• Atmosphere
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• v.29 no.3
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• pp.257-267
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• 2019

This study is to assess the applicability of the Extreme Forecast Index (EFI) algorithm of the ECMWF seasonal forecast system to the Global Seasonal Forecasting System version 5 (GloSea5), operational seasonal forecast system of the Korea Meteorological Administration (KMA). The EFI is based on the difference between Cumulative Distribution Function (CDF) curves of the model's climate data and the current ensemble forecast distribution, which is essential to diagnose the predictability in the extreme cases. To investigate its applicability, the experiment was conducted during the heat-wave cases (the year of 1994 and 2003) and compared GloSea5 hindcast data based EFI with anomaly data of ERA-Interim. The data also used to determine quantitative estimates of Probability Of Detection (POD), False Alarm Ratio (FAR), and spatial pattern correlation. The results showed that the area of ERA-Interim indicating above 4-degree temperature corresponded to the area of EFI 0.8 and above. POD showed high ratio (0.7 and 0.9, respectively), when ERA-Interim anomaly data were the highest (on Jul. 11, 1994 (> $5^{\circ}C$) and Aug. 8, 2003 (> $7^{\circ}C$), respectively). The spatial pattern showed a high correlation in the range of 0.5~0.9. However, the correlation decreased as the lead time increased. Furthermore, the case of Korea heat wave in 2018 was conducted using GloSea5 forecast data to validate EFI showed successful prediction for two to three weeks lead time. As a result, the EFI forecasts can be used to predict the probability that an extreme weather event of interest might occur. Overall, we expected these results to be available for extreme weather forecasting.

• Journal of IKEEE
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• v.23 no.3
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• pp.1096-1099
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• 2019

In this paper, we propose the protocol for construction of smart factory. The proposed protocol for construction of smart factory consists of an OPC UA Server/Client, a technology of TSN realtime communication, a NTP & PTP time synchronization protocol, a FieldBus protocol and conversion module, a technology of saving data for data transmit latency and synchronization protocol. OPC UA server/client is a system integration protocol which makes interface industrial hardware device and supports standardization which allows in all around area and also in not independent from any platform. A technology of TSN realtime communication provides an high sensitive time management and control technology in a way of sharing specific time between devices in the field of high speed network. NTP & PTP time synchronization protocol supports IEEE1588 standardization. A fieldbus protocol and conversion module provide an extendable connectivity by converting industrial protocol to OPC. A technology of saving data for data transmit latency and synchronization protocol provide a resolution function for a loss and latency of data. Results from testing agencies to assess the performance of proposed protocol for construction of smart factory, response time was 0.1367ms, synchronization time was 0.404ms, quantity of concurrent access was 100ea, quantity of interacting protocol was 5ea, data saving and synchronization was 1,000 nodes. It produced the same result as the world's highest level.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.3
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• pp.355-362
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• 2019

This technical note introduces a newly-proposed concept of deep horizontal drillhole disposal of spent nuclear fuel, and considers how it can be applied in the Korean environment. This disposal concept, in which high-level radioactive waste is disposed in deep horizontal drillholes installed with directional drilling technique, is expected to have great advantages over the existing deep mined repository concept in economics and safety. Since this concept is still at the idea level, however, it is necessary for worldwide expert groups to demonstrate its safety and performance. In addition, the development of guidelines by the regulatory body should be supported. The Korean circumstances, which include a narrow territory and a high population density, as well as the amount of spent nuclear fuel, make the NIMBY (Not In My Back Yard) phenomenon very strong and the siting conditions difficult. Under these conditions, if the disposal section of deep horizontal drillhole concept can be located at the continental shelf, with a stable environment, rather than in a coastal land area, it is expected to alleviate the psychological anxiety of the local community and stakeholders. Moreover, even when constructing a centralized deep mined repository in the future, it is necessary to consider locating the repository in the continental shelf.

