• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.109-130
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• 2011

One of the major problems in the area of data mining is the size of the data, as most data set has huge volume these days. Streams of data are normally accumulated into data storages or databases. Transactions in internet, mobile devices and ubiquitous environment produce streams of data continuously. Some data set are just buried un-used inside huge data storage due to its huge size. Some data set is quickly lost as soon as it is created as it is not saved due to many reasons. How to use this large size data and to use data on stream efficiently are challenging questions in the study of data mining. Stream data is a data set that is accumulated to the data storage from a data source continuously. The size of this data set, in many cases, becomes increasingly large over time. To mine information from this massive data, it takes too many resources such as storage, money and time. These unique characteristics of the stream data make it difficult and expensive to store all the stream data sets accumulated over time. Otherwise, if one uses only recent or partial of data to mine information or pattern, there can be losses of valuable information, which can be useful. To avoid these problems, this study suggests a method efficiently accumulates information or patterns in the form of rule set over time. A rule set is mined from a data set in stream and this rule set is accumulated into a master rule set storage, which is also a model for real-time decision making. One of the main advantages of this method is that it takes much smaller storage space compared to the traditional method, which saves the whole data set. Another advantage of using this method is that the accumulated rule set is used as a prediction model. Prompt response to the request from users is possible anytime as the rule set is ready anytime to be used to make decisions. This makes real-time decision making possible, which is the greatest advantage of this method. Based on theories of ensemble approaches, combination of many different models can produce better prediction model in performance. The consolidated rule set actually covers all the data set while the traditional sampling approach only covers part of the whole data set. This study uses a stock market data that has a heterogeneous data set as the characteristic of data varies over time. The indexes in stock market data can fluctuate in different situations whenever there is an event influencing the stock market index. Therefore the variance of the values in each variable is large compared to that of the homogeneous data set. Prediction with heterogeneous data set is naturally much more difficult, compared to that of homogeneous data set as it is more difficult to predict in unpredictable situation. This study tests two general mining approaches and compare prediction performances of these two suggested methods with the method we suggest in this study. The first approach is inducing a rule set from the recent data set to predict new data set. The seocnd one is inducing a rule set from all the data which have been accumulated from the beginning every time one has to predict new data set. We found neither of these two is as good as the method of accumulated rule set in its performance. Furthermore, the study shows experiments with different prediction models. The first approach is building a prediction model only with more important rule sets and the second approach is the method using all the rule sets by assigning weights on the rules based on their performance. The second approach shows better performance compared to the first one. The experiments also show that the suggested method in this study can be an efficient approach for mining information and pattern with stream data. This method has a limitation of bounding its application to stock market data. More dynamic real-time steam data set is desirable for the application of this method. There is also another problem in this study. When the number of rules is increasing over time, it has to manage special rules such as redundant rules or conflicting rules efficiently.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.237-246
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• 2016

This study is therefore aimed at measuring the surface dose rate and the spatial dose rate in and outside the radionuclide facility in order to ensure safety of the patients, radiation workers and family care-givers in their use of such equipment and to provide a basic framework for further research on radiation protection. The study was conducted at 4 restrooms in and outside the radionuclide facility of a general hospital in Incheon between May 1 and July 31, 2014. During the study period, the spatial contamination dose rate and the surface contamination dose rate before and after radiation use were measured at the 4 places-thyroid therapy room, PET center, gamma camera room, and outpatient department. According to the restroom use survey by hospitals, restrooms in the radionuclide facility were used not only by patients but also by family care-givers and some of radiation workers. The highest cumulative spatial radiation dose rate was 8.86 mSv/hr at camera room restroom, followed by 7.31 mSv/hr at radioactive iodine therapy room restroom, 2.29 mSv/hr at PET center restroom, and 0.26 mSv/hr at outpatient department restroom, respectively. The surface radiation dose rate measured before and after radiation use was the highest at toilets, which are in direct contact with patient's excretion, followed by the center and the entrance of restrooms. Unsealed radioactive sources used in nuclear medicine are relatively safe due to short half lives and low energy. A patient who received those radioactive sources, however, may become a mobile radioactive source and contaminate areas the patient contacts-camera room, sedation room, and restroom-through secretion and excretion. Therefore, patients administered radionuclides should be advised to drink sufficient amounts of water to efficiently minimize radiation exposure to others by reducing the biological half-life, and members of the public-family care-givers, pregnant women, and children-be as far away from the patients until the dose remains below the permitted dose limit.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.9
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• pp.14-23
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• 2010

