• Journal of Korea Water Resources Association
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• v.53 no.10
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• pp.845-859
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• 2020

Climate change and recent heat waves have drawn public attention toward other environmental issues, such as water pollution in the form of algal blooms, chemical leaks, and oil spills. Water pollution by the leakage of chemicals may severely affect human health as well as contaminate the air, water, and soil and cause discoloration or death of crops that come in contact with these chemicals. Chemicals that may spill into water streams are often colorless and water-soluble, which makes it difficult to determine whether the water is polluted using the naked eye. When a chemical spill occurs, it is usually detected through a simple contact detection device by installing sensors at locations where leakage is likely to occur. The drawback with the approach using contact detection sensors is that it relies heavily on the skill of field workers. Moreover, these sensors are installed at a limited number of locations, so spill detection is not possible in areas where they are not installed. Recently hyperspectral images have been used to identify land cover and vegetation and to determine water quality by analyzing the inherent spectral characteristics of these materials. While hyperspectral sensors can potentially be used to detect chemical substances, there is currently a lack of research on the detection of chemicals in water streams using hyperspectral sensors. Therefore, this study utilized remote sensing techniques and the latest sensor technology to overcome the limitations of contact detection technology in detecting the leakage of hazardous chemical into aquatic systems. In this study, we aimed to determine whether 18 types of hazardous chemicals could be individually classified using hyperspectral image. To this end, we obtained hyperspectral images of each chemical to establish a spectral library. We expect that future studies will expand the spectral library database for hazardous chemicals and that verification of its application in water streams will be conducted so that it can be applied to real-time monitoring to facilitate rapid detection and response when a chemical spill has occurred.

• Journal of Plant Biotechnology
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• v.43 no.3
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• pp.359-366
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• 2016

Tradescantia is a perennial plant in the family of Commelinaceae. It is known to be sensitive to radiation. In this study, Tradescantia BNL 4430 was irradiated with gamma radiation at doses of 50 to 1,000 mGy in a phytotron equipped with a $^{60}Co$ radiation source at Korea Atomic Energy Research Institute, Korea. At 13 days after irradiation, we extracted RNA from irradiated floral tissues for RNA-seq. Transcriptome assembly produced a total of 77, 326 unique transcripts. In plantlets exposed to 50, 250, 500, and 1000 mGy, the numbers of up-regulated genes with more than 2-fold of expression compared that in the control were 116, 222, 246, and 308, respectively. Most of the up-regulated genes induced by 50 mGy were heat shock proteins (HSPs) such as HSP 70, indicating that protein misfolding, aggregation, and translocation might have occurred during radiation stress. Similarly, highly up-regulated transcripts of the IQ-domain 6 were induced by 250 mGy, KAR-UP oxidoreductase 1 was induced by 500 mGy, and zinc transporter 1 precursor was induced by 1000 mGy. Reverse transcriptase (RT) PCR and quantitative real time PCR (qRT-PCR) further validated the increased mRNA expression levels of selected genes, consistent with DEG analysis results. However, 2.3 to 97- fold higher expression activities were induced by different doses of radiation based on qRT-PCR results. Results on the transcriptome of Tradescantia in response to radiation might provide unique identifiers to develop in situ monitoring kit for measuring radiation exposure around radiation facilities.

• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.97-106
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• 2019

The purpose of this study was to investigate the effect of the type and measurement location of a fabric strain gauge sensor on the detection performance for respiratory signals. We implemented two types of sensors to measure the respiratory signal and attached them to a band to detect the respiratory signal. Eight healthy males in their 20s were the subject of this study. They were asked to wear two respiratory bands in turns. While the subjects were measured for 30 seconds standing comfortably, the respiratory was given at 15 breaths per minute were synchronized, and then a 10-second break; subsequently, the entire measurement was repeated. Measurement locations were at the chest and abdomen. In addition, to verify the performance of respiratory measurement in the movement state, the subjects were asked to walk in place at a speed of 80 strides per minute(SPM), and the respiratory was measured using the same method mentioned earlier. Meanwhile, to acquire a reference signal, the SS5LB of BIOPAC Systems, Inc., was worn by the subjects simultaneously with the experimental sensor. The Kruskal-Wallis test and Bonferroni post hoc tests were performed using SPSS 24.0 to verify the difference in measurement performances among the group of eight combinations of sensor types, measurement locations, and movement states. In addition, the Wilcoxon test was conducted to examine whether there are differences according to sensor type, measurement location, and movement state. The results showed that the respiratory signal detection performance was the best when the respiratory was measured in the chest using the CNT-coated fabric sensor regardless of the movement state. Based on the results of this study, we will develop a chest belt-type wearable platform that can monitor the various vital signal in real time without disturbing the movements in an outdoor environment or in daily activities.

