• Journal of Korea Entertainment Industry Association
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• v.14 no.3
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• pp.463-473
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• 2020

This study was conducted to provide basic data to find measures to alleviate the job stress of 119 Emergency Medical Technicians by identifying the mediating effect of resilience for life care in the relationship between stress coping and job stress of 119 Emergency Medical Technicians. The data for this study were collected from October 5, 2019, to October 31, 2019. The subject was 205 119 Emergency Medical Technicians working in 119 safety centers located in G Metropolitan City. The collected data were analyzed by independent t-test, ANOVA, Scheffé test, Pearson's correlation coefficients, hierarchical multiple regression analysis, and Sobel test using the SPSS Statistics 21.0 program. As a result oh the study, The mediation effect of resilience was not statistically significant in the relationship between stress coping of seeking social support type and job stress; the mediation effect of resilience was not statistically significant in the relationship between stress coping of seeking positive thinking type and job stress. but, resilience was revealed that resilience completely mediates the relationship between problem-solving type and job stress, and partially mediates the relationship between avoidance type and job stress. The measures to reduce the job stress of 119 Emergency Medical Technicians derived from the above results are as follows. First, among the 119 Emergency Medical Technicians, problem-solving stress coping type 119 Emergency Medical Technicians need to reduce job stress through resilience improvement program. Second, avoidance stress coping type 119 Emergency Medical Technicians should take part in education programs that can reduce job stress in parallel with resilience improvement program.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.641-650
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• 2020

Purpose The purpose of this study was to confirm the relationship between dietary self-efficacy, physical self-efficacy, and parental rearing attitudes considering obese children from the vulnerable class that utilized Community Child Care (CCC) centers. Methods In this study, sampling was conducted and 126 children from the vulnerable class who visited 11 regional children's centers located in A city, K province were chosen. The collected data was analyzed using t-test and ANOVA using the SPSS Window 22.0. The Pearson's Correlation coefficient was determined through multiple regression analysis. Results Obesity factors of vulnerable children included dietary efficacy, parents' parenting attitude, family type, single-parent family, parental obesity. Parental obesity held the greatest explanatory power of these variables, as 32% of the vulnerable children had at least one obese parent. Conclusion It is suggested that it is necessary to develop a nursing intervention strategy in which children and parents can participate in consideration of the environmental factors, such as parental attitude and family type of vulnerable children visiting Community Child Care (CCC) centers in the future.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.79-94
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• 2020

The purpose of this study is to analyze the difference in the effect of presence for the activation of virtual reality sports on participation satisfaction, to suggest continuous screen golf exercise participation, and to provide empirical and academic data for the development of the entire virtual reality sports market. To achieve this purpose, the survey period was from March 13 to May 13, 2020, with five researchers and assistants. The purpose of this study and the questionnaire were fully explained to consumers who experienced screen golf directly, and 247 questionnaires were used as the final valid sample by making a questionnaire with self-administration method. The data processing method was the statistical program Windows SPSS 18.0. First, factor analysis and reliability analysis, second, frequency analysis mean(M) and standard deviation(SD), third, Scheffe analysis among t-test and One-way ANOVA analysis, fourth, correlation analysis between variables and multiple regression analysis were conducted. The results of this study through these methods and procedures are as follows. First, there was a significant difference in participation satisfaction of presence in gender, and participation period of general characteristics. Second, there was a high difference in social presence, social self-reliance, and Ego, which are sub-factors of Presence, in social satisfaction, psychological satisfaction, and physical satisfaction. Third, the sub-factors of Presence, Social Presence, Social Self-Reliance, and Ego, were found to have a high effect on the sub-factors of Participation Satisfaction, Social Satisfaction, and Psychological Satisfaction.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• The Journal of the Korea Contents Association
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• v.8 no.10
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• pp.361-372
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• 2008

The purpose of this study was to verify the relationship between perfectionism and job stress of archery trainers. Participants of this study were 113 archery trainers who worked at the middle and high school's archery teams. Some of the archery trainers who participated in korea archery championship for junior in 2007 were selected using the purposive sampling method. The questionnaire was Multidimensional Perfectionism Scale developed by Hewitt and Flett(1991) which was revised by Lim(2005) into Korean and The Job Stress Scale developed by Jo(1998). Responses were made on 5-point and 7-point scale. The statistical methods for the analysis of this study were Pearson's correlation and multiple regression analysis. The results of this study were as follows. First, there was self perfectionism, person perfectionism, social perfectionism highly on the perfectionism of archery trainers and job condition stress, game stress, job load stress, support system stress, interpersonal relation stress highly on the job stress. Second, there was statistical significant relation between the job condition stress, game stress, job load stress and self perfectionism, between the game stress, job load stress and person perfectionism. Third, self perfectionism affect on job condition stress and self and person perfectionism affect on game stress, job load stress.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.32 no.1
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• pp.33-41
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• 1996

