• 한국CDE학회논문집
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• 제11권1호
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• pp.20-26
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• 2006

This paper presents a procedure to compute pencil curves from a triangular mesh which is offset with the radius of a given ball-end mill. An offset triangular mesh has numerous self-intersections caused by an abundance of invalid triangles, which do not contribute to the valid CL-surface. Conceptually, we can obtain valid pencil curves by combining all intersections tying on the outer skin of the offset triangular mesh, i.e., the valid CL-surface. The underlying concept of the proposed algorithm is that visible intersections are always valid for pencil curves, because visible intersections lie on the outer skin of the offset model. To obtain the visibility of intersections efficiently, the proposed algorithm uses a graphics board, which performs hidden surface removal on up to a million polygons per second.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1113-1114
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• 1996

We describe an algorithm to control an autonomous guided vehicle with 2-diagonal driving wheels, which navigates in the clean room.

• 제어로봇시스템학회논문지
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• 제11권12호
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• pp.1011-1019
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• 2005

In this paper, Ubiquitous Home Mess-Cleanup Robot(UHMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of tile self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulate,, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and UHMR. Finally, the good performance of the designed UHMR is confirmed through the results of the mess clean-up and arrangement.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1612-1616
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• 2005

In this paper, a Home Mess-Cleanup Robot(HMR), which has a practical function of the automatic mess-cleanup, is developed. The vacuum-cleaner had made the burden of house chore lighten but the operation labour of a vacuum-cleaner had been so severe. Recently, the cleaning robot was producted to perfectly solve the cleaning labour of a house but it also was not successful because it still had a problem of mess-cleaning, which was the clean-up of big trash and the arrangement of newspapers, clothes, etc. The cleaning robot is to just vacuum dust and small trash but has no function to arrange and take away before the automatic vacuum-cleaning. For this reason, the market for the cleaning robot is not yet built up. So, we need a design method and technological algorithm of new automatic machine to solve the problem of mess-cleanup in house. It needs functions of agile automatic navigation, novel manipulation system for mess-cleanup. The automatic navigation system has to be controlled for the full scanning of living room, to recognize the absolute position and orientation of the self, the precise tracking of the desired path, and to distinguish the mess object to clean-up from obstacle object to just avoid. The manipulator, which is not needed in the vacuum-cleaning robot, must have the functions, how to distinguish big trash to clean from mess objects to arrange, how to grasp in according to the form of mess objects, how to move to the destination in according to mess objects and arrange them. We use the RFID system to solve the problems in this paper and propose the reading algorithm of RFID tags installed in indoor objects and environments. Then, it should be an intelligent system so that the mess cleaning task can be autonomously performed in a wide variety of situations and environments. It needs to also has the entertainment functions for the good communication between the human and HMR. Finally, the good performance of the designed HMR is confirmed through the results of the mess clean-up and arrangement.

• 한국측량학회지
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• 제21권4호
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• pp.317-322
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• 2003

본 논문에서는 우리나라 해안에 설치된 GPS상시관측소(제주도, 호미곶, 주문진, 마라도, 팔미도, 울릉도, 영도) 데이터를 사용하여 각 관측소의 상대적 높이차를 구한 후, CLEAN 알고리즘에 의한 스펙트럼 분석을 실시함으로써 해양조석의 부하성분들 중에서 반일분조성분으로 인한 지각의 연직변동량을 추정하고, 이들을 일본과 우리나라 주변에 대하여 지역적으로 개량한 해양조석모델(NAO99jb)로부터 계산된 결과들과 비교$.$분석을 실시하고자 하였다. 그 결과, 총 4개의 반일분조($M_2, N_2, S_2, K_2$) 중 $M_2$와 $N_2$의 부하효과에 의한 부하성분의 진폭 및 위상 차를 결정하였으며, 관측된 부하성분의 진폭과 위상차는 모델에서 구한 부하성분의 진폭과 위상차와 거의 일치되는 양상물을 보이고 있었다. 그러나 주기의 문제로 인해 $S_2$, $K_2$ 반일분조에 대한 부하성분은 산출하지 못하였으며, 또한 일분조(Diurnal) 주기에서는 잡음의 양이 증가함으로 인하여 부하성분을 산출하지 않았다.

