• Earthquakes and Structures
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• v.7 no.4
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• pp.449-462
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• 2014

Seismically induced structural damage, as well as any damage caused by a natural catastrophic event, covers a wide area. This suggests to supervise the event consequences by vision tools. This paper reports the evolution from the results obtained by the project RADATT (RApid Damage Assessment Telematics Tool) funded by the European Commission within FP4. The aim was to supply a rapid and reliable damage detector/estimator for an area where a catastrophic event had occurred. Here, a general open-source methodology for the detection and the estimation of the damage caused by natural catastrophes is developed. The suitable available hazard and vulnerability data and satellite pictures covering the area of interest represent the required bits of information for updated telematics tools able to manage it. As a result the global damage is detected by the simple use of open source software. A case-study to a highly dense agglomerate of buildings is discussed in order to provide the main details of the proposed methodology.

• Journal of Environmental Science International
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• v.25 no.12
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• pp.1653-1660
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• 2016

Drought is a reoccurring worldwide natural hazard that affects not only food production but also economics, health, and infrastructure. Drought monitoring is usually performed with precipitation-based indices without consideration of the actual state and amount of the land surface properties. A drought index based on the actual evapotranspiration can overcome these shortcomings. The severity of a drought can be quantified by making a spatial map. The procedure for estimating actual evapotranspiration is costly and complicated, and requires land surface information. The possibility of utilizing drone-driven remotely sensed data for actual evapotranspiration estimation was analyzed in this study. A drone collected data was used to calculate the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI). The spatial resolution was 10 m with a grid of $404{\times}395$. The collected data were applied and parameterized to an actual evapotranspiration estimation. The result shows that drone-based data is useful for estimating actual evapotranspiration and the corresponding drought indices.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.2
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• pp.769-773
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• 2013

Background: A literature review on 1,104,269 cancer patients concluded that the prevalence of multiple primary malignancies (MPM) is between 0.73% and 11.7%. MPMs seem to have higher incidence than that influenced by hazard only. The purpose of this study was to investigate clinically useful information for effective screening for synchronous and metachronous second primary cancers and to identify a potential surveillance protocol. Materials and Methods: Using statistical and epidemiological indicators we evaluated the patients with MPMs (double locations) admitted to Dr. Abdurrahman Yurtarslan Ankara Oncology Education and Research Hospital between 1981 and 2010. Results: Out of the 130 cases, 24 (18.4%) were synchronous while 106 cases (81.6%) were metachronous tumours. Mean interval time from first to second primary cancers was 4.65 years (0-27 years). The most frequent malignant associations were breast-breast, breast-endometrium and breast-ovary. Both primary and secondary tumors tended to be in an advanced stage explained by the low compliance of the patients to follow-up. Conclusions: The possibility that MPMs exist must always be considered during pretreatment evaluation. Screening procedures are especially useful for the early detection of associated tumors, whereas careful monitoring of patients treated for primary cancer and a good communication between patients and medical care teams should ensure early detection of secondary tumors, and subsequent appropriate management.

• Earthquakes and Structures
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• v.18 no.2
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• pp.163-170
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• 2020

Floor acceleration plays a major role in the seismic design of nonstructural components and equipment supported by structures. Large floor acceleration may cause structural damage to or even collapse of buildings. For precision instruments in high-tech factories, even small floor accelerations can cause considerable damage in this study. Six P-wave parameters, namely the peak measurement of acceleration, peak measurement of velocity, peak measurement of displacement, effective predominant period, integral of squared velocity, and cumulative absolute velocity, were estimated from the first 3 s of a vertical ground acceleration time history. Subsequently, a new predictive algorithm was developed, which utilizes the aforementioned parameters with the floor height and fundamental period of the structure as the new inputs of a support vector regression model. Representative earthquakes, which were recorded by the Structure Strong Earthquake Monitoring System of the Central Weather Bureau in Taiwan from 1992 to 2016, were used to construct the support vector regression model for predicting the peak floor acceleration (PFA) of each floor. The results indicated that the accuracy of the predicted PFA, which was defined as a PFA within a one-level difference from the measured PFA on Taiwan's seismic intensity scale, was 96.96%. The proposed system can be integrated into the existing earthquake early warning system to provide complete protection to life and the economy.

• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.495-495
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• 2011

Miniaturized sensors capable of both sensitive and selective real-time monitoring of target analytes are tremendously valuable for various applications ranging from hazard detection to medical diagnostics. The wide-spread use of such sensors is currently limited due to insufficient selectivity for target molecules. We developed selective nanocoatings by combining trinitrotoluene (TNT) receptors bound to conjugated polydiacetylene (PDA) with single-walled carbon nanotube-field effect transistors (SWNT-FET). Selective binding events between TNT molecules and phage display derived TNT receptors were effectively transduced to sensitive SWNT-FET conductance sensors through the PDA coating. The resulting sensors exhibited unprecedented 1 fM sensitivity toward TNT in real time, with excellent selectivity over various similar aromatic compounds. Our biomimetic receptor coating approach may be useful for the development of sensitive and selective micro and nanoelectronic sensor devices for various other target analytes.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.707-715
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• 2020

