• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.131-154
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• 2022

Recently, researches on unstructured data analysis have been actively conducted with the development of information and communication technology. In particular, topic modeling is a representative technique for discovering core topics from massive text data. In the early stages of topic modeling, most studies focused only on topic discovery. As the topic modeling field matured, studies on the change of the topic according to the change of time began to be carried out. Accordingly, interest in dynamic topic modeling that handle changes in keywords constituting the topic is also increasing. Dynamic topic modeling identifies major topics from the data of the initial period and manages the change and flow of topics in a way that utilizes topic information of the previous period to derive further topics in subsequent periods. However, it is very difficult to understand and interpret the results of dynamic topic modeling. The results of traditional dynamic topic modeling simply reveal changes in keywords and their rankings. However, this information is insufficient to represent how the meaning of the topic has changed. Therefore, in this study, we propose a method to visualize topics by period by reflecting the meaning of keywords in each topic. In addition, we propose a method that can intuitively interpret changes in topics and relationships between or among topics. The detailed method of visualizing topics by period is as follows. In the first step, dynamic topic modeling is implemented to derive the top keywords of each period and their weight from text data. In the second step, we derive vectors of top keywords of each topic from the pre-trained word embedding model. Then, we perform dimension reduction for the extracted vectors. Then, we formulate a semantic vector of each topic by calculating weight sum of keywords in each vector using topic weight of each keyword. In the third step, we visualize the semantic vector of each topic using matplotlib, and analyze the relationship between or among the topics based on the visualized result. The change of topic can be interpreted in the following manners. From the result of dynamic topic modeling, we identify rising top 5 keywords and descending top 5 keywords for each period to show the change of the topic. Existing many topic visualization studies usually visualize keywords of each topic, but our approach proposed in this study differs from previous studies in that it attempts to visualize each topic itself. To evaluate the practical applicability of the proposed methodology, we performed an experiment on 1,847 abstracts of artificial intelligence-related papers. The experiment was performed by dividing abstracts of artificial intelligence-related papers into three periods (2016-2017, 2018-2019, 2020-2021). We selected seven topics based on the consistency score, and utilized the pre-trained word embedding model of Word2vec trained with 'Wikipedia', an Internet encyclopedia. Based on the proposed methodology, we generated a semantic vector for each topic. Through this, by reflecting the meaning of keywords, we visualized and interpreted the themes by period. Through these experiments, we confirmed that the rising and descending of the topic weight of a keyword can be usefully used to interpret the semantic change of the corresponding topic and to grasp the relationship among topics. In this study, to overcome the limitations of dynamic topic modeling results, we used word embedding and dimension reduction techniques to visualize topics by era. The results of this study are meaningful in that they broadened the scope of topic understanding through the visualization of dynamic topic modeling results. In addition, the academic contribution can be acknowledged in that it laid the foundation for follow-up studies using various word embeddings and dimensionality reduction techniques to improve the performance of the proposed methodology.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of Popular Narrative
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• v.25 no.4
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• pp.191-221
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• 2019

This study aims to analyze the post-humanistic imagination that has emerged as a major academic thesis in Korean literature, especially novels. In particular, this paper focuses on Cho Ha-hyung's two novels Chimera's Morning(2004) and A Prefabricated Bodhi Tree(2008), published in the early 2000s, for intensive analysis. Post-humanism can be seen as an extension of post-modernism that tried to overcome the limitations of modernity and seek to establish a new world view. In particular, this thought pays attention to the comprehensive understanding of how the rapid development of science and technology, which has developed since the 20th century, has changed the view of humanity and human-centered civilization itself. At the concrete level, it is developing in the direction of constructing a new subject idea by reflecting and dismantling Western-, reason-, and male-centered power mechanisms that are the core of modern civilization. Cho attempts to discover and re-illuminate the surrounding figures, non-humans, and objects that were not noticed in the classic works written in the past. This ideological flow reflects the fact that the concept of human beings, which had been dominated by the humanities in recent years, has been completely changed, and the natural science and technology perspective is applied to the discourse field in various ways. From the point of view of post-humanism, objects that have not been classified as humans and objects that were considered inferior to humans should be included in human or comparable levels. These questions generate interdisciplinary research tasks by involving the large categories of philosophy, such as ontology, epistemology and empirical fields, as well as calling for the participation of the entire literature, science and social sciences. Against the backdrop of a disaster-hit world, Chimera's Morning and A Prefabricated Bodhi Tree depict human beings as variants transformed by bio-technology, and creatures made out of the artificial intelligence built by computer simulations. Post-humanistic ideas in Cho's novels provide a reflective opportunity to comprehensively reconsider the world's shape and human identity reproduced in the text, and to re-explore boundary lines and hierarchy order that distinguish between human and non-human.