• The Journal of Bigdata
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• v.3 no.2
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• pp.59-70
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• 2018

In order to provide stable district heat supplying service to the certain limited residential area, it is the most important to forecast the short-term future demand more accurately and produce and supply heat in efficient way. However, it is very difficult to develop a universal heat demand forecasting model that can be applied to general situations because the factors affecting the heat consumption are very diverse and the consumption patterns are changed according to individual consumers and regional characteristics. In particular, considering all of the various variables that can affect heat demand does not help improve performance in terms of accuracy and versatility. Therefore, this study aims to develop a demand forecasting model using deep learning based on only limited information that can be acquired in real time. A demand forecasting model was developed by learning the artificial neural network of the Tensorflow using past data consisting only of the outdoor temperature of the area and date as input variables. The performance of the proposed model was evaluated by comparing the accuracy of demand predicted with the previous regression model. The proposed heat demand forecasting model in this research showed that it is possible to enhance the accuracy using only limited variables which can be secured in real time. For the demand forecasting in a certain region, the proposed model can be customized by adding some features which can reflect the regional characteristics.

• Journal of IKEEE
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• v.23 no.1
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• pp.112-119
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• 2019

In this paper, we propose a deep learning structure suitable for embedded system. The flame detection process of the proposed deep learning structure consists of four steps : flame area detection using flame color model, flame image classification using deep learning structure for flame color specialization, $N{\times}N$ cell separation in detected flame area, flame image classification using deep learning structure for flame shape specialization. First, only the color of the flame is extracted from the input image and then labeled to detect the flame area. Second, area of flame detected is the input of a deep learning structure specialized in flame color and is classified as flame image only if the probability of flame class at the output is greater than 75%. Third, divide the detected flame region of the images classified as flame images less than 75% in the preceding section into $N{\times}N$ units. Fourthly, small cells divided into $N{\times}N$ units are inserted into the input of a deep learning structure specialized to the shape of the flame and each cell is judged to be flame proof and classified as flame images if more than 50% of cells are classified as flame images. To verify the effectiveness of the proposed deep learning structure, we experimented with a flame database of ImageNet. Experimental results show that the proposed deep learning structure has an average resource occupancy rate of 29.86% and an 8 second fast flame detection time. The flame detection rate averaged 0.95% lower compared to the existing deep learning structure, but this was the result of light construction of the deep learning structure for application to embedded systems. Therefore, the deep learning structure for flame detection proposed in this paper has been proved suitable for the application of embedded system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.12
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• pp.910-917
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• 2018

This paper describes the developments to improve the feeling and safety of the remote control system of unmanned vehicles. Generally, in the case of the remote control systems, a joystick-type device or a simple steering-wheel are used. There are many cases, in which there are operations without considering the feedback to users and driving feel. Recently, as the application area of the unmanned vehicles has been extended, the problems caused by not considering the feedback are emphasized. Therefore, the need for a force feedback-haptic control arises to solve these problems. In this study, the force feedback-haptic control algorithm considering the vehicle parameters is proposed. The vehicle parameters include first the state variables of dynamics, such as the body side-slip angle (${\beta}$) and yawrate (${\gamma}$), and second, the parameters representing the driving situations. Force feedback-haptic control technology consists of the algorithms for general and specific situations, and considers the situation transition process. To verify the algorithms, a simulator was constructed using the vehicle dynamics simulation tool with CAN communication environment. Using the simulator, the feasibility of the algorithms was verified in various scenarios.

• Journal of the Microelectronics and Packaging Society
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• v.26 no.1
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• pp.29-33
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• 2019

With shrinking form factor and improving performance of electronic packages, high input/output (I/O) density is considered as an important factor. Fan out wafer-level packaging (FO-WLP) has been paid great attention as an alternative. However, FO-WLP is vulnerable to warpage during its manufacturing process. Minimizing warpage is essential for controlling production yield, and in turn, package reliability. While many studies investigated the effect of process and design parameters on warpage using finite element analysis, they did not take uncertainty into consideration. As parameters, including material properties, chip positions, have uncertainty from the point of manufacturing view, the uncertainty should be considered to reduce the gap between the results from the field and the finite element analysis. This paper focuses on the effect of uncertainty of Young's modulus of chip on fan-out wafer level packaging warpage using finite element analysis. It is assumed that Young's modulus of each chip follows the normal distribution. Simulation results show that the uncertainty of Young's modulus affects the maximum von Mises stress. As a result, it is necessary to control the uncertainty of Young's modulus of silicon chip since the maximum von Mises stress is a parameter related to the package reliability.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.464-466
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• 2019

