• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.29-32
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• 2007

Tidal channel development is influenced by sediment type, grain size, composition and tidal current. Tidal channels are usually characterized by channel development, density and shape. Quantitative analysis of tidal channels using remotely sensed data have rarely been studied. The objective of this study is to quantify tidal channels in terms of fractal dimension and compare different inter-tidal channel patterns. For the fractal analysis, we used Box counting method which had been successfully applied to streams, coastlines and others linear features. For a study, the southern part of Ganghwado tidal flats was selected where is famous for high dynamics of tidal currents and vast tidal flats. This area has different widths and lengths of tidal channels. IKONOS and Komsat-2 MSC images were used for extracting tidal channels, and the Box counting method was applied to obtain fractal dimensions (D) for each tidal channel. Yeochari area possesses channels with linear pattern and less dense development and accordingly show low D values ranging from 1.037 to 1.038. On other hands, area (near Donggumdo and Yeongjongdo ) of dendrites channel pattern and dense development resulted in high D values from 1.2057 to 1.2667. Also, area possesses channels with linear pattern had low density about $18{\sim}24%$. Area of dendritic channel pattern had high density about $34{\sim}69%$. The difference of fractal dimensions about 0.2 according to channel development in tidal flats is relatively large enough to use as an index for tidal channel classification. Also, area where channels showed linear pattern had low density about $18{\sim}24%$. Area of dendritic channel pattern had high density about $34{\sim}69%$. Using fractal dimension and density, it would be possible to quantify the tidal channel development in association with surface characteristics.

• 한국군사과학기술학회지
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• 제24권2호
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• pp.228-236
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• 2021

In order to understand the underwater noise source factor of the linear pump type forced ejection system, a reduced-model compressed water experiment device was developed. The reduced-model compressed water experiment device consists of a reverberation tank, a linear pump type forced ejection device, and an underwater vehicle. The underwater noise source was selected from the hydraulic ram moving speed, the hydraulic ram/piston pipe spacing, the ejection pipe inlet/water ram area ratio, and the number of water ram inlets. The underwater vehicle was ejected into the reverberation tank by the device. The source level was derived from the measured sound pressure. The source level tends to increase as the hydraulic ram/piston tube spacing and the hydraulic ram moving speed increase. The source level tended to increase as the area ratio was increased, but the level was weak. The number of water ram inlet did not affect the source level.

• 경영과학
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• 제12권1호
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• pp.125-138
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• 1995

This paper is to develop an integrated environment software on MS-DOS for linear programming. For the purpose, First, the linear programming integrated environment software satisfying both the educational purpose and the professional purpose was designed and constructed on MS-DOS. Second, the text editor with big capacity was developed. The arithmetic form analyser was also developed and connected to the test editor so that users can input data in the arithmetic form. As a result, users can learn and perform linear programming in the linear programming integrated environment software.

• ETRI Journal
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• 제29권1호
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• pp.110-112
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• 2007

As an alternative to the classic linear detector which only assumes noise variance, a new robust detector with noise variance estimation censoring input signals over AWGN is proposed. The results demonstrate that analytic detection probability matches the simulation results for the linear detector and that the new robust detector shows better performance than the linear detector when the number of samples increases.

• 한국정밀공학회지
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• 제10권4호
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• pp.104-108
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• 1993

The linear length measurements are most frequently performed and should be most accurate among other parts in dimensional metrology. We developed the linear measuring system using a laser interferometer to improve the accuracy and to shorten the calibration time. The uncertainty of the system is 0.01 .mu. for 500mm steel gage block. The range of the measurement and resolution of the system are 1000mm and 0.01 .mu. m, respectively.

