• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.182-186
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• 2019

When a camera is employed for 3D sensing, accurate camera calibration is vital as it is a prerequisite for the subsequent steps of the sensing process. Camera calibration is usually performed by complex mathematical modeling and geometric analysis. On the other contrary, data learning using an artificial neural network can establish a transformation relation between the 3D space and the 2D camera image without explicit camera modeling. However, a neural network requires a large amount of accurate data for its learning. A significantly large amount of time and work using a precise system setup is needed to collect extensive data accurately in practice. In this study, we propose a two-step neural calibration method that is effective when only a small amount of learning data is available. In the first step, the camera projection transformation matrix is determined using the limited available data. In the second step, the transformation matrix is used for generating a large amount of synthetic data, and the neural network is trained using the generated data. Results of simulation study have shown that the proposed method as valid and effective.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9B
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• pp.832-844
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• 2008

Distributed localization algorithms are necessary for large-scale wireless sensor network applications. In this paper, we introduce an efficient node distribution based localization algorithm that emphasizes simple refinement and low system load for low-cost and low-rate wireless sensors. Each node adaptively chooses neighbor nodes for sensors, update its position estimate by minimizing a local cost function and then passes this update to the neighbor nodes. The update process considers a distribution of nodes for large-scale networks which have same density in a unit area for optimizing the system performance. Neighbor nodes are selected within a range which provides the smallest received signal strength error based on the real experiments. MATLAB simulation showed that the proposed algorithm is more accurate than trilateration and les complex than multidimensional scaling. The implementation on MicaZ using TinyOS-2.x confirmed the practicality of the proposed algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.193-202
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• 2017

Development of Intelligent Systems involves effective integration of large-scaled knowledge processing and understanding, human-machine interaction, and intelligent services. Especially, in our project for development of a self-growing knowledge-based system with inference methodologies utilizing the big data technology, we are building a platform called WiseKB as the central knowledge base for storing massive amount of knowledge and enabling question-answering by inferences. WiseKB thus requires an effective methodology to analyze diverse requirements convoluted with the integration of various components of knowledge representation, resource management, knowledge storing, complex hybrid inference, and knowledge learning, In this paper, we propose an integrated requirement analysis method that blends the traditional sequential method and the iterative-incremental method to achieve an efficient requirement analysis for large-scale systems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.895-906
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• 2014

A fundamental study of the dynamically penetrating anchor (DPA - colloquially known as torpedo anchor) embedded into deep seabed was conducted using measurement data and numerical approaches. Numerical simulation of such a structure penetration was often suffered by severe mesh distortion arising from very large soil deformation, complex contact condition and nonlinear soil behavior. In recent years, a Coupled Eulerian-Lagrangian method (CEL) has been used to solve geomechanical boundary value problems involving large deformations. In this study, 3D finite element analyses using the CEL formulation are carried out to simulate the construction process of dynamic anchors. Through comparisons with results of field measurements, the CEL method in the present study is in good agreement with the general trend observed by in-situ measurements and thus, predicts a realistic large deformation movement for the dynamic anchors by free-fall dropping, which the conventional FE method cannot. Additionally, the appropriate parametric studies needed for verifying the characteristic of dynamic anchor are also discussed.

• Journal of the Society of Naval Architects of Korea
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• v.53 no.5
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• pp.388-399
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• 2016

A motion analysis of an underwater towed cable is a complex task due to its nonlinear nature of the problem. The major source of the nonlinearity of the underwater cable analysis is that the motion of the cable involves large rigid-body motion. This large rigid-body motion makes difficult to use standard displacement-based finite element method. In this paper, the authors apply recently developed nodal position-based finite element method which can deal with the geometric nonlinearity due to the large rigid-body motion. In order to enhance the stability of the large-scale nonlinear cable motion simulation, an efficient time-integration scheme is proposed, namely predictor/multi-corrector Newmark scheme. Three different predictors are introduced, and the best predictor in terms of stability and robustness for impulsive cable motion analysis is proposed. As a result, the nonlinear motion of underwater cable is predicted in a very efficient manner compared to the classical finite element of finite difference methods. The efficacy of the method is demonstrated with several test cases, involving static and dynamic motion of a single cable element, and also under water towed cable composed of multiple cable elements.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.5
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• pp.210-218
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• 2003

