• Journal of KIISE:Databases
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• v.28 no.3
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• pp.430-448
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• 2001

In navigation system, a primary task is to compute the minimum cost route from the current location to the destination. One of major problems for navigation systems is that a significant amount of computation time is required when the digital road map is large. Since navigation systems are real time systems, it is critical that the path be computed while satisfying a time constraint. In this paper, we have developed a HiTi(Hierarchical MulTi) graph model for hierarchically structuring large digital road maps to speedup the minimum cost path computation. We propose a new shortest path algorithm named SPAH, which utilizes HiTi graph model of a digital road map for its computation. We prove that the shortest path computed by SPAH is the optimal. Our performance analysis of SPAH also showed that it significantly reduces the computation time over exiting methods. We present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1069-1078
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• 2018

Demand response (DR) programs give opportunity to consumers to manage their electricity bills. Besides, distribution system operator (DSO) is interested in using DR programs to obtain technical and economic benefits for distribution network. Since small consumers have difficulties to individually take part in the electricity market, an entity named demand response provider (DRP) has been recently defined to aggregate the DR of small consumers. However, implementing DR programs face challenges to fairly allocate benefits and payments between DRP and DSO. This paper presents a procedure for modeling the interaction between DRP and DSO based on a bilevel programming model. Both DSO and DRP behave from their own viewpoint with different objective functions. On the one hand, DRP bids the potential of DR programs, which are load shifting and load curtailment, to maximize its expected profit and on the other hand, DSO purchases electric power from either the electricity market or DRP to supply its consumers by minimizing its overall cost. In the proposed bilevel programming approach, the upper level problem represents the DRP decisions, while the lower level problem represents the DSO behavior. The obtained bilevel programming problem (BPP) is converted into a single level optimizing problem using its Karush-Kuhn-Tucker (KKT) optimality conditions. Furthermore, point estimate method (PEM) is employed to model the uncertainties of the power demands and the electricity market prices. The efficiency of the presented model is verified through the case studies and analysis of the obtained results.

• Journal of Science and Technology Studies
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• v.16 no.2
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• pp.33-63
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• 2016

This paper compares and contrasts the concept of nature and the theory of evolution held by leading synthetic biologists and transhumanists in the post-genomic era. Synthetic biology, which emerged in the early 2000s, aims to design biological systems that perform specific functions with the two key concepts of "rational design" and "directed evolution". However, synthetic biology has also raised serious concerns about the creation of man-made biological materials and the manipulation of the direction and speed of evolution. It is no wonder that transhumanists, who dream of creating new, enhanced human species, have welcomed the arrival of synthetic biology. How, then, can we deal with the nature reinvented by synthetic biology? By what means can one justify research that may affect the process of evolution? What intellectual resources do synthetic biology and transhumanism share in common? What influence would the new trend of commercialization of science and technology exert upon the development of synthetic biology? Addressing those questions, this paper argues that the moral authority of nature can be restored in this post-genomic era.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.181-190
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• 2007

This paper presents a collision avoidance system for intelligent ship. Unlike collision avoidance system of other unmanned vehicles, the collision avoidance system for intelligent ship aims at not only deriving a reasonable and safe path to the goal but also keeping COLRECs(International Regulations for Preventing Collisions at Sea). The heuristic search based on the BK-products is adopted to achieve the general purpose of collision avoidance system; deriving a reasonable and safe path. The rule of action to avoid collision is adopted for the other necessary and sufficient condition; keeping the COLREGs. The verification of proposed collision avoidance system is performed with scenarios that represent encounter situations classified in the COLREGs, then it is compared with $A^{\ast}$ search method in view of optimality and safety. The analysis of simulation result revels that the proposed collision avoidance system is practical and effective candidate for real-time collision avoidance system of intelligent ship.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.21-28
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• 2015

Feature normalization as a pre-processing step has been widely used to reduce the effect of different scale in each feature dimension and error rate in classification. Most of the existing normalization methods, however, do not use the class labels of data points and, as a result, do not guarantee the optimality of normalization in classification aspect. A supervised rank normalization method, combination of rank normalization and supervised learning technique, was proposed and demonstrated better result than others. In this paper, another technique, training sample selection, is introduced in supervised feature normalization to reduce classification error more. Training sample selection is a common technique for increasing classification accuracy by removing noisy samples and can be applied in supervised normalization method. Two sample selection measures based on the classes of neighboring samples and the distance to neighboring samples were proposed and both of them showed better results than previous supervised rank normalization method.

• Journal of the Korea Society of Computer and Information
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• v.18 no.11
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• pp.31-38
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• 2013

Feature normalization as a pre-processing step has been widely used in classification problems to reduce the effect of different scale in each feature dimension and error as a result. Most of the existing methods, however, assume some distribution function on feature distribution. Even worse, existing methods do not use the labels of data points and, as a result, do not guarantee the optimality of the normalization results in classification. In this paper, proposed is a supervised rank normalization which combines rank normalization and a supervised learning technique. The proposed method does not assume any feature distribution like rank normalization and uses class labels of nearest neighbors in classification to reduce error. SVM, in particular, tries to draw a decision boundary in the middle of class overlapping zone, the reduction of data density in that area helps SVM to find a decision boundary reducing generalized error. All the things mentioned above can be verified through experimental results.