• Journal of Popular Narrative
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• v.25 no.1
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• pp.9-54
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• 2019

Since the birth of melodrama in the early Enlightenment era, it has flowed through various cultures and media. In order to grasp the principle of differentiation of melodrama and the direction of its change, a developmental approach to the formation process of melodrama is necessary. In this regard, this paper examines the formation process of modern melodrama and its aesthetic features around the time of the French Revolution. The modern melodrama was formed in the period between the end of the 18th century and the start of the 19th century. It was born at the intersectional point of the contradictions of the modern imagination and the political paradox of the French Revolution, which demanded an autonomous citizenship but did not recognize a woman as a citizen. The aesthetic of women's sacrifice and tears reproduced in the modern melodrama is a political aspiration to restore a corrupt society by glamorizing a woman as a moral icon. This was an icon to save a society under divide and crisis and a coordination of emotions to conceal sexist violence in the politics of the exclusion of women. The aesthetic of women's sacrifice and tears reproduced in modern melodrama has consistently been considered under negative evaluation such as a play of moral hypocrisy and vulgar drama. However, the academic interest in melodrama in the 1970s has been amplified due to the "Sirk-melo" which is a transition to the new aesthetic of women's sacrifice and tears, encompassing not only women, but also races and classes. In modern society, entering the era of uncertainty, where various social problems, national disasters, and global disasters have become commonplace, 'the aesthetic of women's sacrifice and tears' are shifting from gender differences to various victim narratives. Reviewing new theoretical trends and changes of recent melodrama as well as analyzing specific works are left as follow-up tasks.Since the birth of the melodrama in the early Enlightenment era, it has flowed through various cultures and media. In order to grasp the principle of differentiation of melodrama and the direction of its change, a developmental approach to the formation process of melodrama is basically necessary. In this regard, this paper examines the formation process of modern melodrama and its aesthetic features around the time of the French Revolution.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.265-276
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• 2023

The purpose of this study was to develop a plan to ensure that students lacking basic science skills acquire the minimum needed science learning ability while completing the common curriculum. We surveyed 27 elementary and secondary science teachers with experience in research and teaching related to basic skills support to investigate their perceptions of the criteria for minimum achievement standards using Consensual Qualitative Research (CQR) and Analytic Hierarchy Process (AHP). The results indicated that the science teachers tended to describe low achievers as lacking science learning competency, accumulating a science learning deficit, and lacking prerequisite knowledge. However, there were some differences in the characteristics that the elementary and secondary teachers paid attention to in students with insufficient science and basic academic skills. Specifically, the secondary teachers demonstrated greater sensitivity towards low learning motivation and difficulties in using scientific symbols, whereas the elementary teachers were more sensitive towards students' attitudes towards science or lack of experience. Furthermore, it has been observed that the prioritization of items, categorized by school level, differs in terms of setting minimum achievement standards to ensure basic skill support. This implies the need to develop minimum achievement standards considering various variables based on the school level. As there are diverse opinions among science teachers, depending on their expertise, regarding the factors to be considered when developing these standards to guarantee science and basic skill support. Based on the findings of the study, policy support is required to enhance teachers' professionalism in developing students' basic skills while considering the individual context and diversity of low achievers. Additionally, it is crucial to establish a shared vision for students lacking basic skills to reduce the gap between national policy and the practices of science teachers in ensuring support for basic skills.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.57-84
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• 2023

With the development of information and communications technology (ICT) and big data technology, anyone can easily obtain and utilize vast amounts of data through the Internet. Therefore, the capability of selecting high-quality data from a large amount of information is becoming more important than the capability of just collecting them. This trend continues in academia; literature reviews, such as systematic and non-systematic reviews, have been conducted in various research fields to construct a healthy knowledge structure by selecting high-quality research from accumulated research materials. Meanwhile, after the COVID-19 pandemic, remote healthcare services, which have not been agreed upon, are allowed to a limited extent, and new healthcare services such as health recommender systems (HRS) equipped with artificial intelligence (AI) and big data technologies are in the spotlight. Although, in practice, HRS are considered one of the most important technologies to lead the future healthcare industry, literature review on HRS is relatively rare compared to other fields. In addition, although HRS are fields of convergence with a strong interdisciplinary nature, prior literature review studies have mainly applied either systematic or non-systematic review methods; hence, there are limitations in analyzing interactions or dynamic relationships with other research fields. Therefore, in this study, the overall network structure of HRS and surrounding research fields were identified using citation network analysis (CNA). Additionally, in this process, in order to address the problem that the latest papers are underestimated in their citation relationships, the GraphSAGE algorithm was applied. As a result, this study identified 'recommender system', 'wireless & IoT', 'computer vision', and 'text mining' as increasingly important research fields related to HRS research, and confirmed that 'personalization' and 'privacy' are emerging issues in HRS research. The study findings would provide both academic and practical insights into identifying the structure of the HRS research community, examining related research trends, and designing future HRS research directions.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.6-7
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• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.1
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• pp.91-104
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• 2023

