• Smart Structures and Systems
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• v.6 no.5_6
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• pp.731-748
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• 2010

Impact detection and health monitoring are very important tasks for civil infrastructures, such as bridges. Piezoceramic based transducers are widely researched for these tasks due to the piezoceramic material's inherent advantages of dual sensing and actuation ability, which enables the active sensing method for structural health monitoring with a network of piezoceramic transducers. Wireless sensor networks, which are easy for deployment, have great potential in health monitoring systems for large civil infrastructures to identify early-age damages. However, most commercial wireless sensor networks are general purpose and may not be optimized for a network of piezoceramic based transducers. Wireless networks of piezoceramic transducers for active sensing have special requirements, such as relatively high sampling rate (at a few-thousand Hz), incorporation of an amplifier for the piezoceramic element for actuation, and low energy consumption for actuation. In this paper, a wireless network is specially designed for piezoceramic transducers to implement impact detection and active sensing for structural health monitoring. A power efficient embedded system is designed to form the wireless sensor network that is capable of high sampling rate. A 32 bit RISC wireless microcontroller is chosen as the main processor. Detailed design of the hardware system and software system of the wireless sensor network is presented in this paper. To verify the functionality of the wireless sensor network, it is deployed on a two-story concrete frame with embedded piezoceramic transducers, and the active sensing property of piezoceramic material is used to detect the damage in the structure. Experimental results show that the wireless sensor network can effectively implement active sensing and impact detection with high sampling rate while maintaining low power consumption by performing offline data processing and minimizing wireless communication.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.262-267
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• 2008

Recently, landslides frequently occur on natural slope and/or man-made cut slope during periods of intense rainfall. With a rapidly increasing population on or near steep terrain, landslides have become one of the most significant natural hazards. Thus, it is necessary to protect people from landslides and to minimize the damage of houses, roads and other facilities. To accomplish this goal, many landslide monitoring systems have been developed throughout the world. In this paper, a simple landslide detection system that enables people to escape the endangered area is introduced. The system is focused on the debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of wireless sensor nodes, gateway, and remote server system. Wireless sensor nodes and gateway are deployed by commercially available Microstrain G-Link products. Five wireless sensor nodes and one gateway are installed at the test slope for detecting ground movement. The acceleration and inclination data of test slope can be obtained, which provides a potential to detect landslide. In addition, thresholds to determine whether the test slope is stable or not are suggested by a series of numerical simulations, using geotechnical analysis software package. It is obtained that the alarm should be issued if the x-direction displacement of sensor node is greater than 20mili-meters and the inclination of sensor node is greater than 3 degrees. It is expected that the landslide detection method using wireless senor network can provide early warning where landslides are prone to occur.

• Journal of Environmental Health Sciences
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• v.48 no.1
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• pp.1-8
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• 2022

Objectives: The purpose of this study is to reveal the circumstances under which the cases of harm to health caused by humidifier disinfectant were neglected and show the points where the number of victims and the degree of damage could have been reduced. In addition, it attempts to describe how damage management proceeded immediately after the incident and actually exacerbated the damage. Finally, it explores the unfortunate aspects of the recent trial. By doing so, it attempts to take this as an opportunity to consider whether a tragic event such as the humidifier disinfectant incident could occur in the future. Methods: This study collected and analyzed data on chemical material characteristics related to humidifier disinfectants, data on health effect characteristics, data on related laws and regulations from the Ministry of Environment, data related to the damage investigation by the Korea Environmental Industry and Technology Institute, and current contents. Results: The lack of related systems and laws is the area where the greatest responsibility for the cause of the humidifier disinfectant disaster falls, so it is difficult for the government to escape this responsibility. Establishing a dedicated department to identify the prevalence of certain diseases within the functions of the Health Insurance Review and Assessment Service to monitor health can greatly contribute to the prevention and management of diseases through early detection and management of group outbreaks caused by harmful factors. Humidifier disinfectant damage relief should have been expanded earlier beyond HDLI (humidifier disinfectant lung injury) to include non-specific diseases such as asthma, pneumonia, and interstitial pneumonia. The scope of relief benefits should have also been expanded earlier to include the payment of disability benefits. Fortunately, with the 2020 revision of the Special Act, the conditions for estimating causal relations were eased and individual screening systems such as health impact assessment were reorganized along with the introduction of a rapid screening system. Conclusions: The management system for chemical substances in a country is clearly of paramount importance, and the ministry in charge must have a response system in case of damage to health effects. Administration that looks at the victims' situation from their point of view is needed, and technical countermeasures are required to quickly recognize the prevalence of certain diseases.

