• Journal of Energy Engineering
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• v.22 no.3
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• pp.287-293
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• 2013

This study was carried out to diminish the formation of scale in boilers which is one of the defect elements when they are operating. The defect relating to scale can cause a fatal impact on the explosion of boilers due to the overheating of their tubes, or it can affect the flow of water inside boilers with its bad circulation and result in a disparity of water inside the equipment. Heat transfer in the scale is low comparing to the boiler material, so it can lead to energy losses and has also impact on the global warming. In 2005, the Korean government introduced a system which requires boiler users to install the equipment which can prevent or eliminate the formation of scale to improve the management of water quality in boilers. The study on the techniques for preventing or eliminating the formation of scale started in 1821 and since then subsequently there have been lots of similar studies. The first one was about the scale reduction using potato starch. Since an ultrasonic scale preventer developed by a scientist from a Russian acoustic institute was introduced in1993, a variety of equipment of this kind have been disseminated in Korea. There has been a need to demonstrate the condition for the best performances of such equipment. Boilers are mostly composed of the main body and 288 the tube with a circular curved surface. I carried out a demonstration study on a circular tube which affects the scale defect the most among the boiler components. As a result of it, I found out the fact that the ultrasonic wave needs to reach a certain level of sound pressure and frequency to affect the formation of scale.

• Fire Science and Engineering
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• v.32 no.3
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• pp.67-75
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• 2018

To reduce the number of casualties in the case of fire, an alarm sound needs to be delivered to the people who remain in the apartment unit. On the other hand, it was reported that the fire alarm sound generated in the elevator hall was not delivered sufficiently to the people staying in the apartment units. In this study, the background noise level and noise level generated in an apartment unit were measured during the day and night time. In addition, the transmission of the fire alarm sound into the each room of apartment units was simulated and compared with the background noise level. The fire alarm sound generated in the elevator halls was reduced by the fire door and doors, and was not transmitted sufficiently into the internal spaces of the apartment units. Starting evacuation action was difficult after hearing the fire alarm sound generated outside the apartment units. To improve the transmission of an alarm sound to the inner spaces of apartment units, an acoustic simulation was carried out for cases where the alarm sound generator was installed on a wall-pad in the living room and the alarm sound generator was installed on the ceiling of each rooms in apartment units. Background noise of + 15 dB and 75 dB (A) were satisfied when alarm sound generator was installed on the ceiling of each room.

• Science of Emotion and Sensibility
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• v.24 no.1
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• pp.91-104
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• 2021

This study explored users' emotional states identified from the wake-up words -"Hi, KIA!"- using a machine learning algorithm considering the user interface of passenger cars' voice. We targeted four emotional states, namely, excited, angry, desperate, and neutral, and created a total of 12 emotional scenarios in the context of car driving. Nine college students participated and recorded sentences as guided in the visualized scenario. The wake-up words were extracted from whole sentences, resulting in two data sets. We used the soundgen package and svmRadial method of caret package in open source-based R code to collect acoustic features of the recorded voices and performed machine learning-based analysis to determine the predictability of the modeled algorithm. We compared the accuracy of wake-up words (60.19%: 22%~81%) with that of whole sentences (41.51%) for all nine participants in relation to the four emotional categories. Accuracy and sensitivity performance of individual differences were noticeable, while the selected features were relatively constant. This study provides empirical evidence regarding the potential application of the wake-up words in the practice of emotion-driven user experience in communication between users and the artificial intelligence system.

• Journal of the Korea Society for Simulation
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• v.31 no.3
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• pp.45-54
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• 2022

This paper is about designing and implementing the simulation training equipment (simulator) for the CBRN Reconnaissance Vehicle-II (armor type). The simulation training equipment (simulator) is a military training equipment in a virtual environment that analyzes the training using various CBRN equipment according to the CBRN situation and make a professional report. The controller or training instructor can construct a scenario using the instructor control system for a possible CBRN situation, spread the situation, and observe the process of the trainee performing the propagated situation appropriately. All process can be monitored and analyzed by the system, and it can be recorded, so it is also used for AAR (After Action Review). To implement CBRN situation training in a virtual environment, instructor control (IOS), host (HOS), video (IGS), input/output device (IOC), and sound (ACS) were implemented, a long-range chemical automatic detector (LCA), a combined chemical detector (CAD), a control (MCC) and an operation (OCC) computer were developed as simulators. In this paper, the design and development of simulation training equipment for CBRN Reconnaissance Vehicle-II (armor type) was conducted, and the performance was verified through integrated tests and acceptance tests.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.152-163
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• 2022

In this paper, we present a method to enable an unmanned aerial vehicle to drop the sonobuoy, an essential element of anti-submarine warfare, in an optimal deployment. To this end, an environment simulating the distribution of sound detection performance was configured through the Unity game engine, and the environment directly configured using Unity ML-Agents and the reinforcement learning algorithm written in Python from the outside communicated with each other and learned. In particular, reinforcement learning is introduced to prevent the accumulation of wrong actions and affect learning, and to secure the maximum detection area for the sonobuoy while the vehicle flies to the target point in the shortest time. The optimal placement of the sonobuoy was achieved by applying the Deep Deterministic Policy Gradient (DDPG) algorithm. As a result of the learning, the agent flew through the sea area and passed only the points to achieve the optimal placement among the 70 target candidates. This means that an autonomous aerial vehicle that deploys a sonobuoy in the shortest time and maximum detection area, which is the requirement for optimal placement, has been implemented.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.539-549
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• 2024

This study employed text mining techniques like frequency analysis, word clouds, and LDA topic modeling to assess consumer satisfaction and dissatisfaction with Hyundai Motor Company in the Chinese market, compared to brands such as Toyota, Volkswagen, Buick, and Geely. Focusing on compact vehicles from these brands between 2021 and 2023, this study analyzed customer reviews. The results indicated Hyundai Avante's positive factors, including a long wheelbase. However, it also highlighted dissatisfaction aspects like Manipulate, engine performance, trunk space, chassis and suspension, safety features, quantity and brand of audio speakers, music membership service, separation band, screen reflection, CarLife, and map services. Addressing these issues could significantly enhance Hyundai's competitiveness in the Chinese market. Previous studies mainly focused on literature research and surveys, which only revealed consumer perceptions limited to the variables set by the researchers. This study, through text mining and comparing various car brands, aims to gain a deeper understanding of market trends and consumer preferences, providing useful information for marketing strategies of Hyundai and other brands in the Chinese market.