• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.637-639
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• 2021

As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.137-142
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• 1996

An algorithm for solving the cardinality constrained linear programming knapsack problem is presented. The algorithm has a convenient structure for a branch-and-bound approach to the integer version, especially to the 0-1 collapsing knapsack problem. A numerical example is given.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.326-331
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• 1988

In this paper, an iterative leaning control algorithm for the linear discrete system is proposed. Based upon the parameter estimation method, the learning for good tracking control is acqured through a sequence of repetitive operations. A series of simulation are performed to show the validity of this algorithm.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.73-77
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• 2016

This paper deals with the network reliability problem that decides the communication line between main two districts while the k districts were destroyed in military communication network that the n communication lines are connected in m districts. For this problem, there is only in used the mathematical approach as linear programming (LP) software package and has been unknown the polynomial time algorithm. In this paper we suggest the heuristic algorithm with O(n) linear time complexity to solve the optimal solution for this problem. This paper suggests the flow path algorithm (FPA) and level path algorithm (LPA). The FPA is to search the maximum number of distinct paths between two districts. The LPA is to construct the levels and delete the unnecessary nodes and edges. The proposed algorithm can be get the same optimal solution as LP for experimental data.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.81-86
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• 2015

This paper suggests heuristic algorithm with linear time complexity to decide the normal and optimal point at minimum loss/maximum profit maximum shortest scheduling problem with additional loss cost and bonus profit cost. This algorithm computes only the earliest ending time for each node. Therefore, this algorithm can be get the critical path and project duration within O(n) time complexity and reduces the five steps of critical path method to one step. The proposed algorithm can be show the result more visually than linear programming and critical path method. For real experimental data, the proposed algorithm obtains the same solution as linear programming more quickly.

• Steel and Composite Structures
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• v.12 no.6
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• pp.505-522
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• 2012

An artificial bee colony (ABC) algorithm is developed for the optimum design of geometrically non-linear steel frames. The ABC is a new swarm intelligence method which simulates the intelligent foraging behaviour of honeybee swarm for solving the optimization problems. Minimum weight design of steel frames is aimed under the strength, displacement and size constraints. The geometric non-linearity of the frame members is taken into account in the optimum design algorithm. The performance of the ABC algorithm is tested on three steel frames taken from literature. The results obtained from the design examples demonstrate that the ABC algorithm could find better designs than other meta-heuristic optimization algorithms in shorter time.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.144-147
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• 1987

An adaptive control algorithm for a plant with unmodelled dynamics is proposed. The upper bounds of the output due to the unmodelled dynamics and measurement noise is assumed to be known. Linear programming is used in estimating the bounds of plant parameters. Projection type algorithm is used in estimating the plant parameter with these bounds. This algorithm is nearly the same as those proposed by Kreisselmeier or Middleton except that the bounds are computed by linear programming. The stability of the proposed algorithm Can be proved in nearly the same way as that of Middleton. Simulation results show that the proposed algorithm gives better parameter convergence and smaller overshoot in the plant output than the algorithm without computing the bounds of plant parameters by linear programming.

• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2247-2258
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• 1997

Quadtree, which is hierarchical data structure, is a very important data structure to represent binary images. Since a linear quadtree representation as is a way to store a quadtree is efficient to save space compared with other representations. It is, however, complicated and takes a large amount of time to build the linear quadtree. In this paper, we present O(1) time a linear quadtree building algorithm for a $n{\times}n$ binary image using three-dimensional $n{\times}n{\times}n$ processors on RMESH structure. Our algorithm, by use of O(1) time collapsing algorithm and reported O(1) time sorting algorithm, is simpler and easier to understand than resently presented algorithm on PARBUS structure.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.58-65
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• 1994

A recursive on-line algorithm for orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters time delay and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursiveform by using new functions of two dimensional autocorrelations and crosscorrelations of inputs and outputs. This proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.58-63
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• 1993

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear MIMO systems with unknown parameters, time delay, and order. This algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extended to a recursive form by using new functions of two dimensional autocorrelations and cross-correlations of inputs and outputs. The proposed algorithm can also cope with slowly time-varying or order-varying systems. Various simulations reveal the performance of the algorithm.