• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.1-25
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• 2008

Ⅰ. Introduction Retailers in the 21st century are being told that future retailers are those who can execute seamless multi-channel access. The reason is that retailers should be where shoppers want them, when they want them anytime, anywhere and in multiple formats. Multi-channel access is considered one of the top 10 trends of all business in the next decade (Patricia T. Warrington, et al., 2007) And most firms use both direct and indirect channels in their markets. Given this trend, we need to evaluate a channel equity more systematically than before as this issue is expected to get more attention to consumers as well as to brand managers. Consumers are becoming very much confused concerning the choice of place where they shop for durable goods as there are at least 6-7 retail options. On the other hand, manufacturers have to deal with category killers, their dealers network, Internet shopping malls, and other avenue of distribution channels and they hope their retail channel behave like extensions of their own companies. They would like their products to be foremost in the retailer's mind-the first to be proposed and effectively communicated to potential customers. To enable this hope to come reality, they should know each channel's advantages and disadvantages from consumer perspectives. In addition, customer satisfaction is the key determinant of retail customer loyalty. However, there are only a few researches regarding the effects of shopping satisfaction and perceptions on consumers' channel choices and channels. The purpose of this study was to assess Korean consumers' channel choice and satisfaction towards channels they prefer to use in the case of electronic goods shopping. Korean electronic goods retail market is one of good example of multi-channel shopping environments. As the Korea retail market has been undergoing significant structural changes since it had opened to global retailers in 1996, new formats such as hypermarkets, Internet shopping malls and category killers have arrived for the last decade. Korean electronic goods shoppers have seven major channels : (1)category killers (2) hypermarket (3) manufacturer dealer shop (4) Internet shopping malls (5) department store (6) TV home-shopping (7) speciality shopping arcade. Korean retail sector has been modernized with amazing speed for the last decade. Overall summary of major retail channels is as follows: Hypermarket has been number 1 retailer type in sales volume from 2003 ; non-store retailing has been number 2 from 2007 ; department store is now number 3 ; small scale category killers are growing rapidly in the area of electronics and office products in particular. We try to evaluate each channel's equity using a consumer survey. The survey was done by telephone interview with 1000 housewife who lives nationwide. Sampling was done according to 2005 national census and average interview time was 10 to 15 minutes. Ⅱ. Research Summary We have found that seven major retail channels compete with each other within Korean consumers' minds in terms of price and service. Each channel seem to have its unique selling points. Department stores were perceived as the best electronic goods shopping destinations due to after service. Internet shopping malls were perceived as the convenient channel owing to price checking. Category killers and hypermarkets were more attractive in both price merits and location conveniences. On the other hand, manufacturers dealer networks were pulling customers mainly by location and after service. Category killers and hypermarkets were most beloved retail channel for Korean consumers. However category killers compete mainly with department stores and shopping arcades while hypermarkets tend to compete with Internet and TV home shopping channels. Regarding channel satisfaction, the top 3 channels were service-driven retailers: department stores (4.27); dealer shop (4.21); and Internet shopping malls (4.21). Speciality shopping arcade(3.98) were the least satisfied channels among Korean consumers. Ⅲ. Implications We try to identify the whole picture of multi-channel retail shopping environments and its implications in the context of Korean electronic goods. From manufacturers' perspectives, multi-channel may cause channel conflicts. Furthermore, inter-channel competition draws much more attention as hypermarkets and category killers have grown rapidly in recent years. At the same time, from consumers' perspectives, 'buy where' is becoming an important buying decision as it would decide the level of shopping satisfaction. We need to develop the concept of 'channel equity' to manage multi-channel distribution effectively. Firms should measure and monitor their prime channel equity in regular basis to maximize their channel potentials. Prototype channel equity positioning map has been developed as follows. We expect more studies to develop the concept of 'channel equity' in the future.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.6
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• pp.737-747
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• 1999

