• Journal of Life Science
• /
• v.21 no.1
• /
• pp.1-8
• /
• 2011

The purpose of this study was to investigate whether 12-weeks of movement training would increase the psoas major cross-sectional area (CSA) in senior men and women. Fifty eight men and women aged 65 to 80 years old ($69.6{\pm}3.7$, 30 male, 28 female) were divided into a control (n=19) and exercise group (n=39). Subjects were assessed before and after the training program for stature, body mass, and magnetic resonance imaging of the psoas major and the quadriceps muscle. The experimental group performed exercises using machines designed to improve the movement of the hip at a frequency of twice every week, with a total of 23 trainings in 12-weeks. Magnetic resonance images of both thighs and the abdomen and psoas major were obtained, aimed at 50% of the length of the greater trochanter and the lower edge of the femur and between the fourth (L4) and fifth (L5) lumbars. A 9.4% increase in the psoas major CSA in the training group was observed. In the male and female breakdown, a 11.5% and 8.4% change was observed in males and females, respectively. In the quadriceps, there was no significant statistical improvement in either males or females. Furthermore, in the control group, there was no significant change seen in either the psoas major or the quadriceps. As a result of conducting training that enables upkeep of posture and smooth linkage of the lumbar spine, the pelvis and thighbone, the psoas major CSA of older adults were improved in a short period of time. For this reason, the possibility of improving the psoas CSA, which decreases remarkably with increased age, by improving the linkage of the body trunk is also suggested.

• Journal of Preventive Medicine and Public Health
• /
• v.21 no.2 s.24
• /
• pp.217-223
• /
• 1988

A cross-sectional survey was conducted to determine the prevalence rate of scoliosis in elementary, middle and high school boys in May 1988. The study population included 1,393 male students in Pusan ; 463 students of 4th grade in two elementary schools, 543 students of 1st grade in one middle school and 387 students of 1st grade in one high school. The students of elementary school were screened with inspection by two physicians at the same time and the students of middle and high schools were screened with both inspection by the same physicians and 70mm chest X-ray. Positive students in any one of the two screening tests were measured for height and body weight and asked for the shoulder side on which he carries the school bag. The angle of curvature on X-ray film was measured by Cobb's method. The number of positive students in any one of the two screening tests were 15(3.2%) in elementary schools, 174(32.0%) in middle school and 92(23.8%) in high school. However, positive rates in both tests were only 2.2% for the middle school students and 2.6% for the high school students and among these students 1.1% out of total middle school students and 2.3% of high school students had a curvature equal to or greater than $5^{\circ}$ of Cobb's angle on 70mm chest X-ray film. There was a statistically significant association between the direction of spinal curve and the shoulder side on which one carries school bag among positive students in both screening 1.sts (p<0.05) Mean height and body weight of 281 positive students in any one of two screening tests were compared with the Korean standard for the same age. Mean weight of elementary school students was nearly the same as the standard weight but the height was slightly shorter than the standard. However, both mean height and weight of the middle school students were lower than the standard while those of the high school students were higher. The prevalence rate of scoliosis for the 2nd and 3rd grades of high school is presumed to be higher than that of the 1st grade of high school and the rate for girls will be even higher than the rate for boys of the same age. Thus, scoliosis seems to be an important school health problem. To prevent scoliosis, it is recommeded to reduce the weight of school bag, educate the students to keep a right posture and exercise periodically.

• Asia pacific journal of information systems
• /
• v.19 no.4
• /
• pp.47-75
• /
• 2009

