• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.318-322
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• 2001

This paper deals with sensing ability of smart sensor that has a sensing ability to distinguish materials according to surface types of smart sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. We made two types of smart sensors in our experiment. Then, we estimated the ability to recognize objects according to smart sensor type. We estimated the sensing ability of smart sensor with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to surface types of smart sensor. Sensing ability of smart sensors was evaluated relatively through a new $R_{SAI}$ method. Applications of smart sensors are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.etc.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.1
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• pp.22-27
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• 2004

A new method that estimates the sensing ability of HH smart sensor is proposed. The new signal processing method have been developed that can distinguish among different materials relatively. The HH smart sensor was developed far recognition of materials. The HH smart sensor was made for experiment. Then, it was estimated the ability to recognize objects according to acceleration value. The sensing ability of HH smart sensor has been estimated with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to acceleration value changing. Dynamic characteristics of HH smart sensor were evaluated relatively through a new $R_{SAI}$ method that uses the power spectrum density. Applications of this method are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.922-926
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• 2001

This paper deals with sensing ability of smart sensor that has a sensing ability to distinguish materials according to frequency changing. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. We estimated the sensing ability of smart sensor with the $R_{SAI}$ method according to frequency changing. Experiments and analysis were executed to estimate the ability to recognize objects according to frequency changing. Sensing ability of smart sensors was evaluated relatively through a new $R_{SAI}$ method. Applications of smart sensors are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1756-1761
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• 2021

Although the COVID-19 outbreak that occurred in Wuhan, Hubei around December 2019, seemed to be gradually decreasing, it was gradually increasing as of November 2020 and June 2021, and estimated confirmed cases were 192 million worldwide and approximately 184 thousand in South Korea. The Central Disaster and Safety Countermeasures Headquarters have been taking strong countermeasures by implementing level 4 social distancing. However, as the highly infectious COVID-19 variants, such as Delta mutation, have been on the rise, the number of daily confirmed cases in Korea has increased to 1,800. Therefore, the number of cumulative confirmed COVID-19 cases is predicted using ARIMA algorithms to emphasize the severity of COVID-19. In the process, differences are used to remove trends and seasonality, and p, d, and q values are determined and forecasted in ARIMA using MA, AR, autocorrelation functions, and partial autocorrelation functions. Finally, forecast and actual values are compared to evaluate how well it was forecasted.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.125-133
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• 2008

Motion blur is a blurring effect on an image caused by the relative motion between the camera and objects in the scene. When an image is captured, motion blurs are caused by relative motion between the camera and the scene. When different objects are moving at different speeds, the characteristics of the blur effect for each object appear differently. To restore the spatially variant blurred image, each of the blur extents should be identified. In this paper, we propose a new method for the identification of blur extent locally using RATS from the image in which the spatially variant motion blur is caused Experiment shows that the proposed algorithm successfully segments the objects with different blurs and identifies the blur extents quite well.

• Fire Science and Engineering
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• v.28 no.2
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• pp.69-75
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• 2014

This study derives the factors which affect the occurrence of arson from statistical data (population, economic, and social factors) by multiple regression analysis. Multiple regression analysis applies to 4 forms of functions, linear functions, semi-log functions, inverse log functions, and dual log functions. Also analysis respectively functions by using the stepwise progress which considered selection and deletion of the independent variable factors by each steps. In order to solve a problem of multiple regression analysis, autocorrelation and multicollinearity, Variance Inflation Factor (VIF) and the Durbin-Watson coefficient were considered. Through the analysis, the optimal model was determined by adjusted Rsquared which means statistical significance used determination, Adjusted R-squared of linear function is scored 0.935 (93.5%), the highest of the 4 forms of function, and so linear function is the optimal model in this study. Then interpretation to the optimal model is conducted. As a result of the analysis, the factors affecting the arson were resulted in lines, the incidence of crime (0.829), the general divorce rate (0.151), the financial autonomy rate (0.149), and the consumer price index (0.099).

