• Journal of The Geomorphological Association of Korea
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• v.25 no.3
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• pp.43-55
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• 2018

This study aimed to identify different sedimentary environments of Gochang coast according to geomorphic conditions of each bore hole. To achieve the aim, this study utilized the classification of sedimentary environmental conditions of surface sediment, which was based on grain size distribution characteristics.In other words, three sedimentary environmental conditions ofsandy flat + sand beach, coastal sand dune and weathered bedrock soil, which were distinguished based on grain size distribution characteristics of mean-sorting for surface sediments, were applied to the sediments of bore holes. Four sedimentary environments could be identified in Gochang coast. First, the lake sedimentary environment originated from terrestrial sediments seems to have been dominated by weathered bedrock soil that the surface flow has deposited in a coastal wetland or a boundary, which is affected by the sea. Second, the lake sedimentary environment that is little affected by coastal sand dunes is located at the center of a valley, which is connected to the land, and the dune slack of Saban-ri. The surface flow of weather bedrock soil is the main source of deposits. However, there seems to have been a temporary influence of the sea. Third, the lake sedimentary environment that is strongly affected by coastal sand dunes is located at the dune slack of Yeongjeong-ri. This environment shows traces of a change from a coastal sand dune into the dune slack. Finally, the coastalsand dune sedimentary environment, which wasinvestigated by boring the current coastal sand dune, shows a temporary influence of the land but seems to have maintained the overall stability. Consequently, this study demonstrated that the grain size distribution characteristics of the present surface sediments could be effectively applied to identify the sedimentary environments of the paleo bore hole sediments. In addition, the paleo change of sedimentary environment could also be identified in many places of Gochang coast. If the results of this study are combined with the age dating and geochemical analysis in future works, the paleo environmental change in Gochang coast will be restored more precisely.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.15-28
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• 2022

Due to recent expansion of online market such as clothing, utilizing customer review has become a major marketing measure. User review has been used as a tool of analyzing sentiment of customers. Sentiment analysis can be largely classified with machine learning-based and lexicon-based method. Machine learning-based method is a learning classification model referring review and labels. As research of sentiment analysis has been developed, multi-modal models learned by images and video data in reviews has been studied. Characteristics of words in reviews are differentiated depending on products' and customers' categories. In this paper, sentiment is analyzed via considering review data and metadata of products and users. Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM), Self Attention-based Multi-head Attention models and Bidirectional Encoder Representation from Transformer (BERT) are used in this study. Same Multi-Layer Perceptron (MLP) model is used upon every products information. This paper suggests a multi-modal sentiment analysis model that simultaneously considers user reviews and product meta-information.

• Journal of the Korean earth science society
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• v.43 no.3
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• pp.430-445
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• 2022

The purpose of this study was to explore the learning effects in elementary school students who participated in a geological field trip conducted under the theme 'minerals and rocks', focusing on novelty space. A total of 10 sixth-grade students participated in this program held at a public elementary school in Seoul as part of after-school club activities. Students observed mineral and rock samples in a classroom and outdoor learning environment. The authors collected activity papers (texts, drawing), researchers' participation notes, video and audio recordings containing the study participants' activities, and post-interview data To analyze the learning effects in the cognitive domain of students, the observation analysis framework for rock classification of Remmen and Frøyland (2020) and the rock description analysis framework of Oh (2020) were used. Additionally, to explore the learning effects of psychological and geographic areas, students' drawings, texts, discourses, and interview data were inductively analyzed. The results showed that the students demonstrated 'everyday' and 'transitional' observations in the classroom learning environment, while in the outdoor learning environment (school playground, community-based activities), they demonstrated 'transitional' and 'scientific' observations. Moreover, as the scientific observation stage progressed, more types of descriptive words for rocks were used. In terms of psychological and geographic aspects, students showed their selection of places to explore familiar outdoor learning environments, positive perceptions of outdoor learning, and aesthetic appreciation. Finally, this study not only discussed novelty space as a tool for analyzing students' learning effects but also suggested the need for an academic approach considering new learning environments, such as learning through virtual field trips.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.10-21
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• 2022

In order to improve formal presentation attitudes such as presentation of job interviews and presentation of project results at the company, there are few automated methods other than observation by colleagues or professors. In previous studies, it was reported that the speaker's stable speech and gaze processing affect the delivery power in the presentation. Also, there are studies that show that proper feedback on one's presentation has the effect of increasing the presenter's ability to present. In this paper, considering the positive aspects of correction, we developed a program that intelligently corrects the wrong presentation habits and attitudes of college students through facial analysis of videos and analyzed the proposed program's performance. The proposed program was developed through web-based verification of the use of redundant words and facial recognition and textualization of the presentation contents. To this end, an artificial intelligence model for classification was developed, and after extracting the video object, facial feature points were recognized based on the coordinates. Then, using 4000 facial data, the performance of the algorithm in this paper was compared and analyzed with the case of facial recognition using a Teachable Machine. Use the program to help presenters by correcting their presentation attitude.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.1-18
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• 2021

