• Journal of Korean Foot and Ankle Society
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• v.25 no.1
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• pp.6-9
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• 2021

The term chronic lateral ankle instability (CLAI) embraces a spectrum of conditions that involve functional and mechanical instability, both in athletes and lower-demand patients. The hallmarks of CLAI are recurrent sprains, persistent pain, and repeated episodes of the ankle giving way. CLAI is the main complication of acute ankle sprains, which can cause discomfort in daily and sports activity. Approximately 10% to 30% of patients with acute ligament ruptures will develop chronic instability over the course of a year from the index injury. An accurate diagnostic approach and successful treatment plan should be established based on a comprehensive understanding of the concept of functional and mechanical instability. Unfortunately, the optimal modality for the management of CLAI is unclear. Even after conservative treatment or surgical intervention, it could result in degenerative changes to the ankle joint in the long term. Thus far, the incidence of ligamentous posttraumatic ankle osteoarthritis was reported to be 13% to 78%. The mean latency time between injury and osteoarthritis was at least 10 to 34.3 years. CLAI is an important pathological condition that can cause discomfort or dysfunction in daily activity in the short term, resulting in joint destruction in the long term. Therefore, it is important to understand the various complications that can occur when CLAI is not treated properly.

• Journal of the Korean Dietetic Association
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• v.25 no.1
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• pp.44-58
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• 2019

Predicting the number of meals in a foodservice organization is an important decision-making process that is essential for successful food production, such as reducing the amount of residue, preventing menu quality deterioration, and preventing rising costs. Compared to other demand forecasts, the menu of dietary personnel includes diverse menus, and various dietary supplements include a range of side dishes. In addition to the menus, diverse subjects for prediction are very difficult problems. Therefore, the purpose of this study was to establish a method for predicting the number of meals including predictive modeling and considering various factors in addition to menus which are actually used in the field. For this purpose, 63 variables in eight categories such as the daily available number of people for the meals, the number of people in the time series, daily menu details, weekdays or seasons, days before or after holidays, weather and temperature, holidays or year-end, and events were identified as decision variables. An ensemble model using six prediction models was then constructed to predict the number of meals. As a result, the prediction error rate was reduced from 10%~11% to approximately 6~7%, which was expected to reduce the residual amount by approximately 40%.

• Journal of Environmental Health Sciences
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• v.7 no.1
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• pp.1-7
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• 1981

During 20 days from November 4 to 28, 1980, the quantities of grease and oil, BOD (biological oxygen demand), COD (chemical oxygen demand), SS (suspended solid) were measured at Grit Chamber, Primary Sedimentation Tank, Secondary Sedimentation Tank in Chung Gye Chun sewage treatment plant. The results were as follows. 1. The average of grease and oil quantities were 251mg/l at Grit Chamber, 185mg/l at Primary Sedimentation Tank, 47mg/l at Secondary Sedimentation Tank. 2. In the secondary treatment for the removal of grease and oil, the removed quantities of grease and oil were increased according to increasing the quantities of influent grease and oil. The regression equation were as follows G.O.removed=0.731 G.O. influent+3.235 (r=0.887) 3. The average of grease and oil removal rate was 76.4% and the standard deviation of grease and oil removal rate daily was 10.6%. 4. G.O. (grease and oil) and BOD, COD, SS showed significant correlationship at Grit Chamber, Primary Sedimentation Tank, Secondary Sedimentation Tank. (P<0.05). 5. In the secondary treatment, effluent grease & oil and other parameters were analyzed by means of Stepwise multiple regression. Multple regression equation for estimates of effluent grease and oil were as follows. $GO_E=-9.1637+2.0380 SS_E+0.068 SS_I$ (r=0.778) 6. The correlative parameters for the effluent grease and oil seem to be the influent SS and the effluent SS. 7. It was estimated that the removal of grease and oil would be improved by means of improvement of suspended solids removal efficiency but it is necessary to inquire further into the study.

• Journal of Korean Society of Water and Wastewater
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• v.9 no.2
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• pp.118-126
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• 1995

The variation of the urban water demand and the amount of water in the distribution reservoir was studied with time for a day. The city of Kwangju in Korea was selected as a study area. The population of Kwangju in the end of 1993 was more than one million and two hundred thousand peoples. The average of daily water use in 1993 was about three hundred and fifty thousand tons a day. One day was devided into 12 divisions with a 2 hour increment. The water use demand related to the amount of water in the distribution reservoir was observed for the given time interval of a day. The water use index was defind in percentage that indicates the ratio of the amount of water use for a time interval to the amount of water use for a day. The water use index with consideration of the water stored in the reservoir was found to be useful to manage and to operate the water supply systems in real time.