• The Transactions of the Korea Information Processing Society
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• v.7 no.11S
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• pp.3651-3667
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• 2000

Recently, in the distributed multimedia environments based on internet, as radical growing technologies, the most of researchers focus on both streaming technology and distributed object thchnology, Specially, the studies which are tried to integrate the streaming services on the distributed object technology have been progressing. These technologies are applied to various stream service mamgements and protocols. However, the stream service management mexlels which are being proposed by the existing researches are insufficient for suporting the QoS of stream services. Besides, the existing models have the problems that cannot support the extensibility and the reusability, when the QoS-reiatedfunctions are being developed as a sub-module which is suited on the specific-purpose application services. For solving these problems, in this paper. we suggested a QoS Integrated platform which can extend and reuse using the distributed object technologies, and guarantee the QoS of the stream services. A structure of platform we suggested consists of three components such as User Control Module(UCM), QoS Management Module(QoSM) and Stream Object. Stream Object has Send/Receive operations for transmitting the RTP packets over TCP/IP. User Control ModuleI(UCM) controls Stream Objects via the COREA service objects. QoS Management Modulel(QoSM) has the functions which maintain the QoS of stream service between the UCMs in client and server. As QoS control methexlologies, procedures of resource monitoring, negotiation, and resource adaptation are executed via the interactions among these comiXments mentioned above. For constmcting this QoS integrated platform, we first implemented the modules mentioned above independently, and then, used IDL for defining interfaces among these mexlules so that can support platform independence, interoperability and portability base on COREA. This platform is constructed using OrbixWeb 3.1c following CORBA specification on Solaris 2.5/2.7, Java language, Java, Java Media Framework API 2.0, Mini-SQL1.0.16 and multimedia equipments. As results for verifying this platform functionally, we showed executing results of each module we mentioned above, and a numerical data obtained from QoS control procedures on client and server's GUI, while stream service is executing on our platform.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.558-569
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• 2020

This study examined the frequency of a broiler's stay in each area as stock density using an ICT-based image analysis technique from the perspective of precision livestock farming (PLF) according to the increase in the domestic broiler farms to understand the normal behavior patterns of broilers by age. The broiler was used in the experimental box (3.3×2.7 m) in a poultry house in Gyeonggi province. The stock densities were 9.5 birds/㎡ (n=85) and 19 birds/㎡ (n=170), respectively, and the frequency of stay by feeding, water, and rest area was monitored using a top-view camera. The image data of three-colored-specific broilers identified as the stock density were acquired by age (12, 16, 22, 27, and 29 days) for six hours. In the collected image data, the object tracking technique was used to record the cumulative movement path by connecting approximately 640,000 frames at 30 fps to quantify the frequency of stay in each area. In each stock density, it was significant in the order of the rest area, feeding, and water area (p<0.001). In 9.5 birds/㎡, it was at 57.9, 24.2, and 17.9 %, and 73.2, 16.8, and 10 % in 19 birds/㎡. The frequency of a broiler's stay could be evaluated in each area as the stock density using an ICT-based image analysis technique that minimizes stress. This method is expected to be used to provide basic material for developing an ICT-based management system through real-time monitoring.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.235-250
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• 2021

The overarching question of this study is how a typical rice cultivation system in Gimje, Korea was keeping up with the triple-win challenge of climate-smart agriculture (CSA). To answer this question, we have employed (1) quantitative data from direct measurement of energy, water, carbon and information flows in and out of a rice cultivation system and (2) appropriate metrics to assess production, efficiency, GHG fluxes, and resilience. The study site was one of the Korean Network of Flux measurement (KoFlux) sites (i.e., GRK) located at Gimje, Korea, managed by National Academy of Agricultural Science, Rural Development Administration. Fluxes of energy, water, carbon dioxide (CO₂) and methane (CH₄) were directly measured using eddy-covariance technique during the growing seasons of 2011, 2012 and 2014. The production indicators include gross primary productivity (GPP), grain yield, light use efficiency (LUE), water use efficiency (WUE), and carbon uptake efficiency (CUE). The GHG mitigation was assessed with indicators such as fluxes of carbon dioxide (F_CO2), methane (F_CH4), and nitrous oxide (F_N2O). Resilience was assessed in terms of self-organization (S), using information-theoretic approach. Overall, the results demonstrated that the rice cultivation system at GRK was climate-smart in 2011 in a relative sense but failed to maintain in the following years. Resilience was high and changed little for three year. However, the apparent competing goals or trade-offs between productivity and GHG mitigation were found within individual years as well as between the years, causing difficulties in achieving the triple-win scenario. The pursuit of CSA requires for stakeholders to prioritize their goals (i.e., governance) and to practice opportune interventions (i.e., management) based on the feedback from real-time assessment of the CSA indicators (i.e., monitoring) - i.e., a purpose-driven visioneering.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1817-1826
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• 2022

