• KIPS Transactions on Software and Data Engineering
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• v.6 no.6
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• pp.315-320
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• 2017

Estimating the correct pose of augmented objects on the real camera view efficiently is one of the most important questions in image tracking area. In computer vision, Homography is used for camera pose estimation in augmented reality system with markerless. To estimating Homography, several algorithm like SURF features which extracted from images are used. Based on extracted features, Homography is estimated. For this purpose, RANSAC algorithm is well used to estimate homography and DCS-RANSAC algorithm is researched which apply constraints dynamically based on Constraint Satisfaction Problem to improve performance. In DCS-RANSAC, however, the dataset is based on pattern of feature distribution of images manually, so this algorithm cannot classify the input image, pattern of feature distribution is not recognized in DCS-RANSAC algorithm, which lead to reduce it's performance. To improve this problem, we suggest the KCS-RANSAC algorithm using K-means clustering in CS-RANSAC to cluster the images automatically based on pattern of feature distribution and apply constraints to each image groups. The suggested algorithm cluster the images automatically and apply the constraints to each clustered image groups. The experiment result shows that our KCS-RANSAC algorithm outperformed the DCS-RANSAC algorithm in terms of speed, accuracy, and inlier rate.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.3
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• pp.25-34
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• 2014

The purposes of this study are two folds: (a) to identify the influences of tourism on subjective well-being, and (b) to understand the roles of travel motivation, constraint and personal value in subjective well-being. A polling agency was employed to select 500 respondents by quota sampling, and data was collected by online survey. ANOVA and regression results showed that tourism participants, compared to the non-participants, have a tendency to select tourism as a mean to enhance their subjective well-being because they are more self-motivated people. Their high motivation to take a trip lead to set up their feasible goals to achieve by the tourism experience and their relatively few constraints help them to have trip easily. The people's satisfaction in tourism contributes to the satisfaction in his/her leisure life, which in turn contributes to his/her subjective well-being. It is also revealed that tourism participation and subjective income level are significant variables affecting subjective well-being, which explain 21.1 percent of the variance. The research suggests various managerial implications to reduce constraints and several ideas for future researches.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.307-312
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• 2016

Markerless tracking for augmented reality using Homography can augment virtual objects correctly and naturally on live view of real-world environment by using correct pose and direction of camera. The RANSAC algorithm is widely used for estimating Homography. CS-RANSAC algorithm is one of the novel algorithm which cooperates a constraint satisfaction problem(CSP) into RANSAC algorithm for increasing accuracy and decreasing processing time. However, CS-RANSAC algorithm can be degraded performance of calculating Homography that is caused by selecting feature points which estimate low accuracy Homography in the sampling step. In this paper, we propose feature point filtering method based on CS-RANSAC for efficient planar Homography estimating the proposed algorithm evaluate which feature points estimate high accuracy Homography for removing unnecessary feature point from the next sampling step using Symmetric Transfer Error to increase accuracy and decrease processing time. To evaluate our proposed method we have compared our algorithm with the bagic CS-RANSAC algorithm, and basic RANSAC algorithm in terms of processing time, error rate(Symmetric Transfer Error), and inlier rate. The experiment shows that the proposed method produces 5% decrease in processing time, 14% decrease in Symmetric Transfer Error, and higher accurate homography by comparing the basic CS-RANSAC algorithm.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.11-22
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• 2004

A distributed constraint satisfaction problem (distributed CSP) is a constraint satisfaction problem(CSP) in which variables and constraints are distributed among multiple automated agents. ACSP is a problem to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of AI problems can be formalized as CSPs. Similarly, various application problems in DAI (Distributed AI) that are concerned with finding a consistent combination of agent actions can be formalized as distributed CAPs. In recent years, many new backtracking algorithms for solving distributed CSPs have been proposed. But most of all, they have common drawbacks that the algorithm assumes the priority of agents is static. In this thesis, we establish a basic algorithm for solving distributed CSPs called dynamic priority search algorithm that is more efficient than common backtracking algorithms in which the priority order is static. In this algorithm, agents act asynchronously and concurrently based on their local knowledge without any global control, and have a flexible organization, in which the hierarchical order is changed dynamically, while the completeness of the algorithm is guaranteed. And we showed that the dynamic priority search algorithm can solve various problems, such as the distributed 200-queens problem, the distributed graph-coloring problem that common backtracking algorithm fails to solve within a reasonable amount of time. The experimental results on example problems show that this algorithm is by far more efficient than the backtracking algorithm, in which the priority order is static. The priority order represents a hierarchy of agent authority, i.e., the priority of decision-making. Therefore, these results imply that a flexible agent organization, in which the hierarchical order is changed dynamically, actually performs better than an organization in which the hierarchical order is static and rigid. Furthermore, we describe that the agent can be available to hold multiple variables in the searching scheme.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.801-808
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• 2013

In the virtual space with the interactive 3D contents, the degree of mental satisfaction is determined by how fully it reflect the real world. There are a few factors for getting the high completeness of virtual space. The first is the modeling technique with high-polygons and high-resolution textures which can heighten an visual effect. The second is the functionality. It is about how realistic represents dynamic actions between the virtual space and the user or the system. Although the studies on the techniques for animating and controlling the virtual characters have been continued, there are problems such that the long production time, the high cost, and the animation without expected behaviors. This paper suggest a method of behavior control of animation by designing the optimized skeleton which produces the movement of character and applying the procedural technique using physical law and mathematical analysis. The proposed method is free from the constraint on one-to-one correspondence rules, and reduce the production time by controlling the simple parameters, and to increase the degree of visual satisfaction.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.4
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• pp.49-63
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• 2020

