• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1217-1227
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• 2018

This paper aims to evaluate the applicability of dam inflow prediction model using recurrent neural network theory. To achieve this goal, the Artificial Neural Network (ANN) model and the Elman Recurrent Neural Network(RNN) model were applied to hydro-meteorological data sets for the Soyanggang dam and the Chungju dam basin during dam operation period. For the model training, inflow, rainfall, temperature, sunshine duration, wind speed were used as input data and daily inflow of dam for 10 days were used for output data. The verification was carried out through dam inflow prediction between July, 2016 and June, 2018. The results showed that there was no significant difference in prediction performance between ANN model and the Elman RNN model in the Soyanggang dam basin but the prediction results of the Elman RNN model are comparatively superior to those of the ANN model in the Chungju dam basin. Consequently, the Elman RNN prediction performance is expected to be similar to or better than the ANN model. The prediction performance of Elman RNN was notable during the low dam inflow period. The performance of the multiple hidden layer structure of Elman RNN looks more effective in prediction than that of a single hidden layer structure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.169-180
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• 2018

White light-emitting diodes (LEDs) are more economical than fluorescent lights, and provide high brightness, a high lifetime expectancy, and greater durability. As LEDs are closely connected with people's daily lives, dimming control of LED is an important component in providing energy savings and improving quality of life. In visible light communications systems using these LEDs, multiple input multiple output (MIMO) technology has attracted a lot of attention, in that it can attain the channel capacity in proportion to the number of antennas. This paper analyzes the power performance of three kinds of modulation in visible light communications (VLC) systems applied space-time block code (STBC) techniques. The modulation schemes are return-to-zero on-off keying (RZ-OOK), variable pulse position modulation (VPPM), and overlapping pulse position modulation (OPPM), and dimming control was applied. The power requirements and power consumption were used as metrics to compare the power efficiency in $2{\times}2$ STBC-VLC environments under the three kinds of modulation. We confirm that dimming control affects the communications performance of each modulation scheme. VPPM showed greater consumption among the three modulations, and OPPM showed energy savings comparable to VPPM.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.1
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• pp.68-81
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• 2021

The agricultural ecosystem is one of the major sources of greenhouse gas (GHG) emissions. In order to search for climate change adaptation options which mitigate GHG emissions while maintaining crop yield, it is advantageous to integrate multiple models at a high spatial resolution. The objective of this study was to develop a tool to support integrated assessment of climate change impact b y coupling the DSSAT model and the DNDC model. DNDC Regional Input File Tool(DRIFT) was developed to prepare input data for the regional mode of DNDC model using input data and output data of the DSSAT model. In a case study, GHG emissions under the climate change conditions were simulated using the input data prepared b y the DRIFT. The time to prepare the input data was increased b y increasing the number of grid points. Most of the process took a relatively short time, while it took most of the time to convert the daily flood depth data of the DSSAT model to the flood period of the DNDC model. Still, processing a large amount of data would require a long time, which could be reduced by parallelizing some calculation processes. Expanding the DRIFT to other models would help reduce the time required to prepare input data for the models.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.415-423
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• 2021

Recently, an R-based point time series data validation system has been established for the statistical post processing and improvement of the National Center for AgroMeteorology-Land Atmosphere Modeling Package (NCAM-LAMP) medium-range prediction data. The time series verification system was used to compare the NCAM-LAMP with the AWS observations and GDAPS medium-range prediction model data operated by Korea Meteorological Administration. For this comparison, the model latitude and longitude data closest to the observation station were extracted and a total of nine points were selected. For each point, the characteristics of the model prediction error were obtained by comparing the daily average of the previous prediction data of air temperature, wind speed, and hourly precipitation, and then we tried to improve the next prediction data using Support Vector Machine( SVM) method. For three months from August to October 2017, the SVM method was used to calibrate the predicted time series data for each run. It was found that The SVM-based correction was promising and encouraging for wind speed and precipitation variables than for temperature variable. The correction effect was small in August but considerably increased in September and October. These results indicate that the SVM method can contribute to mitigate the gradual degradation of medium-range predictability as the model boundary data flows into the model interior.