Recently, researches on Management Information Systems (MIS) have laid out theoretical foundation and academic paradigms by introducing diverse theories, themes, and methodologies. Especially, academic paradigms of MIS encourage a user-friendly approach by developing the technologies from the users' perspectives, which reflects the existence of strong causal relationships between information systems and user's behavior. As in other areas in social science the use of structural equation modeling (SEM) has rapidly increased in recent years especially in the MIS area. The SEM technique is important because it provides powerful ways to address key IS research problems. It also has a unique ability to simultaneously examine a series of casual relationships while analyzing multiple independent and dependent variables all at the same time. In spite of providing many benefits to the MIS researchers, there are some potential pitfalls with the analytical technique. The research objective of this study is to provide some guidelines for an appropriate use of SEM based on the assessment of current practice of using SEM in the MIS research. This study focuses on several statistical issues related to the use of SEM in the MIS research. Selected articles are assessed in three parts through the meta analysis. The first part is related to the initial specification of theoretical model of interest. The second is about data screening prior to model estimation and testing. And the last part concerns estimation and testing of theoretical models based on empirical data. This study reviewed the use of SEM in 164 empirical research articles published in four major MIS journals in Korea (APJIS, ISR, JIS and JITAM) from 1991 to 2007. APJIS, ISR, JIS and JITAM accounted for 73, 17, 58, and 16 of the total number of applications, respectively. The number of published applications has been increased over time. LISREL was the most frequently used SEM software among MIS researchers (97 studies (59.15%)), followed by AMOS (45 studies (27.44%)). In the first part, regarding issues related to the initial specification of theoretical model of interest, all of the studies have used cross-sectional data. The studies that use cross-sectional data may be able to better explain their structural model as a set of relationships. Most of SEM studies, meanwhile, have employed. confirmatory-type analysis (146 articles (89%)). For the model specification issue about model formulation, 159 (96.9%) of the studies were the full structural equation model. For only 5 researches, SEM was used for the measurement model with a set of observed variables. The average sample size for all models was 365.41, with some models retaining a sample as small as 50 and as large as 500. The second part of the issue is related to data screening prior to model estimation and testing. Data screening is important for researchers particularly in defining how they deal with missing values. Overall, discussion of data screening was reported in 118 (71.95%) of the studies while there was no study discussing evidence of multivariate normality for the models. On the third part, issues related to the estimation and testing of theoretical models on empirical data, assessing model fit is one of most important issues because it provides adequate statistical power for research models. There were multiple fit indices used in the SEM applications. The test was reported in the most of studies (146 (89%)), whereas normed-test was reported less frequently (65 studies (39.64%)). It is important that normed- of 3 or lower is required for adequate model fit. The most popular model fit indices were GFI (109 (66.46%)), AGFI (84 (51.22%)), NFI (44 (47.56%)), RMR (42 (25.61%)), CFI (59 (35.98%)), RMSEA (62 (37.80)), and NNFI (48 (29.27%)). Regarding the test of construct validity, convergent validity has been examined in 109 studies (66.46%) and discriminant validity in 98 (59.76%). 81 studies (49.39%) have reported the average variance extracted (AVE). However, there was little discussion of direct (47 (28.66%)), indirect, and total effect in the SEM models. Based on these findings, we suggest general guidelines for the use of SEM and propose some recommendations on concerning issues of latent variables models, raw data, sample size, data screening, reporting parameter estimated, model fit statistics, multivariate normality, confirmatory factor analysis, reliabilities and the decomposition of effects.

• Journal of Korea Water Resources Association
• /
• v.54 no.12
• /
• pp.1339-1348
• /
• 2021

In accordance with the River Law, the basic river maintenance plan is established every 5-10 years with a considerable national budget for domestic rivers, and various river surveys such as the river section required for HEC-RAS simulation for flood level calculation are being conducted. However, river survey data are provided only in the form of a pdf report to the River Management Geographic Information System (RIMGIS), and the original data are distributedly owned by designers who performed the river maintenance plan in CAD format. It is a situation that the usability for other purposes is considerably lowered. In addition, when using surveyed CAD-type cross-sectional data for HEC-RAS, tools such as 'Dream' are used, but the reality is that time and cost are almost as close as manual work. In this study, RAUT (River Information Auto Upload Tool), a tool that can solve these problems, was developed. First, the RAUT tool attempted to automate the complicated steps of manually inputting CAD survey data and simulating the input data of the HEC-RAS one-dimensional model used in establishing the basic river plan in practice. Second, it is possible to directly read CAD survey data, which is river spatial information, and automatically upload it to the river spatial information DB based on the standard data model (ArcRiver), enabling the management of river survey data in the river maintenance plan at the national level. In other words, if RIMGIS uses a tool such as RAUT, it will be able to systematically manage national river survey data such as river section. The developed RAUT reads the river spatial information CAD data of the river maintenance master plan targeting the Jeju-do agar basin, builds it into a mySQL-based spatial DB, and automatically generates topographic data for HEC-RAS one-dimensional simulation from the built DB. A pilot process was implemented.

