• 대한의용생체공학회:의공학회지
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• 제35권6호
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• pp.219-226
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• 2014

This study is to develop a basic life support (BLS) app using the android based smartphone and to evaluate the function of the app. Suggested app contains chest compression feedback function, the map of automated external defibrillator (AED), direct emergency call and the basic knowledge of BLS. Using the accelerometer of the smartphone, we implemented a real-time algorithm that estimates the chest compression depth and rate for high quality cardiopulmonary resuscitation (CPR). The accuracy of algorithm was evaluated by manikin experiment. We made contents which were easy to learn the BLS for the layperson and implemented a function that provides the AED location information based on the user's current location. From the manikin experiment, the chest compression depth and rate were no significant differences between the manikin data and the app's feedback data (p > 0.05). Developed BLS app was uploaded on Google Play Store and it was free to download. We expected that this app is useful to learn the BLS for the layperson.

• 정보과학회 컴퓨팅의 실제 논문지
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• 제22권8호
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• pp.351-356
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• 2016

최근 안드로이드 플랫폼용 스마트 폰이 증가함에 따라 관련 어플리케이션 수도 크게 증가하고 있다. 안드로이드용 어플리케이션은 화면 구성 등을 위해 자바와 XML을 동시에 사용하는데, 이 둘 사이에서 다양한 문제가 많이 발생하고 있지만, 이를 고려한 정적 분석 연구와 도구는 부족하다. 본 논문에서는 자바와 XML 사이에서 발생 할 수 있는 문제점들과 품질 지표들을 살펴보고 이를 정적 분석 기법으로 분석 할 수 있는 방안을 제안하고자 한다. 제안한 방법으로 구글 플레이 스토어의 150개 어플리케이션을 대상으로 실험한 결과 172건의 문제점들과 35건의 성능 저하 이슈들을 발견하였다. 본 연구를 통해 안드로이드용 어플리케이션에 대한 정적 분석 연구와 소프트웨어 품질 향상에 기여하고자 한다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2018년도 추계학술발표대회
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• pp.729-732
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• 2018

모바일 게임 산업의 발달로 많은 사용자들이 게임을 이용하면서, 그들의 만족감을 사용리뷰를 통해 드러낸다. 실제로 각 리뷰의 범주가 모두 다르지만 현재 구글 플레이 앱스토어(Google Play App Store)의 게임 리뷰 범주는 3가지로 매우 제한적이다. 따라서 본 연구에서는 빠르고 정확한 고객의 요구를 필요로 하는 게임 소프트웨어의 특성을 고려하여 게임 리뷰를 입력했을 때, 게임의 운영 및 시스템에 맞도록 리뷰의 카테고리를 세분화하고 만족도를 분석하는 시스템을 개발한다. 제안 시스템은 인공신경망 모델인 CNN을 평점을 기반으로 훈련시켜 리뷰에 대한 만족도를 도출한다. 또한 Word2Vec을 이용해 단어들 간의 유사도를 구하고, 이를 활용한 단어 배열을 이용하여 가장 스코어가 높은 카테고리로 배정한다. 본 논문은 제안한 리뷰 만족도 및 카테고리 분류 시스템이 실제 효과적으로 리뷰를 보다 의미 있는 정보로써 제공할 수 있음을 보인다.

• International Journal of Internet, Broadcasting and Communication
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• 제13권1호
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• pp.107-115
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• 2021

This paper presents a smartphone application for the clinical practice education conducted in hospitals, with an aim to evaluate its effectiveness. A nonequivalent control group posttest design was used, which included a total of 100 nursing of school students who conducted their clinical practice. They were divided into one control and one experimental group (50 students each). The control group was directly trained in the clinical practice orientation, and the experimental group was a group who self-learned the clinical practice orientation using a smartphone application. Research data were collected between March 5 and April 27, 2019. They were analyzed with descriptive statistics and independent t-test, using the SPSS Statistics Version 24. The smartphone application customized for the clinical practice education was implemented through the following four phases: analysis, design, development, and evaluation. The developed application was registered in Google Play (for Android apps) and Apple Store, and related information was provided, making it available for download. The study showed that the satisfaction with and self-confidence in learning differed significantly between the groups. However, technology acceptance and knowledge acquired through practice showed no statistically significant difference. The research results serve as basic data for applying smartphone applications as an educational method that can replace traditional modes of education, serving as a significant indicator of the education delivery method diversification.

• 한국의류산업학회지
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• 제25권3호
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• pp.379-385
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• 2023

Recently, with the development of IT technology, interest in mobile applications has increased, and as products and contents that go beyond existing services are released in the beauty industry, interest is steadily increasing. Accordingly, various studies have been conducted, but studies analyzing the functions of beauty applications have been insufficient. Therefore, this study aims to analyze the functions of beauty applications and help in the development and development of future beauty applications. The research method analyzed the functions of beauty applications that have been downloaded more than 100 million through the Google Play Store, and the search period was from October 11, 2020 to November 3, 2020. As a result of the study, it was found that there is a difference in the name of the function, the function being provided, and the application method of the function for each application. As a result of function analysis, a total of 36 functions were classified, and it was analyzed that 30 functions were provided in YCM, 14 functions in YCP, 21 functions in BP, and 10 functions in SS. Therefore, by analyzing the functions of beauty applications through this study, we intend to provide useful data in the future development of beauty applications and help in the development of beauty applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권9호
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• pp.2334-2347
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• 2023

