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Exploring the Humanistic Practice of Je Baek-seok (齊白石(제백석)의 인학(印學)적 실천 탐색)

  • Zhu, Yuanye
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.1
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    • pp.427-436
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    • 2023
  • Je Baek-seok, who is well versed in poetry, calligraphy, painting, and sculpture, has established himself as the most outstanding painter and pavilion in the history of modern and contemporary Chinese art. During the Ming and Qing Dynasties, the art of the pavilion was developed greatly during the enlightenment period, with the emergence of many masters of the pavilion, including Jeonggyeong, Hwanghwangseokyeo, Oyangji, Jo Ji-gyeom, Hwang Mok-bo, and Oh Chang-seok. Je Baek-seok formed an original ritual under this social background. Je Baek-seok's tactics were formed by imitating works from the Hanwi period, and he harmonized Jin Kwon, Sopan, and Janggunin while using the penmanship of the Cheonbal Shinchambi based on the "Sasam Gongsanbi." In addition, by boldly using the Danipdo method, it is possible to use the human face as much as possible while fully exhibiting the artistry of calligraphy and adding to the atmosphere of gold stone. This paper mainly analyzed and reviewed the process of Je Baek-seok's transcription transformation and humanities practice from two aspects. First, it is planned to summarize the process of Je Baek-seok's transformation into a Jeonseo. Second, Je Baek-seok's humanities practice was analyzed. This paper will further understand Je Baek-seok's humanistic ideas and practical search by clarifying the originality of Je Baek-seok's engraving art with examples of Je Baek-seok's works, and it is believed that this will provide future scholars with learning paths and rich experiences.

Literary Text and the Cultural Interpretation - A Study of the Model of 「History of Spanish Literature」 (문학텍스트와 문학적 해석 -「스페인 문학사」를 통한 모델 연구)

  • Na, Songjoo
    • Cross-Cultural Studies
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    • v.26
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    • pp.465-485
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    • 2012
  • Instructing "History of Spanish Literature" class faces various types of limits and obstacles, just as other foreign language literature history classes do. Majority of students enter the university without having any previous spanish learning experience, which means, for them, even the interpretation of the text itself can be difficult. Moreover, the fact that "History of Spanish Literature" is traced all the way back to the Middle Age, students encounter even more difficulties and find factors that make them feel the class is not interesting. To list several, such factors include the embarrassment felt by the students, antiquated expressions, literature texts filled with deliberately broken grammars, explanations written in pretentious vocabularies, disorderly introduction of many different literary works that ignores the big picture, in which in return, reduces academic interest in students, and finally general lack of interest in literate itself due to the fact that the following generation is used to visual media. Although recognizing such problem that causes the distortion of the value of our lives and literature is a very imminent problem, there has not even been a primary discussion on such matter. Thus, the problem of what to teach in "History of Spanish Literature" class remains unsolved so far. Such problem includes wether to teach the history of authors and literature works, or the chronology of the text, the correlations, and what style of writing to teach first among many, and how to teach to read with criticism, and how to effectively utilize the limited class time to teach. However, unfortunately, there has not been any sorts of discussion among the insructors. I, as well, am not so proud of myself either when I question myself of how little and insufficiently did I contemplate about such problems. Living in the era so called the visual media era or the crisis of humanity studies, now there is a strong need to bring some change in the education of literature history. To suggest a solution to make such necessary change, I recommended to incorporate the visual media, the culture or custom that students are accustomed to, to the class. This solution is not only an attempt to introduce various fields to students, superseding the mere literature reserch area, but also the result that reflects the voice of students who come from a different cultural background and generation. Thus, what not to forget is that the bottom line of adopting a new teaching method is to increase the class participation of students and broaden the horizon of the Spanish literature. However, the ultimate goal of "History of Spanish Literature" class is the contemplation about humanity, not the progress in linguistic ability. Similarly, the ultimate goal of university education is to train students to become a successful member of the society. To achieve such goal, cultural approach to the literature text helps not only Spanish learning but also pragmatic education. Moreover, it helps to go beyond of what a mere functional person does. However, despite such optimistic expectations, foreign literature class has to face limits of eclecticism. As for the solution, as mentioned above, the method of teaching that mainly incorporates cultural text is a approach that fulfills the students with sensibility who live in the visual era. Second, it is a three-dimensional and sensible approach for the visual era, not an annotation that searches for any ambiguous vocabularies or metaphors. Third, it is the method that reduces the burdensome amount of reading. Fourth, it triggers interest in students including philosophical, sociocultural, and political ones. Such experience is expected to stimulate the intellectual curiosity in students and moreover motivates them to continues their study in graduate school, because it itself can be an interesting area of study.

Video Analysis System for Action and Emotion Detection by Object with Hierarchical Clustering based Re-ID (계층적 군집화 기반 Re-ID를 활용한 객체별 행동 및 표정 검출용 영상 분석 시스템)

  • Lee, Sang-Hyun;Yang, Seong-Hun;Oh, Seung-Jin;Kang, Jinbeom
    • 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.

A Study on Outplacement Countermeasure and Retention Level Examination Analysis about Outplacement Competency of Special Security Government Official (특정직 경호공무원의 전직역량에 대한 보유수준 분석 및 전직지원방안 연구)

  • Kim, Beom-Seok
    • Korean Security Journal
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    • no.33
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    • pp.51-80
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    • 2012
  • This study is to summarize main contents which was mentioned by Beomseok Kim' doctoral dissertation. The purpose of this study focuses on presenting the outplacement countermeasure and retention level examination analysis about outplacement competency of special security government official through implement of questionnaire method. The questionnaire for retention level examination including four groups of outplacement competency and twenty subcategories was implemented in the object of six hundered persons relevant to outplacement more than forty age and five grade administration official of special security government officials, who have outplacement experiences as outplacement successors, outplacement losers, and outplacement expectants, in order to achieve this research purpose effectively. The questionnaire examination items are four groups of outplacement competency and twenty subcategories which are the group of knowledge competency & four subcategories including expert knowledge, outplacement knowledge, self comprehension, and organization comprehension, the group of skill competency & nine subcategories including job skill competency, job performance skill, problem-solving skill, reforming skill, communication skill, organization management skill, crisis management skill, career development skill, and human network application skill, the group of attitude-emotion competency & seven subcategories including positive attitude, active attitude, responsibility, professionalism, devoting-sacrificing attitude, affinity, and self-controlling ability, and the group of value-ethics competency & two subcategories including ethical consciousness and morality. The respondents highly regard twenty-two outplacement competency and they consider themselves well-qualified for the subcategories valued over 4.0 such as the professional knowledge, active attitude, responsibility, ethics and morality while they mark the other subcategories below average still need to be improved. Thus, the following is suggestions for successful outplacement. First, individual effort is essential to strengthen their capabilities based on accurate self evaluation, for which the awareness and concept need to be redefined to help them face up to the reality by readjusting career goal to a realistic level. Second, active career development plan to improve shortcoming in terms of outplacement competency is required. Third, it is necessary to establish the infrastructure related to outplacement training such as ON-OFF Line training system and facilities for learning to reinforce user-oriented outplacement training as a regular training course before during after the retirement.

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A Study on Enhancing Personalization Recommendation Service Performance with CNN-based Review Helpfulness Score Prediction (CNN 기반 리뷰 유용성 점수 예측을 통한 개인화 추천 서비스 성능 향상에 관한 연구)

  • Li, Qinglong;Lee, Byunghyun;Li, Xinzhe;Kim, Jae Kyeong
    • Journal of Intelligence and Information Systems
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    • v.27 no.3
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    • pp.29-56
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    • 2021
  • Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.