• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.9
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• pp.5801-5812
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• 2014

The retention basin is a hydraulic structure for flood mitigation by storing river flow over a design flood. In this study, numerical models were adopted to simulate the flood mitigation effects by a retention basin. The large flood condition was applied as a boundary condition to consider an abnormal flood caused by climate change. Furthermore, the two-dimensional numerical model was adopted to regenerate the complex flow pattern due to the topography and lateral flow near the retention basin. The numerical results of the one- and two-dimensional model were analyzed and compared. The results showed that the two-dimensional model is more applicable to assessing flood mitigation by the retention basin with a complex topography and lateral flow patterns.

• The Journal of Information Systems
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• v.29 no.1
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• pp.75-91
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• 2020

Purpose Retrofit, defined to be addition of new technologies or features to the old system to increase efficiency or to abate GHG emissions, is considered as an important alternative for the old coal-fired power plant. The purpose of this study is to propose mathematical method to model multiple alternative retrofit in Generation Capacity Expansion Planning(GCEP) problem, and to get insight to the retrofit patterns from realistic case studies. Design/methodology/approach This study made a multi-alternative retrofit GECP model by adopting some new variables and equations to the existing GECP model. Added variables and equations are to ensure the retrofit feature that the life time of retrofitted plant is the remaining life time of the old power plant. We formulated such that multiple retrofit alternatives are simultaneously compared and the best retrofit alternative can be selected. And we found that old approach to model retrofit has a problem that old plant with long remaining life time is retrofitted earlier than the one with short remaining life time, fixed the problem by some constraints with some binary variables. Therefore, the proposed model is formulated into a mixed binary programming problem, and coded and run using the GAMS/cplex. Findings According to the empirical analysis result, we found that approach to model the multiple alternative retrofit proposed in this study is comparing simultaneously multiple retrofit alternatives and select the best retrofit satisfying the retrofit features related to the life time. And we found that retrofit order problem is cleared. In addition, the model is expected to be very useful in evaluating and developing the national policies concerning coal-fired power plant retrofit.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.195-208
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• 2009

A network design problem (NDP) formulated as a mathematical program is generally used to find an optimum value to minimize or to maximize some objectives such as total travel time, social benefit, or others. NDP has, however, some limits of describing components of travel patterns like activities and trip generation due to its modeling simplicity, and also it has difficulty in including attributes of regional planning. In order to cope with such limits, this paper extends NDP to the urban planning field and proposes a mathematical program which can describe the interactions between urban social activities and transportation planning. Based on this model the authors try to optimize both urban activities and the transportation system. The model developed in this paper is tested to assess its application with a real-size regional transportation network.

• Smart Media Journal
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• v.13 no.5
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• pp.19-25
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• 2024

The biggest type of behavior that prevents people with developmental disabilities from entering society is aggressive behavior. Aggressive behavior can pose a threat not only to the personal safety of the person with a developmental disability, but also to the physical safety of others. In this study, we propose a wearable system using a low-power processor. The proposed system uses an IMU (Inertial Measurement Unit) to analyze user behavior, and when attack behavior is not detected for a certain period of time through an LED array attached to the developed system, an interesting LED is displayed. By expressing patterns, we provide behavioral intervention through compensation to people with developmental disabilities. In order to implement a system that must be worn for a long time in a power-limited environment, we present a method to optimize performance and energy consumption across all stages, from data preprocessing to AI model application.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.241-253
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• 2003

SCA (Software Communication Architecture), which has been adopted as a SDR(Software Defined Radio) Forum standard, provides a framework that successfully exploits common design patterns of embedded systems software. However, the SCA is inadequate as a component framework since it does not explicitly specify (1) a component model that defines how to express a component interface and how to implement it, (2) a package model that defines what and how to package in deployment units, and (3) a deployment model that defines the deployment environment and deployment process. In this paper, we propose a SCA-based component framework for SDR. Specifically, we present (1) a component model that defines a component as a specialized CORBA object that implements object management functionality, (2) a package model exploiting the existing XML descriptors of the SCA, and (3) a deployment model that defines a SCA-based deployment environment, a boot-up process that restores the deployment state, and a deployment process that supports lazy application instantiation and dynamic component replacement.

• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.47-62
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• 1999

To meet the interoperability requirements associated with geospatial data access and geoprocessing, much efforts to design prototypical systems conforming to $OpenGIS^{TM}$ specification has been made. With respect to Object Web GIS, however, current internet mapping technology mainly focuses on either developing mapping libraries or client applications regardless of the future needs for interoperability such as an integration of $OpenGIS^{TM}$ standard for CORBA. In this paper, we propose an $OpenGIS^{TM}$ compliant mapping kernel. OpenViews, which is designed to meet those requirements. The kernel of OpenViews encapsulates the process of acquiring geospatial data in the format of $OpenGIS^{TM}$ Geometry through ORB(Object Request Broker). OpenViews, being designed based on well-known design patterns, is a highly extensible in that programmers can easily customize it on the object oriented architecture. The components implemented in OpenViews are CORBA/Java objects, and as such are portable and scalable in a networked environment. A companion package, OpenBroker, is also developed as a portable geoprocessing application server to facilitate the implementation and configuration of server side CORBA objects. It can be used for implementing objects for spatial analysis service which would be independent of legacy spatial database systems in many cases. OpenViews, together with OpenBroker, has been successfully prototyped using the technologies including EJB and servlet as the core components of an Open GIS compliant internet mapping.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.5
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• pp.68-77
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• 2013

