• Mass Spectrometry Letters
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• v.15 no.2
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• pp.95-106
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• 2024

Taraxacum coreanum, known as the native Korean white dandelion, has been historically used in traditional medicine due to its various therapeutic properties. However, the specific benefits and mechanisms of white dandelion in alleviating particular symptoms or diseases remain uncertain due to the complexity of its phytochemical profile. In this study, we aimed to elucidate the phytochemical profiles of methanolic extracts of different parts of the white dandelion (flower, leaf, stem, and root) using hybrid ion-mobility Q-TOF MS. Using the trapped ion mobility-based PASEF technique, 3715 and 2114 molecular features with MS2 fragments were obtained in positive and negative ion modes, respectively, and then a total of 360 and 156 phytochemical compounds were annotated by matching with a reference spectral library in positive and negative ion modes, respectively. Subsequent feature-based molecular networking analysis revealed the phytochemical differences across the four different parts of the white dandelion. Our findings indicated that the methanolic extracts contained various bioactive compounds, including lipids, flavonoids, phenolic acids, and sesquiterpenes. In particular, lipids such as linoleic acids, lysophosphatidylcholines, and sesquiterpenoids were predominantly present in the leaf, while flavonoid glycosides and lysophosphoethanolamines were notably enriched in the flower. An assessment of the total phenolic content (TPC) and total flavonoid content (TFC) of the methanolic extracts revealed that the majority of phytochemicals were concentrated in the flower. Interestingly, despite the root extract displaying the lowest TPC and TFC values, it exhibited the highest radical scavenging rate when normalized to TPC and TFC, suggesting a potent antioxidant effect. These findings and further investigations into the biological activities and medicinal potential of the identified compounds, particularly those exclusive to specific plant parts, may contribute to the development of novel therapeutic agents derived from white dandelion.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.30-37
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• 2021

Various devices are connected to the Internet, and attacks using the Internet are occurring. Among such attacks, there are attacks that use malicious URLs to make users access to wrong phishing sites or distribute malicious viruses. Therefore, how to detect such malicious URL attacks is one of the important security issues. Among recent deep learning technologies, neural networks are showing good performance in image recognition, speech recognition, and pattern recognition. This neural network can be applied to research that analyzes and detects patterns of malicious URL characteristics. In this paper, performance analysis according to various parameters was performed on a method of detecting malicious URLs using neural networks. In this paper, malicious URL detection performance was analyzed while changing the activation function, learning rate, and neural network structure. The experimental data was crawled by Alexa top 1 million and Whois to build the data, and the machine learning library used TensorFlow. As a result of the experiment, when the number of layers is 4, the learning rate is 0.005, and the number of nodes in each layer is 100, the accuracy of 97.8% and the f1 score of 92.94% are obtained.

• Journal of Fashion Business
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• v.21 no.4
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• pp.127-143
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• 2017

In this study, we examine a variety of influences in the field of design and analysis about the value of visual tactile design. In hair design, through study on visual tactility, creative design inspiration in the field of hair design enables development of quality research. Research methods use Internet publications such as local and foreign data, analysis, and related research and book forms, such as network searches. library goes for consideration by a literature search. Contents of this study used review of the case and by visual tactility design, for this study, expressive characteristics by color, texture and form of hair design, from 2014-2017 trend shown in the last three years the expressions of visual tactility being used through the analysis of design by date of the case. Result of this study is, visual tactile design appearing in the areas of hair design, that are not of the rules that are active, abstract form, texture, described as a visual feel the promotion of effective, and light and high brightness is sweet tactile impression, high saturation was cold, dark color was hard and heavy, red system is warm and the blue system is cold sense. In general, design trend in hair for three years from 2014-2017, visual tactility in 2014 is a high saturation and unstructured also soft and bright colors. 2015 is on the overall shape, color, texture, hybrid design configuration is more. As of 2016, 2017 is curved and straight texture, appearance of the hybrid mix to maximize the visual tactility.

• Journal of Fashion Business
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• v.20 no.5
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• pp.87-101
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• 2016

In this study, a variety of influence in the field of design and analysis about the value of a Grunge Design and the creative design inspirations in the field of hair design to help the development of the quality of research. The research methods use the Internet publications such as local and foreign information, analysis and related research and book form, such as the network search, library goes for consideration by a literature search. The contents of this study used review of the case and by Grunge design, expressive characteristics by color, texture and form of Grunge hair design, from 2014 to 2016 trend collections in the last three years through the analysis of design by date of the case. The result of this study is, Grunge design appearing in the areas of hair design, that are grunge anti fashion like the beauty of the disorder, the disharmony, the incomplete, the kitsch, the poverty. Although Grunge means dirt, filth, rubbish as a slang but it is valuable which was raised from the anti fashion to high fashion and alternative of main stream fashion and the hair design in modern fashion also brought. In this study, we can understand the grunge hair design in modern fashion was started from lower place as alternative and forecast the potentialities, the formativeness of the grunge design and value of the beauty and grunge anti fashion the identity and the spirit appearing steadily a modern fashion influence are reflected in our next fashion and design characteristics.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.148-154
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• 2019