To estimate biomass and distribution of the Antarctic krill (Euphausia superba), hydroacoustic survey was conducted on board of R/V Yuzhmorgeologiya, which was chartered by Korea Antarctic Research Program (KARP) group from 18 to 21 December 1998, in the northern part of the South Shetland Islands, Antarctic Ocean, The scientific echo sounder (towing body type) used was EK- 500 (SIMRAD, Norway) with echo integrator (BI-500) at 38 kHz frequency and recorded mean backscattering cross-section coefficient (SA) per 1 $mile^2$ of sea surface. Also, Bongo net sampling was carried out to determine the size of krill and CTD (Conductivity, Temperature and Depth) casting to understand physical structure. Water column was divided into 5 layers (22$\~$65 m, 65$\~$115 m, l15$\~$65 m, 165$\~$215 m and 215$\~$315 m) to know vertical distribution of krill biomass. The standard length of krill collected was between 30 mm and 51 mm, and adult krill had single mode (41 mm). Maximum horizontal length of krill patch was about 35 nautical mile and vertical thickness was about 275 m. High density of krill was appeared in frontal area between Circumpolar Deep Water (>$1^{\circ}C$) and very low temperature water mass (< $-0.5^{\circ}C$) that originate from Weddell Sea. According to the results calculated using target strength equation, krill density was totally higher in continental slope and open water areas than in coastal area. In the study area, krill seems to distribute in depth; density was low at first layer ($\={\rho}=17.0\;g/m^2$) and higher at fourth layer ($\={\rho}=40.19\;g/m^2$). The estimated krill biomass at total survey area and water column was about 2.77 million metric ion ($\={\rho}=151.0\;g/m^2$) and coefficient of valiance ( CV, $\%$) was 19.92. The proportions and biomass of krill biomass at each layer were as follows; layer 1 ($11.3\%$, 0.31 million metric ton, CV=16.24), layer 2 ($13.3\%$, 0.37 million metric ton, CV=34.91), layer 3 ($23.7\%$, 0.66 million metric ton, CV=41.5), layer 4 ($26.6\%$, 0.74 million metric ton, CV=27.84) and layer 5 ($25\%$, 0.69 million metric ton, CV= 26.83).

• Journal of agricultural medicine and community health
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• v.30 no.2
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• pp.167-182
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• 2005

Objectives: This study was performed to investigate the prevalence of knee osteoarthritis according to the criteria of diagnosing knee osteoarthritis in rural women and the factors related with this disease. Methods: The data obtained from 200 women older than 40 years of age residing in 5 Ri's in Goryeong-gun. Gyeongsanbuk-do by random cluster sampling from September to October 2002. Knee osteoarthritis was determined positive according to the Kellgren and Lawrence classification and knee pain. Results: Among these subjects, 71.0% showed more than grade 2 in radiologic finding and the rate of knee pain according to the survey was 67.0%. The rate of subjects meeting the criteria of knee osteoarthritis was 54.0%. According to univariate analysis, the prevalence of knee osteoarthritis increased with age and those farming people and people working in household industry was significantly high at 58.9% compared with others. The prevalence of knee osteoarthritis showed a significant relationship with the family history and past history of knee injury and knee surgery(p<0.01), and diabetes mellitus(p<0.05). The score of ADL was significantly different in the subjects with knee osteoarthritis compared with normal group(p<0.05). When the presence of knee osteoarthritis and the period of the life style of seating down on the floor were compared, a significant difference was present between the osteoarthritis group and normal group. As for metabolic factors, the blood sugar level, bone density, and body mass index(BMI) were significantly different in the osteoarthritis group compared with normal group. When multiple logistic regression analysis was performed with the presence of knee osteoarthritis as the dependent variable, the prevalence of knee osteoarthritis was significantly affected by older age, subjects farming or working in household industry, the history of knee injury, the history of surgery, higher blood sugar level, and higher BMI. Conclusions: These subjects need an intervention through self-care programs such as exercise for preventing osteoarthritis, weight control programs, other exercise programs strengthening knee joints, and guidelines when working in vinyl houses.

• Journal of Korean Society of Forest Science
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• v.74 no.1
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• pp.67-81
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• 1986

To investigate the stand structure of the stocked broad-leaved forests in Korea, 1,000 plots, allocated by systematic sampling method, were interpreted on the aerial photographs accompanied with ground survey. Total area of the stocked broad-leaved forests except Jeju island was 818,286ha and the percentage to total forest area was 12.7%. Total stock volume of the stocked broad-leaved forests was $38,890,779m^3$ and the percentage to total stocked forest volume was 27.4%. Mean number of trees per ha was 947 trees/ha, basal area was $11.17m^3/ha$, DBH was 11.30cm, tree height was 7.65m, stock volume was $44.96m^3/ha$, and current annual volume increment was $3.64m^3/ha$ in total land. The 64.7, 79.8 and 52.7 percent of the stocked broad-leaved forest area were distributed at elevations of 300-900m, in slope degree of above 25, and in northern aspect, respectively. Standfactors were apt to get better with the increase of distance from the car road way and the village, and with the increase of elevation belt.