• Proceedings of the KSRS Conference
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• v.2
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• pp.827-830
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• 2006

The tsunami from the megathrust earthquake magnitude 9.3 on 26 December 2004 is the largest tsunami the world has known in over forty years. This tsunami destructively attacked 13 countries around Indian Ocean with at least 230,000 fatalities, displaced people 2,089,883 and 1.5 million people who lost their livelihoods. The ratio of women and children killed to men is 3 to 1. The total damage costs US$ 10.73 billion and rebuilding costs US$ 10.375 billion. The tsunami's death toll could have been drastically reduced, if the warning was disseminated quickly and effectively to the coastal dwellers along the Indian Ocean rim. With a warning system in Indian Ocean similar to that operating in the Pacific Ocean since 1965, it would have been possible to warn, evacuate and save countless lives. The best tribute we can pay to all who perished or suffered in this disaster is to heed its powerful lessons. UNESCO/IOC have put their tremendous effort on better disaster preparedness, functional early warning systems and realistic arrangements to cope with tsunami disaster. They organized ICG/IOTWS (Indian Ocean Tsunami Warning System) and the third of this meeting is held in Bali, Indonesia during $31^{st}$ July to $4^{th}$ August 2006. A US$ 53 million interim warning system using tidal gauges and undersea sensors is nearing completion in the Indian Ocean with the assistance from IOC. The tsunami warning depends strictly on an early detection of a tsunami (wave) perturbation in the ocean itself. It does not and cannot depend on seismological information alone. In the case of 26 December 2004 tsunami when the NOAA/PMEL DART (Deep-ocean Assessment and Reporting of Tsunami) system has not been deployed, the initialized input of sea surface perturbation for the MOST (Method Of Splitting Tsunami) model was from the tsunamigenic-earthquake source model. It is the first time that the satellite altimeters can detect the signal of tsunami wave in the Bay of Bengal and was used to validate the output from the MOST model in the deep ocean. In the case of Thailand, the inundation part of the MOST model was run from Sumatra 2004 for inundation mapping purposes. The medium and high resolution satellite data were used to assess the degree of the damage from Indian Ocean tsunami of 2004 with NDVI classification at 6 provinces on the Andaman seacoast of Thailand. With the tide-gauge station data, run-up surveys, bathymetry and coastal topography data and land-use classification from satellite imageries, we can use these information for coastal zone management on evacuation plan and construction code.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.507-516
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• 2019

Costs invested in road maintenance and road development are on the rise. However, due to accidents such as portholes and ground subsidence, the risks to the drivers' safety and the material damage caused by accidents are also increasing. Following this trend, we have developed a system that determines road damage, according to the magnitude of vibration generated without directly intervening the driver when driving. In this paper, we implemented the system using a remote control car (RC car) simulator due to the limitation of the environment in which the actual vehicle is not available in the process of developing the system. In addition, we attached a vibration sensor and GPS sensor to the body of the RC car simulator to measure the vibration value and location information generated by the movement of the vehicle in real-time while driving, and transmitting the corresponding data to the server. In this way, we implemented a system that allows external users to check the damage of roads and the maintenance of the repaired roads based on data more easily than the existing systems. By using this system, we can perform early prediction of road breakage and pattern prediction based on the data. Further, for the RC car simulator, commercialization will be possible by combining it with business in other fields that require flatness.

