• The Journal of Korean Obstetrics and Gynecology
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• v.28 no.3
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• pp.40-53
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• 2015

Objectives The purpose of this study is to report the gynecologic use of Angelicae Gigantis Radix in uterus and gynecology part of Dongeuibogam. Methods I searched prescriptions containing Angelicae Gigantis Radix in uterus and gynecology part of Dongeuibogam and analyzed the selected prescriptions to research the use of Angelicae Gigantis Radix in uterus and gynecology part of Dongeuibogam. Results Prescriptions containing Angelicae Gigantis Radix are utilized for 10 disease patterns in uterus part. The number of prescriptions containing Angelicae Gigantis Radix is 50 in uterus part. Prescriptions containing Angelicae Gigantis Radix are utilized for 29 disease patterns in gynecology part. The number of Prescriptions containing Angelicae Gigantis Radix is 90 in gynecology part. Angelicae Gigantis Radix was taken as a sovereign, minister drug of prescriptions containing Angelicae Gigantis Radix of uterus and gynecology part. In many prescriptions, Angelicae Gigantis Radix is used in the treatment of amenorrhea and dysmenorrhea in uterus part. Prescriptions containing Angelicae Gigantis Radix are used to treat not only female infertility but also male infertility in gynecology part. The Samul-tang is the most useful prescription which contains Angelicae Gigantis Radix. Conclusions Angelicae Gigantis Radix is an effectual medicinal herb for menstrual disease, vaginal discharge, pregnancy disease, postpartum disease. So I consider that it is necessary to study methods which improve convenience and effect of prescriptions containing Angelicae Gigantis Radix.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.49 no.12
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• pp.665-672
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• 2000

This paper described the measurement technology to analyze the partial discharge characteristics for long term aging of insulations. This system was consisted of high voltage generation and measurement part, PD detection part, digital conversion and signal processing part. We used the VXI system for digital conversion and signal processing part. In the digital conversion part, we studied the error of partial discharge magnitude and memory capacity for reading digital signal with the sampling rate. In the signal processing part, we showed the program algorithm to count pulses and read peak values of partial discharge. The allowable minimum sampling rate of digizer was decided to 250kS/s through analyzing test. We confirmed that this system was very useful in the study of $\phi-q-n$ characteristics of long term PD experiments with specimens being consisted of internal void defects and CIGRE II electrodes.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.516-519
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• 2001

To diagnose a patient's blood vessel disease, apoplexy, hypertension, arteriosclerosis, the blood velocity is very important. Determining the blood velocity methods using ultrasound are Continuous Doppler System and Pulse Doppler System. In using the Pulse Doppler System, we can obtain the position of blood velocity. But it is more complex hardware than Continuous Doppler System and it has low SNR(signal-noise ratio). So in this study, to obtain a believable information we use the Continuous Pulse Doppler System. Thus system have analog part and digital part. In analog part is composed of ultrasound generating part, the amplifying part to amplify the received signal from ultrasound sensor, the demodulation part to detect blood velocity and the filtering part to remove the noise. In digital part is composed of the A/D conversion part, digital signal processing part, and the communication part to communicate the PC. In this study to implement efficient ultrasound blood velocity measurement system, we can get the patient's blood velocity information in realtime. Thus, It is a useful in the accurate diagnosis with C.T(computered tomography), M.R.I(magnetic resonance imaging).

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.647-658
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• 2009

It is already known from the previous study that flood seems to have heavier tail. Therefore, to make prediction of future extreme label, some agreement of tail behavior of extreme data is highly required. The LH-moments estimation method, the generalized form of L-moments is an useful method of characterizing the upper part of the distribution. LH-moments are based on linear combination of higher order statistics. In this study, we have formulated LH-moments of five distributions useful in hydrology such as, two types of three parameter kappa distributions, beta-${\kappa}$ distribution, beta-p distribution and a generalized Gumbel distribution. Using LH-moments reduces the undue influences that small sample may have on the estimation of large return period events.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.744-752
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• 2012

