Yu Hua

Yu Hua
Are you Yu Hua?

Claim your profile, edit publications, add additional information:

Contact Details

Yu Hua

Pubs By Year

Pub Categories

Computer Science - Distributed; Parallel; and Cluster Computing (2)
Physics - Optics (1)
High Energy Physics - Experiment (1)
High Energy Physics - Phenomenology (1)
Computer Science - Cryptography and Security (1)

Publications Authored By Yu Hua

Data deduplication is able to effectively identify and eliminate redundant data and only maintain a single copy of files and chunks. Hence, it is widely used in cloud storage systems to save storage space and network bandwidth. However, the occurrence of deduplication can be easily identified by monitoring and analyzing network traffic, which leads to the risk of user privacy leakage. Read More

The K_S-K_L asymmetries in the D meson decays, induced by the interference between the Cabibbo-favored and the doubly Cabibbo-suppressed amplitudes, can help to understand the dynamics of charm decays. We study the K_S-K_L asymmetries and the branching fractions of corresponding processes in the factorization-assisted topological-amplitude approach in which significant flavor SU(3) symmetry breaking effects are included. Except for the two-body non-leptonic D decays into K_S or K_L and another pseudoscalar meson, we firstly study the K_S-K_L asymmetries in the processes decaying into neutral kaons and a vector meson. Read More

The nitrogen vacancy (NV) center in diamond has been widely applied for quantum information and sensing in last decade. Based on the laser polarization dependent excitation of fluorescence emission, we propose a super-resolution microscopy of NV center. A series of wide field images of NV centers are taken with different polarizations of the linear polarized excitation laser. Read More

Nearest Neighbor(s) search is the fundamental computational primitive to tackle massive dataset. Locality Sensitive Hashing (LSH) has been a bracing tool for Nearest Neighbor(s) search in high dimensional spaces. However, traditional LSH systems cannot be applied in online big data systems to handle a large volume of query/update requests, because most of the systems optimize the query efficiency with the assumption of infrequent updates and missing the parallel-friendly design. Read More