• Title/Summary/Keyword: Demand estimation

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Research on the Actual Condition of Working Conditions in the Small and Medium Clinics (중소 병.의원 근무환경 실태조사)

  • Cheol, Kweon-Dae;Mi, Jang-Myeong;Hei, Jang-Yun;Mo, Chung-Kyung;Sin, Kwak-Choong
    • Journal of radiological science and technology
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    • v.28 no.1
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    • pp.55-65
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    • 2005
  • Research of actual condition of working conditions in the small and clinics, in the Seoul metropolitan city and Kyeonggido province. With the health care environmental change such as a rapid increase of the elderly people, rapid increase of health promotion needs, it is necessary to analyse and identity of the actual condition of working conditions for present and new radiological technologist. Research of general characteristics for the present radiological technologist. To research of the status employment, business scope, pay, working conditions, radiation safety management, equipment, and category association. Defining the problems of related working conditions, radiation safety management for the comprehensive methods to promote the rights the radiological technologist. A proposal for establishment legislature and system of the actual condition in the hospital for radiological technologist. Estimation for the demand and supply numbers of present radiological technologist and improvement of employment relations. Improved and refined scope business and duty regulation related to radiological technologist. Application for the establishment and development of promotion rights to utilize as basic data in a legislative and system frame of reference to implement the radiological technologist.

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A Study on the Estimation of Pedestrian Signal Timing (횡단보도 보행신호시간 산정에 관한 연구)

  • An, Gye-Hyeong;Kim, Eun-Jeong;Lee, Yong-Il;Jeong, Jun-Ha;Kim, Yeong-Chan
    • Journal of Korean Society of Transportation
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    • v.24 no.5 s.91
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    • pp.57-66
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    • 2006
  • This paper presents new pedestrian signal timings considering pedestrian demand Pedestrian characteristics, and land use which were obtained by Pedestrian characteristics field survey and pedestrian signal operation survey. Pedestrian signal timings suggested were compared to the existing pedestrian signal timings by using real field data. pedestrian characteristics field survey was conducted to collect pedestrian crossing speed data and reaction time data. Sixteen areas in Seoul were selected for the data collection. The average pedestrian crossing speed was 1.30m/sec and the 15th Percentile speed was 1.11m/sec. The average reaction time was 2.24 seconds. Pedestrian crossing speed differs by land use, road width. pedestrian age, sex, and number of Pedestrians. Reaction time also differs by road width, pedestrian age, and number of pedestrians. Statistical testing was performed to secure reliability of the collected data.

Comparison of Approximate Nonlinear Methods for Incremental Dynamic Analysis of Seismic Performance (내진성능의 증분동적해석을 위한 비선형 약산법의 비교 검토)

  • Bae, Kyeong-Geun;Yu, Myeong-Hwa;Kang, Pyeong-Doo;Kim, Jae-Ung
    • Journal of the Earthquake Engineering Society of Korea
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    • v.12 no.1
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    • pp.79-87
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    • 2008
  • Seismic performance evaluation of structure requires an estimation of the structural performance in terms of displacement demand imposed by earthquakes on the structure. Incremental Dynamic Analysis(IDA) is a analysis method that has recently emerged to estimate structural performance under earthquakes. This method can obtained the entire range of structural performance from the linear elastic stage to yielding and finally collapse by subjecting the structure to increasing levels of ground acceleration. Most structures are expected to deform beyond the limit of linearly elastic behavior when subjected to strong ground motion. The nonlinear response history analysis(NRHA) among various nonlinear analysis methods is the most accurate to compute seismic performance of structures, but it is time-consuming and necessitate more efforts. The nonlinear approximate methods, which is more practical and reliable tools for predicting seismic behavior of structures, are extensively studied. The uncoupled modal response history analysis(UMRHA) is a method which can find the nonlinear reponse of the structures for ESDF from the pushover curve using NRHA or response spectrum. The direct spectrum analysis(DSA) is approximate nonlinear method to evaluate nonlinear response of structures, without iterative computations, given by the structural linear vibration period and yield strength from the pushover analysis. In this study, the practicality and the reliability of seismic performance of approximate nonlinear methods for incremental dynamic analysis of mixed building structures are to be compared.