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as an one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problems. In data preprocessing part, Principal Component Analysis(PCA) which is generally used in face recognition, which is useful to express some classes using reduction, since it is effective to maintain the rate of recognition and to reduce the amount of data at the same time. However, because of there of the whole face image, it can not guarantee the detection rate about the change of viewpoint and whole image. Thus, to compensate for the defects, Linear Discriminant Analysis(LDA) is used to enhance the separation of different classes. In this paper, we combine the PCA&LDA algorithm and design the optimized pRBFNNs for recognition module. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as two kinds of polynomials such as constant, and linear. The coefficients of connection weight identified with back-propagation using gradient descent method. The output of the pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to face image(ex Yale, AT&T) datasets and then demonstrated from the viewpoint of the output performance and recognition rate.

• Nuclear Engineering and Technology
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• v.53 no.4
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• pp.1199-1209
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• 2021

The detection of unexpected loose parts in the primary coolant system in a nuclear power plant remains an extremely important issue. It is essential to develop a methodology for the localization and mass estimation of loose parts owing to the high prediction error of conventional methods. An effective approach is presented for the localization and mass estimation of a loose part using machine-learning and deep-learning algorithms. First, a methodology was developed to estimate both the impact location and the mass of a loose part at the same times in a real structure in which geometric changes exist. Second, an impact database was constructed through a series of impact finite-element analyses (FEAs). Then, impact parameter prediction modes were generated for localization and mass estimation of a simulated metallic loose part using machine-learning algorithms (artificial neural network, Gaussian process, and support vector machine) and a deep-learning algorithm (convolutional neural network). The usefulness of the methodology was validated through blind tests, and the noise effect of the training data was also investigated. The high performance obtained in this study shows that the proposed methodology using an FEA-based database and deep learning is useful for localization and mass estimation of loose parts on site.

• Journal of Microbiology and Biotechnology
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• v.32 no.8
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• pp.1026-1033
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• 2022

This study presents a novel DNA part characterization technique that increases throughput by combinatorial DNA part assembly, solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. We confirmed that the fluorescence intensities of colonies on plates were comparable to fluorescence at the single-cell level from a high-end, flow-cytometry device and developed a high-throughput image analysis pipeline. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA parts and their combinations with a single sequencing experiment. Using our techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h without any automated equipment. We anticipate that this high-throughput and easy-to-use part characterization technique will contribute to increasing part diversity and be useful for building genetic circuits and metabolic pathways in synthetic biology.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.751-758
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• 2001

Exergy concept is applied to the analysis of part-load performance of gas turbine engine. Exergy is a useful tool to find the source of irreversibility in thermal system. In this study, details of the performance characteristics of a heavy-duty gas turbine, l50MW-class GE 7FA model, are described by theoretical investigations with exergy analysis. Result shows that exergy destruction rate of gas turbine increases with decreased load, which means increase of irreversibility. Also, it is found that variations of IGV angle and amount of cooling air for turbine blades are closely related to the inefficiencies of compressor and turbine, respectively.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.293-297
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• 2004

This paper is described manufacturing to jewelry by using rapid prototype. At that time, the SLC file is useful for solved generating errors to part build file. Then. we have reduced the time of manufacturing complicated three-dimensional form. Generally, it is used the STL file for rapid prototype that it is necessary to considerable time when complicated firm as jewelry generated pan build file. But the SLC file is solved to problem because it consists of configuration of a section. Neter the less, Generating Part build file hate had a lot of problem when the SLC file is used.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.267-271
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• 2000

A part definition must not only provide shape information of a nominal part but also contain non-shape information such as tolerances, surface roughness and material attributes. Although machining features are useful for suitable shape information for process reasoning in the CAPP, they need to be integrated with tolerance information for effective process planning. We develop the tolerance modeler that efficiently integrates machining features with tolerance information for feature-based CAPP It is based on the association of machining features, tolerance features. and tolerances Tolerance features, where tolerances are assigned, are classified into two types; one is the face that is a topological entity on a solid model and the other is the functional geometry that is not referenced to topological entities. The functional geometry is represented by using machining features All the data for representing tolerance information with machining features are stored completely and unambiguously in the independent tolerance structure. The developed tolerance modeler is implemented as a module of a comprehensive feature-based CAPP system.