• Journal of the Korean Society of School Health
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• v.11 no.2
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• pp.171-187
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• 1998

In recent years, adolescent issues including smoking, drinking, drug abuse, juvenile delinquency, deviant sexual behavior, mental health problems, high suicide rate, juvenile delinquency and absence without due notice, etc are emerging as serious social problems and the debate on these controversial issues is heating up. The previous studies on adolescent health behavior and social juvenile delinquency such as run-away from home and absence without due notice have been conducted mostly by cause analysis utilizing social demographic factors or biological factors. In other words, the main factors analyzed were demographic and economic factors or parent's educational level, etc, which were the fixed environmental ones that were unable to cause the change in the health behavior. Accordingly, the purpose of this study is to analyze factors which are changeable and fixable among the factors influencing the adolescent's health behavior and misconducts and, eventually influencing factors which can be used as the basis to establish health policies and health promotion program to reduce the health risk behavior and misconducts of adolescents. The study subjects were selected by dividing senior high school student in Seoul by region and through random sampling. The 890 subjects were selected from 10 schools including the preparatory school, vocational schools and institutional schools. The duration of the study was for July 1-5, 1997 for the first survey and the second one, for August 25-September 10. Regarding the analysis method, the SAS program was used. The adoptablity of theoretical model was tested through covariance structural analysis utilizing PC-LISREL 8.12 Program. The major findings of the study are as follows: As a result of establishing the model of factors influencing health behavior and juvenile delinquency, in case of male students as the health behavior self-efficacy, education level of fathers, economic level, self-control and the health interest of parent were higher, students were more likely to practice the health promoting behavior. Juvenile delinquency and health risk behavior were prevalent among those with the less shyness, the lower health behavior self-efficacy, lower self-control, lower self-assertiveness, lower economic level. The self-control was the most powerful factor. In case of female students, those with higher health behavior self-efficacy were more likely to practice the health promoting behavior whereas those with lower health behavior self-efficacy, lower self-control, lower self- assertiveness, less shyness were more likely to practice health risk behavior and juvenile delinquency. In case of prep schools, those with higher health behavior self-efficacy and better perceived health status were more likely to practice the health promoting behavior while those with less shyness, lower health behavior self-efficacy and lower academic achievement were more likely to engage in health risk behavior and juvenile delinquency. In case of vocational schools, as health behavior self-efficacy and economic level were higher, the practice rate of health promoting behavior was higher. As the self-control, shyness, self-assertiveness, health behavior self-efficacy were lower, the rate of health risk behavior and juvenile delinquency were higher. In case of social institutional schools, as, the health behavior self-efficacy, social support and economic level, health interest of parents were higher, the rate of health promoting behavior were higher. As the self-control, shyness, self-assertiveness, health behavior self-efficacy and social support were lower, the rate of health risk behavior and juvenile delinquency were higher. So the health promoting behavior was positively related to the health behavior self-efficacy, health interest of parents, social support, education level of fathers, level of perceived health status, economic level. The health risk behavior and juvenile delinquency were higher with the lower health behavior self-efficacy, self-control and self-assertiveness, lower health locus control, less shyness and loneliness, lower economic level and academic achievement. In conclusion, the health risk behavior and juvenile delinquency can be reduced by enhancing self-control, self-assertiveness, health behavior self-efficacy and social support. According to the final model drawn by connecting health behavior and juvenile delinquency, the reduction of health risk behavior can greatly contribute to decreasing social juvenile delinquency as the process of juvenile delinquency was extended from common behaviors to problem behaviors and further into juvenile delinquency.