• 한국통신학회논문지
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• 제41권6호
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• pp.672-677
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• 2016

인터넷의 발전은 네트워크 기술과 응용의 확장적 배치와 더불어 성공적으로 고무되어 왔다. 하지만, 요즘에는 인터넷의 사용은 심각한 트래픽 과부하를 야기 시킨다. 따라서, 우리는 효율적인 자원 할당을 위해 네트워크 가상화의 지속적인 연구와 발전이 필요하다. 본 논문은 Piecewise Linear 비용함수를 이용한 비용 최소화 가상 네트워크 매핑 알고리즘을 제안 한다. 노드 매핑에는 선형 프로그래밍을 이용한 알고리즘과 D-VINE을 이용하였고, 링크 매핑에는 선형 프로그래밍 솔루션을 기반으로 최단 경로 알고리즘을 이용하였다. 이와 같은 방법으로 네트워크상에서 Linear와 Tree 구조로 형성된 VN request의 도착률에 따른 평균 비용을 ViNEYard와 비교 분석하였다. 시뮬레이션 구현을 통해 우리의 알고리즘이 ViNEYard 을 사용할 때 보다 발생하는 평균 비용이 낮음을 확인할 수 있었다.

• 한국진공학회지
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• 제22권1호
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• pp.1-6
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• 2013

$600{\times}1,200mm$ 기판에 대면적 CIGS 광흡수층 증착을 위한 선형증발원 개발을 위해 다른 크기의 노즐과 일정한 노즐 간격을 가지는 선형증발원의 플럭스 밀도를 전산 모사하여 플럭스 균일도 ${\pm}5%$의 조건을 구하였다. 이를 바탕으로 제작된 선형증발원을 이용하여 Cu, In의 단일막 두께균일도를 확인하였고, CIGS 광흡수층을 동시증발법으로 증착하여 박막의 두께균일도 및 증착 조성의 균일도로 선형증발원을 평가하였다. XRF 조성 분석을 통해 구한 조성불균일도는 600 mm 폭에서 $$Cu{\leq_-}5%$$, $$In{\leq_-}7%$$, $$Ga{\leq_-}4%$$, $$Se{\leq_-}3%$$으로 균일한 조성비로 성막된 것을 확인하였고 SEM 분석을 통해 표면 결정립의 형상을 확인하였다. 또한 XRD측정을 통해 선형증발원 방향의 대면적 CIGS 광흡수층이 칼코피라이트 구조임을 확인하였다. 이를 통해서 개발된 하향 선형증발원이 CIGS 광흡수층 증착에 적합함을 확인하였다.

• Animal cells and systems
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• 제4권3호
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• pp.215-221
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• 2000

Our anatomical and behavioral studies of embryonic rats that developed in microgravity suggest that the vestibular sensory system, like the visual system, has genetically mediated precesses of development that establish crude connections between the periphery and the brain. Environmental stimuli also regulate connection formation including terminal branch formation and fine-tuning of synaptic contacts. Axons of vestibular sensory neurons from grabistatic as well as linear acceleration receptors reach their targets in both microgravity and norm81 gravity, suggesting that this is a genetically regulated component of development. However, microgravity exposure delays the development of terminal branches and synapses in gravistatic but not linear acceleration-sensitive neurons and also produces behavioral changes. These latter changes reflect environmentally controlled processes of development.

• 한국정밀공학회지
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• 제25권6호
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• pp.126-133
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• 2008

Linear motors are efficient mechanism that offers high speed and positioning accuracy. By eliminating mechanical transmission mechanisms such as ball screw or rack-pinion, much higher speed and greater acceleration can be achieved without backlash or excessive friction. However, an important disadvantage of linear motor system is its high power loss and heating up of motor and neighboring machine components on operation. For the application of the linear motors to precision machine tools an effective cooling method and thermal optimizing measures are required. This paper presents an investigation into the thermal behavior of linear motors with the objective of deriving the optimum cooling conditions. To reach these goals several experiments were carried out, varying operating and cooling conditions. From the experimental results, this research proposed cooling conditions to improve the thermal characteristics of the linear motors.

• Journal of Information Processing Systems
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• 제18권2호
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• pp.268-281
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• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.