In order to obtain the most favourable classification system for fishing gears, the problems in the existing systems were investigated and a new system in which the fishing method was adopted as the criterion of classification and the kinds of fishing gears were obtained by exchanging the word method into gear in the fishing methods classified newly for eliminating the problems was established. The new system to which the actual gears are arranged is as follows ; (1)Harvesting gear \circled1Plucking gears : Clamp, Tong, Wrench, etc. \circled2Sweeping gears : Push net, Coral sweep net, etc. \circled3Dredging gears : Hand dredge net, Boat dredge net, etc. (2)Sticking gears \circled1Shot sticking gears : Spear, Sharp plummet, Harpoon, etc. \circled2Pulled sticking gears : Gaff, Comb, Rake, Hook harrow, Jerking hook, etc. \circled3Left sticking gears : Rip - hook set line. (3)Angling gears \circled1Jerky angling gears (a)Single - jerky angling gears : Hand line, Pole line, etc. (b)Multiple - jerky angling gears : squid hook. \circled2Idly angling gears (a)Set angling gears : Set long line. (b)Drifted angling gears : Drift long line, Drift vertical line, etc. \circled3Dragged angling gears : Troll line. (4)Shelter gears : Eel tube, Webfoot - octopus pot, Octopus pot, etc. (5)Attracting gears : Fishing basket. (6)Cutoff gears : Wall, Screen net, Window net, etc. (7)Guiding gears \circled1Horizontally guiding gears : Triangular set net, Elliptic set net, Rectangular set net, Fish weir, etc. \circled2Vertically guiding gears : Pound net. \circled3Deeply guiding gears : Funnel net. (8)Receiving gears \circled1Jumping - fish receiving gears : Fish - receiving scoop net, Fish - receiving raft, etc. \circled2Drifting - fish receiving gears (a)Set drifting - fish receiving gears : Bamboo screen, Pillar stow net, Long stow net, etc. (b)Movable drifting - fish receiving gears : Stow net. (9)Bagging gears \circled1Drag - bagging gears (a)Bottom - drag bagging gears : Bottom otter trawl, Bottom beam trawl, Bottom pair trawl, etc. (b)Midwater - drag gagging gears : Midwater otter trawl, Midwater pair trawl, etc. (c)Surface - drag gagging gears : Anchovy drag net. \circled2Seine - bagging gears (a)Beach - seine bagging gears : Skimming scoop net, Beach seine, etc. (b)Boat - seine bagging gears : Boat seine, Danish seine, etc. \circled3Drive - bagging gears : Drive - in dustpan net, Inner drive - in net, etc. (10)Surrounding gears \circled1Incomplete surrounding gears : Lampara net, Ring net, etc. \circled2Complete surrounding gears : Purse seine, Round haul net, etc. (11)Covering gears \circled1Drop - type covering gears : Wooden cover, Lantern net, etc. \circled2Spread - type covering gears : Cast net. (12)Lifting gears \circled1Wait - lifting gears : Scoop net, Scrape net, etc. \circled2Gatherable lifting gears : Saury lift net, Anchovy lift net, etc. (13)Adherent gears \circled1Gilling gears (a)Set gilling gears : Bottom gill net, Floating gill net. (b)Drifted gilling gears : Drift gill net. (c)Encircled gilling gears : Encircled gill net. (d)Seine - gilling gears : Seining gill net. (e)Dragged gilling gears : Dragged gill net. \circled2Tangling gears (a)Set tangling gears : Double trammel net, Triple trammel net, etc. (b)Encircled tangling gears : Encircled tangle net. (c)Dragged tangling gears : Dragged tangle net. \circled3Restrainting gears (a)Drifted restrainting gears : Pocket net(Gen - type net). (b)Dragged restrainting gears : Dragged pocket net. (14)Sucking gears : Fish pumps.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.179-187
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• 2018