• Korean Journal of Materials Research
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• v.6 no.6
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• pp.632-635
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• 1996

조성 변조된 비정질 Fe80Zr20박막의 자기적 성질과 기계적 성질 변화를 전해적 방법에 의한 수소 취입 시간의 함수로 측정하여, 그 상관 관계를 연구하였다. 박막의 Young's modulus는 진동 cantilever 시료의 공명 주파수를 , 10-4nm의 측정 감도를 지닌 laser heterodyne interferometer를 써서 측정하였다. 농도 2N의 인산 전해액에 침적된 시료에 26.3mA/$\textrm{cm}^2$의 전류를 흘려 이루어진 수소취입에 의해, Fe80Zr20 박막의 포화자화 정도는 8배, Young's modulus는 18배 가량 증가하였다. Fe80Zr20박막의 자기적 성질의 변화가 원자적 scale의 미세 구조 변화에 의한 것이라는 간접적인 증거를 제공하였으며, cantilever 시료의 공명주파수 측정을 통하여 박막재료의 기계적 성질을 연구할 수 있는 새로운 가능성을 제시하였다.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.262-267
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• 2022

이커머스 리뷰와 같은 특정 도메인의 경우, 텍스트 표현벡터 학습을 위한 양질의 오픈 학습 데이터를 구하기 어렵다. 또한 사람이 수동으로 검수하며 학습데이터를 만드는 경우, 많은 시간과 비용을 소모하게 된다. 따라서 본 논문에서는 수동으로 검수된 데이터없이 양질의 텍스트 표현벡터를 만들 수 있도록 두 단계의 대조 학습 시스템을 제안한다. 이 두 단계 대조 학습 시스템은 레이블링 된 학습데이터가 필요하지 않은 자기지도 학습 단계와 리뷰의 특성을 고려한 자동 레이블링 기반의 지도 학습 단계로 구성된다. 또한 노이즈에 강한 오류함수와 한국어에 유효한 데이터 증강 기법을 적용한다. 그 결과 스피어먼 상관 계수 기반의 성능 평가를 통해, 베이스 모델과 비교하여 성능을 14.03 향상하였다.

• Journal of Ocean Engineering and Technology
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• v.8 no.2
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• pp.47-55
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• 1994

The purpose of the present study is to investigate the effect of specimen thickness on statistical properties of crack growth resistance. In this study, the resistance S$\delta$$_h$(x) to fatigue crack growth was treated as a spatial stochastic process. which varies randomly on the crack surface. The theoretical autocorrelation functions of the resistance to fatigue crack growth considering specimen thickness are discussed for several correlation lengths. The main results obtained are : (1) The theoretical autocorrelation functions of S$\delta$$_h$(x) are almost independent of specimen of specimen thickness except for the origin. (2) The variance increases with decreasing specimen thickness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.655-657
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• 2010

현재 코골이를 방지하는 위한 기구로는 양압 산소호흡기, 스프레이, 전기자극기, 수술, 구강내 보조기구가 있으나 개인용으로 사용하기에는 가격이 너무 고가이어서 일반적인 코골이 환자에게 적용하기에는 무리가 있으며 사용자에 따라 부작용의 위험이 있다. 본 논문에서는 정확하고 안정적인 코골이 신호인식을 위해 시계열 분석방법을 통해서 선형적인 성질보다 비선형적인 성질이 강한 코골이 신호의 카오틱 신호 유무를 해석하였다. 본 논문에서 사용한 시계열 데이터는 30대 성인남자로부터 수면시간 6시간중중 발생하는 코골이 음성신호를 마이크를 통해 샘플링 주파수 22kHz, 모노 형태로 수집한 것이다. 위상공간의 궤적 분석, 매입차원에 의한 상관적분 분석, 파워 스펙트럼과 자기상관함수 분석 등의 정량 및 정성적 분석방법을 통해서 수집한 코골이 신호의 분석결과 신호가 부분적으로 주기적 성질을 가지는 카오스 신호임을 확인하였다.