• Journal of the Korean Mathematical Society
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• v.56 no.5
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• pp.1247-1263
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• 2019

In ordered trees, two randomly chosen vertices are said to be dependent if one lies under the other. If not, we say that they are independent. We consider several classes of ordered trees with uniform updegree requirements and find the generating functions for the trees with two marked dependent/independent vertices. As a result, we compute the probability for two vertices being dependent/independent. We also count such trees by the distance between two independent vertices.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.105-111
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• 2004

DNA computing has been using to solve TSP (Traveling Salesman Problems). However, when the typical DNA computing is applied to TSP, it can`t efficiently express vertices and weights of between vertices. In this paper, we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to efficiently express vertices and weights of between vertices for TSP. We applied ACO to TSP and as a result ACO could express DNA codes which have variable lengths and weights of between vertices more efficiently than Adleman`s DNA computing algorithm could. In addition, compared to Adleman`s DNA computing algorithm, ACO could reduce search time and biological error rate by 50% and could search for a shortest path in a short time.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• Journal of applied mathematics & informatics
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• v.17 no.1_2_3
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• pp.1-23
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• 2005

The shortest-paths problem is a fundamental problem in graph theory and finds diverse applications in various fields. This is why shortest path algorithms have been designed more thoroughly than any other algorithm in graph theory. A large number of optimization problems are mathematically equivalent to the problem of finding shortest paths in a graph. The shortest-path between a pair of vertices is defined as the path with shortest length between the pair of vertices. The shortest path from one vertex to another often gives the best way to route a message between the vertices. This paper presents an $O(n^2)$ time sequential algorithm and an $O(n^2/p+logn)$ time parallel algorithm on EREW PRAM model for solving all pairs shortest paths problem on circular-arc graphs, where p and n represent respectively the number of processors and the number of vertices of the circular-arc graph.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• Industrial Engineering and Management Systems
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• v.12 no.3
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• pp.198-206
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• 2013

The team orienteering problem (TOP) or the multiple tour maximum collection problem can be considered as a generic model that can be applied to a number of challenging applications in logistics, tourism, and other fields. This problem is generally defined as the problem of determining P paths, in which the traveling time of each path is limited by $T_{max}$ that maximizes the total collected score. In the TOP, a set of N vertices i is given, each with a score $S_i$. The starting point (vertex 1) and the end point (vertex N) of all paths are fixed. The time $t_{ij}$ needed to travel from vertex i to j is known for all vertices. Some exact and heuristics approaches had been proposed in the past for solving the TOP. This paper proposes a new solution methodology for solving the TOP using the particle swarm optimization, especially by proposing a solution representation and its decoding method. The performance of the proposed algorithm is then evaluated using several benchmark datasets for the TOP. The computational results show that the proposed algorithm using specific settings is capable of finding good solution for the corresponding TOP instance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.6
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• pp.65-72
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• 2009

This paper presents a vision based localization method for indoor mobile robots using the types of vertices from a monocular image. In the images captured from a camera of a robot, the types of vertices are determined by searching vertical edges and their branch edges with a geometric constraints. For obtaining correspondence between the comers of a 2-D map and the vertex of images, the type of vertices and geometrical constraints induced from a geometric analysis. The vertices are matched with the comers by a heuristic method using the type and position of the vertices and the comers. With the matched pairs, nonlinear equations derived from the perspective and rigid transformations are produced. The pose of the robot is computed by solving the equations using a least-squares optimization technique. Experimental results show that the proposed localization method is effective and applicable to the localization of indoor environments.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.43-50
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• 2011

We present a trade-off technique for fast but qualitative planar shape deformation using a layered mesh. We construct a layered mesh that is embedding a planar input shape; the upper-layer is denoted as a control mesh and the other lower-layer as a shape mesh that is defined by mean value coordinates relative to the control mesh. First, we try to preserve some shape properties including user constraints for the control mesh by means of a known existing nonlinear least square optimization technique, which produces deformed positions of the control mesh vertices. Then, we compute the deformed positions of the shape mesh vertices indirectly from the deformed control mesh by means of simple coordinates computation. The control mesh consists of a small number of vertices while the shape layer contains relatively a large number of vertices in order to embed the input shape as tightly as possible. Since the time-consuming optimization technique is applied only to the control mesh, the overall execution is extremely fast; however, the quality of deformation is sacrificed due to the sacrificed quality of the control mesh and its relativity to the shape mesh. In order to change the deformation behavior and consequently to compensate the quality sacrifice, we present a method to control the deformation stiffness by incorporating the orientation into the user constraints. According to our experiments, the proposed technique produces a planar shape deformation fast enough for real-time applications on limited embedded systems such as cell phones and tablet PCs.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.769-776
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• 2003

DNA computing has used to solve MCP (Maximal Clique Problem). However, when current DNA computing is applied to MCP. it can't efficiently express vertices and edges and it has a problem that can't look for solutions, by misusing wrong restriction enzyme. In this paper we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to solve MCP's problem. We applied ACO to MCP and as a result ACO could express DNA codes of variable lengths and generate codes without unnecessary vertices than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could get about four times as many as Adleman's final solutions by reducing search time and biological error rate by 15%.

• Korean Journal of Computational Design and Engineering
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• v.10 no.1
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• pp.27-39
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• 2005

Implicit surfaces are geometric shapes which are defined by implicit functions and exist in three-dimensional space. Recently, implicit surfaces have received much attention in solid modeling applications because they are easy to represent the location of points and to use boolean operations. However, it is difficult to chart points on implicit surfaces for rendering. As efficient rendering method of implicit surfaces, the original Adaptively Sampled Distance Fields (ADFs) $method^{[1]}$ is to use sampled distance fields which subdivide the three dimensional space of implicit surfaces into many cells with high sampling rates in regions where the distance field contains fine detail and low sampling rates where the field varies smoothly. In this paper, in order to maintain the sharp features efficiently with small number of cells, an extended ADFs method is proposed, applying the Dual/Primal mesh optimization $method^{[2]}$ to the original ADFs method. The Dual/Primal mesh optimization method maintains sharp features, moving the vertices to tangent plane of implicit surfaces and reconstructing the vertices by applying a curvature-weighted factor. The proposed extended ADFs method is applied to several examples of implicit surfaces to evaluate the efficiency of the rendering performance.