• The Korean Journal of Nuclear Medicine
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• v.36 no.1
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• pp.34-38
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• 2002

Positron emission tomography(PET) is an imaging method that employs radionuclide and tomography techniques. Since 1995, we applied PET not only to the diagnosis of breast cancer but also to the detection of abnormalities in the augmented breast and to the detection of metastasis. Until 2001, we evaluated 242 breast cases by PET at PET center of Seoul National University Hospital. Our group has reported serially at the international journals. In the first report, PET showed high sensitivity for detecting breast cancer, both the primary and axillary node metastasis. A total of 27 patients underwent breast operations based on PET results at Seoul National University Hospital from 1995 to 1996. The diagnostic accuracy of PET were 97% for the primary tumor mass and 96% for axillary lymph node metastasis. In case of the breast augmented, PET also showed excellent diagnostic results for primary breast cancer and axillary lymph node metastasis where mammography and ultrasound could not diagnose properly. PET also had outstanding results in the detection of recurrent or metastatic breast cancer(sensitivity 94%, specificity 80%, accuracy 89%). In addition, our study gave some evidence that PET could be applied further to evaluate the growth rate of tumors by measuring SUV, and finally to prognosticated the disease. PET could also be applied to evaluate the response after chemotherapy to measure its metabolic rate and size. In conclsion, PET is a highly sensitive, accurate diagnostic tool for breast cancer of primary lesion in various conditions including metastasis.

• Structural Engineering and Mechanics
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• v.16 no.2
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• pp.219-240
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• 2003

One of the most versatile approaches for analyzing the dynamic behavior of structural systems is direct time integration of semi-discrete equations of motion. However responses computed by time integration are generally inexact and hence the corresponding errors would rather be studied in advance. In spite of the various error estimation formulations that exist in the literature, it is accepted practice to repeat the analyses with smaller time steps, followed by a comparison between the results. In this paper, after a review of this simple method and disregarding the round-off errors, a more efficient, reliable and yet simple method for estimating errors and enhancing the accuracy is proposed. The main objectives of this research are more realistic error estimation based on the concept of convergence, approximately controlling the reliability by comparing the actual rate of convergence with the integration method's order of accuracy, and enhancement of reliability by applying Richardson's extrapolation. Starting from the errors at specific time instants, the study is then generalized to cases in which the errors should be estimated and decreased at specific events e.g. peak responses. Numerical study illustrates the efficacy of the proposed method.

• Ocean Systems Engineering
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• v.4 no.1
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• pp.53-62
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• 2014

The detection of ship wakes image can demonstrate substantial information regarding on a ship, such as its tonnage, type, direction, and speed of movement. Consequently, the wake target recognition is a favorable way for ship identification. This paper proposes a Local Binary Pattern (LBP) approach to extract image features (wakes) for training an Improved Back Propagation Artificial Neural Network (IBPANN) to identify ship speed. This method is applied to sort and recognize the ship wakes of five different speeds images, the result shows that the detection accuracy is satisfied as expected, the average correctness rates of wakes target recognition at the five speeds may be achieved over 80%. Specifically, the lower ship's speed, the better accurate rate, sometimes it's accuracy could be close to 100%. In addition, one significant feature of this method is that it can receive a higher recognition rate than the nearest neighbor classification method.

• Korean Journal of Optics and Photonics
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• v.23 no.5
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• pp.197-202
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• 2012

We present the results of performance test and analysis of a laser radar system prototype for mapping applications. The laser radar system consisting of fiber laser and avalanche photo-detector and other related component modules was designed and manufactured. The laser radar system now has the status of a prototype for the testing of laboratory performance. Main performance parameters of the system such as laser source characteristics, range accuracy, extinction ratio, and false alarm rate were experimentally measured and the results were analyzed. It confirmed that the laser radar system prototype is performing at a proper level.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.943-953
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• 2010

From a mixture distribution of the score random variable for credit evaluation, there are many methods of estimating optimal thresholds. Most the research news is based on the assumption of normal distributions. In this paper, we extend non-normal distributions such as Weibull, Logistic and Gamma distributions to estimate an optimal threshold by using a hypotheses test method and other methods maximizing the total accuracy and the true rate. The type I and II errors are obtained and compared with their sums. Finally we discuss their e ciency and derive conclusions for non-normal distributions.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.10
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• pp.811-816
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• 2018

