• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.295-314
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• 2021

The purpose of this study is to find out the factors that affect the 'public librarian servant's' Collective Self-Esteem (CSE) in Korean relation-oriented collectivism. The research was organized into a research model by setting up a hypothesis on the impact relationship the between the group Collective self-esteem, the work environment factors and cognition of Superior institution of the Public librarian servant. The relevant data collection was conducted for public librarian servant working in public libraries nationwide through the method of survey. From April 3, 2020 to May 14, 2020, it was conducted for Public Librarian Servant in public libraries nationwide with Civil Service System, Office of Education, Ministry of Culture·Sports and Tourism based on responses for 301 Public Librarian Servant from 559 institution. According to the analysis, the cognition of the superior institution of Public Librarian Servant influences the cognition of Collective Self-Esteem among the sub-factors of Collective - Self - Esteem of Collective Self-Esteem. This study is meaningful in that 'Public Librarian Servant' who was treated as an individual entity in the study of Library and Information Science study, as being has relationship with various groups and is dealt with multi-dimensionally in Korean relation-oriented collectivism culture. Research suggests that when Public Librarian Servant exist as one of the subordinate organizations to vast Civil service system, it suggest that Public Librarian Servants should find out a balance for improve their relatively low social values.

• The Journal of Internal Korean Medicine
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• v.45 no.1
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• pp.11-30
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• 2024

Objectives: This study evaluated the effects of Ssanghwa-tang (SHT) on lung injury and muscle loss in a COPD mouse model. Methods: C57BL/6 mice were challenged with cigarette smoke extract and lipopolysaccharide, and then treated with two concentrations of SHT (250 and 500 mg/kg). After sacrifice, the bronchoalveolar lavage fluid (BALF) or lung tissue was analyzed by cytospin, ELISA, real-time PCR, flow cytometry analysis, and H&E and Masson's trichrome staining. The grip strength of COPD mice was measured using a grip strength meter. The running time of COPD mice was measured by a treadmill test. Muscle tissue of the quadriceps was stained with H&E and Masson's trichrome staining. Results: SHT significantly inhibited the increase in neutrophil numbers in BALF and significantly decreased immune cell activity in BALF and lung tissue. It also significantly inhibited the increase in TNF-α, IL-17, and MIP2 in BALF. Real-time PCR analysis revealed that the mRNA expression of TNF-α, IL-17, MIP2, and TRPV1 in lung tissue showed a significant decrease compared with the control group. Lung tissue damage was significantly reduced in the histological analysis. The grip strength and running time of the COPD mice showed a significant decrease compared with the control group. In histological staining, SHT was found to reduce the damage to muscle tissue. Conclusions: This study indicates that SHT can be used as a therapeutic agent for COPD patients by inhibiting lung injury and muscle loss.

• Journal of KIISE:Databases
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• v.33 no.6
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• pp.600-619
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• 2006

According to recent technical advances on sensors and mobile devices, processing of data streams generated by the devices is becoming an important research issue. The data stream of real values obtained at continuous time points is called streaming time-series. Due to the unique features of streaming time-series that are different from those of traditional time-series, similarity matching problem on the streaming time-series should be solved in a new way. In this paper, we propose an efficient algorithm for streaming time- series matching problem that supports normalization transform. While the existing algorithms compare streaming time-series without any transform, the algorithm proposed in the paper compares them after they are normalization-transformed. The normalization transform is useful for finding time-series that have similar fluctuation trends even though they consist of distant element values. The major contributions of this paper are as follows. (1) By using a theorem presented in the context of subsequence matching that supports normalization transform[4], we propose a simple algorithm for solving the problem. (2) For improving search performance, we extend the simple algorithm to use $k\;({\geq}\;1)$ indexes. (3) For a given k, for achieving optimal search performance of the extended algorithm, we present an approximation method for choosing k window sizes to construct k indexes. (4) Based on the notion of continuity[8] on streaming time-series, we further extend our algorithm so that it can simultaneously obtain the search results for $m\;({\geq}\;1)$ time points from present $t_0$ to a time point $(t_0+m-1)$ in the near future by retrieving the index only once. (5) Through a series of experiments, we compare search performances of the algorithms proposed in this paper, and show their performance trends according to k and m values. To the best of our knowledge, since there has been no algorithm that solves the same problem presented in this paper, we compare search performances of our algorithms with the sequential scan algorithm. The experiment result showed that our algorithms outperformed the sequential scan algorithm by up to 13.2 times. The performances of our algorithms should be more improved, as k is increased.