• Journal of Korean Port Research
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• v.11 no.2
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• pp.231-240
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• 1997

In the United States, a number of ocean outfalls discharge primary treated effluent into deep sea water and contribute for more efficient wastewater treatment. The long multiport diffuser connected by long pipe from a treatment plant discharge wastewater into deep water due to the steep slope of the sea bed. However, Plume discharged from the diffuser can have significant impacts on coastal communities and possibly immediate consequence on public health. Therefore, there have been growing interests about the dynamics of plume in the vicinity of the ocean outfalls. It is expected that the ocean outfall should be considered for more efficient and reliable wastewater treatments as soon as possible around coastal area in South Korea. A number of studies of plume ynamics have used various models to predict plume behavior. However, in many cases, the calculated values of plume behavior are in significantly poor agreement with realistic values. Therefore, in this study, it is recommended that improvements should be made in the application of the plume model to more simulate the actual discharge characteristics and ocean conditions. It should be noted that input parameters in plume models reflect realistic ocean conditions like waves as well as currents. In this study, as one of the new parameters, current and long wave-influenced plume rise and initial dilution have been taken into account by using simple linear wave theory under some specific assumptions for more reliable plume behavior description. Among the improved plume models approved by EPA (Environmental Protection Agency), the RSB(Roberts-Snyder-Baurngartner) and UM(Updated Merge) models were chosen for the calculation of plume behavior, and the variation calculated by both models on the basis of long period wave was compared in terms of plume rise and initial dilution.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.218-225
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• 2016

It is important to select the personnel with ideal pilot aptitude considering dramatically advancing aircraft performance and complexity of military operations as a consequence to the highly developed science and technology. The opportunity cost lost from dropouts and human error being the first cause of aviation accidents are the realistic reasons for the significance of personnel selection based on their aptitude. This study analyses the ROKAF pilot aptitude test that was improved in 2004, using various classification models. This study discusses the significance of the selected variables along with the direction of ROKAF pilot aptitude test for its development in the future. The accuracy of the classification models was improved by taking into account differing personnel characteristics of individuals on the test.

• Tunnel and Underground Space
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• v.17 no.5
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• pp.372-380
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• 2007

Surface damage due to subsidence is an inevitable consequence of underground mining, which may be immediate or delayed for many years. The surface damage due to abandoned underground mine is observed to be two subsidence types such as simple sinkhole or trough formation to a large scale sliding of the ground from with in the subsided area. An evaluation of the risk of a subsidence occurrence is vital in the areas affected by mining subsidence. For a subsidence prediction or a risk evaluation, there has been used various methods using empirical models, profile functions, influence functions and numerical models. In this study, a simple but efficient evaluation method of subsidence hazard is suggested, which is based on a diffusion theory and uses just information about geometry of caving and topography. The diffusion model has an analogous relationship with granular model which can explain a mechanism of subsidence. The diffusion model is applied for the evaluation of subsidence hazard in abandoned metal and coal mines. The model is found to be a simple but efficient tool because it needs information of geometry of caving and gangway and the topography.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.411-425
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• 2013

The importance and necessity of the credit loan are increasing over time. Also, it is a natural consequence that the increase of the risk for borrower increases the risk of non-performing loan. Thus, we need to predict accurately in order to prevent the loss of a credit loan company. Our final goal is to build reliable and accurate prediction model, so we proceed the following steps: At first, we can get an appropriate sample by using several resampling methods. Second, we can consider variety models and tools to fit our resampling data. Finally, in order to find the best model for our real data, various models were compared and assessed.

• Biomolecules & Therapeutics
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• v.20 no.1
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• pp.125-131
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• 2012

Impulsiveness is an important component of many psychiatric disorders including Attention-deficit/hyperactivity disorder (ADHD). Although the neurobiological basis of ADHD is unresolved, behavioral tests in animal models have become indispensable tools for improving our understanding of this disorder. In the punishment/extinction paradigm, impulsivity is shown by subjects that persevere with responding despite punishment or unrewarded responses. Exploiting this principle, we developed a new behavioral test that would evaluate impulsivity in the most validated animal model of ADHD of the Spontaneously Hypertensive rat (SHR) as compared with the normotensive "control" strain, the Wistar Kyoto rat (WKY). In this paradigm we call the Electro-Foot Shock aversive water Drinking test (EFSDT), water-deprived rats should pass over an electrified quadrant of the EFSDT apparatus to drink water. We reasoned that impulsive animals show increased frequency to drink water even with the presentation of an aversive consequence (electro-shock). Through this assay, we showed that the SHR was more impulsive than the WKY as it demonstrated more "drinking attempts" and drinking frequency. Methylphenidate, the most widely used ADHD medication, significantly reduced drinking frequency of both SHR and WKY in the EFSDT. Thus, the present assay may be considered as another behavioral tool to measure impulsivity in animal disease models, especially in the context of ADHD.

