• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.5
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• pp.46-55
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• 2006

In general, 3-dimensional point-mass equation has been widely used for the trajectory optimization of the fixed-wing aircraft and reentry vehicle. But it should be modified and represent target vehicle's own characteristics. For a lighter-than-air vehicle such as an airship, there exists different and peculiar flight characteristics compared with the aircraft. The first part of this paper is to derive the dynamic equation of motion for the mid-altitude unmanned airship and the second part is to obtain the optimal trajectories under the minimal time flight given constraints. The trajectory optimization problem is converted into the nonlinear programming problem using Sequential Quadratic Programming approach. Finally numerical solutions are presented in the last part of the paper.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.11
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• pp.562-571
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• 2007

This paper considers variants of k-center problems to find the set of disks with centers on a given (or moving) line with fixed orientation such that the disks contain a given point set and the maximum radius of the disks is minimized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1460-1468
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• 2000

The goal of this research is the real-time implementation of MPEG-1 Layer III audio decoder using the fixed-point digital signal processor of TMS320C6201 The main job for this work is twofold: one is to convert floating-point operation in the decoder into fixed-point operation while maintaining the high resolution, and the other is to optimize the program to make it run in real-time with memory size as small as possible. We, especially, devote much time to the descaling module in the decoder for conversion of floating-point operation into fixed-point operation with high accuracy. The inverse modified cosine transform(IMDCT) and synthesis polyphase filter bank modules are optimized in order to reduce the amount of computation and memory size. After the optimization process, in this paper, the implemented decoder uses about 26% of maximum computation capacity of TMS320C6201. The program memory, data ROM, data RAM used in the decoder are about 6.77kwords, 3.13 kwords and 9.94 kwords, respectively. Comparing the PCM output of fixed-point computation with that of floating-point computation, we achieve the signal-to-noise ratio of more than 60 dB. A real-time operation is demonstrated on the PC using the sound I/O and host communication functions in the EVM board.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.1-8
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• 2018

Recently, the convolutional neural network shows high performance in many computer vision tasks. However, convolutional neural networks require enormous amount of operation, so it is difficult to adopt them in the embedded environments. To solve this problem, many studies are performed on the ASIC or FPGA implementation, where an efficient representation method is required. The fixed-point representation is adequate for the ASIC or FPGA implementation but causes a performance degradation. This paper proposes a separate optimization of representations for the convolutional layers and the batch normalization layers. With the proposed method, the required bit width for the convolutional layers is reduced from 16 bits to 10 bits for the ResNet-50 neural network. Since the computation amount of the convolutional layers occupies the most of the entire computation, the bit width reduction in the convolutional layers enables the efficient implementation of the convolutional neural networks.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.251-258
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• 2019

In the future, various products are created in various fields using artificial intelligence. In this age, it is a very important problem to know the operation principle of artificial intelligence learning method and to use it correctly. This paper introduces artificial intelligence learning methods that have been known so far. Learning of artificial intelligence is based on the fixed point iteration method of mathematics. The GD(Gradient Descent) method, which adjusts the convergence speed based on the fixed point iteration method, the Momentum method to summate the amount of gradient, and finally, the Adam method that mixed these methods. This paper describes the advantages and disadvantages of each method. In particularly, the Adam method having adaptivity controls learning ability of machine learning. And we analyze how these methods affect digital signals. The changes in the learning process of digital signals are the basis of accurate application and accurate judgment in the future work and research using artificial intelligence.

