• 한국연소학회:학술대회논문집
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• 2002.11a
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• pp.157-163
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• 2002

Using the CFD method, we investigated the combustion characteristics of grate-rotary kiln incinerator through the residence time, path line of flow and distributions of temperature and CO mass fraction according to the shape of mixing chamber and the existence and nonexistence of baffle at the exit of bypass duct. The results show that the now mixing and residence time could be variable according to the shape of mixing chamber and baffle, and we could know the temperature in the mixing chamber could increase too high if the combustion process on the grate retarded.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.15-24
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• 2000

Stand-alone global position system receiver based on C/A code tracking generates position error of 100m mainly due to the selective availability and ionospheric and tropospheric delay errors. The differential GPS is the most commonly used method for removing those bias range error components. The relative GPS, although somewhat restrictive in its use, is ideally suited to the car monitoring system for improved Automatic Vehicle location, especially where the DGPS infrastructure is not available. The RGPS does not require any additional hardware, facility or external infrastructure and can be operated within the system with existing host computer and communication link. This paper presents detailed description of the RGPS concept and its implementation for real-time data processing. Performance of RGPS is evaluated with real data and is compared with DGPS.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.220-225
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• 2003

In this paper, various types of racing line are analyzed for the best time to go through a 90 degree comer. 'Best' means the least time, at the greatest average speed. The comer concerned here has the long straights before and after the corner so that the vehicle is able to n with its maximum speed along the straights. It is shown that both inside and outside driving lines including the modified outside driving lines never beat classical racing line. It is also found that outside driving line is better than inside driving inside driving line as long as there are straight lines before and after the comer.

• Journal of IKEEE
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• v.22 no.4
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• pp.992-998
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• 2018

Presentation is a technique that is logically and confidently conveying your thoughts and opinions in front of others. It is essential when you go to school or work. However, it takes a lot of time, money, and effort to improve your presentation skills. In this paper, we describe the development of a presentation coaching application that analyzes the presentation practice video. The application program can analyze the presentation time, the speaker's expression, the use of duplicate words, etc.

• Journal of the Korean Society of Costume
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• v.56 no.3 s.102
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• pp.81-90
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• 2006

The objective of the study is to review trends of clothing export in important countries of the world and thus to know the present stage of clothing export in Korea. For the purpose, changes of export amount, competitiveness and product life cycle were analysed in the countries from the 1960's to the 1990's. The results are as following: First, on the aspect of export amount, industrialized countries lost the lead to newly industrializing countries from the 1960's. Developing countries, as China, win the lead. Second, on the competitiveness aspect, industrialized countries lost competitiveness to newly industrializing countries before the 1960's. And newly industrializing countries were outpaced by China in the export competitiveness from the early 1990's. Third, on the aspect of product life cycle, industrialized countries go first through each period of product life cycle, introduction, growth, maturity and decline, and they all, excluding Japan, sustained period of Maturity for a long time. newly industrializing countries and developing countries go orderly through each period of product life cycle after industrialized countries. As to Korea, duration of each period was short. Specially characteristics of decline period appeared partly in the early 1990's. From the results, the theory of product life cycle, helping to explain changes in production and trade in new product lines, estimated to applicable to clothing export. The phenomena, Italy, Hong Kong and America sustain high competitiveness in the world clothing market for a long time, is needed to be studied carefully. The study about strong points in their clothing industries and competitiveness drive program be to influence Korean export policy in the future.

