• Journal of Radiation Protection and Research
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• v.35 no.1
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• pp.26-33
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• 2010

A computed Radiography (CR) system by use of reusable Image Plate (IP) offers a convenient and reliable way to replace a conventional film-screen system for NDT (non-destructive testing) field. The quality of a radiography to detect a defect of welded objects depends on the procedure embracing several factors such as measurement conditions, image plate type/class, radiation energy, radiation type, and source to image plate distance. Also, the ability of images to detect a flaw reduces with increasing object thickness. In the study, the properties of gamma ray source were summarized for NDT field and inspection images of CR image system manufactured by FUJI were acquired using $^{75}Se$ and $^{192}Ir$ with welded objects. We analyzed the gray scale of hole defect image by using XCAP image processing program and calculated the image contrast and SNR in definition. Also the sesitivities of image quality indicator(IQI) were calculated for hot and cooling tube image of $^{75}Se$ and $^{192}Ir$.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.289-293
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• 2005

Pattern classification extracts various types of pattern information expressing objects in the real world and decides their class. The top priority of pattern classification technologies is to improve the performance of classification and, for this, many researches have tried various approaches for the last 40 years. Classification methods used in pattern classification include base classifier based on the probabilistic inference of patterns, decision tree, method based on distance function, neural network and clustering but they are not efficient in analyzing a large amount of multi-dimensional data. Thus, there are active researches on multiple classifier systems, which improve the performance of classification by combining problems using a number of mutually compensatory classifiers. The present study identifies problems in previous researches on multiple SVM classifiers, and proposes BORSE, a model that, based on 1:M policy in order to expand SVM to a multiple class classifier, regards each SVM output as a signal with non-linear pattern, trains the neural network for the pattern and combine the final results of classification performance.

• Korean Journal of Optics and Photonics
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• v.10 no.2
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• pp.146-151
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• 1999

We demonstrated a harmonic mode locking scheme that used regeneratie phase modulation to get a high and stable repetition rate in a figure-of-eight fiber soliton laser. From the detected beat spectra of the laser output, a sinusoidal clock freguency tone of 400 MHz, the 96th harmonics of the fundamental mode locking frequency, was extracted with a high Q filter and was used to drive the phase modulator, resulting in stable output of soliton pulse train synchronized with the modulation signal. Generated soliton pulses had FWHM pulsewidth of 930 fs and 3.1 nm linewidth, yielding pulsewidth-bandwidth product of 0.359 that was close to the transform limit. As the modulation frequency always followed the beat frequency of laser modes, stable harmonic mode locking was achieved without the adjustment of the cavity length, which has been commonly required in actively mode-locked lasers.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.27-33
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• 2010

In this study, we conducted the classification experiments with GMM (Gaussian Mixture Model) from combining the extracted features by using microphone, Gyro sensor and Acceleration sensor in 9 different environment types. Existing studies of Context Aware wanted to recognize the Environment situation mainly using the Environment sound data with microphone, but there was limitation of reflecting recognition owing to structural characteristics of Environment sound which are composed of various noises combination. Hence we proposed the additional application methods which added Gyro sensor and Acceleration sensor data in order to reflect recognition agent's movement feature. According to the experimental results, the method combining Acceleration sensor data with the data of existing Environment sound feature improves the recognition performance by more than 5%, when compared with existing methods of getting only Environment sound feature data from the Microphone.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.163-168
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• 2008

Navigation system based on indoor location estimation is one of the core technologies in mobile robot systems. Wireless sensor network has great potential in the indoor location estimation due to its characteristics such as low power consumption, low cost, and simplicity. In this paper we present an algorithm to estimate the indoor location of mobile robot based on wireless sensor network and fuzzy modeling. ZigBee-based sensor network usually uses RSSI(Received Signal Strength Indication) values to measure the distance between two sensor nodes, which are affected by signal distortion, reflection, channel fading, and path loss. Therefore we need a proper correction method to obtain accurate distance information with RSSI. We develop the fuzzy distance models based on RSSI values and an efficient algorithm to estimate the robot location which applies to the navigation algorithm incorporating the time-varying data of environmental conditions which are received from the wireless sensor network.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.2 s.302
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• pp.39-48
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• 2005

