• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.41-48
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• 2023

In this paper, we propose an analysis of recent trends in the NFT (Non-Fungible Token) industry using topic modeling techniques, focusing on their universal application across various industrial fields. For this study, patent data was utilized to understand industry trends. We collected data on 371 domestic and 454 international NFT-related patents registered in the patent information search service KIPRIS from 2017, when the first NFT standard was introduced, to October 2023. In the preprocessing stage, stopwords and lemmas were removed, and only noun words were extracted. For the analysis, the top 50 words by frequency were listed, and their corresponding TF-IDF values were examined to derive key keywords of the industry trends. Next, Using the LDA algorithm, we identified four major latent topics within the patent data, both domestically and internationally. We analyzed these topics and presented our findings on NFT industry trends, underpinned by real-world industry cases. While previous review presented trends from an academic perspective using paper data, this study is significant as it provides practical trend information based on data rooted in field practice. It is expected to be a useful reference for professionals in the NFT industry for understanding market conditions and generating new items.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.1-10
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• 2023

This paper proposes a method to extend Inter-Carrier Interference (ICI) canceling Orthogonal Frequency Division Multiplexing (OFDM) receivers for 5G mobile systems to spatial multiplexing 2×2 MIMO (Multiple Input Multiple Output) systems to support high-speed ground transportation services by linear motor cars traveling at 500 km/h. In Japan, linear-motor high-speed ground transportation service is scheduled to begin in 2027. To expand the coverage area of base stations, 5G mobile systems in high-speed moving trains will have multiple base station antennas transmitting the same downlink (DL) signal, forming an expanded cell size along the train rails. 5G terminals in a fast-moving train can cause the forward and backward antenna signals to be Doppler-shifted in opposite directions, so the receiver in the train may have trouble estimating the exact channel transfer function (CTF) for demodulation. A receiver in such high-speed train sees the transmission channel which is composed of multiple Doppler-shifted propagation paths. Then, a loss of sub-carrier orthogonality due to Doppler-spread channels causes ICI. The ICI Canceller is realized by the following three steps. First, using the Demodulation Reference Symbol (DMRS) pilot signals, it analyzes three parameters such as attenuation, relative delay, and Doppler-shift of each multi-path component. Secondly, based on the sets of three parameters, Channel Transfer Function (CTF) of sender sub-carrier number n to receiver sub-carrier number l is generated. In case of n≠l, the CTF corresponds to ICI factor. Thirdly, since ICI factor is obtained, by applying ICI reverse operation by Multi-Tap Equalizer, ICI canceling can be realized. ICI canceling performance has been simulated assuming severe channel condition such as 500 km/h, 8 path reverse Doppler Shift for QPSK, 16QAM, 64QAM and 256QAM modulations. In particular, 2×2MIMO QPSK and 16QAM modulation schemes, BER (Bit Error Rate) improvement was observed when the number of taps in the multi-tap equalizer was set to 31 or more taps, at a moving speed of 500 km/h and in an 8-pass reverse doppler shift environment.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3874-3897
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• 2023

A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High-Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next-generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds-averaged Navier-Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.1
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• pp.63-74
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• 2024

In agriculture, frost can be devastating, which is why observation and forecasting are so important. According to a recent report analyzing frost observation data from the Korea Meteorological Administration, despite global warming due to climate change, the late frost date in spring has not been accelerated, and the frequency of frost has not decreased. Therefore, it is important to automate and continuously operate frost observation in risk areas to prevent agricultural frost damage. In the existing frost observation using leaf wetness sensors, there is a problem that the reference voltage value fluctuates over a long period of time due to contamination of the observation sensor or changes in the humidity of the surrounding environment. In this study, a datalogger program was implemented to automatically solve these problems. The established frost observation system can stably and automatically accumulate time-resolved observation data over a long period of time. This data can be utilized in the future for the development of frost diagnosis models using machine learning methods and the production of frost occurrence prediction information for surrounding areas.