The records system is believed to have started in Italy in the 14th century in line with trade developments in Europe. In 1491, Luca Pacioli, a mathematician, and an Italian Franciscan monk wrote the first book that described double-entry accounting processes. In many countries, including Korea, the government accounting standards used single-entry bookkeeping rather than double-entry bookkeeping that can be aggregated by account subject. The cash-based and single-entry bookkeeping used by the government in the past had limitations in providing clear information on financial status and establishing a performance-oriented financial management system. Accordingly, the National Accounting Act (promulgated in October 2007) stipulated the introduction of double-entry bookkeeping and accrual accounting systems in the government sector from January 1, 2009. Furthermore, the Korean government has also introduced International Financial Reporting Standards (IFRS), and the System of National Accounts (SNA). Since 2014, Korea owned five national accounts. In Korea, valuation began with the 1968 National Wealth Statistics Survey. The academic origins of the valuation of national wealth statistics which had been investigated by due diligence every 10 years since 1968 are based on the 'Engineering Valuation' of professor Marston in the Department of Industrial Engineering at Iowa State University in the 1930s. This field has spread to economics, etc. In economics, it became the basis of capital stock estimation for positive economics such as econometrics. The valuation by the National Wealth Statistics Survey contributed greatly to converting the book value of accounting data into vintage data. And in 2000 National Statistical Office collected actual disposal data for the 1-digit asset class and obtained the ASL(average service life) by Iowa curve. Then, with the data on fixed capital formation centered on the National B/S Team of the Bank of Korea, the national wealth statistics were prepared by the Permanent Inventory Method(PIM). The asset classification was also classified into 59 types, including 2 types of residential buildings, 4 types of non-residential buildings, 14 types of structures, 9 types of transportation equipment, 28 types of machinery, and 2 types of intangible fixed assets. Tables of useful lives of tangible fixed assets published by the Korea Appraisal Board in 1999 and 2013 were made by the Iowa curve method. In Korea, the Iowa curve method has been adopted as a method of ASL estimation. There are three types of the Iowa curve method. The retirement rate method of the three types is the best because it is based on the collection and compilation of the data of all properties in service during a period of recent years, both properties retired and that are still in service. We hope the retirement rate method instead of the individual unit method is used in the estimation of ASL. Recently Korean government's accounting system has been developed. When revenue expenditure and capital expenditure were mixed in the past single-entry bookkeeping we would like to suggest that BOK and National Statistical Office have accumulated knowledge of a rational difference between revenue expenditure and capital expenditure. In particular, it is important when it is estimated capital stock by PIM. Korea also needs an empirical study on economic depreciation like Hulten & Wykoff Catalog A of the US BEA.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.247-256
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• 2019

The importance of the convergence education is getting more and more emphasized. But the university convergence education has not yet met today's needs. So this study is focused on showing effective practice methods and finding development directions of the university convergence criticism education. One of a significant trend of the contemporary academic education of liberal arts is the tendency of the convergent and integrative studies. What is essential in the convergent and integrative studies creativity. The zeitgeist of knowledge-based society is change and innovation. In response to its request, college education is being asked to do convergence education, And general education as the basis of convergence education is strengthened.

• Korean Journal of School Psychology
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• v.16 no.3
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• pp.231-263
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• 2019

The purpose of this study was to verify the effects of growth orientation, life satisfaction, perceived stress, positive psychological capital and interpersonal relationships in the group coaching program for the promotion of growth orientation for university students based on the model of the social-cognitive approach to motivation. The program consisted of eight topics: growth orientation, growth mindset and brain plasticity, self-directed goal setting, talent which is a product of ongoing effort, failure attitude and perspective change, positive emotion, thinking and behavior, value of growth orientation and self-coaching, respectively. The program comprised a total of eight sessions, 120 minutes each, and the final program was completed through a preliminary experiment with three university students. In order to verify the effectiveness of the program, 48 university students were divided into 16 in the experimental group, 16 in the comparative group, and 16 in the control group. The experimental group participated in the group coaching program to enhance the growth orientation based on the model of the social-cognitive approach to motivation developed in this study, the comparative group participated in a learning goal orientation improvement program based on an incremental implicit theory, and the control group did not carry out any program. Three groups were tested in pre, post, follow-up1(after 1 month) and follow-up2(after 3 months) in order to growth orientation, life satisfaction, perceived stress, positive psychological capital and interpersonal relationships. We performed analysis to confirm the homogeneity to the data of the three groups and to verify the interaction effects between times and groups. As a result, it was confirmed that the group coaching program to promote growth orientation, life satisfaction, perceived stress, positive psychological capital and interpersonal relationships had statistically significant effect and was more effective than the comparative program due to the larger effective size. Also, we confirmed that the coaching effect was sustained after the program was finished and more effectively maintained than the comparative program. Based on the results of this study, this study has academic implications because it verify the effectiveness of the group coaching for the promotion of the growth orientation by scient ic method.