• Clean Technology
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• v.23 no.3
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• pp.248-255
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• 2017

In dismantling factories for recycling, it is important to input actual working data to a personal computer (PC) in order to monitor the work results and related recycling rate of the inputs. This should be performed with a keyboard, a mouse, or other devices. But when a worker is working in the factory, it could be bothersome or time consuming to go to the PC. Especially, workers who works at dismantling factories have a generally low education level are scared to use a PC, which could be used as a pretext for not using the PC. In some cases, data input is performed by a worker after the day's job. In this case, it could take additional time, the worker can make more mistakes, and the data could be unreliable. In this study, we developed a man-machine interface (MMI) device using a safety helmet. A joystick-like device, pushbuttons, and a radio frequency (RF) device for wireless communication is equipped in a safety helmet. This MMI device has functions similar to a PC mouse, and it has a long communication distance. RF is used because it consumes less battery power than Bluetooth. With this MMI device, workers need not go to a PC to input data or to control the PC, and they can control the PC from a long distance. The efficiency of PCs in a factory could be increased by using the developed MMI system, and workers at the dismantling factories could have less reluctance in using the PC.

• Journal of Wellbeing Management and Applied Psychology
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• v.2 no.1
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• pp.1-8
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• 2019

"In the future, 80% of doctors will be replaced by advanced technology." It has been talked about for a long time. When I first heard this story, people said it was ridiculous. But now that AlphaGo has won the Go match against Lee Se-dol, and many global companies have come up with a variety of services and products based on artificial intelligence, the story has become no more than ridiculous. In other words, it is beginning to come true. Artificial intelligence technology is already widely used in manufacturing and service industries. This spread of artificial intelligence is sure to usher in an era of great change in our future. And it is safe to say that it is the "medical world" where the biggest changes will be made. So how on earth does artificial intelligence replace medical personnel? If replaced, where would you stand out? In order to understand this, we must first be familiar with deep learning, which is the basis of medical artificial intelligence. And as the fourth industrial revolution gradually approaches reality, various occupational groups are becoming meaningless, as in the preceding industrial revolution, and in this paper we will learn about the impact of this situation on the medical community.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.287-295
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• 2017

Since Google's AlphaGo defeated a world champion of Go players in 2016, there have been many interests in the deep learning. In the financial sector, a Robo-Advisor using deep learning gains a significant attention, which builds and manages portfolios of financial instruments for investors.In this paper, we have proposed the a deep learning algorithm geared toward identification and forecast of the KOSPI index direction,and we also have compared the accuracy of the prediction.In an application of forecasting the financial market index direction, we have shown that the Robo-Advisor using deep learning has a significant effect on finance industry. The Robo-Advisor collects a massive data such as earnings statements, news reports and regulatory filings, analyzes those and recommends investors how to view market trends and identify the best time to purchase financial assets. On the other hand, the Robo-Advisor allows businesses to learn more about their customers, develop better marketing strategies, increase sales and decrease costs.

• Sleep Medicine and Psychophysiology
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• v.19 no.1
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• pp.11-17
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• 2012

Objective: Among various methods developed to quantitatively explore electroencephalograms (EEG), we focused on a wavelet method that was known to yield robust results under nonstationary conditions. The aim of this study was thus to introduce the wavelet method and demonstrate its potential use in clinical sleep studies. Method: This study involved artificial EEG specifically designed to validate the wavelet method. The method was performed to obtain time-dependent spectral power and phase angles of the signal. Synchrony of multichannel EEG was analyzed by an order parameter of the instantaneous phase. The standard methods, such as Fourier transformation and coherence, were also performed and compared with the wavelet method. The method was further validated with clinical EEG and ERP samples available as pilot studies at academic sleep centers. Result: The time-frequency plot and phase synchrony level obtained by the wavelet method clearly showed dynamic changes in the EEG waveforms artificially fabricated. When applied to clinical samples, the method successfully detected changes in spectral power across the sleep onset period and identified differences between the target and background ERP. Conclusion: Our results suggest that the wavelet method could be an alternative and/or complementary tool to the conventional Fourier method in quantifying and identifying EEG and ERP biomarkers robustly, especially when the signals were nonstationary in a short time scale (1-100 seconds).

• Imaging Science in Dentistry
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• v.54 no.3
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• pp.240-250
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• 2024

Purpose: This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. Materials and Methods: A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which were determined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. Results: In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The time required to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually, compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Conclusion: Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculate these measurements, the efficiency of diagnosis and treatment may be improved.