• The Journal of Korean Society for School & Community Health Education
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• v.25 no.1
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• pp.1-15
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• 2024

Objectives: This study aims to examine the general characteristics and physical activity characteristics of young and middle-aged individuals with hypertension, with the goal of identifying key influencing factors and providing public health policy recommendations. Methods: Participants in this study used data from the 2021 Community Health Survey. The study participants include 5,511 individuals diagnosed with hypertension in the young and middle-aged group (aged 19 to 49). The collected data were analyzed using SPSS 26.0. Results: Model 1 is the influencing factors of young and middle-aged hypertensive patients according to general characteristics. The explanatory power is R²= .065. The influencing factors are as follows. Economic activity (𝛽= -.219, p<.001), breakfast per week (𝛽= .117, p<.001), gender (𝛽= .090, p<.001), subjective health status (𝛽= .073, p<.001), and education level (𝛽= .069, p<.001). Model 2 is the influencing factors of young and middle-aged hypertensive patients, including physical activity characteristics. The explanatory power is R²= .076. The influencing factors are as follows. Strength exercises (𝛽= -4.791, p<.001), the walking activity (𝛽= -2.694, p<.01), and the high-intensity physical activity (𝛽= -2.629, p<.01). Conclusion: The active management of young and middle-aged hypertension is essential to prevent progression to serious disease. To prevent hypertension in young and middle-aged people, health education is needed to develop and utilize health promotion programs that take into account general characteristics and physical activity characteristics.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.7
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• pp.2386-2396
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• 1996

A numerical simulation has been performed for isothermal and reacting flows in an exisymmetric, bluff-body research combustor. The present formulation is based on the density-weighted averaged Navier-Stokes equations together with a k-epsilon. turbulence model and a modified eddy-breakup combustion model. The PISO algorithm is employed for solution of thel Navier-Stokes system. Comparison between measurements and predictions are made for a centerline axial velocities, location of stagnation points, strength of recirculation zone, and temperature profile. Even though the numerical simulation gives acceptable agreement with experimental data in many respects, the present model is defictient in predicting the recoveryt rate of a central near-wake region, the non-isotropic turbulence effects, and variation of turbulent Schmidt number. Several possible explanations for these discrepancies have been discussed.

• Journal of muscle and joint health
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• v.8 no.1
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• pp.122-140
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• 2001

The aims of this study were to understand and to predict the determinent factors affecting the exercise behaviors and physical fitness by testing the Pender's revised health promotion model, and to help the patients with rheumatoid arthritis and osteoarthritis perform the continous exercise program, and to help them maximize the physical effect such as muscle strength, endurance, and functional status and mental effects including self efficacy and quality of life, and improve the physical and mental well being, and to provide a basis for the nursing intervention strategies. Of the selected variables in this study, the endogenous variables included the physical fitness, exercise score, exercise participation, perceived benefits of action, perceived barriers of action to exercise, activity-related affect(depression) and perceived self-efficacy, interpersonal influences(family support), situational factors(duration of arthritis, fatigue) and the exogenous variables included personal sociocultural factor(education level), personal biologic factor(body mass index), personal psychologic factor(perceived health status) and prior related behavior factors(previous participation in exercise, life-style). We analyzed the clinical records of 208 patients with rheumatoid arthritis and degenerative arthritis who visited the outpatient clinics at H university hospital in Seoul. Data were composed of self reported qustionnaire and good of fitness score which were obtained by padalling the ergometer of bicycle for 9 minutes. SPSS Win 8.0 and Window LISREL 8.12a were used for statistical analysis. Of 75 hypothetical paths that influence on physical fitness, exercise participation, exercise score, perceived benefits of action, perceived barriers of action to exercise, activity-related affect(depression) and perceived self-efficacy, interpersonal influences(family support), situational factors(duration of arthritis, fatigue), 40 were supported. The physical fitness was directly influenced by life-style, perceived health status, education level, family support, fatigue, which explained 12% of physical fitness. The exercise participation were directly influenced by life-style, education level, past exercise behavior, perceived benefits of action, perceived barriers of action, depression and duration of arthritis, which explained 47% of exercise participation. Exercise score were directly affected by perceived self efficacy. BMI, life-style, past exercise behavior, perceived benefits of action, family support, perceived health status. perceived barriers of action, and fatigue, which explained 70%. Perceived benefits of action was directly influenced by BMI, life-style, which explained 39%. Perceived barriers of action were directly influeced by past exercise behavior, perceived health status, which explained 7%. Perceived self efficacy were directly influeced by level of education, perceived health status, life-style, which explained 57%. Depression were directly influeced by past exercise behavior, BMI, life-style, which explained 27%. Family support were directly influeced by life-style, perceived health status, which explained 29%. Fatigue were directly influeced by BMI, life-style, perceived health status. which explained 41%. Duration of arthritis were directly influeced by life-style, past exercise behavior, BMI, which explained 6%. In conclusion, important variables for physical fitness were life-style, and variable affecting exercise participation were life-style. Perceived self-efficacy of exercise was a significant predictor of exercise score. BMI, Life-style, perceived benefits of action, family support, past exercise behavior showed direct effects on perceived self-efficacy. Therefore, disease related factor should be minimized for physical performance and well being in nursing intervention for patients with rheumatoid arthritis, and plans to promote and continue exercise should be seeked to reduce disability. In addition, Exercise program should be planned and performed by the exact evaluation of exercise according to the ability of the patients and the contents to improve the importance of exercise and self efficacy in self control program, dedicated educational program should be involved. This study suggest that the methods to reduce the disease related factors, the importance of daily life-style, recognition of benefit of exercise, and educational program to promote self efficacy should be considered in the exercise behavior promotion and nursing intervention for continous performance. The significance of this study is also thought to provide patients with chronic arthritis the specific data for maximal physical and mental well being through exercise, chronic therapeutic procedure, daily adaptation and confrontation in nursing intervention.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.4
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• pp.257-268
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• 2012

