• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.445-458
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• 2020

The least absolute shrinkage and selection operator (LASSO) is a popular method for a high-dimensional regression model. LASSO has high prediction accuracy; however, it also selects many irrelevant variables. In this paper, we consider the moderately clipped LASSO (MCL) for the high-dimensional generalized linear model which is a hybrid method of the LASSO and minimax concave penalty (MCP). The MCL preserves advantages of the LASSO and MCP since it shows high prediction accuracy and successfully selects relevant variables. We prove that the MCL achieves the oracle property under some regularity conditions, even when the number of parameters is larger than the sample size. An efficient algorithm is also provided. Various numerical studies confirm that the MCL can be a better alternative to other competitors.

• 한국정밀공학회지
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• 제15권11호
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• pp.76-82
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• 1998

In this study, the Ball screw and Servo motor Mechanism is considered as a High Speed Tool Feed System for the machining of a piston of a reciprocating engine. For the machining of a piston, that shapes oval, high speed servo mechanism is needed as a positioning of a cutting tool, and the stroke of tool is 0.1 mm ~ 1 mm. Ball screw and servo motor Mechanism is available very much because this mechanism is used widely in general machine. This Mechanism has been designed with the use of the decrease in mass and partial wear of the ball screw for high speed positioning of tool. Also the periodic learning control method with the inverse transfer function compensation has been applied to the positioning control for the high accuracy positioning of tool. These applications lead the achievement of the machining of a piston with an accuracy of 5${\mu}{\textrm}{m}$ at 2500 rpm in CNC turning.

• International Journal of Computer Science & Network Security
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• 제23권5호
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• pp.179-192
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• 2023

The widespread use of Cloud Computing, Internet of Things (IoT), and social media in the Information Communication Technology (ICT) field has resulted in continuous and unavoidable cyber-attacks on users and critical infrastructures worldwide. Traditional security measures such as firewalls and encryption systems are not effective in countering these sophisticated cyber-attacks. Therefore, Intrusion Detection and Prevention Systems (IDPS) are necessary to reduce the risk to an absolute minimum. Although IDPSs can detect various types of cyber-attacks with high accuracy, their performance is limited by a high false alarm rate. This study proposes a new technique called Fuzzy Logic - Objective Risk Analysis (FLORA) that can significantly reduce false positive alarm rates and maintain a high level of security against serious cyber-attacks. The FLORA model has a high fuzzy accuracy rate of 90.11% and can predict vulnerabilities with a high level of certainty. It also has a mechanism for monitoring and recording digital forensic evidence which can be used in legal prosecution proceedings in different jurisdictions.

• Current Optics and Photonics
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• 제7권5호
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• pp.537-544
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• 2023

Differential phase contrast (DPC) microscopy, a central quantitative phase imaging (QPI) technique in cell biology, facilitates label-free, real-time monitoring of intrinsic optical phase variations in biological samples. The existing DPC imaging theory, while important for QPI, is grounded in paraxial diffraction theory. However, this theory lacks accuracy when applied to high numerical aperture (NA) systems that are vital for high-resolution cellular studies. To tackle this limitation, we have, for the first time, formulated a nonparaxial DPC imaging equation with a transmission cross-coefficient (TCC) for high NA DPC microscopy. Our theoretical framework incorporates the apodization of the high NA objective lens, nonparaxial light propagation, and the angular distribution of source intensity or detector sensitivity. Thus, our TCC model deviates significantly from traditional paraxial TCCs, influenced by both NA and the angular variation of illumination or detection. Our nonparaxial imaging theory could enhance phase retrieval accuracy in QPI based on high NA DPC imaging.