Municipal governments today are facing increasingly complex issues while resources continue to be constraint but the service quality expectation from citizen is more demanding. They must develop and implement tools that help manage operations more efficiently. While Lean Six Sigma principle and tools have been widely applied to profit organizations, the extant literature has not provided many cases of such application to local governments. This research presents a case study of applying Lean Six Sigma approaches and tools to a municipal government of a small town in USA to improve process efficiency, quality performance, and citizen satisfaction. In this case study, DMAIC (Define, Measure, Analyze, Implement, and Control) is used as a tool to define current issues, develop, and measure performance metrics, and recommend action plans. The result of this case study shows that applying the principles and tools of Lean Six Sigma provides an excellent way to improve the process efficiency and quality of providing public work services at a local government.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.9
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• pp.1521-1526
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• 2007

This paper presents the application of Adaptive Evolutionary Algorithm (AEA) to search an optimal setting of overcurrent relay coordination to protect ring distribution systems. The AEA takes the merits of both a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner to use the global search capability of GA and the local search capability of ES. The overcurrent relay settings and coordination requirements are formulated into a set of constraint equations and an objective function is developed to manage the overcurrent relay settings by the Time Coordination Method. The domain of overcurrent relays coordination for the ring-fed distribution systems is a non-linear system with a lot of local optimum points and a highly constrained optimization problem. Thus conventional methods fail in searching for the global optimum. AEA is employed to search for the optimum relay settings with maximum satisfaction of coordination constraints. The simulation results show that the proposed method can optimize the overcurrent relay settings, reduce relay mis-coordinated operations, and find better optimal overcurrent relay settings than the present available methods.

• Journal of the Korean housing association
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• v.13 no.5
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• pp.51-58
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• 2002

The purpose of this study is to examine residents' perception and needs for storage according to the family life cycle. In order to achieve our goal, the questionnaire survey is used. We sample the questionnaire surveys of 250 apartment households in Seoul. The data collect by the questionnaire survey was analyzed by examining the frequency, percentage on the SPSS/PC+ Statistics package. The results of the study are obtained as follows: 1) In research on the actual storage condition, residents tend to feel constraint on storage of the season goods and the storage satisfaction on the service area is founded lowest. Therefore, it is needed more efficient space plan on the balcony storage and the interior storage for the season goods. 2) In research on the storage consciousness and attitude, residents tend to keep the goods of no use and prefer to arrange neatly rather than use conveniently. Therefore, it is needed more efficient space in the balcony for the storage of the goods of no use and the colsed furniture rather than the open furniture is suited for arrangement. 3) In research on the storage needs, needs for the built-in furniture in all family life cycle show highly and residents want to a space for the exclusive use of the storage. In a solution, we propose to equip with the interior storage and the exterior cooperative storage

• Journal of applied mathematics & informatics
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• v.8 no.1
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• pp.181-197
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• 2001

A heuristic method TABU-CSP using Tabu Search (TS) is described for solving Constraint Satisfaction Problems (CSPs). The method is started with a complete but inconsistent solution of a binary CSP and obtained in prespecified number of iterations either a consistent solution or a near optimal solution with an acceptable number of conflicts. The repair in the solution at each iterative step is done by using two heuristics alternatively. The first heuristic is a min-conflicts heuristic that chooses a variable with the maximum number of conflicts and reassigns it the value which leads to the minimum number of conflicts. If the acceptable solution is not reached after the search continued for a certain number of iterations, the min-conflict heuristic is changed and the variable selected least number of times is chosen for repair. If an acceptable solution is not reached, the method switches back to the min-conflict heuristic and proceeds further. This allowed the method to explore a different region of search space space for the solution as well as to prevent cycling. The demonstration of the method is shown on a toy problem [9]which has no solution. The method is then tested on various randomly generated CSPs with different starting solutions. The performance of the proposed method in terms of the average number of consistency is checked and the average number of conflicts is conflicts is compared with that of the Branch and Bound(BB) method used to obtain the same solution. In almost all cases, the proposed method moves faster to the acceptable solution than BB.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.239-249
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• 2001

Competitive coevolution models, often called host-parasite models, are searching models that imitate the biological coevolution that is a series of reciprocal changes in two competing species. The models are known to be an effective method of solving complex and dynamic problems such as game problems, neural network design problems and constraint satisfaction problems. However, previous models consider only ectoparasites that live on the outside of the host when designing the models, not considering endoparasites that live on the inside of the host. This has a limitation to exploiting some information. In this paper, we develop an artificial adaptation model simulating the process in which hosts coevolve with both ectoparasites and endoparasites. In the model, the endoparasites play important roles as follows. By means of them, we can keep the history on results of previous competition between hosts and parasites, and use endogeneous fitness, not exogeneous. Extensive experiments are carried out to show the coevolution phenomenon and to verify the performance of the proposed model. Nim game problems and neural network problems are used as test-bed problems. The results are reported in this paper.