• Journal of Intelligence and Information Systems
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• v.15 no.4
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• pp.123-140
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• 2009

Fuzzy neural network is an integrated model of artificial neural network and fuzzy system and it has been successfully applied in control and forecasting area. Recently ANFIS(Adaptive Network-based Fuzzy Inference System) has been noticed widely among various fuzzy neural network models because of outstanding performance of control and forecasting accuracy. ANFIS has capability to refine its fuzzy rules interactively with human expert. In particular, when we use initial rule structure for machine learning which is generated from human expert, it is highly probable to reach global optimum solution as well as shorten time to convergence. We propose metrics to evaluate interpretability of generated rules as a means of acquiring domain knowledge and compare level of interpretability of ANFIS fuzzy rules to those of C5.0 classification rules. The proposed metrics also can be used to evaluate capability of rule generation for the various machine learning methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1972-1978
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• 2010

AAM(Active Appearance Model) is one of the most effective ways to detect deformable 2D objects and is a kind of mathematical optimization methods. The cost function is a convex function because it is a least-square function, but the search space is not convex space so it is not guaranteed that a local minimum is the optimal solution. That is, if the initial value does not depart from around the global minimum, it converges to a local minimum, so it is difficult to detect face contour correctly. In this study, an AAM-based face tracking algorithm is proposed, which is robust to various lighting conditions and backgrounds. Eye detection is performed using SIFT and Genetic algorithm, the information of eye are used for AAM's initial matching information. Through experiments, it is verified that the proposed AAM-based face tracking method is more robust with respect to pose and background of face than the conventional basic AAM-based face tracking method.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.541-548
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• 2007

Due to the mathematical convergence property, Simulated Annealing (SA) has been one of the most popular optimization algorithms. However, because of its problem of slow convergence in the practical use, many variations of SA like Fast SA (FSA) have been developed for faster convergence. In this paper, we propose and prove that Greedy SA (GSA) also finds the global optimum in probability in the continuous space optimization problems. Because the greedy selection does not allow the cost to become worse, GSA is expected to have faster convergence than the conventional FSA that uses Metropolis selection. In the computer simulation, the proposed method is shown to have as good performance as FSA with Metropolis selection in the viewpoints of the convergence speed and the quality of the found solution. Furthermore, the greedy selection does not concern the cost value itself but uses only dominance of the costs of solutions, which makes GSA invariant to the problem scaling.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.363-384
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• 2011

As the complexity of software is increasing, generating an effective test data has become a necessity. This necessity has increased the demand for techniques that can generate test data effectively. This paper proposes a test data generation technique based on adequacy based testing criteria. Adequacy based testing criteria uses the concept of mutation analysis to check the adequacy of test data. In general, mutation analysis is applied after the test data is generated. But, in this work, we propose a technique that applies mutation analysis at the time of test data generation only, rather than applying it after the test data has been generated. This saves significant amount of time (required to generate adequate test cases) as compared to the latter case as the total time in the latter case is the sum of the time to generate test data and the time to apply mutation analysis to the generated test data. We also use genetic algorithms that explore the complete domain of the program to provide near-global optimum solution. In this paper, we first define and explain the proposed technique. Then we validate the proposed technique using ten real time programs. The proposed technique is compared with path testing technique (that use reliability based testing criteria) for these ten programs. The results show that the adequacy based proposed technique is better than the reliability based path testing technique and there is a significant reduce in number of generated test cases and time taken to generate test cases.

