• Information Systems Review
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• v.24 no.1
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• pp.21-37
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• 2022

Drug repositioning, one of the methods of developing new drugs, is a useful way to discover new indications by allowing drugs that have already been approved for use in people to be used for other purposes. Recently, with the development of machine learning technology, the case of analyzing vast amounts of biological information and using it to develop new drugs is increasing. The use of machine learning technology to drug repositioning will help quickly find effective treatments. Currently, the world is having a difficult time due to a new disease caused by coronavirus (COVID-19), a severe acute respiratory syndrome. Drug repositioning that repurposes drugsthat have already been clinically approved could be an alternative to therapeutics to treat COVID-19 patients. This study intends to examine research trends in the field of drug repositioning using machine learning techniques. In Pub Med, a total of 4,821 papers were collected with the keyword 'Drug Repositioning'using the web scraping technique. After data preprocessing, frequency analysis, LDA-based topic modeling, random forest classification analysis, and prediction performance evaluation were performed on 4,419 papers. Associated words were analyzed based on the Word2vec model, and after reducing the PCA dimension, K-Means clustered to generate labels, and then the structured organization of the literature was visualized using the t-SNE algorithm. Hierarchical clustering was applied to the LDA results and visualized as a heat map. This study identified the research topics related to drug repositioning, and presented a method to derive and visualize meaningful topics from a large amount of literature using a machine learning algorithm. It is expected that it will help to be used as basic data for establishing research or development strategies in the field of drug repositioning in the future.

• Journal of the Korean Society of School Health
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• v.37 no.1
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• pp.1-11
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• 2024

Purpose: The purpose of the study was to conduct a descriptive survey to examine the knowledge, infection prevention behaviors, and health beliefs regarding COVID-19 and to identify factors that influence infection prevention behaviors in elementary and middle school students based on the Health Belief Model. Methods: The study included 388 elementary and middle school students in Seoul, Gyeonggi, and Jeonbuk provinces. Data were collected from September 1 to September 15, 2023. The questionnaire consisted of 10 questions about COVID-19 knowledge, 13 questions about infection prevention behaviors, and 15 questions about health beliefs. The collected data were subjected to multiple hierarchical regression analyses. The cronbach's α of infection prevention behaviors was 0.83, the KR-20 of COVID-19 related knowledge was 0.68, and the Cronbach's α of COVID-19 related health beliefs was 0. 78. Results: In Model 1, females showed higher levels of infection prevention behaviors than males (β=.14, p=.006) and middle school students showed lower levels of infection prevention behaviors than elementary school students (β=-.10, p=.037). In Model 2, among COVID-19-related health beliefs, barriers had a significant negative effect on infection prevention behaviors (β=-.20, p<.001) and cues to action had a significant positive effect on infection prevention behaviors (β=.14, p=.037), indicating that lower barriers and higher cues to action were associated with higher levels of infection prevention behaviors. Conclusion: The results showed that prevention behaviors were associated with lower barriers and higher cues to action among COVID-19 health beliefs. Elementary and middle school students in Korea spend a lot of time in groups at private academies or school, which are closed spaces with poor ventilation, making them vulnerable to new infectious diseases such as COVID-19. Unlike adults, infectious diseases can have serious impact on their mental and social health. Therefore, it is necessary for schools to provide accurate and timely health education about COVID-19 to increase cues to action for elementary and middle school students in order to improve their infection prevention behaviors.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.425-435
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• 2023

Organoleptic parameters such as color, odor, and flavor influence consumer perception of drinking water quality. This study aims to evaluate the taste of the selected bottled and tap water samples using an electronic tongue (E-tongue) instead of a sensory test. Bottled and tap water's mineral components are related to the overall preference for water taste. Contrary to the sensory test, the potentiometric E-tongue method presented in this study distinguishes taste by measuring the mineral components in water, and the data obtained can be statistically analyzed. Eleven bottled water products from various brands and one tap water from I city in Korea were evaluated. The E-tongue data were statistically analyzed using multivariate statistical tools such as hierarchical clustering analysis (HCA), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the E-tongue method can clearly distinguish taste discrimination in drinking water differing in water quality based on the ion-related water quality parameters. The water quality parameters that affect taste discrimination were found to be total dissolved solids (TDS), sodium (Na+), calcium (Ca²⁺), magnesium (Mg²⁺), sulfate (SO₄^2-), chloride (Cl^-), potassium (K⁺) and pH. The distance calculation of HCA was used to quantify the differences between 12 different types of drinking water. The proposed E-tongue method is a practical tool to quantitatively evaluate the differences between samples in water quality items related to the ionic components. It can be helpful in quality control of drinking water.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.217-226
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• 2024

