• 대한기계학회논문집B
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• 제24권4호
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• pp.504-511
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• 2000

PIV(Particle Image Velocimetry) is a recently developed technique for visualizing the fluid velocity fields. Because it has several advantages over the LDV(Laser Doppler Velocimetry), it became one of the most popular diagnostic tools in spite of its short history. However, its application to combustion is restricted by some problems such as flame illumination, scattered light refraction, particle density variation due to heat release, the combined effect of abrupt change in particle density and fluid velocity on flame contour, and thermophoresis which is particle lagging due to temperature gradient. These problems are expected to be originated from the non-continuous characteristics of flames and the limitations of particle dynamics. In the present study, these problems were considered for the visualization of the instantaneous coaxial hydrogen diffusion flame. And the instantaneous flame contour was detected using particle density difference. The visualized diffusion flame velocity field shows its turbulent and meandering nature. It was also observed that the flame is located inside the outer shear layer and flame geometry is largely influenced by the vorticity.

• Communications for Statistical Applications and Methods
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• 제19권5호
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• pp.685-696
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• 2012

These days the interest of quality leads to the necessity of control charts for monitoring the process in various fields of practical applications. The $\overline{X}$ chart is one of the most widely used tools for quality control that also performs well under the normality of quality characteristics. However, quality characteristics tend to have nonnormal properties in real applications. Numerous recent studies have tried to find and explore the performance of $\overline{X}$ chart due to non-normality; however previous studies numerically examined the effects of non-normality and did not provide any theoretical justification. Moreover, numerical studies are restricted to specific type of distributions such as Burr or gamma distribution that are known to be flexible but can hardly replace other general distributions. In this paper, we approximate the false alarm rate(FAR) of the $\overline{X}$ chart using the Edgeworth expansion up to 1/n-order with the fourth cumulant. This allows us to examine the theoretical effects of nonnormality, as measured by the skewness and kurtosis, on $\overline{X}$ chart. In addition, we investigate the effect of skewness and kurtosis on $\overline{X}$ chart in numerical studies. We use a skewed-normal distribution with a skew parameter to comprehensively investigate the effect of skewness.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• 제28권4호
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• pp.192-196
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• 2017

Social (pragmatic) communication disorder (SCD) is a new diagnosis included under communication disorders in the neurodevelopmental disorders section of Diagnostic and Statistical Manual of Mental Disorders-5. SCD is defined as a primary deficit in the social use of nonverbal and verbal communication. SCD has very much in common with pragmatic language impairment, which is characterized by difficulties in understanding and using language in context and following the social rules of language, despite relative strengths in word knowledge and grammar. SCD and Autism Spectrum Disorder (ASD) are similar in that they both involve deficits in social communication skills, however individuals with SCD do not demonstrate restricted interests, repetitive behaviors, insistence on sameness, or sensory abnormalities. It is essential to rule out a diagnosis of ASD by verifying the lack of these additional symptoms, current or past. The criteria for SCD are qualitatively different from those of ASD and are not equivalent to those of mild ASD. It is clinically important that SCD should be differentiated from high-functioning ASD (such as Asperger syndrome) and nonverbal learning disabilities. The ultimate goals are the refinement of the conceptualization, development and validation of assessment tools and interventions, and obtaining a comprehensive understanding of the shared and unique etiologic factors for SCD in relation to those of other neurodevelopmental disorders.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.32-36
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• 2002

High-speed movement and high-precision machining are the two most important requirements of present machine tool structures to reduce machining time and to increase the precision of products in various industrial fields such as semiconductor, automobile, and mold fabrication. The high speed operation of machine tools tue usually restricted not only by the low stiffness but also by the low damping of machine tool structures, which induces vibration during high speed machining. If the damping of machine tool structures is low, self induced or regenerative vibrations are bound to occur at high speed operation because the natural frequencies of machine tool structures can not be increased indefinitely. Therefore, the high damping capacity of a machine tool structure is an important factor for high speed machine tool structures. Polymer concrete has high potential for machine tool bed due to its good damping characteristics. In this study, a polymer concrete bed combined with welded steel structure i.e., a hybrid structure was desisted and manufactured for a high-speed gantry-type milling machine through static and dynamic analyses using finite element method. Then the dynamic characteristics were tested experimentally.

• Journal of Information Technology Applications and Management
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• 제24권4호
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• pp.57-69
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• 2017

Due to the development of technology even in learning and education area, many studies have begun to make a new attempts to research by using SNS, breaking away from traditional learning methods. However, the limitations of these studies are restricted only to the use of wireless Internet and writing on Web sites. This study aims to conduct a research on English learning activities that utilize various technologies such as Bigdata, Facebook, Social Network Services (SNS) and English applications. In addition, this study looks into how these modern technologies can be integrated in the classrooms and which activities can be applied in the English classroom. This research is to suggest effective English learning methods through a thorough investigation on the effectivity of various technologies based on the Web 2.0 such as Flickr, blogs, MySpace, and online discussion board within the context of the English learning. To verify the effect of the study, the subjects are divided into experimental and control group. The experiment is proceeded with pre- and post-test. The experimental group is designed to verify the effects using SNS tools such as Facebook, Bigdata, and Online Massive Learning. A survey is conducted to determine the preference of utilizing social networking sites and to analyze the effects in class. The result is that the average scores for experimental group have improved more than the average of control group. The comparison of pre and post-test of the experimental group shows that the significance of the higher and median group was statistically significant at the p<0.01.

