• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.137-142
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• 2008

In this paper, we apply a logistic regression model to the data of snow damage on sugi (Cryptomeria japonica) occurred in Toyama prefecture (in Japan) in 2004 for estimating the risk probability. In order to specify the factors effecting snow damage, we apply a model selection procedure determining optimal subset of explanatory variables. In this process we consider the following 3 information criteria, 1) Akaike's information criterion, 2) Baysian information criterion, 3) Bias-corrected Akaike's information criterion. For the selected variables, we give a proper interpretation from the viewpoint of natural disaster.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.32.6-32
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• 2002

The damage localization of the structural system using the natural frequency measurement only is proposed. The existing methods use the changes of mode shape, strain mode shape or curvature mode shape before and after the damage occurrence as these shapes carry the geometric information of the structure. Basically, the change of natural frequencies of the structure can be used as the indicator of the damage occurrence but not as the indicator of the damage location as the natural frequency changes does not carry the geometric information of the structure. In this research, the feedback scope method that measures the natural frequency changes of the structure with and without the feedback Ioo...

• Smart Structures and Systems
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• v.5 no.6
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• pp.681-697
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• 2009

Limited, noisy data in vibration testing is a hindrance to the development of structural damage detection. This paper presents a method for optimizing sensor placement and performing damage detection using finite element model updating. Sensitivity analysis of the modal flexibility matrix determines the optimal sensor locations for collecting information on structural damage. The optimal sensor locations require the instrumentation of only a limited number of degrees of freedom. Using noisy modal data from only these limited sensor locations, a method based on model updating and changes in the flexibility matrix successfully determines the location and severity of the imposed damage in numerical simulations. In addition, a steel cantilever beam experiment performed in the laboratory that considered the effects of model error and noise tested the validity of the method. The results show that the proposed approach effectively and robustly detects structural damage using limited, optimal sensor information.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.103-111
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• 2017

Recently, new variants of Ransomware are becoming a new security issue. Ransomware continues to evolve to avoid network of security solutions and extort users' information to demand Bitcoin using social engineering technique. Ransomware is damaging to users not only in Korea but also in all around the world. In this thesis, it will present research solution to prevent and cope from damage by new variants Ransomware, by studying on the types and damage cases of Ransomware that cause social problems. Ransomware which introduced in this paper, is the most issued malicious code in 2016, so it will evolve to a new and more powerful Ransomware which security officers cannot predict to gain profit. In this thesis, it proposes 4 methods to prevent the damage from the new variants of Ransomware to minimize the damage and infection from Ransomware. Most importantly, if user infected from Ransomware, it is very hard to recover. Thus, it is important that users understand the basic security rules and effort to prevent them from infection.

• Computers and Concrete
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• v.20 no.5
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• pp.563-572
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• 2017

Ordinary reinforced concrete (RC) and prestressed concrete bridges are two popular and typical types of short- and medium-span bridges that accounts for the vast majority of all existing bridges. The cost of maintaining, repairing or replacing degraded existing RC bridges is immense. Detecting the abnormality of RC bridges at an early stage and taking the protective measures in advance are effective ways to improve maintenance practices and reduce the maintenance cost. This study proposes a systematic method from influence line (IL) identification to damage detection with applications to RC bridges. An IL identification method which integrates the cubic B-spline function with Tikhonov regularization is first proposed based on the vehicle information and the corresponding moving vehicle induced bridge response time history. Subsequently, IL change is defined as a damage index for bridge damage detection, and information fusion technique that synthesizes ILs of multiple locations/sensors is used to improve the efficiency and accuracy of damage localization. Finally, the feasibility of the proposed systematic method is verified through experimental tests on a three-span continuous RC beam. The comparison suggests that the identified ILs can well match with the baseline ILs, and it demonstrates that the proposed IL identification method has a high accuracy and a great potential in engineering applications. Results in this case indicate that deflection ILs are superior than strain ILs for damage detection of RC beams, and the performance of damage localization can be significantly improved with the information fusion of multiple ILs.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.3-5
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• 2008

