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Study on the Sequential Generation of Monthly Rainfall Amounts (월강우량의 모의발생에 관한 연구)

  • 이근후;류한열
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.18 no.4
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    • pp.4232-4241
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    • 1976
  • This study was carried out to clarify the stochastic characteristics of monthly rainfalls and to select a proper model for generating the sequential monthly rainfall amounts. The results abtained are as follows: 1. Log-Normal distribution function is the best fit theoretical distribution function to the empirical distribution of monthly rainfall amounts. 2. Seasonal and random components are found to exist in the time series of monthly rainfall amounts and non-stationarity is shown from the correlograms. 3. The Monte Carlo model shows a tendency to underestimate the mean values and standard deviations of monthly rainfall amounts. 4. The 1st order Markov model reproduces means, standard deviations, and coefficient of skewness with an error of ten percent or less. 5. A correlogram derived from the data generated by 1st order Markov model shows the charaterstics of historical data exactly. 6. It is concluded that the 1st order Markov model is superior to the Monte Carlo model in their reproducing ability of stochastic properties of monthly rainfall amounts.

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An Adaptable Destination-Based Dissemination Algorithm Using a Publish/Subscribe Model in Vehicular Networks

  • Morales, Mildred Madai Caballeros;Haw, Rim;Cho, Eung-Jun;Hong, Choong-Seon;Lee, Sung-Won
    • Journal of Computing Science and Engineering
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    • v.6 no.3
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    • pp.227-242
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    • 2012
  • Vehicular Ad Hoc Networks (VANETs) are highly dynamic and unstable due to the heterogeneous nature of the communications, intermittent links, high mobility and constant changes in network topology. Currently, some of the most important challenges of VANETs are the scalability problem, congestion, unnecessary duplication of data, low delivery rate, communication delay and temporary fragmentation. Many recent studies have focused on a hybrid mechanism to disseminate information implementing the store and forward technique in sparse vehicular networks, as well as clustering techniques to avoid the scalability problem in dense vehicular networks. However, the selection of intermediate nodes in the store and forward technique, the stability of the clusters and the unnecessary duplication of data remain as central challenges. Therefore, we propose an adaptable destination-based dissemination algorithm (DBDA) using the publish/subscribe model. DBDA considers the destination of the vehicles as an important parameter to form the clusters and select the intermediate nodes, contrary to other proposed solutions. Additionally, DBDA implements a publish/subscribe model. This model provides a context-aware service to select the intermediate nodes according to the importance of the message, destination, current location and speed of the vehicles; as a result, it avoids delay, congestion, unnecessary duplications and low delivery rate.

Modeling of Sediment and Phosphorous Transport in a River Channel (하천 내 유사와 인 이동에 관한 모델링)

  • Kim, Kyunghyun
    • Journal of Korean Society on Water Environment
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    • v.26 no.2
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    • pp.332-342
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    • 2010
  • A model has been developed to investigate in-river sediment and phosphorus dynamics. This advective-dispersive model is coupled with hydrodynamics and sediment transport submodels to simulate suspended sediment, total dissolved phosphorus, total phosphorus, and particulate phosphorus concentrations under unsteady flow conditions. It emphasizes sediment and phosphorus dynamics in unsteady flow conditions, in which the study differs from many previous solute transport studies, conducted in relatively steady flow conditions. The diffusion wave approaximation was employed for unsteady flow simulations. The first-order adsorption and linear adsorption isotherm model was used on the basis of the three-layered riverbed submodel with riverbed sediment exchange and erosion/deposition processes. Various numerical methods were tested to select a method that had minimal numerical dispersion under unsteady flow conditions. The responses of the model to the change of model parameter values were tested as well.

The Universal Design of Microwave Oven considering Old Persons (노인 사용자를 고려한 전자렌지의 유니버셜 디자인)

  • Song, Bok-Hui;Yun, Han-Gyeong;Jeong, Gwang-Tae
    • Journal of the Ergonomics Society of Korea
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    • v.19 no.1
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    • pp.37-48
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    • 2000
  • Universal design is an approach to create environments and products that recognizes the diversity of users, regardless of their ability or age. Recently, old person and disabled person rapidly go on increasing in number. So, universal design concept becomes more and more important in product and environment, etc. In this study, we dealt with the universal design problem of microwave oven considering old persons. New design model for microwave oven was developed and evaluated using human factors approach. The principles of universal design was developed through literature survey and questionnaire survey for old persons, and then design alternatives were developed according to these principles. Two experiments were performed in this study. The purpose of the first experiment was to select final design alternative and the experiment was performed using rapid prototypes. The second one was a usability testing for the real model of final alternative. In this experiment, the real model was compared with the existing real product. As the result, the new design model was a little more excellent than the existing model in usability.

