• Journal of Korean Physical Therapy Science
• /
• v.13 no.4
• /
• pp.43-62
• /
• 2006

The survey was conducted with participation of the 289 handicapped persons residing at the rural area OOeup-gun in Kyungbook for the period of March 2 - May 31, 2006, to study the nature in general of the handicapped and the boundaries of their need. For the nature in general of the handicapped, the study was done by gender iscrimination, age, marital status, religion, educational level, occupation, monthly income, disability cause, disabled duration, disability type, disability level. For the boundaries of their need, the study was done by demand of financial support, educational demand, demand of voluntary workers, need of rehabilitation and medical treatment, job training, improvement of living conditions, or so. Using the Win.SPSS program, we made a frequency analysis and conclusions on the nature in general of the handicapped and the boundaries of their need on a 2-test. Conclusions are : 1. Nature in general of the handicapped The existence of the handicapped shows high at the age over 51 (71.6%), male-handicapped (65.1%), primary school graduates (62.9%), farming engaging (65.2%), monthly income less than one million Won (80.5%), cause by disease (53.8%), duration more than 10 years (61.6%), disability at level 3 (39.8%), extremity disability (66.4%). 2. Correlation of nature in general with demand of the handicapped a. In demanding the financial support, support for helper’s compensation shows high (p<0.05). In demanding the necessity of voluntary workers, the male-handicapped appears high during the absence of family assistance and the female-handicapped appears differently per week and also appears high during the absence of family assistance (p<0.05). b. In educational demand of the handicapped by their age, the age below 30 demands technical-job training and the age over 31 demands medical education for health care (p<0.01). c. In demanding the financial support by educational level, support for living cost shows high (p<0.05). d. In demanding improvement of living conditions by postnatal cause of disability, improvement of house structure shows high (p<0.05). e. In demanding assistance of voluntary workers by disabled duration, "No Need" shows high in the disabled duration more than 4 years (p<0.05). f. In demanding rehabilitation and medical treatment by disability type, home-visiting treatment, oriental medical treatment and physical therapy show high (p<0.001). g. In educational demand by disability level, medical education for health care shows high (p<0.01).

• The Journal of the Korea Contents Association
• /
• v.16 no.3
• /
• pp.305-318
• /
• 2016

Perceptions of organizational politics(POPs) have stress-based effect as job demand and lead to employee's negative attitudes and behaviors. According to job demand resource model, burnout develops when high job demand deplete employee's resources, which lead employees to low levels of motivation and high levels of cynicism and frustration. Currently, in studying the relationship between POPs and burnout there is a lack of researches on certain settings and conditions. The present study examined a model in which relationship between POPs and burnout was mediated by psychological need satisfaction. And also, this study tested moderating role of psychological capital between POPs and need satisfaction. A total of 220 employees in telco and electronic manufacturing company in South Korea participated in this study. The result of this study showed that need satisfaction works as mediating variable between POPs and burnout and psychological capital had moderating effect between POPs and need satisfaction. This study proposes a new framework of POPs by examining linking mechanism of need satisfaction and psychological capital. The results of this study provide practical insight to HR practitioners and business leaders.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.18 no.3
• /
• pp.310-316
• /
• 2011

Purpose: In the present study, the difference in patients' nursing demands and nursing performance as perceived by the patients was examined. Methods: The participants were 272 patients on maintenance hemodialysis at five university hospitals. Nursing need and nursing performance were measured using the tool developed by Lee for this study. Results: The mean score for nursing demand was 3.35 points out of 4. The scores were higher for participants with middle school graduation or less, those not professing religion, and those whose medical insurance was of the medicaid type. The mean score for perceived nursing performance was 3.22 points out of 4. Nursing performance as perceived by hemodialysis patients was lower than nursing demand for 22 of 28 items. The item with the largest difference between nursing performance and nursing demand was 'Give a pain-free injection', followed by 'Explain about insurance benefits and supports' and 'Maintain quiet environment in the hemodialysis unit enabling rest during hemodialysis'. Conclusion: The results show that nursing performance as perceived by hemodialysis patients was lower than nursing demand. This result indicates a need to develop appropriate strategies to enhance nursing performance, especially for items that showed low nursing performance.

• Korean Journal of Childcare and Education
• /
• v.12 no.6
• /
• pp.123-137
• /
• 2016

The purpose of this study was to forecast demand of childcare teachers based ion four different scenarios. In order to, the demand for childcare teachers from 2015 to 2024 were forecasted using time series techniques with data on the number of childcare teachers from 2003 to 2014. Results were as followings. Firstly, the demand for childcare teachers was expected to increase until 2019, but after 2020 steadily decreased in terms of scenario 1(child teacher ratio regulation). According to scenario 2(child teacher ratio based on 17 cities and provinces), the demand for childcare teachers was expected to need 440 teachers more until 2016. Then, according to scenario 3(two teachers each class), Scenario 4-1(one teacher and one staff each 2 toddler class and 3 older class) and scenario 4-2(one teacher and one staff each class), the demand of childcare teachers and staffs were estimated. These results implicated that childcare teachers and staffs supply policy would be established according to forecast demand.

