• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1229-1244
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• 2017

In recent years, as demand for data-based analytical methodologies increases in various fields, optimization methods have been developed to handle them. In particular, various constraints required for problems in statistics and machine learning can be solved by convex optimization. Alternating direction method of multipliers (ADMM) can effectively deal with linear constraints, and it can be effectively used as a parallel optimization algorithm. ADMM is an approximation algorithm that solves complex original problems by dividing and combining the partial problems that are easier to optimize than original problems. It is useful for optimizing non-smooth or composite objective functions. It is widely used in statistical and machine learning because it can systematically construct algorithms based on dual theory and proximal operator. In this paper, we will examine applications of ADMM algorithm in various fields related to statistics, and focus on two major points: (1) splitting strategy of objective function, and (2) role of the proximal operator in explaining the Lagrangian method and its dual problem. In this case, we introduce methodologies that utilize regularization. Simulation results are presented to demonstrate effectiveness of the lasso.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1234-1243
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• 1992

A systematic procedure to design fuzzy PID controllers is developed in this paper. The concept of local fuzzy control cell is proposed by introducing both an adequate global control rule and membership functions to simplify a fuzzy logic controller. Fuzzy decision is made by using algebraic product and parallel firing arithematic mean, and a defuzzification strategy is adopted for improving the computational efficiency based on nonfuzzy micro-processor. A direct method, transforming the typical output of quasi-linear fuzzy operator to the digital compensator of PID form, is also proposed. Finally, the proposed algorithm is applied to an DC-servo motor. It is found that this algorithm is systematic and robust through computer simulations and implementation of controller using Intel 8097 micro-processor.

• Journal of Biosystems Engineering
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• v.36 no.6
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• pp.467-475
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• 2011

Aerial spraying technology using a small unmanned helicopter is an efficient and practical tool to achieve stable agricultural production to improve the working condition. An attitude controller for the agricultural helicopter would be helpful to aerial application operator. In order to construct the flight controller, a state space model of the helicopter should be identified using a dynamic analysis program, such as CIFER$^{(R)}$. To obtain the state space a model of the helicopter, frequency-sweep flight tests were performed and time history data were acquired using a custom-built stick position transmitter. Four elements of stick commands were accessed for the collective pitch (heave), aileron (roll), elevator (pitch), rudder (yaw) maneuvers. The test results showed that rudder stick position signal was highly linear with rudder input channel signal of the receiver; however, collective pitch stick position signal was exponentially manipulated for the convenience of control stick handling. The acquired stick position and flight dynamic data during sweep tests would be analyzed in the followed study.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.13-30
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• 2010

Let C be a nonempty closed convex subset of a real Hilbert space H. Consider the following iterative algorithm given by $x_0\;{\in}\;C$ arbitrarily chosen, $x_{n+1}\;=\;{\alpha}_n{\gamma}f(W_nx_n)+{\beta}_nx_n+((1-{\beta}_n)I-{\alpha}_nA)W_nP_C(I-s_nB)x_n$, ${\forall}_n\;{\geq}\;0$, where $\gamma$ > 0, B : C $\rightarrow$ H is a $\beta$-inverse-strongly monotone mapping, f is a contraction of H into itself with a coefficient $\alpha$ (0 < $\alpha$ < 1), $P_C$ is a projection of H onto C, A is a strongly positive linear bounded operator on H and $W_n$ is the W-mapping generated by a finite family of nonexpansive mappings $T_1$, $T_2$, ${\ldots}$, $T_N$ and {$\lambda_{n,1}$}, {$\lambda_{n,2}$}, ${\ldots}$, {$\lambda_{n,N}$}. Nonexpansivity of each $T_i$ ensures the nonexpansivity of $W_n$. We prove that the sequence {$x_n$} generated by the above iterative algorithm converges strongly to a common fixed point $q\;{\in}\;F$ := $\bigcap^N_{i=1}F(T_i)\;\bigcap\;VI(C,\;B)$ which solves the variational inequality $\langle({\gamma}f\;-\;A)q,\;p\;-\;q{\rangle}\;{\leq}\;0$ for all $p\;{\in}\;F$. Using this result, we consider the problem of finding a common fixed point of a finite family of nonexpansive mappings and a strictly pseudocontractive mapping and the problem of finding a common element of the set of common fixed points of a finite family of nonexpansive mappings and the set of zeros of an inverse-strongly monotone mapping. The results obtained in this paper extend and improve the several recent results in this area.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.12
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• pp.573-580
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• 2017

Deep Neural Network (DNN) is a large layered neural network which is consisted of a number of layers of non-linear units. Deep Learning which represented as DNN has been applied very successfully in various applications. However, many issues in DNN have been identified through past researches. Among these issues, generalization is the most well-known problem. A Recent study, Dropout, successfully addressed this problem. Also, Dropout plays a role as noise, and so it helps to learn robust feature during learning in DNN such as Denoising AutoEncoder. However, because of a large computations required in Dropout, training takes a lot of time. Since Dropout keeps changing an inter-layer representation during the training session, the learning rates should be small, which makes training time longer. In this paper, using mutation operation, we reduce computation and improve generalization performance compared with Dropout. Also, we experimented proposed method to compare with Dropout method and showed that our method is superior to the Dropout one.

