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A GVC (Global Value Chain) optimization requires appropriate approach to make it happen, however, a good approach is not enough when the optimization requires a big changing throughout the chain. It is very important to have a methodology of change management during change processes for GVC optimization. This paper describes the principle of change management, and illustrates a case study on how to...
Low-rank matrix recovery (MR) has been widely used in data analysis and dimensionality reduction. As a direct heuristic to MR, convex relaxation is usually degraded by the repeated calling of singular value decomposition (SVD), especially in large-scale applications. In this paper, we propose a novel Riemannian optimization method (ROAM) for MR problem by exploiting the Riemannian geometry of the...
With the rapid progress of information and electronic technology, traditional industrial processes are becoming more and more complex. It is very important for manufacturing enterprises to manage and control the product quality under the circumstance of big data. Based on artificial systems, computational experiments, and parallel execution approach, modeling methods by mechanism, data, heuristic...
It is difficult to select a composite service with the lowest actual executing cost using the existing methods for QoS-aware service composition in cloud computing. By analyzing the dynamic execution process of composite service with state transition matrix, this paper proposes a new QoS aware optimal service composition method. In view of the effect of composite services reliability on the composite...
With the fast development of the economy, the urban traffic demands increases rapidly, Bus rapid transit (BRT) system, a new type and high efficient bus operator system and a comprehensive mass transit system between the metro and regular bus systems, can alleviate traffic congestion, reduce resident traffic cost effectively, and improve transportation quality and efficiency, with its advantages becomes...
This paper addresses optimal spectrum sensing in cognitive radio networks considering its system level cost that accounts for the local processing cost of sensing (sample collection and energy calculation at each secondary user) as well as the transmission cost (forwarding energy statistic from secondary users to fusion center). The optimization problem solves for the appropriate number of samples...
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