• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.38.3-39
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• 2010

While major solar proton events (SPEs) come from the coronal mass eject (CME)-driven shocks in solar wind, there are many evidences that potentiality of CMEs to generate SPEs depends on its early evolution near the Sun and on different solar activities observed around the CME liftoff time. To decipher origin of SPE release, we have investigated onset time comparison of the SPE with CME, metric type II radio burst, and hard X-ray flare. For this, we select 30 SPEs observed from 1997 to 2006 by using the particle instrument ERNE onboard SOHO, which allows proton flux anisotropy measurement in the energy range ~10 - 50MeV. Onset time of the SPEs is inferred by considering the energy-dependent proton transport time. As results, we found that (1) SPE onset time is comparable to that of type II but later than type III onset time and HXR start time, (2) SPE onset time is mostly later than the peak time of HXR flare, (3) almost half of the SPE onsets occurred after the HXR emission, and (4) there are two groups of CME height at the onset time of SPE; one is the height below 5 Rs (low corona) and the other is above 5Rs (high corona). In this talk, we will present the onset time comparison and discuss about the origin of the SPE onset.

• Journal of KIISE
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• v.42 no.8
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• pp.1022-1030
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• 2015

The context-awareness of mobile applications yields several issues for testing, since mobile applications should be able to be tested in any environment and under any contextual input. In previous studies of testing for Android applications as an event-driven system, many researchers have focused on using generated test cases considering only Graphical User Interface (GUI) events. However, it is difficult to find failures that could be detected when considering the changes in the context in which applications run. It is even more important to consider various contexts since the mobile applications adapt and use the new features and sensors of mobile devices. In this paper, we provide a method of systematically generating various executing contexts from permissions. By referring to the lists of permissions, the resources used by the applications for running Android applications can be easily inferred. To evaluate the efficiency of our testing method, we applied the method on two open source projects and showed that it contributes to improve the statement code coverage.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.43-52
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• 2016

Wireless sensor network (WSN) technology has been implemented using commercial off-the-shelf microcontrollers (MCUs), In this paper, we propose a simulation environment to realize the physical evaluation of FPGA-based node by considering vertically cross-layered WSN in terms of physical node device and network interconnection perspective. The proposed simulation framework emulates the physical FPGA-based sensor nodes to interoperate with the NS3 through the runtime infrastructure (RTI). For the emulation and interoperation of FPGA-based nodes, we extend a vendor-providing FPGA design tool from the host computer and a script to execute the interoperation procedures. The standalone NS-3 is also revised to perform interoperation through the RTI. To resolve the different time-advance mechanisms between the FPGA emulation and event-driven NS3 simulation, the pre-simulation technique is applied to the proposed environment. The proposed environment is applied to IEEE 802.15.4-based low-rate, wireless personal area network communication.

• Structural Engineering and Mechanics
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• v.69 no.4
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• pp.407-416
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• 2019

This paper develops a wireless sensor for online fatigue crack detection and failure warning based on crack-induced nonlinear ultrasonic modulation. The wireless sensor consists of packaged piezoelectric (PZT) module, an excitation/sensing module, a data acquisition/processing module, a wireless communication module, and a power supply module. The packaged PZT and the excitation/sensing module generate ultrasonic waves on a structure and capture the response. Based on nonlinear ultrasonic modulation created by a crack, the data acquisition/processing module periodically performs fatigue crack diagnosis and provides failure warning if a component failure is imminent. The outcomes are transmitted to a base through the wireless communication module where two-levels duty cycling media access control (MAC) is implemented. The uniqueness of the paper lies in that 1) the proposed wireless sensor is developed specifically for online fatigue crack detection and failure warning, 2) failure warning as well as crack diagnosis are provided based on crack-induced nonlinear ultrasonic modulation, 3) event-driven operation of the sensor, considering rare extreme events such as earthquakes, is made possible with a power minimization strategy, and 4) the applicability of the wireless sensor to steel welded members is examined through field and laboratory tests. A fatigue crack on a steel welded specimen was successfully detected when the overall width of the crack was around $30{\mu}m$, and a failure warnings were provided when about 97.6% of the remaining useful fatigue lives were reached. Four wireless sensors were deployed on Yeongjong Grand Bridge in Souht Korea. The wireless sensor consumed 282.95 J for 3 weeks, and the processed results on the sensor were transmitted up to 20 m with over 90% success rate.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.157-166
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• 2021