• Journal of Biosystems Engineering
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• v.37 no.5
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• pp.287-295
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• 2012

Purpose: Some of the most representative approaches are to apply next generation technologies to save energy consumption, fully automated control system to appropriately maintain environmental conditions, and autonomous assistance system to reduce labor load and ensure operator's safety. Nevertheless, improvement of upcoming method for soil cultured greenhouse has not been sufficiently achieved. Geometrical complexity of ground in protected crop cultivation might be one of the most dominant factors in design of autonomous vehicle. While there is a practical solution fairly enough to promise an accurate travelling, such as autonomous sprayer guided by rail or induction coil, for various reasons including the limitation of producer's budget, the previously developed sprayer has not been widely distributed to market. Methods: In this study, we developed an autonomous sprayer considering travelling performance on geometrical complexity of ground in soil cultured greenhouse. To maintain a stable travelling and to acquire a real time feedback, common wire with 80 mm thick and body frame and sprayer boom. To evaluate performance of the prototype, tracking performance, climbing performance and spraying boom's uniform leveling performance were individually evaluated by corresponding experimental tests. Results: The autonomous guidance system was proved to be sufficiently suitable for accurate linear traveling with RMS as lower than approximately 10 cm from designated path. Also the prototype could climb $10^{\circ}$ of ground's slope angle with 40 kg of water weight. Uniform leveling of spraying boom was successfully performed within $0.5^{\circ}$ of sprayer boom's slope. Conclusions: Considering more complex pathways and coarse ground conditions, evaluations and improvements of the prototype should be performed for promising reliability to commercialization.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.147-156
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• 2009

We present a methodology for modeling and solving the transit frequency design problem with variable demand. The problem is described as a bi-level model based on a non-cooperative Stackelberg game. The upper-level operator problem is formulated as a non-linear optimization model to minimize net cost, which includes operating cost, travel cost and revenue, with fleet size and frequency constraints. The lower-level user problem is formulated as a capacity-constrained stochastic user equilibrium assignment model with variable demand, considering transfer delay between transit lines. An efficient algorithm is also presented for solving the proposed model. The upper-level model is solved by a gradient projection method, and the lower-level model is solved by an existing iterative balancing method. An application of the proposed model and algorithm is presented using a small test network. The results of this application show that the proposed algorithm converges well to an optimal point. The methodology of this study is expected to contribute to form a theoretical basis for diagnosing the problems of current transit systems and for improving its operational efficiency to increase the demand as well as the level of service.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.3
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• pp.333-347
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• 2013

The present study numerically models the interaction between a regular wave and the roll motion of a rectangular floating structure. In order to simulate two-dimensional incompressible viscous two-phase flow in a numerical wave tank with the rectangular floating structure, the present study used the volume of fluid method based on the finite volume method. The sliding mesh technique is adopted to handle the motion of the rectangular floating structure induced by fluid-structure interaction. The effect of the wave period on the flow, roll motion and forces acting on the structure is examined by considering three different wave periods. The time variations of the wave height and the roll motion of the rectangular structure are in good agreement with experimental results for all wave periods. The present response amplitude operator is in good agreement with experimental results with the linear potential theory. The present numerical results effectively represent the entire process of vortex generation and evolution described by the experimental results. The longer wave period showed a different mechanism of the vortex evolution near each bottom corner of the structure compared to cases of shorter wave periods. In addition, the x-directional and z-directional forces acting on the structure are analyzed.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.2
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• pp.41-50
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• 2004

Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

• Journal of the Korea Computer Graphics Society
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• v.22 no.5
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• pp.1-16
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• 2016

In this paper, we propose and efficient curve reconstruction method based on the classical least-square fitting scheme. Specifically, given planar sample points equipped with normals, we reconstruct the objective curve as the zero set of a hierarchical implicit ZP(Zwart-Powell)-spline that can recover large holes of dataset without loosing the fine details. As regularizers, we adopted two: a Tikhonov regularizer to reduce the singularity of the linear system and a discrete Laplacian operator to smooth out the isocurves. Benchmark tests with quantitative measurements are done and our method shows much better quality than polynomial methods. Compared with the hierarchical bi-quadratic spline for datasets with holes, our method results in compatible quality but with less than 90% computational overhead.