• Journal of dental hygiene science
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• v.12 no.2
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• pp.131-137
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• 2012

The purpose of this study was to examine the sociopsychological stress of dental hygiene students, any possible gaps among them according to their general characteristics and the most influential factor for their stress. The subjects in this study were the dental hygiene students who were selected by convenience sampling from three different colleges. After a survey was conducted for about a month between March and April, 2011, the answer sheets from 561 students were analyzed. As for the sociopsychological stress of the dental hygiene students, economic stress was the heaviest sociopsychological stress that the students suffered(3.17). Regarding differences in each stressor according to general characteristics, they were more stressed out about their economy, families, interpersonal relationships and studies when they had a less conversation with their families. And they had more stress about their economy, families, interpersonal relationships and studies when they found themselves to be more unhealthy. The gaps between them and the others were statistically significant. As a result of analyzing the influential factors for their stress, they had more stress when they had a less conversation with their families(p<0.001) and when they found themselves not to be in good health(p<0.001). It's required to seek ways for dental hygiene students to cope with their stress properly, and the development of stress management programs is necessary. Besides, education and training should be provided for them to regulate their own stress successfully.

• Korean Journal of Environment and Ecology
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• v.34 no.5
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• pp.454-465
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• 2020

This study measured the present number of encounters and established the evaluation criterion for the allowable number of encounters in the Seoseokdae summit area (SSA) of Mudeungsan National Park to examine managerial conditions of the number of visitors to the Seoseokdae trail section (STS). Data were obtained from a questionnaire survey of 263 visitors to STS selected through convenient sampling during June 2019. The average number of encounters in SSA was 18.7. Most of the respondents (95.4%) encountered fewer than 30 other visitors. The average maximum number of simultaneous users (AMNSU, measured at 15-minute intervals) in SSA was 13.4 persons (range: 3~31 persons). The AMNSU by the hour was the highest with 21.0 persons at 13-14, followed by 19.8 persons at 11-12, 15.5 persons at 14-15, 15.3 persons at 12-13, 12.3 persons at 10-11, and 10.8 persons at 8-9. Acceptable encounter number (AEN) developed by long-question format (LQF) was 59.2 persons, and that by short-question format (SQF) was 55.1 persons. AEN of the respondents who preferred "near-nature experience" at 27.5 persons was fewer than those who preferred "resort/tourism area like experience" at 46.6 persons. The present number of encounters and AMNUS (range: 3~31 persons) in SSA were fewer than AENs derived from LQF (59.2 persons) and SQF (55.1 persons). Eighty-three percent of the respondents preferred "near-nature experience," while only 10.5% of the respondents preferred "resort/tourism area like experience." 78.4% of the respondents did not perceive that SSA was crowded. The absolute majority of the respondents (92.3%) answered higher personal AEN than the perceived encounter numbers (PEN). The gaps between the personal AEN and the PEN were negatively correlated with perceived crowding.

• Research in Community and Public Health Nursing
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• v.9 no.2
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• pp.502-517
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• 1998

