• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.203-208
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• 2006

The main research conducted previously on GPS ionosphere in China is first introduced. Besides, the current investigations include as follows: (1) GPS-based spatial environmental, especially the ionosphere, monitoring, modeling and analysis, including ground/space-based GPS ionosphere electron density (IED) through occultation/tomography technologies with GPS data from global/regional network, development of a GNSS-based platform for imaging ionosphere and atmosphere (GPFIIA), and preliminary test results through performing the first 3D imaging for the IED over China, (2) The atmospheric and ionospheric modeling for GPS-based surveying, navigation and orbit determination, involving high precisely ionospheric TEC modeling for phase-based long/median range network RTK system for achieving CM-level real time positioning, next generation GNSS broadcast ionospheric time-delay algorithm required for higher correction accuracy, and orbit determination for Low-Earth-orbiter satellites using single frequency GPS receivers, and (3) Research products in applications for national significant projects: GPS-based ionospheric effects modeling for precise positioning and orbit determination applied to China's manned space-engineering, including spatial robot navigation and control and international space station intersection and docking required for related national significant projects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.10
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• pp.1277-1286
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• 2018

In this paper, we provide flexible scalability of computing resources in cloud environment and Apache Hadoop based cloud environment for analysis of public medical information big data. In fact, it includes the ability to quickly and flexibly extend storage, memory, and other resources in a situation where log data accumulates or grows over time. In addition, when real-time analysis of accumulated unstructured log data is required, the system adopts Hadoop-based analysis module to overcome the processing limit of existing analysis tools. Therefore, it provides a function to perform parallel distributed processing of a large amount of log data quickly and reliably. Perform frequency analysis and chi-square test for big data analysis. In addition, multivariate logistic regression analysis of significance level 0.05 and multivariate logistic regression analysis of meaningful variables (p<0.05) were performed. Multivariate logistic regression analysis was performed for each model 3.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.289-297
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• 2010

In this paper, A method to prevent the external acoustic noise from being misrecognized as the speech recognition object is presented in the speech activity detection process for the speech recognition. Also this paper confirmed besides the acoustic energy to the lip movement image signals. First of all, the successive images are obtained through the image camera for personal computer and the lip movement whether or not is discriminated. The next, the lip movement image signal data is stored in the shared memory and shares with the speech recognition process. In the mean time, the acoustic energy whether or not by the utterance of a speaker is verified by confirming data stored in the shared memory in the speech activity detection process which is the preprocess phase of the speech recognition. Finally, as a experimental result of linking the speech recognition processor and the image processor, it is confirmed to be normal progression to the output of the speech recognition result if face to the image camera and speak. On the other hand, it is confirmed not to the output the result of the speech recognition if does not face to the image camera and speak. Also, the initial feature values under off-line are replaced by them. Similarly, the initial template image captured while off-line is replaced with a template image captured under on-line, so the discrimination of the lip movement image tracking is raised. An image processing test bed was implemented to confirm the lip movement image tracking process visually and to analyze the related parameters on a real-time basis. As a result of linking the speech and image processing system, the interworking rate shows 99.3% in the various illumination environments.

• Journal of Korean Neurosurgical Society
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• v.64 no.6
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• pp.933-943
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• 2021