• Journal of the Korean Orthopaedic Association
• /
• v.55 no.2
• /
• pp.127-134
• /
• 2020

Purpose: The aims of this study were (1) to investigate the relationship between the characteristics of allogenic bone block and the compressive strength of an allogenic bone block measured by biomechanical experiments, and (2) to compare the maximum pressure load of allogenic bone block with the gap pressure measured at the high tibial opening osteotomy. Materials and Methods: Ten patients who provided informed consent for gap pressure measurements during opening wedge high tibial osteotomy (OWHTO) were included. The gap pressures were measured at 1 mm intervals while opening the osteotomy site from 8 mm to 14 mm. Seventeen U-shaped allogenous wedge bone blocks were made from the femur, tibia, and humerus. The height, width, cross-sectional area, and cortex thickness of the bone blocks were measured, along with the maximum compressive load just before breakage. The relationship between these characteristics and the maximum pressure load of the bone blocks was evaluated. The gap pressures measured in OWHTO were compared with the maximum pressure loads of the allogenous wedge bone blocks to evaluate the possibility of inserting allogenous wedge bone blocks into the osteotomy site without a distractor in OWHTO. Results: The OWHTO gap pressure increased with increasing osteotomy site opening. The mean gap pressure, which occurred at a 14-mm opening, was 282±93 N; the maximum pressure was 427 N. The maximum pressure load of the allografts was 13,379±6,469 N (minimum, 5,868; maximum, 29,130 N) and was correlated significantly with the cortical bone thickness (correlation coefficient=0.693, p=0.002) and cross-sectional area (correlation coefficient=0.826, p<0.001). Depending on the sterilization method, the maximum pressure loads for the bone blocks were 13,406±5,928 N for freeze-dried and 13,348±7,449 N for fresh frozen. The maximum compressive load of the allogenous wedge bone blocks was 13.7-times greater than that in OWHTO opened to 14 mm (5,868 N vs. 427 N). Conclusion: The compressive strength of allogenous wedge bone blocks was sufficiently greater than the gap pressure in OWHTO. Therefore, allogenous wedge bone blocks can be inserted safely into the osteotomy site without a distractor.

• Journal of Korean Society of Forest Science
• /
• v.112 no.1
• /
• pp.83-92
• /
• 2023

This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R²) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.

• Journal of Korea Water Resources Association
• /
• v.56 no.4
• /
• pp.235-243
• /
• 2023

Due to the revision of the River Act and the enactment of the Act on the Investigation, Planning, and Management of Water Resources, a regular bed change survey has become mandatory and a system is being prepared such that local governments can manage water resources in a planned manner. Since the topography of a bed cannot be measured directly, it is indirectly measured via contact-type depth measurements such as level survey or using an echo sounder, which features a low spatial resolution and does not allow continuous surveying owing to constraints in data acquisition. Therefore, a depth measurement method using remote sensing-LiDAR or hyperspectral imaging-has recently been developed, which allows a wider area survey than the contact-type method as it acquires hyperspectral images from a lightweight hyperspectral sensor mounted on a frequently operating drone and by applying the optimal bandwidth ratio search algorithm to estimate the depth. In the existing hyperspectral remote sensing technique, specific physical quantities are analyzed after matching the hyperspectral image acquired by the drone's path to the image of a surface unit. Previous studies focus primarily on the application of this technology to measure the bathymetry of sandy rivers, whereas bed materials are rarely evaluated. In this study, the existing hyperspectral image-based water depth estimation technique is applied to rivers with vegetation, whereas spatio-temporal hyperspectral imaging and cross-sectional hyperspectral imaging are performed for two cases in the same area before and after vegetation is removed. The result shows that the water depth estimation in the absence of vegetation is more accurate, and in the presence of vegetation, the water depth is estimated by recognizing the height of vegetation as the bottom. In addition, highly accurate water depth estimation is achieved not only in conventional cross-sectional hyperspectral imaging, but also in spatio-temporal hyperspectral imaging. As such, the possibility of monitoring bed fluctuations (water depth fluctuation) using spatio-temporal hyperspectral imaging is confirmed.

