• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.731-736
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• 2023

Recently, the medical field has been applying mandatory Electronic Medical Records (EMRs) and Electronic Health Records (EHRs) systems that computerize and manage medical records, and distributing them throughout the entire medical industry to utilize patients' past medical records for additional medical procedures. However, the conversations between medical professionals and patients that occur during general medical consultations and counseling sessions are not separately recorded or stored, so additional important patient information cannot be efficiently utilized. Therefore, we propose an electronic medical record system that uses speech recognition and natural language processing deep learning to store conversations between medical professionals and patients in text form, automatically extracts and summarizes important medical consultation information, and generates electronic medical records. The system acquires text information through the recognition process of medical professionals and patients' medical consultation content. The acquired text is then divided into multiple sentences, and the importance of multiple keywords included in the generated sentences is calculated. Based on the calculated importance, the system ranks multiple sentences and summarizes them to create the final electronic medical record data. The proposed system's performance is verified to be excellent through quantitative analysis.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.64-65
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• 2023

The purpose of this study was to assess the current status of cyber security at the Busan Port container terminal and derive strengthening factors through exploratory research. In recent years, the maritime industry has actively adopted Fourth Industrial Revolution technologies, resulting in changes in the form of ports, such as automated and smart terminals. While these changes have brought positive improvements in port efficiency, they have also increased the potential for cyber security incidents and threats, including information leakage through cargo handling equipment and ransomware attacks leading to terminal operations disruption. Especially in the case of ports, cyber security threats can have not only local effects within the port but also physical damage and implications for national security. However, despite the growing cyber security threats within ports, research related to domestic port cyber security remains limited. Therefore, this study aimed to identify factors for enhancing cyber security in ports and derive future enhancement strategies. The study conducted an analysis focusing on the Busan Port container terminal, which is one of the leading ports in South Korea actively adopting Fourth Industrial Revolution technologies, and conducted a survey of stakeholders in the Busan Port container terminal. Subsequently, exploratory factor analysis was used to derive strengthening factors. This study holds significance in providing directions for enhancing cyber security in domestic container ports in the future.

• Journal of IKEEE
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• v.28 no.3
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• pp.329-336
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• 2024

Organic light emitting diode(OLED) is distributed in layers with different refractive index, which leads to total internal reflection and low light extraction efficiency. As a result, light extraction technologies have been investigated that include structures such as MLA. However, technologies such as MLA are using petroleum-based polymers, which cause environmental problems during disposal. Therefore, this study investigates the use of eco-friendly polymers hydroxyethyl cellulose(HEC) and tannic acid(TA) to produce external light extraction films. HEC is biodegradable and has high transparency, making it suitable for eco-friend external light extraction films. The TA used as an additive is a polyphenolic molecule, which is expected to form strong hydrogen bonds with HEC. In addition, TA can protect OLED from damage by UV light through its phenolic groups. HECTA MLA films were produced by dissolving HEC and TA in water without using additional solvents and then imprinting them on MLA mould. When the HECTA MLA film was attached to the outside of the OLED and analysed, it showed a high Haze of more than 80%, and the external quantum efficiency and current efficiency of the OLED were improved by 38% and 39%, respectively, compared to the reference.

• Journal of Korea Entertainment Industry Association
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• v.15 no.1
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• pp.221-228
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• 2021

This study aims to provide basic data for developing hand functional training programs using a keyboard to see if there is a relationship between the smart keyboard input speed using both hands, the Dexterity of the hand and the eye-hand coordination ability. The smartphone keyboard input speed, Purdue Pegboard, Grooved Pegboard Test, and Korean-Developmental-Test of Visual Perception-Adolescent were evaluated for 40 university students Province. An independent sample t-test and one-way ANOVA were conducted to identify differences in smartphone keyboard input speed, dexterity, eye-hand coordination ability and visual-motion using both hands according to the general characteristics of the subjects. Pearson correlation was also conducted to find out the relationship between hand-used smartphone keyboard input speed, hand dexterity, eye-hand coordination ability and visual-motor. As a result, the smartphone keyboard input speed using both hands showed a correlation with the dominant hand in the Purdue Pegboard Test (r=-.313, p<.05). In addition, the input speed of the smartphone keyboard is Copying(r=-.333, p<.05), Visual Motor Search(r=.455, p<.01), Visual Motor speed(r=-.453, p<.01) and Form Constancy (r=-.341, p<.05) in the item of K-DTVP-A. Therefore, it is believed that it will be helpful in the development of a treatment program using a smartphone, and it is expected that the effectiveness of a treatment program using a smartphone will be proven through additional experimental studies in the future.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.193-202
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• 2019

This study focuses on what changes are required as to a curriculum of dance department in the university in the age of the 4th industrial revolution. By comparing and analyzing the curricula of dance department in the five universities in Seoul, five academic subjects as to curricula of dance department, which covers what to learn for dance education in the age of the 4th industrial revolution, are presented. First, dance integrative education, the integration of creativity and science education, can be referred to as a subject that stimulates ideas and creativity and raises artistic sensitivity based on STEAM. Second, the curriculum characterized by prediction of the future prospect through Big Data can be utilized well in dealing with dance performance, career path of dance-majoring people, and job creation by analyzing public opinion, evaluation, and feelings. Third, video education. Seeing the images as modern major media tends to occupy most of the expressive area of art, dance by dint of video enables existing dance work to be created as new form of art, expanding dance boundaries in academic and performing art viewpoint. Fourth, VR and AR are essential techniques in the era of smart media. Whether upcoming dance studies are in the form of performance or education or industry, for VR and AR to be digitally applied into every relevant field, keeping with the time, learning about VR and AR is indispensable. Last, the 4th industrial revolution and the curriculum of dance art are needed to foresee the changes in the 4th industrial revolution and to educate changes, development and seeking in dance curriculum.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.78-95
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• 2024

