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Intelligent transportation systems, e.g., Uber, have become an important tool for urban transportation. An important problem is k nearest neighbor (kNN) search on moving objects with road-network constraints, which, given moving objects on the road networks and a query, finds k nearest objects to the query location. Existing studies focus on either kNN search on static objects or continuous kNN search...
Data anonymization techniques are the main way to achieve privacy protection, and as a classical anonymity model, K-anonymity is the most effective and frequently-used. But the majority of K-anonymity algorithms can hardly balance the data quality and efficiency, and ignore the privacy of the data to improve the data quality. To solve the problems above, by introducing the concept of “diameter” and...
In this paper, a novel navigation based on vision for wireless capsule endoscopies is proposed. The algorithm based on dark regions was improved by setting the Region of Interest (ROI) to limit the search coverage around the last navigation point, introducing the morphology method to eliminate diverticula and vesicae and raising the concept of position weight to reckon navigation points in the case...
Efficient top-k query processing in highly distributed environments is useful but challenging. This paper focuses on the problem over vertically partitioned data and aims to propose efficient algorithms with lower communication cost. Two new algorithms, DBPA and BulkDBPA, are proposed in this paper. DBPA is a direct extension of the centralized algorithm BPA2 into distributed environments. Absorbing...
Grid computing deals with computationally intensive distributed resources on heterogeneous environment, so grid scheduling is a fundamental challenge and is critical to performance and cost. Traditional grid scheduling algorithms most use deterministic models. But grid environments in the real world are subject to many sources of uncertainty or randomness, such as network status, job execution costs,...
Optimal assigning jobs to resources is an important problem in grid computing. Now grid scheduling policies are mostly traditional heuristic algorithms for scheduling n independent tasks on m processors in early finishing time. However grids have developed to wide area, heterogeneous and non autonomous environments, business objective also became crucial for the success of the scheduling. Therefore...
This paper presents a new algorithm for exact estimation of the minimum memory size required by programs dealing with array computations. Based on parametric partitioning of the iteration space and formalized live variable analysis, our algorithm transforms the minimum memory size estimation into an equivalent problem: integer point counting for intersection/union of mappings of parameterized polytopes...
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