• Korean Journal of Construction Engineering and Management
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• v.23 no.5
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• pp.65-76
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• 2022

The New Excellent Technology (NET) designation system, introduced in 1989 for the purpose of promoting the development of domestic construction technology and enhancing national competitiveness, reviews the statement of construction cost of new technologies. And the cost reduction effect such as design, construction, and maintenance cost and the effect of reducing the construction duration are evaluated as an evaluation criteria of economic feasibility. However, in this evaluation process, differences of opinion between the institution of construction cost estimating standard management and the new technology developer about unique technologies frequently occur. In addition it is difficult to objectively compare the construction duration with existing similar technologies because there is no information on productivity as the current cost estimating standards for new technologies only present the required amount per unit quantity. In this study, the current state of cost estimating criteria review procedure, evaluation criteria, and cost estimating standards establishment method were analyzed when screening for the designation of a new construction technologies, and compared with overseas cost estimating standards, measures to improve the cost estimating standards of current construction new technologies were suggested. Through the improved cost estimating standards of this study, it is expected that cost information on new technologies will be provided to clients in more detail than the current ones, and the availability and applicability of new construction technologies would be improved by simplifying the construction cost calculation process more.

• Radiation Oncology Journal
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• v.24 no.4
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• pp.300-308
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• 2006

$\underline{Purpose}$: To develop a wireless CCTV system in semi-beam's eye view (BEV) to monitor daily patient setup in radiation therapy. $\underline{Materials\;and\;Methods}$: In order to get patient images in semi-BEV, CCTV cameras are installed in a custom-made acrylic applicator below the treatment head of a linear accelerator. The images from the cameras are transmitted via radio frequency signal (${\sim}2.4\;GHz$ and 10 mW RF output). An expected problem with this system is radio frequency interference, which is solved utilizing RF shielding with Cu foils and median filtering software. The images are analyzed by our custom-made software. In the software, three anatomical landmarks in the patient surface are indicated by a user, then automatically the 3 dimensional structures are obtained and registered by utilizing a localization procedure consisting mainly of stereo matching algorithm and Gauss-Newton optimization. This algorithm is applied to phantom images to investigate the setup accuracy. Respiratory gating system is also researched with real-time image processing. A line-laser marker projected on a patient's surface is extracted by binary image processing and the breath pattern is calculated and displayed in real-time. $\underline{Results}$: More than 80% of the camera noises from the linear accelerator are eliminated by wrapping the camera with copper foils. The accuracy of the localization procedure is found to be on the order of $1.5{\pm}0.7\;mm$ with a point phantom and sub-millimeters and degrees with a custom-made head/neck phantom. With line-laser marker, real-time respiratory monitoring is possible in the delay time of ${\sim}0.17\;sec$. $\underline{Conclusion}$: The wireless CCTV camera system is the novel tool which can monitor daily patient setups. The feasibility of respiratory gating system with the wireless CCTV is hopeful.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.1
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• pp.83-89
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• 2014

Purpose : In case of the intensity modulated radiation therapy (IMRT) using Tomotherapy and linear accelerator (Linac), it was to compare and to evaluate the imaging dose of MVCT and CBCT that were performed daily for the correct set up of the patient. Materials and Methods : The human body model Phantom (Anderson rando Phantom, USA) was divided into the three parts as Head, Thorax, pelvis, and after GafChromic EBT3 film cut to the size of $0.5{\times}0.5cm2$.in the center of the recording area were situated on the ant, post, left, and right surface of the phantom and 2cm in depth from the ant, post, left, right, and center surface of the phantom, the surface dose and inner dose were measured repeatedly three times, respectively, using the tomotherapy (Hi Art) and the OBI of NovalisTx. The measured film calculated the output value by RIP version6.0 and then the average value of the dose was calculated by the one-way analysis of variance. Results : Using the human body model phantom, the results of MVCT and CBCT performance were that measurements of MVCT inner dose were showed $15.43cGy{\pm}6.05$ in the head, $16.62cGy{\pm}3.08$ in the thorax, $16.81cGy{\pm}5.24$ in the pelvis, and measurements of CBCT inner dose were showed $13.28{\pm}3.68$ in the head, from $13.66{\pm}4.04$ in the thorax, $15.52{\pm}3.52$ in the pelvis. The measurements of surface dose were showed in case of MVCT performance, $11.64{\pm}4.05$ in the head, $12.16{\pm}4.38$ in the thorax, $12.05{\pm}2.71$ in the pelvis, and in case of CBCT performance, $14.59{\pm}3.51$ in the head, $15.82{\pm}2.89$ in the thorax, $17.48{\pm}2.80$ in the pelvis, respectively. Conclusion : In case of Inner dose, the MVCT using MV energy showed higher than the CBCT using kV energy at 1.16 times in the head, at 1.22 times in the thorax, at 1.08 times in the pelvis, and in case of surface dose, the CBCT was higher than MVCT, at 1.25 times in the head, at 1.30 times in the thorax, at 1.45 times in the pelvis. Imaging dose was a small amount compared to the therapeutic dose but it was thought to affect partially to normal tissue because it was done in daily schedule. However, IMRT treatment was necessarily parallel with the IGRT treatment through the image-guide to minimize errors between planned and actual treatment. Thus, to minimize imaging dose that the patients receive, when planning the treatment, it should be set up a treatment plan considering imaging dose, or it must be performed by minimizing the scan range when shooting MVCT.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1079-1094
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• 2008

