• Journal of Korean Medicine Rehabilitation
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• v.32 no.2
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• pp.65-81
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• 2022

Objectives This study aimed to assess the effects of oral administration of deer antler extracts on an osteoporosis-induced animal model. We analyzed the results of using deer antler single extracts on animal models with osteoporosis through a systematic review and meta-analysis. Methods We included osteoporosis studies in animal experiments that administrated deer antler extracts orally. We searched the following 13 databases without a language restriction: PubMed, EMBASE, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), China National Knowledge Infrastructure (CNKI), Wanfang, Korean Medical Database (KMbase), National Digital Science Library (NDSL), Korean Traditional Knowledge (Koreantk), Oriental Medicine Advanced Searching Integrated System (OASIS), Research Information Sharing Service (RISS), Korea Institute of Science and Technology Information (KISTI), and Koreanstudies Information Service System (KISS). We used Systematic Review Centre for Laboratory Animal Experimentation's risk of bias tool for assessing the methodological quality of the included studies. Results A total of 299 potentially relevant studies were searched and 11 were included for a systematic review. Nine studies used a single deer antler extract. A study compared the effects of single extracts of deer antler and antler glue, while another study compared the effects of three single extracts of deer antler, old antler, and antler glue. For evaluating the intervention effect, bone mineral density (BMD) was measured as the primary outcome, while the histomorphometric indicators of the bone and serum alkaline phosphatase and osteocalcin levels were used as the secondary outcome variables. On conducting a meta-analysis of studies on single deer antler extract, BMD was observed to be significantly increased compared to that in control group (standardized mean difference [SMD]=2.11; 95% confidence interval [CI]=1.58~2.65; Z=7.75; p<0.00001; I²=56%). As a result of meta-analysis, according to the concentration of deer antler, the group with high concentration showed statistically significantly higher BMD than the group with low concentration (SMD=1.28; 95% CI=0.74~1.82; Z=4.63; p<0.00001; I²=9%). Conclusions The research shows that the deer antler extracts have significant anti-osteoporotic effects on the osteoporosis-induced animal model. However the studies included in this research had a high methodological risk of bias. This indicates the requirement of considerable attention in the interpretation of the study results.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.51-67
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• 2022

The purpose of this study is to diagnose the current status of alternative materials in Korea and to suggest directions and goals for the development of alternative materials. The comprehensive list of national alternative materials and the list of popular and new books were analyzed using the collection evaluation method. Results first the percentage of alternative material collections based on the popular book list for 10 years is 90.1%. The production rate of alternative materials is low in the subjects of 'Language', 'Art' and 'Technology and Science'. Most of the service formats were 'text only daisy'. Second, the CCHR(Common Collection Holding Ratio) and CUI(Collection Uniqueness index) of alternative materials were analyzed using the union catalog. Libraries with a large volume of books have a high proportion of CCHR and CUI. Topics with the highest CCHR are 'Literature' and 'Social Science'. The subjects with the highest collection uniqueness index are 'religion', 'art', and 'language'. Third, the replacement ratio of new books for 3 years is 5.09%. During the same period, the average book purchase rate of public libraries was 8.83%. The average book purchase rate in public libraries is 8.83%, and it is necessary to increase the collection rate of alternative materials based on this ratio.

• Journal of Information Management
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• v.38 no.3
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• pp.111-135
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• 2007

The purpose of this study is to identify the citing behaviors of researchers in the field of mechanical engineering. It tries to verify if there is a significant difference on citing behavior of researchers between the past and the present with dissertations produced in P University as samples. For the comparison, years 1996 and 2004 are selected for the citation analysis. It analyzed four aspects, such as types of resources cited, languages used in cited documents, years since their publication of cited documents, and the journals indexed in SCI. The results of the analysis are; First, journals are the most cited than any other types of information resources. The citation of WWW resources which are gradually increasing for research is not shown in 1996, but there were some cited in 2004. Second, doctoral candidates usually cite document in English for their study. Statistics show that the use of resources in Japanese is on the decrease. Third, doctoral candidates in the discipline prefer materials published within 4-7 years, 8-11 years rather than 0-3 years since their publication. Last, journals indexed in SCI among the citation in dissertations are about 33 percent for both 1996 and 2004.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.401-408
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• 2023