For the establishment and comparison of environmental plans across various domains, considering climate change and urban issues, it is crucial to build spatial data at the regional scale classified with consistent criteria. This study mapping the Local Climate Zone (LCZ) of Changwon City, where active climate and environmental research is being conducted, using the protocol suggested by the World Urban Database and Access Portal Tools (WUDAPT). Additionally, to address the fragmentation issue where some grids are classified with different climate characteristics despite being in regions with homogeneous climate traits, a filtering technique was applied, and the LCZ classification characteristics were compared according to the filtering radius. Using satellite images, ground reference data, and the supervised classification machine learning technique Random Forest, classification maps without filtering and with filtering radii of 1, 2, and 3 were produced, and their accuracies were compared. Furthermore, to compare the LCZ classification characteristics according to building types in urban areas, an urban form index used in GIS-based classification methodology was created and compared with the ranges suggested in previous studies. As a result, the overall accuracy was highest when the filtering radius was 1. When comparing the urban form index, the differences between LCZ types were minimal, and most satisfied the ranges of previous studies. However, the study identified a limitation in reflecting the height information of buildings, and it is believed that adding data to complement this would yield results with higher accuracy. The findings of this study can be used as reference material for creating fundamental spatial data for environmental research related to urban climates in South Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Journal of Korea Technology Innovation Society
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• v.17 no.2
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• pp.380-420
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• 2014

We increasingly see the importance of employees acquiring enough expert capability or innovation capability to prepare for ever growing uncertainties in their operation domains. However, despite the above circumstances, there have not been an enough number of researches on how operational input components for employees' innovation outcome, innovation activities such as acquisition, exercise and promotion effort of employee's innovation capability, and their resulting innovation outcome interact with each other. This trend is believed to have been resulted because most of the current researches on innovation focus on the units of country, industry and corporate entity levels but not on an individual corporation's innovation input components, innovation outcome and innovation activities themselves. Therefore, this study intends to avoid the currently prevalent study frames and views on innovation and focus more on the strategic policies required for the enhancement of an organization's innovation capabilities by quantitatively analyzing employees' innovation outcomes and their most suggested relevant innovation activities. The research model that this study deploys offers both linear and structural model on the trio of learning, innovation capability and innovation outcome, and then suggests the 4 relevant hypotheses which are quantitatively tested and analyzed as follows: Hypothesis 1] The different levels of innovation capability produce different innovation outcomes (accepted, p-value = 0.000<0.05). Hypothesis 2] The different amounts of learning time produce different innovation capabilities (rejected, p-value = 0.199, 0.220>0.05). Hypothesis 3] The different amounts of learning time produce different innovation outcomes. (accepted, p-value = 0.000<0.05). Hypothesis 4] the innovation capability acts as a significant parameter in the relationship of the amount of learning time and innovation outcome (structural modeling test). This structural model after the t-tests on Hypotheses 1 through 4 proves that irregular on-the-job training and e-learning directly affects the learning time factor while job experience level, employment period and capability level measurement also directly impacts on the innovation capability factor. Also this hypothesis gets further supported by the fact that the patent time absolutely and directly affects the innovation capability factor rather than the learning time factor. Through the 4 hypotheses, this study proposes as measures to maximize an organization's innovation outcome. firstly, frequent irregular on-the-job training that is based on an e-learning system, secondly, efficient innovation management of employment period, job skill levels, etc through active sponsorship and energization community of practice (CoP) as a form of irregular learning, and thirdly a model of Yί=f(e, i, s, t, w)+${\varepsilon}$ as an innovation outcome function that is soundly based on a smart system of capability level measurement. The innovation outcome function is what this study considers the most appropriate and important reference model.

• Journal of Sasang Constitutional Medicine
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• v.10 no.1
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• pp.215-233
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• 1998

The object of this study is 27 patients who had been treated in the Oriental Medical Hospital at Dong Eui Medical Center during 6 months from January 1998 to June 1998. We proceeded the judgment of Sasang Constitution by Questionaire of Sasang Constitution Classification II(QSCC II). The following conclusion were made in comparison with Questionaire of Sasang Constitution Classification II(QSCC II) and Questionaire of Pusan Sasang seminar. 1. The subject of "the facial type is small and sharp" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is more than Taeumin group and Soyangin group. 2. The subject of "the walking form is fast and shake the body" is significant differences in Sasang Constitution classification. The frequency of Taeumin group and Soeumin group is less than Soyangin group. 3. The subject of "the skin type is white and thin" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is more than Soyangin group, and the frequency of Taeumin group is low marks. 4. The subject of "the skin type is tender and dry" is significant differences in Sasang Constitution classification. The frequency of Taeumin group and Soyangin group is less than Soeumin group. 5. The subject of "the image of face is smart" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is more than Taeumin group and the frequency of Soyangin group is low marks. 6. The subject of "the sweating type is not sweatier" is significant differences in Sasang Constitution classification. The frequency of Taeumin group and Soeumin group is less than Soyangin group. 7. The subject of "the desire of eating is changeable accoding to emotion" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is more than Taeumin group and Soyangin group. 8. The subject of "the health is changeable accoding to the type of stool" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is more than Soyangin group and the frequency of Taeumin group is low marks. 9. The subject of "the type of voiding is changeable accoding to the drinking when they have a fever" is significant differences in Sasang Constitution classification. The frequency of Taeumin group and Soyangin group is less than Soeumin group. 10. The subject of "the skin type is soft" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is more than Taeumin group and Soyangin group. 11. The subject of "the chief complaint is the forgetfulness" is significant differences in Sasang Constitution classification. The frequency of Soeumin group is less than Taeumin group and Soyangin group.

• 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.