Controllers used in nuclear power plants require high reliability. A controller including a Field Programmable Gate Array (FPGA) and a Complex Programmable Logic Device (referred to hereinafter as FPGA) has been applied to many Nuclear Power Plants (NPP) in the past, including the APR1400 (Advanced Power Reactor 1400), a Korean digital nuclear power plant. Initially, the FPGA was considered as a general IC (Integrated Circuit) and verified only by device verification and performance testing. In the 1990s, research on FPGA verification began, and until the FPGA became a chip, it was regarded as software and the software Verification and Validation (V&V) using IEEE 1012-2004 was implemented. Currently, IEC 62566, which is a European standard, has been applied for a lot of verification. This method has been evaluated as the most sensible method to date. This is because the method of verifying the characteristics of SoC (System on Chip), which has been a problem in the existing verification method, is sufficiently applied. However, IEC 62566 is a European standard that has not yet been adopted in the United States and maintains the application of IEEE 1012 for FPGA. IEEE 1012-2004 or IEC 62566 is a technical standard. In practice, various methods are applied to meet technical standards. In this paper, we describe the procedure and important points of verification method of Nuclear Safety Class FPGA applying SoC verification method.

• Journal of Korean Society on Water Environment
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• v.35 no.2
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• pp.145-151
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• 2019

The purpose of this study was to investigate treatment characteristics of diatomite filtration, that would allow water recovery from biologically-treated effluent for reuse. Diatomite, Celpure 100, and acid clay were used as filter-aids, with a support filter manufactured from polyethylene (PE), and polypropylene (PP). This pre-coating process using diatomite filter-aids, is used in the filtration range of pressure filters, and has consistently provided high-quality separation. The results showed that variations in average removal efficiency of SS, and T-P from biologically treated effluent by the diatomite-coated PE filter, were approximately 82.2 ~ 88.9 % and 4.8 ~ 21.1 %, respectively. T-P treatment efficiency of the PP filter pre-coated with diatomite and $Celpure^{(R)}100$ at $57.64g/m^2$, was approximately $24{\pm}10%$ and $40{\pm}15%$ on average, respectively. Particle size distribution of secondary effluent varied from 0.05 to $200{\mu}m$, and $d_{50}$ value was $20.76{\mu}m$. The size distribution of particles in the diatomite filtrate ranged from 1.26 to $101.1{\mu}m$ when pre-coated with diatomite filter-aid, at a content of $57.64g/m^2$. Diatomite filter aids, i.e., the particles that form the pre-coating layer, capture very fine particles as well as macromolecules, owing to their complex structure with numerous fine microscopic pores, and surface properties. The filtration process using diatomite and $Celpure^{(R)}100$ as filter aids, has been successfully applied, to recover water from sewage for reuse. The disadvantage of the process, is that the particle size of the filter-aid is spent, because of pressurization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.7
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• pp.353-362
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• 2019

Thermodynamic analysis of cascade refrigeration systems has attracted considerable research attention. On the other hand, a system evaluation based on thermodynamic analyses of the individual parts, including the evaporator, condenser, intercooler, expansion valve, etc., has received less attention. In this study, performance analysis was conducted on a cascade refrigeration system, which has an individual cooling and refrigeration evaporator, and equips the intercooler and air-cooled condenser in a series in a lower cycle. The thermo-fluid design was then performed on the major components of the system - upper condenser, lower condenser, cooling evaporator, refrigeration evaporator, intercooler, compressor, electronic expansion valve - of 15 kW refrigeration, and 8 kW cooling capacity using R-410A. A series of simulations were conducted on the designed system. The change in outdoor temperature from 26 C to 38 C resulted in the cooling capacity of the lower evaporator remaining approximately the same, whereas it decreased by 9% at the upper evaporator and by 63% at the intercooler. The COP decreased with increasing outdoor temperature. In addition, the COP of the cycle with the intercooler operation was higher that of the cycle without the intercooler operation. Furthermore, the increase in the upper condenser size by two fold increased the upper evaporator by 4%. On the other hand, the lower evaporator capacity remained the same. The COP of the upper cycle increased with increasing upper condenser size, whereas that of the lower cycle remained almost the same. When the size of the lower condenser was increased 2.8 fold, the intercooler capacity increased by 8%, whereas those of upper and the lower evaporator remained approximately the same. Furthermore, the COP of the lower cycle increased with an increase in the lower condenser. On the other hand, the change of the upper condenser was minimal.