• 한국멀티미디어학회논문지
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• 제18권11호
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• pp.1358-1366
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• 2015

This paper proposes an automatic composition method using the training capability of artificial neural networks and chord progression rules that are widely used by human composers. After training a given song, the new melody is generated by the trained artificial neural networks through applying a different initial melody to the neural networks. The generated melody should be modified to fit the rhythm and chord progression rules for generating natural melody. In order to achieve this object, we devised a post-processing method such as chord candidate generation, chord progression, and melody correction. From some tests we could find that the melody after the post-processing was very improved from the melody generated by artificial neural networks. This enables our composition system to generate a melody which is similar to those generated by human composers.

• 구강회복응용과학지
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• 제24권2호
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• pp.193-201
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• 2008

하악 완전 무치악 환자의 보철수복에 있어 임플란트 식립 후 피개의치의 제작은 첫 번째 치료 옵션으로 고려되어질 수 있다. 임플란트 지지 텔레스코프 피개의치를 제작하는 경우 인공치 및 유지 장치의 배열을 위한 악간 공간이 필요하다. 임플란트 상부 보철물의 passive한 fit은 보철물의 기계적 실패를 막는 중요한 요소이다. Gold electroforming system을 이용하여 제작한 telescopic attachment는 우수한 마진 적합도 및 passive한 fit을 보이며 얇은 코핑 두께로 인하여 좁은 악간 공간에서도 사용이 가능한 장점이 있다. 본 증례에서는 4개의 임플란트 식립 후 Gold electroforming system을 이용하여 telescopic overdenture를 제작하여 기능 및 심미적으로 좋은 결과를 나타내었다.

• 구강회복응용과학지
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• 제18권4호
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• pp.313-320
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• 2002

The purpose of the present study was to evaluate the marginal discrepancy and topography of artificial crown on teeth extracted due to severe periodontal disease. Twenty specimens were invested into metamethylacrylate resin and cutted into vertical slices along with the long axis of tooth. The selected marginal discrepancy between the outer edge of the crown and the finishing line of abutment was examined by stereo- microscope(Olympus, PM-VSP-3, Japan) at magnification of up to 10, and the topography of finishing margin on crown was observed by stereomicroscopeat magnification of up to $70{\times}$. The results were as follows. (1) The mean marginal discrepancy between extracted tooth and artificial crown were $50.82{\mu}m$. (2) There was a considerable difference in the microstructure of finishing margins among specimens. Microscopic Structure on finishing margin showed indefinite line, poor fit (open, underextended and overextended), distorted margin, and surface roughness. This study suggested that there could be necessary to consider the response of periodontium to the emergence profile of natural tooth and precision of marginal geometry while establishing treatment planning for the reconsruction of the artificial crown.

• Smart Structures and Systems
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• 제33권1호
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• pp.65-91
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• 2024

The use of five optimization techniques for the prediction of a strength-based concrete mixture's best-fit model is examined in this work. Five optimization techniques are utilized for this purpose: Slime Mold Algorithm (SMA), Black Hole Algorithm (BHA), Multi-Verse Optimizer (MVO), Vortex Search (VS), and Whale Optimization Algorithm (WOA). MATLAB employs a hybrid learning strategy to train an artificial neural network that combines least square estimation with backpropagation. Thus, 72 samples are utilized as training datasets and 31 as testing datasets, totaling 103. The multi-layer perceptron (MLP) is used to analyze all data, and results are verified by comparison. For training datasets in the best-fit models of SMA-MLP, BHA-MLP, MVO-MLP, VS-MLP, and WOA-MLP, the statistical indices of coefficient of determination (R²) in training phase are 0.9603, 0.9679, 0.9827, 0.9841 and 0.9770, and in testing phase are 0.9567, 0.9552, 0.9594, 0.9888 and 0.9695 respectively. In addition, the best-fit structures for training for SMA, BHA, MVO, VS, and WOA (all combined with multilayer perceptron, MLP) are achieved when the term population size was modified to 450, 500, 250, 150, and 500, respectively. Among all the suggested options, VS could offer a stronger prediction network for training MLP.

• 대한의용생체공학회:의공학회지
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• 제19권2호
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• pp.163-170
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• 1998

인공심장의 주된 합병증인 혈전과 감염의 문제를 줄이고 장착 환자의 삶의 질을 높이기 위하여 체내 완전 매립형 전기 유압식 인공심장을 개발하고 있는 것과 이 모델을 이용한 동물실험에 대하여 보고하는 바이다. 이 인공심장은 혈액펌프, 유압구동기, 구동제어회로, 경피적 에너지-정보 전송시스템, 체내 받테리 등으로 구성되어 있다. 실험동물은 체중 62Kg의 송아지를 이용하였다. 흉강내 이식하는데 어려움은 없었고, 수술 후 생존하는 동안 혈역학적으로 문제는 없었으며 특이한 합병증도 발생하지 않았다. 그러나 이식 11일째 기계적인 결함으로 작동이 정지하였다. 앞으로 기계적 수명이나 생체적 합성 등의 문제 등히 해결되어야 할 것이다.