• Spatial Information Research
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• 제11권2호
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• pp.101-117
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• 2003

고해상도 위성영상분석은 국지적 규모의 토지피복 변화 및 대기 상태의 모니터링을 위한 효과적인 기술로 인식되어 왔다. 본 연구에서는 고해상도 영상인 IKONOS 영상과 기존에 작성된 토지이용도를 이용하여 국지적 규모의 토지피복도를 새로 작성하였다. 토지피복 분류기법으로는 퍼지분류 기법을 사용하였으며, 소속함수의 결합방법으로 minimum 연산자를 이용하였다. 분리도 분석에서는 모든 밴드에서 분리도가 높지 않은데, 원인은 계절적 영향에 따른 분광반사율의 차이 때문이다. 토지피복도 작성결과 육상에서는 침엽수림과 경지가, 해양에서는 간석지 및 해빈의 변화가 가장 크다. 분류의 전체정확도는 95.0%, kappa 계수는 0.94%로 나타나 높은 분류정확도를 보였다. 분류항목별 정확도에서는 대부분의 분류항목이 90% 이상의 분류정확도를 보였다. 그러나 혼합림과 하천 및 저수지 등은 낮은 분류정확도를 보였다. 이들 원인은 농경지 담수로 인하여 수역으로 분류항목이 변하거나 유사한 분광패턴으로 분류항목이 혼재된 결과이다. 이들 분류항목의 분류정확도를 높이기 위해서는 계절적 요인을 반드시 고려하여야 할 것이다. 결론적으로 IKONOS 영상은 토지이용도 작성 및 수정이 가능하며, 추후 GIS 공간자료와 통합하여 토지피복도를 작성한다면 보다 정확한 의사결정 보조 자료로서 유용하게 활용될 수 있을 것이다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.230-233
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• 1993

This paper described a relationship between motion speed and working accuracy of industrial articulated robot arms. Working accuracy of the robot arm deteriorates at high speed operation caused by a nonlinear transformation of the kinematics and the time delay of the robot arm dynamic. The deterioration of the following trajectory was expressed as a linear function of the squares of the robot arm motion speed, depending upon a posture of the robot arm and division interval of the objective trajectory.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.379-383
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• 1995

In this paper, vision inspection module for dimensional measurement has been developed. For high accuracy of CMM, camera calibration and edge detection with subpixel accuracy have been implemented. In measurement process, the position of vision probe can be recognized in PC by serial communication with CMM controller. The developed vision inspection module can be widely applied to the practical measurement process.

• 전자공학회논문지A
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• 제33A권6호
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• pp.239-247
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• 1996

The accuracy of sample-and-hold amplifiers (SHA's) empolying a CMOS process in limited by nonideal factors such as linearity errors of an op amp and feedthrough errors of switches. In this work, after some linearity improvement techniques for an op amp are discussed, three different SHA's for video signal processing are designed, simulated, and compared. The CMOS SHA design techniques with a 12-bit level accuracy are proposed by minimizing cirucit errors based on the simulated results.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.291-296
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• 2000

Liner DC motors are widely used for servo-actuator, which would be applied for semiconductor equipments and precise machining systems. we have been developed linear DC motor with high speed, acceleration and position accuracy. From performance test, the position accuracy. From performance test, the position and repeatability accuracy were able to be controlled with 10 ${\mu}{\textrm}{m}$ and $\pm$1 ${\mu}{\textrm}{m}$, respectively. The highest acceleration and speed were obtained 3 G and 2m/sec, respectively. Static thrust force was 270N, and then error was 25%.

• 대한산업공학회지
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• 제38권4호
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• pp.276-284
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• 2012

Classification algorithms generally assume that the data is complete. However, missing values are common in real data sets due to various reasons. In this paper, we propose to use locally linear reconstruction (LLR) for missing value imputation to improve the classification performance when missing values exist. We first investigate how much missing values degenerate the classification performance with regard to various missing ratios. Then, we compare the proposed missing value imputation (LLR) with three well-known single imputation methods over three different classifiers using eight data sets. The experimental results showed that (1) any imputation methods, although some of them are very simple, helped to improve the classification accuracy; (2) among the imputation methods, the proposed LLR imputation was the most effective over all missing ratios, and (3) when the missing ratio is relatively high, LLR was outstanding and its classification accuracy was as high as the classification accuracy derived from the compete data set.