This study is a descriptive research study to figure out the effect of unstable an adult attachment, self-mercy and emotional recognition clarity on interpersonal skills targeting nursing freshman. From 27th of March 2023 to 7th of April 2023, data gathered from the nursing freshman of university in J city, G province were analyzed. Using IBM SPSS/25, the data was analyzed descriptive statistic t-test, ANOVA and multiple correlation analysis. Interpersonal skills have negative correlation with unstable adults attachment(r=-.19, p=.005), and also have positive correlation with self-mercy (r=.38, p<.001) and emotional recognition clarity (r=.28, p<.001). Using hierarchical multiple regression analysis of factors that effects on interpersonal skills of survey subjects, self-mercy was the factor predict one's interpersonal skills the most, extroverted, mixed and emotional recognition clarity in order. The higher self- mercy and emotional recognition clarity are, the bigger influences interpersonal skills have and 24.5% of explanatory power. For nursing school students, interpersonal skills was one of the essential qualities so various methods to improve their interpersonal skills should be figured out.

• Journal of Internet Computing and Services
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• v.25 no.3
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• pp.83-92
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• 2024

Recently, the importance of HR analytics for data-based decision-making in establishing and operating an effective human resource management system for companies is increasing. In addition, there is growing interest in the effect of employees' perceptions of organizational justice on positive organizational behavior. Therefore, in this study, among the various factors affecting teamwork behavior, we analyzed the impact on teamwork behavior such as perception of organizational justice and organizational culture. Organizational justice has a significant impact on the formation of members' attitudes, but its meaning may vary depending on the organizational context. In this study, we divided organizational justice into four types (procedural, distributive, interpersonal, and informational fairness) and confirmed their impact on teamwork behavior. In addition, organizational culture was divided into hierarchy culture and innovation culture, and how to regulate these relationships was examined. To analyze these relationships, individual-level data collected from 657 people at domestic companies were used for analysis. According to the analysis results, in a hierarchical culture, procedural justice and information justice had a positive influence on teamwork behavior through the mediating process of job satisfaction, and in an innovative culture, interpersonal justice and information justice had a positive influence on teamwork behavior through job satisfaction. It was confirmed to have a (+) effect. These research results provide implications for people management by indicating that, although organizational justice is important to members and organizations, it may be perceived differently and have different meanings depending on the organizational context. Through the use of the information presented in this study, we will provide value that can effectively and efficiently implement a company's human resource management system.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.81-96
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• 2013

Video information retrieval has become a very important issue because of the explosive increase in video data from Web content development. Meanwhile, content-based video analysis using visual features has been the main source for video information retrieval and browsing. Content in video can be represented with content-based analysis techniques, which can extract various features from audio-visual data such as frames, shots, colors, texture, or shape. Moreover, similarity between videos can be measured through content-based analysis. However, a movie that is one of typical types of video data is organized by story as well as audio-visual data. This causes a semantic gap between significant information recognized by people and information resulting from content-based analysis, when content-based video analysis using only audio-visual data of low level is applied to information retrieval of movie. The reason for this semantic gap is that the story line for a movie is high level information, with relationships in the content that changes as the movie progresses. Information retrieval related to the story line of a movie cannot be executed by only content-based analysis techniques. A formal model is needed, which can determine relationships among movie contents, or track meaning changes, in order to accurately retrieve the story information. Recently, story-based video analysis techniques have emerged using a social network concept for story information retrieval. These approaches represent a story by using the relationships between characters in a movie, but these approaches have problems. First, they do not express dynamic changes in relationships between characters according to story development. Second, they miss profound information, such as emotions indicating the identities and psychological states of the characters. Emotion is essential to understanding a character's motivation, conflict, and resolution. Third, they do not take account of events and background that contribute to the story. As a result, this paper reviews the importance and weaknesses of previous video analysis methods ranging from content-based approaches to story analysis based on social network. Also, we suggest necessary elements, such as character, background, and events, based on narrative structures introduced in the literature. We extract characters' emotional words from the script of the movie Pretty Woman by using the hierarchical attribute of WordNet, which is an extensive English thesaurus. WordNet offers relationships between words (e.g., synonyms, hypernyms, hyponyms, antonyms). We present a method to visualize the emotional pattern of a character over time. Second, a character's inner nature must be predetermined in order to model a character arc that can depict the character's growth and development. To this end, we analyze the amount of the character's dialogue in the script and track the character's inner nature using social network concepts, such as in-degree (incoming links) and out-degree (outgoing links). Additionally, we propose a method that can track a character's inner nature by tracing indices such as degree, in-degree, and out-degree of the character network in a movie through its progression. Finally, the spatial background where characters meet and where events take place is an important element in the story. We take advantage of the movie script to extracting significant spatial background and suggest a scene map describing spatial arrangements and distances in the movie. Important places where main characters first meet or where they stay during long periods of time can be extracted through this scene map. In view of the aforementioned three elements (character, event, background), we extract a variety of information related to the story and evaluate the performance of the proposed method. We can track story information extracted over time and detect a change in the character's emotion or inner nature, spatial movement, and conflicts and resolutions in the story.

