• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.928-938
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• 2019

Republic of Korea has established 'Transmission and Reception for Terrestrial UHDTV Broadcasting Service' standard based on ATSC 3.0, the next-generation broadcasting standard in North America and is now providing commercial services. Republic of Korea has been studying terrestrial UHDTV based disaster broadcasting service using the ATSC 3.0 AEA system's technology since 2018. ATSC 3.0 has established a standard for expanding disaster broadcasting services, which were used to be simple push-type text message broadcasting, by introducing bidirectional and rich-media transporting mechanisms. However, the disaster information is still focused on the general public, and disaster broadcasting service including detailed information for the vulnerable are still insufficient. In this paper, we proposed the optimized disaster broadcasting service for vulnerable populations based on ATSC 3.0 after defined the disaster vulnerable populations as the target of the service. And we defined the extension element of disaster broadcasting message for service provision. The proposed service can be an effective means to increase the possibility of disaster information reception and evacuation to vulnerable populations. In addition, it is expected to be used as a basic research for development of diverse and effective advanced services for vulnerable populations through linkage with existing disaster alerting and countermeasures studies.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.1
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• pp.58-68
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• 2002

Recently as recognition to prevent nature disasters is reaching the climax, the most important job of government official is to provide information related to the prevention of nature disasters through the Web and to bring notice to prevent disaster under people. Especially, if the case of daily forest fire hazard index is provided within visualization on Web, people may have more chances to understand about forest fire and less damages by large scale of forest fire. Forest fire hazard index presentation system developed in this paper presents daily forest fire hazard index on map visually also provides the information related to it in text format. In order to develop this system, CBDP(Component Based Development Process) is proposed in this paper. This development process tries to emphasize the view of reusability so that it has lifecycle which starts from requirement and domain analysis and finishes to component generation. Moreover, The concept of this development process tries to reflect component based method, which becomes hot issue in software field nowadays. In the future, the component developed in this paper may be possibly reused in other Web GIS application, which has similar function to it so that it may take less cost and time to develop other similar system.

• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.149-163
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• 2021

The 4th industrial revolution refers to the next-generation industrial revolution led by information and communication technologies such as artificial intelligence (AI), Internet of Things (IoT), robot technology, drones, autonomous driving and virtual reality (VR) and it also has made a significant impact on the development of the advertising industry. However, the world is rapidly changing to a non-contact, non-face-to-face living environment to prevent the spread of COVID 19. Accordingly, the role of the 4th industrial revolution and advertising is changing. Therefore, in this study, text analysis was performed using Big Kinds to examine the 4th industrial revolution and changes in advertising before and after COVID 19. Comparisons were made between 2019 before COVID 19 and 2020 after COVID 19. Main topics and documents were classified through LDA topic model analysis and Word2vec, a deep learning technique. As the result of the study showed that before COVID 19, policies, contents, AI, etc. appeared, but after COVID 19, the field gradually expanded to finance, advertising, and delivery services utilizing data. Further, education appeared as an important issue. In addition, if the use of advertising related to the 4th industrial revolution technology was mainstream before COVID 19, keywords such as participation, cooperation, and daily necessities, were more actively used for education on advanced technology, while talent cultivation appeared prominently. Thus, these research results are meaningful in suggesting a multifaceted strategy that can be applied theoretically and practically, while suggesting the future direction of advertising in the 4th industrial revolution after COVID 19.

• Journal of Korean Theatre Studies Association
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• no.53
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• pp.167-202
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• 2014

When video composes mise-en-scene during the performance, it reflects the aspect of contemporary image culture, where the individual as creator joins in the image culture through the device of cell phone and computer remediating the former video technology. It also closely related with the contemporary theatre culture in which 1960's and 1970's video art was weaved into the contemporary performance theatre. With these cultural background, theatre practitioners regarded media-friendly mise-en-scene as an alternative facing the cultural landscape the linear representational narrative did not correspond to the present culture. Nonetheless, it can not be ignored that video in the performance theatre is remediating its historical function: to criticize the social reality. to enrich the aesthetic or emotional reality. I focused video in the performance theatre could feature the object with the image by realizing the realtime relay, emphasizing the situation within the frame, and strengthening the reality by alluding the object as a gesutre. So I explored its two historical manuel. First, video recorded the spot, communicated the information, and arose the audience's recognition of the object to its critical function. Second, video in performance theatre could redistribute perceptual way according to the editing method like as close up, slow motion, multiple perspective, montage and collage, and transformation of the image to the aesthetic function. Reminding the historical function of video in contemporary performance theatre, I analyzed two shows, Schaubuhne's Hamlet and Lenea de Sombra's Amarillo which were introduced to Korean audiences during the 2010 Seoul Theatre Olympics. It is known to us that Ostermeir found real social reality as a text and made the play the context. In this, he used video as a vehicle to penetrate the social reality through the hero's perspective. It is also noteworthy that Ostermeir understood Hamlet's dilemma as these days' young generation's propensity. They delayed action while being involved in image culture. Besides his use of video in the piece revitalized the aesthetic function of video by hypermedial perceptual method. Amarillo combined documentary theatre method with installation, physical theatre, and video relay on the spot, and activated aesthetic function with the intermediality, its interacting co-relationship between the media. In this performance theatre, video has recorded and pursued the absent presence of the real people who died or lost in the desert. At the same time it fantasized the emotional aspect of the people at the moment of their death, which would be opaque or non prominent otherwise. As a conclusion, I found the video in contemporary performance theatre visualized the rupture between the media and perform their intermediality. It attempted to disturb the transparent immediacy to invoke the spectator's perception to the theatrical situation, to open its emotional and spiritual aspect, and to remind the realities as with Schaubuhne's Hamlet and Lenea de Sombra's Amarillo.

• Journal of Korean Library and Information Science Society
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• v.52 no.2
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• pp.401-428
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• 2021

Recently, libraries are trying to communicate with users using various social media. Among them, Instagram is the most used SNS by users recently. Therefore, in this study, in order to effectively operate the library Instagram, we looked at how Instagram in the library is operated, what posts and contents people are interested in, and how the library can utilize it. By analyzing the Instagram operation status of Instagram, we tried to suggest improvement plans and activation plans. For this purpose, theoretical background research on SNS and Instagram, analysis of prior research, and related data were collected and analyzed. Next, for 82 domestic library accounts opened on Instagram, the library type, region, and Instagram account number of posts, 'followers', 'follows', images, etc. were collected, and the Text, hashtags, upload date, number of 'likes' and comments were analyzed. As a result of the study, it was found that increasing followers, uploading user-customized posts, formalizing account profiles, using library-specific hashtags, and communication with users are necessary to activate library Instagram.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.241-264
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• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.59-65
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• 2021

This is a case study on the use of Albert Camus' La Peste, which has gained its popularity in today's generation of post-COVID as well as the use of big data analysis tools for major and elective classes. First, we asked students majoring in French to compare the use of vocabulary and the number of appearances for characters using big data analysis, for about 400 pages of the original text. As a result, we were able to confirm a similar relationship between Camus' Absurdism and the vocabulary used within La Peste, in addition to noting the heavy frequency of resistant characters. Students in elective classes were asked to read the literature in a Korean-translated version to determine the frequency of vocabulary and characters' appearances. Students were able to strongly relate to La Peste due to its commonality between COVID and the plague in the literature. We also received high levels of class satisfaction regarding the use of big data analysis tools. The students showed a positive response both towards choosing La Peste as the work of literature and using big data, the main tool in the Fourth Industrial Evolution. We were able to identify good results even in a non-contact environment, as long as the literature does not rely on traditional methods but rather lectures to reflect current situations.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.