This study purpose is to improve athletes by investigating the relation between the leadership behavior type of athletes and athlete satisfaction and exercise flow. The sampling method was non-probabilistic sampling method. The number of questionnaires was 381 for analyzing the data. SPSS/PC+ Window 21.0 version statistical program were used for analyzing the questionnaire answers. Frequency analysis, factor analysis, correlation analysis and multiple regression analysis were used. The study results are as follows. First, there were positive correlations between leadership behavior type of athletes and athlete satisfaction and exercise flow, but not between authoritative behavior of leader behavior type and exercise flow. Second, the effect of leadership behavior type of athletes on satisfaction of athletes was positive on social interaction related with training, instruction, and social support, on task execution related with training and instruction, and on coaching related with training, instruction, and positive feedback. Third, the effect of leadership behavior type of athletes on flow of exercise was positive on cognitive commitment related with training, instructions and positive feedback, and on behavioral commitment related with training, instructions, positive feedback, and social interaction. So, athletes will be able to perform good exercise skills if they come to the game in flowing exercise satisfaction and exercise.

• Asian Journal of Turfgrass Science
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• v.20 no.1
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• pp.11-23
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• 2006

This study was carried out to propose low types of green speed expectation models for fast putting green management by changing mowing height($4.0{\sim}2.5$ mm) and timing of rolling, dew removal and dew removal+rolling. Ball roll distance data were taken from the creeping bentgrass(Agrostis palustris Huds. 'Penncross') practice green of east course at the Lakeside C.C. in October 18, 2001 and May 25, 2002. Data were subjected to multi-regression analysis using Statistical Package for the Social Science. Among four types of green speed expectation models, the best multiple-regression equation for fast green management was as follows; $Y_4=4.171-0.225{\cdot}X_1-0.038{\cdot}X_2$ (where, $Y_4$ : green speed(m) after single dew removal+single rolling, $X_1$ : mowing height($4.0{\sim}2.5,\;X_2$ : passage of time ($0{\sim}8$ h.)). The equation[single dew removal by using sponge roller $\rightarrow$ single mowing at 3.0 mm height or less $\rightarrow$ single rolling] explained to provide fast green over 3.2 m (Stimpmeter readings required for USGA championship play) until the end of first round. Therefore, this cultural practice system was believed to provide fast putting green condition for professional golf tournament

• Journal of dental hygiene science
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• v.11 no.5
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• pp.431-436
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• 2011

The aim of this study was to compare the effects of the short-term use of the desensitizing dentifrices marketed in Korea in vitro. Fifty human dentine specimens were wet ground with silicone carbide paper and etched with 6% citric acid for 90 seconds to allow complete opening of the dentinal tubule. Ten specimens from each group were brushed for 50 and 150 strokes with a V8 Cross Brushing Machine(Sabri Co., U. S. A). All the specimens were evaluated by SEM(${\times}3000$). The degree of occlusion of the dentinal tubules was quantified using an image analyzer. The results were analyzed by one-way ANOVA and Tukey's multiple comparisons using Window SPSS. The dentifrices containing nano-carbonate apatite, potassium nitrate and hydroxyapatite showed significantly higher occlusion effects than the other dentifrices after toothbrushing for 50 strokes(p<0.05). The Sensodyne freshmint$^{(R)}$dentifrice showed 34% fewer open tubular areas compared with the Sensodyne original$^{(R)}$dentifrice for 50 strokes. According to the short-term use of desensitizing dentifrices, the dentifrices containing nano-carbonate apatite, potassium nitrate and hydroxyapatite were most effective in occluding the dentinal tubules.

• Journal of dental hygiene science
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• v.8 no.1
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• pp.35-42
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• 2008

This survey was compared and analyzed about the primary factor that dental office's working environment effect on physical subjective symptom and based on self-filling survey, 656 dental hygienists on July through August 2006, and analyzed using descriptive statics, ANOVA and Multiple Regression Analysis. The result of satisfaction degree of hospital working environment was pretty low about office air condition. Most people have complained that office's air quality makes it difficult to their work and mentioned that they were sore and dull all over the back, shoulder, and neck. The odor is major factor to be satisfied with office environment. Proper ventilates the way open the window more often was essential to maintain fresh indoor air quality and keep the extraction materials by separator and sealing tightly for remove the odor. Other factors were temperature, lighting fixture, ventilation facilities, and freshness of air. Dental hygienist was unsatisfied with hospital air condition and this polluted air condition was the cause of physical subjective symptom in work place. Furthermore, this research would be applied for improvement of working environment by decreasing of indoor air pollution.