• (The) Korean Journal of Educational Psychology
• /
• v.32 no.1
• /
• pp.99-130
• /
• 2018

The purpose of this study was to examine the longitudinal relationship between resilience and social support of school violence exposure types including school bullying, victimization, and dual experience. The study used data obtained from the third year (2012) of the Seoul Education Longitudinal Study of 1,137 elementary school students in grade 6 who reported experiencing school violence. The results of the autoregressive cross-lagged model are as follows. First, as a result of measuring the self-regression coefficients of resilience and social support of the youth exposed to school violence at 3 time points (2012, 2014, and 2016), it was found for all types of violence that resilience and social support at the previous time point showed a signigicant positive effect on the same variable at the next time point. Second, in the case of the cross-lagged effects of resilience and social support, the effect of previous social support on resilience at the next time point was statistically significant for the victimization group, but not for the bullying or dual experience groups. Third, considering the opposite path from resilience to social support, resilience at the previous time point had a significant influence on the social support at the next time point for both the bullying and victimization groups. This result is new and can be complementary to the cross-sectional studies so far using a longitudinal view. The results of this study suggest that the bullying and victimized students who are relatively more resilient are less likely to perceive social support than those who are not resilient. Finally, we discuss the longitudinal relationship between resilience and social support, the limitations of this study, and implications for future research.

• KDI Journal of Economic Policy
• /
• v.12 no.4
• /
• pp.21-46
• /
• 1990

This paper, a sequel to Yoo and Lee (1990), attempts to investigate the interindustry determinants of technical efficiency in Korea's manufacturing industries, and also to conduct an exploratory analysis on the stability of technical efficiency over time. The hypotheses set forth in this paper are most found in the existing literature on technical efficiency. They are, however, revised and shed a new light upon, whenever possible, to accommodate any Korea-specific conditions. The set of regressors used in the cross-sectional analysis are chosen and the hypotheses are posed in such a way that our result can be made comparable to those of similar studies conducted for the U.S. and Japan by Caves and Barton (1990) and Uekusa and Torii (1987), respectively. It is interesting to observe a certain degree of similarity as well as differentiation between the cross-section evidence on Korea's manufacturing industries and that on the U.S. and Japanese industries. As for the similarities, we can find positive and significant effects on technical efficiency of relative size of production and the extent of specialization in production, and negative and significant effect of the variations in capital-labor ratio within industries. The curvature influence of concentration ratio on technical efficiency is also confirmed in the Korean case. There are differences, too. We cannot find any significant effects of capital vintage, R&D and foreign competition on technical efficiency, all of which were shown to be robust determinants of technical efficiency in the U.S. case. We note, however, that the variables measuring capital vintage effect, R&D and the degree of foreign competition in Korean markets are suspected to suffer from serious measurement errors incurred in data collection and/or conversion of industrial classification system into the KSIC (Korea Standard Industrial Classification) system. Thus, we are reluctant to accept the findings on the effects of these variables as definitive conclusions on Korea's industrial organization. Another finding that interests us is that the cross-industry evidence becomes consistently strong when we use the efficiency estimates based on gross output instead of value added, which provides us with an ex post empirical criterion to choose an output measure between the two in estimating the production frontier. We also conduct exploratory analyses on the stability of the estimates of technical efficiency in Korea's manufacturing industries. Though the method of testing stability employed in this paper is never a complete one, we cannot find strong evidence that our efficiency estimates are stable over time. The outcome is both surprising and disappointing. We can also show that the instability of technical efficiency over time is partly explained by the way we constructed our measures of technical efficiency. To the extent that our efficiency estimates depend on the shape of the empirical distribution of plants in the input-output space, any movements of the production frontier over time are not reflected in the estimates, and possibilities exist of associating a higher level of technical efficiency with a downward movement of the production frontier over time, and so on. Thus, we find that efficiency measures that take into account not only the distributional changes, but also the shifts of the production frontier over time, increase the extent of stability, and are more appropriate for use in a dynamic context. The remaining portion of the instability of technical efficiency over time is not explained satisfactorily in this paper, and future research should address this question.