After the hydrogen fluoride leak in Gumi in 2012, the government has been systemizing the disaster management system, such as responding to and managing chemical accidents. In particular, the Ministry of the Interior and Safety (MOIS) is in charge of evacuation of residents following chemical accidents based on the Framework Act on Management of Disaster and Safety. In this study, an application plan was presented to support and utilize the decision-making support for evacuation of residents after a chemical accident using the chemical accident investigation equipment of the National Disaster Management Research Institute (NDMI). In the equipment operation system for scientific information collection due to chemical accidents, the roles and purpose of use of long/short distance measurement equipment were presented according to regular and emergency situations. Using the data acquired through long/short distance measurement equipment, it can be used as basic data for resident evacuation decision-making by monitoring whether chemicals are detected in an emergency and managing data on detected substances by company in a regular situation. As a result of measuring chemical substances in order to verify on-site usability by equipment only for the regular operation system, it was confirmed that real-time detection of chemical substances is possible with long distance measuring equipment. In addition, it was confirmed that it was necessary to check the measurable distance and range of the equipment in the future. In the case of short distance measurement equipment, hydrocarbon-based substances were mainly detected, and it was confirmed that it was measured at a higher level in Ulsan-Mipo National Industrial Complex than in Onsan National Industrial Complex. It is expected that it can be used as basic data to support decision-making in the event of chemical accidents through continuous data construction in the future.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1827-1836
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• 2022

Disasters that occur unexpectedly are difficult to predict. In addition, the scale and damage are increasing compared to the past. Sometimes one disaster can develop into another disaster. Among the four stages of disaster management, search and rescue are carried out in the response stage when an emergency occurs. Therefore, personnel such as firefighters who are put into the scene are put in at a lot of risk. In this respect, in the initial response process at the disaster site, robots are a technology with high potential to reduce damage to human life and property. In addition, Light Detection And Ranging (LiDAR) can acquire a relatively wide range of 3D information using a laser. Due to its high accuracy and precision, it is a very useful sensor when considering the characteristics of a disaster site. Therefore, in this study, development and experiments were conducted so that the robot could perform real-time monitoring at the disaster site. Multi-sensor module was developed by combining LiDAR, Inertial Measurement Unit (IMU) sensor, and computing board. Then, this module was mounted on the robot, and a customized Simultaneous Localization and Mapping (SLAM) algorithm was developed. A method for stably mounting a multi-sensor module to a robot to maintain optimal accuracy at disaster sites was studied. And to check the performance of the module, SLAM was tested inside the disaster building, and various SLAM algorithms and distance comparisons were performed. As a result, PackSLAM developed in this study showed lower error compared to other algorithms, showing the possibility of application in disaster sites. In the future, in order to further enhance usability at disaster sites, various experiments will be conducted by establishing a rough terrain environment with many obstacles.

• Tunnel and Underground Space
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• v.32 no.5
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• pp.285-297
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• 2022

We report results of Extended Leak-Off Test (XLOT) conducted in a large diameter borehole, which is drilled for installation of deep borehole geophysical monitoring system to monitor micro-earthquakes and fault behavior of major fault zones in the southeastern Korean Peninsula. The borehole was planned to secure a final diameter of 200 mm (or more) at a depth of ~1 km, with 12" diameter wellbore to intermediate depths, and 7-7/8" (~200 mm) to the bottom hole depth. We drilled first the 12" borehole to approximately 504 m deep and installed American Petroleum Institute standard 8-5/8" casing, then annulus between the casing and bedrock was fully cemented. XLOT was carried out for several purposes such as confirming casing and cementing integrity, measuring rock stress states. To that end, we drilled additional 4 m long open hole interval to directly inject water and pressurize into the rock mass using the upper API casings. During the XLOT, flow rates and interval pressures were recorded in real time. Based on the logs we tried to analyze hydraulic conductivity of the test interval.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.