• The korean journal of orthodontics
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• v.21 no.1 s.33
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• pp.113-130
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• 1991

This study was undertaken to investigate soft tissue profile changes by orthodontic treatment in female patients. Traditional cephalometric appraisal yields data of dubious scientific value, the soft tissue profile forms were evaluated by finite element method. The subject was divided into three groups according to Angle's classification and each group was composed of 25 female patients averaged aged 12-14 years at the start of treatment. The changes in soft tissue form were evaluated by computing the degree of distortion in each triangle after treatment compared with the triangle before treatment. The conclusions were as follows; 1. The soft tissue profile forms were evaluated by finite element method and independent evaluation of each element by local changes was possible. 2. Maximum and minimum principal strains showed marked variability depending on the particular finite element and each group and Class II, III sample was greater than Class I sample. 3. Soft tissue size changes as a result of orthodontic treatment was not related to those of shape. 4. Soft tissue changes by orthodontic treatment were variable in individual patient, and were not related to Angle's classification.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.215-220
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• 2013

The super computer calls usually as the super computer in case the computing power of the computer is 20 G flops (GFLOPS) or greater. In the past, the computer equipped with the vector processor (the instrument processing the order having the logic operation and maximum value or minimum value besides the common computer instruction) processing the scientific calculation with the super high speed was installed as the super computer. Recently, cyber attack focuses on supercomputer because if it is being infected, then it will affect hundreds of client PC. Therefore, our research paper analyzed super computer security issues and biometric countermeasure to develop the level of security on super computer.

• Journal of Mechanical Science and Technology
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• v.19 no.11
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• pp.2007-2015
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• 2005

A large-scale analysis to evaluate complex material and structural behaviors is one of interesting topic in diverse engineering and scientific fields. Also, the utilization of massively parallel processors has been a recent trend of high performance computing. The objective of this paper is to introduce a parallel process system which consists of general purpose finite element analysis solver as well as parallelized PC cluster. The later was constructed using eight processing elements and the former was developed adopting both hierarchical domain decomposition method and balancing domain decomposition method. Then, to verify the efficiency of the established system, it was applied for structural analysis of steam generator in nuclear power plant. Since the prototypal evaluation results agreed well to the corresponding reference solutions it is believed that, after reinforcement of PC cluster by increasing number of processing elements, the promising parallel process system can be utilized as a useful tool for advanced structural integrity evaluation.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.231-236
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• 2020

This paper addresses the analysis method about optimal performance and required quantity for Mission-Based drones. In the case of drones, although scientific verification of operational performance and quantity of demanded, such as total flight time, total operation time, and appropriate required quantity, is required depending on the operation concept, there is no methodology for analyzing them systematically. That is the reason this research was carried out. Through the suggestion and study about Mission-Based six step analysis method and, this study can present the optimal ROC (Required Operational Capability) and the required quantity based on the operational concept of drones, and technical and economic effects were suggested.

• Smart Structures and Systems
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• v.26 no.1
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• pp.11-21
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• 2020

The hinge joint is the key to the overall cooperative working performance of the assembled beam bridge, and it is also the weakest part during the service period. This paper proposes a method for monitoring and evaluating the lateral cooperative working performance of fabricated beam bridges based on dynamic strain correlation coefficient indicator. This method is suitable for monitoring and evaluation of hinge joints status between prefabricated girders and overall cooperative working performance of bridge, without interruption of traffic and easy implementation. The remote cloud monitoring and diagnosis system was designed and implemented on a real assembled beam bridge. The algorithms of data preprocessing, online indicator extraction and status diagnosis were given, and the corresponding software platform and scientific computing environment for cloud operation were developed. Through the analysis of real bridge monitoring data, the effectiveness and accuracy of the method are proved and it can be used in the health monitoring system of such bridges.

• Journal of Magnetics
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• v.19 no.3
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• pp.255-260
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• 2014

A portable clip-type pulsimeter equipped with a magnetic sensing Hall device has been developed to raise the accuracy of oriental disease diagnosis and therapy by convergence of magnetism and oriental medicine. To improve accuracy and reliability of conventional pulsimeter due to subjective analysis of the pulse wave and measuring position dependency of the arterial pulse sensor, the fuzzy algorithm was applied to analyze the strong- and weak-pulse wave symptom. Optimal time for electronic acupuncture was calculated using fuzzy rules and interference were drawn from objective data in view of pre-treatment. Moreover, the electrical characteristics of the pain parts that respond to acupuncture point were applied in view of post-treatment to propose the scientific pulse wave algorithm and simulation experiment.

