• Korean Institute of Interior Design Journal
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• v.25 no.3
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• pp.31-39
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• 2016

This study is aimed to increase the possibility of using the Christopher Alexander's pattern language. The methodology of this study is (i) to analyze the pattern language by using the network analysis tool in order to understand the complicate network structure of the pattern language, and (ii) to apply the Alexander's method of using the pattern language by using the network analysis tool (Gephi) and to examine the feasibility of the network analysis tool as a tool for using the pattern language. Firstly, as a result of analysing the pattern language, (i) the pattern language classified by pattern number is distinguished by the patterns of towns, buildings and construction, among which the pattern of buildings plays a key function in the networks; (ii) the buildings functions a medium connecting between the towns and the construction; and (iii) the pattern language is divided into 6 sub-modules, through which the user can select a pattern. Secondly, the result of using the network analysis tool as a tool for using the pattern language (i) suggests the new method of using the pattern language by using the network analysis tool (Gephi); (ii) makes it possible to easily figure out the characteristics of the links between the patterns; and (iii) increases the completeness of the pattern language by making it easy to find out the sub-patterns in selecting a pattern.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.616-619
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• 2007

Nowadays, urbanized area expands its boundary, and distribution of urbanized area is gradually transformed into more complicated pattern. In Korea, SMA(Seoul Metropolitan Area) has outstanding urbanized area since 1950s. But it is ambiguous whether urban distribution is clustered or dispersed. This study aims to show the way in which expansion of urbanized area impacts on spatial distribution pattern of urbanized area. We use quadrat analysis, nearest-neighbor analysis and fractal analysis to know distribution pattern of urbanized area in time-series urban growth. The quadrat analysis indicates that distribution pattern of urbanized area is clustered but the cohesion is gradually weakened. And the nearest-neighbor analysis shows that point patterns are changed that urbanized area distribution pattern is progressively changed from clustered pattern into dispersed pattern. The fractal dimension analysis shows that 1972's distribution dimension is 1.428 and 2000's dimension is 1.777. Therefore, as time goes by, the complexity of urbanized area is more increased through the years. As a result, we can show that the cohesion of the urbanized area is weakened and complicated.

• Earthquakes and Structures
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• v.6 no.4
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• pp.437-455
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• 2014

Some conventional lateral load patterns for pushover analysis, and proposing a new accurate pattern was investigated in present research. The new proposed load pattern has load distribution according weight and stiffness variation in height and mode shape of structure. The assessment of pushover application with mentioned pattern in X type braced steel frames and steel moment resisting frames, with stiffness and mass variation in height, was studied completely and the obtained results were compared with nonlinear dynamic analysis method (including time history analysis). The methods were compared from standpoints of some basic parameters such as displacement, drift and shape of lateral load pattern. It is concluded that proposed load pattern results are closer to nonlinear dynamic analysis (NDA) compared to other pushover load patterns especially in tall and medium-rise buildings having different stiffness and mass during the height.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1209-1211
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• 2003

The wavelet and semivariogram analysis method are used to identify the city landscape and farmland landscape pattern on the 1m resolution IKONOS images. The results prove that wavelet method is a potential way for landscape pattern analysis. Compared to semivariogram analysis, Wavelet analysis can not only detect the overall spatial pattern, but also find multi-scale and direction structures. In this experiment, the wavelet analysis results indicate: (1) the city landscape image is mainly composed of three level structures whose spatial pattern characters appear at 2m, 16m, 128m and 256m accordingly; (2) the farmland landscape is mainly two scale spatial patterns appearing at the 2m, 128m and 256m. IKONOS Remote sensing, with the high spatial and spectral information, is a powerful tool that can use in many ecological systems research and sustainable management.

• Journal of Oriental Neuropsychiatry
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• v.26 no.4
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• pp.407-416
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• 2015

Objectives: This study was performed to evaluate the reliability and validity of the instrument on pattern identifications for depression. Methods: Two assessors carried out an evaluation about the instrument on pattern identifications for depression, targeting 201 participants, who after taking the HAM-D score over 12 or under 7 twice. Results: Inter-assessor reliability was higher than intra-assessor reliability in a reliability analysis about classification of pattern identification evaluated by the instrument on pattern identifications for depression. Reliability of intra-assessor and inter-assessor showed a moderate to strong agreement when reliability analysis about classification score of the pattern identification had been performed. Reliability analysis to evaluate the validity of the instrument on pattern identifications for depression showed moderate agreement. Conclusions: The results reveal that reliability analysis of the instrument on pattern identifications for depression showed an over moderate agreement and validity analysis represented a positive correlation.

• East Asian Journal of Business Economics (EAJBE)
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• v.7 no.4
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• pp.51-58
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• 2019

Purpose - This paper aims to analyze the difference of technological innovative pattern by industry. Research design and methodology - we try to identify the major factors which can exert an effective influence on actual innovation output, utilizing the result of Korean Innovation Survey. By doing so, this work can make a comparison with Pavitt (1984) and succeeding discussion on sectoral pattern of innovation Results - Analysis on major industry in Korea shows that there are substantial differences in terms of the source of innovation, organization-related factor, and appropriation mechanism among each industry, and differential strategy to be proper for the nature of each industry is needed. There is some variation within industries which deemed as same type of sector defined by Pavitt. Conclusions - This analysis call for elaborate analysis on sectoral pattern of innovation, considering the change and difference of innovative environment as well as differential business strategy and way to do innovate, which is proper considering the nature of innovative pattern in each industry for successful technological innovation in Korea. At the same time, proper policy measure considering the differential pattern of technological innovation is needed.

