• 농업과학연구
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• 제46권2호
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• pp.293-301
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• 2019

This study was done to estimate the effect of progeny numbers and pedigree depth on the accuracy of the estimated breeding value (EBV) using best linear unbiased prediction (BLUP) method in Hanwoo. The experiment groups (sire = 100, 200, and 300; progeny = 4 and 8) were made by random sampling and by genetic evaluation of the following traits: Body weight (BW), carcass weight (CW), eye muscle area (EMA), back fat thickness (BFT) and marbling score (MS9). As a result of the genetic evaluation, the accuracy of the EBV was roughly 30 - 60% with 4 progenies, and the accuracy of the EBV increased by about 50 - 75% with 8 progenies. In the other words, when the number of progenies increased from 4 to 8, the accuracy of the EBV simultaneously increased by about 15 - 20%. Moreover, when the number of sires was higher, variations in the accuracy of the EBV within the groups for each trait decreased. Therefore, this result indicates that not only the number of progeny but also the number of sires can affect the accuracy of the EBV. Consequently, collecting information on the progeny and careful management of that information are very important things in the Hanwoo breeding system. Therefore, the EBV can show more precise results when conducting genetic evaluations.

• 대한의용생체공학회:의공학회지
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• 제43권1호
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• pp.45-51
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• 2022

The purpose of this study is to improve the classification accuracy compared to the existing InceptionV3 model by proposing a new model modified with the fully connected hierarchical structure of InceptionV3, which showed excellent performance in medical image classification. The data used for model training were trained after data augmentation on a total of 1026 chest X-ray images of patients diagnosed with normal heart and Cardiomegaly at Kyungpook National University Hospital. As a result of the experiment, the learning classification accuracy and loss of the InceptionV3 model were 99.57% and 1.42, and the accuracy and loss of the proposed model were 99.81% and 0.92. As a result of the classification performance evaluation for precision, recall, and F1 score of Inception V3, the precision of the normal heart was 78%, the recall rate was 100%, and the F1 score was 88. The classification accuracy for Cardiomegaly was 100%, the recall rate was 78%, and the F1 score was 88. On the other hand, in the case of the proposed model, the accuracy for a normal heart was 100%, the recall rate was 92%, and the F1 score was 96. The classification accuracy for Cardiomegaly was 95%, the recall rate was 100%, and the F1 score was 97. If the chest X-ray image for normal heart and Cardiomegaly can be classified using the model proposed based on the study results, better classification will be possible and the reliability of classification performance will gradually increase.

• Asian-Australasian Journal of Animal Sciences
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• 제30권2호
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• pp.149-153
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• 2017

Objective: This study was to determine the relationship between estimated breeding value and phenotype information after farrowing when juvenile selection was made in candidate pigs without phenotype information. Methods: After collecting phenotypic and genomic information for the total number of piglets born by Landrace pigs, selection accuracy between genomic breeding value estimates using genomic information and breeding value estimates of best linear unbiased prediction (BLUP) using conventional pedigree information were compared. Results: Genetic standard deviation (${\sigma}_a$) for the total number of piglets born was 0.91. Since the total number of piglets born for candidate pigs was unknown, the accuracy of the breeding value estimated from pedigree information was 0.080. When genomic information was used, the accuracy of the breeding value was 0.216. Assuming that the replacement rate of sows per year is 100% and generation interval is 1 year, genetic gain per year is 0.346 head when genomic information is used. It is 0.128 when BLUP is used. Conclusion: Genetic gain estimated from single step best linear unbiased prediction (ssBLUP) method is by 2.7 times higher than that the one estimated from BLUP method, i.e., 270% more improvement in efficiency.

• 대한기계학회논문집
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• 제7권1호
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• pp.1-10
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• 1983

The photoelastic determination of S.I.F. in Fracture mechanics has been regarded as one of the most effective and practical experimental methods in which stresses are read directly, except a few shortcomings involved in the process of experiment; the difficulties of making a sharp crack tip similar to the practical one and nearly impossibilities of carving an arbitrarily shaped crack on the test plate, etc. To eliminate flaws mentioned above, recently, Kitagawa and Watanabe of Tokyo Univ.developed a new method named"Teflon Insert Method". which has improved experimental accuracy to a considerable extent byt remaining still room for further improvement, that is, the elimination of bonding boundary scars which render photoelastic fringes obscure. In this paper, a newly exploited"Teflon Molding Method" was attempted for the completion of teflon-epoxy experimental method. The experimental results obtained by this method are compared with existent theoretical and experimental values to evaluate its accuracy. As result, 1-6% of margin of errors were appeared in a series of photoelastic experiments which defied any other conventional method in terms of experimental accuracy.perimental accuracy.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2002년도 Proceedings of International Symposium on Remote Sensing
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• pp.780-785
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• 2002

As the KOMPSAT-1 satellite can roll tilt up to $\pm$45$^{\circ}$, we have analyzed some EOC images taken at different tilt angles fur this study. The required ground coordinates for bundle adjustment and geometric accuracy, are read from the digital map produced by the National Geography Institution, at a scale of 1:5, 000. These are the steps taken for the tilting angle of KOMPSAT-1 satellite to be present in the evaluation of the accuracy of the geometric of each different stereo image data: Firstly, as the tilting angle is different in each image, the satellite dynamic characteristic must be determined by the sensor modeling. Then the best sensor modeling equation is determined. The result of this research, the difference between the RMSE values of individual stereo images is due more the quality of image and ground coordinates than to the tilt angle. The bundle adjustment using three KOMPSAT-1 stereo pairs, first degree of polynomials for modeling the satellite position were sufficient.

