Shuai Zheng

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—While early emphasis of Infrastructure as a Service (IaaS) clouds was on providing resource elasticity to end users, providers are increasingly interested in over-committing their resources to maximize the utilization and returns of their capital investments. In principle, over-committing resources hedges that users—on average—only need a small portion of(More)
Real life data often includes information from different channels. For example, in computer vision, we can describe an image using different image features, such as pixel intensity, color, HOG, GIST feature, SIFT features , etc.. These different aspects of the same objects are often called multi-view (or multi-modal) data. Low-rank regression model has been(More)
—Intrinsic to " big data " processing workloads (e.g., iterative MapReduce, Pregel, etc.) are cyclical resource utilization patterns that are highly synchronized across different resource types as well as the workers in a cluster. In Infrastructure as a Service settings, cloud providers do not exploit this characteristic to better manage VMs because they(More)
High Performance Computing (HPC) is becoming a common tool in many research areas. Social influence (e.g., project collaboration) among increasing users of HPC systems creates bursty behavior in underlying workloads. This bursty behavior is increasingly common with the advent of grid computing and cloud computing. Mining the user bursty behavior is(More)
BACKGROUND Alendronate (ALE) is a conventional drug used to treat osteoporosis. Low-magnitude whole-body vibration (WBV) exercise has been developed as a potential treatment for osteoporosis. The aim of this study was to investigate whether low-magnitude WBV could enhance the protective effect of ALE on bone properties in ovariectomized rats. METHODS A(More)
Advanced oxidation protein products (AOPPs) are novel markers of oxidation-mediated protein damage, and accumulation of AOPPs is involved in many pathophysiological conditions. Our previous studies demonstrated that the serum level of AOPPs negatively correlated with the age-related change in bone mineral density (BMD) in rats and that AOPPs inhibited rat(More)
Deep Learning is a very powerful machine learning model. Deep Learning trains a large number of parameters for multiple layers and is very slow when data is in large scale and the architecture size is large. Inspired from the shrinking technique used in accelerating computation of Support Vector Machines (SVM) algorithm and screening technique used in(More)
BACKGROUND Advanced oxidation protein products (AOPPs) are acknowledged as a novel marker of oxidation-mediated protein damage. This study aimed to investigate the plasma levels of AOPPs in postmenopausal osteoporotic women, and to determine the relationship between AOPPs accumulation and lumbar bone mineral destiny (BMD) or bone turnover markers. (More)
Genetic etiology in majority of patients with sporadic thoracic aortic aneurysm and dissections (STAAD) remains unknown. Recent GWAS study suggested common variant(s) in FBN1 is associated with STAAD. The present study aims to test this hypothesis and to identify mutation spectrum by targeted exome sequencing of the FBN1 gene in 146 unrelated patients with(More)