• Journal of the Korean Society of Food Science and Nutrition
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• v.39 no.1
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• pp.54-63
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• 2010

Baicalin, a flavonoid, was shown to have diverse effects such as anti-inflammatory, anti-cancer, anti-viral, anti-bacterial and others. Recently, we found that the baicalin inhibits adipogenesis through the modulations of anti-adipogenic and pro-adipogenic factors of the adipogenesis pathway. In the present study, we further characterized the molecular mechanism of the anti-adipogenic effect of baicalin using microarray technology. Microarray analyses were conducted to analyze the gene expression profiles during the differentiation time course (0 day, 2 day, 4 day and 7 day) in 3T3-L1 cells with or without baicalin treatment. We identified a total of 3972 genes of which expressions were changed more than 2 fold. These 3972 genes were further analyzed using hierarchical clustering analysis, resulting in 20 clusters. Four clusters among 20 showed clearly up-regulated expression patterns (cluster 8 and cluster 10) or clearly down-regulated expression patterns (cluster 12 and cluster 14) by baicalin treatment for over-all differentiation period. The cluster 8 and cluster 10 included many genes which enhance cell proliferation or inhibit adipogenesis. On the other hand, the cluster 12 and cluster 14 included many genes which are related with proliferation inhibition, cell cycle arrest, cell growth suppression or adipogenesis induction. In conclusion, these data provide detailed information on the molecular mechanism of baicalin-induced inhibition of adipogenesis.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.213-226
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• 2011

In global supply chain, the scheduling problems of large products such as ships, airplanes, space shuttles, assembled constructions, and/or automobiles are complicated by nature. New scheduling systems are often developed in order to reduce inherent computational complexity. As a result, a problem can be decomposed into small sub-problems, problems that contain independently small scheduling systems integrating into the initial problem. As one of the authors experienced, DAS (Daewoo Shipbuilding Scheduling System) has adopted a two-layered hierarchical architecture. In the hierarchical architecture, individual scheduling systems composed of a high-level dock scheduler, DAS-ERECT and low-level assembly plant schedulers, DAS-PBS, DAS-3DS, DAS-NPS, and DAS-A7 try to search the best schedules under their own constraints. Moreover, the steep growth of communication technology and logistics enables it to introduce distributed multi-nation production plants by which different parts are produced by designated plants. Therefore vertical and lateral coordination among decomposed scheduling systems is necessary. No standard coordination mechanism of multiple scheduling systems exists, even though there are various scheduling systems existing in the area of scheduling research. Previous research regarding the coordination mechanism has mainly focused on external conversation without capacity model. Prior research has heavily focuses on agent-based coordination in the area of agent research. Yet, no scheduling domain has been developed. Previous research regarding the agent-based scheduling has paid its ample attention to internal coordination of scheduling process, a process that has not been efficient. In this study, we suggest a general framework for agent-based coordination of multiple scheduling systems in global supply chain. The purpose of this study was to design a standard coordination mechanism. To do so, we first define an individual scheduling agent responsible for their own plants and a meta-level coordination agent involved with each individual scheduling agent. We then suggest variables and values describing the individual scheduling agent and meta-level coordination agent. These variables and values are represented by Backus-Naur Form. Second, we suggest scheduling agent communication protocols for each scheduling agent topology classified into the system architectures, existence or nonexistence of coordinator, and directions of coordination. If there was a coordinating agent, an individual scheduling agent could communicate with another individual agent indirectly through the coordinator. On the other hand, if there was not any coordinating agent existing, an individual scheduling agent should communicate with another individual agent directly. To apply agent communication language specifically to the scheduling coordination domain, we had to additionally define an inner language, a language that suitably expresses scheduling coordination. A scheduling agent communication language is devised for the communication among agents independent of domain. We adopt three message layers which are ACL layer, scheduling coordination layer, and industry-specific layer. The ACL layer is a domain independent outer language layer. The scheduling coordination layer has terms necessary for scheduling coordination. The industry-specific layer expresses the industry specification. Third, in order to improve the efficiency of communication among scheduling agents and avoid possible infinite loops, we suggest a look-ahead load balancing model which supports to monitor participating agents and to analyze the status of the agents. To build the look-ahead load balancing model, the status of participating agents should be monitored. Most of all, the amount of sharing information should be considered. If complete information is collected, updating and maintenance cost of sharing information will be increasing although the frequency of communication will be decreasing. Therefore the level of detail and updating period of sharing information should be decided contingently. By means of this standard coordination mechanism, we can easily model coordination processes of multiple scheduling systems into supply chain. Finally, we apply this mechanism to shipbuilding domain and develop a prototype system which consists of a dock-scheduling agent, four assembly- plant-scheduling agents, and a meta-level coordination agent. A series of experiments using the real world data are used to empirically examine this mechanism. The results of this study show that the effect of agent-based platform on coordinated scheduling is evident in terms of the number of tardy jobs, tardiness, and makespan.

