• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.332-334
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• 2015

Nowadays a disaster event such as a building on fire, an earthquake or typhoon could occur any time, and any where. In such event, a warning notification system is a vital tool to send warning notifications to at-risk people in advance and provide them useful information to escape the dangerous area. Though some systems have been proposed such as emergency alert system using android, SMS or P2P overlay network, these works mainly focus on a reliable message distribution methods. In this work, we introduce a full prototype implementation of a personalized warning notification system based on geosocial information, which generates a personalized warning message for each user and delivers the messages through email or an android application. The system consists of four main modules: a web interface, database, a knowledge-based message generator, and message distributor. An android application is also created for user to receive warning messages on their smart phone. The prototype has been demonstrated successfully with a building-on-fire scenario.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.229-229
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• 2016

현재 국내외에서 제공되고 있는 기후변화 시나리오 자료의 경우 일단위로 제공되고 있다. 그러나 수자원 설계 및 계획 시 중요한 입력자료 중 하나는 시간단위 강우 자료이다. 이러한 시간단위 자료는 강우-유추 분석, 댐 설계 및 위험도 분석에 있어 중요한 입력 변수중 하나이므로 기후변화 시나리오에 따른 영향을 평가하기 위해선 신뢰성 있는 상세화 기법이 필요하다. 국내외에서는 일단위에서 일단위로 상세화 하는 기법, 또는 공간상세화 기법 연구는 상당히 진행된바 있는 반면, 시간단위 상세화 기법 연구는 일단위 연구에 비해 상대적으로 미진한 실정이다. 즉 일단위 상세화 기법의 경우 Weather generator, Weather typing 등 다양한 기법이 존재하고 이를 활용한 연구사례가 많지만, 시간단위 상세화 기법의 Poisson 기법을 활용한 사례가 다수 존재하였다. 이러한 이유로 본 연구에서는 기후변화 시나리오에 따른 영향을 평가하기 위해 Bayesian 기법을 도입하여 신뢰성 있는 시간단위 강우량을 생성할 수 있는 모형을 개발하였으며, 연대별로 산정된 결과는 빈도해석을 통해 미래 확률강우량을 제시하였다. 본 연구에서 제안하고자 하는 Bayesian Copula 모형은 기존 주변확률분포(marginal distribution) 매개변수와 Copula 매개변수 추정시 각각 다른 기법을 활용하여 추정하며, 각각 모형에서 발생하는 불확실성은 추정하지 못하는 반면, Bayesian Copula 모형의 경우 매개변수의 사후분포를 정량적으로 제시할 수 있으며, 추정되는 확률강우량 역시 불확실성을 정량적으로 산정할 수 있는 장점을 확인할 수 있었다.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.296-296
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• 2015

The aim of this paper is to numerically explore the feasibility of designing a Mini-Hydro turbine. The interest for this kind of horizontal axis turbine relies on its versatility. For instance, in the field of renewable energy, this kind of turbine may be considered for different applications, such as: tidal power, run-of-the-river hydroelectricity, wave energy conversion. It is fundamental to improve the turbine performance and to decrease the equipment costs for achievement of "environmental friendly" solutions and maximization of the "cost-advantage". In the present work, the commercial CFD code ANSYS is used to perform 3D simulations, solving the incompressible Unsteady Reynolds-Averaged Navier-Stokes (U-RANS) equations discretized by means of a finite volume approach. The implicit segregated version of the solver is employed. The pressure-velocity coupling is achieved by means of the SIMPLE algorithm. The convective terms are discretized using a second order accurate upwind scheme, and pressure and viscous terms are discretized by a second-order-accurate centered scheme. A second order implicit time formulation is also used. Turbulence closure is provided by the realizable k - turbulence model. In this study, a mini hydro turbine (3kW) has been considered for utilization of horizontal axis impeller. The turbine performance and flow behavior have been evaluated by means of numerical simulations. Moreover, the performance of the impeller varied in the pressure distribution, torque, rotational speed and power generated by the different number of blades and angles. The model has been validated, comparing numerical results with available experimental data.

• Nuclear Engineering and Technology
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• v.49 no.5
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• pp.928-940
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• 2017

An experiment using the $Prim{\ddot{a}}rkreisl{\ddot{a}}ufe$ Versuchsanlage (PKL) was performed for the OECD/NEA PKL-3 Project as a counterpart to a previous test with the large-scale test facility (LSTF) on a cold leg smallbreak loss-of-coolant accident with an accident management (AM) measure in a pressurized water reactor. Concerning the AM measure, the rate of steam generator (SG) secondary-side depressurization was controlled to achieve a primary depressurization rate of 200 K/h as a common test condition; however, the onset timings of the SG depressurization were different from each other. In both tests, rapid recovery started in the core collapsed liquid level after loop seal clearing, which caused whole core quench. Some discrepancies appeared between the LSTF and PKL test results for the core collapsed liquid level, the cladding surface temperature, and the primary pressure. The RELAP5/MOD3.3 code predicted the overall trends of the major thermal-hydraulic responses observed in the LSTF test well, and indicated a remaining problem in the prediction of primary coolant distribution. Results of uncertainty analysis for the LSTF test clarified the influences of the combination of multiple uncertain parameters on peak cladding temperature within the defined uncertain ranges.