The EFDC model with find grid resolution system connecting the Gyeong-Gi bay and Han River estuary was constructed to study on spring-neap variability of net volume transport at each channel of the Han River estuary. The simulation time of numerical model is 124 days from May to August, 2009 with freshwater discharge at Han, Imjin and Yeseong River. The calibration and verification of model results was confirmed using harmonic components of water level and tidal current. The net volume transport was calculated during 30 days with normal freshwater conditions at Seokmo channel and Yeomha channel around Ganghwado. The ebbing net volume transport of 44% and 56% is drained into Gyeong-Gi bay through Yeomha and Seokmo channel, respectively. The ebbing net volume transport nearby Seodo at Yeomha channel convergence flooding net volume transport at Incheon harbor, and drain (westward direction) through channel of tidal flat between Ganghwado and Yeongjongdo to the Gyeong-Gi bay. The averaged net volume transport during 4 tidal cycles was compared to variation of spring-neap periods of the Yeomha channel. The convergence position is moved up- and down-ward according to spring-neap variability. The movement of the convergence zone is appeared because 1) increasing of discharged rate tidal flat channel between Ganghwado and Yeongjongdo at the spring period, 2) The growth of barotropic forcing with downward direction at the spring tide, and 3) The strength of the baroclinic pressure gradient is greater than spring with mixing processes.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.125-141
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• 2021

The rapidly changing social structure of the digital environment is having a significant impact on economic activities. That is also an important issue for Individuals who want to sustain economic activities and countries that support policies. Non-face-to-face industries have been revitalized due to the problem of human capital utilization attributed to aging population, the real economic recession caused by Corona 19, contraction of face-to-face economic activities, reduction of employment, and job instability. Accordingly, digital media contents based economic activities have become commonplace, and the government's main policy issue is to use human capital effectively for media contents based economic activities. Adaptation to the digital environment has become a necessity, not a choice, for those who wish to continue to be in employment. Therefore, this study analyzed the effects of digital and individual abilities on intention to sustain the economic activity and verified the modulation effect of the role model. In order to achieve the purpose of this research, an online survey was conducted on men and women aged 20 to 80 nationwide, and 382 of the 385 collected questionaires were analyzed. The SPSS 23.0 program was used to analyze this study, and the questionaire questions were measured using the Likert 5-point scale. As a result of the analysis, first, the ability to utilize media contents in digital capacity has a positive impact on the intention to sustain economic activity, and that the higher the ability to utilize the latest digital media contents such as SNS, the more likely the intention to sustain economic activity. Secondly, it was found that the financial strength of individuals' abilities was affected by the negative impact, and that the experiences were affected by positive(+) impact on the intention to sustain economic activity. Thirdly, the social environment has no significant effect on the intention to sustain economic activity. Fourth, it was found that family support amongst social support has a positive impact on the intention to sustain economic activity, and that various emotional support for families has increased intention to sustain economic activity. Fifth, the role model was found to have a positive(+) impact on economic sustainability, while the ability to utilize media content and family support played a modulating role on economic sustainability. Therefore, as a result of this research, the government's policy support for employment and entrepreneurship is required in accordance with digital media content based digital education and human structure in order to sustain economic activities.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.167-181
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• 2018