This paper reports the fabrication of a DVB-T/H System in Package (SiP) that is able to receive and process the DVB-T/H signal. The DVB-T/H is the European telecommunication standard for Digital Video Broadcasting (DVB). An IC-embedded Printed Circuit Board (PCB) process, interpose a chip between PCB layers, has applied to the DVB-T/H SiP. The chip inserted in DVB-T/H SiP is the System on Chip (SoC) for mobile TV. It is comprised of a RF block for DVB-T/H RF signal and a digital block to convert received signal to digital signal for an application processor. To operate the DVB-T/H IC, a 3MHz DC-DC converter and LDO are on the DVB-T/H SiP. And a 38.4MHz crystal is used as a clock source. The fabricated DVB-T/H SiP form 4 layers which size is $8mm{\times}8mm$. The DVB-T/H IC is located between 2nd and 3rd layer. According to the result of simulation, the RF signal sensitivity is improved since the layout modification of the ground plane and via. And we confirmed the adjustment of LC value on power transmission is necessary to turn down the noise level in a SiP. Although the size of a DVB-T/H SiP is decreased over 70% than reference module, the power consumption and efficiency is on a par with reference module. The average power consumption is 297mW and the efficiency is 87%. But, the RF signal sensitivity is declined by average 3.8dB. This is caused by the decrease of the RF signal sensitivity which is 2.8dB, because of the noise from the DC-DC converter.

• Journal of Environmental Impact Assessment
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• v.24 no.6
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• pp.578-592
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• 2015

To investigate characteristics and seasonal variations of carbonaceous species for $PM_{2.5}$ in Seoul metropolitan area, Korea, we measured organic carbon (OC) and elemental carbon (EC) from January 2014 to December 2014 using a semi-continuous OC/EC Analyzer (Model-4, Sunset Lab.). Mean concentrations of OC and EC were estimated $4.1{\pm}2.7{\mu}g/m^3$ and $1.6{\pm}1.0{\mu}g/m^3$, respectively. The annual averaged OC/EC ratio was $2.9{\pm}2.7$. Concentrations of OC and EC comprised 13% and 5% of $PM_{2.5}$ and the mass fraction of both was the highest in fall. OC and EC showed similar trend in seasonal variations. Concentrations of those showed a clear seasonal variation with the highest in winter and the lowest in summer. The correlations between the two were the best during the winter ($r^2=0.88$). As results of carbonaceous species analysis, the dominant factor in view of fine particle ($PM_{2.5}$) is primary emission source such as mobile, fossil fuel combustion during commute time(08:00~10:00 or 17:00~21:00) and winter season. Continuous monitoring of atmospheric carbonaceous species is essential to provide the science-based data to policy-maker establishing the air quality improvement policy.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.1
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• pp.9-18
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• 2017

Arsenic (As) has been considered as the most toxic one among various hazardous materials and As contamination can be caused naturally and anthropogenically. Major forms of arsenic in groundwater are arsenite [(As(III)] and/or arsenate [(As(V)], depending on redox condition: arsenite and arsenate are predominant in reduced and oxidized environments, respectively. Because arsenite is much more toxic and mobile than arsenate, there have been a number of studies on the reduction of its toxicity through oxidation of As(III) to As(V). This study was initiated to develop photocatalytic oxidation process for treatment of groundwater contaminated with arsenite. The performance of two types of light sources (UV lamp and UV LED) was compared and the feasibility of goethite as a photocatalyst was evaluated. The highest removal efficiency of the process was achieved at a goethite dose of 0.05 g/L. Based on the comparison of oxidation efficiencies of arsenite between two light sources, the apparent performance of UV LED was inferior to that of UV lamp. However, when the results were appraised on the basis of their emitting UV irradiation, the higher performance was achieved by UV LED than by UV lamp. This study demonstrates that environmentally friendly process of goethite-catalytic photo-oxidation without any addition of foreign catalyst is feasible for the reduction of arsenite in groundwater containing naturally-occurring goethite. In addition, this study confirms that UV LED can be used in the photo-oxidation of arsenite as an alternative light source of UV lamp to remedy the drawbacks of UV lamp, such as long stabilization time, high electrical power consumption, short lifespan, and high heat output requiring large cooling facilities.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.589-597
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• 2023

Floating debris in large quantities from land during heavy rainfall has adverse social, economic, and environmental impacts, but the monitoring system for the concentration area and amount is insufficient. In this study, we proposed an efficient monitoring method for floating debris entering the river during heavy rainfall in Daecheong Lake, the largest water supply source in the central region, and applied remote sensing techniques to estimate the standing-stock of floating debris. To investigate the status of floating debris in the upper of Daecheong Lake, we used a tracking buoy equipped with a low-orbit satellite communication terminal to identify the movement route and behavior characteristics, and used a drone to estimate the potential concentration area and standing-stock of floating debris. The location tracking buoys moved rapidly during the period when the cumulative rainfall for 3 days increased by more than 200 to 300 mm. In the case of Hotan Bridge, which showed the longest distance, it moved about 72.8 km for one day, and the maximum moving speed at this time was 5.71 km/h. As a result of calculating the standing-stock of floating debris using a drone after heavy rainfall, it was found to be 658.8 to 9,165.4 tons, with the largest amount occurring in the Seokhori area. In this study, we were able to identify the main concentrations of floating debris by using location-tracking buoys and drones. It is believed that remote sensing-based monitoring methods, which are more mobile and quicker than traditional monitoring methods, can contribute to reducing the cost of collecting and processing large amounts of floating debris that flows in during heavy rain periods in the future.