• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.193-198
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• 1994

다축가공은 3축 이상의 동시제어축을 이용하여 복잡한 형상을 효율적으로 가공할 수 있는 첨예의 기술인 반면, 가공 설비의 고가로 인해 실제현장에 보급되지 못하고 있는 실정이다. 부가축 방식에 의한 저축화 가공방식은 이러한 현실적 문제에 대처할 수 있는 강력한 방식으로서, 본 연구팀에서는 3축 CNC 공작기계에 부가축 테이블 방식을 이용하여 5축 곡면가공을 구현한 바 있으며, 정삭가공 알고리즘을 개발한 바 있다. 본 연구에서는 부가축 환경하에서 황삭가공 알고리 즘을 다루며, 기존의 전축환경의 황삭가공에 비해공구자세를 인텍싱 형태로 변화시킬 수 있다는 차이가 있으며, 이에 따라 자세조정횟수의 초소화가 생산성 지표로 부각된다. 본 연구에서 개발된 황삭경로 알고리즘은 자세조정횟수를 포함 하여 공구접근영역, 공구교환횟수, 피드조정을 통하여 전체적을 황삭가공시간의 최소화로 접근하였다. 연구된 알고리즘 은 컴퓨터시뮬레이션을 통하여 검증하였으며, 실제절삭을 통한 검증이 추진중에 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.07a
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• pp.33-34
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• 2012

토석류 퇴적 모델은 토석류에 의한 피해지 예측을 위해 그 효용성이 입증된 모델이지만 이를 이용하기 위해서는 몇 가지 파라미터를 필요로 한다. 파라미터를 자동으로 추정하기 위한 방법은 여러 가지가 있지만 토석류에 의한 피해지 예측을 위한 데이터는 충분히 양을 확보하기가 어려우므로 기존의 학습 기법을 적용하는데 어려움이 있다. 본 논문에서는 인공 신경망을 학습시키는 과정에서 기존 샘플로부터 의사 샘플을 생성하고 이를 학습에 사용함으로써 보다 안정적인 학습이 가능한 의사 샘플 신경망을 제안하였다. 제안한 의사 샘플 신경망은 해공간을 평탄화시킴으로써 잘못된 국부 최적해에 빠질 확률을 줄여주고 따라서 보다 안정적인 파라미터 추정이 가능하다는 사실을 실험을 통해 확인할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.121-123
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• 2006

베이지안 네트워크 병합은 여러 개의 베이지안 네트워크를 하나의 네트워크로 합치는 것을 말한다. 일반적으로 사용되는 병합 알고리즘은 병합 순서에 따라 최종결과 네트워크의 복잡도가 달라지는 문제를 갖고 있고, 최종 병합 네트워크의 에지 수를 최소화하는 병합 순서를 찾는 것은 NP-hard라고 증명되었다. 본 논문에서는 최적의 병합 순서를 결정하기 위해 진화 알고리즘을 사용하는 방법을 제안한다. 해공간 분석을 통해 permutation index 표현방법이 해탐색에 유리함을 보이고 이를 이용한 진화 알고리즘을 제안한다. 실험결과, 기존의 휴리스틱과 greedy 탐색 방법에 비해 제안한 방법이 우수한 성능을 보였다.

• Journal of Chest Surgery
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• v.7 no.1
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• pp.23-30
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• 1974

During the 35 month period from November 1966 to November 1967 and from June 1971 to March 1973 I had experienced 127 cases of non fatal wounds of chest in Viet-Nam. .Among these 127 cases, 62[45.4%] were gun shot wounds, 49[35.8%] were shrapnel wounds and the other were traffic accident. stab wounds and miscellanous. Approximately 21% of gun shot wound were perforating and 79% were penetrating but all cases of shrapnel wounds were penetrating. Of these 127 cases. 90% evacuated to hospital within 6 hours and average time 2.5 hours. The tranfusion requirement of these cases ranged from zero to 36 pints of whole blood with an average of 2.600cc. Initial intrathoracic findings were hemopneumothorax and hemothorax mostly. and the incidence of open thoracotomy was 9.5%[12cases] and closed thoracotomy was 82.8%[104cases], which were contrast to the reports from Korean conflict. I had experienced 24 cases with complication, such as large hematoma in lung parenchyme[8 cases], atelectasis[4 cases], pyothorax [3 cases], pneumonia [3 cases], fibrothorax [3 cases], pleural effusion [2 cases] and wound infection [2 cases]. Mortality rate for entire group was 4.7% but the cases associated with brain injury was 100%, with spinal cord injury was 50%, with large vessel 50%, and abdominal injury was 33.3%, and nobody died solely of thoracic injury.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.315-323
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• 2000

In this paper, we propose a method of constructing neural networks using bio-inpired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants, Here is, we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting nechanism. The DNA coding method has no limitation in expressing the produlation the rule of L-system. Evolutionary algotithms motivated by Darwinaian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it one step ahead prediction of Mackey-Glass time series, Sunspot data and KOSPI data.

