• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Korean Journal of Heritage: History & Science
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• v.44 no.2
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• pp.76-95
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• 2011

After dismantled, Mireuksajiseoktap(Stone pagoda of Mireuksa Templesite) is being in the stage of restoration design. Now, different ways - producing restoration model, a 3 dimension simulation - have been requested to make more detailed and clearer restoration design prior to confirmation of its restoration design and actual restoration carry-out. This thesis proposes the way to build the detailed model for better restoration plan using extensively-used Reverse Engineering technique and Rapid Prototyping. It also introduces each stage such as a 3-dimension actual measurement, building database, a 3-dimension simulation etc., to build a desirable model. On the top of that, this thesis reveals that after dismantled, MIruksaji stone pagoda's interior and exterior were not constructed into pieces but wholeness, so that its looks can be grasped in more virtually and clearly. Secondly, this thesis makes a 3-dimension study on the 2-dimension design possible by acquiring basic materials about a 3-dimension design. Thirdly, the individual feature of each member like the change of member location can be comprehended, considering comparing analysis and joint condition of member. Lastly, in the structural perspective this thesis can be used as reference materials for structure reinforcement design by grasping destructed aspects of stone pagoda and weak points of the structure. In dismantlement-repair and restoration work of cultural properties that require delicate attention and exactness, there may be evitable errors on time and space in building reinforcement and restoration design based on a 2-dimension plan. Especially, the more complicate and bigger the subject is, the more difficult an analysis about the status quo and its delicate design are. A series of pre-review, based on the 3-dimension data according to actual measurement, can be one of the effective way to minimize the possibility that errors about time - space happen by building more delicate plan and resolving difficulties.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.49-52
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• 1989

Some limits are in two-dimensional analysis by finite element method to electromagnetic machine having finite dimension. Therefore three-dimensional analysis by finite element method, which are modeling original form of models are needed in order to gain accurate solutions. This paper present three-dimensional time varing magnetic field analysis method using electric field E and magnetic scarlar potential $\Omega$, and examine sample model.

• Proceedings of the IEEK Conference
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• 2003.07b
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• pp.775-778
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• 2003

In this paper, we report our quantum mechanical approach for the analysis of FinFET in a self-consistent manner. The simulation results are carefully investigated for FinFET with an electrical channel length(Leff) of 30nm and with a fin thickness(Tsi) of 10～35nm. We also demonstrated the differences in the simulations for the classical and quantum-mechanical simulation approaches, respectively. These simulation results also imply that it is necessary to solve the coupled Poisson and Schrodinger equations in a self-consistent manner for analyzing the sub-30nm MOSFETS including FinFET.

• Journal of the Korea Computer Industry Society
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• v.10 no.5
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• pp.207-212
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• 2009

In this paper, the cardiac color animation software for cardiac activation system based on PC was developed. This software was implemented with 3 dimension cardiac color modeling and rotating.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.198-200
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• 1997

This paper consider a simple Nondestructive Testing(NDT) having eddy currnt effect. We analyzed the two dimension modeling of alternative magnetic field. eddy current with voltage source. And, the current magnitude and phase data obtained from each different frequency five object position is used for learning the neural network. Therefore, we can recognize an object position pattern from new input current magnitude, phase data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.3
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• pp.30-35
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• 2008

As demands for being economical, precise drilling process is on the increase. Therefore, the objective of this study is to develop a step cutter that can be controllable through micro dimension and can be changed from separate manufacturing processes of drilling and boring into an integrated one. In order to attain this object the step cutter is designed with a 3D geometric modeling and the design could be modified easily by using parametric modeling methodology. Also, collision is not occurred during manufacturing process because of cutting simulation. The step cutter is assembled by parts made up of 5-axis machining and sintering. Validation tests are accomplished. They show that developed cutter has characteristics such as reduction of machining time as well as the good surface roughness of the machined hole. Indeed, reliability could be obtained from a durability test.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.353-356
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• 2002

In vehicle accidents, the rolling, pitching, and yawing which are produced by collisions affect the motions of vehicle. Therefore, vehicle behavior under impact situation should be analyzed in three-dimension. In this study, three-dimensional vehicle dynamic equations based on impulse-momentum conservation principles under vehicle impact are introduced for simulation. This analysis has been performed by the real vehicle impact data from JARI and RICSAC. This study suggested each system modeling such as suspension, steering, brake and tire as well as the appropriate vehicle behavior simulation model with respect to pre and post impact.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.215-222
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• 1997

This paper deals with the problem of generating a uniform tetrahedral mesh which fills a 3-D space with the tetrahedra which are close to the equilateral tetrahedra as possible. This problem is particularly interesting in finite element modeling where a fat triangulation minimizes the error of an analysis. Fat triangulation is defined as a scheme for generating an equilateral triangulation as possible in a given dimension. In finite element modeling, there are many algorithms for generating a mesh in 2-D and 3-D. One of the difficulties in generating a mesh in 3-D is that a 3-D object can not be filled with uniform equilateral tetrahedra only regardless of the shape of the boundary. Fat triangulation in 3-D has been proved to be the one which fills a 3-D space with the tetrahedra which are close to the equilateral as possible. Topological and geometrical properties of the fat triangulation and its application to meshing algorithm are investigated.

• Communications for Statistical Applications and Methods
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• v.20 no.3
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• pp.235-240
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• 2013

Generalized linear mixed models(GLMMs) are frequently used for the analysis of longitudinal categorical data when the subject-specific effects is of interest. In GLMMs, the structure of the random effects covariance matrix is important for the estimation of fixed effects and to explain subject and time variations. The estimation of the matrix is not simple because of the high dimension and the positive definiteness; subsequently, we practically use the simple structure of the covariance matrix such as AR(1). However, this strong assumption can result in biased estimates of the fixed effects. In this paper, we introduce Bayesian modeling approaches for the random effects covariance matrix using a modified Cholesky decomposition. The modified Cholesky decomposition approach has been used to explain a heterogenous random effects covariance matrix and the subsequent estimated covariance matrix will be positive definite. We analyze metabolic syndrome data from a Korean Genomic Epidemiology Study using these methods.