An increase in oil and gas plants caused by development of process industry have brought into the increase in use of flammable and toxic materials in the complex process under high temperature and pressure. There is always possibility of fire and explosion of dangerous chemicals, which exist as raw materials, intermediates, and finished goods whether used or stored in the industrial plants. Since there is the need of efforts on disaster damage reduction or mitigation process, we have been conducting a research to relate explosion model on the background of real 3D terrain model. By predicting the extent of damage caused by recent disasters, we will be able to improve efficiency of recovery and, sure, to take preventive measure and emergency counterplan in response to unprepared disaster. For disaster damage prediction, it is general to conduct quantitative risk assessment, using engineering model for environmental description of the target area. There are different engineering models, according to type of disaster, to be used for industry disaster such as UVCE (Unconfined Vapour Cloud Explosion), BLEVE (Boiling Liquid Evaporation Vapour Explosion), Fireball and so on, among them, we estimate explosion damage through UVCE model which is used in the event of explosion of high frequency and severe damage. When flammable gas in a tank is released to the air, firing it brings about explosion, then we can assess the effect of explosion. As 3D terrain information data is utilized to predict and estimate the extent of damage for each human and material. 3D terrain data with synthetic environment (SEDRIS) gives us more accurate damage prediction for industrial disaster and this research will show appropriate prediction results.

• Earthquakes and Structures
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• v.23 no.1
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• pp.1-11
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• 2022

This study implements a hybrid Genetic Algorithm to detect, locate, and quantify structural damage for multistory shear buildings using partial modal data. Measuring modal responses at multiple locations on a structure is both challenging and expensive in practice. The proposed method's objective function is based on the building's dynamic properties and can also be employed with partial modal information. This method includes initial residuals between the numerical and experimental model and a damage penalization term to avoid false damages. To test the proposed method, a numerical example of a ten-story shear building with noisy and partial modal information was explored. The obtained results were in agreement with the previously published research. The proposed method's performance was also verified using experimental modal data of an 8-DOF spring-mass system and a five-story shear building. The predicted results for numerical and experimental examples indicated that the proposed method is reliable in identifying the damage for multistory shear buildings.

• Journal of KIBIM
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• v.13 no.4
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• pp.64-73
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• 2023

This study introduces a method of estimating the 3D coordinates of structural damage from the detection results of visual inspection provided in 2D image coordinates using sensing data of UAV and 3D shape information of BIM. This estimation process takes place in a virtual space and utilizes the BIM model, so it is possible to immediately identify which member of the structure the estimated location corresponds to. Difference from conventional structural damage localization methods that require 3D scanning or additional sensor attachment, it is a method that can be applied locally and rapidly. Measurement accuracy was calculated through the distance difference between the measured position measured by TLS (Terrestrial Laser Scanner) and the estimated position calculated by the method proposed in this study, which can determine the applicability of this study and the direction of future research.

• Convergence Security Journal
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• v.14 no.5
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• pp.31-36
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• 2014

As security management center of financial area, financial ISAC monitors financial corporations and provides security services. Financial ISAC minimizes damage by responding quickly to external attack such as hacking, virus but it is poor at handling internal attack. For the efficient management and stable operation of information source, also to respond jointly to online hacking, the necessity of information sharing system increases day by day in and outside country. This paper proposes financial ISAC that can prevent a secondary damage of leakage information as well as providing security services. The proposed financial ISAC provides new password to financial corporation in which the same ID and password as leakage information are used and in case of financial information leakage it warns customers against phishing etc.

• Earthquakes and Structures
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• v.3 no.2
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• pp.117-140
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• 2012

The proposed research includes a comprehensive study on the seismic vulnerability assessment of typical building types, representative of the structural materials, the seismic codes and the construction techniques of Southern Europe. A damage database is created after the elaboration of the results of the observational data obtained from post-earthquake surveys carried out in the area struck by the September 7, 1999 Athens earthquake, a near field seismic event in an extended urban region. The observational database comprises 180.945 buildings which developed damage of varying degree, type and extent. The dataset is elaborated in order to gather useful information about the structural parameters influence on the seismic vulnerability and their correlation to the type and degree of building damages in near field earthquakes. The damage calibration of the observational data was based on label - damage provided by Earthquake Planning and Protection Organization (EPPO) in Greece and referred to the qualitative characterization for the recording of damage in post-earthquake surveys. Important conclusions are drawn on the parameters that influence the seismic response based on the wide homogeneous database which adds to the reliability of the collected information and reduces the scatter on the produced results.