• 디지털콘텐츠학회 논문지
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• 제17권6호
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• pp.449-459
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• 2016

본 논문에서는 기존의 인공신경망을 이용한 자동작곡 방법에서 발생한 세 가지 문제점을 개선하는 새로운 방법을 제안한다. 첫 번째 문제는 인공신경망이 출력한 곡의 박자를 음악이론에 맞도록 후처리 하는 것에서 모든 경우를 처리하지 못하여 발생한 문제이다. 두 번째 문제는 음표를 학습하는 인공신경망에 음표와 구분되는 큰 값으로 쉼표를 같이 학습하다보니 음표공간이 왜곡되어 발생하는 문제이다. 마지막 문제는 새로운 곡 작곡 시 사용자가 작곡해서 넣어준 초기 멜로디와 박자가 인공신경망이 출력하는 나머지 멜로디와 박자와 어울리지 못하여 발생하는 문제이다. 본 논문에서는 이러한 문제를 해결하기 위하여 개선된 박자 후처리 알고리즘과 초기 멜로디 처리 방법을 제안하였으며 쉼표용 인공신경망을 새로이 도입하였다. 실험결과 새로 제안한 방법이 기존의 방법에서 발생한 세 가지 문제점을 모두 해결하는 것으로 판명되었다.

• BMB Reports
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• 제28권2호
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• pp.184-190
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• 1995

Functional study of the gap junction channel has been hindered by its inaccessibility in situ. Identification of forms of this channel in artificial membrane has been elusive because of the lack of identifying channel physiology. Connexin32 forms gap junction channels between neighboring cells in rat liver. Connexin32 was affinity-purified using a monoclonal antibody and reconstituted into artificial phospholipid vesicles. The reconstituted connexin32 formed channels through the vesicle membrane that were permeable to sucrose (Stokes radius: $5{\AA}$). The permeability to sucrose was reversibly reduced by acidic pH. In addition, the pH effect on the permeability to sucrose fit well with by the Hill's equation (where, n=2.7 and pK=6.7).

• 한국정보시스템학회지:정보시스템연구
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• 제25권4호
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• pp.23-36
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• 2016

Purpose Recently, many researchers have paid much attention to the Artificial Intelligence fields of GVGP, PCG. The paper suggests that the improved MCTS algorithm to apply for the framework can generate better AI agent. Design/methodology/approach As noted, the MCTS generate magnificent performance without an advanced training and in turn, fit applying to the field of GVGP which does not need prior knowledge. The improved and modified MCTS shows that the survival rate is increased interestingly and the search can be done in a significant way. The study was done with 2 different sets. Findings The results showed that the 10 training set which was not given any prior knowledge and the other training set which played a role as validation set generated better performance than the existed MCTS algorithm. Besed upon the results, the further study was suggested.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2020년도 제61차 동계학술대회논문집 28권1호
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• pp.271-272
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• 2020

Data mining is known useful in medical area when no availability of evidence favoring a particular treatment option is found. Huge volume of structured/unstructured data is collected by the healthcare field in order to find unknown information or knowledge for effective diagnosis and clinical decision making. The data of 5,179 records considered for analysis has been collected from Korean National Health and Nutrition Examination Survey(KHANES) during 2-years. Data splitting, referred as the training and test sets, was applied to predict to fit the model. We analyzed to predict chronic kidney disease (CKD) using data mining method such as naive Bayes, logistic regression, CART and artificial neural network(ANN). This result present to select significant features and data mining techniques for the lifestyle factors related CKD.

• 소성∙가공
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• 제29권2호
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• pp.76-88
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• 2020

The need for advanced high strength steel (AHSS) forming technology is increasing as interest in light weight and safe automobiles increases. Multipoint dieless forming (MDF) is a novel sheet metal forming technology that can create any desired longitudinal and transverse curvature in sheet metal. However, since the springback phenomenon becomes larger with high strength metal such as AHSS, predicting the required MDF to produce the exact desired curvature in two directions is more difficult. In this study, a prediction model using artificial neural network (ANN) was developed to predict the springback that occurs during AHSS forming through MDF. In order to verify the validity of model, a fit test was performed and the results were compared with the conventional regression model. The data required for training was obtained through simulation, then further random sample data was created to verify the prediction performance. The predicted results were compared with the simulation results. As a result of this comparison, it was found that the prediction of our ANN based model was more accurate than regression analysis. If a sufficient amount of data is used in training, the ANN model can play a major role in reducing the forming cost of high-strength steels.