• Steel and Composite Structures
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• v.37 no.6
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• pp.663-678
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• 2020

This paper proposes a novel topology optimization method generating multiple materials for external linear plane crack structures based on the combination of IsoGeometric Analysis (IGA) and eXtended Finite Element Method (X-FEM). A so-called eXtended IsoGeometric Analysis (X-IGA) is derived for a mechanical description of a strong discontinuity state's continuous boundaries through the inherited special properties of X-FEM. In X-IGA, control points and patches play the same role with nodes and sub-domains in the finite element method. While being similar to X-FEM, enrichment functions are added to finite element approximation without any mesh generation. The geometry of structures based on basic functions of Non-Uniform Rational B-Splines (NURBS) provides accurate and reliable results. Moreover, the basis function to define the geometry becomes a systematic p-refinement to control the field approximation order without altering the geometry or its parameterization. The accuracy of analytical solutions of X-IGA for the crack problem, which is superior to a conventional X-FEM, guarantees the reliability of the optimal multi-material retrofitting against external cracks through using topology optimization. Topology optimization is applied to the minimal compliance design of two-dimensional plane linear cracked structures retrofitted by multiple distinct materials to prevent the propagation of the present crack pattern. The alternating active-phase algorithm with optimality criteria-based algorithms is employed to update design variables of element densities. Numerical results under different lengths, positions, and angles of given cracks verify the proposed method's efficiency and feasibility in using X-IGA compared to a conventional X-FEM.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.32-42
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• 2021

The printing process can have to print various colors with a limited capacity of printing facility such as ink containers that are needed cleaning to change color. In each container, cleaning time exists to assign corresponding inks, and it is considered as the setup cost required to reduce the increasing productivity. The existing manual method, which is based on the worker's experience or intuition, is difficult to respond to the diversification of color requirements, mathematical modeling and algorithms are suggested for efficient scheduling. In this study, we propose a new type of scheduling problem for the printing process. First, we suggest a mathematical model that optimizes the color assignment and scheduling. Although the suggested model guarantees global optimality, it needs a lot of computational time to solve. Thus, we decompose the original problem into sequencing orders and allocating ink problems. An approximate function is used to compute the job scheduling, and local search heuristic based on 2-opt algorithm is suggested for reducing computational time. In order to verify the effectiveness of our method, we compared the algorithms' performance. The results show that the suggested decomposition structure can find acceptable solutions within a reasonable time. Also, we present schematized results for field application.

• Asia Marketing Journal
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• v.15 no.3
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• pp.141-157
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• 2013

Managing customers based on customer equity (CE) has emerged as the most effective way of doing business because of its ability to foster profitable customer relationship management (CRM) through appropriate marketing activities. Most research studies provide conceptual and empirical evidence of the positive link between CE and firm performance. However, regarding this possibility, it has been suggested by some researchers that this link may not hold true for other firms with different firmographic factors, such as firm growth rate, size, and resources. As previous research emphasizes that marketing managers should implement a strategy based on their unique business environment, our study addresses this issue by extending the framework to a different industry setting to investigate the impact of CE on firm performance. We develop a model for examining the relationship between the firm's estimated CE and firm performance by each time period using a distributed lagged model. Then, we investigate the effect of CE on the firm's profitability using a regression analysis. Finally, even though CRM is in increasing demand and firms are focusing on the customer as an asset, we conclude that there is a limited condition for this positive effect of CE. When the life cycle was divided by growth rate, CE was shown to have a distinctive effect on profit. In the case of a high-growth stage, the effect of CE on profit is positive because of its potential customer base, whereas the effect is not significant in a low-growth stage. That is, when the business environment is saturated and the firms are no longer competing in the market, CRM may not be effective. In other words, a long-term performance orientation may not be as effective as previously believed. This research contributes to the previous literature, providing a counterintuitive suggestion that firm managers should be cautious about implementing a CRM strategy and should allocate resources properly in terms of their resource capabilities and ability depending on their situation.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.351-356
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• 2022

Among the path planning methods used to generate the ship's path, the graph search-based method is widely used because it has the advantage of its completeness, optimality. In order to apply the graph-based search method to the berthing path plan, the deviation from the path must be minimized. Path following suitability should be considered essential, since path deviation during berthing can lead to collisions with berthing facilities. However, existing studies of graph search-based berthing path planning are dangerous for application to real-world navigation environments because they produce results with a course change just before berthing. Therefore, in this paper, we develop a cost function suitable for path following, and propose a 3D A* algorithm that applies it. In addition, in order to evaluate the suitability for the actual operating environment, the results of the path generation of the algorithm are compared with the trajectory of the data collected by manned operations.