• Journal of Fashion Business
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• v.22 no.5
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• pp.125-136
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• 2018

This study intended to develop a motorcycle safe vest that can be prepared against accidents by mounting a smart module (with built-in sensor) on the safe vest in order to emphasize safety among functional aspects of the motorcycle clothing. The research method investigated professional books, prior research, and Internet data to examine the characteristics of motorcycle wear and the theoretical examination of smart wear, and analyzed the functional characteristics of the design by reviewing smart jacket and vest design cases for motorcycles currently on the market. As a results of study an interface device sensor, which contains a sensor with IMU(Intertial Measurement Unit) and CPU(Central Processing Unit), was inserted into a motorcycle top in order to draw attention to the safety of motorcycle riders. The IMU sensor attached to the vest detected the tilting motion of the rider to either left or right side to obtain data on left or right direction, sudden stop, and so forth and displayed left or right turn signal and sudden stop sign on the backplate (back) through the LED module. As for charging the device to operate LEDs, a generator, which is designed to convert the heat energy in the exhaust into electric energy, was used to efficiently self-produce the power required to operate LEDs of the top while riding.

• Journal of Power Electronics
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• v.19 no.2
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• pp.580-590
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• 2019

The concept of virtual synchronous generators (VSGs) is a valuable means for improving the frequency stability of microgrids (MGs). However, a great virtual inertia in a VSG's controller may cause power oscillation, thereby deteriorating system stability. In this study, a small-signal model of an MG with two paralleled VSGs is established, and a control strategy for maintaining a constant inertial time with an increasing active-frequency droop coefficient (m) is proposed on the basis of a root locus analysis. The power oscillation is suppressed by adjusting virtual synchronous reactance, damping coefficient, and load frequency coefficient under the same inertial time constant. In addition, the dynamic load distribution is sensitive to the controller parameters, especially under the parallel operation of VSGs with different capacities. Therefore, an active power increment method is introduced to improve the precision of active power sharing in dynamic response. Simulation and experimental is used to verify the theoretical analysis findings.

• Journal of Information Technology Applications and Management
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• v.29 no.6
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• pp.81-93
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• 2022

As deep learning technology in natural language and visual processing has rapidly developed, collaborative filtering-based recommendation systems using deep learning technology are being actively introduced in the recommendation field. In this study, OCF-GAN, a hybrid collaborative filtering model using GAN, was proposed to solve the one-class and cold-start problems, and its usefulness was verified through performance evaluation. OCF-GAN based on conditional GAN consists of a generator that generates a pattern similar to the actual user preference pattern and a discriminator that tries to distinguish the actual preference pattern from the generated preference pattern. When the training is completed, user preference vectors are generated based on the actual distribution of preferred items. In addition, the cold-start problem was solved by using a hybrid collaborative filtering recommendation method that additionally utilizes user and item profiles. As a result of the performance evaluation, it was found that the performance of the OCF-GAN with additional information was superior in all indicators of the Top 5 and Top 20 recommendations compared to the existing GAN-based recommender. This phenomenon was more clearly revealed in experiments with cold-start users and items.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.4 no.1
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• pp.59-64
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• 2006

Ion exchange resin particles should not be found in steam generator(S/G) sludge. The suspicious spherical resin particles observed in S/G sludge sample were characterized for particle size distribution under optical microscope using the micro-technique, for element analysis by the electron probe micro analysis (EPMA), and for molecular identification by the IR spectroscopy. The particle sizes are distributed from 1 to $200{\mu}m$ for the sludge, while 40 to $500{\mu}m$ for the spherical resin particles. The results of the elemental analysis showed different major impurities: Si, Al, Mn, Cr, Ni, Zn and Ti for the sludge particles, while Si, Cu, Zn for the spherical resin particles. However, both particles contain Fe as a matrix of magnetite $(Fe_3O_4)$. IR spectrum of the spherical particles was not quite similar to the IR spectrum of ion exchange resins used in S/G system. These results indicate that the spherical particles are not related to ion exchange resin particles and may be formed by the process of the sludge formation.

• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.51-56
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• 2020

It is going to select one X-ray generating device for diagnosis in a radiography laboratory at K university in Gangwon-do to detect bacteria on the surface contamination of tables, IP cassettes, and lead gowns for medical radiation shielding and to inform students of the need for proper disinfection control and hand hygiene. Then disinfection was carried out with tissue, tissue cleaner and 70% alchol and immediately collected with sterile cotton swabs to assess the contamination distribution status and disinfection effects of the surface. The results of measuring the degree of contamination on the surface showed that the largest number of bacteria were detected in Apron, and the evaluation of the disinfection effects according to surface contamination showed a noticeable effect at 70% Alcohol in IP Cassette, and the disinfection effect was the same for Apron. Therefore, in order to prevent bacterial infections among students, basic hand washing and regular disinfection should be performed before the practice to prevent infection.