• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.565-570
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• 2023

There are people who are sensitive to cosmetic ingredients, such as pregnant women and skin disease patients. There are also people who experience side effects from cosmetics. To avoid this, it is cumbersome to search for harmful ingredients in cosmetics one by one when shopping. In addition, knowing and remembering functional ingredients that suit you is helpful when purchasing new cosmetics. There is a need for a system that allows you to immediately know the cosmetics ingredients in the field through photography. In this paper, we introduce an application for smartphones, <Hwa Ahn>, which allows you to immediately know the cosmetics ingredients by photographing the ingredients displayed in the cosmetics. This system is more effective and convenient than the existing system in that it automatically recognizes and automatically classifies the ingredients of the cosmetic when the camera is illuminated on the cosmetic ingredients or retrieves the photos of the cosmetic ingredients from the album. If the system is widely used, it is expected that it will prevent skin diseases caused by cosmetics in daily life and reduce purchases of cosmetics that are not suitable for you.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.2
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• pp.31-45
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• 2023

This study deals with exploring qualitative steps and paths that appear as YouTube users' usage time increases quantitatively. For the study, I applied theories from psychology and neuroscience, subdivided the interval between the personalization algorithm of the recommendation system, and active use and analyzed the relationship between variables in this process. According to the theory behavioral model theory (FBM), variable reward, and dopamine addiction were applied. Personalization algorithms easy clicks as triggers according to associated content presentation functions in behavioral model theory (FBM). Variable rewards increase motivational effectiveness with unpredictability of the content you search, and dopamine nation is summarized as stimulating the dopaminergic nerve to continuously and actively consume content. This study is expected to make an academic and practical contribution in that it divides the purpose of use of content in the personalization algorithm and active use section into four stages from a psychological perspective: first use, reuse, continuous use, and active use, and analyzes the path.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.113-128
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• 2022

The objective of this study is to pay attention to the personal media environment that is in the center of rapid changes in the media industry, to especially explore the activity area of one-person or minority media creators who lead the mobile media environment that could be connected, watched, and produced anywhere, and to closely examine the mutual ecosystem between creators and viewers. Especially, paying attention to the recommendation service YouTube provides, for example, based on the big data algorithm related to users' habitual use, when users' data used are provided more, the users face the advanced service, this study aimed to examine the effects of recommendation service on the formation of trust between user and producer, user flow, and subscription intention, and also to demonstrate the process of forming this mutual relation through concrete data. In the conclusion, implications that can be inferred based on the research results and suggestions for further research in the future were presented.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.425-427
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• 2021

Entering the modern society, due to changes in daily life as well as social life, the sleep deprivation and unsatisfactory sleep environment that modern people have, ranked the lowest in the sleep deprivation nation in the world and the lowest in the nation considered to be sleep deprivation. This is about 'sleep pillows using Arduino,' which can improve the 'sleep environment', which is the 2nd largest cause of sleep deprivation. The few minutes before you go to sleep, the moment of time, can determine the quality of your sleep, and the quality of your sleep determines the satisfaction of your daily life. Using Arduino, you can improve the quality of your sleep through various functions. Through Arduino, you can create a sleeping environment for the sleeper by adjusting the sleeper's breathing measurement, lighting, and Bluetooth speaker and create an environment that suits you. Through this, we will be able to improve the sleep deprivation of modern people and have a more prosperous life.

• Journal of Information Processing Systems
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• v.18 no.6
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• pp.729-740
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• 2022

Netflix, Amazon Prime, and YouTube are the most popular and fastest-growing streaming services globally. It is a matter of great interest for the streaming service providers to preview their service infrastructure and streaming strategy in order to provide new streaming services. Hence, the first part of the paper presents a detailed survey of the Content Distribution Network (CDN) and cloud infrastructure of these service providers. To understand the streaming strategy of these service providers, the second part of the paper deduces a common quality-of-service (QoS) model based on rebuffering time, bitrate, progressive download ratio, and standard deviation of the On-Off cycle. This model is then used to analyze and compare the streaming behaviors of these services. This study concluded that the streaming behaviors of all these services are similar as they all use Dynamic Adaptive Streaming over HTTP (DASH) on top of TCP. However, the amount of data that they download in the buffering state and steady-state vary, resulting in different progressive download ratios, rebuffering levels, and bitrates. The characteristics of their On-Off cycle are also different resulting in different QoS. Hence a thorough adaptive bit rate (ABR) analysis is presented in this paper. The streaming behaviors of these services are tested on different access network bandwidths, ranging from 75 kbps to 30 Mbps. The survey results indicate that Netflix QoS and streaming behavior are significantly consistent followed by Amazon Prime and YouTube. Our approach can be used to compare and contrast the streaming services' strategies and finetune their ABR and flow control mechanisms.