Over the past decade, deep learning has been in spotlight among various machine learning algorithms. In particular, CNN(Convolutional Neural Network), which is known as the effective solution for recognizing and classifying images or voices, has been popularly applied to classification and prediction problems. In this study, we investigate the way to apply CNN in business problem solving. Specifically, this study propose to apply CNN to stock market prediction, one of the most challenging tasks in the machine learning research. As mentioned, CNN has strength in interpreting images. Thus, the model proposed in this study adopts CNN as the binary classifier that predicts stock market direction (upward or downward) by using time series graphs as its inputs. That is, our proposal is to build a machine learning algorithm that mimics an experts called 'technical analysts' who examine the graph of past price movement, and predict future financial price movements. Our proposed model named 'CNN-FG(Convolutional Neural Network using Fluctuation Graph)' consists of five steps. In the first step, it divides the dataset into the intervals of 5 days. And then, it creates time series graphs for the divided dataset in step 2. The size of the image in which the graph is drawn is $40(pixels){\times}40(pixels)$, and the graph of each independent variable was drawn using different colors. In step 3, the model converts the images into the matrices. Each image is converted into the combination of three matrices in order to express the value of the color using R(red), G(green), and B(blue) scale. In the next step, it splits the dataset of the graph images into training and validation datasets. We used 80% of the total dataset as the training dataset, and the remaining 20% as the validation dataset. And then, CNN classifiers are trained using the images of training dataset in the final step. Regarding the parameters of CNN-FG, we adopted two convolution filters ($5{\times}5{\times}6$ and $5{\times}5{\times}9$) in the convolution layer. In the pooling layer, $2{\times}2$ max pooling filter was used. The numbers of the nodes in two hidden layers were set to, respectively, 900 and 32, and the number of the nodes in the output layer was set to 2(one is for the prediction of upward trend, and the other one is for downward trend). Activation functions for the convolution layer and the hidden layer were set to ReLU(Rectified Linear Unit), and one for the output layer set to Softmax function. To validate our model - CNN-FG, we applied it to the prediction of KOSPI200 for 2,026 days in eight years (from 2009 to 2016). To match the proportions of the two groups in the independent variable (i.e. tomorrow's stock market movement), we selected 1,950 samples by applying random sampling. Finally, we built the training dataset using 80% of the total dataset (1,560 samples), and the validation dataset using 20% (390 samples). The dependent variables of the experimental dataset included twelve technical indicators popularly been used in the previous studies. They include Stochastic %K, Stochastic %D, Momentum, ROC(rate of change), LW %R(Larry William's %R), A/D oscillator(accumulation/distribution oscillator), OSCP(price oscillator), CCI(commodity channel index), and so on. To confirm the superiority of CNN-FG, we compared its prediction accuracy with the ones of other classification models. Experimental results showed that CNN-FG outperforms LOGIT(logistic regression), ANN(artificial neural network), and SVM(support vector machine) with the statistical significance. These empirical results imply that converting time series business data into graphs and building CNN-based classification models using these graphs can be effective from the perspective of prediction accuracy. Thus, this paper sheds a light on how to apply deep learning techniques to the domain of business problem solving.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.361-370
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• 2017

In the Brain MRI, RF Pulse is irradiated on the human body in order to acquire an image. At this time, a considerable part of the irradiated RF Pulse energy is absorbed as it is in our body. This will raise the temperature of the human body, but depending on the extent of exposure, it will affect the human body. The change of the SAR and the temperature of the head according to the change of the magnetic field strength is examined. And to investigate the difference in results depending on the use of dental implant. In the human head model, 64 MHz RF Pulse frequency generated from 1.5 T, 128 MHz RF Pulse frequency generated from 3.0 T, and 298 MHz RF Pulse frequency generated from 7.0 T send a frequency and experiment was performed using dental implant using the XFDTD program, we measured the SAR and body temperature changes around the head. The SAR value showed up to about 5800 times the difference at the RF Pulse frequency of 256 MHz, when with dental implant than without dental implant and as the frequency increased, the use of the dental implant increased difference in the SAR value. The change of the temperature of the head showed a temperature rise nearly 2 to 4 times when with dental implant than without dental implant. As the RF Pulse frequency increase, the SAR value increase, but the change of the temperature of the head decrease. Because of as the frequency increase, wavelength is smaller and the more the amount absorbed by the surface of the human. Physiological and biochemical studies of the human body ar necessary through studies of the presence of dental implant and the cause of reaction caused by change in the RF Pulse frequency.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.6227-6232
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• 2012

