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OPT-VCG: A Novel Proposal for 3D SoC Test Optimization
Jingbo Shao,Yongqing Fu,Xiaoxiao Liu,Guohui Zhou 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.2
As an emerging technology for on-chip interconnect scaling in vertical direction in semiconductor industry, through-silicon-via (TSV) demonstrates its advantages and has been adopted for 3D SoC implementation. Optimal test architecture and test scheduling are significant for stacked 3D SoC design. However existing design methods cannot achieve both optimal test time and individual rationality. In this paper, game theory based 3D SoC test architecture optimization and test scheduling method is proposed under constraints of the available number of TSVs for test time minimization and rational test band width allocation. VCG algorithm is brought to 3D SoC design. Three kinds of stacked SoCs are built using ITC’02 SoC test benchmarks, and experimental results on them show the advantages of the proposed method over prior work.
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Database Performance Optimization for SQL Server Based on Hierarchical Queuing Network Model
Jingbo Shao,Xiaoxiao Liu,Yingmei Li,Jingyu Liu 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.1
With the ever-increasing complexity and variety of database workload, database application system has been imposed on higher and higher performance requirements. Database system consists of software and hardware. And the factors that affect database performance are uncertain. In order to tackle the issue of database system for SQL server, this paper proposes hierarchical queuing network model for performance prediction, and a model is established for both software resources and hardware resources, the nested resources are linearized by hierarchical calling, thus finding out the main factors for system performance bottleneck, and system performance is adjusted and optimized accordingly. The performance tuning algorithm for SQL server database based on the hierarchical queuing network is presented in detail. And TPC-C benchmark is adopted for simulation. Experimental results show the proposed method achieves 16.8% performance increase on average, and TPS is improved by 40% compared to previous method.
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Soil characteristics and new formation model of loess on the Chinese Loess Plateau
Jingbo Zhao,Xiaoqing Luo,Yandong Ma,Tianjie Shao,Yingli Yue 한국지질과학협의회 2017 Geosciences Journal Vol.21 No.4
In this paper characteristics of loess are discussed from a pedological perspective. A new model of loess formation is presented, developed in different soil formation processes according to its pedogenic characteristics, including soil structure, organic matter content and CaCO3 content. Loess has all the characteristics of typical soils and all five soil-forming factors have important roles in loess formation. In this regard, loess is a type soil and the previous concept of loess actually comprises various kinds of palaeosols developed in cold and arid climatic conditions. The loess-forming process is, in fact, equivalent to a pedogenic process and loess layers with different characteristics represent different pedogenic processes indicative of different environments, such as desert-steppe, steppe or forest-steppe climatic conditions. In contrast to red-brown palaeosol layers, which develop in warm and wet climates, loesses – more accurately called ‘loessial palaeosols’ – are grey-yellow palaeosols and can be regarded as a reliable indicator of cold and arid climate. The model of loess formation suggests that aeolian dust transfers to grey-yellow palaeosols via pedogenesis and the characteristics of loess are mainly a result of climatic conditions and diagenesis processes after its sedimentation. This new model of loess formation also suggests that traditional pedological theory has its limitations when explaining soil formation processes.
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Study of Data Stream Clustering Based on MSF
Yingmei Li,Min Li,Jingbo Shao,Gaoyang Wang 보안공학연구지원센터 2015 International Journal of Database Theory and Appli Vol.8 No.1
Nowadays with the rapid development of wireless sensor networks, and network traffic monitoring, stream data gradually becomes one of the most popular data models. Stream data is different from the traditional static data. Clustering analysis is an important technology for data mining, so that many researchers pay their attention to the clustering of stream data. In this paper, MSFS algorithm is proposed. By means of the experimental verification analysis, based on biologically inspired computational model, higher clustering purity on both the real dataset and the simulation datasets existence is demonstrated for the proposed algorithm. In other words, the cluster result of MSFS algorithm is advantageous over previous method.
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Numerical simulation of holes and inclusions using adaptive polygonal finite element method
Shengyong Ding,Guojian Shao,Ang Li,Jingbo Su,Hougai Shi 대한기계학회 2017 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.31 No.9
An adaptive polygonal finite element method using the techniques of cut-cell and quadtree refinement is presented for modeling holes and inclusions in 2-D solids. A mesh template is used to ensure the high-quality refined elements generated in quadtree refinement. By coupling the level set method, the polygonal computational mesh is directly extracted from the mesh template in every adaptive cycle. An error estimator based on recovery stress is devoted for adaptive purpose, which allows the mesh where it is needed is further refining. This method allows to model arbitrary shape holes and inclusions in arbitrary-geometry 2-D solid using the initial mesh of few rectangular elements, which considerably simplifies construction of the finite element model. And one curved boundary can be accurately represented though several steps of refinement. Numerical examples are solved and the obtained results are compared with reference solutions to show the simplicity and efficiency of the proposed method.
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