• Journal of Ocean Engineering and Technology
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• v.34 no.2
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• pp.147-154
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• 2020

Underwater acoustics that is the study of the phenomenon of underwater wave propagation and its interaction with boundaries, has mainly been applied to the fields of underwater communication, target detection, marine resources, marine environment, and underwater sound sources. Based on the scientific and engineering understanding of acoustic signals/data, recent studies combining traditional and data-driven machine learning methods have shown continuous progress. Machine learning, represented by deep learning, has shown unprecedented success in a variety of fields, owing to big data, graphical processor unit computing, and advances in algorithms. Although machine learning has not yet been implemented in every single field of underwater acoustics, it will be used more actively in the future in line with the ongoing development and overwhelming achievements of this method. To understand the research trends of machine learning applications in underwater acoustics, the general theoretical background of several related machine learning techniques is introduced in this paper.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.8
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• pp.1024-1033
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• 1997

The past several years have witnessed an ever-increasing acceptance and adoption of parallel processing, both for high performance scientific computing as well as for more general purpose applications. Furthermore with increasing needs to perform the complex flow calculations in an efficient manner, the use of the message passing model on distributed networks has emerged as an important alternative to the expensive supercomputers. This work attempts to provide a generic framework to enable the parallelization of all CFD-related works using the master-slave model. This framework consists of (1) input geometry, (2) domain decomposition, (3) grid generation, (4) flow computations, (5) flow visualization, and (6) output display as the sequential components, but performs computations for (2) to (5) in parallel on the workstation clustering. The flow computations are parallized by having multiple copies of the flow-code to solve a PDE on different spatial regions on different processors, while their flow data are exchanged across the region boundaries, and the solution is time-stepped. The Parallel Virtual Machine (PVM) is used for distributed communication in this work.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.375-393
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• 2008

The dynamic cast operation allows flexibility in the design and use of data management facilities in object-oriented programs. Dynamic cast has an important role in the implementation of the Data Management Services (DMS) of the Mission Data System Project (MDS), the Jet Propulsion Laboratory's experimental work for providing a state-based and goal-oriented unified architecture for testing and development of mission software. DMS is responsible for the storage and transport of control and scientific data in a remote autonomous spacecraft. Like similar operators in other languages, the C++ dynamic cast operator does not provide the timing guarantees needed for hard real-time embedded systems. In a recent study, Gibbs and Stroustrup (G&S) devised a dynamic cast implementation strategy that guarantees fast constant-time performance. This paper presents the definition and application of a cosimulation framework to formally verify and evaluate the G&S fast dynamic casting scheme and its applicability in the Mission Data System DMS application. We describe the systematic process of model-based simulation and analysis that has led to performance improvement of the G&S algorithm's heuristics by about a factor of 2. In this work we introduce and apply a library for extracting semantic information from C++ source code that helps us deliver a practical and verifiable implementation of the fast dynamic casting algorithm.

• Journal of Information Technology Services
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• v.19 no.2
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• pp.93-107
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• 2020

Recently, artificial intelligence (AI) technologies has been widely used in various fields such as finance, and distribution. Accordingly, Korea has also announced its AI R&D strategy for the realization of i-Korea 4.0 in May 2018. However, Korea's AI technology is inferior to major competitors such as the US, Canada, and Japan Therefore, in order to cope with the 4th industrial revolution, it is necessary to allocate AI R&D budgets efficiently through selection and concentration so as to gain competitive advantage under a limited budget. In this study, the importance of each AI technology was evaluated in multi-dimensional way through the questionnaire of expert group using the evaluation index derived from the literature review From the results of this study, we draw the following implication. In order to successfully establish the AI technology development strategies, it is necessary to prioritize the cognitive computing technology that has great market growth potential, ripple effect of technology development, and the urgency of technology development according to the principle of selection and concentration. To this end, it is necessary to find creative ideas, manage assessments, converge multidisciplinary systems and strengthen core competencies. In addition, since AI technology has a large impact on socioeconomic development, it is necessary to comprehensively grasp and manage scientific and technological regulations in order to systematically promote AI technology development.