• Journal of the military operations research society of Korea
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• v.32 no.2
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• pp.78-91
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• 2006

Recently mass customization has become a new paradigm in the global market to satisfy both the diversified demands of customers but also the efficiency of the mass production system. In this paper, mass customization is embodied by a new product development method with which various product families are produced from standard "product platform" developed from historical data. The product platform, the key concept of this proposed method, is significantly efficient as a solution to the customer demand of high variety and small quantity products. The proposed method is applied to build the platform family of naval ships, utilizing the concept of "Group Technology". In addition, cost effectiveness of the proposed method is analyzed and the applicable range of requirement conditions are presented. In conclusion, some remarkable effects such as reduction in production cost and development time are expected by employing this method to the procurement process of the naval ships.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.175-182
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• 2016

In the 21st century knowledge and information society, Electronic Contracts made with the intention of electronic computer information networks are emerging as a new legal problem which can not be solved in the conventional legal system governing contracts. In other words, the indicator's decision determines the effect and formation of the contracts in the face-to-face or written contracts but electronic decision through computer information network is established the working process of electronic signals-electronic contracts are not only difficult to separate the decision-making process but questioned to be solved by the theory of the general legal action. Ministry of Transportation is scheduled to introduce real estate sales and lease contract using a variety of electronic devices such as computer, tablet PC, smart phones and so on without a paper contract. This system is conducted to global expansion of Seoul in demonstration zone on May 8, 2016 and will be implemented nationwide in the second half of 2017. Electronics contract Real estate has some benefits because made by linking electronic contract system and the electronic registration system - the economic effects discounts on various kinds of fees, the prevention from real estate fraud beforehand and the solution to the complexity of the process the seller and the buyer visits The Real estate agency. However, it has some problem- the disorder in the real estate contract market, the occurrence of the real estate agency accident and the author of the electronic real estate contracts have limited only to realtor. In this paper, I suggest the activation plan to search for establishment and effect of electronic contracts and declaration of intention in electronic depending on the Electronic Contract Real Estate system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.60-69
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• 2013

Highlighted by recent security breaches including Google, Western Energy Company, and the Stuxnet infiltration of Iranian nuclear sites, Cyber warfare attacks pose a threat to national and global security. In particular, targeted attacks such as APT exploiting a high degree of stealthiness over a long period, has extended their victims from PCs and enterprise servers to government organizations and critical national infrastructure whereas the existing security measures exhibited limited capabilities in detecting and countermeasuring them. As a solution to fight against such attacks, we designed and implemented a security monitoring system, which shares security information and helps cooperative countermeasure. The proposed security monitoring system collects security event logs from heterogeneous security devices, analyses them, and visualizes the security status using 3D technology. The capability of the proposed system was evaluated and demonstrated throughly by deploying it under real network in a ISP for a week.

• Journal of Korean Society of Steel Construction
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• v.21 no.4
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• pp.361-373
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• 2009

Using the genetic algorithm, the optimal-design technique of the Nielsen arch bridge was proposed in this paper. The design parameters were the arch-rise ratio and the steel weight ratio of the Nielsen arch bridge, and optimal-design techniques were utilized to analyze the behavior of the bridge. The optimal parameter values were determined for the estimated optimal level. The parameter determination requires the standardization of the safety, utility, and economic concepts as the critical factors of a structure. For this, a genetic algorithm was used, whose global-optimal-solution search ability is superior to the optimization technique, and whose object function in the optimal design is the total weight of the structure. The constraints for the optimization were displacement, internal stress, and time and space. The structural analysis was a combination of the small displacement theory and the genetic algorithm, and the runtime was reduced for parallel processing. The optimal-design technique that was developed in this study was employed and deduced using the optimal arch-rise ratio, steel weight ratio, and optimal-design domain. The optimal-design technique was presented so it could be applied in the industry.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.84-91
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• 2006

In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

• Journal of Global Scholars of Marketing Science
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• v.16 no.1
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• pp.13-26
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• 2006

In this research, we develope a procedure for detecting a random non-stationarity to the individual's purchasing rate in a stationary NED model. On this purpose, we derive the likelihood ratio statistic for a testing null and alternative hypotheses defined as whether there is no significant structural change in a stationary NED model or any. Where the structural change comes from a random non-stationarity(marketing mix activities or seasonality, for example) to the individual's purchasing rate. We also apply the developed method to a panel data for a frequently purchased good. This research could be a solution to include the non-stationarity in a stationary NED model. We also expect that the developed model could give a signal for an early detection of significant changes in marketing environment, and a mean for a measurement of the effects of marketing mix activities.