9,829 research outputs found

    Survey on Additive Manufacturing, Cloud 3D Printing and Services

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    Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

    A framework for modelling mobile radio access networks for intelligent fault management

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    LEVERAGING SOA IN BANKING SYSTEMS INTEGRATION

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    There is no doubt that the systems integration is one of the most important and complicated tasks in software filed especially for complex applications like banking systems. Complexity in integrating banking systems often comes from continues changes in both technical and business features provided by them to meet customer needs. Banking systems always come from different software vendors which mean using platforms and different design and architecture patterns, and this for sure adds extra complexity for integrating them. Serviceoriented architecture (SOA) is a promising method in software filed that aims to build or restructure software systems in a manner that makes their maintenance and integration easier. Agility is the most important goal that should be achieved when building and integrating banking systems. Simply, agility is needed to meet market needs quickly and efficiently and SOA is the way that could provide itSOA, SOI, P2P Integration, Web Services, and Legacy Code

    Understanding new venture market application search processes: A propositional model.

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    Technology-based ventures are confronted with complex decisions on how to apply their technology platform in highly uncertain and ambiguous market environments. Based on four case studies, a dynamic decision model is developed in which we highlight the similarities between the search and learning processes in venture development contexts and in new product development contexts. This entrepreneurial search and learning process is understood as consisting of sequences of episodes – characterized by uncertainty and ambiguity - and scripts – i.e. approaches to market application search. The model implies that a venture's adaptability - i.e. its ability to move efficiently and effectively between these episodes and their related scripts - influences its survival.Case studies; Decision; Decisions; Learning; Market; Model; Processes; Product; Product development; Research; Sequences; Similarity; Studies; Technology; Uncertainty;

    Agent modelling of cluster formation processes in regional economic systems

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    The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment

    Public survey instruments for business administration using social network analysis and big data

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    Purpose: The subject matter of this research is closely intertwined with the scientific discussion about the necessity of developing and implementing practice-oriented means of measuring social well-being taking into account the intensity of contacts between individuals. The aim of the research is to test the toolkit for analyzing social networks and to develop a research algorithm to identify sources of consolidation of public opinion and key agents of influence. The research methodology is based on postulates of sociology, graph theory, social network analysis and cluster analysis. Design/Methodology/Approach: The basis for the empirical research was provided by the data representing the reflection of social media users on the existing image of Russia and its activities in the Arctic, chosen as a model case. Findings: The algorithm allows to estimate the density and intensity of connections between actors, to trace the main channels of formation of public opinion and key agents of influence, to identify implicit patterns and trends, to relate information flows and events with current information causes and news stories for the subsequent formation of a "cleansed" image of the object under study and the key actors with whom this object is associated. Practical Implications: The work contributes to filling the existing gap in the scientific literature, caused by insufficient elaboration of the issues of applying the social network analysis to solve sociological problems. Originality/Value: The work contributes to filling the existing gap in the scientific literature formed as a result of insufficient development of practical issues of using analysis of social networks to solve sociological problems.peer-reviewe

    Digital Ecosystems: Ecosystem-Oriented Architectures

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    We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa
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