• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.281-283
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• 2021

The representative companies mentioned in the recommendation service in the domestic OTT(Over-the-top media service) market are YouTube and Netflix. YouTube, through various methods, started personalized recommendations in earnest by introducing an algorithm to machine learning that records and uses users' viewing time from 2016. Netflix categorizes users by collecting information such as the user's selected video, viewing time zone, and video viewing device, and groups people with similar viewing patterns into the same group. It records and uses the information collected from the user and the tag information attached to the video. In this paper, we propose a method to improve video media recommendation by automatically generating metadata of video media that was written by hand.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.284-286
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• 2021

With the continuous development of the Internet and digital, platforms are emerging to store large amounts of media data and provide customized services to individuals through online. Companies that provide these services recommend movies that suit their personal tastes to promote media consumption. Each company is doing a lot of research on various algorithms to recommend media that users prefer. Movies are divided into genres such as action, melodrama, horror, and drama, and the film's audio (music, sound effect, voice) is an important production element that makes up the film. In this research, based on movie trailers, we extract audio for each genre, check the commonalities of audio for each genre, distinguish movie genres through supervised learning of artificial intelligence, and propose a utilization method for generating metadata in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.277-280
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• 2021

Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.509-517
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• 2023

The reactive web service provides a related word recommendation system using the TextRank algorithm and a word-based idea generation service selected by the user. In the related word recommendation system, the method of weighting each word using the TextRank algorithm and the probability output method using SoftMax are discussed. The idea generation service discusses the idea generation method and the artificial intelligence reinforce-learning method using mini-GPT. The reactive web discusses the linkage process between React, Spring Boot, and Flask, and describes the overall operation method. When the user enters the desired topic, it provides the associated word. The user constructs a mind map by selecting a related word or adding a desired word. When a user selects a word to combine from a constructed mind-map, it provides newly generated ideas and related patents. This web service can share generated ideas with other users, and improves artificial intelligence by receiving user feedback as a horoscope.

• Journal of Venture Innovation
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• v.5 no.4
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• pp.41-56
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• 2022

This study was conducted to empirically analyze the effect of various job characteristics on job satisfaction under the smart work environment, which has become a hot topic recently. To this end, job characteristics under the smart work environment were subdivided into job autonomy, job flexibility, and job efficiency. In addition, although these job characteristics had a direct effect on job satisfaction, the learning agility of employees was also considered to be important factors. Job autonomy, job flexibility, and job efficiency all had a significant positive (+) effect on job satisfaction. In the case of learning agility, it was found that there was a mediating effect in all paths. The results of this study had academic significance in that they empirically tested the relationship between job characteristics of smart work and job satisfaction according to the progress to contact free society..

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.557-561
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• 2021

A meatadata has become an essential element in order to recommend video content to users. However, it is passively generated by video content providers. In the paper, a method for automatically generating metadata was studied in the existing manual metadata input method. In addition to the method of extracting emotion tags in the previous study, a study was conducted on a method for automatically generating metadata for genre and country of production through movie audio. The genre was extracted from the audio spectrogram using the ResNet34 artificial neural network model, a transfer learning model, and the language of the speaker in the movie was detected through speech recognition. Through this, it was possible to confirm the possibility of automatically generating metadata through artificial intelligence.

• Journal of Practical Engineering Education
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• v.16 no.2
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• pp.185-193
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• 2024

With the advent of smartphones, people can access various information through the internet anytime and anywhere. Even in the vehicle environment, users can use the internet. Users interact with web and applications every day and get information. However, as the amount of data to be processed by the program increases, users inevitably receive a message to wait. User waiting is an inconvenient experience, but minimizing user waiting is the best way because there is time required for data processing. However, if the service processing time exceeds the expected time, users experience more severe boredom and pain. Therefore, various methods and researches are being conducted to alleviate the boredom of user waiting. The most commonly used method to alleviate user waiting boredom is loading. In this study, we investigated the effect of skeleton loading, the latest loading technique, on user waiting experience, and how attractive it is as a design technique in terms of UI compared to other loading techniques.

• Journal of the Korean Applied Science and Technology
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• v.41 no.1
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• pp.149-157
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• 2024

Bupleurum falcatum L. is one of the medicinal crops and has excellent pharmacological activities such as reducing fever, sedation, inhibition of hepatopathy, anti-inflammatory, and anticancer. Currently, it is used for food or medicine, but the use as a cosmetic is insufficient, so the suitability and use value as a cosmetic material were reviewed. Using the Bupleurum falcatum L. extract, polyphenol, flavonoid, antioxidant, and anti-inflammatory tests were conducted. The total polyphenol content was 14.71±0.16 mg·TAE/g, and the total flavonoid content was 1.42±0.05 mg·QE/g. The antioxidant activity showed excellent activity in a concentration-dependent activative, and the NO expression inhibition ability was 61.21% at 1,000 ㎍/mL, confirming that the anti-inflammatory activity was excellent. Through this study, the antioxidant and anti-inflammatory effects of Bupleurum falcatum L. extract are excellent, so it is considered to be of sufficient value as a natural material for cosmetics.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.291-296
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• 2024

This study analyzed various machine learning models that predict employment outcomes after vocational training using pre-assessment data of disabled vocational trainees. The study selected and utilized the most appropriate machine learning models based on a data set containing various personal characteristics, including trainees' gender, age, and type of disability. Through this analysis, the goal is to improve the employment rate and job satisfaction of disabled trainees using only pre-assessment data. As a result, it presents a universal approach that can be applied not only to people with disabilities, but also to vocational trainees from a variety of backgrounds. This is expected to make an important contribution to the development and implementation of tailored vocational training programs, ultimately helping to achieve better employment outcomes and job satisfaction.

• Journal of Digital Policy
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• v.3 no.1
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• pp.21-25
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• 2024

This is a case study that sought to consider whether taping, which focuses on instability of the sacroiliac joint, is a potential intervention method that may be helpful for low back pain. In the case of a 58-year-old participant, we summarized the notable results from a taping training session that a man with a history of back surgery due to disc herniation and stenosis participated in to reduce ongoing pain. As an intervention method, tape was applied between the 2nd and 4th sacrum on both sides from the spinous tuberosity. It was stretched to a tension of 80% and attached past the sacroiliac joint, and then the ends were raised at about 45° on both sides and attached toward the gluteus medius muscle. Then, along the erector spinae muscle from the iliac crest. Bilateral taping up to the level of the 10th rib was applied. Through this intervention, positive case results were observed from both VAS and ODI test tools, with VAS recorded as 5 to 0 and disability index recorded as 13 to 0, respectively.