• 대한기계학회논문집
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• 제17권8호
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• pp.2110-2121
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• 1993

A numerical investigation has been carried out for the flow characteristics after exchange of some filters from the original layer to the new low pressure loss layer with equal filtering efficiency. The solution domain includes upper plenum, filter layer, clean space, access panels, and lower plenum. The concept of the distributed pressure resistance was applied to describe the momentum loss in filter layer and access panels. The evolution of the flow field is simulated using the low Reynolds number k-.epsilon. over bar turbulent model and SIMPLE algorithm based on the finite volume method. As a result, after the exchange of filter layer the power requirement can be reduced by 8-9 percent. The results also demonstrate that the perpendicularity of the flow near access panels may become worse at new filter layer than origianl filter layer. But the situation can be recovered by adjusting the jopening ratio of access panels.

• The Journal of the Acoustical Society of Korea
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• 제27권1E호
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• pp.1-10
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• 2008

A noise suppression algorithm is proposed for nonstationary noisy environments. The proposed algorithm is different from the conventional approaches such as the spectral subtraction algorithm and the minimum statistics noise estimation algorithm in that it classifies speech and noise signals in time-frequency bins. It calculates the ratio of the variance of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. If the ratio is greater than an adaptive threshold, speech is considered to be present. Our adaptive algorithm tracks the threshold and controls the trade-off between residual noise and distortion. The estimated clean speech power spectrum is obtained by a modified gain function and the updated noisy power spectrum of the time-frequency bin. This new algorithm has the advantages of simplicity and light computational load for estimating the noise. This algorithm reduces the residual noise significantly, and is superior to the conventional methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.1183-1186
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• 1998

Adaptive nois canceller can extract the noiseremoved spech in noisy speech signal by adapting the filter-coefficients to the background noise environment. A kind of LMS algorithm is one of the most popular adaptive algorithm for noise cancellation due to low complexity, good numerical property and the merit of easy implementation. However there is the matter of increasing misadjustment at voiced speech signal. Therefore the demanded speech signal may be extracted. In this paper, we propose a fast and noise robust wavelet packet adaptive noise canceller with NLMS-SUM method LMS combined algorithm. That is, we decompose the frequency of noisy speech signal at the base of the proposed analysis tree structure. NLMS algorithm in low frequency band can efficiently dliminate the effect of the low frequency noise and SUM method LMS algorithm at each high frequency band can remove the high frequency nosie. The proposed wavelet packet adaptive noise canceller is enhanced the more in SNR and according to Itakura-Satio(IS) distance, it is closer to the clean speech signal than any other previous adaptive noise canceller.

• Communications for Statistical Applications and Methods
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• 제9권1호
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• pp.291-304
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• 2002

This article is concerned with an effective algorithm for the identification of multiple outliers in linear regression. It proposes a hybrid algorithm which employs the least median of squares estimator, instead of the least squares estimator, to construct an Initial clean subset in the stepwise forward search scheme. The performance of the proposed algorithm is evaluated and compared with the existing competitor via an extensive Monte Carlo simulation. The algorithm appears to be superior to the competitor for the most of scenarios explored in the simulation study. Particularly it copes with the masking problem quite well. In addition, the orthogonal decomposition and Its updating techniques are considered to improve the computational efficiency and numerical stability of the algorithm.

• 유통과학연구
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• 제18권1호
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• pp.15-26
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• 2020

Purpose: This study is to analyze the image classification using Convolution Neural Network and Transfer Learning for Jeju Island and to suggest related implications. As the biggest tourist destination in Korea, Jeju Island encounters environmental issues frequently caused by marine debris along the seaside. The ever-increasing volume of plastic waste requires multidirectional management and protection. Research design, data and methodology: In this study, the deep learning CNN algorithm was used to train a number of images from Jeju clean and polluted beaches. In the process of validating and testing pre-processed images, we attempted to explore their applicability to coastal tourism applications through probabilities of classifying images and predicting clean shores. Results: We transformed and augmented 194 small image dataset into 3,880 image data. The results of the pre-trained test set were 85%, 70% and 86%, and then its accuracy has increased through the process. We finally obtained a rapid convergence of 97.73% and 100% (20/20) in the actual training and validation sets. Conclusions: The tested algorithms are expected to implement in applications for tourism service distribution aimed at reducing coastal waste or in CCTVs as a detector or indicator for residents and tourists to protect clean beaches on Jeju Island.