This research intends to survey family environment, health behavior and health status of the students in urban-rural elementary schools and analyze those factors comparatively, and use the result as basic material for school health teacher to teach health education in connection with family and regional areas. It also intends to improve a pupil's self-abilitiy in health care. The subjects involve 2,774 students of urban elementary schools and 583 student in rural ones, who were selected by means of a multi -stage probability sampling. Using the questionnaire and school documents, we collected data on family environment, health behavior and health status for 19 days. Feb. 2nd 1998 through Feb. 20th 1998. The R -form of Family Environment Scale (Moos, 1974) was used in the analysis of family environment(Cronbach's Alpha =0.80). Questionnaires of Health Behavior in School-aged children used by the WHO in Europe(Aaro et al., 1986) and the ones developed by the Health Promotion Committee of the Western Pacific(WHO, 1995)(adapted by long Young-suk and Moon Young-hee(1996)) were used in the analysis of health behavior, as well documents on absences due to sickness, school health room-visits, levels of physical strength, height, weight and degree of obesity were used to determine health status. In next step, We used them with an $X^2$-test, t-test, Odds Ratio, and a 95% Confidence Interval. 1. In two dimensions of three, family-relationship (t=3.41, p=0.001) and system -maintenances(t= 2.41, p=0.0l6) the mean score of urban children were significantly higher than those of rural ones. In the personal development dimension however, there was little significant difference. Assorting family environment into 10 sub-fields and analyzing them, we recognized that urban children were superior to rural children in the sub-fields of expressiveness (t =3.47, p=0.001), conflict (t=0.48, p=0.001), active-recreational orientation (t = 1.97, p=0.049) and organization (t=4.33, p=0.000). 2. Referring to the Odds Ratios of urban-rural children's health behaviors, urban children set up more desirable behavior than rural children wear ing safety belts (Odds Ratio =0.32, p=0.000), washing hands after meals(Odds Ratio = 0.43, p= 0.000), washing hands after excreting (Odds Ratio = 0.39, p=O.OOO), washing hands after coming - home ( Odds Ratio = 0.75, p = 0.003), brushing teeth before sleeping(Odds Ratio =0.45, p=0.000), brushing teeth more than once a day (Odds Ratio =0.73, p=0.0l2), drinking boiled water (Odds Ratio = 0.49, p=0.000), collecting garbage at home(Odds Ratio=0.31, p=0.000) and in the school(Odds Ratio =0. 67, p=0.000). All these led to significant differences. As to taking milk(Odds Ratio = 1.50, p=0.000), taking care of eyesight(Odds Ratio=1.41, p=0.001) and getting physical exercise in(Odds Ratio = 1.33, p=0.0l9) and outside the school(Odds Ratio = 1.32, p=0.005), rural children had more desirable behavior which also revealed a significant difference. There was little significant difference in smoking, but the smoking rate of rural children(5.5%) was larger than that of urban children(3.9%). 3. Health status was analyzed in terms of absences, school health room-visits, levels of physical strength, and the degree of obesity, height and weight. Considering Odds Ratios of the health status of urban-rural children, the health status of rural children was significantly better than that of the urban ones in the level of physical strength(t=1.51, p=0.000) and the degree of obesity(t=1.84, p=0.000). The mean height of urban children ($150.4{\pm}7.5cm$) is taller than that of their counterparts($149.5{\pm}7.9$), which revealed a significant difference (t =2.47, p=0.0l4). The mean weight of urban children($42.9{\pm}8.6kg$) is larger than that of their counterparts($41.8{\pm}9.0kg$), which was also a significant difference(t=2.81, p=0.005). Considering the results above, we can recognize that there are significant differences in family environment, health behavior, and health status in urban-rural children. These results also suggestion ideas for health education. What we would suggest for the health program of elementary schools is that school health teachers should play an active role in promoting the need and importance of health education, develop the appropriate programs which correspond to the regional characteristics, and incorporate them into schools to improve children's ability to manage their own health management.

• Tuberculosis and Respiratory Diseases
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• v.58 no.3
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• pp.230-242
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• 2005

Background : Spirometry should be compared with the normal predictive values obtained from the same population using the same procedures, because different ethnicity and different procedures are known to influence the spirometry results. This study was performed to obtain the normal predictive values of the Forced Vital Capacity(FVC), Forced Expiratory Volume in 1 Second($FEV_1$), Forced Expiratory Volume in 6 Seconds($FEV_6$), and $FEV_1/FVC$ for a representative Korean population. Methods : Based on the 2000 Population Census of the National Statistical Office of Korea, stratified random sampling was carried out to obtain representative samples of the Korean population. This study was performed as a part of the National Health and Nutrition Survey of Korea in 2001. The lung function was measured using the standardized methods and protocols recommended by the American Thoracic Society. Among those 4,816 subjects who had performed spirometry performed, there was a total of 1,212 nonsmokers (206 males and 1,006 females) with no significant history of respiratory diseases and symptoms, with clear chest X-rays, and with no significant exposure to respiratory hazards subjects. Their residence and age distribution was representative of the whole nation. Mixed effect models were examined based on the Akaike's information criteria in statistical analysis, and those variables common to both genders were analyzed by regression analysis to obtain the final equations. Results : The variables affecting the normal predicted values of the FVC and $FEV_6$ for males and females were $age^2$, height, and weight. The variables affecting the normal predicted values of the $FEV_1$ for males and females were $age^2$, and height. The variables affecting the normal predicted values of the $FEV_1/FVC$ for male and female were age and height. Conclusion : The predicted values of the FVC and $FEV_1$ was higher in this study than in other Korean or foreign studies, even though the difference was < 10%. When compared with those predicted values for Caucasian populations, the study results were actually comparable or higher, which might be due to the stricter criteria of the normal population and the systemic quality controls applied to the whole study procedures together with the rapid physical growth of the younger generations in Korea.