• Journal of Life Science
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• v.19 no.7
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• pp.994-1002
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• 2009

A bacteriocin-producing bacterium identified as Bacillus licheniformis was isolated from soybean sauce. Antibacterial activity was confirmed by paper disc diffusion method, using Micrococcus luteus as a test organism. The bacteriocin also showed antibacterial activities against Bacillus sphaericus, Lactobacillus bulgaricus, Lactobacillus planiarum, Paenibacillus polymyxa, and Pediococcus dextrinicus. Optimal culture conditions for the production of bacteriocin was attained by growing the cells in an MRS medium at a pH of 6.5~ 7.0 and a temperature of 37$^\circ$C for 36$\sim$48 hr. Solvents such as chloroform, ethanol, acetone, and acetonitrile had little effect on bacteriocin activity. However, about 50% of bacteriocin activity diminished with treatment of methanol and isopropanol at the final concentration of 50% at 25$^\circ$C for 1 hr. It was stable against a pH variation range from 3.0 and 7.0, but the activity reduced to 50% at a pH range from 9.0 to 11.0. It's activity was not affected by heat treatment at 100$^\circ$C for 30 min and 50% of activity was retained after heat treatment at 100$^\circ$C for 60 min, showing high thermostability. The bacteriocin was purified to a homogeneity through ammonium sulfate precipitation, SP-Sepharose ion-exchange chromatography, and reverse-phase high-performance liquid chromatography (HPLC). The entire purification protocol led to a 75-fold increase in specific activity and a 13.5% yield of bacteriocin activity. The molecular weight of purified bacteriocin was estimated to be about 2.5 kDa by tricine-SDS-PAGE.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.133-148
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• 2014

Recently, with the advent of various information channels, the number of has continued to grow. The main cause of this phenomenon can be found in the significant increase of unstructured data, as the use of smart devices enables users to create data in the form of text, audio, images, and video. In various types of unstructured data, the user's opinion and a variety of information is clearly expressed in text data such as news, reports, papers, and various articles. Thus, active attempts have been made to create new value by analyzing these texts. The representative techniques used in text analysis are text mining and opinion mining. These share certain important characteristics; for example, they not only use text documents as input data, but also use many natural language processing techniques such as filtering and parsing. Therefore, opinion mining is usually recognized as a sub-concept of text mining, or, in many cases, the two terms are used interchangeably in the literature. Suppose that the purpose of a certain classification analysis is to predict a positive or negative opinion contained in some documents. If we focus on the classification process, the analysis can be regarded as a traditional text mining case. However, if we observe that the target of the analysis is a positive or negative opinion, the analysis can be regarded as a typical example of opinion mining. In other words, two methods (i.e., text mining and opinion mining) are available for opinion classification. Thus, in order to distinguish between the two, a precise definition of each method is needed. In this paper, we found that it is very difficult to distinguish between the two methods clearly with respect to the purpose of analysis and the type of results. We conclude that the most definitive criterion to distinguish text mining from opinion mining is whether an analysis utilizes any kind of sentiment lexicon. We first established two prediction models, one based on opinion mining and the other on text mining. Next, we compared the main processes used by the two prediction models. Finally, we compared their prediction accuracy. We then analyzed 2,000 movie reviews. The results revealed that the prediction model based on opinion mining showed higher average prediction accuracy compared to the text mining model. Moreover, in the lift chart generated by the opinion mining based model, the prediction accuracy for the documents with strong certainty was higher than that for the documents with weak certainty. Most of all, opinion mining has a meaningful advantage in that it can reduce learning time dramatically, because a sentiment lexicon generated once can be reused in a similar application domain. Additionally, the classification results can be clearly explained by using a sentiment lexicon. This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of movie reviews. Additionally, various parameters in the parsing and filtering steps of the text mining may have affected the accuracy of the prediction models. However, this research contributes a performance and comparison of text mining analysis and opinion mining analysis for opinion classification. In future research, a more precise evaluation of the two methods should be made through intensive experiments.

• Korean Journal of Heritage: History & Science
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• v.51 no.1
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• pp.32-47
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• 2018

The purpose of this study is to examine the vegetation maintenance project that was conducted as a part of the Official Development Assistance (ODA) project for the historic site of Angkor, to analyze the aspects and characteristics of the project, and to derive implications for the establishment of future policies and strategies. First, the key words used in the vegetation maintenance project at the historic site of Angkor do not only refer to the concept of plants (and more specifically to 'trees') but also to the concept of heritage. In other words, the concept of heritage is not limited to architectural structures but is also intended to mean the vegetation and surroundings that form the historic site. Second, the expansion of the value of vegetation has contributed to the establishment of the basic principles of conservation based on the 'coexistence' between architectural structures and vegetation; here, vegetation has come to be recognized as an 'essential' element in the conservation of historic sites. Third, the range of vegetation maintenance has expanded from each tree to the surroundings of the temples, and vegetation maintenance came to adopt 'integrative' and 'active' directions to improve not only the growth environment of the vegetation but also the viewing environment experienced by visitors. This change means that it is necessary for the historic site maintenance project to comprehensively deal with the temples and their surrounding areas. Fourth, for the effective performance of the ODA project, the role of the International Coordinating Committee for the Safeguarding and Development of the Historic Site of Angkor (ICC-Angkor), under the influence of UNESCO, was expanded from an examination of the problems with the existing projects to a search for solutions to technical consultation and supervision. This implies that, in order to perform the ODA project in a way that is appropriate to the local conditions, it is important to reach gradual and phased agreements with ICC-Angkor.

