• Korean Journal of Health Education and Promotion
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• v.22 no.4
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• pp.179-202
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• 2005

Purpose: The purpose of this study was to develop the health promotion program for rural elderly through PRECEDE process. Method: The health promotion program was developed based on the preliminary diagnosis. The data collection was performed from March 10th to April 9th, 2003. The subjects were selected at Mari Myun, Geochang Gun, in Korea. The preliminary diagnosis was examined with the 115 elders. Data was analyzed by descriptive statistics and Cronbach's n test with SPSS/Win 10.0 program. Results: The health promotion program was developed based on diagnostic result using PRECEDE model. The developed program was corrected and revised with the advices from 6 experts. The final program included health responsibility(cancer prevention and early detection, hygienic, false teeth management no smoking and moderation in drink, and chronic disease prevention and management), physical activity(6 kinds of exercise), nutrition(low sodium diet calcium intake, and right eating habit), spiritual growth(spiritual demand and death preparation teaching), interpersonal relations(relationship with couple, children, grandchildren, neighborhood), and stress management(sports dance, foot massage, positive thought, and song class). Conclusion: I propose that it is necessary to identity the effect of health promotion program for rural elderly. And strategy development that can spread the health promotion program elderly is needed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2991-3000
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• 1996

In this paper, an effective neural acquisition system is suggested for acquisition of the DS/SS communication system. The suggested system uses a binary neural network which geometrically analyzes and learns a given PN sequence in the binary field. the probabilities of detection and false alarm are obtained and are compared to simulation values. The equation of the mean acquisition time is derived and is compared to the doubledwell time of the serial serial search system. The significant improvement of the performance is demonstrated. As the length of synchronization sequence becomes longer and the number is increased, the performance is improved.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.1
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• pp.72-77
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• 2008

In this paper, we propose a novel structure where the energy detector has multiples of verification using time delay in order to improve its performance. Additionally, the performance is investigated by simulation and compared to that of the original energy detector. The simulation result shows that the proposed scheme improves the performance when SNR is compared with the mis-detection probability for both 1% and 10% of false alarm probability. The performance is also described in terms of ROC.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.3-8
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• 2014

Recently, a spectrum sensing technique employing the maximum value of a received power spectrum as a test statistic has been presented in the literature for the purpose of detecting a wireless microphone signal in TV bands This detects the presence of a primary user by comparing the test statistic with some threshold, which depends on the background noise power level as well as a target false alarm rate. Therefore its performance may deteriorate when the noise power uncertainty occurs. As a means to mitigate this difficulty, we present a spectrum sensing strategy adopting the ratio of the maximum and the minimum value of the power spectrum as a test statistic and analyze its performance of spectrum sensing.

• The Korean Journal of Nuclear Medicine
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• v.38 no.5
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• pp.331-337
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• 2004

Cardiac neurotransmission imaging allows in vivo assessment of presynaptic reuptake, neurotransmitter storage and postsynaptic receptors. Among the various neurotransmitter, I-123 MIBG is most available and relatively well-established. Metaiodobenzylguanidine (MIBG) is an analogue of the false neurotransmitter guanethidine. It is taken up to adrenergic neurons by uptake-1 mechanism as same as norepinephrine. As tagged with I-123, it can be used to image sympathetic function in various organs including heart with planar or SPECT techniques. I-123 MIBG imaging has a unique advantage to evaluate myocardial neuronal activity in which the heart has no significant structural abnormality or even no functional derangement measured with other conventional examination. In patients with cardiomyopathy and heart failure, this imaging has most sensitive technique to predict prognosis and treatment response of betablocker or ACE inhibitor. In diabetic patients, it allow very early detection of autonomic neuropathy. In patients with dangerous arrhythmia such as ventricular tachycardia or fibrillation, MIBG imaging may be only an abnormal result among various exams. In patients with ischemic heart disease, sympathetic derangement may be used as the method of risk stratification. In heart transplanted patients, sympathetic reinnervation is well evaluated. Adriamycin-induced cardiotoxicity is detected earlier than ventricular dysfunction with sympathetic dysfunction. Neurodegenerative disorder such as Parkinson's disease or dementia with Lewy bodies has also cardiac sympathetic dysfunction. Noninvasive assessment of cardiac sympathetic nerve activity with I-123 MIBG imaging nay be improve understanding of the pathophysiology of cardiac disease and make a contribution to predict survival and therapy efficacy.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.277-296
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• 2016

There is a need for rapid and objective assessment of concrete bridge decks for maintenance decision making. Infrared Thermography (IRT) has great potential to identify deck delaminations more objectively than routine visual inspections or chain drag tests. In addition, it is possible to collect reliable data rapidly with appropriate IRT cameras attached to vehicles and the data are analyzed effectively. This research compares three infrared cameras with different specifications at different times and speeds for data collection, and explores several factors affecting the utilization of IRT in regards to subsurface damage detection in concrete structures, specifically when the IRT is utilized for high-speed bridge deck inspection at normal driving speeds. These results show that IRT can detect up to 2.54 cm delamination from the concrete surface at any time period. It is observed that nighttime would be the most suitable time frame with less false detections and interferences from the sunlight and less adverse effect due to direct sunlight, making more "noise" for the IRT results. This study also revealed two important factors of camera specifications for high-speed inspection by IRT as shorter integration time and higher pixel resolution.

• The Journal of the Acoustical Society of Korea
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• v.20 no.3
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• pp.3-7
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• 2001

In active sonar system using CW signal, when the noise included reverberation has not the white characteristics, the CFAR detector estimates high threshold. Because of this reason it cannot detect targets and not resolve the closely spaced multiple targets. In order to solve these problems, we propose an adaptive reverberation rejection filter The proposed filter is composed of an adaptive filter and a fixed filter with its coefficients. To study the performance of the proposed adaptive reverberation rejection filter, various experiments have been performed under In moving active sonar environments. As a results, the proposed method has the improved performance than the previous methods.

• Genomics & Informatics
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• v.5 no.1
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• pp.1-5
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• 2007

Embryonic stem cells can be differentiated into various types of cells, requiring a tight regulation of transcription. Biomarkers related to each lineage of cells are used to guide the differentiation into neural or any other fates. In previous experiments, we reported the guided differentiation (GD)-specific genes by comparing profiles of random differentiation (RD). Interestingly 68% of differentially expressed genes in GD overlap with that of RD, which makes it difficult for us to separate the lineages by examining several markers. In this paper, we design a prediction model to identify the differentiation into neural fates from any other lineage. From the profiles of 11,376 genes, 203 differentially expressed genes between neural and random differentiation were selected by random variance T-test with 95% confidence and 5% false discovery rate. Based on support vector machine algorithm, we could select 79 marker genes from the 203 informative genes to construct the optimal prediction model. Here we propose a prediction model for the prediction of neural fates from random differentiation which is constructed with a perfect accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.35-46
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• 1994

In this paper, the performance of DS/SS acquisition system over frequency nonselective Rician fading channel is analyzed by means of packet loss probability. The power ratio of the fading component to the specular compnent. seccessive constant fadong chips k. and correlation coefficient among k chipe are taken for channel parameters. The false alarm probabilities and detection probabilities are derived, and packet loss probability is evaluated in terms of these probablities in the stats transition diagram. From the results of the performance test, these exists the region of packet loss probability in crease because of autocorrelation sidelobe. As k increases, the packet loss probabolotoes decrease.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.