• Journal of The Korean Association For Science Education
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• v.39 no.5
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• pp.599-611
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• 2019

The purpose of this study is to analyze the systems thinking level of pre-service teachers using rubrics of evaluating systems thinking. For this purpose, systems thinking level model, which can be applied to education or science education, was selected through literature analysis. Eight pre-service teachers' systems thinking were investigated through the systems thinking analysis tool used in domestic research. The systems thinking presented by the pre-service teachers were transformed into the box type causal map using Sibley et al. (2007). Two researchers analyzed the systems thinking using rubrics of evaluating systems thinking. For data analysis, quantitative analysis was performed through correlation analysis using SPSS. In addition, the qualitative analysis of the box type causal map was conducted and the consistency with the quantitative analysis results was verified. The results indicated that the correlation between the 5-Likert systems thinking measurement instrument and the rubrics score was highly correlated with the Pearson product-moment of .762 (p <.05). In the hierarchical correlation of the systems thinking level, the STH model was analyzed with a very high correlation with the Pearson product-moment of .722~.791, and 4-step model was analyzed .381~.730. The qualitative analysis suggested the concept to be included in the low level of system thinking, the higher the level, the less the concept that is presented properly. In conclusion, the level of systems thinking can be derived as a result of research that there is clearly, a hierarchical part. Based on the results of this study, it is necessary to develop a systems thinking level model applicable to science education and develop and validate items that can measure the level of systems thinking.

• Korea Journal of Hospital Management
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• v.7 no.1
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• pp.41-63
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• 2002

The purpose of this study is to analyze the interrelation of influential factors in organizational conflict and organizational commitment. The data for this study were collected through a self-administered survey with a structured Questionnaire to 1,167 subjects from several nursing staff members, administration staff members and medical technicians of six hospitals. In this analysis frequency test, t-test, ANOVA, hierarchical multiple regression and structural equation model were used. The main findings of this study are as follows. 1. Factors which influence organizational conflict were analyzed. The type of occupation and the year of service were socio-demographic variables which influenced organizational conflict positively. Adjusted R square was 0.03. Perceptions on organizational structure and organizational culture were analyzed with two- level variables that were added. The findings were as follows. Adjusted R square increased to 0.25. The year of service, internal process culture and rational goal culture were positive variables. The design of organizational structure, human relations culture and open system culture were negative variables. 2. Variables which influence organizational commitment were analyzed. Age and the year of service were positive variables, while academic background based on high school education was a negative variable. Adjusted R square was 0.16. Perceptions on organizational structure and organizational culture were analyzed with two-level variables that were added. The findings were as follows. The characteristics of organizational structure, human relations culture and organizational culture were positive variables. Adjusted R square increased to 0.55. The variables of organizational conflict were added in 3 steps. Findings were as follows. The variables of hierarchical conflict showed negative influence and were included in two-level influential variables. Adjusted R square increased to 0.56. 3. Structural equation model was analyzed in order to examine the relation between organizational structure and the variables of organizational culture, organizational conflict and organizational commitment. Thirteen path coefficients out of seventeen path coefficients were significant. Age had negative influence on organizational conflict and positive influence on organizational commitment. The year of service had positive influence on organizational conflict and organizational commitment. The design of organizational structure, human relations culture and open system culture had negative influence on organizational. conflict. They had positive influence on organizational commitment. Internal process culture and rational goal culture had positive influence on organizational conflict. Organizational conflict had negative influence on organizational commitment. The squared multiple correlation of this model was 25.1% in organizational conflict and 52.7% in organizational commitment. The conclusion of this study is as follows. Factors in organizational structure and organizational culture, rather than socio-demographic factors, had a stronger influence on the organizational conflict and organizational commitment of hospitals. In order to decrease organizational conflict, to increase organizational commitment and to maximize the effectiveness of hospital management, it is necessary to understand the overall relation between organizational structure, organizational culture, organizational conflict and organizational commitment, with the effort of improving personalized factors and individual factors of organization management.