• Korean Chemical Engineering Research
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• v.56 no.6
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• pp.871-877
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• 2018

Storing the surplus energy from renewable energy resource is one of the challenges related to intermittent and fluctuating nature of renewable energy electricity production. $CO_2$ methanation is well known reaction that as a renewable energy storage system. $CO_2$ methanation requires a catalyst to be active at relatively low temperatures ($250-500^{\circ}C$) and selectivity towards methane. In this study, the catalytic performance test was conducted using a pressurized bubbling fluidized bed reactor (Diameter: 0.025 m and Height: 0.35 m) with $Ni/{\gamma}-Al_2O_3$ (Ni70%, and ${\gamma}-Al_2O_3$30%) catalyst. The range of the reaction conditions were $H_2/CO_2$ mole ratio range of 4.0-6.0, temperature of $300-420^{\circ}C$, pressure of 1-9 bar, and gas velocity ($U_0/U_{mf}$) of 1-5. As the $H_2/CO_2$ mole ratio, temperature and pressure increased, $CO_2$ conversion increases at the experimental temperature range. However, $CO_2$ conversion decreases with increasing gas velocity due to poor mixing characteristics in the fluidized bed. The maximum $CO_2$ conversion of 99.6% was obtained with the operating condition as follows; $H_2/CO_2$ ratio of 5, temperature of $400^{\circ}C$, pressure of 9 bar, and $U_0/U_{mf}$ of 1.4-3.

• Journal of the Korean Electrochemical Society
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• v.22 no.1
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• pp.36-42
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• 2019

A macroporous Sn thick film as a high capacity negative electrode for a lithium ion secondary battery was prepared by using a chemical etching method using nitric acid for a Sn film having a thickness of $52{\mu}m$. The porous Sn thick film greatly reduced the over-voltage for the alloying reaction with lithium by the increased reaction area. At the same time. The porous structure of active Sn film plays a part in the buffer and reduces the damage by the volume change during cycles. Since the porous Sn thick film electrode does not require the use of the binder and the conductive carbon black, it has substantially larger energy density. As the concentration of nitric acid in etching solution increased, the degree of the etching increased. The etching of the Sn film effectively proceeded with nitric acid of 3 M concentration or more. The porous Sn film could not be recovered because the most of Sn was eluted within 60 seconds by the rapid etching rate in the 5 M nitric acid. In the case of etching with 4 M nitric acid for 60 seconds, the appropriate porous Sn film was formed with 48.9% of weight loss and 40.3% of thickness change during chemical acid etching process. As the degree of etching of Sn film increased, the electrochemical activity and the reversible capacity for the lithium storage of the Sn film electrode were increased. The highest reversible specific capacity of 650 mAh/g was achieved at the etching condition with 4 M nitric acid. The porous Sn film electrode showed better cycle performance than the conventional electrode using a Sn powder.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.1
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• pp.151-166
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• 2019

New drug development requires 10 to 15 years of long time and more than $ 1 billion in funding, ranging from basic research${\rightarrow}$preclinical medicine${\rightarrow}$clinical medicine${\rightarrow}$product approval${\rightarrow}$sales. Many new drug development bio-venture companies will continue to pursue new drug development with funds secured through listing on the securities market. This study focuses on the impact of the listing on the market of bio-venture companies in the development of new drugs. It is necessary to determine whether the increase in registered patent, preclinical, clinical and technology transfer contracts at the time of listing (D) The results of this study are as follows. We also analyzed whether the registered patent, preclinical, and clinical effects had significant effect on technology transfer contracts at two years after listing and listing. The results of the analysis are as follows. First, Korea's new drug development bio-venture firms increased their registered patents but did not increase their pre-clinical, clinical and technology transfer contracts. Second, at the time of listing and two years after listing, pre-employment has a significant effect on Korea's technology transfer contracts and has a significant effect on overseas technology transfer contracts. However, registered patents and clinics have significant influence on technology transfer contracts. Korea 's new drug development bio-venture firms showed patent increase despite the stock market listing, but pre-clinical, clinical and technology transfer contracts did not increase. In order to strengthen technological commercialization of new drug development bio-venture companies in the future, it is required to establish R & D strategy for efficient use of IPO subscription funds, open innovation through strengthening industry-academia-partnerships, and more sophisticated preclinical and clinical strategy establishment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.3
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• pp.73-84
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• 2019