Seismic Performance of Concrete Masonry Unit (CMU) Infills in Reinforced Concrete Moment Framing System (철근콘크리트 모멘트 골조시스템에서 조적 끼움벽의 내진성능)

  • Hong, Jong-Kook
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.23 no.1
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    • pp.19-26
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    • 2019
  • The masonry infill walls are one of the most popular components that are used for dividing and arranging spaces in building construction. In spite of the fact that the masonry infills have many advantages, the system needs to be used with caution when the earthquake load is to be considered. The infills tend to develop diagonal compression struts during earthquake and increase the demand in surrounding RC frames. If there are openings in the infill walls, the loading path gets even complicated and the engineering judgements are required for designing the system. In this study, a masonry infill system was investigated through finite element analysis (FEA) and the results were compared with the current design standard, ASCE 41. It is noted that the equivalent width of the compression strut estimated by ASCE 41 could be 32% less than that using detailed FEA. The global load resisting capacity was also estimated by 28% less when ASCE 41 was used compare to the FEA case. Rather than using expensive FEA, the adapting ASCE 41 for the analysis and design of the masonry infills with openings would provide a good estimation by about 25% conservatively.

The Estimation of Sand Dam Storage using a Watershed Hydrologic Model and Reservoir Routing Method (유역 수문모형과 저수지 추적기법을 연계한 샌드댐 저류량 산정)

  • Chung, Il-Moon;Lee, Jeongwoo;Lee, Jeong Eun;Choi, Jung-Ryel
    • The Journal of Engineering Geology
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    • v.28 no.4
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    • pp.541-552
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    • 2018
  • The implementation of drought measures in the upstream areas of river basins is seldom considered with respect to water supply. However, the demand for such measures is increasing rapidly owing to the occurrence of severe droughts, and interventions on streams and the water supply are needed. Physical interventions are an option to prevent streams from becoming dry and to maintain stream water flow, but dam construction is challenging because of environmental and ecological considerations. Here, a feasibility study was conducted to assess the potential effects of sand dams, which are widely used in arid regions in Africa. The SWAT-K model, which is a hydrologic model used for Korean watersheds, is used to estimate the flow rate of water in an ungauged watershed. The changes in water storage of the sand-dammed reservoir and in downstream flow rates are estimated for two types of sand dam (natural and dredged). The results show that sand dams are capable of increasing the downstream flow rate during normal conditions and of mitigating water supply problems caused by the withdrawal of water during drought periods.

A study on the estimation of onion's bulb weight using multi-level model (다층모형을 활용한 양파 구중 추정 연구)

  • Kim, Junki;Choi, Seung-cheon;Kim, Jaehwi;Seo, Hong-Seok
    • The Korean Journal of Applied Statistics
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    • v.33 no.6
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    • pp.763-776
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    • 2020
  • Onions show severe volatility in production and price because crop conditions highly depend on the weather. The government has designated onions as a sensitive agricultural product, and prepared various measures to stabilize the supply and demand. First of all, preemptive and reliable information on predicting onion production is essential to implement appropriate and effective measures. This study aims to contribute to improving the accuracy of production forecasting by developing a model to estimate the final weight of onions bulb. For the analysis, multi-level model is used to reflect the hierarchical data characteristics consisting of above-ground growth data in individual units and meteorological data in parcel units. The result shows that as the number of leaf, stem diameter, and plant height in early May increase, the bulb weight increases. The amount of precipitation as well as the number of days beyond a certain temperature inhibiting carbon assimilation have negative effects on bulb weight, However, the daily range of temperature and more precipitation near the harvest season are statistically significant as positive effects. Also, it is confirmed that the fitness and explanatory power of the model is improved by considering the interaction terms between level-1 and level-2 variables.

Research on Longitudinal Slope Estimation Using Digital Elevation Model (수치표고모델 정보를 활용한 도로 종단경사 산출 연구)

  • Han, Yohee;Jung, Yeonghun;Chun, Uibum;Kim, Youngchan;Park, Shin Hyoung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.6
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    • pp.84-99
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    • 2021
  • As the micro-mobility market grows, the demand for route guidance, that includes uphill information as well, is increasing. Since the climbing angle depends on the electric motor uesed, it is necessary to establish an uphill road DB according to the threshold standard. Although road alignment information is a very important element in the basic information of the roads, there is no information currently on the longitudinal slope in the road digital map. The High Definition(HD) map which is being built as a preparation for the era of autonomous vehicles has the altitude value, unlike the existing standard node link system. However, the HD map is very insufficient because it has the altitude value only for some sections of the road network. This paper, hence, intends to propose a method to generate the road longitudinal slope using currently available data. We developed a method of computing the longitudinal slope by combining the digital elevation model and the standard link system. After creating an altitude at the road link point divided by 4m based on the Seoul road network, we calculated individual slope per unit distance of the road. After designating a representative slope for each road link, we have extracted the very steep road that cannot be climbed with personal mobility and the slippery roads that cannot be used during heavy snowfall. We additionally described errors in the altitude values due to surrounding terrain and the issues related to the slope calculation method. In the future, we expect that the road longitudinal slope information will be used as basic data that can be used for various convergence analyses.

