• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.241-251
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• 2022

Diagnosis and management of customer's skin condition is an important essential function in the cosmetics and beauty industry. As the social media environment spreads and generalizes to all fields of society, the interaction of questions and answers to various and delicate concerns and requirements regarding the diagnosis and management of skin conditions is being actively dealt with in the social media community. However, since social media information is very diverse and atypical big data, an intelligent skin condition diagnosis system that combines appropriate skin condition information analysis and artificial intelligence technology is necessary. In this paper, we developed the skin condition diagnosis system SCDIS to intelligently diagnose and manage the skin condition of customers by processing the text analysis information of social media into learning data. In SCDIS, an artificial neural network model, AnnTFIDF, that automatically diagnoses skin condition types using artificial neural network technology, a deep learning machine learning method, was built up and used. The performance of the artificial neural network model AnnTFIDF was analyzed using test sample data, and the accuracy of the skin condition type diagnosis prediction value showed a high performance of about 95%. Through the experimental and performance analysis results of this paper, SCDIS can be evaluated as an intelligent tool that can be used efficiently in the skin condition analysis and diagnosis management process in the cosmetic and beauty industry. And this study can be used as a basic research to solve the new technology trend, customized cosmetics manufacturing and consumer-oriented beauty industry technology demand.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.133-154
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• 2021

Today smart phone is the most common media with a vehicle called 'application'. In order to understand how media users select applications and build their repertoire, this study conducted two-step approach using big data from smart phone log for 4 weeks in November 2019, and finally classified 8 media repertoire groups. Each of the eight media repertoire groups showed differences in time spent of mobile application category compared to other groups, and also showed differences between groups in demographic distribution. In addition to the academic contribution of identifying the mobile application repertoire with large scale behavioral data, this study also has significance in proposing a two-step approach that overcomes 'outlier issue' in behavioral data by extracting prototype vectors using SOM (Sefl-Organized Map) and applying it to k-means clustering for optimization of the classification. The study is also meaningful in that it categorizes customers using e-commerce services, identifies customer structure based on behavioral data, and provides practical guides to e-commerce communities that execute appropriate services or marketing decisions for each customer group.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.675-681
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• 2021

With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

• Journal of the Korea Institute of Building Construction
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• v.22 no.4
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• pp.403-414
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• 2022

Many studies have been conducted on asset management of public facilities, as the importance of such management has been increasing. This basic study aims to present strategies for the practical use of public asset management, and seeks to propose efficient management and utilization measures from a cost perspective by comparing and analyzing the importance and impact relationship between cost items for public asset management. In this study, 19 sub-items and the top 4 items were chosen by deriving cost factors based on the previous literature. A survey was conducted, and the results of the survey were analyzed by using the Analytic Hierarchy Process(AHP) and Interpretive Structural Modeling (ISM) methods. The AHP was used to derive the priority between items, and ISM was used to identify major groups and mutual influences. As a result, those items showing both high priority and high importance, such as user cost, dismantling/disposal cost, replacement cost, maintenance/repair cost, etc. are determined as priority items to be considered for public asset management of public facilities. Also, it is necessary to minimize the impact on other items in public asset management by those items which are impacted less by other items but have significant impact on the items such as initial construction costs, conceptual design costs, construction costs, and supervision costs. It is expected that the results and analysis methods presented in this study can be used to provide strategies for asset management of public facilities.

• Smart Media Journal
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• v.11 no.6
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• pp.37-50
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• 2022

This proposes a direction to build and provide an exhibition space based on the metaverse platform so that artists can independently open their own exhibitions in an online environment. Although many artists are produced every year, offline exhibitions are becoming difficult due to not many art galleries, and offline exhibitions are becoming impossible due to Corona, which began at the end of 2019, and online exhibitions are emerging as an alternative. We analyze cases of existing online exhibition methods and visit online exhibition methods such as web, video, and virtual reality and metaverse environment then present a plan for individual exhibitions in consideration of the recent metaverse environment. The proposed metaverse-based personal exhibition method is structured so that artists can construct a space on the metaverse and place their works, and then viewers can freely take a look on it from a remote location. Based on the proposed exhibition direction, the representative metaverse platform was applied to confirm the characteristics and possibilities of exhibition space and composition of works and users' exhibition experience. In the face of the rise of online exhibitions, space can be constructed in the direction the artist pursues in online exhibitions as well as offline exhibitions, but also online exhibitions, and hopes that online exhibitions will become another genre of exhibitions rather than incidental after the end of Covid-19.

• Journal of Industrial Convergence
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• v.21 no.1
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• pp.67-76
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• 2023

COVID-19, which occurred in 2019, has a strong contagious power, has serious symptoms of infection and after-effects, and death in severe cases depending on the underlying disease and symptoms. As COVID-19 is highly contagious, in Korea, screening clinics have been set up across the country to determine whether or not to be positive for COVID-19 and isolate the infected to prevent the spread of COVID-19. However, there are cases where COVID-19 test applicants flock to screening clinics and cannot receive tests due to longer waiting times, and there is a risk that secondary infections may occur in the atmosphere. In this study, the reservation and notification system can be applied from the existing screening care system to solve spatial constraints, reducing waiting time with screening appointments, and solving population bottlenecks to screening clinics. Taking the COVID-19 pandemic as an experience, we propose a system that can present directions in future pandemic situations. To process real-time data, we use Google's Firebase to use Realtime Database in the cloud environment. Because a real-time database is used, users can check the status of screening clinics in real time through the app, make reservations, and receive notifications about test reservations.

• Korean Journal of Ecology and Environment
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• v.55 no.4
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• pp.330-340
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• 2022

We deduced the proper estimation methodology for the amount of carbon sequestration by damaged trees for Environmental Impact Assessment (EIA). The nine development projects related to renewable energy, damaged trees occur, assessment status and used method of evaluating the carbon storage of damaged trees were summarized. And after re-calculating the carbon storage of damaged trees through allometric equations, the difference between the two groups, re-calculated the damaged trees carbon storage and the damaged trees carbon storage in the report, was validated. As a result, damaged trees carbon storage in words was more than the re-calculated damaged trees carbon storage, and it was statistically significant (p<0.005). This result means that the existing method for calculating damaged tree carbon storage is overcalculated. It was judged that it was necessary to improve the calculation method. Therefore, allometric equations suitable for each dominated-tree species should be used when calculating the damaged tree carbon storage. Furthermore, we propose to establish a carbon storage calculation system based on actual data from the ecosystem so that researchers can efficiently and accurately the damaged trees carbon storage.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.275-284
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• 2023

Virtual reality simulations are used for education and training in various fields, and are especially widely used in the medical field recently. The education/training simulator consists of tactile/force feedback generation and image/sound output hardware that provides a sense similar to a doctor's treatment of a real patient using real surgical tools, and software that produces realistic images and tactile feedback. Existing simulators are complicated and expensive because they have to use various types of hardware to simulate various surgical instruments used during surgery. In this paper, we propose a dental surgical simulation system using a force feedback device and a morphable haptic controller. Haptic hardware determines whether the surgical tool collides with the surgical site and provides a sense of resistance and vibration. In particular, haptic controllers that can be deformed, such as length changes and bending, can express various senses felt depending on the shape of various surgical tools. When the user manipulates the haptic feedback device, events such as movement of the haptic feedback device or button clicks are delivered to the simulation system, resulting in interaction between dental surgical tools and oral internal models, and thus haptic feedback is delivered to the haptic feedback device. Using these basic techniques, we provide a realistic training experience of impacted wisdom tooth extraction surgery, a representative dental surgery technique, in a virtual environment represented by sophisticated three-dimensional models.