• Women's Health Nursing
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• v.29 no.3
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• pp.179-189
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• 2023

Purpose: This scoping review investigated the content and quality of YouTube videos on women's health. Methods: A literature search of the Cochrane Library, PubMed, Embase, CINAHL, ERIC, and RISS databases was performed using the keywords "('youtube'/exp OR youtube OR 'social media'/exp OR 'social media' OR (('social'/exp OR social) AND ('media'/exp OR media))) AND ('female health care' OR (('female'/exp OR female) AND ('health'/exp OR health) AND ('care'/exp OR care)))" from February 21 to 27, 2023. Peer-reviewed analytic studies in English or Korean that focused on women's health using YouTube were included. Results: The review identified 21 articles that covered various themes related to women's health, such as breast cancer, urinary disease, sexual health, pelvic organ prolapse, the human papillomavirus vaccine, Papanikolaou smears, contraception, women's health information during the coronavirus disease 2019 pandemic, obstetric epidural anesthesia, and placenta accreta. However, the overall quality of the content was low, inaccurate, unreliable, and misleading. Conclusion: This scoping review demonstrated that YouTube videos on women's health covered diverse topics, but the quality of the content needed improvement. More reliable and high-quality videos produced by academic institutes and healthcare professionals specializing in women's health are needed for social media to be usable as a reliable source of women's health information. The high number of views and shares received by the videos underscores the importance of providing accurate and reliable information on women's health.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.15-29
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• 2024

With recent advances in information and communication technology, YouTube has become a powerful online space for users to create and share content about their interests and experiences, creating new cultural phenomena. In particular, there needs to be more research on social media in the manufacturing sector because, unlike distribution and retail, there has been relatively little direct contact with consumers. YouTube can positively affect firms' performance by promoting products and brands. On the other hand, it can also cause risks, such as production disruption due to rumors or misinformation. Thus, it is necessary for firms to examine how information about an electric automobile defects spreads on YouTube according to the number of subscribers and views through statistical network analysis.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.91-105
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• 2024

Car accidents occur as a result of collisions between vehicles, leading to both vehicle damage and personal and material losses. This study developed a vehicle accident detection model based on 2,550 image frames extracted from car accident videos uploaded to YouTube, captured by CCTV. To preprocess the data, bounding boxes were annotated using roboflow.com, and the dataset was augmented by flipping images at various angles. The You Only Look Once version 8 (YOLOv8) model was employed for training, achieving an average accuracy of 0.954 in accident detection. The proposed model holds practical significance by facilitating prompt alarm transmission in emergency situations. Furthermore, it contributes to the research on developing an effective and efficient mechanism for vehicle accident detection, which can be utilized on devices like smartphones. Future research aims to refine the detection capabilities by integrating additional data including sound.

• Journal of Contemporary Eastern Asia
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• v.23 no.1
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• pp.18-34
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• 2024

In what was labeled the "nut rage" incident, the vice president of Korean Air, Hyun-Ah Cho (Heather Cho), demonstrated behavior that exemplifies corporate transgression and deviation from societal moral standards toward a flight attendant aboard a flight. Such behavior instigated the public to express negative sentiment on various social media platforms. This study investigates word-of-mouth network on YouTube in response to the crisis, patterns of co-commenting activities across selected YouTube videos, as well as public responses to the incident by employing social and semantic network analysis. A total of 512 YouTube videos featuring the crisis from December 8, 2014 through November 11, 2018, and 52,772 public comments to the videos were collected. The central videos in the network successfully attracted the public's attention and engagements. The results suggest that the video network was decentralized, with multiple videos acting as hubs in the network. The public commented on various videos instead of focusing on a few. The contents of influential videos uploaded by popular news organizations revealed not only Cho's behaviors related to the nut rage crisis but also unrelated illegal behaviors and the moral violations committed by the family members of Korean Air. The public attached derogatory remarks to Cho and her family, and the comments also addressed ethical concerns, management issues of the company, and boycott intentions. The results imply that adverse public reaction was related to the long-standing problem caused by family ownership and governance in large Korean corporations. This Korean Air scandal illustrates backlash toward a leadership breakdown by the family business conglomerate prevalent in the Korean society. This study provides insights for effective handling of similar crises.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.856-874
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• 2019

The performance of recommender systems (RS) has been measured mainly in terms of accuracy. However, there are other aspects of performance that are difficult to understand in terms of accuracy, such as coverage, serendipity, and satisfaction with recommended results. Moreover, particularly with RSs that suggest multiple items at a time, such as YouTube, user satisfaction with recommended results may vary not only depending on their accuracy, but also on their configuration, content, and design displayed to the user. This is true when classifying an RS as a single RS with one recommended result and as a multiple RS with diverse results. No empirical analysis has been conducted on the influence of the content and distribution of recommendation items on user satisfaction. In this study, we propose a research model representing the content and distribution of recommended items and how they affect user satisfaction with the RS. We focus on RSs that recommend multiple items. We performed an empirical analysis involving 149 YouTube users. The results suggest that user satisfaction with recommended results is significantly affected according to the HHI (Herfindahl-Hirschman Index). In addition, satisfaction significantly increased when the recommended item on the top of the list was the same category in terms of content that users were currently watching. Particularly when the purpose of using RS is hedonic, not utilitarian, the results showed greater satisfaction when the number of views of the recommended items was evenly distributed. However, other characteristics of selected content, such as view count and playback time, had relatively less impact on satisfaction with recommended items. To the best of our knowledge, this study is the first to show that the category concentration of items impacts user satisfaction on websites recommending diverse items in different categories using a content-based filtering system, such as YouTube. In addition, our use of the HHI index, which has been extensively used in economics research, to show the distributional characteristics of recommended items, is also unique. The HHI for categories of recommended items was useful in explaining user satisfaction.