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Development of Yield Forecast Models for Vegetables Using Artificial Neural Networks: the Case of Chilli Pepper (인공 신경망을 이용한 채소 단수 예측 모형 개발: 고추를 중심으로)

  • Lee, Choon-Soo;Yang, Sung-Bum
    • Korean Journal of Organic Agriculture
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    • v.25 no.3
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    • pp.555-567
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    • 2017
  • This study suggests the yield forecast model for chilli pepper using artificial neural network. For this, we select the most suitable network models for chilli pepper's yield and compare the predictive power with adaptive expectation model and panel model. The results show that the predictive power of artificial neural network with 5 weather input variables (temperature, precipitation, temperature range, humidity, sunshine amount) is higher than the alternative models. Implications for forecasting of yields are suggested at the end of this study.

A Determinant Model for Methods to Calculate the Weighted Value of Each Indicator for Environmental Evaluation (환경평가를 위한 지표의 가중치 산정방법 결정 모형)

  • Lee, Gwan-Gue;Yang, Byoung-E
    • Journal of Environmental Impact Assessment
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    • v.10 no.1
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    • pp.59-71
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    • 2001
  • This study aims to propose a determinant model to select a method on calculating weight of each indicator for environmental evaluation. According to analyzing and comparing with three types of methods for calculating weights which are usually used to evaluate environment with indicators, the weights which were obtained by each type were all different from each other. This means that a differential weighting method must be applied to each of environmental evaluation studies. Therefore, a determinant model is required to determine weight-calculating methods. Three types of weighting methods, such as weighting by importance degree, weighting by eigen-value and weighting by analytic hierarchy process, were compared. Under the necessity, a determinant model was drawn for selecting a compatible method to calculate weights of indicators in environmental evaluation.

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A Portfolio Model for National IT R&D Strategy Project Selection Methods

  • Ryu, Dong-Hyun;Lee, Woo-Jin
    • Journal of information and communication convergence engineering
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    • v.9 no.5
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    • pp.491-499
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    • 2011
  • In this paper, we offer a new strategic portfolio model for national IT R&D project selection in Korea. A risk and return (R-R) portfolio model was developed using an objectively quantified index on the two axes of risk and return, in order to select a strategic project and allocate resources in compliance with a national IT R&D strategy. We strategize using the R-R portfolio model to solve the non-strategy and subjectivity problems of the existing national R&D project selection model. We also use the quantified evaluation index of the IT technology road map (TRM) and the technical level reports (TLR) for the subjectivity of project selection, and try to discover the weights using the analytic hierarchy process (AHP). In addition, we intend to maximize the chance for a successful national IT R&D project, by selecting a strategic portfolio project and balancing the allocation of resources effectively and objectively.

Sensor Placement Method for Damage Identification (균열 진단을 위한 센서 위치 선정)

  • Kim, Chung-Hwan;Kwon, Kye-Si
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.17 no.4 s.121
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    • pp.324-332
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    • 2007
  • Sensor placement method for damage identification has been developed for model updating using Taguchi method. In order to select the optimal sensor location, the analysis of variance of objective function using orthogonal array was carried out. Then, modal data at the selected locations were used for damage identification using model updating. The numerical model of a cantilever beam was used in order to compare the damage identification results with conventional sensor location method.

Models for forecasting food poisoning occurrences (식중독 발생 예측모형)

  • Yeo, In-Kwon
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1117-1125
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    • 2012
  • The occurrence of food poisoning is usually modeled by meteorological variables like the temperature and the humidity. In this paper, we investigate the relationship between food poisoning occurrence and climate variables in Korea and compare Poisson regression and autoregressive moving average model to select the forecast model. We confirm that lagged climate variables affect the food poisoning occurrences. However, it turns out that, from the viewpoint of the prediction, the number of previous occurrences is more influential to the current occurrence than meteorological variables and Poisson regression model is less reliable.

Assessment of Ammunition Companies Using IDEA model (IDEA를 이용한 탄약중대의 효율성 평가)

  • Bae Yeong-Min;Kim Jae-Hui;Kim Seung-Gwon
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2006.05a
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    • pp.1707-1714
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    • 2006
  • In order to enhance sustainable war fighting capabilities, it is important to maintain a good ammunition support system. In this paper, we evaluate the performance of Ammunition companies using Imprecise Data Envelopment Analysis (IDEA)-BCC and IDEA-Additive model, which can deal with imprecise data in DEA. In order to select a list of input and output variables, we used a multiple regression analysis. We could choose input variables that have significant effects on the output performance with stepwise regression model. From the regression analysis, the number of soldiers, officers, and ammunition warehouses were selected as the input variables. Seven out of sixteen Ammunition companies were found to be inefficient by the IDEA-BCC model. And using IDEA-Additive model, we could identify the input excess and the output shortfall in reaching at a point on the efficiency frontier.

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