• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.125-137
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• 2012

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. For such reason, lots of intrusion detection system has been developed. Intrusion detection system has abilities to detect abnormal behavior and unknown intrusions also it can detect intrusions by using patterns studied from various penetration methods. Various algorithms are studying now such as the statistical method for detecting abnormal behavior, extracting abnormal behavior, and developing patterns that can be expected. Etc. This study using clustering of data mining and association rule analyzes detecting areas based on two models and helps design detection system which detecting abnormal behavior, unknown attack, misuse attack in a large network.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1563-1570
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• 1999

In this paper, we proposed the FPA(Fixed Partition Averaging) algorithm in order to improve the storage requirement and classification time of Memory Based Reasoning method. The proposed method enables us to use the storage more efficiently by extracting representatives out of training patterns. After partitioning the pattern space into a fixed number of equally-sized hyperrectangles, it averages patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.56-65
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• 1993

This paper presents the design consideration of the MFNNs(Multilayer Feed forward Neural Networks) based on the distribution of the given teching patterns. By extracting the feature points from the given teaching patterns, the structure of a network including the netowrk size and interconnection weights of a network is initialized. This network is trained based on the modified version of the EBP(Error Back Propagation) algorithm. As a result, the proposed method has the advantage of learning speed compared to the conventional learning of the MFNNs with randomly chosen initial weights. To show the effectiveness of the suggested approach, the simulation result on the approximation of a two demensional continuous function is shown.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.101-112
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• 1998

Data mining, which is also referred to as knowledge discovery in database, means a process of nontrivial extraction of implicit, previously unknown and potentially useful information (such as knowledge rules, constraints, regularities) from data in databases. The discovered knowledge can be applied to information management, decision making, and many other applications. In this paper, a new data mining problem, discovering sequential patterns, is proposed which is to find all sequential patterns using sampling method. Recognizing that the quantity of database is growing exponentially and transaction database is frequently updated, sampling method is a fast algorithm reducing time and cost while extracting the trend of customer behavior. This method analyzes the fraction of database but can in general lead to results of a very high degree of accuracy. The relaxation factor, as well as the sample size, can be properly adjusted so as to improve the result accuracy while minimizing the corresponding execution time. The superiority of the proposed algorithm will be shown through analyzing accuracy and efficiency by comparing with Apriori All algorithm.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.1
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• pp.163-180
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• 2019

A pattern is a symbolic mark of the psychological expression and ornamental desire of the human interior. In particular, plant patterns, from ancient times to modern times, express beauty across both the east and the west. The Joseon dynasty had a strong national will, and it was a time when the symbolism of Korea was established. Plant patterns were decorative and symbolic, filled with meaning in both the textile and craft sectors. This study looked at the frequency and figurative characteristics of the types of plant patterns in textiles, ceramics, woodworking, and metal craftsmanship of the Joseon dynasty. In addition, pattern designs were developed by extracting unit patterns to maintain the original shape, and by adding, magnifying, reducing, and superimposing flat steps and employing the four-fold sequence. The data collected was 826 examples in textiles and crafts, and 34 species of plants were analyzed as follows. In general, the flower patterns preferred soft flowers, flowers, apricot, and peony patterns, and fruit patterns emerged as decorative designs for pottery and woodwork from the 17th century, featuring pomegranates, grapes, fluorines, peaches, and walnut floss. Textiles and woodwork were arranged with many circular designs, while pottery and metal crafts were filled in many ways. Expressive types appeared to be the same as stylistic types for textiles and ceramics, and the construction types were the same in pottery and metal crafts. As such, it was found that even in the different areas of the sculpture, the same aesthetic values were reflected in the common figurative features today. Therefore, in this study, we developed a unique and competitive pattern design that accommodates the modern times and the Joseon dynasty. This development is expected to contribute not only to the development of cultural and tourism products in the future, but also to the tourism industry induced by the Korean wave.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.11
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• pp.15-20
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• 2004

This paper proposed a very simple method of extracting an effective permittivity from the data of scattering parameters measured on the transmission line of coplanar waveguides in the frequency range of microwave or millimeter waves. This is an extracting method of an effective permittivity $\varepsilon$$_{eff}$ in the case of $\beta$$\ell$ =n$\pi$ (n=integer), where the value of S$_{11}$ changes abruptly following the operating frequency. The experimental value of the effective permittivity $\varepsilon$$_{eff}$ on a dielectric substrate of Rogers 4003$^{TM}$ material of $\varepsilon$$_{r}$ =3.38 showed the value of 2.042, which differs in the error of -3.4% to 8% from those calculated from the previously reported formulae. This result showed that the measurement method was very simple, as well as applied directly to the fabricated circuit patterns, even though the circuit patterns might be complicated or on the substrate of different dielectric materials.s.als.

• Journal of the Korean Society of Food Science and Nutrition
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• v.15 no.1
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• pp.22-26
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• 1986

This investigation was carried out to study the effect of heating treatment on the saponin fractions in ginseng extract and crude saponin. The changes of saponin patterns and amounts were investigated using HPLC and compared with peak area of each fraction. Shape of crude saponin was changed more easy to compare with in ginseng extract. The more extracting temperature risen and treated time longer, the more changes of saponin amounts and patterns were shown, expecially at $100^{\circ}C$ over. All of the saponin fraction except ginsenoside-Rd were relatively unstable in heating treatment. Suitable extracting condition was extracted at $80^{\circ}C$ for 40 hours with $H_2O$.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.51-60
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• 2021

Due to the growth of digital media technology, there is increasing demand of personalized education based on context data of learners throughout overall education area. For music education, several studies have been conducted for providing appropriate educational contents to learners by considering some factors such as the proficiency, the amount of practice, and their capability. In this paper, a technique has been defined to recommend the appropriate music scores to learners by extracting and analyzing the practice data and chord data. Concretely, several meaningful relationships among chords patterns and learners were analyzed and visualized by constructing the learners' profiles of proficiency, extracting the chord sequences from music scores. In addition, we showed the potential for use in personalized education by analyzing music similarity, learner's proficiency similarity, learner's proficiency of music and chord, mastered chords and chords sequence patterns. After that, the chord practice programs can be effectively generated considering various music scores using the synthetically summarized chord sequence graphs for the music scores that the learners selected.

• Journal of Internet Computing and Services
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• v.5 no.1
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• pp.1-13
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• 2004

The effect of Application system with class units is not sufficient because of independency and reuse of Component elements due to component abstraction based on only source code. Therefore We need to apply design pattern approach to represent not only the problem abstraction but also information and relationship between system elements for generic solutions of specific domain, Also, it is essential to software reverse engineering acquiring the correct understandings of the system through examining the existing systems and utilizing the acquired knowledges as reusable resources. In this paper, the extraction algorithm with JAVA and the validity of applying reverse engineering with extracting design patterns from source codes of the existing object-oriented system; are devised. The architecture of automatic tool is designed and implemented for 1) automatic extraction of design patterns and 2) reuse tool for retrieving, editing and rebuilding of design patterns.