Interleukin-4 receptor (IL-4R) gene single nucleotide polymorphisms (SNPs) are implicated in cancer development. However, results from the published reports have remained inconclusive. The objective of this study was to conduct a meta-analysis investigating the association between polymorphisms in IL-4R gene and cancer risk. Pubmed, EMBASE and China National Knowledge Infrastructure (CNKI) were searched for case-control studies published up to October 30, 2012 that investigated IL-4R polymorphisms and cancer risk. Odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the strength of any associations. Three IL-4R polymorphisms (Q576R, rs1801275; I75V, rs1805010; S503P, rs1805015) in 21 case-control studies were analyzed. Our meta-analysis indicated that these three polymorphisms are not associated with cancer risk when all studies were pooled together. In the subgroup analysis by tumor site, the results showed that Q576R G allele carriers were associated with a significantly decreased cervical cancer risk (recessive model: OR = 0.77, 95%CI = 0.60-0.98; homozygote comparison: OR = 0.76, 95%CI = 0.58-0.98). I75V G allele carriers were associated with a decreased risk of renal cancer (dominant model = 0.71, 95%CI = 0.57-0.89, heterozygote comparison: OR = 0.69, 95%CI = 0.55-0.87). When stratified by ethnicity, Q576R G allele carriers were associated with a decreased cancer risk in Caucasians (dominant model: OR = 0.90, 95%CI = 0.83-0.98; heterozygote comparison: OR = 0.89, 95%CI = 0.82-0.98). I75V G allele carriers were associated with a decreased cancer risk in Asians (heterozygote comparison: OR = 0.76, 95%CI = 0.62-0.94). S503P C allele carriers were also associated with a decreased cancer risk in Asians (CC VS TT: OR = 0.29, 95%CI = 0.08-0.99). Our results suggest that Q576R, I75V and S503P may be associated with a decreased cancer risk for certain types of cancers and in some specific ethnic groups. Future case-control studies with large sample size are needed to evaluate these associations in detail.

• The Journal of Industrial Distribution & Business
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• v.2 no.1
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• pp.5-15
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• 2011

Prior to the introduction of the CRM, we need to analyze the characteristics and the situations of the company, and should establish a clear vision of the CRM. And each company should identify elements and technologies for introducing the most suitable CRM for them, and optimize them, with long-term perspective. In addition, it requires the implementation strategy which integrates the existing company's routine marketing activities with the concept of the CRM. According to the implementation strategy, the company should improve the business process which is the most effective in investment step by step, and the information system strategy, which develops system investment gradually, should harmonize with it. First, we recognized that raising the company value is important by maximizing customer lifetime value (LTV) by understanding customer needs, and achieving the company's goal through customer satisfaction. Second, we understood that adopting the CRM should be accompanied by changes in the structure, business process and customer contact channels, and it can be successfully integrated with business when it gets proper understandings and attentions of the management. Third, the reality is that there are few cases of successful implementation of domestic companies, and some companies that successfully implement the system mean nothing but implement the solution for developing the CRM. Therefore, it needs to be observed for the long haul, and it seems that we need to approach more systematically to implementation cases for each industry about implementation of the CRM. Fourth, the CRM is no longer the preserve of major companies, and it is the time that medium and small sized enterprises also need it. Taking lesson from Switzerland's small size store merchants who successfully adopt right size of the CRM for their business, for domestic medium and small sized enterprises, the necessity to develop business through developing the CRM models which fit their situations and maintaining relationships with customers has been grown. Fifth, for adopting the CRM business processes, changing or converting the CRM system to the model which fits the company's situation is important rather than applying the advanced company's CRM system model. In other words, the CRM solution which can maximize their own strength by developing the CRM program that makes the most of features and characteristics of the company should be adopted.

• The Journal of Engineering Geology
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• v.18 no.4
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• pp.447-457
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• 2008

Laboratory tests for single plane sliding were conducted using the model rock slope to investigate the cut slope deformability and failure mechanism due to combined effect of engineering characteristics such as angle of sliding plane, water force, joint roughness and infillings. Also the possibility of prediction of slope failure through displacement monitoring was explored. The joint roughness was prepared in forms of saw-tooth type having different roughness specifications. The infillings was maintained between upper and lower roughness plane from zero to 1.2 times of the amplitude of the surface projections. Water force was expressed as the percent filling of tension crack from dry (0%) to full (100%), and constantly increased from 0% at the rate of 0.5%/min and 1%/min upto failure. Total of 50 tests were performed at sliding angles of $30^{\circ}$ and $35^{\circ}$ based on different combinations of joint roughness, infilling thickness and water force increment conditions. For smooth sliding plane, it was found that the linear type of deformability exhibited irrespective of the infilling thickness and water force conditions. For sliding planes having roughness, stepping or exponential types of deformability were predominant under condition that the infilling thickness is lower or higher than asperity height, respectively. These arise from the fact that, once the infilling thickness exceeds asperities, strength and deformability of the sliding plane is controlled by the engineering characteristics of the infilling materials. The results obtained in this study clearly show that the water force at failure was found to increase with increasing joint roughness, and to decrease with increasing filling thickness. It seems possible to estimate failure time using the inverse velocity method for sliding plane having exponential type of deformability. However, it is necessary to estimate failure time by trial and error basis to predict failure of the slope accurately.