Estimation of regional flow duration curve applicable to ungauged areas using machine learning technique (머신러닝 기법을 이용한 미계측 유역에 적용 가능한 지역화 유황곡선 산정)

  • Jeung, Se Jin;Lee, Seung Pil;Kim, Byung Sik
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1183-1193
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    • 2021
  • Low flow affects various fields such as river water supply management and planning, and irrigation water. A sufficient period of flow data is required to calculate the Flow Duration Curve. However, in order to calculate the Flow Duration Curve, it is essential to secure flow data for more than 30 years. However, in the case of rivers below the national river unit, there is no long-term flow data or there are observed data missing for a certain period in the middle, so there is a limit to calculating the Flow Duration Curve for each river. In the past, statistical-based methods such as Multiple Regression Analysis and ARIMA models were used to predict sulfur in the unmeasured watershed, but recently, the demand for machine learning and deep learning models is increasing. Therefore, in this study, we present the DNN technique, which is a machine learning technique that fits the latest paradigm. The DNN technique is a method that compensates for the shortcomings of the ANN technique, such as difficult to find optimal parameter values in the learning process and slow learning time. Therefore, in this study, the Flow Duration Curve applicable to the unmeasured watershed is calculated using the DNN model. First, the factors affecting the Flow Duration Curve were collected and statistically significant variables were selected through multicollinearity analysis between the factors, and input data were built into the machine learning model. The effectiveness of machine learning techniques was reviewed through statistical verification.

The Impact of Exchange Rate Volatility on Korea's Exports of Machinery Intermediate Goods to East Asian Countries: Around the Global Financial Crisis (환율변동성이 동아시아 국가에 대한 한국의 기계류 중간재 수출에 미치는 영향: 글로벌 금융위기 전후를 중심으로)

  • Jung, Moon-Hyun
    • Korea Trade Review
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    • v.43 no.3
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    • pp.169-198
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    • 2018
  • The purpose of this paper is to investigate the impact of exchange rate volatility on the export of Korean machinery intermediate goods to East Asian countries using the export demand model. In order to secure the validity of the estimation of the exchange rate volatility for the export of machinery intermediate goods, various methods of volatility measurement are used including the GARCH model, the moving average standard deviation and the 12-month fixed average standard deviation. The long-term relationship between variables was analyzed by applying the panel cointegration tests and DOLS & FMOLS panel estimations. Analysis results found that prior to the global financial crisis in 2008, the total exports of machinery and exchange rate volatility positively affect the exports of intermediate goods such as general machinery, electronic machinery and transportation equipment, but did not affect the exports of precision machinery intermediate goods. After the global financial crisis, however, exchange rate volatility negatively affected total exports and the exports of all machinery intermediate goods. When analyzing the period before and after the global financial crisis, it had a positive impact on exports of precision machinery intermediate goods and a negative effect on total exports and the exports of other machinery intermediate goods.

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Multi-objective Genetic Algorism Model for Determining an Optimal Capital Structure of Privately-Financed Infrastructure Projects (민간투자사업의 최적 자본구조 결정을 위한 다목적 유전자 알고리즘 모델에 관한 연구)

  • Yun, Sungmin;Han, Seung Heon;Kim, Du Yon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.1D
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    • pp.107-117
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    • 2008
  • Private financing is playing an increasing role in public infrastructure construction projects worldwide. However, private investors/operators are exposed to the financial risk of low profitability due to the inaccurate estimation of facility demand, operation income, maintenance costs, etc. From the operator's perspective, a sound and thorough financial feasibility study is required to establish the appropriate capital structure of a project. Operators tend to reduce the equity amount to minimize the level of risk exposure, while creditors persist to raise it, in an attempt to secure a sufficient level of financial involvement from the operators. Therefore, it is important for creditors and operators to reach an agreement for a balanced capital structure that synthetically considers both profitability and repayment capacity. This paper presents an optimal capital structure model for successful private infrastructure investment. This model finds the optimized point where the profitability is balanced with the repayment capacity, with the use of the concept of utility function and multi-objective GA (Generic Algorithm)-based optimization. A case study is presented to show the validity of the model and its verification. The research conclusions provide a proper capital structure for privately-financed infrastructure projects through a proposed multi-objective model.