• 전기학회논문지
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• 제61권10호
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• pp.1483-1488
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• 2012

This paper analyzed the precision and accuracy of the altitude-aided GNSS using the altitude information from digital map. The precision of altitude-aided GNSS is analysed using the theoretically derived DOP. It is confirmed that the precision of altitude-aided GNSS is superior to the general 3D positioning method. It is also shown that the DOP of altitude-aided GNSS is independent of altitude bias error while the accuracy was influenced by the altitude bias error. Furthermore, it is shown that, since the altitude bias error influenced differently to each pseudorange measurement, the effect of the altitude bias error is more serious than clock bias error which does not influence position error at all. The results are evaluated by the simulation using the commercial RF simulator and GPS receiver. It confirmed that altitude-aided GNSS could improve not only precision but also accuracy if the altitude bias error are small. These results are expected to be easily applied for the performance improvement to the land and maritime applications.

• 인터넷정보학회논문지
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• 제7권3호
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• pp.169-178
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• 2006

본 논문은 연관규칙탐사 기술에서 사용되는 빈발항목집합을 변형하여 문서분류의 문서에서 빈발단어집합을 정의하고, 이를 사용하여 문서분류 방법으로 잘 알려진 NaiveBayes에 적용하여 이 방법의 정확도를 개선한다. 이 기술의 적용을 위하여 하나의 문서는 여러 개의 문단으로 나뉘어졌으며, 각 문단에 나타나는 단어들의 집합을 트랜잭션화하여 빈발단어 집합을 찾을 수 있도록 하였다. 제안한 방법은 Al::Categorizer 프레임워크에서 구현되었으며 로이터-21578 데이터를 사용하여 그 정확도가 측정되었다. 문단에서의 라인수와 학습문서의 크기를 변화하면서 정확도를 측정하였다. 측정된 결과로부터 제안된 방법이 기존의 방법에 비하여 정확도를 개선한다는 사실을 알 수 있었다.

• 한국멀티미디어학회논문지
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• 제23권1호
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• pp.31-42
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• 2020

During the 4th Industrial Revolution, service platforms utilizing diverse contents are emerging, and research on recommended systems that can be customized to users to provide quality service is being conducted. hybrid recommendation systems that provide high accuracy recommendations are being researched in various domains, and various filtering techniques, machine learning, and deep learning are being applied to recommended systems. However, in a recommended service environment where data must be analyzed and processed real time, the accuracy of the recommendation is important, but the computational speed is also very important. Due to high level of model complexity, a hybrid recommendation system or a Deep Learning-based recommendation system takes a long time to calculate. In this paper, a Cascade-hybrid recommended algorithm is proposed that can reduce the computational time while maintaining the accuracy of the recommendation. The proposed algorithm was designed to reduce the complexity of the model and minimize the computational speed while processing sequentially, rather than using existing weights or using a hybrid recommendation technique handled in parallel. Therefore, through the algorithms in this paper, contents can be analyzed and recommended effectively and real time through services such as SNS environments or shared economy platforms.

• 한국항행학회논문지
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• 제13권2호
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• pp.178-186
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• 2009

SBAS(Satellite Based Augmentation System) 시스템에서는 GNSS 사용자들의 위치 정확도 향상을 위해 위성궤도 및 시계보정정보를 제공하고 있는데, 본 논문에서는 이러한 보정정보의 정확도에 대해 분석하였다. IGS(International GNSS Service)에서 제공하는 GPS 위성의 정밀궤도력을 참값으로 가정하고, 그에 대한 오차를 이용하여 정확도를 분석/수행하였다. 이때 IGS 정밀궤도력과의 정확한 비교를 위해 GPS 위성에 대한 안테나 위상중심 편차와 P1-C1 편이를 고려하였다. SBAS 위성궤도 및 시계보정 정보로는 미국의 WAAS와 일본의 MSAS 보정정보를 이용하였다. 정확도 분석을 통해 SBAS에서 제공하는 위성궤도 보정정보와 위성시계 보정정보가 상당한 상관관계를 가지고 있음을 확인하였다. 또한 보정정보의 정확도는 SBAS 시스템의 지상 네트워크 크기와 위성의 궤적에 영향을 받는 것을 확인하였다.

• 한국멀티미디어학회논문지
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• 제21권8호
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• pp.982-990
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• 2018

In recent years, many wearable devices and mobile apps related to life care have been developed, and a service for measuring the movement during walking and showing the amount of exercise has been provided. However, they do not measure walking in detail, so there may be errors in the total calorie consumption. If the user's behavior is measured by a multi-axis sensor and learned by a machine learning algorithm to recognize the kind of behavior, the detailed operation of walking can be autonomously distinguished and the total calorie consumption can be calculated more than the conventional method. In order to verify this, we measured activities and created a model using a machine learning algorithm. As a result of the comparison experiment, it was confirmed that the average accuracy was 12.5% or more higher than that of the conventional method. Also, in the measurement of the momentum, the calorie consumption accuracy is more than 49.53% than that of the conventional method. If the activity recognition is performed using the wearable device and the machine learning algorithm, the accuracy can be improved and the energy consumption calculation accuracy can be improved.