• Journal of Industrial Convergence
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• v.21 no.9
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• pp.123-132
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• 2023

I think it would be better to rewrite the Korean abstract. To analyze the personal characteristics of the participants and identify their perception of violence using the Q methodology, the scores of 20 parenting parents on 25 Q cards were statistically analyzed using forced normal distribution. There are three factors and from the most agreeable to the most disagreeable statements, they have shown their perception of violence. It was helpful in identifying parents' subjective perceptions and types of child abuse, and it suggested the need to define child abuse so that parents can have a correct perception of child abuse, rather than an abstract perception. In this perspective, the results of this study provide preliminary data for improving the recognition of parenting parents on child abuse.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.48-60
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• 2024

With the exponential growth of satellite data utilization, machine learning has become pivotal in enhancing innovation and cybersecurity in satellite systems. This paper investigates the role of machine learning techniques in identifying and mitigating vulnerabilities and code smells within satellite software. We explore satellite system architecture and survey applications like vulnerability analysis, source code refactoring, and security flaw detection, emphasizing feature extraction methodologies such as Abstract Syntax Trees (AST) and Control Flow Graphs (CFG). We present practical examples of feature extraction and training models using machine learning techniques like Random Forests, Support Vector Machines, and Gradient Boosting. Additionally, we review open-access satellite datasets and address prevalent code smells through systematic refactoring solutions. By integrating continuous code review and refactoring into satellite software development, this research aims to improve maintainability, scalability, and cybersecurity, providing novel insights for the advancement of satellite software development and security. The value of this paper lies in its focus on addressing the identification of vulnerabilities and resolution of code smells in satellite software. In terms of the authors' contributions, we detail methods for applying machine learning to identify potential vulnerabilities and code smells in satellite software. Furthermore, the study presents techniques for feature extraction and model training, utilizing Abstract Syntax Trees (AST) and Control Flow Graphs (CFG) to extract relevant features for machine learning training. Regarding the results, we discuss the analysis of vulnerabilities, the identification of code smells, maintenance, and security enhancement through practical examples. This underscores the significant improvement in the maintainability and scalability of satellite software through continuous code review and refactoring.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.69-75
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• 2007

The information in physical planning field shows the socio-economic potentials of land resources while cadastral data does the physical and legal realities of the land. The two domains commonly deal with land information but have different views. Cadastre has to evolved to the multi-purpose ones which provide value-added information and support a wide spectrum of decision makers by mixing their own information with other spatial/non-spatial databases. In this context, the demands of data exchange between the two domains is growing up but this cannot be done without resolving the heterogeneity between the two information applications. Both of either discipline sees the reality within its own scope, which means each has a unique way to abstract real world phenomena to the database. The heterogeneity problem emerges when an GIS is autonomously and independently established. It causes considerable communication difficulties since heterogeneity of representations forms unique data semantics for each database. The semantic heterogeneity obviously creates an obstacle to data exchange but, at the same time, it can be a key to solve the problems too. Therefore, the study focuses on facilitating data sharing between the fields of cadastre and physical planning by resolving the semantic heterogeneity. The core job is developing a conversion mechanism of cadastral data into the information for the physical planning by DB coupling techniques.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.222-236
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• 1997

Conventional solid or surface modeling systems cannot represent both the complete solid model and the abstract model in a unified framework. Recently, non-manifold modeling systems are proposed to solve this problem. This paper describes FlexDesigner, an open kernel system for modeling non-manifold models. It summarizes the data structure for non-manifold models, system design methodology, system modularization, and the typical characteristics of each module in the system. A data structure based on partial-topological elements is adopted to represent the relationship among topological elements. It is efficient in the usage of memory and has topological completeness compared with other published data structures. It can handle many non-manifold situations such as isolate vertices, dangling edges, dangling faces, a mixed dimensional model, and a cellular model. FlexDesigner is modularized hierarchically and designed by the object-oriented methodology for reusability. FlexDesigner is developed using the C++ and OpenGL on both SGI workstation and IBM PC.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.178-179
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• 2011

The exchange of information with legacy systems is a main issue in the era of SMARTGRID. Because WAMAC(Wide Area Monitoring and Control) system has monitoring function, as well as control function, it is very necessary for WAMAC to exchange data and information with SCADA(Supervisory Control and Data Acquisition) / EMS(Energy Management System). IEC 61970 CIM(Common Information Model) is an abstract model that represents all the major objects in an electric utility enterprise typically involved in utility operations. In this paper, a proposal that adopting CIM to WAMAC model be submitted so that the integration of various legacy system and application for itself be able to be flexible.

