design cases generate new knowledge that is more widely applicable to use than specific design cases. The abstraction and generalization of design cases into hierarchical levels of abstractions provide the designer with the flexibility to apply any level of abstract and generalized knowledge for a new layout design problem. Existing case-based layout learning (CBLL) systems abstract and generalize cases into single levels of abstractions, but not into a hierarchy. In this paper, we propose a new approach, termed customized viewpoint - spatial (CV-S), which supports the generalization and abstraction of spatial layouts into hierarchies along with a supporting system, SPIDA (SPatial Intelligent Design Assistant)
Disentangling agglomeration and network externalities : a conceptual typology
Agglomeration and network externalities are fuzzy concepts. When different meanings are (un)intentionally juxtaposed in analyses of the agglomeration/network externalities-menagerie, researchers may reach inaccurate conclusions about how they interlock. Both externality types can be analytically combined, but only when one adopts a coherent approach to their conceptualization and operationalization, to which end we provide a combinatorial typology. We illustrate the typology by applying a state-of-the-art bipartite network projection detailing the presence of globalized producer services firms in cities in 2012. This leads to two one-mode graphs that can be validly interpreted as topological renderings of agglomeration and network externalities
Machine-Part cell formation through visual decipherable clustering of Self Organizing Map
Machine-part cell formation is used in cellular manufacturing in order to
process a large variety, quality, lower work in process levels, reducing
manufacturing lead-time and customer response time while retaining flexibility
for new products. This paper presents a new and novel approach for obtaining
machine cells and part families. In the cellular manufacturing the fundamental
problem is the formation of part families and machine cells. The present paper
deals with the Self Organising Map (SOM) method an unsupervised learning
algorithm in Artificial Intelligence, and has been used as a visually
decipherable clustering tool of machine-part cell formation. The objective of
the paper is to cluster the binary machine-part matrix through visually
decipherable cluster of SOM color-coding and labelling via the SOM map nodes in
such a way that the part families are processed in that machine cells. The
Umatrix, component plane, principal component projection, scatter plot and
histogram of SOM have been reported in the present work for the successful
visualization of the machine-part cell formation. Computational result with the
proposed algorithm on a set of group technology problems available in the
literature is also presented. The proposed SOM approach produced solutions with
a grouping efficacy that is at least as good as any results earlier reported in
the literature and improved the grouping efficacy for 70% of the problems and
found immensely useful to both industry practitioners and researchers.Comment: 18 pages,3 table, 4 figure
Detecting early signs of the 2007-2008 crisis in the world trade
Since 2007, several contributions have tried to identify early-warning
signals of the financial crisis. However, the vast majority of analyses has
focused on financial systems and little theoretical work has been done on the
economic counterpart. In the present paper we fill this gap and employ the
theoretical tools of network theory to shed light on the response of world
trade to the financial crisis of 2007 and the economic recession of 2008-2009.
We have explored the evolution of the bipartite World Trade Web (WTW) across
the years 1995-2010, monitoring the behavior of the system both before and
after 2007. Our analysis shows early structural changes in the WTW topology:
since 2003, the WTW becomes increasingly compatible with the picture of a
network where correlations between countries and products are progressively
lost. Moreover, the WTW structural modification can be considered as concluded
in 2010, after a seemingly stationary phase of three years. We have also
refined our analysis by considering specific subsets of countries and products:
the most statistically significant early-warning signals are provided by the
most volatile macrosectors, especially when measured on developing countries,
suggesting the emerging economies as being the most sensitive ones to the
global economic cycles.Comment: 18 pages, 9 figure
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