The study was performed to prepare basic data for the development of entrepreneur education programs for nursing students through literature review and text network of relevant studies on entrepreneurship education for college students. The research was found in the database of the Korea Education and Research Information Service, the Korean Academic Information Service System, DBpia and the National Assembly Library with keywords such as 'entrepreneur', 'student', 'education', 'program' and 'training. The final selected paper was 35 studies in Korea from 2000 to September 2016. The largest number of studies have been conducted since 2011 with 85.71%, and the largest proportion of survey(88.57 %). The major independent variables were entrepreneur self-efficacy and entrepreneurship and the dependent variables were entrepreneur intention and entreprenuer self-efficacy. Based on this result, entrepreneur education programs will be developed suitable for the target, and it can promote the entrepreneur education for nursing students.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.135-152
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• 2015

The goal of this paper is to explore the field of Computer and Information Science with the aid of text mining techniques by mining Computer and Information Science related conference data available in DBLP (Digital Bibliography & Library Project). Although studies based on bibliometric analysis are most prevalent in investigating dynamics of a research field, we attempt to understand dynamics of the field by utilizing Latent Dirichlet Allocation (LDA)-based multinomial topic modeling. For this study, we collect 236,170 documents from 353 conferences related to Computer and Information Science in DBLP. We aim to include conferences in the field of Computer and Information Science as broad as possible. We analyze topic modeling results along with datasets collected over the period of 2000 to 2011 including top authors per topic and top conferences per topic. We identify the following four different patterns in topic trends in the field of computer and information science during this period: growing (network related topics), shrinking (AI and data mining related topics), continuing (web, text mining information retrieval and database related topics), and fluctuating pattern (HCI, information system and multimedia system related topics).

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.93-114
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• 2023

Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.

• Korean Journal of Oriental Medicine
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• v.17 no.2
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• pp.63-71
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• 2011

Objectives : We studied the ISP(information strategy plan) of oasis spanning 5 years. From this study we aimed at total road map to upgrade the service systematically and to carry out the related projects. If we do it as road map, oasis will be the core infra service contributing to the improvement of TKM(traditional korean medicine) research capability. Methods : We carried out 3 step ISP method composed of environmental analysis, current status analysis and future plan. We used paper, report and trend analysis document as base materials and did the survey to get opinions from users and TKM experts. We limited this study to drawing the conceptual design of oasis. Results : From environmental analysis we knew that China and USA built up the largest TM databases. We did the survey to get the activation ways of oasis. And we did the benchmarking on the advanced services through current status analysis. Finally we determined 'maximize the research value based the open TKM knowledge infra' as oasis' vision. And we designed oasis' future system which is composed of service layer, application layer and contents layer. Conclusion : First TKM related documents, research materials, researcher information and standards are merged to elevate the TKM information level. Concretely large scale TKM information infra project such as TKM information classification code development, TKM library network building and CAM research information offering are carried out at the same time.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.18-36
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• 2024

As interest in ESG has been increased, it is easy to find papers that empirically study that a company's ESG activities have a positive impact on the company's performance. However, research on what ESG activities companies should actually engage in is relatively lacking. Accordingly, this study systematically classifies ESG activities of companies and seeks to provide insight to companies seeking to plan new ESG activities. This study analyzes how Chinese manufacturing companies perform ESG activities based on their dynamic capabilities in the global economy and how they differ in their activities. This study used the ESG annual reports of 151 Chinese manufacturing listed companies on the Shanghai & Shenzhen Stock Exchange and ESG indicators of China Securities Index Company (CSI) as data. This study focused on the following three research questions. The first is to determine whether there are any differences in ESG activities between companies with high ESG scores (TOP-25) and companies with low ESG scores (BOT-25), and the second is to determine whether there are any changes in ESG activities over a 10-year period (2010-2019), focusing only on companies with high ESG scores. The results showed that there was a significant difference in ESG activities between high and low ESG scorers, while tracking the year-to-year change in activities of the top-25 companies did not show any difference in ESG activities. In the third study, social network analysis was conducted on the keywords of E/S/G. Through the co-concurrence matrix technique, we visualized the ESG activities of companies in a four-quadrant graph and set the direction for ESG activities based on this.