• Journal of the Korean Crystal Growth and Crystal Technology
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• v.26 no.6
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• pp.225-231
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• 2016

The valence band maximum (VBM) and conduction band minimum (CBM) of Al-doped GaInAsSb alloys substrated on GaSb are calculated by using an analytic approximation based on the tight binding method. The relative positions of the VBM and CBM between Al-GaInASSb and GaSb determine band alignement type, valence band offset (VBO) and conductin band offset (CBO) for the heterojunctions. In this study, aluminium doping is assumed to be substituted in the cation site and limited up to 20 % because it can easily oxidize and degrade materials. It is found that the Al-doped alloys exhibit type-II band alignments over the entire composition range and make the band gaps increase, whereas the VBO and CBO decrease. The decreasing rate of VBO is higher than that of CBO, which implies the Al components play a decisive role in controlling electrons at the interface. The Al-dopled GaInAsSb alloy has a direct band gap induced by $E({\Gamma})$ with a considerable distance from the E(L) and E(X), however, $E({\Gamma})$ approaches to E(L) and E(X) in the high Sb concentration (Sb > 0.7-0.8) which might affect the electron mobility and degrade the optical quality.

• Korean Journal of Optics and Photonics
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• v.25 no.1
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• pp.29-37
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• 2014

We have studied and demonstrated general, systematic error-correction methods for a dual rotating quarter-wave plate ellipsometer. To estimate and correct 5 systematic error sources (three offset angles and two unexpected retarder phase delays), we used 11 of the 25 Fourier components of the ellipsometry signal obtained in the absence of an optical sample. Using these 11 Fourier components, we can determine the errors from the 5 sources with nonlinear optimization methods. We found systematic errors ${\epsilon}_3$, ${\epsilon}_4$, ${\epsilon}_5$) are more sensitive to the inverted Mueller matrix than retarder phase delay errors (${\epsilon}_1$, ${\epsilon}_2$) because of their small condition numbers. To correct these systematic errors we have found that error of any variety must be less than 0.05 rad. Finally, we can use the magnitudes of these errors to correct the Mueller matrix of optical components. From our experimental ellipsometry signals, we can measure phase delay and the rotational angular position of its fast axis for a half-wave plate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2338-2343
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• 2015

An analytical model was developed in this study and then implemented into a tool for automation of FEA (Finite Element Analysis) of a spindle system for natural frequencies and modes in the universal FEA software, ANSYS. VBA of EXCEL was used for the implementation. It allowed graphic user interfaces (GUIs) to be developed for a user to interact with the tool and, in addition, an EXCEL spreadsheet to be used for data arrangement. A code was developed in the language of ANSYS to generate the geometric model of the spindle system, sequentially to construct the analytical model based on the information in the GUIs, and finally to perform computation for the FEA. Its automation of the model generation and analysis can help to identify a near optimal design of the spindle system under design in minimum time and efforts.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.5
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• pp.361-366
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• 2017

As the recent development of computing architecture and application software technology, real world simulation, which is the ultimate destination of computer simulation, is emerging as a practical issue in several research sectors. In this paper, metal plate motion in a square shock tube for small time interval was calculated using a supercomputing-based fluid-structure-combustion multi-physics simulation tool called Illinois Rocstar, developed in a US national R amp; D program at the University of Illinois. Afterwards, the simulation results were compared with those from experiments. The coupled solvers for unsteady compressible fluid dynamics and for structural analysis were based on the finite volume structured grid system and the large deformation linear elastic model, respectively. In addition, a strong correlation between calculation and experiment was shown, probably because of the predictor-corrector time-integration scheme framework. In the future, additional validation studies and code improvements for higher accuracy will be conducted to obtain a reliable open-source software research tool.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.9
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• pp.479-490
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• 2001

In this paper, we consider the method of partitioning a sphere into faces with a set of spherical convex polygons $\Gamma$=$｛P_1...P_n｝$ for determining the maximum of minimum intersection. This problem is commonly related with five geometric problems that fin the densest hemisphere containing the maximum subset of $\Gamma$, a great circle separating $\Gamma$, a great circle bisecting $\Gamma$ and a great circle intersecting the minimum or maximum subset of $\Gamma$. In order to efficiently compute the minimum or maximum intersection of spherical polygons. we take the approach of edge-based partition, in which the ownerships of edges rather than faces are manipulated as the sphere is incrementally partitioned by each of the polygons. Finally, by gathering the unordered split edges with the maximum number of ownerships. we approximately obtain the centroids of the solution faces without constructing their boundaries. Our algorithm for finding the maximum intersection is analyzed to have an efficient time complexity O(nv) where n and v respectively, are the numbers of polygons and all vertices. Furthermore, it is practical from the view of implementation, since it computes numerical values. robustly and deals with all the degenerate cases, Using the similar approach, the boundary of a general intersection can be constructed in O(nv+LlogL) time, where : is the output-senstive number of solution edges.