• Fashion & Textile Research Journal
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• v.15 no.1
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• pp.147-155
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• 2013

The demand to complement the elderly body shape with comfortable clothing has greatly increased with the growing elderly population and their improved social-economic level. However, apparel industries have not provided significant production and sale strategies that reflect and consider elderly body shape characteristics. This study investigated the demand and complaints of current silver wear. This study was conducted on 100 elderly people 65 and over. The questionnaires were composed of Korean Activities of Daily Living (K-ADL) that reflect the general characteristics of the respondents related to clothing (clothing requirements and demands) and free comments on each question. Subsequently, we found that the most uncomfortable clothing parts were 'sleeve length' and 'crotch' in women and 'neck circumference' and 'pocket' in men when wearing shirts and pants respectively. Respondents felt that the button and zipper knob sizes were too small with the buttons too numerous. The results suggest that we should consider body shape changes caused by aging in order to develop elderly clothing patterns to improve the level of ADL. We anticipate apparel industries for the elderly to expand due to the rapid increase in the elderly population.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• Journal of the Korean Applied Science and Technology
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• v.19 no.4
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• pp.302-310
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• 2002

Demand for organic analysis increase as industries are growing and many products are spreaded in the daily life. One of many products is oil spill dispersant. It was used for oil accident in the ocean. When oil spill dispersant spread at the ocean, the petroleum in the ocean is dispersed. The oil spill dispersant is made of non ionic surfactant and petroleum oil. The non ionic surfactant disperse petroleum from oil accident. The other part is petroleum oil which has aromatic hydrocarbon. Because the aromatic hydrocarbon is cancerogenic material, it directly injure animals in the ocean. This cause the second pollution in the human body. Many oil accidents still are controlled by oil spill dispersant. Therefore quality control of the oil spill dispersant become important and this also demand for the exact quantitative analysis of aromatic hydrocarbon. Hereupon the first we develop separate petroleum oil from surfactant. The second standardize analytical method of aromatic hydrocarbon in the separated petroleum oil.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.190-197
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• 2013

People are living longer than ever before. As a result, life expectancy is going up and the demand of long-term care facilities is increasing in most countries. The facilities provide rehabilitative, restorative, and skilled nursing care to patients or residents in need of assistance with activities of daily living. This study deals with the capacitated location and allocation problem of long-term care facilities in a city that consists of a finite number of regions. Assuming that in each region candidate locations for three types of facilities are already given, two integer programming models are developed under the closest assignment rule reflecting the demand characteristics of the facilities. Both the location and type of the facilities to be built become decision variables. To show the validity of the models, numerical problems are solved with commercial software, CPLEX. Also, sensitivity studies were conducted to identify relationships between the system parameters.

• KIEAE Journal
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• v.12 no.6
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• pp.3-10
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• 2012

Small park in the community is a public asset that is commonly used by the residents daily and performs an important role to activate the community. The purpose of this study is to draw a small park plan through community participation. In concrete, this study tries to find out the demand of the residents about their small park plan, observe the changes in their demand in the process of debate and analyze the effect of the residents' participation. Small group workshop method was adopted in the study and three groups were set up and surveys were made in two stages. Two dimensional pictogram cards and three dimensional digital park formation tools were used. The results of workshop study indicated as follows: Firstly, residents wanted to have community farming garden, green house and flower garden to grow plants, natural walls and safe resting facilities. Secondly, individual and diverse opinions presented at first could be converted to common opinions through mutual exchanges of opinions in the process of debates. Thirdly, digital park formation program functioned well as an effective visual tool to draw the attention and quick responses of the residents and to reach an agreement. It is expected that the results of this study show the effectiveness of residents' participation tools in the process of drawing agreements in the community society that requires the residents' demands and agreement and this study will be usefully utilized in planning community spaces with residents' participation hereafter.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.157-158
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• 2019

발전소 관리의 단기 전력 수요에 대한 정확한 예측은 전력 시스템의 안전하고 효율적인 작동을 보장하는데 필수적이다. 따라서 본 연구는 가우스 커널 함수 네트워크 (GKFNs)의 심층 구조를 이용하여 일일 최대 전력 수요를 예측하는 새로운 방법을 제시한다. 제안 된 GKFN의 깊이 구조는 표준 GKFN에 비해 예측 정확도를 향상시킨다. 한국의 일일 최대 전력 수요를 예측하기위한 시뮬레이션은 제안 된 예측 모델이 GKFN 모델, k-NN 및 SVR과 같은 다른 예측 모델에 비해 예측 성능에 이점이 있음을 보여준다. GKFN의 제안된 심층 구조는 시계열 예측 및 회귀 문제의 다양한 문제에 적용될 수 있다.