Despite decades of work experience, workers at small- and medium-sized enterprises(SME) here have yet to make inroads into the self-employed sector that utilizes the job competency they have accumulated at work after retirement. Unlike large companies, SME do not have a proper system for improving the long-term job competency of their employees as they focus on their immediate performance. It is necessary to analyse the independent variables affecting the job competency of employees of SME to derive practical implications for the personnel of SME. In the preceding studies, there are independent variable analyses that affect job competency in specialized industries, such as health care, public officials and IT, but the analysis of workers at SME is insufficient. This study set the person-job fit and organizational justice based on the prior studies of the independent variables that affect the job competency of SME general workers as a dependent variable. The sub-variables of each variable derived knowledge, skills, experience, and desire for person-job fit, and distribution, procedural and deployment justice for organizational justice, respectively. The survey of employees of SME in Korea was conducted from February to March 2019 by Likert 5 scales, and the survey was retrieved from 323 people and analyzed in a demonstration using the SPSS and AMOS statistics package. Among the four sub-independent variables of person-job fit, knowledge, skills and experience were shown to have a significant impact on the job competency, and desire was not shown to be so. Among the three sub-independent variables of organizational justice, deployment justice has a significant impact on job competency, but distribution and procedural justices have not. Personnel managers of SME need to improve the job competency of their employees by appropriately utilizing independent variables such as knowledge, skills, experience and deployment at each stage, including recruitment, deployment, and promotion. Future job competency modeling studies are needed to overcome the limitations of this study, which fails to objectively measure job competency.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.5
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• pp.159-175
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• 2021

This study attempted to analyze the relationship between influencer's characteristic factors such as professionalism, authenticity, and interactivity and content quality factors consisting of accuracy, completeness, and diversity on brand attitude and purchase attitude through trust and self-consistency. To reveal the structural relationship between main variables, a survey was conducted on 201 users. An EFA, CFA, and reliability analysis were performed to confirm reliability and validity. And structural equation was conducted to verify hypothesis. The main results are as follows. First, it was found that professionalism and interactivity had a significant positive effect on trust. And, accuracy, completeness, and variety were all found to have a significant positive effect on trust. Second, in the relationship between individual characteristic factors and self-consistency, it was found that professionalism and authenticity had a significant positive effect on self-consistency. In addition, in the relationship between content quality and self-consistency, accuracy, completeness, and diversity were found to have a positive effect on self-consistency along with trust. Third, in the relationship between trust and self-consistency on brand attitude and purchase intention, both trust and self-consistency were found to have a statistically significant positive effect on brand attitude. It was found that only self-consistency and brand attitude had a statistically significant positive effect on purchase intention. These findings showed that when users perceive professionalism and interaction with influencer, trust increases, and professionalism and progress increase self-consistency with influencer. In addition, in the case of content quality, it was found that trust and self-consistency responded positively when perceived content quality through content accuracy, completeness, and diversity. Also, trust and self-consistency increased attitudes toward brands and could influence consumption behavior such as purchase intention. Therefore, for effective marketing performance using influencer's influence in the field of influencer marketing, which has a strong information delivery on products and brands, not only personal characteristics such as professionalism, authenticity, and interactivity, but also quality of content should be considered. The above research results are expected to suggest implications for marketing strategies and practices as one available basic data to exert the expected effect of marketing using influencer.

• Journal of Korean Elementary Science Education
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• v.41 no.4
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• pp.658-672
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• 2022

The unique teaching and learning difficulties of speed-related units in elementary school science are mainly due to the student's lack of mathematical thinking ability and procedural knowledge on speed measurement, and curriculums and textbooks must be constructed with these in mind. To identify the implications of composing a new science curriculum and relevant textbooks, this study reviewed the structure and contents of the speed-related units of three curriculums from the 2007 revised curriculum to the 2015 revised curriculum and the resulting textbooks and examined their relevance in light of the literature. Results showed that the current content carries the risk of making students calculate only the speed of an object through a mechanical algorithm by memorization rather than grasp the multifaceted relation between traveled distance, duration time, and speed. Findings also highlighted the need to reorganize the curriculum and textbooks to offer students the opportunity to learn the meaning of speed step-by-step by visualizing materials such as double number lines and dealing with simple numbers that are easy to calculate and understand intuitively. In addition, this paper discussed the urgency of improving inquiry performance such as process skills by observing and measuring an actual object's movement, displaying it as a graph, and interpreting it rather than conducting data interpretation through investigation. Lastly, although the current curriculum and textbooks emphasize the connection with daily life in their application aspects, they also deal with dynamics-related content somewhat differently from kinematics, which is the main learning content of the unit. Hence, it is necessary to reorganize the contents focusing on cases related to speed so that students can grasp the concept of speed and use it in their everyday lives. With regard to the new curriculum and textbooks, this study proposes that students be provided the opportunity to systematically and deeply study core topics rather than exclude content that is difficult to learn and challenging to teach so that students realize the value of science and enjoy learning it.