• Research in Community and Public Health Nursing
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• v.15 no.1
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• pp.102-109
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• 2004

Purpose: The purpose of this study was to confirm a structural model for health promotion for industrial workers. Methods: Data was collected by questionnaires from 294 industrial workers at a food manufacturing factory. The data collected were analyzed through SAS 8.1 and Window LISREL 8.12a. Results: 1. The result of the test showed that the measurement of fitness was $x^2$=(삭제) 443.35, $x^2$/df 5.3415, GFI .86, AGFI .75, RMR .060, NFI .95, NNFI .93, CN 77.58, and those other than NFI and NNFI did not well fit into the practical data. 2. 15 out of 29 paths in a constructed model were statistically significant. 3. The measurements for total fitness in the modified model were $x^2$= (삭제) 146.51, $x^2$/df 1.8546, GFI .95, AGFI .91, RMR .042, NFI .98, NNFI .99, CN 223.44, all of which showed fitness in good shape to the practical data. 4. The result of the study for the modified model indicated that perceived self efficacy had the most significant direct effect on health promotion behaviors, and self esteem, perceived benefits of action, interpersonal influences, commitment to a plan of action were important factors having influences on them. Conclusion: The derived model in this study is considered appropriate in explaining and predicting health promoting behavior of industrial workers. Therefore, it can effectively be used as a reference model for further studies and suggested implication in nursing practice.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.1
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• pp.74-81
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• 2003

In this study, we'd implemented a real time embedded speech recognition system that requires minimum memory size for speech recognition engine and DB. The word to be recognized consist of 40 commands used in a PCS phone and 10 digits. The speech data spoken by 15 male and 15 female speakers was recorded and analyzed by short time analysis method, which window size is 256. The LPC parameters of each frame were computed through Levinson-Burbin algorithm and they were transformed to Cepstrum parameters. Before the analysis, speech data should be processed by pre-emphasis that will remove the DC component in speech and emphasize high frequency band. Baum-Welch reestimation algorithm was used for the training of HMM. In test phone, we could get a recognition rate using likelihood method. We implemented an embedded system by porting the speech recognition engine on ARM core evaluation board. The overall recognition rate of this system was 95%, while the rate on 40 commands was 96% and that 10 digits was 94%.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.3
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• pp.90-95
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• 2015

This study presents a method to test quite small-sized and light-weighted micro-drill bits which are used to make holes in printed circuit boards(PCB). After getting images of micro-drill bits through the high resolution microscope, we developed image processing algorithms to detect fiducial points, and then measured diverse factors of the drill-bit based on these points. We also developed the window-based inspection system to automatically discriminate normal and abnormal status. For the relative comparison of its performance, the system was compared with an existing inspection system using test images. Experimental results showed that the proposed system slightly improved performance, and also classified correctly some misjudged errors which were occurred in the existing system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.95-99
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• 2002

The Loose Part Monitoring System(LPMS) has been designed to detect. locate and evaluate detached or loosened parts and foreign objects in the reactor coolant system. In this paper, at first, we presents an application of the back propagation neural network. At the preprocessing step, the moving window average filter is adopted to reject the reject the low frequency background noise components. And then, extracting the acoustic signature such as Starting point of impact signal. Rising time. Half period. and Global time, they are used as the inputs to neural network . Secondly, we applied the neural network algorithm to LPMS in order to estimate the mass of loose parts. We trained the impact test data of YGN3 using the backpropagation method. The input parameter for training is Rising clime. Half Period amplitude. The result shored that the neural network would be applied to LPMS. Also, applying the neural network to thin practical false alarm data during startup and impact test signal at nuclear power plant, the false alarms are reduced effectively.

• Journal of Families and Better Life
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• v.20 no.2
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• pp.83-95
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• 2002

The objectives of this study were 1) to analyze the attitudes about Elderly Assisted Living(EAL), 2) to consider the policy implications for elderly communal housing according to socio-economic status(income, occupation and education). The survey was undertaken from August to September, 2000 in Seoul and Kyunggi-Do(Ilsan, Bundang). The data were analyzed by SPSS Window program. The major findings were as follows: Most of the respondents prefered to live in EAL(over 56%), under 10 units and desired to be serviced(housework.leisure medical program.meal service). The upper class respondents preferred high-rise apartment style inner city or suburban and prefered paid services in EAL. They would willingly to pay over 800,000 won for living expenses and more than 200 million won for buying their own EAL. The middle class respondents prefered 5 stories multi-family house style with common facilities as a number. And they prefered to common facilities opening to public if the quality of facilities were better. The low class respondents prefered 5 stories multi-family house style and prefered to live within 30 minutes apart from their families and friends. They would pay under 300,000~600,000won for monthly living expenses and under 100 million won for their own EAL.