• Genomics & Informatics
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• v.4 no.4
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• pp.173-181
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• 2006

Pattern finding is one of the important tasks in a protein or DNA sequence analysis. Alignment is the widely used technique for finding patterns in sequence analysis. BLAST (Basic Local Alignment Search Tool) is one of the most popularly used tools in bio-informatics to explore available DNA or protein sequence databases. BLAST may generate a huge output for a large sequence data that contains various sequence patterns. However, BLAST does not provide a tool to summarize and analyze the patterns or matched alignments in the BLAST output file. BLAST lacks of general and robust parsing tools to extract the essential information out from its output. This paper presents a pattern summary system which is a powerful and comprehensive tool for discovering pattern structures in huge amount of sequence data in the BLAST. The pattern summary system can identify clusters of patterns, extract the cluster pattern sequences from the subject database of BLAST, and display the clusters graphically to show the distribution of clusters in the subject database.

• Archives of Pharmacal Research
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• v.15 no.4
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• pp.376-378
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• 1992

A chemical tool was developed for the analysis of complex mixtures such as crude drugs by the method of pattern recognition. Pattern recognition was accomplished by a multiple reference peak identification method and three kinds of outlier statistics. This tool was tested on the analysis of synthetic mixtures.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1118-1130
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• 2006

Existed pattern analysis algorithms in data streams environment have researched performance improvement and effective memory usage. But when new data streams come, existed pattern analysis algorithms have to analyze patterns again and have to generate pattern tree again. This approach needs many calculations in real situation that needs real time pattern analysis. This paper proposes a method that continuously analyzes patterns of incoming data streams in real time. This method analyzes patterns fast, and thereafter obtains real time patterns by updating previously analyzed patterns. The incoming data streams are divided into several sequences based on time based window. Informations of the sequences are inputted into a hash table. When the number of the sequences are over predefined bound, patterns are analyzed from the hash table. The patterns form a pattern tree, and later created new patterns update the pattern tree. In this way, real time patterns are always maintained in the pattern tree. During pattern analysis, suffixes of both new pattern and existed pattern in the tree can be same. Then a pointer is created from the new pattern to the existed pattern. This method reduce calculation time during duplicated pattern analysis. And old patterns in the tree are deleted easily by FIFO method. The advantage of our algorithm is proved by performance comparison with existed method, MILE, in a condition that pattern is changed continuously. And we look around performance variation by changing several variable in the algorithm.

• Journal of Korean Academy of Nursing Administration
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• v.9 no.3
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• pp.415-427
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• 2003

Purpose: The purpose of this study was to investigate the degree and pattern of knowledge management process, and to identify the relationship between knowledge management process and organizational effectiveness in clinical nurses. Method: Participants were 665 regular clinical nurses who had worked for over 1 year in general units of 9 tertiary medical hospitals including 2 national university hospitals, 5 university hospitals, and 2 hospitals founded by business enterprises. Data were collected from March to May 2003 through questionnaires. Four structured instruments were used to collect the data: Knowledge Management Process Scale(Jeong, Lee, Lee, & Kim, 2003), cCommitment Questionnaire(Mowday, Steers, & Porter, 1979), General Satisfaction Scale(CooK, Hepworth, Wall, & Warr, 1981), and one for general characteristics. The data were analyzed using factor analysis, reliability analysis, descriptive analysis, cluster analysis, one-way ANOVA, Scheffe test, correlation analysis with the SPSS for Windows 10.0 program. Result: 1) The average score for knowledge management process in nurses was $3.08{\pm}.54$ on a 5-point Likert scale. In order from highest mean score, the elements of knowledge management process, were Knowledge $Utilization(3.35{\pm}.57)$, Knowledge $Sharing(3.07{\pm}.58)$, Knowledge $Creation(2.99{\pm}.63)$, and Knowledge $Storage(2.91{\pm}.82)$. 2) Four knowledge management patterns for nurses, which were derived from cluster analysis, were inactivate pattern, delayed pattern, activate pattern, and high-activate pattern of knowledge management. 3) The degree of knowledge management process activation and 4 elements of knowledge management process, Knowledge Creation, Knowledge Storage, Knowledge Sharing, and Knowledge Utilization, were significantly correlated with nurses' organizational commitment and job satisfaction(p=.000). 4) The nurses' organizational commitment and job satisfaction showed significant differences according to the knowledge management patterns derived from cluster analysis of high-activate pattern, activate pattern, delayed pattern, inactivate pattern(p=.000). Conclusion: These results suggest that there are four knowledge management patterns for nurses, and knowledge management process positively affects the nurses' organizational commitment and job satisfaction. From the above findings, knowledge management process is empirically verified as a useful and effective method to increase organizational effectiveness, and develop the organization.