• Journal of radiological science and technology
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• v.39 no.1
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• pp.99-105
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• 2016

The noise power spectrum (NPS) is one of the most general methods for measuring the noise amplitude and the quality of an image acquired from a uniform radiation field. The purpose of this study was to compare different NPS methodologies by using megavoltage X-ray energies. The NPS evaluation methods in diagnostic radiation were applied to therapy using the International Electro-technical Commission standard (IEC 62220-1). Various radiation therapy (RT) devices such as TrueBeam$^{TM}$(Varian), BEAMVIEW$^{PLUS}$(Siemens), iViewGT(Elekta) and Clinac$^R$ iX (Varian) were used. In order to measure the region of interest (ROI) of the NPS, we used the following four factors: the overlapping impact, the non-overlapping impact, the flatness and penumbra. As for NPS results, iViewGT(Elekta) had the higher amplitude of noise, compared to BEAMVIEW$^{PLUS}$ (Siemens), TrueBeam$^{TM}$(Varian) flattening filter, Clinac$^{R}$iXaS1000(Varian) and TrueBeam$^{TM}$(Varian) flattening filter free. The present study revealed that various factors could be employed to produce megavoltage imaging (MVI) of the NPS and as a baseline standard for NPS methodologies control in MVI.

• Journal of the Korean Vacuum Society
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• v.18 no.4
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• pp.302-309
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• 2009

We fabricated a Si nano floating gate memory with Schottky barrier tunneling transistor structure. The device was consisted of Schottky barriers of Er-silicide at source/drain and Si nanoclusters in the gate stack formed by LPCVD-digital gas feeding method. Transistor operations due to the Schottky barrier tunneling were observed under small gate bias < 2V. The nonvolatile memory properties were investigated by measuring the threshold voltage shift along the gate bias voltage and time. We obtained the 10/50 mseconds for write/erase times and the memory window of $\sim5V$ under ${\pm}20\;V$ write/erase voltages. However, the memory window decreased to 0.4V after 104seconds, which was attributed to the Er-related defects in the tunneling oxide layer. Good write/erase endurance was maintained until $10^3$ write/erase times. However, the threshold voltages moved upward, and the memory window became small after more write/erase operations. Defects in the LPCVD control oxide were discussed for the endurance results. The experimental results point to the possibility of a Si nano floating gate memory with Schottky barrier tunneling transistor structure for Si nanoscale nonvolatile memory device.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.217-225
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• 2019

The purpose of this study was to quantitate signal to noise ratio and contrast to noise ratio of the portal vein using CT and 3.0T MRI and to investigate the optimal imaging device. Twenty patients who inspective CT and 3.0T MRI between February 2018 and April 2018 were randomly assigned to receive data from the picture archiving communication system. The SNR and CNR values were evaluated by measuring the mean and standard deviation of the region of interest of the four regions of the portal vein (the main portal vein, the right vein, the left vein, and the middle vein). The results showed that SNR was 9.180.72 in the right context, 9.410.84 in the left context, 9.540.59 in the middle context, 9.550.75 in the order context, and 22.292.03 in the right context and 25.893 in the 3.0T MRI. 19, median context: 24.392.87, and order Mac: 26.642.30 (p<0.05). CNR was 3.790.68 in the CT context, 3.740.65 in the left context, 3.710.39 in the middle context, 3.790.68 in the order context, 9.490.65 in the right context, and 11.0001.90 in the 3.0T MRI, Intermediate context: 12.701.75, order Mac: 10.010.98, 3.0T MRI was higher than CT (p<0.05). In conclusion, SNR and CNR values were higher in the 3.0T MRI than CT in the 4 portal regions. Therefore, 3.0T MRI using non-ionizing radiation was the most superior imaging equipment than CT.

• Korea Trade Review
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• v.48 no.3
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• pp.131-150
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• 2023

The purpose of this study was to find a countermeasure to the U.S. import refusals for the Korean healthcare and life sciences industry. To this end, an analysis of trends during the pandemic was conducted using the KITA Border Rejection Database, which includes information on items and types of import refusals. The reason for rejection was also analyzed according to the FDA violation codes. The degree of countermeasure for import refusals was identified by measuring the unit rejection rate (URR). The results of the analysis showed that the major U.S. import refusals for the Korean healthcare and life sciences industry had expanded from contact lenses to COVID-19 diagnostic kits and drugs after the pandemic broke out. The major reasons for import refusals were non-compliance with the Predicate Device and Drugs Act and non-approval by the FDA for products and facilities. On the other hand, the unit rejection rate (URR) of major items in the Korean healthcare and life sciences industry was measured higher than the industry average. The results therefore showed a low level of response to U.S. import refusals. The results of the analysis of reasons for import refusals by item according to FDA violation codes were as follows. First of all, the main violation for contact lenses and COVID-19 diagnostic kits corresponded to misbranding. This was often due to the fact that Korean companies did not provide the relevant notices and information required by the FDA. Many cases also failed to demonstrate a substantial equivalency compared to predicate devices already on the market. On the other hand, applications for new unapproved drugs were not accepted as they had yet to pass relevant regulations that would prove their safety and efficacy. In conclusion, import refusals for the Korean healthcare and life sciences industry were found to be closely related to technical barriers to trade (TBT).