• The Journal of Korean Obstetrics and Gynecology
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• v.37 no.1
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• pp.75-88
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• 2024

Objectives: This study aimed to identify the current use of Korean medicine for obesity and its effect for women in climacteric period. Methods: We studied women aged 45-55 who visited Daejeon Korean medicine Hospital of Daejeon University to lose body weight from January 1, 2021 to December 31, 2022 via an analysis of the medical records. The treatment duration was continuous for more than 2 weeks, and a body composition was measured by Inbody 770 at 2 to 4 weeks after the first visit. Results: 28 patients were finally selected and their average age was 49.32±3.38 years. Based on the body mass index (BMI) classification, 19 were in the 1st obesity group, 5 in the 2nd obesity group, 3 in the overweight group and 1 in the normal group. Patients usually complained comcomitant symptoms, and the symptoms of menopausal disorder was the most frequent. The average treatment duration was 3.68±0.67 weeks and the average treatment frequency was 3.93±0.98 times. All patients took herbal medicines Gambi-tang and 23 took modified fasting therapy including Gamro-su. 14 were treated by whole body far-infrared therapy and 6 were gotten partial obesity treatment. Among patients treated for accompanying symptoms, menopausal disorders were the most common (35.71%), and herbal medicine such as Gamisoyou-san, Hominis Placenta Pharmacopuncture, moxibustion, and cupping were used. After treatment, on average, body composition changed significantly; body weight 3.28±1.82 kg, BMI 1.36±1.04 kg/m², body fat 1.70±1.67 kg, skeletal muscle mass 0.81±0.91 kg, abdominal circumference 2.04±2.6 cm, and visceral fat area 8.91±12.83 cm². Conclusions: We analyzed general characteristics, BMI distribution, types of Korean medicine treatment and change of body composition. This study could be used as reference to provide practical data of treatment for obese women in climacteric period.

• Annals of Occupational and Environmental Medicine
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• v.34
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• pp.15.1-15.9
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• 2022

Background: Most previous longitudinal studies on lifestyle and gastroesophageal reflux disease (GERD) have focused on physical activity rather than sitting time. The main purpose of this study was to investigate the relationship between prolonged sitting time and the development of erosive esophagitis (EE). Methods: A self-report questionnaire was used for measuring sitting time in the Kangbuk Samsung Health Study. Sitting time was categorized into four groups: ≤ 6, 7-8, 9-10, and ≥ 11 hours/day. Esophagogastroduodenoscopy (EGD) was performed by experienced endoscopists who were unawared of the aims of this study. Hazard ratios (HRs) and 95% confidence intervals (CIs) for the development of EE were estimated using Cox proportional hazards analyses with ≤ 6 hours/day sitting time as the reference. Results: There were 6,524 participants included in the study. During a mean follow-up of 3.14 years, 2,048 incident cases developed EE. In age- and sex-adjusted models, the HR in the group sitting ≥ 11 hours per day compared ≤ 6 hours per day was 0.88 (95% CI: 0.76-0.99). After further adjusting for alcohol intake, smoking status, educational level, history of diabetes, and history of dyslipidemia, sitting time was still significantly related to the risk of EE (HR, 0.87; 95% CI: 0.76-0.98). After further adjustment for exercise frequency, this association persisted (HR, 0.86; 95% CI: 0.76-0.98). In subgroup analysis by obesity, the relationship between sitting time and EE was only significant among participants with body mass index < 25 kg/m² (HR, 0.82; 95% CI: 0.71-0.95). Conclusions: Generally, prolonged sitting time is harmful to health, but with regard to EE, it is difficult to conclude that this is the case.

• Journal of dental hygiene science
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• v.12 no.4
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• pp.404-412
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• 2012