• Journal of Intelligence and Information Systems
• /
• v.22 no.3
• /
• pp.45-69
• /
• 2016

Recently, sentiment analysis using open Internet data is actively performed for various purposes. As online Internet communication channels become popular, companies try to capture public sentiment of them from online open information sources. This research is conducted for the purpose of analyzing pulbic sentiment of Korean Top-10 companies using a multi-categorical sentiment lexicon. Whereas existing researches related to public sentiment measurement based on big data approach classify sentiment into dimensions, this research classifies public sentiment into multiple categories. Dimensional sentiment structure has been commonly applied in sentiment analysis of various applications, because it is academically proven, and has a clear advantage of capturing degree of sentiment and interrelation of each dimension. However, the dimensional structure is not effective when measuring public sentiment because human sentiment is too complex to be divided into few dimensions. In addition, special training is needed for ordinary people to express their feeling into dimensional structure. People do not divide their sentiment into dimensions, nor do they need psychological training when they feel. People would not express their feeling in the way of dimensional structure like positive/negative or active/passive; rather they express theirs in the way of categorical sentiment like sadness, rage, happiness and so on. That is, categorial approach of sentiment analysis is more natural than dimensional approach. Accordingly, this research suggests multi-categorical sentiment structure as an alternative way to measure social sentiment from the point of the public. Multi-categorical sentiment structure classifies sentiments following the way that ordinary people do although there are possibility to contain some subjectiveness. In this research, nine categories: 'Sadness', 'Anger', 'Happiness', 'Disgust', 'Surprise', 'Fear', 'Interest', 'Boredom' and 'Pain' are used as multi-categorical sentiment structure. To capture public sentiment of Korean Top-10 companies, Internet news data of the companies are collected over the past 25 months from a representative Korean portal site. Based on the sentiment words extracted from previous researches, we have created a sentiment lexicon, and analyzed the frequency of the words coming up within the news data. The frequency of each sentiment category was calculated as a ratio out of the total sentiment words to make ranks of distributions. Sentiment comparison among top-4 companies, which are 'Samsung', 'Hyundai', 'SK', and 'LG', were separately visualized. As a next step, the research tested hypothesis to prove the usefulness of the multi-categorical sentiment lexicon. It tested how effective categorial sentiment can be used as relative comparison index in cross sectional and time series analysis. To test the effectiveness of the sentiment lexicon as cross sectional comparison index, pair-wise t-test and Duncan test were conducted. Two pairs of companies, 'Samsung' and 'Hanjin', 'SK' and 'Hanjin' were chosen to compare whether each categorical sentiment is significantly different in pair-wise t-test. Since category 'Sadness' has the largest vocabularies, it is chosen to figure out whether the subgroups of the companies are significantly different in Duncan test. It is proved that five sentiment categories of Samsung and Hanjin and four sentiment categories of SK and Hanjin are different significantly. In category 'Sadness', it has been figured out that there were six subgroups that are significantly different. To test the effectiveness of the sentiment lexicon as time series comparison index, 'nut rage' incident of Hanjin is selected as an example case. Term frequency of sentiment words of the month when the incident happened and term frequency of the one month before the event are compared. Sentiment categories was redivided into positive/negative sentiment, and it is tried to figure out whether the event actually has some negative impact on public sentiment of the company. The difference in each category was visualized, moreover the variation of word list of sentiment 'Rage' was shown to be more concrete. As a result, there was huge before-and-after difference of sentiment that ordinary people feel to the company. Both hypotheses have turned out to be statistically significant, and therefore sentiment analysis in business area using multi-categorical sentiment lexicons has persuasive power. This research implies that categorical sentiment analysis can be used as an alternative method to supplement dimensional sentiment analysis when figuring out public sentiment in business environment.