• Journal of Internet of Things and Convergence
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• v.3 no.2
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• pp.33-39
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• 2017

The purpose of this study is to analyze the characteristics of talents required in electronic companies in the 4th industrial revolution. we conducted a network analysis on the key talent of the companies presented in over 100 job announcements to companies in the electronics industry. The results of the study are as follows. First, electronic companies showed the most favored creative talents, preferring collaborative talent and challenging talent. Second, looking at the core definitions of talent, change, response, problem solving, performance creation, communication, challenge, professionalism, enthusiasm, development, aggressiveness and spontaneity were used. In other words, key keywords emerging from the 4^th industrial revolution were being used continuously. Third, in the Centrality analysis, talented people who emphasize humanity also appeared. Based on the study, it suggested that manpower training of the 4^th Industrial Revolution.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.149-156
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• 2010

Since the premature convergence phenomenon of genetic algorithms (GAs) degrades the performances of GAs significantly, solving this problem provides a lot of effects to the performances of GAs. In this paper, we propose a selective mutation method in order to improve the performances of GAs by alleviating this phenomenon. In the selective mutation, individuals are additionally mutated at the specific region according to their ranks. From this selective mutation, individuals with low ranks are changed a lot and those with high ranks are changed small in the phenotype. Finally, some good individuals search around them in detail and the other individuals have more chances to search new areas. This results in enhancing the performances of GAs through alleviating of the premature convergence phenomenon. We measured the performances of our method with four typical function optimization problems. It was found from experiments that our proposed method considerably improved the performances of GAs.

• KIISE Transactions on Computing Practices
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• v.20 no.12
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• pp.694-699
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• 2014

In mobile ad-hoc networks (MANET), the network topology and neighboring nodes change frequently, since MANET is composed of nodes that have mobility without a fixed network infrastructure. The AODV routing protocol is advantageous for MANET, but AODV has a delay in the transmission of data packets because AODV can not transmit data during route recovery. This paper proposes solving the above problem of AODV by using a bypass generation mechanism for data transmission during route recovery. For further improvement, additional mechanisms that coordinate the reception threshold of a hello packet are proposed in order to improve the accuracy of the information obtained from the neighboring nodes when the bypass is generated due to a link failure and the immediacy of the route recovery. Simulation results show that the proposed technique improves the performance in terms of the delay in transmission compared to traditional AODV.

• Journal of KIISE:Databases
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• v.35 no.3
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• pp.243-256
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• 2008

With rapid growth of Internet, the amount of information in the Web is increasing exponentially. However, information on the current Web is understandable only for human, and thus it makes the exact information retrieval difficult. For solving this problem, the Semantic Web is suggested and we must use ontology languages that can endow data to semantics for implementing it. One of the representative ontology languages is OWL(Web Ontology Language) adopted as a recommendation by the World-Wide Web Consortium. OWL has richer expression power and formal semantics than other ontology languages such as RDF and RDF-S. In addition, OWL includes hierarchical structure information between classes or properties. Therefore, an efficient OWL storage model considering hierarchical structure for effective information retrieval on the Semantic Web is required. In this paper, we suggest the XPOS(XPath-based OWL Storage) model including hierarchy information between classes or properties as XPath form and enabling intuitive and effective information retrieval. Also, we show the comparative evaluation results on the performance of XPOS model, Sesame, and the XML storage-based storage model regarding query processing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10C
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• pp.621-628
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• 2011

The skin color has been used as important cues in the systems for detecting or recognizmg the face. However, the color difference in images under different illuminants makes it difficult to find out the skin in these systems. For solving the problem, this paper proposes a method of recovering skin colors based on well-known color constancy approaches, such as Retinex, Gray World, White Patch, and Simplified Horn. To acquire experimental images under the colored scene illumination, the effects of colored illuminants were added to source images. Next, result images, having the corrected skin color by the constancy methods, were derived from the source images. The experiment results showed that most of the skin colors in our experiments were recovered into some steady range in the color space, and that Gray World had higher performance than the other methods compared.