Objective : Percutaneous pedicle screw (PPS) fixation is a needle based procedure that requires fluoroscopic image guidance. Consequently, radiation exposure is inevitable for patients, surgeons, and operation room staff. We hypothesize that reducing the production of radiation emission will result in reduced radiation exposure for everyone in the operation room. Research was performed to evaluate reduction of radiation exposure by modifying imaging manner and mode of radiation source. Methods : A total of 170 patients (680 screws) who underwent fusion surgery with PPS fixation from September 2019 to March 2020 were analyzed in this study. Personal dosimeters (Polimaster Ltd.) were worn at the collar outside a lead apron to measure radiation exposure. Patients were assigned to four groups based on imaging manner of fluoroscopy and radiation modification (pulse mode with reduced dose) : continuous use without radiation modification (group 1, n=34), intermittent use without radiation modification (group 2, n=54), continuous use with radiation modification (group 3, n=26), and intermittent use with radiation modification (group 4, n=56). Post hoc Tukey Honest significant difference test was used for individual comparisons of radiation exposure/screw and fluoroscopic time/screw. Results : The average radiation exposure/screw was 71.45±45.75 µSv/screw for group 1, 18.77±11.51 µSv/screw for group 2, 19.58±7.00 µSv/screw for group 3, and 4.26±2.89 µSv/screw for group 4. By changing imaging manner from continuous multiple shot to intermittent single shot, 73.7% radiation reduction was achieved in the no radiation modification groups (groups 1, 2), and 78.2% radiation reduction was achieved in the radiation modification groups (groups 3, 4). Radiation source modification from continuous mode with standard dose to pulse mode with reduced dose resulted in 72.6% radiation reduction in continuous imaging groups (groups 1, 3) and 77.3% radiation reduction in intermittent imaging groups (groups 2, 4). The average radiation exposure/screw was reduced 94.1% by changing imaging manner and modifying radiation source from continuous imaging with standard fluoroscopy setting (group 1) to intermittent imaging with modified fluoroscopy setting (group 4). A total of 680 screws were reviewed postoperatively, and 99.3% (675) were evaluated as pedicle breach grade 0 (<2 mm). Conclusion : The average radiation exposure/screw for a spinal surgeon can be reduced 94.1% by changing imaging manner and modifying radiation source from real-time imaging with standard dose to intermittent imaging with modified dose. These modifications can be instantly applied to any procedure using fluoroscopic guidance and may reduce the overall radiation exposure of spine surgeons.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.6
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• pp.523-529
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• 2020

Power distribution management system is essential for the efficient management and operation of power distribution networks. The power distribution system is a system that manages the distribution network based on IT, and has been evolving along with the development of the power industry. The current power distribution system is designed to operate at a relatively low network transmission speed based on the independent operation of the main equipment. However, due to distributed resources such as photovoltaic or energy storage devices, which are rapidly increasing in popularity in recent years, the operation of future distribution environments is becoming more complex, and various information needs to be collected in real time. In this study, the requirements of the next-generation power distribution system were derived to overcome the limitations of the existing power distribution system, and based on this, the communication network system and performance requirements for the distribution system were defined. In order to verify the performance of the designed system, a software-based terminal device simulator was developed because it takes excessive time and cost to introduce a large-scale system such as a power distribution system. Using the simulator, a test environment similar to the actual operation was established, and the number of terminal devices was increased up to 1,000. The proposed system was shown to satisfy the requirements to support the functions of the next-generation power distribution system, recording less than 10 % of the communication network bandwidth.

• Journal of Environmental Health Sciences
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• v.49 no.4
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• pp.183-189
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• 2023

Background: The indoor air quality of classrooms, in which the capacity per unit area is high and students spend time together, must be managed for safety and comfort. It is necessary to develop an eco-friendly indoor air quality reduction method rather than biased management that relies solely on air purifiers. Objectives: In this study, plants and air purifiers were installed in middle school classrooms to evaluate the indoor PM_2.5 reduction. Methods: Four middle school classrooms were selected as test beds. Air quality was monitored in real-time every one minute using IoT equipment installed in the classrooms, corridors, and rooftops. After measuring the background concentration, plants and air purifiers were installed in the classroom and the PM_2.5 reduction effect was analyzed through continuous monitoring. Results: After installing the plants and air purifiers, the average PM_2.5 concentration was 33.7 ㎍/m³ in the classrooms without plants and air purifiers, 25.6 ㎍/m³ in classrooms with plants only, and 21.7 ㎍/m³ in classrooms with air purifiers only. In the classroom where plants and air purifiers were installed together, it was 20.0 ㎍/m³. The reduction rates before and after installation were 4.5% for classrooms with plants only, 16.5% for classrooms with air purifiers only, and 27.6% for classrooms with both plants and air purifiers. The I/O ratio, which compares the concentration of PM_2.5 in classrooms with corridors and outside air, also showed the lowest in the order of plants and air purifiers, air purifiers, and plant-only classrooms. Conclusions: The PM_2.5 reduction effect of using plants was confirmed, and it is expected to be used as basic data for the development of environmentally-friendly indoor air quality improvement methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.185-190
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• 2023

