• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6028-6042
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• 2019

Since Sparse Nonnegative Matrix Factorization (SNMF) method can control the sparsity of the decomposed matrix, and then it can be adopted to control the sparsity of facial feature extraction and recognition. In order to improve the accuracy of SNMF method for facial feature recognition, new additive iterative rules based on the improved iterative step sizes are proposed to improve the SNMF method, and then the traditional multiplicative iterative rules of SNMF are transformed to additive iterative rules. Meanwhile, to further increase the sparsity of the basis matrix decomposed by the improved SNMF method, a threshold-sparse constraint is adopted to make the basis matrix to a zero-one matrix, which can further improve the accuracy of facial feature recognition. The improved SNMF method based on the additive iterative rules and threshold-sparse constraint is abbreviated as ASNMF, which is adopted to recognize the ORL and CK+ facial datasets, and achieved recognition rate of 96% and 100%, respectively. Meanwhile, from the results of the contrast experiments, it can be found that the recognition rate achieved by the ASNMF method is obviously higher than the basic NMF, traditional SNMF, convex nonnegative matrix factorization (CNMF) and Deep NMF.

• Journal of the Korea Society of Computer and Information
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• v.15 no.2
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• pp.127-134
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• 2010

In continuous vocabulary recognition system by probability distribution of clustering method has used model parameters of an advance estimate to generated each contexts for phoneme data surely needed but it has it's bad points of gaussian model the accuracy unsecure of composed model for phoneme data. To improve suggested probability distribution mixed gaussian model to optimized that phoneme data search supported configuration thread system. This paper of configuration thread system has used extension facet classification user phoneme configuration thread information offered gaussian model the accuracy secure. System performance as a result of represent vocabulary dependence recognition rate of 98.31%, vocabulary independence recognition rate of 97.63%.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.6
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• pp.497-504
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• 2001

A study to improve the accuracy of a map-based compressor model with experiment was performed. Corrections on the effects of suction gas superheat and heat leakage from a compressor shell are required to apply the compressor amp model based on the empirical performance data(map) of compressor manufacturers to the actual system. So experiments to assess the effects of superheat and hat leakage were performed and the corrected equations were made. Compressors and refrigerant used in the experiment were the high pressure type rotary compressor and R-22, experiments were performed by compressor calorimeter. From the experiment, a volumetric efficiency correction factor$(F_ν)$ showed the value of 0.77, slightly higher than 0.75 proposed by Dabiri and Rice for low pressure type reciprocating compressor, and the heat leakage from the compressor shell turned out to be a factor that influenced the discharged mass flow rate. The relation between heat leakage of compressor shell and the variation of discharged mass flow rate from compressor was considered in compressor map modeling as an empirical function. With this function, the prediction accuracy of compressor model in system conditions was improved.