• The Journal of Society for e-Business Studies
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• v.18 no.4
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• pp.195-214
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• 2013

Case-based reasoning is a methodology for solving problems more quickly and efficiently by bringing the most similar case of a given problem from past cases and transforming it to fit the current situation. The most important performance indicator of case-based reasoning is the number of cases, so it is difficult to apply the methodology for the area which has not enough cases. In this paper, we proposed a method to exchange cases based on the Semantic Web in order to overcome the problems. Inparticular, we separated cases into sub-cases to make it possible creating new cases by combining the appropriate sub-cases even if there was no proper full case. In order to achieve that, we designed an ontology that connects a case and its sub-cases, represents detailed similarity rules that compare sub-cases, and represents the rules for the combination of sub-cases. Moreover, we designed and implemented a semantic distributed case-based reasoning framework where a case requester can request sub-cases via the Web from case providers and integrates sub-cases into a new case by using the ontology.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.21 no.3
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• pp.147-152
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• 2010

Objectives : The purpose of this study was to investigate the deficits in executive function in children with ADHD and anxiety disorder, and further, to characterize executive function deficits among the two groups. Methods : Subjects consisted of 60 children between the ages of 5 and 14 (16 Normal, 24 ADHD, 20 Anxiety Disorder). Neuropsychological tests (KEDI-WISC, CCTT, STROOP, WCST, ROCF) for assessing cognitive and executive function were individually administered to all subjects. Results : There were no significant differences in FSIQ or PIQ among the three groups. However, the ADHD group tended to score lower on the VIQ and subtest of similarity, vocabulary, and digit span tests. The three groups did not significantly differ with respect to CCTT test results. On the STROOP test, the ADHD group showed poor performance on the word, color, and color-word subtests. The three groups did not exhibit significant differences in WCST test results ; however, the anxiety group performed poorly belonging to below 25 percentile rank on perseverative response. On the ROCF test, the ADHD group performed poorly with respect to their organization score and in particular, regarding copy and immediate recall. The anxiety group also performed poorly with regard to organization ; however, this was limited only to immediate recall. Conclusion : Children with ADHD displayed poor inhibition and organizational abilities compared to children with anxiety and normal controls. Further, children with anxiety disorder exhibited low cognitive flexibility and voluntary problem-solving abilities compared to ADHD children and normal controls. Based on these results, we suggest that the characteristics of executive dysfunction in ADHD and anxiety disorder in children are different.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.5
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• pp.517-524
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• 2004

The fuzzy set theory has been wide used in clustering of machine learning with data mining since fuzzy theory has been introduced in 1960s. In particular, fuzzy C-means algorithm is a popular fuzzy clustering algorithm up to date. An element is assigned to any cluster with each membership value using fuzzy C-means algorithm. This algorithm is affected from the location of initial cluster center and the proper cluster size like a general clustering algorithm as K-means algorithm. This setting up for initial clustering is subjective. So, we get improper results according to circumstances. In this paper, we propose a cluster merging using enhanced density based fuzzy C-means clustering algorithm for solving this problem. Our algorithm determines initial cluster size and center using the properties of training data. Proposed algorithm uses grid for deciding initial cluster center and size. For experiments, objective machine learning data are used for performance comparison between our algorithm and others.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.112-119
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• 2010

This paper defines the probability models for determining the disparity map given stereo images and derives the methods for solving the problem, which is proven to be equivalent to an energy-based stereo matching. Under the assumptions the difference between the pixel on the left image and the corresponding pixel on the right image and the difference between the disparities of the neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameter is proposed. Usually energy-based stereo matching methods are so sensitive to the parameter that it should be carefully determined. The proposed method alternates between estimating the parameter with the intermediate disparity map and estimating the disparity map with the estimated parameter, after computing it with random initial parameter. It is shown that the parameter estimated by the proposed method converges to the optimum and its performance can be improved significantly by adjusting the parameter and modifying the energy term.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.8
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• pp.921-931
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• 2011

This paper presents a data-fitting technique in which a B-spline hypervolume is used to approximate a given data set of scattered data samples. We describe the implementation of the data structure of a B-spline hypervolume, and we measure its memory size to show that the representation is compact. The proposed technique includes two algorithms. One is for the determination of the knot vectors of a B-spline hypervolume. The other is for the control points, which are determined by solving a linear least-squares minimization problem where the solution is independent of the data-set complexity. The proposed approach is demonstrated with various data-set configurations to reveal its performance in terms of approximation accuracy, memory use, and running time. In addition, we compare our approach with existing methods and present unconstrained optimization examples to show the potential for various applications.