• Culinary science and hospitality research
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• v.23 no.7
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• pp.20-30
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• 2017

This study was conducted for the optimization of ingredients in salad dressing using Hwangdo peach (Prunus persica L. Batsch). The experiment was designed according to the D-optimal design of mixture design, which included 14 experimental points with 4 replicates for three independent variables (olive oil 40~65%, peach puree 27~50%, vinegar 8~20%). The linear regression models for pH, viscosity and color value and the quadratic regression models for emulsion stability, all sensory evaluation of the products were proven to be valid by the F-test for the overall significance of the regression model at a 5% level. Viscosity and pH of the products increased as olive oil content. Color value, viscosity and pH of the products increased as peach puree content. pH, viscosity, redness, and yellowness of the products decreased as vinegar content. Sensory evaluation result of the products showed that general preference for the products were increasingly affected by the increases in contents then decreased as they exceeded the optimum levels. In consequence, according to result from the first stage of the experiment, the optimum ingredients ratios of the raw materials were set in olive oil 52.43%, peach puree 35.07%, and vinegar 13.91% for ingredients of apricot dressing. These results provided the possibility that peach can be applied to the preparation of a dressing, and thereby present baseline data for the development of new dressings. This is also presumed to meet demands of customers who are always in pursuit of new products.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.18 no.2
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• pp.169-177
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• 2000

The modelling technique on the terrain of real-world in geo-spatial information system is a primary element for geo-information processing. This paper is designed to make use of TIN in geo-spatial information system and study the development and application of high-precision 3-D spatial analysis technique applied to terrain features. According to this research, MODEL 3 applied to breakline in mild slope/steep slope and MODEL 2 applied to peak in complex region show relatively low RMSE. This consequence proves that these two models have high precision in comparison with other models. This study also finds out optimal routines in the estimation method of slope grade and in the construction method of surface. N_T, LSP_T and LSQ_T in mild slope, N_T in steep slope, and LSQ_T in complex region turn out to be the optimal routines for high-precision 3-D spatial analysis.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.6
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• pp.415-424
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• 2004

In this paper, we introduce and investigate a new category of rule-based fuzzy inference system based on Information Granulation(IG). The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of “If..., then...” statements, and exploits the theory of system optimization and fuzzy implication rules. The form of the fuzzy rules comes with three types of fuzzy inferences: a simplified one that involves conclusions that are fixed numeric values, a linear one where the conclusion part is viewed as a linear function of inputs, and a regression polynomial one as the extended type of the linear one. By the nature of the rule-based fuzzy systems, these fuzzy models are geared toward capturing relationships between information granules. The form of the information granules themselves becomes an important design features of the fuzzy model. Information granulation with the aid of HCM(Hard C-Means) clustering algorithm hell)s determine the initial parameters of rule-based fuzzy model such as the initial apexes of the membership functions and the initial values of polynomial function being used in the Premise and consequence Part of the fuzzy rules. And then the initial Parameters are tuned (adjusted) effectively with the aid of the improved complex method(ICM) and the standard least square method(LSM). In the sequel, the ICM and LSM lead to fine-tuning of the parameters of premise membership functions and consequent polynomial functions in the rules of fuzzy model. An aggregate objective function with a weighting factor is proposed in order to achieve a balance between performance of the fuzzy model. Numerical examples are included to evaluate the performance of the proposed model. They are also contrasted with the performance of the fuzzy models existing in the literature.

• Steel and Composite Structures
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• v.25 no.6
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• pp.663-670
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• 2017

The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

• Advances in aircraft and spacecraft science
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• v.5 no.3
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• pp.363-383
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• 2018

One-dimensional (1D) models of incompressible flows, can be of interest for many applications in which fast resolution times are demanded, such as fluid-structure interaction of flows in compliant pipes and hemodynamics. This work proposes a higher-order 1D theory for the flow-field analysis of incompressible, laminar, and viscous fluids in rigid pipes. This methodology is developed in the domain of the Carrera Unified Formulation (CUF), which was first employed in structural mechanics. In the framework of 1D modelling, CUF allows to express the primary variables (i.e., velocity and pressure fields in the case of incompressible flows) as arbitrary expansions of the generalized unknowns, which are functions of the 1D computational domain coordinate. As a consequence, the governing equations can be expressed in terms of fundamental nuclei, which are invariant of the theory approximation order. Several numerical examples are considered for validating this novel methodology, including simple Poiseuille flows in circular pipes and more complex velocity/pressure profiles of Stokes fluids into non-conventional computational domains. The attention is mainly focused on the use of hierarchical McLaurin polynomials as well as piece-wise nonlocal Lagrange expansions of the generalized unknowns across the pipe section. The preliminary results show the great advantages in terms of computational costs of the proposed method. Furthermore, they provide enough confidence for future extensions to more complex fluid-dynamics problems and fluid-structure interaction analysis.