Metaverse services generate text data, data of ubiquitous computing, in real-time to analyze user emotions. Analysis of user emotions is an important task in metaverse services. This study aims to classify user sentiments using deep learning and pre-trained language models based on the transformer structure. Previous studies collected data from a single platform, whereas the current study incorporated the review data as "Metaverse" keyword from the YouTube and Google Play Store platforms for general utilization. As a result, the Bidirectional Encoder Representations from Transformers (BERT) and Robustly optimized BERT approach (RoBERTa) models using the soft voting mechanism achieved a highest accuracy of 88.57%. In addition, the area under the curve (AUC) score of the ensemble model comprising RoBERTa, BERT, and A Lite BERT (ALBERT) was 0.9458. The results demonstrate that the ensemble combined with the RoBERTa model exhibits good performance. Therefore, the RoBERTa model can be applied on platforms that provide metaverse services. The findings contribute to the advancement of natural language processing techniques in metaverse services, which are increasingly important in digital platforms and virtual environments. Overall, this study provides empirical evidence that sentiment analysis using deep learning and pre-trained language models is a promising approach to improving user experiences in metaverse services.

• 스마트미디어저널
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• 제12권10호
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• pp.38-46
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• 2023

Farming activities are transforming from traditional skill-based agriculture into knowledge-based and technology-driven digital agriculture. The use of intelligent information and communication technology introduces the idea of smart farming that enables farmers to collect weather data, monitor crop growth remotely and detect crop diseases easily. The introduction of Plantix, a pest and disease management tool in the form of a mobile application has allowed farmers to identify pests and diseases of the crop using their mobile devices. Hence, this study collected the reviews of Plantix to explore the response of the users on the Google Play Store towards the application through Latent Dirichlet Allocation (LDA) topic modeling. Results indicate four latent topics in the reviews: two positive evaluations (compliments, appreciation) and two suggestions (plant options, recommendations). We found the users suggested the application to additional plant options and additional features that might help the farmers with their difficulties. In addition, the application is expected to benefit the farmer more by having an early alert of diseases to farmers and providing various substitutes and a list of components for the remedial measures.

• 한국의류산업학회지
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• 제25권6호
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• pp.739-744
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• 2023

With the popularization of 5G networks and the development of AI (artificial intelligence) technology, Metaverse, which creates production capacity by combining virtual space and reality, is attracting attention. In this study, we searched for makeup applications with more than 100 million downloads from October 11, 2020 to November 3, 2020 through the Google Play Store. As a result of the search, four applications were found: YouCam Makeup, YouCam Perfect, Beauty Plus, and Sweet Snap. Based on the functions provided by the four applications, we attempted to suggest makeup functions applicable to Zepeto's avatar. Functions for the eyes (eyeliner, eyelashes, mascara, eye shadow, eye shape, eyebrow shape, lenses, double eyelids), functions for the nose (nose shape), functions for the mouth (lipstick, lip shape, smile function) ) Functions corresponding to the facial contour (contour, skin foundation, blusher, shading, highlighter, face painting, theme makeup) and functions corresponding to the body (body adjustment) were proposed. This study is the first in the beauty field to propose a method of applying the functions of the Metaverse platform as the importance of digital platforms is highlighted, and is the first to propose a makeup function applied to the Metaverse so that it can be used as important basic data in the future.

• 한국의류산업학회지
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• 제25권6호
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• pp.725-731
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• 2023

With the development of technology, many changes have emerged in how consumers acquire information without restrictions on their location and time. As changes and interest in digital platforms increase, beauty industry applications are being developed in order to attract customers. Therefore, this study has provided the empirical data necessary for the development and advancement of beauty applications in the future by analyzing preferences for makeup applications according to age. The method of this study involved searching for makeup applications that had been downloaded more than 100 million times through the Google Play Store between October 11, 2020 to November 3, 2020. Four applications were identified: YouCma Makeup, YouCam Perfect, Beauty Plus, and Sweet Snap. The surveyed functions were tested on 100 people in their teens, 20s, 30s, and 40s, with a similar profile of 100 people in their teens, 20s, 30s, and 40s surveyed from January 3, 2022 to April 23, 2022. The functional preferences of the application were investigated, and the results were analyzed through frequency analysis. The results are as follows: the application that received the greatest preference for features by age was YCM, which was found to have subdivided functions that provide users a wider range of choices and more detailed work when compared to other applications which enable photo retouching.

• 스마트미디어저널
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• 제13권6호
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• pp.35-43
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• 2024

During the post-pandemic period, the interest in foreign language learning surged, leading to increased usage of language-learning apps. With the rising demand for these apps, analyzing app reviews becomes essential, as they provide valuable insights into user experiences and suggestions for improvement. This research focuses on extracting insights into users' opinions, sentiments, and overall satisfaction from reviews of HelloTalk, one of the most renowned language-learning apps. We employed topic modeling and emotion analysis approaches to analyze reviews collected from the Google Play Store. Several experiments were conducted to evaluate the performance of sentiment classification models with different settings. In addition, we identified dominant emotions and topics within the app reviews using feature importance analysis. The experimental results show that the Random Forest model with topics and emotions outperforms other approaches in accuracy, recall, and F1 score. The findings reveal that topics emphasizing language learning and community interactions, as well as the use of language learning tools and the learning experience, are prominent. Moreover, the emotions of 'admiration' and 'annoyance' emerge as significant factors across all models. This research highlights that incorporating emotion scores into the model and utilizing a broader range of emotion labels enhances model performance.