• The Journal of Korean Obstetrics and Gynecology
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• v.23 no.4
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• pp.95-108
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• 2010

Purpose: This study was to investigate the correlation among body weight, body composition, delivery method, parity, weight gain during pregnancy and obesity before pregnancy of patients who received postpartum care in one oriental medicine hospital. Mothods: From September 1, 2009 to August 31, 2008, we included 34 postpartum patients who had body composition analysis when admission and discharge among 47 postpartum patients who were hospitalized and received postpartum care in $\bigcirc\bigcirc$ University $\bigcirc\bigcirc$ Hospital. We used SPSS 14.0 for window to test for statistical significance. Results: After postpartum care, body weight and BMI of mothers was significantly decreased and the weight loss was almost body water. Mothers who had cesarean section had relatively severe edema and mothers who had been overweight before pregnancy had high BMI, body fat and abdominal fat. After delivery, body fat percentage was increased highly and body weight retention lasted long in mothers who had gained over 12.5kg during pregnancy. Conclusion: Living habits including diet has a significant effect on weight change of mothers during early puerperium, therefore it is required to teach mothers about breast-feeding, diet, and exercise to help their weight return to normal.

• The KIPS Transactions:PartD
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• v.11D no.1
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• pp.95-104
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• 2004

This paper proposes an efficient remote video evaluation system that is matched well with personalized characteristics of students using information filtering based on user profile. For making a question in forms of video, a key frame extraction method based on coordinate, size and color information is proposed. And Question-mating intervals are extracted using gray-level histogram difference and time window. Also, question-making method that combined category-based system with keyword-based system is used for efficient evaluation. Therefore, students can enhance their study achievement through both supplementing their inferior area and preserving their interest area.

• The KIPS Transactions:PartA
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• v.15A no.3
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• pp.135-140
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• 2008

This paper describes a high-speed CMOS demultiplexer using redundant multi-valued logic (RMVL). The proposed circuit receives serial binary data and is converted to parallel redundant multi-valued data using RMVL. The converted data are reconverted to parallel binary data. By the redundant multi-valued data conversion, the RMVL makes it possible to achieve higher operating speeds than that of a conventional binary logic. The implemented demultiplexer consists of eight integrators. Each integrator is composed of an accumulator, a window comparator, a decoder and a D flip flop. The demultiplexer is designed with TSMC $0.18{\mu}m$ standard CMOS process. The validity and effectiveness are verified through the HSPICE simulation. The demultiplexer is achieved the maximum data rate of 20 Gb/s and the average power consumption of 95.85 mW.

• Journal of Bio-Environment Control
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• v.5 no.2
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• pp.210-214
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• 1996

The measuring system was developed for automation of hydroponic culture. It runs in Windows 3.1 and 95. Main window contains greenhouse screen and menu bars such as system setting, sensor calibration, greenhouse status, actuator control, file management, view, and help. Users can use pop-up menu, tool bar and status bat as well as menu bar for manipulation. Especially it was designed to retain flexibility for researchers, who changed detecting sensors frequently. Users can change storage intervals of files, of which 3 types were prepared to use in other software like as statistical programs, graphic programs and/or spread sheets. This system was adopted to deep flow culture system and evaluated to be appropriate for any kind of hydroponic systems.

• Journal of the Korean Society of Visualization
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• v.3 no.2
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• pp.71-78
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• 2005

Uncertainty introduced by a cross-correlation algorithm based on FFT has been investigated using PIV standard images. The standard images were generated by the Monte Carlo simulation method. Both bias and random errors from the velocity vector have been analyzed with regard to the particle diameter, displacement, and the number of particles. The uncertainty of velocity is evaluated based upon the IS0/IEC standard. As a result, a total error of $0.26\%$ is included in the PIV cross-correlation algorithm. In addition, the uncertainty budget is presented, where the effect of the above three variables is examined. According to the budget, the variation of the number of particles within the interrogation window mainly contributes to the combined standard uncertainty of the real measured velocity field when excluding the effect of errors by the experiments itself. Finally, the expanded uncertainty is found to be about $12\%$ at the $95\%$ confidence level.