This paper proposes a novel approach to recognize nine kinds of motion for a multifunction myoelectric hand, acquiring four channel EMG signals from electrodes placed on the forearm. To analyze EMG with properties of nonstationary signal, time-frequency features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. From experimental results, we show that the proposed method enhances the recognition accuracy, and makes it possible to implement a real-time pattern recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.89-98
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• 2004

In this paper, we implement a digital holographic security card system that combines digital holographic memory using random phase encoded reference beams with electrical biometrics. Digitally encoded data including a document, a picture of face, and a fingerprint are recorded by multiplexing of holographic memory. A random phase mask encoding reference beams are used as a decoded key to protect illegal counterfeit. As a result, we can achieve a raw BER of 3.6${\times}$10-4 and shift selectivity of 4${\mu}{\textrm}{m}$ using the 2D random phase mask. Also, we develop a recording pattern and image processing which are suitable for a low cost reader without a position sensing photo-detector for real time data extraction and remove danger of fraud from unauthorized person by comparing the reconstructed holographic data with the live fingerprint data.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.1
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• pp.49-57
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• 2002

Including RF Package inductance, substrate coupling through conductive silicon(Si)-substrate is modeled and quantitatively characterized. 2-port substrate coupling model is extended for the characterization of multi-port substrate coupling between digital circuit block and analog/RF circuit block. Furthermore, scalable parameter extraction model is developed. Multi-port substrate coupling can be investigated by linearly superposing a frequency-dependent 2-port substrate coupling model using scalable parameters. In addition, Substrate coupling including RF package inductance effect is quantitatively investigated. It is shown that package effect increases substrate coupling and shifts a characteristic frequencies(i.e., poles) to the higher frequency range. The proposed methodology can be efficiently used to the mixed-signal circuit performance verification.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.3
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• pp.419-429
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• 1999

Identifying the boundary of the effective receiving power of waves is one of the most important factors for cell optimization. In this paper, we introduce a propagation loss prediction model which yields highly accurate prediction in very complex areas as Seoul where a mixture of many large buildings, small buildings, broad streets, narrow alleys, rivers and forests co-exist in an irregular arrangement. This prediction model is based on neural networks trained on field measurement data collected in the past. Using these data along with 3-D digital elevation maps and vector data for building structures, we extract the parameter values which mainly affect the amount of propagation loss. These parameter values are then used as the inputs to the neural network. Trained neural network becomes the approximated function of the propagation loss model which generalizes very well and can predict accurately in the regions not included in training the neural network. The experimental results show a superior performance over the other models in the cells operating in the city of Seoul.

• The Korea Journal of Herbology
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• v.32 no.1
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• pp.75-81
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• 2017

Objectives : The present study was designed to investigate effects of mixed extracts (9:1, v/v) of Hwangryunhaedoktang, Chamaecyparis obtusa essential oil. We evaluated the antimicrobial and antioxidant activity by manufacturing mixed extracts as the materials for functional medicinal herb cosmetics. Methods : We performed antimicrobial were tested microbes (Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Candida albicans, Propionibacterium acnes) by disc diffusion method and measure clear zone. Antioxidant activities were measured by DPPH (1,1-diphenyl-2-picrylhydrazyl) radical scavenging activity. Results : Antimicrobial activities of mixed extracts against S. epidermideis, P. acnes, S. aureus, E. coli, and Candida. A were $10.9{\pm}3.0mm$, $16.9{\pm}2.0mm$, $9.2{\pm}2.0mm$, $10.3{\pm}1.0mm$, $11.8{\pm}3.0mm$ respectively. The Chamaecyparis obtusa essential oil had the highest antimicrobial activities against S. epidermideis, P. acnes, S. aureus, E. coli, and Candia. A and clear zone of microbes ware $16.7{\pm}3.0mm$, $28.8{\pm}0.2mm$, $15.9{\pm}2.0mm$, $11.5{\pm}1.0mm$, $16.3{\pm}3.0mm$. Hwangryunhaedoktang extract showed antimicrobial activity but only P. acnes and S. aureus The antioxidant activities of the mixed extracts were tested through the evaluation of DPPH radical scavenging activity. The 100 % mixed extracts were found to have 90 % DPPH radical scavenging activity. The mixed extracts was presented similar antioxidant activities compared with that of ascorbic acid. As a result, A mixture extract is expected to have antimicrobial effects and free radical scavenging activity was found. Conclusions : Accordingly, It can be concluded that mixed extracts has the potential to cosmetic material.