Recently, tracking radar requires the development of millimeter wave tracking radar to acquire target information with high resolution in various environments. The development of millimeter wave tracking radar requires the development of transmission and receiving components that can be applied to the millimeter wave tracking radar, as well as verification of the applicability of the tracking radar. In order to verify the applicability of the developed transmitting and receiving components, it is necessary to develop a signal acquisition device that can control the transmitting and receiving components using the operating concept of a tracking radar and check the status of the received signal. In this paper, we implemented a signal acquisition device that can confirm the applicability of components developed for millimeter wave tracking radar. The signal acquisition device was designed to process in real time the OOOMHz center frequency and OOMHz bandwidth signals input from 4 channels to verify the received signal. In addition, component control applying the tracking radar operation concept was designed to be controlled by communication such as RS422, RS232, and SPI and generation of control signals for the transmission and receiving time. Lastly, the implemented signal acquisition device was verified through a signal acquisition device performance test.

• Journal of Music and Human Behavior
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• v.3 no.1
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• pp.13-28
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• 2006

Autistic children have difficulties in communication. They tend to have more difficulties in general expression than in understanding sentences. This thesis tested the effect of music activities on children who have difficulties in language expression. As a research method, a group of autistic middle school students was selected who were attending normal schools. Three male students were selected for the test of K-ABC and CARS. Music treatments on the selected students were applied fifteen times, twice a week, for thirty minutes every time. The total treatment process could be divided into two stages. The stage one included the first twelve treatments and the stage two included following three treatments. In the stage one, the selected autistic students learned twenty four musics under real-world-like social circumstances. In the stage two, the students repeatedly learned the twenty four musics. A week before beginning the music treatment, the students were tested by PRES and a test developed by the author of this thesis. And a week after all treatments were completed, the students were tested again with the same test method to check if the students' expressive language ability got improved. The results of the research were as the following: First, the music treatment helped improve the autistic student's ability of expressing themselves such as 'requesting', 'rejecting', 'applying social customs' and 'providing information'. Second, the author of this thesis first had a hypothesis that the tested students might show different levels of achievements according to their intellectual ability or expressive language ability in K-ABC test, PRES and CARS. But it was not true. The student's level of achievement by music activities was proved not to have a significant correlation with their intellectual or expressive language abilities in the tests. Third, it was found that, through pre- and post-test of PRES, the music treatments could improve the receptive language ability as well as the expressive language ability. It saw great effect that musical data that utilize in specially this research investigator according to children's ability, autistic children write lyrics setting in social circumstance that is revealed much routinely and composes. To front, expect that suitable a lot of musics are developed in function and ability of subject person for elevation of expressive language ability.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

• Journal of Nutrition and Health
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• v.55 no.5
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• pp.587-600
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• 2022

Purpose: This study was performed to analyze customer needs for the operation of unmanned food stores on a university campus. Methods: A total of 329 responses were collected from customers who had purchased food at the stores. Statistical analyses were conducted using the SPSS program for frequency analysis, χ2-test, t-test, one-way analysis of variance, and Duncan's multiple range test. Results: On average, the overall satisfaction score for lunch and the eating location was 3.91 out of 5 points. Overall satisfaction was significantly higher for home cooking, and lower for eating at convenience stores (p < 0.001), and the score for eating with family was significantly higher than for eating alone or with friends (p < 0.001). On average, the intention to use an unmanned store received a score of 3.98 out of 5 points, while 'home cooking (3.76)' was significantly lower than other eating locations and eating at 'convenience stores (4.38)' was significantly higher than other eating locations (p < 0.05). The desired time of use for unmanned food stores was 'lunch (54.1%)', 'dinner (46.2%)', and 'afternoon snack (41.9%)', and the desired foods were 'doshirak (62.0%)', 'sandwich (56.2%)', 'fruit cup (54.4%)', 'salad (51.7%)', and 'kimbap (50.5%)'. There were significantly more opinions that single-person households would use unmanned food stores for dinner more than family households (p < 0.05), and significantly more willingness to purchase fruit cup (p < 0.05). The average prices (Korean won) that the subjects were willing to pay for the purchase of food were 4,991 for doshirak, 3,403 for salad, 2,745 for fruit cup, 2,609 for sandwich, and 2,235 for kimbap. Conclusion: For the successful operation of the unmanned food stores on the university campus, the store manager should grasp the customer's needs in real-time and establish an effective marketing strategy.