The purpose of this study is to design textbook metadata as a basic task for building a textbook database. To this end, reading textbooks were defined as a category of textbooks, and a metadata development methodology was established through previous research. In order to ensure that bibliographically essential elements are not omitted, the catalog description elements of institutions that collect, accumulate, and service textbooks such as the National Library of Korea were investigated. The elements of Dublin Core, MODS, and KEM were mapped to derive elements suitable for describing textbooks. Finally, a set of textbook metadata elements consisting of 14 elements in three categories - bibliography, context, and textbook characteristics were presented by adding publication type, genre, and curriculum period elements. The 14 elements are titles, authors, publications, formats, identification sign, languages, locations, subject names, annotation, genres, table of contents, subjects, curriculum period, and curriculum information. In this study, we contributed to this field by discussing how to organize textbook resources with national knowledge resources, and in future studies, we proposed to evaluate usability by applying metadata elements to actual textbooks and revise and supplement them according to the evaluation results.

• Journal of Microbiology and Biotechnology
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• v.15 no.6
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• pp.1337-1345
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• 2005

Vibrio vulnificus is the causative agent of foodborne diseases such as gastroenteritis and life-threatening septicemia. Microbial pathogenicity is a complex phenomenon in which expression of numerous virulence factors is frequently controlled by a common regulatory system. In the present study, a mutant exhibiting decreased cytotoxic activity toward intestinal epithelial cells was screened from a library of V. vulnificus mutants constructed by a random transposon mutagenesis. By a transposon-tagging method, an open reading frame, fexA, a homologue of Escherichia coli areA, was identified and cloned. The nucleotide and deduced amino acid sequences of the fexA were analyzed, and the amino acid sequence of FexA from V. vulnificus was $84\%\;to\;97\%$ similar to those of AreA, an aerobic respiration control global regulator, from other Enterobacteriaceae. Functions of the FexA were assessed by the construction of an isogenic mutant, whose fexA gene was inactivated by allelic exchanges, and by evaluating its phenotype changes in vitro and in mice. The disruption of fexA resulted in a significant alteration in growth rate under aerobic as well as anaerobic conditions. When compared to the wild-type, the fexA mutant exhibited a substantial decrease in motility and cytotoxicity toward intestinal epithelial cell lines in vitro. Furthermore, the intraperitoneal $LD_{50}$ of the fexA mutant was approximately $10^{1}-10^{2}$ times higher than that of parental wild-type. Therefore, it appears that FexA is a novel global regulator controlling numerous genes and contributing to the pathogenesis as well as growth of V. vulnificus.

• Journal of Microbiology and Biotechnology
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• v.27 no.1
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• pp.101-111
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• 2017

The task of improving a fungal strain is highly time-consuming due to the requirement of a large number of flasks in order to obtain a library with enough diversity. In addition, fermentations (particularly those for fungal cells) are typically performed in high-volume (100-250 ml) shake-flasks. In this study, for large and rapid screening of itaconic acid (IA) high-yielding mutants of Aspergillus terreus, a miniaturized culture method was developed using 12-well and 24-well microtiter plates (MTPs, working volume = 1-2 ml). These miniaturized MTP fermentations were successful, only when highly filamentous forms were induced in the growth cultures. Under these conditions, loose-pelleted morphologies of optimum sizes (less than 0.5 mm in diameter) were casually induced in the MTP production cultures, which turned out to be the prerequisite for the active IA biosynthesis by the mutated strains in the miniaturized fermentations. Another crucial factor for successful MTP fermentation was to supply an optimal amount of dissolved oxygen into the fermentation broth through increasing the agitation speed (240 rpm) and reducing the working volume (1 ml) of each 24-well microtiter plate. Notably, almost identical fermentation physiologies resulted in the 250 ml shake-flasks, as well as in the 12-well and 24-well MTP cultures conducted under the respective optimum conditions, as expressed in terms of the distribution of IA productivity of each mutant. These results reveal that MTP cultures could be considered as viable alternatives for the labor-intensive shake-flask fermentations even for filamentous fungal cells, leading to the rapid development of IA high-yield mutant strains.