Forecasting dam inflow based on high reliability is required for efficient dam operation. In this study, deep learning technique, which is one of the data-driven methods and has been used in many fields of research, was manipulated to predict the dam inflow. The Long Short-Term Memory deep learning with Sequence-to-Sequence model (LSTM-s2s), which provides high performance in predicting time-series data, was applied for forecasting inflow of Soyang River dam. Various statistical metrics or evaluation indicators, including correlation coefficient (CC), Nash-Sutcliffe efficiency coefficient (NSE), percent bias (PBIAS), and error in peak value (PE), were used to evaluate the predictive performance of the model. The result of this study presented that the LSTM-s2s model showed high accuracy in the prediction of dam inflow and also provided good performance for runoff event based runoff prediction. It was found that the deep learning based approach could be used for efficient dam operation for water resource management during wet and dry seasons.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.62-68
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• 2023

An aerial relay system utilizing an unmanned aerial vehicle(UAV) or drone is addressed for event-driven operations such as temporary communication services for disaster affected area, military and first responder support. UAV relay system (URS) targets to provide a reliable communication service to a remote user equipment or an operator, therefore, a fast UAV placement to guarantee a minimum quality of service(QoS) is important when an operation is requested. Researches on UAV utilization in communication systems mostly target to derive the optimal position of UAV to maximize the performance, however, fast deployment of UAV is much more important than optimal placement under emergency situations. To this end, this paper derives the feasible area for UAV placement, investigates the effect of performance requirements on that area, and suggests UAV placement to certainly guarantee the performance requirements. Simulation results demonstrate that the feasible area derived in this paper matches that obtained by an exhaustive search.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.163-163
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• 2023

Flooding has become an increasing event which is one of the major natural disasters responsible for direct economic damage in South Korea. Driven by climate change, precipitation extremes play significant role on the flood damage and its further increase is expected to exacerbate the socioeconomic impact in the country. However, the empirical evidence associating changes in precipitation extremes to the historical flood damage is limited. Thus, there is a need to assess the causal relationship between changes in precipitation extremes and flood damage, especially in agricultural region like Chungcheong region in South Korea. The spatial and temporal changes of precipitation extremes from 10 synoptic stations based on daily precipitation data were analyzed using the ClimPACT2 tool and Mann-Kendall test. The four precipitation extreme indices consisting of consecutive wet days (CWD), number of very heavy precipitation wet days (R30 mm), maximum 1-day precipitation amount (Rx1day), and simple daily precipitation intensity (SDII), which represent changes in intensity, frequency, and duration, respectively, and the time series data on flooded area and flood damage from 1985 to 2020 were used to investigate the causal relationship in the ARDL-ECM framework and pairwise Granger causality analysis. The trend results showed that majority of the precipitation indices indicated positive trends, however, CWD showed no significant changes. ARDL-ECM framework showed that there was a long-run relationship among the variables. Further analysis on the empirical results showed that flooded area and Rx1day have significant positive impacts on the flood damage in both short and long-runs while R30 mm only indicated significant positive impact in the short-run, both in the current period, which implies that an increase in flooded area, Rx1day, and R30 mm will cause an increase in the flood damage. The pairwise Granger analysis showed unidirectional causality from the flooded area, R30 mm, Rx1day, and SDII to flood damage. Thus, these precipitation indices could be useful as indicators of pluvial flood damage in Chungcheong region of South Korea.