• Journal of Industrial Convergence
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• v.21 no.12
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• pp.55-62
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• 2023

Recent ransomware attacks employ various techniques and pathways, posing significant challenges in early detection and defense. Consequently, the scale of damage is continually growing. This paper introduces a machine learning-based approach for effective ransomware detection by focusing on file encryption and encryption patterns, which are pivotal functionalities utilized by ransomware. Ransomware is identified by analyzing password behavior and encryption patterns, making it possible to detect specific ransomware variants and new types of ransomware, thereby mitigating ransomware attacks effectively. The proposed machine learning-based encryption behavior detection technique extracts encryption and encryption pattern characteristics and trains them using a machine learning classifier. The final outcome is an ensemble of results from two classifiers. The classifier plays a key role in determining the presence or absence of ransomware, leading to enhanced accuracy. The proposed technique is implemented using the numpy, pandas, and Python's Scikit-Learn library. Evaluation indicators reveal an average accuracy of 94%, precision of 95%, recall rate of 93%, and an F1 score of 95%. These performance results validate the feasibility of ransomware detection through encryption behavior analysis, and further research is encouraged to enhance the technique for proactive ransomware detection.

• Childhood Kidney Diseases
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• v.7 no.2
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• pp.189-196
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• 2003

Purpose : Ureteral duplication is a common urologic anomaly and early diagnosis may prevent irreversible renal damage. We thus aimed to evaluate the benefits of prenatal sonography in early detection. Methods : We retrospectively studied 55 children with duplicated systems who were admitted to Severance Hospital, Yonsei University, Seoul, Korea from January 1998 to July 2003. Results : The mean age at diagnosis was 2.3 years old. 89% of the children had complete duplicated ureter. 47% of the children visited the hospital with an initial complaint of abnormal prenatal sonographic findings. Among these patients, 70.8% had DMSA defects. The mean differential renal function(DRF) in the DMSA scan was 48.2% in the group diagnosed prenatally. In the postnatally-diagnosed group, DMSA defects were found in 67.7% patients and the mean DRF was 45.5%. Conclusion : In comparison with the past studies, the mean age at diagnosis is becoming younger, and the proportion of abnormal prenatal sonography as an initial complaint larger. Other clinical manifestations were similar. The difference of the renal damage between the prenatally diagnosed group and the postnatally diagnosed group was not statistically significant. A multi-center study may help to prove the importance of prenatal sonography in early diagnosis and treatment of ureteral duplication. (J Korean Soc Pediatr Nephrol 2003;7:189-196)

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.689-693
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• 2023

Domestic bridges with a service life of more than 30 years are expected to account for approximately 54% of all bridges within the next 10 years. As bridges rapidly deteriorate, it is necessary to establish an appropriate maintenance plan. Recent domestic and international research have focused on the integration of BIM to digitize bridge maintenance information and then enhance accessibility and usability of the information. Accordingly, this study developed a BIM-FEM interoperability algorithm for bridge decks to convert maintenance information into data and efficiently manage the history of maintenance. After creating an initial crack BIM based on an exterior damage map, bridge specification and damage information were linked to a numerical analysis that performs damage analysis considering damage scenarios and design loads. The spread of cracks obtained from the analysis results were updated into the BIM. Based on the damage spread information on the BIM, an automated technology was also developed to assess both the current and future condition ratings of the bridge deck. This approach can enable an efficient maintenance of the deck using the history data from bridge inspection and diagnosis as well as future information on cracks and defects. The expected early detection and prevention would ultimately improve the lifespan and safety of bridges.

• Journal of Korean Society of societal Security
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• v.1 no.2
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• pp.61-66
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• 2008

More than 70% of Korea consists of mountainous area and during the construction of roads and railroads many cut-slopes are inevitably formed. A number of environmental factors, such as the rainy season and frost heave during winter/thaw during spring, can result in rock falls and landslides. The failure of slopes is increasing every year and can cause damage to vehicles, personal injury and even fatality. In order to help protect people and property, there is a need for real-time monitoring systems to detect the early stages of slope failures. In this respect, the GMG has been using Translation Rotation Settlement (TRS) sensor units installed on slopes to monitor movement in real-time. However, the data lines of this system are vulnerable and the whole system can be damaged by a single lightning strike. In order to overcome this, GMG have proposed the use of Ubiquitous Sensor Networks (USN). The adoption of a USN system in lieu of data cables can help to minimize the risk of lightning damage and improve the reliability of slope monitoring systems.