• 대한안전경영과학회지
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• 제16권4호
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• pp.193-202
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• 2014

Crimes with explosives is one of the mass-destructive crimes that involves the most victims. It is heavily punished under the Korean laws. Mid-eastern area is one of the leading places that are home to improvised explosive device attacks, in the form of religious or political terrorism because of its convenience of use, production and disguise. Improvised bombs are permeating into domestic crimes in Korea as their tools. Use of explosive substances are strictly restricted in this country, but it is not impossible to find its information online and to create private explosives with a bit of interest. And they are being traded in the grey market. For this reason, this thesis offers the method of an efficient safety control of explosive substances, which can be used as raw materials for improvised explosive devices, in order to protect citizens' lives and properties and to promote national security down the road.

• 한국콘텐츠학회논문지
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• 제10권1호
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• pp.59-67
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• 2010

임베디드 시스템 과목을 위한 실습 과제는 주로 임베디드 보드와 소프트웨어 개발 도구를 사용한 하드웨어 실습 키트로 진행된다. 하드웨어 실습 키트는 높은 초기 설치비용, 유지보수의 어려움, 산업계 발전에 비적응적 대처, 교육적 성과의 한계와 같은 단점을 가지고 있다. 본 논문은 임베디드 시스템 하드웨어 실습 키트의 단점을 극복할 수 있는 시뮬레이션 기반의 가상 실습 환경의 사용을 제안하고 가상 실습 키트의 설계 및 구축에 대하여 기술한다. 구축된 가상 실습 키트는 ARM 사의 ARMulator 환경에 기반을 두어 마이크로프로세서 시스템의 주요 하드웨어 IP들을 추가하고 주변장치들을 위한 사용자 인터페이스 모듈을 개발하여 구축되었다. 검증용 예제 프로그램을 이용하여 동작의 정확성을 확인하였으며 실시간 운영체제 실습도 가능하도록 MicroC/OS-II를 이식하였다.

• 한국컴퓨터정보학회논문지
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• 제13권7호
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• pp.19-27
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• 2008

컴퓨팅 자원 사용에 제약이 많은 임베디드 소프트웨어 개발에 있어서 성능 분석 도구는 품질 개선을 위해 매우 중요한 역할을 한다. 그러나 기존 임베디드 소프트웨어 성능 분석 도구들은 단일 개발자의 교차개발 지원을 위한 성능분석 환경만을 제공하기 때문에 임베디드 소프트웨어를 위한 협업 성능분석 도구로서 활용될 수 없다. 본 논문에서는 협업 환경에서 임베디드 소프트웨어 성능 분석을 효과적으로 수행하기 위한 서버 기반의 새로운 성능 분석도구를 제안한다. 제안하는 성능분석 도구는 개발 소프트웨어에 대해 실행한 성능 분석로그를 협업 개발자들 기호에 맞는 다양한 그래픽 뷰로 생성하여 개발자간의 신속하고 효율적인 정보 공유를 가능하게 함으로써 프로그램의 성능 향상을 위한 개발자의 성능 분석 환경을 크게 개선할 수 있다.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1377-1385
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• 2016

Conventional X-band marine radar has been used as one of the effective tools for collecting and retrieving ocean surface information parameters for three decades. Several wave information extracting algorithms have been designed in such a way that they can be utilized for efficiently estimating sea surface wave parameters such as current velocities, wave direction, significant wave heights in VTS (Vessel Traffic Service). However, their performances are still restricted. For the purpose of overcoming the performance limits, in this paper, first the conventional algorithms are analyzed and their performances are compared, and then a new control algorithm is proposed. Furthermore, we try to improve the estimation performances of typical wave parameters including wave directions and significant wave heights by introducing linear regression model in the process of computing wave information extraction. Through several simulations with the X-band radar images, it is shown that the proposed method is very effective in estimating the wave information compared to the real measured buoy data.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.212-222
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• 2021

Multiple waves of COVID-19 highlighted one crucial aspect of this pandemic worldwide that factors affecting the spread of COVID-19 infection are evolving based on various regional and local practices and events. The introduction of vaccines since early 2021 is expected to significantly control and reduce the cases. However, virus mutations and its new variant has challenged these expectations. Several countries, which contained the COVID-19 pandemic successfully in the first wave, failed to repeat the same in the second and third waves. This work focuses on COVID-19 pandemic control and management in Saudi Arabia. This work aims to predict new cases using deep learning using various important factors. The proposed method is called Deep Learning and Dynamic Weighing-based (DLDW) COVID-19 cases prediction method. Special consideration has been given to the evolving factors that are responsible for recent surges in the pandemic. For this purpose, two weights are assigned to data instance which are based on feature importance and dynamic weight-based time. Older data is given fewer weights and vice-versa. Feature selection identifies the factors affecting the rate of new cases evolved over the period. The DLDW method produced 80.39% prediction accuracy, 6.54%, 9.15%, and 7.19% higher than the three other classifiers, Deep learning (DL), Random Forest (RF), and Gradient Boosting Machine (GBM). Further in Saudi Arabia, our study implicitly concluded that lockdowns, vaccination, and self-aware restricted mobility of residents are effective tools in controlling and managing the COVID-19 pandemic.