• Asia-Pacific Journal of Business
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• v.15 no.1
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• pp.209-223
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• 2024

Purpose - This article analyzes the impact of macroeconomic variables of the United States, China, and Korea on KOSPI and VKOSPI, in that United States and China have a great influence on Korea, having an export-driven economy. Design/methodology/approach - The influence of US, China, and Korea interest rates, industrial production index, consumer price index, US employment index, Chinese real estate index, and Korea's foreign exchange reserves on KOSPI and VKOSPI is analyzed on monthly basis from Jan 2012 to Aug 2023, using multifactor model. Findings - The KOSPI showed a positive relationship with the U.S. industrial production index and Korea's foreign exchange reserves, and a negative relationship with the U.S. employment index and Chinese real estate index. The VKOSPI showed a positive relationship with the Chinese consumer price index, and a negative relationship with the U.S. interest rates, and Korean foreign exchange reserves. Next, dividing the analysis into two periods with the Covid crisis and the analysis by country, the impact of US macroeconomic variables on KOSPI was greater than Chinese ones and the impact of Chinese macroeconomic variables on VKOSPI was greater than US ones. The result of the forward predictive failure test confirmed that it was appropriate to divide the period into two periods with economic event, the Covid Crisis. After the Covid crisis, the impact of macroeconomic variables on KOSPI and VKOSPI increased. This reflects the financial market co-movements due to governments' policy coordination and central bank liquidity supply to overcome the crisis in the pandemic situation. Research implications or Originality - This study is meaningful in that it analyzed the effects of macroeconomic variables on KOSPI and VKOSPI simultaneously. In addition, the leverage effect can also be confirmed through the relationship between macroeconomic variables and KOSPI and VKOSPI. This article examined the fundamental changes in the Korean and global financial markets following the shock of Corona by applying this research model before and after Covid crisis.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.347-361
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• 2023

Water utilities are making various efforts to reduce water losses from water networks, and an essential part of them is to recognize the moment when a pipe burst occurs during operation quickly. Several physics-based methods and data-driven analysis are applied using real-time flow and pressure data measured through a SCADA system or smart meters, and methodologies based on machining learning are currently widely studied. Water utilities should apply various approaches together to increase pipe burst detection. The most intuitive and explainable water balance method and its procedure were presented in this study, and the applicability and detection performance were evaluated by applying this approach to water supply pipelines. Based on these results, water utilities can establish a mass balance-based pipe burst detection system, give a guideline for installing new flow meters, and set the detection parameters with expected performance. The performance of the water balance analysis method is affected by the water network operation conditions, the characteristics of the installed flow meter, and event data, so there is a limit to the general use of the results in all sites. Therefore, water utilities should accumulate experience by applying the water balance method in more fields.

• Sleep Medicine and Psychophysiology
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• v.8 no.1
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• pp.45-51
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• 2001

Objectives: The experience of traffic accident is a kind of the psychosocial stressors to person. The traffic accident-related patients may show the psychophysiologic hyperarousal. So we examined the differences of psychophysiologic response between patients with and without the memory of experienceing a traffic accident. Methods: Twenty-four traffic accident-related patients were divided into two groups according to ther memory of a traffic accident. In psychological assessment, levels of anxiety and depression were evaluated by State-Trait Anxiety Inventory, Beck's Depression Inventory, and Hamilton Rating Scales For Anxiety and Depression. Heart rate, electrodermal response (EDR), and electromyographic activity (EMG) were measured by biofeedback system, and systolic and diastolic blood pressure by automated vital sign monitor during baseline, task, and rest periods. We utilized script-driven imagery technique as a stressful task. The patients listened to the script describing their own traffic accident experience and were instructed to imagine the event during the task period. Statistically analytic data were obtained from the differences of psychological and psychophysiologic data between two groups. Results: The memory group did not show significantly higher EDR than the none memory group, but showed higher tendency during baseline, imagery, and rest periods. The memory group showed significantly lower EMG than the none memory group during rest period. However, there were no differences in other psychophysiologic reponses between the two groups. Conclusion: Our results showed that the memory group had higher tendency in autonomic arousal level such as electrodermal response than the none memory group. We suggest that physicians need to minimize repetitive imagery of traffic accident (reexperience), and decrease the autonomic hyperarousal in the treatment of traffic accident-related patients.