• Journal of Information Technology Services
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• v.6 no.3
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• pp.87-110
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• 2007

Recently, researches on IT Service Management (ITSM) for improving information system operation service and information system outsourcing cost estimation model are proliferating. This study suggests a new cost model of IT operation service and optimizing method based upon the characteristics of operation service as a long-term and continuous business service for both user's and service provider's point of view. This study explains the cost optimization model of IT operation service by improving service request management process, such as adequate reception and control, proper valuation, process management using project management methodology, effective organization and time management of service personnel. Especially in this study, service ability improvement effect and fixed operation cost reduction effect are defined to prove the proposed new cost model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.6
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• pp.1827-1835
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• 1996

This paper addresses the problem of a torch path generation for the 2D laser cutting of a stock plate nested with resular or irregular parts. Under the constaint of the relative positions of parts enforced by nesting, the developed torch path algorithm generate feasible cutting path. In this paper, the basic object is a polygon( a many-slide figure) with holes. A part may be represented as a number of line segments connected end-to-end in counterclockwise order, and formed a closed contour as requied for cutting paths. The objective is to tranverse this cutting contours with a minimum path length. This paper proposes a simulated annealing based dtorch path algorithm, that is an improved version of previously suggested TSP models. Since everypiercing point of parts is not fixed in advance, the algorithm solves as relazed optimization problem for the constraint, thich is one of the main features of the proposed algorithm. For aolving the torch path optimization problem, an efficient generation mechanism of neighborhood structure and as annealing shedule were introduced. In this way, a global solution can be obtained in a reasonable time. Seveeral examples are represented to ilustrate the method.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.879-891
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• 2021

With improvements in living conditions, an increasing number of people are choosing to spend their time traveling. Comfortable tour routes are affected by the season, time, and other local factors. In this paper, the influencing factors and principles of scenic spots are analyzed, a model used to find the available routes is built, and a multi-route choice model based on a game theory utilizing a path recommendation weight is developed. A Monte Carlo analysis of a tourist route subjected to fixed access point conditions is applied to account for uncertainties such as the season, start time, end time, stay time, number of scenic spots, destination, and start point. We use the Dijkstra method to obtain multiple path plans and calculate the path evaluation score using the Monte Carlo method. Finally, according to the user preference in the input path, game theory generates path ordering for user choice. The proposed approach achieves a state-of-the-art performance at the pseudo-imperial palace. Compared with other methods, the proposed method can avoid congestion and reduce the time cost.

• Korean Journal of Computational Design and Engineering
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• v.21 no.4
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• pp.389-396
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• 2016

The necessity for environment-friendly material development has emerged in the recent automotive field due to stricter regulations on fuel economy and environmental concerns. Accordingly, the automotive industry is paying attention to carbon fiber reinforced plastic (CFRP) material with high strength and stiffness properties while the lightweight. In this study, we determine a shape of lower control arm (LCA) for maximizing the strength and stiffness by optimizing the thickness of each layer when the stacking angle is fixed due to the CFRP manufacturing problems. Composite materials are laminated in the order of $0^{\circ}$, $90^{\circ}$, $45^{\circ}$, and $-45^{\circ}$ with a symmetrical structure. For the approximate optimal design, we apply a sequential two-point diagonal quadratic approximate optimization (STDQAO) and use a process integrated design optimization (PIDO) code for this purpose. Based on the physical properties calculated within a predetermined range of laminate thickness, we perform the FEM analysis and verify whether it satisfies the load and stiffness conditions or not. These processes are repeated for successive improved objective function. Optimized CFRP LCA has the equivalent stiffness and strength with light weight structure when compared to conventional aluminum design.

• Korean Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.87-102
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• 1998

Given a sequence of cross-sectional curves, the skinning method generates a freeform surface that interpolates the given curves in that sequence. This thesis presents a construction method of a B-spline skinning surface that is fair and satisfies volume constraints. The fairness metric is based on the parametric energy functional of a surface. The degrees of freedom in surface control are closely related lo control points in the skinning direction. The algorithm fur finding a skinning surface consists of two step. In the first step, an initial fair surface is generated without volume constraints and one coordinate of each control point is fixed. In the second step, a final surface that meets all constraints is constucted by rearranging the other coordinates of each control point that defines the initial surface A variational Lagrange optimization method produces a system of nonlinear equations, which can be solved numerically. Moreover, the reparametrization of given sectional curves is important for the construction of a reasonable skinning surface. This thesis also presents an intuitive metric for reparametrization and gives some examples that are optimized with respect to that metric.