Change in the Global Climate causes flood, drought, heavy snow, and rainfall patterns in the Korean Peninsula. A variety of alternatives related to climate change are considered. The foreign researchers are interested in Low Impact Development(LID); the utilization of water resources and eco friendly development, over 10 years ago. The research and development of related technology has been advanced to apply LID techniques in order to develop several projects in the country. However, sharing of technology or system that can be used easily in the private sector is insufficient. The performance of the elements of LID Technology has not been fully agreed. LID elements of this technology are easy to apply to Apartment complex. The elements are classified technology. The infiltration of elements performs the functions of apartment complex landscaping space technology applied to the target. The water cycle simulation(SWMM 5.0) and technology the implementation of the effectiveness is also verified. For this purpose, three different places in apartment complex to target by SWMM5.0 U.S. EPA conducted utilizing simulated rainfall and applying LID techniques before and after the simulated water cycle (infiltration, surface evaporation, and surface runoff) were conducted. The importance of green space in the LID techniques of quantitative and qualitative storm water control as well as the role of Apartment Housing is to promote Amenity. Remember that the physical limitations of apartment complex and smooth water circulation system for the application of LID integrated management techniques should be applied. To this end, landscapes, architecture, civil engineering, environmental experts for technical consilience between the Low Impact Development efforts are required.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.7
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• pp.667-678
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• 2002

In this paper, a new radiating structure with a multi-layered two-dimensional metallic disk array was proposed for shaping the flat-topped element pattern. It is an infinite periodic planar array structure with metallic disks finitely stacked above the radiating circular waveguide apertures. The theoretical analysis was in detail performed using rigid full-wave analysis, and was based on modal representations for the fields in the partial regions of the array structure and for the currents on the metallic disks. The final system of linear algebraic equations was derived using the orthogonal property of vector wave functions, mode-matching method, boundary conditions and Galerkin's method, and also their unknown modal coefficients needed for calculation of the array characteristics were determined by Gauss elimination method. The application of the algorithm was demonstrated in an array design for shaping the flat-topped element patterns of $\pm$20$^{\circ}$ beam width in Ka-band. The optimal design parameters normalized by a wavelength for general applications are presented, which are obtained through optimization process on the basis of simulation and design experience. A Ka-band experimental breadboard with symmetric nineteen elements was fabricated to compare simulation results with experimental results. The metallic disks array structure stacked above the radiating circular waveguide apertures was realized using ion-beam deposition method on thin polymer films. It was shown that the calculated and measured element patterns of the breadboard were in very close agreement within the beam scanning range. The result analysis for side lobe and grating lobe was done, and also a blindness phenomenon was discussed, which may cause by multi-layered metallic disk structure at the broadside. Input VSWR of the breadboard was less than 1.14, and its gains measured at 29.0 GHz. 29.5 GHz and 30 GHz were 10.2 dB, 10.0 dB and 10.7 dB, respectively. The experimental and simulation results showed that the proposed multi-layered metallic disk array structure could shape the efficient flat-topped element pattern.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support fer multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To date, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques' results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.175-186
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• 1999

Detecting the features of significant patterns from their own historical data is so much crucial to good performance specially in time-series forecasting. Recently, a new data filtering method (or multi-scale decomposition) such as wavelet analysis is considered more useful for handling the time-series that contain strong quasi-cyclical components than other methods. The reason is that wavelet analysis theoretically makes much better local information according to different time intervals from the filtered data. Wavelets can process information effectively at different scales. This implies inherent support for multiresolution analysis, which correlates with time series that exhibit self-similar behavior across different time scales. The specific local properties of wavelets can for example be particularly useful to describe signals with sharp spiky, discontinuous or fractal structure in financial markets based on chaos theory and also allows the removal of noise-dependent high frequencies, while conserving the signal bearing high frequency terms of the signal. To data, the existing studies related to wavelet analysis are increasingly being applied to many different fields. In this study, we focus on several wavelet thresholding criteria or techniques to support multi-signal decomposition methods for financial time series forecasting and apply to forecast Korean Won / U.S. Dollar currency market as a case study. One of the most important problems that has to be solved with the application of the filtering is the correct choice of the filter types and the filter parameters. If the threshold is too small or too large then the wavelet shrinkage estimator will tend to overfit or underfit the data. It is often selected arbitrarily or by adopting a certain theoretical or statistical criteria. Recently, new and versatile techniques have been introduced related to that problem. Our study is to analyze thresholding or filtering methods based on wavelet analysis that use multi-signal decomposition algorithms within the neural network architectures specially in complex financial markets. Secondly, through the comparison with different filtering techniques results we introduce the present different filtering criteria of wavelet analysis to support the neural network learning optimization and analyze the critical issues related to the optimal filter design problems in wavelet analysis. That is, those issues include finding the optimal filter parameter to extract significant input features for the forecasting model. Finally, from existing theory or experimental viewpoint concerning the criteria of wavelets thresholding parameters we propose the design of the optimal wavelet for representing a given signal useful in forecasting models, specially a well known neural network models.