• The Journal of Korean Society for Radiation Therapy
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• v.30 no.1_2
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• pp.49-63
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• 2018

Purpose : The purpose of this study is investigating the changes of treatment plan and comparing skin dose with or without the skin flash. To investigate optimal applications of the skin flash, the changes of skin dose of each plans by various thicknesses of skin flash were measured and analyzed also. Methods and Material : Anthropomorphic phantom was scanned by CT for this study. The 2 fields hybrid IMRT and the 6 fields static IMRT were generated from the Eclipse (ver. 13.7.16, Varian, USA) RTP system. Additional plans were generated from each IMRT plans by changing skin flash thickness to 0.5 cm, 1.0 cm, 1.5 cm, 2.0 cm and 2.5 cm. MU and maximum doses were measured also. The treatment equipment was 6MV of VitalBeam (Varian Medical System, USA). Measuring device was a metal oxide semiconductor field-effect transistor(MOSFET). Measuring points of skin doses are upper (1), middle (2) and lower (3) positions from center of the left breast of the phantom. Other points of skin doses, artificially moved to medial and lateral sides by 0.5 cm, were also measured. Results : The reference value of 2F-hIMRT was 206.7 cGy at 1, 186.7 cGy at 2, and 222 cGy at 3, and reference values of 6F-sIMRT were measured at 192 cGy at 1, 213 cGy at 2, and 215 cGy at 3. In comparison with these reference values, the first measurement point in 2F-hIMRT was 261.3 cGy with a skin flash 2.0 cm and 2.5 cm, and the highest dose difference was 26.1 %diff. and 5.6 %diff, respectively. The third measurement point was 245.3 cGy and 10.5 %diff at the skin flash 2.5 cm. In the 6F-sIMRT, the highest dose difference was observed at 216.3 cGy and 12.7 %diff. when applying the skin flash 2.0 cm for the first measurement point and the dose difference was the largest at the application point of 2.0 cm, not the skin flash 2.5 cm for each measurement point. In cases of medial 0.5 cm shift points of 2F-hIMRT and 6F-sIMRT without skin flash, the measured value was -75.2 %diff. and -70.1 %diff. at 2F, At -14.8, -12.5, and -21.0 %diff. at the 1st, 2nd and 3rd measurement points, respectively. Generally, both treatment plans showed an increase in total MU, maximum dose and %diff as skin flash thickness increased, except for some results. The difference of skin dose using 0.5 cm thickness of skin flash was lowest lesser than 20 % in every conditions. Conclusion : Minimizing the thickness of skin flash by 0.5 cm is considered most ideal because it makes it possible to keep down MUs and lowering maximum doses. In addition, It was found that MUs, maximum doses and differences of skin doses did not increase infinitely as skin flash thickness increase by. If the error margin caused by PTV or other factors is lesser than 1.0 cm, It is considered that there will be many advantages in with the skin flash technique comparing without it.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Applied Chemistry for Engineering
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• v.31 no.1
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• pp.43-48
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• 2020

Fe₂O₃ nanoparticles with the mixed structure of cubic and nanorod were synthesized by precipitation, hydrothermal, sol-gel method, etching process and heat treatment. Fe₂O₃/TiO₂ core-shell (CS) of type Fe₂O₃@TiO₂ composite was fabricated on a 20 nm nanolayer of TiO₂ coated on the surface of Fe₂O₃ nanoparticles. Fe₂O₃/TiO₂ yolk-shell (YS) composite was prepared by chemical etching and heat treatment of Fe₂O₃/TiO₂ CS nanoparticles. Physical properties of Fe₂O₃, Fe₂O₃@TiO₂ CS and Fe₂O₃@TiO₂ YS nanoparticles were characterized by FE-SEM, HR-TEM and X-ray diffraction. The solar reflectance, commission internationale de l'Elcairage (CIE) color coordinate and heat shield temperatures of Fe₂O₃, CS and YS type Fe₂O₃@TiO₂ pigments filled with poly acrylate (PA) paints were investigated by UV-Vis-NIR spectrometer and homemade heat shield temperature measuring device. The Fe₂O₃@TiO₂ YS red pigment filled PA composite exhibited excellent near infrared light reflecting performance and also reduced the heat shield temperature of 13 ℃ than that of Fe₂O₃ filled counterparts.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.253-263
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• 2013

