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第十三届全国量子化学会议

作者： Kailiang Yu Xubo Wang Linjun Wang Department of Chemistry Zhejiang University

Precise structure information is key to understand the intrinsic properties of nanomaterials. Global optimization has proven to be a useful technique for structure prediction of clusters. In literature, there exist many global optimization algorithms, e.g., simulated annealing, basin-hopping, genetic algorithm et al.[1-4] In this study, we have developed a novel global optimization algorithm based on basin-hopping[1-2] and fuzzy search, which could find out all the lowest energy configurations of Lennard-Jones(LJ) clusters with high efficiency. In global optimization, a huge amount of time is devoted to the local structure optimizations to traverse the phase space. We found that most of these optimizations do not necessarily need to be very accurate. To this end, we work in the discrete phase space and obtain a number of promising candidates for global optimization. These structures are re-optimized one by one in the real space to find out the global minima with the lowest energy. In general, we need to carry out the fuzzy search many times to increase the chance of success. As shown in Fig.1, we get all the lowest energy structures of the standard LJ clusters with less than 550 atoms. Interestingly, the average CPU time to find the global minima is almost an exponential function of the number of atoms. The low scaling and high reliability of the present algorithm imply that our global optimization approach may be promising for general cases, e.g. quantum dots.

关键词： global optimization basin-hopping fuzzy search LJ clusters

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Return just your search:privacy-preserving homoglyph search for arbitrary languages

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Frontiers of Computer Science 2022年第2期16卷 140-151页

作者： Bowen ZHAO Shaohua TANG Ximeng LIU Yiming WU School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006China Zheng Zhiming Lab Peng Cheng LaboratoryShenzhen 518055China College of Mathematics and Computer Science Fuzhou UniversityFuzhou 350108China

searchable encryption is an effective way to ensure the security and availability of encrypted outsourced cloud *** existing solutions,the keyword exact search solution is relatively inflexible,while the fuzzy keyword search solution either has a high index overhead or suffers from the ***,no existing fuzzy keyword search solution considers the homoglyph search on encrypted *** this paper,we propose an efficient privacy-preserving homoglyph search scheme supporting arbitrary languages(POSA,in short).We enhance the performance of the fuzzy keyword search in three ***,we formulate the similarity of homoglyph and propose a privacy-preserving homoglyph ***,we put forward an index build mechanism without the false-positive,which reduces the storage overhead of the index and is suitable for arbitrary ***,POSA returns just the user’s search,i.e.,all returned documents contain the search keyword or its *** theoretical analysis and experimental evaluations on real-world datasets demonstrate the effectiveness and efficiency of POSA.

关键词： searchable encryption cloud storage fuzzy search privacy preservation arbitrary languages

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维普期刊数据库

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A Novel fuzzy Keyword Retrieval Scheme over Encrypted Cloud Data

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Wuhan University Journal of Natural Sciences 2013年第5期18卷 393-401页

作者： TIAN Ke ZHANG Weiming LI Ke WU Junming YU Nenghai School of Information Science and Technology University of Science and Technology of China

In this paper, we focus on the fuzzy keyword search problem over the encrypted cloud data in the cloud computing and propose a novel Two-Step-Bloom-Secure-Filter （TSBSF） scheme based on Bloom filter to realize the efficiency and flexibility of data use. The proposed scheme not only reduces the space complexity significantly but also supports the data update with low time complexity and guarantees the search accuracy. Experimental results on real world data have certified the validity and practicality of this novel method.

关键词： fuzzy search privacy preserving cloud computing

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维普期刊数据库

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