• Journal of the military operations research society of Korea
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• v.33 no.2
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• pp.31-47
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• 2007

The main purpose of this study is to find out the best solution of the vehicle routing problem with hard time window by using both genetic algorithm and heuristic. A mathematical programming model was also suggested in the study. The suggested mathematical programming model gives an optimal solution by using ILOG-CPLEX. This study also suggests a hybrid genetic algorithm which considers the improvement of generation for an initial solution by savings heuristic and two heuristic processes. Two heuristic processes consists of 2-opt and Or-opt. Hybrid genetic algorithm is also compared with existing problems suggested by Solomon. We found better solutions rather than the existing genetic algorithm.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.19-26
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• 2013

Pseudo sample neural network (PSNN) is a variant of traditional neural network using pseudo samples to mitigate the local-optima-convergence problem when the size of training samples is small. PSNN can take advantage of the smoothed solution space through the use of pseudo samples. PSNN has a focus on the quantity problem in training, whereas, methods stressing the quality of training samples is presented in this paper to improve further the performance of PSNN. It is evident that typical samples and highly correlated features help in training. In this paper, therefore, kernel density estimation is used to select typical samples and correlation factor is introduced to select features, which can improve the performance of PSNN. Debris flow data set is used to demonstrate the usefulness of the proposed methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3888-3893
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• 2014

The number of waste tires is increasing. One effective recycling method is the pyrolysis of waste tires. Using the pyrolyzed carbon black from waste tires, the characteristics of permanent deformation for PA-13mm porous mixture were evaluated. The confining pressure of 138 kPa and deviatoric stress of 551 kPa were adopted. The testing temperature was $45^{\circ}$ and 50 gyrations of the gyratory compactor was used to simulate the medium traffic level. The mixture modified by 10% PCB showed the largest Marshall Stability of 3.41 kN. The stability of the mixtures with PCB was 50% higher than that of mixture without PCB. The limited laboratory test showed that the use of PCB in a porous pavement decreases the permanent deformation and will be an effective alternative method to reducing the permanent deformation of a porous pavement.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.11-18
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• 2012

Debris flow deposition model is a model to predict affected areas by debris flow and random walk model (RWM) was used to build the model. Although the model was proved to be effective in the prediction of affected areas, the model has several free parameters decided experimentally. There are several well-known methods to estimate parameters, however, they cannot be applied directly to the debris flow problem due to the small size of training data. In this paper, a modified neural network, called pseudo sample neural network (PSNN), was proposed to overcome the sample size problem. In the training phase, PSNN uses pseudo samples, which are generated using the existing samples. The pseudo samples smooth the solution space and reduce the probability of falling into a local optimum. As a result, PSNN can estimate parameter more robustly than traditional neural networks do. All of these can be proved through the experiments using artificial and real data sets.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.9-21
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• 2004

The current paper proposes a genetic algorithm (GA)-based segmentation method that can automatically extract and track moving objects. The proposed method mainly consists of spatial and temporal segmentation; the spatial segmentation divides each frame into regions with accurate boundaries, and the temporal segmentation divides each frame into background and foreground areas. The spatial segmentation is performed using chromosomes that evolve distributed genetic algorithms (DGAs). However, unlike standard DGAs, the chromosomes are initiated from the segmentation result of the previous frame, then only unstable chromosomes corresponding to actual moving object parts are evolved by mating operators. For the temporal segmentation, adaptive thresholding is performed based on the intensity difference between two consecutive frames. The spatial and temporal segmentation results are then combined for object extraction, and tracking is performed using the natural correspondence established by the proposed spatial segmentation method. The main advantages of the proposed method are twofold: First, proposed video segmentation method does not require any a priori information second, the proposed GA-based segmentation method enhances the search efficiency and incorporates a tracking algorithm within its own architecture. These advantages were confirmed by experiments where the proposed method was success fully applied to well-known and natural video sequences.