Globalization has led to an increase in foreign banks' penetration. It is argued that the presence of foreign banks may affect the banking sector of the host countries in several ways including their competition level. It is mentioned that the presence of the foreign banks could heightened the level of competition in the banking sector. Nonetheless, the impact of the foreign banks on competition could be influenced by the degree of information sharing in the banking industry. This study investigates the role of information sharing in moderating the impact of foreign bank penetration on host banking sector competition in selected developing countries. We employ panel data samples of 54 developing countries during the period from 1998 to 2016. The estimation is carried out using the two-step system of the Generalized Method of Moments (GMM) regression technique. This technique is adopted due to its robustness to all forms of endogeneity. The findings of this study show that the presence of information sharing could affect the relationship between foreign banks' penetration and competition. They suggest that improvement in information sharing by a host country may help foreign banks to improve monitoring and reduce the moral hazard and adverse selection problem.

• Journal of Convergence Society for SMB
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• v.4 no.4
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• pp.31-36
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• 2014

Recent advancement in Wireless Sensor Networks (WSNs) has paved the way for WSNs to enable in various environments in monitoring temperature, motion, sound, and vibration. These applications often include the detection of sensitive information from enemy movements in hostile areas or in locations of personnel in buildings. Due to characteristics of WSNs and dealing with sensitive information, wireless sensor nodes tend to be exposed to the enemy or in a hazard area, and security is a major concern in WSNs. Because WSNs pose unique challenges, traditional security techniques used in conventional networks cannot be applied directly, many researchers have developed various security protocols to fit into WSNs. To develop countermeasures of various attacks in WSNs, descriptions and analysis of current security attacks in the network layers must be developed by using a standard notation. However, there is no research paper describing and analyzing security models in WSNs by using a standard notation such as The Unified Modeling Language (UML). Using the UML helps security developers to understand security attacks and design secure WSNs. In this research, we provide standard models for security attacks by UML Sequence Diagrams to describe and analyze possible attacks in the three network layers.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.101-106
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• 2006

The geoidal undulations are needed for determining the orthometric heights from the Global Positioning System GPS-derived ellipsoidal heights. There are several methods for geoidal undulation determination. The paper presents a method employing a simple architecture Two Layer Multiquadric-Biharmonic Artificial Neural Network (TLMB-ANN) to approximate an area of 4200 square kilometres quasigeoid surface with GPS-levelling data. Hardy’s Multiquadric-Biharmonic functions is used as the hidden layer neurons’ activation function and Levenberg-Marquardt algorithm is used to train the artificial neural network. In numerical examples five surfaces were compared: the gravimetric geometry hybrid quasigeoid, Support Vector Machine (SVM) model, Hybrid Fuzzy Neural Network (HFNN) model, Traditional Three Layer Artificial Neural Network (ANN) with tanh activation function and TLMB-ANN surface approximation. The effectiveness of TLMB-ANN surface approximation depends on the number of control points. If the number of well-distributed control points is sufficiently large, the results are similar with those obtained by gravity and geometry hybrid method. Importantly, TLMB-ANN surface approximation model possesses good extrapolation performance with high precision.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.369-372
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• 2008

Recently, landslides have frequently occurred on natural slopes during periods of intense rainfall. With a rapidly increasing population on or near steep terrain in Korea, 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 prediction methods have been developed in the world. In this study, a simple landslide prediction system that enables people to escape the endangered area is introduced. The system is focused to debris flows which happen frequently during periods of intense rainfall. The system is based on the wireless sensor network (WSN) that is composed of sensor nodes, gateway, and server system. Sensor nodes comprising a sensing part and a communication part are developed to detect ground movement. Sensing part is designed to measure inclination angle and acceleration accurately, and communication part is deployed with Bluetooth (IEEE 802.15.1) module to transmit the data to the gateway. To verify the feasibility of this landslide prediction system, a series of experimental studies was performed at a small-scale earth slope equipped with an artificial rainfall dropping device. It is found that sensing nodes installed at slope can detect the ground motion when the slope starts to move. It is expected that the landslide prediction system by wireless senor network can provide early warnings when landslides such as debris flow occurs.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.405-408
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• 2008

Up to now, a lot of houses, roads and other urban facilities have been damaged by natural disasters such as flash floods and landslides. It is reported that the size and frequency of disasters are growing greatly due to global warming. In order to mitigate such disaster, flood forecasting and alerting systems have been developed for the Han river, Geum river, Nak-dong river and Young-san river. These systems, however, do not help small municipal departments cope with the threat of flood. In this study, a real-time urban flood forecasting service (U-FFS) is developed for ubiquitous computing city which includes small river basins. A test bed is deployed at Tan-cheon in Gyeonggido to verify U-FFS. It is found that U-FFS can forecast the water level of outlet of river basin and provide real-time data through internet during heavy rain. Furthermore, it is expected that U-FFS presented in this study can be applied to ubiquitous computing city (u-City) and/or other cities which have suffered from flood damage for a long time.