Frequency Scanning Interferometry(FSI) system, one of the most promising optical surface measurement techniques, generally results in superior optical performance comparing with other 3-dimensional measuring methods as its hardware structure is fixed in operation and only the light frequency is scanned in a specific spectral band without vertical scanning of the target surface or the objective lens. FSI system collects a set of images of interference fringe by changing the frequency of light source. After that, it transforms intensity data of acquired image into frequency information, and calculates the height profile of target objects with the help of frequency analysis based on Fast Fourier Transform(FFT). However, it still suffers from optical noise on target surfaces and relatively long processing time due to the number of images acquired in frequency scanning phase. 1) a Polarization-based Frequency Scanning Interferometry(PFSI) is proposed for optical noise robustness. It consists of tunable laser for light source, ${\lambda}/4$ plate in front of reference mirror, ${\lambda}/4$ plate in front of target object, polarizing beam splitter, polarizer in front of image sensor, polarizer in front of the fiber coupled light source, ${\lambda}/2$ plate between PBS and polarizer of the light source. Using the proposed system, we can solve the problem of fringe image with low contrast by using polarization technique. Also, we can control light distribution of object beam and reference beam. 2) the signal processing acceleration method is proposed for PFSI, based on parallel processing architecture, which consists of parallel processing hardware and software such as Graphic Processing Unit(GPU) and Compute Unified Device Architecture(CUDA). As a result, the processing time reaches into tact time level of real-time processing. Finally, the proposed system is evaluated in terms of accuracy and processing speed through a series of experiment and the obtained results show the effectiveness of the proposed system and method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.825-832
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• 2020

The detection of estrus is very important for the successful reproductive efficiency of cattle. This has prompted the development of electronic estrus detection techniques by using the characterization of estrus behavior. The objective of this study was to investigate the changes in physical activity, mounting behavior and vocalization during estrus in Hanwoo (Korean native cattle). Bio-telemetry devices were attached to 4 multiparous Hanwoo and physical activity was compared, namely mounting behavior and vocalization for 6 days (from 2 days before the day of estrus to 3 days after the day of estrus). Physical activity rapidly increased on the day of estrus (p<0.001) and was frequently observed at night time. Mounting behavior gradually increased, starting from 2 days before the day of estrus and reached its highest level on the day of estrus (p<0.01). The circadian rhythm showed irregularities during this entire period (p>0.05). There was no significant difference in vocalization during the experiment period (p>0.05). In conclusion, we assumed that mounting behavior is an early indicator to detect estrus in Hanwoo and if both mounting behavior and physical activity are considered together it would be possible to detect estrus with a higher probability. Further studies with more information from different sources regarding the measuring of estrus in Hanwoo are needed.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.1-17
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• 2012

Personalized smart devices such as smartphones and smart pads are widely used. Unlike traditional feature phones, theses smart devices allow users to choose a variety of functions, which support not only daily experiences but also business operations. Actually, there exist a huge number of applications accessible by smart device users in online and mobile application markets. Users can choose apps that fit their own tastes and needs, which is impossible for conventional phone users. With the increase in app demand, the tastes and needs of app users are becoming more diverse. To meet these requirements, numerous apps with diverse functions are being released on the market, which leads to fierce competition. Unlike offline markets, online markets have a limitation in that purchasing decisions should be made without experiencing the items. Therefore, online customers rely more on item-related information that can be seen on the item page in which online markets commonly provide details about each item. Customers can feel confident about the quality of an item through the online information and decide whether to purchase it. The same is true of online app markets. To win the sales competition against other apps that perform similar functions, app developers need to focus on writing app descriptions to attract the attention of customers. If we can measure the effect of app descriptions on sales without regard to the app's price and quality, app descriptions that facilitate the sale of apps can be identified. This study intends to provide such a quantitative result for app developers who want to promote the sales of their apps. For this purpose, we collected app details including the descriptions written in Korean from one of the largest app markets in Korea, and then extracted keywords from the descriptions. Next, the impact of the keywords on sales performance was measured through our econometric model. Through this analysis, we were able to analyze the impact of each keyword itself, apart from that of the design or quality. The keywords, comprised of the attribute and evaluation of each app, are extracted by a morpheme analyzer. Our model with the keywords as its input variables was established to analyze their impact on sales performance. A regression analysis was conducted for each category in which apps are included. This analysis was required because we found the keywords, which are emphasized in app descriptions, different category-by-category. The analysis conducted not only for free apps but also for paid apps showed which keywords have more impact on sales performance for each type of app. In the analysis of paid apps in the education category, keywords such as 'search+easy' and 'words+abundant' showed higher effectiveness. In the same category, free apps whose keywords emphasize the quality of apps showed higher sales performance. One interesting fact is that keywords describing not only the app but also the need for the app have asignificant impact. Language learning apps, regardless of whether they are sold free or paid, showed higher sales performance by including the keywords 'foreign language study+important'. This result shows that motivation for the purchase affected sales. While item reviews are widely researched in online markets, item descriptions are not very actively studied. In the case of the mobile app markets, newly introduced apps may not have many item reviews because of the low quantity sold. In such cases, item descriptions can be regarded more important when customers make a decision about purchasing items. This study is the first trial to quantitatively analyze the relationship between an item description and its impact on sales performance. The results show that our research framework successfully provides a list of the most effective sales key terms with the estimates of their effectiveness. Although this study is performed for a specified type of item (i.e., mobile apps), our model can be applied to almost all of the items traded in online markets.