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MapReduce programming model is widely used for large scale and one-time data-intensive distributed computing, but lacks flexibility and efficiency of processing small incremental data. IncMR framework is proposed in this paper for incrementally processing new data of a large data set, which takes state as implicit input and combines it with new data. Map(More)
Multi-cue integration has been researched extensively for robust visual tracking. Researchers aim to use multiple cues under the probabilistic methods, such as Particle Filtering and Condensation. On the other hand, Color-based Mean-Shift has been addressed as an effective and fast algorithm for tracking color blobs. However, this deterministic searching(More)
This paper presents Cloud Bay, an online resource trading and leasing platform for multi-party resource sharing. Following a market-oriented design principle, Cloud Bay provides an abstraction of a shared virtual resource space across multiple administration domains, and features enhanced functionalities for scalable and automatic resource management and(More)
Taxol is a front‑line chemotherapeutic agent for the treatment of patients with multiple types of tumor. However, resistance to Taxol remains one of the principal causes of cancer‑associated mortality. Glutamine, which is metabolized via a glutaminase (GLS)‑dependent process, termed glutaminolysis, is important in cell growth and metabolism. The present(More)
In spaceborne synthetic aperture radar, undersampling at the rate of the pulse repetition frequency causes azimuth ambiguity, which induces ghost into the images. This paper introduces compressed sensing for azimuth ambiguity suppression and presents two novel methods from the perspectives of system design and image formation, known as azimuth random(More)
Colour-based mean shift is an effective and fast algorithm for tracking colour blobs. However, it is vulnerable to full occlusion and target out of range for a few frames. This paper proposes a tracking method based on multi-cue integration and auxiliary objects to deal with these problems. A colour-location-prediction integration mean shift method is(More)
A series of organic thiolate/disulfide redox couples have been synthesized and have been studied systematically in dye-sensitized solar cells (DSCs) on the basis of an organic dye (TH305). Photophysical, photoelectrochemical, and photovoltaic measurements were performed in order to get insights into the effects of different redox couples on the performance(More)
Parallel/Distributed computing frameworks, such as MapReduce and Dryad, have been widely adopted to analyze massive data. Traditionally, these frameworks depend on manual configuration to acquire network proximity information to optimize the data placement and task scheduling. However, this approach is cumbersome, inflexible or even infeasible in largescale(More)
Compressive sensing (CS) techniques offer a framework for the detection and allocation of sparse signal with a reduced number of measurements. This paper proposes a novel SAR range compression, namely compressive sensing with chirp scaling (CS-CS), achieving the same range resolution as conventional SAR approach, while using fewer range samplings. In order(More)