This study is to evaluate the impact of varying spatial resolutions on the uncertainty of Soil and Water Assessment Tool (SWAT) predicted streamflow, non-point source (NPS) pollution loads transport in a small agricultural watershed (1.21 $km^2$) for three cases of model input; Case A is the combination of 2 m DEM, QuickBird land use, Case B is the combination of 10 m DEM, 1/25,000 land use, and Case C is the combination of 30 m DEM, Landsat land use, soil data is used 1/25,000 for three cases respectively. The model was calibrated for 2 years (1999-2000) using daily streamflow and monthly water quality records, and verified for another 2 years (2001-2002). The average Nash and Sutcliffe model efficiency was 0.59 for streamflow and RMSE were 2.08, 4.30 and 0.70 tons/yr for sediment, T-N and T-P respectively. The model was run for a small agricultural watershed with three cases of spatial input data. The hydrological results showed that output uncertainty was biggest by spatial resolution of land use. Streamflow increase the watershed average CN value of QucikBird land use was 0.4 and 1.8 higher than those of 1/25,000 and Landsat land use caused increase of streamflow. On the other hand, The NPS loadings from the model prediction showed that the sediment, T-N and T-P of QuickBird land use (Case A) showed 23.7 %, 43.3 % and 48.4 % higher value than 1/25,000 land use (Case B) and 50.6 %, 50.8 % and 56.9 % higher value than Landsat land use (Case C) respectively.

• Journal of Animal Science and Technology
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• v.52 no.4
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• pp.271-280
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• 2010

This study was conducted to investigate the effects of Aspergillus niger-derived multi-enzyme complex supplementation to feedrestricted lactating sows on performances, milk yield, blood profiles, and manure excretion as compared with ad libitum-fed sows without supplementation of enzyme. Fifty multiparous lactating Berkshire sows were allotted to 5 treatments of 10 sows per treatment during a 28-d lactation period and litter per sow was standardized to 9 suckling piglets. Treatments were ad libitum-fed sows without enzyme and feed-restricted sows supplemented with four increasing levels (0, 0.02, 0.04 and 0.08%) of multi-enzyme complex derived from Aspergillus niger. Blood samples from all sows were collected to determine serum metabolite concentrations before the morning feeding on d 27 of lactation. Litter body weight and a piglet weight at weaning, and litter weight gain significantly (P<0.05) increased with increasing levels of multi-enzyme complex, but there was no significant difference between ad libitum-fed sows without enzyme and feed-restricted sows supplemented with multi-enzyme complex. Body condition score and backfat depth at weaning significantly (P<0.05) increased as multi-enzyme complex level increased. Lactational backfat depth tended (P>0.05) to less decrease with increasing levels of enzyme complex. Serum inorganic phosphorus and non-esterified fatty acid concentrations significantly (P<0.05) increased with increasing levels of enzyme complex. Daily milk yield was not significantly different across treatments, but milk fat yield significantly (P<0.05) increased as multi-enzyme complex level increased. Manure output was significantly (P<0.01) higher for ad libitum-fed sows than for feed-restricted sows, but there was no significant difference among feed-restricted sows supplemented with increasing levels of multi-enzyme complex. Fecal phosphorus amount significantly (P<0.05) decreased with increasing levels of multi-enzyme complex. Feed costs of sows per litter weight gain were reduced by 1.25% to 9.67% with increasing levels of multi-enzyme complex as compared with ad libitum-fed sows without enzyme. The results indicated that multi-enzyme supplementation to feed-restricted lactating sows not only increased litter performances, but also was comparable to ad libitum-fed sows, resulting in reduced feed costs. Moreover, the reduction of fecal phosphorus amount with increasing levels of enzyme complex would contribute to the reduction of environmental pollution.