• International Journal of Computer Science & Network Security
• /
• v.23 no.9
• /
• pp.1-7
• /
• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.210-216
• /
• 2023

Demand prediction is an essential component of any business or supply chain. Large retailers need to keep track of tens of millions of items flows each day to ensure smooth operations and strong margins. The demand prediction is in the epicenter of this planning tornado. For business processes in retail companies that deal with a variety of products with short shelf life and foodstuffs, forecast accuracy is of the utmost importance due to the shifting demand pattern, which is impacted by an environment of dynamic and fast response. All sectors strive to produce the ideal quantity of goods at the ideal time, but for retailers, this issue is especially crucial as they also need to effectively manage perishable inventories. In light of this, this research aims to show how Machine Learning approaches can help with demand forecasting in retail and future sales predictions. This will be done in two steps. One by using historic data and another by using open data of weather conditions, fuel, Consumer Price Index (CPI), holidays, any specific events in that area etc. Several machine learning algorithms were applied and compared using the r-squared and mean absolute percentage error (MAPE) assessment metrics. The suggested method improves the effectiveness and quality of feature selection while using a small number of well-chosen features to increase demand prediction accuracy. The model is tested with a one-year weekly dataset after being trained with a two-year weekly dataset. The results show that the suggested expanded feature selection approach provides a very good MAPE range, a very respectable and encouraging value for anticipating retail demand in retail systems.

• Journal of Electrical Engineering and Technology
• /
• v.12 no.1
• /
• pp.1-10
• /
• 2017

With the current global need for eco-friendly energies, the large scale use of Electric Vehicles (EVs) is predicted. However, the need to frequently charge EVs to an electrical power system involves risks such as rapid increase of demand power. Therefore, in this paper, we propose a practical smart EV charging scheme considering a Time-of-Use (ToU) price to prevent the rapid increase of demand power and provide load leveling function. For a more practical analysis, we conduct simulations based on the actual distribution system and driving patterns in the Republic of Korea. Results show that the proposed method provides a proper load leveling function while preventing a rapid increase of demand power of the system.

• Journal of the Korean Society of School Health
• /
• v.19 no.2
• /
• pp.1-12
• /
• 2006

Purpose： The purpose of this study was to investigate the current conditions and to analysis the needs of health education contents in school nurses and elementary school children. Methods : The survey was conducted through the questionnaire with school nurses and students. Subjects were 60 school nurse and 1483 elementary school children. Data was collected based on the from Mar to Apr. 2004. Finally, data was analyzed using mean, SD, and t-test. Results : The students need the health education related safety, oral hygiene, visual promotion, scoliosis prevention, cyber addiction prevention, anti-bullying and school violence prevention. School nurses suggest the contents of health education such as sex education, drug misuse and overuse prevention. There was also a difference in the need of health education among the school nurse and students. Conclusion：I suggest that health education should be conducted taking students' demand in each grade into consideration. School nurses need to positively improve the priorities of health education based on the students' demand.

• Journal of Home Health Care Nursing
• /
• v.10 no.2
• /
• pp.148-157
• /
• 2003

The purpose of this study was to provide the basic data for developing a program for effective intervention for home health care need of postpartum mothers and newborn babies. The subjects were 104 women. The data were collected from march, 2003 to June, using a 81 item questionnaire and analyzed by SPSS program for frequency, Mean, ANOVA. The results were as follow. 1. The mean of care needs of newborn babies was higher than that of physical demand of Postpartum mothers. The mean of physical demand of Postpartum mothers was $3.99\pm.42$. The mean of care needs of newborn babies was $4.11\pm.50$. 2. The most highest mean of physical demand of Postpartum mothers was wound care for caesarean section and episiotomy($4.53\pm.66$), and then breast engorgement care($4.38\pm.71$). The most highest mean of care needs of newborn babies was emergency care methods($4.58\pm.52$), and then infection control $4.51\pm.56$). 3. 66.3% of postpartum mothers positively desired consultation hospitals centered home care need during postpartial periods. 4. Influential variables of home health care need was postpartial periods. they wanted the first week after delivery, more freqently visiting of home care nurse. 37.5% of postpatial mothers wanted visiting within 1 weeks after delivery. 31.7% wanted 2 times/week. In conclusion, it is necessary to study to make a program in nursing of home health care for postpartum mothers, and to keep on studying repeatedly in order to raise the number of objects and to find related variables.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.31 no.1D
• /
• pp.133-139
• /
• 2011

We built subway stops in order to meet demand. To do so, a standardized method is used to predict the demand. However, in some subway stops there are only few people moving around sparsely, but in some other stops there are too many people crammed in a crowd. The gap between forecasting and actual uses varies from 10% to more than 1,000%. This study is aimed to find out where this discrepancy between predicted vs. actual demand for urban rail transit comes from. Specifically, 40 subway stops in Seoul Metropolitan Area, which were opened last 10 years, are examined. This study suggests that, for better forecasting, we need to consider stops' locational characteristics as well as weekday commute-oriented exogenous factors. Locational characteristics includes; whether a stops is a terminal and/or weekend tourism node. There seems no "one size fits all" solution for transit demand forecasting; locational characteristics need to be reflected.