The main object of this study is to render a better dental education to mental disabilities, teachers, and their parents. By providing a better dental education to them, mental disabilities would understand the importance of their oral hygiene. The study was held in Seoul at two different locations, named H and E mental welfare facilities. Ninety Three mental disabilities were studied by observing their oral behavior, simple oral hygiene index and plaque index prior and post to dental education. At the end of education, following result were gathered from two mental facilities. First, the level of oral behavior in Class 1,2, and 3 mental disabilities were observed prior and post to the dental education. Overall, there was no significant difference among Class 1 mental disabilities with the dental education. Second, in simple oral hygiene index, the severity of mental illness has affected on their oral behavior (F=6.322, p<.001). Third, in simple oral hygiene index, the frequency of dental education, regardless of severity of mental illness has affected on their oral hygiene (F=5.961, p<.01). Fourth, the plaque index also illustrated that the frequency of dental education, regardless of severity of dental illness has affected on their oral hygiene (F=5.126, p<.05). Finally, the general characteristics of mental disabilities according to changes in oral health awareness to gender, age, disability type, educational level do not statistically significant in all variables. Their simple oral hygiene index and plaque index advanced, although after a while they started to lose focus, which brought back their old habits. Nevertheless, in conclusion I believe that helping mental disabilities more frequently to constant reminder, will not only keep them entertained, but help them realize how important oral hygiene practice is, hopefully increasing and benefiting those with mental disabilities for future reference.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.1
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• pp.33-39
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• 2006

Purpose: To determine appropriate sampling frequency and time of multiple blood sampling dual exponential method with $^{99m}Tc$-DTPA for calculating glomerular filtration rate (GFR). Materials & Methods: Thirty four patients were included in this study. Three mCi of $^{99m}Tc$-DTPA was intravenously injected and blood sampling at 9 different times, 5ml each, were done. Using the radioactivity of serum, measured by gamma counter, the GFR was calculated using dual exponential method and corrected with the body surface area. Using spontaneously chosen 2 data points of serum radioactivity, 15 collections of 2-sample GFR were calculated. And 10 collections of 3-sample GFR and 12 collections of 4-sample GFR were also calculated. Using the 9-sample GFR as a reference value, degree of agreement was analyzed with Kendall's $\tau$ correlation coefficients, mean difference and standard deviation. Results: Although some of the 2-sample GFR showed high correlation coefficient, over or underestimation had evolved as the renal function change. The 10-120-240 min 3-sample GFR showed a high correlation coefficient (${\tau}=0.93$), minimal difference ($Mean{\pm}SD=-1.784{\pm}3.972$), and no over or underestimation as the renal function changed. The 4-sample GFR showed no better accuracy than the 3-sample GFR. Conclusions: In the wide spectrum of renal function, the 10-120-240 min 3-sample GFC could be the best choice for estimating the patients' renal function.

• Journal of Biosystems Engineering
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• v.6 no.2
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• pp.65-76
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• 1982

This survey was conducted to investigate the status of repair and maintenance of 4 wheel tractor for a basic reference to the improvement of quality and proper utilization of tractors. Thirty two counties from eight provinces, except Jeju, were covered in this study in order to investigate annual break-down and repair of tractor in 1980. The analyzed results are summarized as follows; 1. The average number of break-down of large size tractors(47ps) was 5.0 times in a year and it was about twice of that of small size tractors(19-23ps). The break-down frequency per 100 hours of use was 1.11 times in the large size and 0.65 times in the small size tractors. 2. 75.6 percent of total break-down was occured in main body of tractor and 24.4 percent in attachments. In particular, the break-down of plow and rotavator was more than 80 percent of total break-down of the small size tractor attachments. 3. The large size tractors which were occured more than one times of break-down a year was 75 percent and its rate of the small size tractor was 62 percent. But 9 percent of tractor surveyed had more than ten times of break-down in a year 4. The frequency of break-down had a peak in May, and it was directly proportional to the hours of use. 5. The causes of break-down were poor maintenance and operation by 29.8 precent, old parts by 30.2 percent, poor quality of parts by 20.6 percent, poor field condition by 16.3 percent and others by 3.1 percent. 6. Annual number of repair was 5.5 times and among them 55.6 percent was done by shop and 44.4 percent by operator. 7. Total required repair time was 30.6 hours a year in the large size tractor and 19.9 hours in the small size tractor. Average repair time was 3.62 hours a time. 8. Annual repair cost was 278 thousand won in the large size tractor and 70 thousand won in the small size tractor. The repair cost per hour of use was 621 won in the large size and 198 won in the small size tractor. 9. The repair cost rate of tractor(Y) was regulated with tractor age (X) as follow; Y=0.752X In case of the service life of tractor was 10 years, the total repair cost rate was 64 percent.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.