While content word-based frequency analysis has obvious limitations to intentional deception or irony, KLIWC has evolved into functional word analysis and KrKwic has evolved as a way to visualize co-occurrence frequencies. However, after more than 10 years of development, several issues still need improvement. Therefore, we tried to develop a new psychological language analysis program by analyzing KLIWC and KrKwic. First, the two programs were analyzed. In particular, the morpheme classification of KLIWC and the Korean morpheme analyzer was compared to enhance the functional word analysis function, and the psychological dictionary were analyzed to strengthen the psychological analysis. As a result of the analysis, the Hannanum part-of-speech analyzer was the most subdivided, but KLIWC for personal pronouns and KKMA for endings and endings were more subdivided, suggesting the integrated use of multiple part-of-speech analyzers to strengthen functional word analysis. Second, the research trends of studies that analyzed texts with these programs were analyzed. As a result of the analysis, the two programs were used in various academic fields, including the field of Interdisciplinary Studies. In particular, KrKwic was used a lot for the analysis of papers and reports, and KLIWC was used a lot for the comparative study of the writer's thoughts, emotions, and personality. Based on these results, the necessity and direction of development of a new psychological language analysis program were suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.225-227
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• 2022

Now In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office in Seoul has built a control center for CCTV control and is building information such as people, vehicle types, license plate recognition and color classification into big data through 24-hour artificial intelligence intelligent image analysis. Seoul Metropolitan Government has signed MOUs with the Ministry of Land, Infrastructure and Transport, the National Police Agency, the Fire Service, the Ministry of Justice, and the military base to enable rapid response to emergency/emergency situations. In other words, we are building a smart city that is safe and can prevent disasters by providing CCTV images of each ward office. In this paper, the CCTV image is designed to extract the characteristics of the vehicle and personnel when an incident occurs through artificial intelligence, and based on this, predict the escape route and enable continuous tracking. It is designed so that the AI automatically selects and displays the CCTV image of the route. It is designed to expand the smart city integration platform by providing image information and extracted information to the adjacent ward office when the escape route of a person or vehicle related to an incident is expected to an area other than the relevant jurisdiction. This paper will contribute as basic data to the development of smart city integrated platform research.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.1
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• pp.29-41
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• 2023

In landscape studies, the concept of naturalness was vast in its categories from physical space to cognitive systems, making it difficult to define terms at once. Therefore, this study summarized the concept and evaluation attributes of 'naturalness' used in the literature through systematic review (SR), and identified the scope of individual attributes that constitute the meaning of naturalness. In addition, the individual attributes classified in previous studies were identified as the meaning chain, one of the cognitive linguistic research methods, and applied to papers targeting naturalness among domestic landscape studies to organize a polysemous meaning system. Meaning chain is a suitable method for grasping words whose meaning expands in a chain due to family resemblance around prototypical meaning, and the dimension is classified according to the classification of naturalness evaluation items and a multi-semantic chain system of naturalness concepts discussed in domestic academia. The results of the study are as follows. First, the attributes of naturalness extracted through foreign landscape literature were classified into four areas: nature perceived as wilderness, nature as non-artificiality, nature as visual landscape, and nature as experience, and 13 detailed attributes. Second, these detailed attributes are generally consistent with domestic landscape studies, but their specific cases were different, and a Korean context was presented in perception of time accumulation, also they suggested that there may be a mutual conflict between naturalness attributes.

• Korean Journal of Heritage: History & Science
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• v.56 no.1
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• pp.162-180
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• 2023

The World Heritage Committee decided to make "cultural landscapes" a world heritage category in the 16th Session of the UNESCO General Conference. The decision was made from a recognition of the importance of interactions between human beings and the natural environment or between cultural heritage and natural heritage. Many countries have created policies and institutions to protect their own cultural landscapes along with the changing times. Korea, however, has not obviously defined the concepts and categories of its cultural landscapes, but manages policies and institutions based on the concept of a scenic spot, which has some similar meanings. In addition, it even borrows the "list of landscape adjectives," one of the representative methods for managing landscapes, from foreign countries. With this background, this paper suggested how to define cultural landscapes according to the global development flow. It created a list of cultural landscape adjectives by gathering the adjectives that can properly express local cultural landscapes in Korea. In particular, it collected 4,556 articles from a local newspaper by focusing on the case of Shinan-gun, Jeollanam-do, and analyzed key words and adjectives included in them by using big data analysis. The results suggested by this paper, such as the "classification table of cultural landscape types," "list of cultural landscape adjectives" and "network map of nouns/adjectives" can be applied to research on other localities, and furthermore, used as basic data for finding and protecting the characteristics of local cultural landscapes in Korea.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.33-43
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• 2023

Not only emotions affect physical sensations, but they also have an impact on physical movements. The responses to emotions vary depending on the type of emotional stimuli. However, research on the effects of emotional stimuli on the activation of bodily movements has not been rigorously examined, and these effects have not been investigated in Autonomous Emotion Recognition (AER) systems. In this study, we aimed to compare the emotional responses of 20 participants to three types of emotional stimuli (words, pictures, and videos) and investigate their activation or deactivation for the AER system. Our dependent measures included emotional responses, computer-based self-reporting methods, and bodily movements recorded using motion capture devices. The results suggested that video stimuli elicited higher levels of emotional movement, and emotional movement patterns were similar across different types of emotional stimuli for happiness, sadness, anger, and neutrality. Additionally, the findings indicated that bodily changes observed during video stimuli had the highest classification accuracy. These findings have implications for future research on the bodily changes elicited by emotional stimuli.

• 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.