When applying the MLFMM algorithm to a large scattering problem, the accuracy of the calculation of the transfer function has a crucial effect on the final simulation results. The numerical accuracy for the double integral on the unit sphere is strongly dependent on the sampling number. With an increasing the sampling points, the overall required memory and running time of the MLFMM simulation also increases. Hence, an optimal over-sampling rate for the number of the sampling points is numerically obtained, which is verified for a real large scattering problem.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.120-121
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• 2006

In this paper, We have designed a face recognition system based on the embedded Linux. This paper has an aim in embedded system to recognize the face more exactly. At first, the contrast of the face image is adjusted with lightening compensation method, the skin and lip color is founded based on YCbCr values from the compensated image. To take advantage of the method based on feature and appearance, these methods are applied to the eyes which has the most highly recognition rate of all the part of the human face. For eyes detecting, which is the most important component of the face recognition, we calculate the horizontal gradient of the face image and the maximum value. This part of the face is resized for fitting the eye image. The image, which is resized for fit to the eye image stored to be compared, is extracted to be the feature vectors using the continuous wavelet transform and these vectors are decided to be whether the same person or not with PNN, to miminize the error rate, the accuracy is analyzed due to the rotation or movement of the face. Also last part of this paper we represent many cases to prove the algorithm contains the feature vector extraction and accuracy of the comparison method.

• Journal of International Academy of Physical Therapy Research
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• v.5 no.2
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• pp.772-780
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• 2014

The purpose of this study is to identify the practical knowledge about osteoporosis and health promoting behavior possessed by male and female university students in their twenties. Next, the study seeks to analyze the difference in the degree of knowledge and practice of health promoting behavior depending on the students' area of study (health-related or non-health-related major) and previous education about osteoporosis. A survey was given to 300 male and female university students in Jeju Island from November 18 to December 6, 2013. Regarding knowledge about osteoporosis, the accuracy rate of health science major participants was 16.8 % higher than that of those of non-health science, and the accuracy rate of participants with previous education about osteoporosis was 12.9 % higher than those who had not. Health promoting behavior showed a higher degree of practice among students in health-related majors and those with previous applicable education. There were significant differences between the knowledge of osteoporosis and major and the presence and absence of prior education. Regarding the degree of health promoting behavior and major, the presence or absence of prior education showed significant differences. Among male and female students in their twenties, the recognition of knowledge about osteoporosis is very low. There is a need to develop various programs that focus on osteoporosis prevention rather than treatment, to improve the quality of education and training content according to the individual, and to lower the target age for osteoporosis education.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.5 s.182
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• pp.177-183
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• 2006

A tape feeder is an important feeding device to supply micro-chips such as 1005 and 0603 components to PCB in SMT process. Traditionally, tape feeding methods using sprocket wheel mechanism has been used for the pickup system of chip-mounters. However, there is growing needs for new feeding mechanism with high accuracy and confidence as electric components are getting much smaller. Thus, recently, a tape feeder using cam-slider mechanism is developed to meet such requirements. The major advantages of developed system are; significantly reduced indexing and backlash errors, slim and compact design, and improved repetitive capacity compared to existing system. In this paper, the performance evaluation criteria for the developed tape feeder are suggested. Stability against induced vibration, positioning accuracy, cycle time, durability and supply error rate are estimated using developed self testers. As a result, the excellence of developed tape feeding mechanism is validated using the effective rating methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3076-3092
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• 2020

An IKPCA-ELM-based intrusion detection method is developed to address the problem of the low accuracy and slow speed of intrusion detection caused by redundancies and high dimensions of data in the network. First, in order to reduce the effects of uneven sample distribution and sample attribute differences on the extraction of KPCA features, the sample attribute mean and mean square error are introduced into the Gaussian radial basis function and polynomial kernel function respectively, and the two improved kernel functions are combined to construct a hybrid kernel function. Second, an improved particle swarm optimization (IPSO) algorithm is proposed to determine the optimal hybrid kernel function for improved kernel principal component analysis (IKPCA). Finally, IKPCA is conducted to complete feature extraction, and an extreme learning machine (ELM) is applied to classify common attack type detection. The experimental results demonstrate the effectiveness of the constructed hybrid kernel function. Compared with other intrusion detection methods, IKPCA-ELM not only ensures high accuracy rates, but also reduces the detection time and false alarm rate, especially reducing the false alarm rate of small sample attacks.