• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.2
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• pp.125-134
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• 2022

Recently, there are an increased the number of reports on the misuse or malicious use of an UAS. Thus, many researchers are studying on defense schemes for UAS by developing or improving C-UAS sensor technology. However, the wrong placement of sensors may lead to a defense failure since the proper placement of sensors is critical for UAS defense. In this study, a multi-object optimization model for C-UAS sensor placement in an air base is proposed. To address the issue, we define two objective functions: the intersection ratio of interested area and the minimum detection range and try to find the optimized placement of sensors that maximizes the two functions. C-UAS placement model is designed using a NSGA-II algorithm, and through experiments and analyses the possibility of its optimization is verified.

• The Korean Journal of Applied Statistics
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• v.37 no.6
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• pp.733-749
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• 2024

In survival analysis, the use of deep neural networks has become popular. It requires the mini-batch type stochastic gradient descent (SGD) algorithm. However, the existence of risk set in the partial likelihood can be problematic, which can be addressed by many previous works. In this paper, we proposed an advanced algorithm compared to the conventional SGD by applying an online mirror descent algorithm. It can be used for any convex optimization problem where the given tasks are closely related to online learning. A re-parameterization trick and bi-level optimization are used to construct the algorithm. The experiments on various setups reveal the superiority of the proposed algorithm. It can contribute to making an efficient mini-batch-based algorithm over the convex optimization and semi-parametric survival models.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.351-357
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• 2011

In this study, we have intended to analyze the possibility of using the precise geoid model and to find the best geoid model for working by the airborne LiDAR system. So we have calculated the geoid height from the precise geoid models (KGEOID08, EGM2008, EIGEN-CG03C) and have analyzed results by comparing the geometric geoid height from surveying and geoid heights from geoid models. As a result, the KGEOID08 that had 0.152m of RMSE was assessed the best geoid model for making DEM(DTM) by airborne LiDAR system. Also we have found the needed arrangement and numbers of reference point when the KGEOID08 was used for conversion into orthometric height of LiDAR data.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.5
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• pp.616-624
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• 2011

The flow characteristics and heat transfer augment on the periodically arranged semi-circular ribs in a rectangular channel for turbulent flow has been investigated numerically. The aspect ratio of the rectangular channel was AR=5, the rib height to hydraulic diameter ratio were 0.07 and rib height to channel height ratio was set as e/H=0.117 for various PR(rib pitch-to-rib height rate) between 8~14, respectively. The SST k-${\omega}$ turbulence model and v2-f turbulence model were used to find out the heat transfer and the flow characteristics of near the wall which are suited to obtain realistic phenomena. The numerical analysis results show turbulent flow characteristics, heat transfer enhancement and friction factor as observed experimentally. The results predict that turbulent kinetic energy(k) is closely relative to the diffusion of recirculation flow. and v2-f turbulence model simulation results have a good agreement with experimental values.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.66-75
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• 2010

In Augmented Reality, it needs restoration and tracking of a real-time scene structure for the augmented 3D model from input video or images. Most of the previous approaches construct accurate 3D models in advance and try to fit them in real-time. However, it is difficult to measure 3D model accurately and requires long pre-processing time to construct exact 3D model specifically. In this research, we suggest a real-time scene structure analysis method for the wide indoor mobile augmented reality, using only generic models without exact pre-constructed models. Our approach reduces cost and time by removing exact modeling process and demonstrates the method for restoration and tracking of the indoor repetitive scene structure such as corridors and stairways in different scales and details.

• Journal of Korean Society of Steel Construction
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• v.19 no.3
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• pp.291-301
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• 2007

The overlay model is a certain kinds of numerical analysis method to present the material non-lineariy which is represented the baushinger effect and the strain hardening. This model simulates the complex behavior of material by controlling the properties of the layers which like the hardening ratio, the section area and the yield stress. In this paper, the constitutive equation and plastic flow rule of each layer which are laid in the plane stress field are obtained by using the thermodynamics. Two numerical examples were tested for the validity of proposed method in uniaxial stress and plane stress field with comparable experimental results. The only parameter for the test is the yield stress distribution of each layers.

• Applied Chemistry for Engineering
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• v.31 no.5
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• pp.520-525
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• 2020

In this study, we developed a machine learning-based model for predicting the production stage temperature of distillation process. It is necessary to predict an accurate temperature for control because the control of the distillation process is done through the production stage temperature. The temperature in distillation process has a nonlinear complex relationship with other variables and time series data, so we used the recurrent neural network algorithms to predict temperature. In the model development process, by adjusting three recurrent neural network based algorithms, and batch size, we selected the most appropriate model for predicting the production stage temperature. LSTM₁₂₈ was selected as the most appropriate model for predicting the production stage temperature. The prediction performance of selected model for the actual temperature is RMSE of 0.0791 and R² of 0.924.

• Communications of Mathematical Education
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• v.36 no.4
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• pp.511-533
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• 2022

The purpose of this study is to develop a learning coaching model suitable for the mathematics subject by reflecting the characteristics of the mathematics subject and the mathematics teaching/learning process in the CARE learning coaching model that supports students' self-directed learning. The mathematics learning coaching model developed in this study is a 'step' and 'element' to apply coaching, and a 'strategy' for carrying out it. Mathematics learning coaching model evaluated rapport, trust, state management, and math pre-test as elements of 'creating a comfortable atmosphere', and problem recognition, hypercognition, restructuring, initiative, and math learning ability as elements of 'improving perception'. Self-efficacy, learning readiness, confirmation (feedback) as elements of the 'reawakening of learning immersion' stage, voluntary motivation and success experiences as elements of the 'empowerment' stage, and various math learning strategies to perform each element presented. The math learning coaching model can be used to help math teachers motivate students to learn and help students solve their own problems.

• Composites Research
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• v.36 no.2
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• pp.92-100
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• 2023

In this paper, a machine learning and deep learning model for the design of circuit analog (CA) radar absorbing structure with a cross-dipole pattern on a glass fiber fabric reinforced plastic is presented. The proposed model can directly calculate reflection loss in the Ku-band (12-18 GHz) without three-dimensional electromagnetic numerical analysis based on the geometry of the Cross-Dipole pattern. For this purpose, the optimal learning model was derived by applying various machine learning and deep learning techniques, and the results calculated by the learning model were compared with the electromagnetic wave absorption characteristics obtained by 3D electromagnetic wave numerical analysis to evaluate the comparative advantages of each model. Most of the implemented models showed similar calculated results to the numerical results, but it was found that the Fully-Connected model could provide the most similar calculated results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.858-861
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• 2012

Distributed sensor nodes for environmental monitoring, have a problem of difficult and expensive battery change. In this case, renewable energy such as solar energy is helpful. We can use high-quality solar energy everyday. In this paper, we model photovoltaic energy prediction model for sensor nodes, which includes charge and discharge characteristics as well as seasonal and monthly characteristics of the solar energy. Our model is useful to predict energy consumption of solar-powered sensor nodes realistically using real world use data of the nodes.