MDO (multidisciplinary design optimization) technology has been proposed and applied to solve large and complex optimization problems where multiple disciplinaries are involved. In this research. an MDO problem is defined for automobile design which has crashworthiness analyses. Crash model which are consisted of airbag, belt integrated seat (BIS), energy absorbing steering system .and safety belt is selected as a practical example for MDO application to vehicle system. Through disciplinary analysis, vehicle system is decomposed into structure subspace and occupant subspace, and coupling variables are identified. Before subspace optimization, values of coupling variables at given design point must be determined with system analysis. The system analysis in MDO is very important in that the coupling between disciplines can be temporary disconnected through the system analysis. As a result of system analysis, subspace optimizations are independently conducted. However, in vehicle crash, system analysis methods such as Newton method and fixed-point iteration can not be applied to one. Therefore, new system analysis algorithm is developed to apply to crashworthiness. It is conducted for system analysis to determine values of coupling variables. MDO algorithm which is applied to vehicle crash is MDOIS (Multidisciplinary Design Optimization Based on Independent Subspaces). Then, structure and occupant subspaces are independently optimized by using MDOIS.

• Journal of Korean Society of societal Security
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• v.2 no.1
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• pp.65-74
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• 2009

In this study, the air pollution management system based GIS has been developed to estimate the emission rate and air pollution modeling of air pollutants, effectively. This system is able to estimate emission rate of air pollutant and to analyze the emission characteristics with high spatial and temporal resolution. air pollution modeling. The air pollution management system was applied to Gwangyang Bay including large industry complex with a large number of emission sources. The air pollution management system was constructed using the spatial database of emission sources in Gwangyang Bay. It was found that the estimated emission rates of air pollutants is similar to the emission characteristics in Gwangyang Bay. Also, the spatial distribution of pollutants was similar to the location of emission sources. The predicted results of air pollution model was showed a good correlation coefficient (0.75) for TSP. The air pollution management system is expected to be effective tool (database system (GIS)) for the management and the control of air pollution.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.403-407
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• 2005

Objective of the research is to demonstrate solar thermal space and ground heating system which is integrated to a greenhouse culture facility for reducing heating cost, increasing the value of product by environment control, and developing advanced culture technology by deploying solar thermal system. Field test for the demonstration was carried out in horticulture complex in Jeju Island. Medium scale solar hot water system was installed in a ground heating culture facility. Reliability and economic aspect of the system which was operated complementary with thermal storage and solar hot water generation were analyzed by investigating collector efficiency, operation performance, and control features. Short term day test on element performance and Long term test of the whole system were carried out. Optimum operating condition and its characteristics were closely investigated by changing the control condition based on the temperature difference which is the most important operating parameter. For establishing more reliable and optimal design data regarding system scale and operation condition, continuous operation and monitoring on the system need to be further carried out. However, it is expected that, in high-insolation areas where large-scale ground storage is adaptable, solar system demonstrated in the research could be economically competitive and promisingly disseminate over various application areas.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.89-94
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• 2010

The most important of rule-base system is the knowledge base that determines the power of rule-base system. The important form of this knowledge is how to descript kinds of rules. The Rule-Base System (RBS) has been using in many field that need reflect quickly change of business rules in management system. As far, when develop the Rule-Based System, we must make a rule engine with a general language. There are three disadvantage of in this developed method. First, while there are many data that must be processed in the system, the speed of processing data will become very slow so that we cannot accept it. Second, we cannot change the current system to make it adaptive to changes of business rules as quickly as possible. Third, large data make the rule engine become very complex. Therefore, in this paper, we propose the two important methods of raising efficiency of Rule-Base System. The first method refers to using the Relational database technology to process the rules of the Rule-Base System, the second method refers to a algorithm of according to Quine McCluskey formula compress the rows of rule table. Because the expressive languages of rule are still remaining many problems, we will introduce a new expressive language, which is Rule-Base Data Model short as RBDM in this paper.

• New & Renewable Energy
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• v.1 no.2 s.2
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• pp.53-59
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• 2005

Objective of the research is to demonstrate solar thermal space and ground heating system which is integrated to a green-house culture facility for reducing healing cost, Increasing the value of product by environment control, and developing advanced culture technology by deploying solar thermal system. Field test for the demonstration was carried out in horticulture complex In Jeju Island. Medium scale solar hot water system was installed in a ground heating culture facility. Reliability and economic aspect of the system which was operated complementary with thermal storage and solar hot water generation were analyzed by investigating collector efficiency, operation performance, and control features. Short term day test on element performance and Long term test of the whole system were carried out. Optimum operating condition and its characteristics were closely Investigated by changing the control condition based on the temperature difference which Is the most important operating parameter For establishing more reliable and optimal design data regarding system scale and operation condition, continuous operation and monitoring on the system need to be further carried out. However, It is expected that, in high-insolation areas where large-scale ground storage is adaptable, solar system demonstrated in the research could be economically competitive and promisingly disseminate over various application areas.