• Journal of Information Technology Applications and Management
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• v.23 no.3
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• pp.1-12
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• 2016

Visual representations for concepts in business management are quite challenging, especially those abstract concepts in Accountancy discipline. For example, there might not be a consensus on what to use to represent such abstraction as an asset, liability, or owner equity. This is because asset can be property, estate, resources, equipment, or any tangible or non-tangible valuables. Cognitive science concepts and behavior engagement have been used to develop visual representations for financial data. The concepts include spatial processing, big picture thinking, and metaphor. Review of past studies together with a brief research plan to test the usability for learning of four new augmented reality 0visuals are provided in the present paper.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.543-554
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• 2013

Model-Driven Development(MDD) helps developers verify requirements and design issues of a software system in the early stage of development process by taking advantage of a software model which is the most highly abstracted form of a software system. In practice, however, many software systems have been developed through a code-centric method that builds a software system bottom-up rather than top-down. So, without support of appropriate tools, it is not easy to introduce MDD to real development process. Although there are many researches about extracting a model from code to help developers introduce MDD to code-centrically developed system, most of them only extracted base-level models. However, using concept of abstract component one can continuously extract higher level model from base-level model. In this paper we propose a practical method for automatic extraction of base level abstract component from source code, which is the first stage of continuous extraction process of abstract component, and validate the method by implementing an extraction tool based on the method. Target code chosen is the source code of TinyOS, an operating system for wireless sensor networks. The tool is applied to the source code of TinyOS, written in nesC language.

• Journal of KIISE:Software and Applications
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• v.26 no.9
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• pp.1114-1124
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• 1999

클러스터링은 동일한 클러스터에 속하는 데이타들 간에는 유사도가 크도록 하고 다른 클러스터에 속하는 데이타들 간에는 유사도가 작도록 주어진 데이타를 몇 개의 클러스터로 묶는 것이다. 어떤 대상을 기술하는 데이타는 수치 속성뿐만 아니라 정성적인 비수치 속성을 갖게 되고, 이들 속성값은 관측 오류, 불확실성, 주관적인 판정 등으로 인해서 정확한 값으로 주어지지 않고 애매한 값으로 주어지는 경우가 많다. 본 논문에서는 애매한 값을 퍼지값으로 표현하는 수치 속성과 비수치 속성을 포함한 데이타에 대한 비유사도 척도를 제안하고, 이 척도를 이용하여 퍼지값을 포함한 데이타에 대하여 퍼지 클러스터링하는 방법을 소개한 다음, 이를 이용한 실험 결과를 보인다. Abstract The objective of clustering is to group a set of data into some number of clusters in a way to minimize the similarity between data belonging to different clusters and to maximize the similarity between data belonging to the same cluster. Many data for real world objects consist of numeric attributes and non-numeric attributes whose values are fuzzily described due to observation error, uncertainty, subjective judgement, and so on. This paper proposes a dissimilarity measure applicable to such data and then introduces a fuzzy clustering method for such data using the proposed dissimilarity measure. It also presents some experiment results to show the applicability of the proposed clustering method and dissimilarity measure.

• Journal of the Korean Chemical Society
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• v.36 no.5
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• pp.720-726
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• 1992

Multivariate analysis such as factor analysis was applied to interpret multivariate data, which were obtained from the overlapped X-ray fluorescence spectra. X-ray fluorescence spectra of 11 reference samples were obtained by the wavelength dispersive spectrometer at a specified range of angle such as $33.50∼34.50^{\circ}$. The data matrix was made from the spectra of 8 samples. The results of abstract factor analysis gave three factors. By the target testing with 8 elements contained in the reference samples, the three factors were found to be Pb, As and Cu. The concentration of these elements in the test samples was determined by target transformation factor analysis regardless overlapping individual peaks.

• The Research Journal of the Costume Culture
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• v.12 no.1
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• pp.59-72
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• 2004

The objectives of this study were to investigate the perceptions of Korean female university students for clothing pattern tendency and structural element of clothing pattern image dimension and to find how individual personality type influence the preferred clothing pattern characteristics. For this study, a questionnaire was designed and sent to 600 female university students of Daejeon, Seoul and metropolitan area. The tool used in this study was MBTI(The Myers-Briggs Type Indicator) Form G Korean version and for the analysis of data SPSS 10.0 package were used. 10 representative patterns for this study were floral, dot, stripe, check, animal, abstract & artistic, geometric, vegetable & leaf, paisely, patchwork pattern. The data were analyzed by factor analysis, arithmetic mean, One-Way ANOVA, x²-test. The major findings were as follows: Clothing pattern image dimension perceived by Korean female university students for 10 representative patterns were basic form, deluxe, specialty, and cultural dimension. Among them, basic form and deluxe dimension were major dimensions. In basic form dimension, dot pattern score was high indicating female students perceive it as light, comfortable, clean, cool and simple pattern image. In deluxe dimension, floral pattern scored high and in specialty dimension, abstract and artistic pattern scored high among other pattern image. In cultural dimension, geometric pattern and check pattern scored high. Based on other detailed analysis results, It is concluded that the personality type greatly influence clothing pattern evaluation. For example, in case of color combination of patchwork pattern, there was a difference in color preference depend on a personality type such as sensing(S) or intuition(N). Therefore, sensing personality type preferred adjacent color combination than contrast color combination. Detailed marketing strategy is necessary in planning textile design of merchandise plan.