• Applied Science and Convergence Technology
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• v.26 no.5
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• pp.129-132
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• 2017

We report a chemical vapor deposition approach and optimized growth condition to the synthesis of single layer molybdenum disulfide ($MoS_2$). Obtaining large grain size with continuous $MoS_2$ atomically thin films is highly responsible to the growth distance between molybdenum trioxide source and receiving silicon substrate. Experimental results indicate that triangular shape $MoS_2$ grain size could be enlarged up to > 80um with the precisely controlled the source-to-substrate distance under 7.5 mm. Furthermore, we demonstrate fabrication of a memory device by employing poly(methyl methacrylate) (PMMA) as insulating layer. The fabricated devices have a PMMA-$MoS_2$/metal configuration and exhibit a bistable resistance switching behavior with high/low-current ratio around $10^3$.

• Korean Journal of Hydrosciences
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• v.8
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• pp.111-123
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• 1997

A one-dimensional eddy diffusion model and a mixed-layer model are developed and applied to simulate the vertical temperature profiles in lakes. Also the running result of each method are compared and analyzed. In an eddy diffusion model, molecular diffusivity is neglected and eddy diffusivity which does not need lake-specific fitting parameter and constant lake's level are applied. The heat exchanges at the water surface and the bottom are formulated by the energy balance and zero energy gradient, respectively. In a mixed-layer model, two layers approach which has a constant thickness is adopted. The application of these models which use explicit finite difference and Runge-Kutta methods respectively demonstrates that the models simulate water temperatures efficiently.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.934-940
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• 1991

The multi-layer neural network that has broadly been utilized in designing the controller of robot manipulator possesses the desirable characteristics of learning capacity, by which the uncertain variation of the dynamic parameters of robot can be handled adaptively, and parallel distributed processing that makes it possible to control on real-time. However the error back propagation algorithm that has been utilized popularly in the learning of the multi-layer neural network has the problem of its slow convergencs speed. In this paper, an approach to improve the convergence speed is proposed using fuzzy logic that can effectively handle the uncertain and fuzzy informations by linguistic level. The effectiveness of the proposed algorithm is demonstrated by computer simulation of PUMA 560 robot manipulator.

• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.421-431
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• 2005

This paper introduces a new approach for saving build time of hybrid rapid prototyping by decomposing a part into minimum number of layers. In the hybrid rapid prototyping, a part of a complicated shape is realized by adding layers of a simpler shape, each of which is obtained by machining a sheet of constant thickness from its top and bottom surfaces. Thus it is desired to decompose a given part into the minimum number of layers while guaranteeing each layer to be fabricated from the given sheets using a 3-axis milling machine. To satisfy these requirements, a concave edge-based algorithm is proposed to decompose a part into layers by considering the tool accessibility, the total number of layers, and the allowable sheet thickness.

• Journal of Electrical Engineering and Technology
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• v.8 no.2
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• pp.238-243
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• 2013

In this paper, a novel approach for optimized installation and operations of battery energy storage system (BESS) and electric double layer capacitor (EDLC) modules for the renewable energy based intermittent generation is presented for them to be connected with an electric power grid. In order to make use of not merely the high energy density of battery but also the high power density of EDLC modules, it is very useful to devise the hybrid system which combines BESS and EDLC modules. The proposed method adopts the linear programming to calculate the optimized capacity as well as the quadratic programming to transmit the optimal operational signals to BESS and EDLC modules. The efficiency of this methodology will be demonstrated in the experimental study with the real data of wind speed in Texas.

• ETRI Journal
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• v.37 no.5
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• pp.898-905
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• 2015

In this paper, we consider a joint beamforming and jamming design to enhance physical layer security against potential multiple eavesdroppers in a multiple-input and single-output cellular broadcast channel. With perfect channel state information at the base station, we propose various design approaches to improve the secrecy of the target user. Among the proposed approaches, the combined beamforming of maximum ratio transmission and zero-forcing transmission with a combination of maximum ratio jamming and zero-forcing jamming (MRT + ZFT with MRJ + ZFJ) shows the best security performance because it utilizes the full transmit antenna dimensions for beamforming and jamming with an efficient power allocation. The simulation results show that the secrecy rate of this particular proposed approach is better than the rates of the considered conventional approaches with quality-of-service and outage probability constraints.

• 한국전산유체공학회:학술대회논문집
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• 2002.10a
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• pp.53-63
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• 2002

In this numerical approach, strut-placed supersonic annular flow is examined. The geometrical variations of strut cause strong influence on flowfield structures. The geometrical variations are as follows, swept effect, attack angle effect, variation of leading edge shape. These changed features such as velocity structure, pressure structure, shock-boundary layer interaction are compared and analyzed according to each geometrical configuration.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.9
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• pp.101-110
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• 1998

In process planning for 3D pocket machining, the critical issues for the optimal process planning are the generation of cutting layers and the tool selection for each cutting layers as well as the other factors such as the determination of machining types, tool path, etc. This paper describes the optimal tool selection on a single cutting layer for 2D pocket machining, the generation of cutting layers for 3D pocket machining, the determination of the thickness of each cutting layers, the determination of the tool combinations for each cutting layers and also the development of an algorithm for determining the machining sequence which reduces the number of tool exchanges, which are based on the backward approach. The branch and bound method is applied to select the optimal tools for each cutting layer, and an algorithmic procedure is developed to determine the machining sequence consisting of the pairs of the cutting layers and cutting tools to be used in the same operation.

• International Journal of Ocean System Engineering
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• v.3 no.3
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• pp.111-115
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• 2013

Blasius equation describes the boundary layer formed over a flat plate inside a fluid and this equation is solved numerically by the method of moments which is a type of weighted residual methods. Compared to the traditionally used Runge - Kutta Method, Method of Moments propose a direct solution to Blasius Equation which makes it easier to solve. The obtained solutions show good agreement with the results found in literature and this study aims to demonstrate the power of the method.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.57-65
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• 2018

Artificial neural network is inspired by the biological neural network. For simplicity, in computer science, it is represented as a set of layers. Many research has been made in evaluating the number of neurons in the hidden layer but still, none was accurate. Several methods are used until now which do not provide the exact formula for calculating the number of thehidden layer as well as the number of neurons in each hidden layer. In this paper model selection approach was presented. Proposed model is based on geographical analysis of decision boundary. Proposed model selection method is useful when we know the distribution of the training data set. To evaluate the performance of the proposed method we compare it to the traditional architecture on IRIS classification problem. According to the experimental result on Iris data proposed method is turned out to be a powerful one.