• Journal of Korean Society of Rural Planning
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• v.17 no.1
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• pp.89-98
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• 2011

Recently, the food industry has evolved into a new and innovative trend according to its globalization and change of food consumption patterns. However, it is hard for the traditional food industry in Korea to meet the changing consumers' needs because of its poorer quality control and lower industrialization technology than other advanced industries. Also the knowledges acquired through a lot of time and efforts would be lost after the human resources with tacit knowledges leave by their too much aging. Especially, the 21st century would be called as knowledge based society which means that knowledge be the important contributing factor in the economic growth. In this regard, this study aimed at proposing the knowledge based system for systematically managing or preserving knowledges of Mosisongpyun industry in Yeonggwang County to seek for the sustainable development of the traditional food industry in Korea. The knowledge based system of Mosisongpyun industry in Yeonggwang County is finally proposed as follows; First, hardware is composed with the necessary unit facilities such as interpretive center, learning and experience room, library, etc. And the integrating facilities such as Mosisongpyun theme park, traditional village, and knowledge industrialization support center are proposed. Second, software is composed with the necessary unit softwares such as the preservation manual of traditional knowledge and skill, web-site administrator, development of graded textbooks, development database software, etc. And the integrating softwares such as development of innovation and management ability in Mosisongpyun industry are proposed. Third, humanware is composed with the necessary unit programs such as exhibition, own training program, incubator support system, etc. And the integrating programs such as the farm association corporation, the testing and research institute, the institution of learning and training are proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.459-461
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• 2022

One of the big differences between Network-on-Chip (NoC) and the existing parallel processing system based on an off-chip network is that data packet routing is performed using a centralized control scheme. In such an environment, the best-effort packet routing problem becomes a real-time assignment problem in which data packet arriving time and processing time is the cost. In this paper, the Hungarian algorithm, a representative computational complexity reduction algorithm for the linear algebraic equation of the allocation problem, is implemented in the form of a hardware accelerator. As a result of logic synthesis using the TSMC 0.18um standard cell library, the area of the circuit designed through case analysis for the cost distribution is reduced by about 16% and the propagation delay of it is reduced by about 52%, compared to the circuit implementing the original operation sequence of the Hungarian algorithm.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1029-1037
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• 2020

The machine learning algorithm has been widely used in water-related fields such as water resources, water management, hydrology, atmospheric science, water quality, water level prediction, weather forecasting, water discharge prediction, water quality forecasting, etc. However, water quality prediction studies based on the machine learning algorithm are limited compared to other water-related applications because of the limited water quality data. Most of the previous water quality prediction studies have predicted monthly water quality, which is useful information but not enough from a practical aspect. In this study, we predicted the dissolved oxygen (DO) using recurrent neural network with long short-term memory model recurrent neural network long-short term memory (RNN-LSTM) algorithms with hourly- and daily-datasets. Bugok Bridge in Oncheoncheon, located in Busan, where the data was collected in real time, was selected as the target for the DO prediction. The 10-month (temperature, wind speed, and relative humidity) data were used as time prediction inputs, and the 5-year (temperature, wind speed, relative humidity, and rainfall) data were used as the daily forecast inputs. Missing data were filled by linear interpolation. The prediction model was coded based on TensorFlow, an open-source library developed by Google. The performance of the RNN-LSTM algorithm for the hourly- or daily-based water quality prediction was tested and analyzed. Research results showed that the hourly data for the water quality is useful for machine learning, and the RNN-LSTM algorithm has potential to be used for hourly- or daily-based water quality forecasting.