• Earthquakes and Structures
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• v.15 no.3
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• pp.253-261
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• 2018

This article details a bridge-specific fragility method developed to enhance the seismic design and resilience of bridges. Current seismic design processes provide guidance for the design of a bridge that will not collapse during a design hazard event. However, they do not provide performance information of the bridge at different hazard levels or due to design changes. Therefore, there is a need for a supplement to this design process that will provide statistical information on the performance of a bridge, beyond traditional emphases on collapse prevention. This article proposes a bridge-specific parameterized fragility method to enable efficient estimation of various levels of damage probability for alternative bridge design parameters. A multi-parameter demand model is developed to incorporate bridge design details directly in the fragility estimation. Monte Carlo simulation and Logistic regression are used to determine the fragility of the bridge or bridge component. The resulting parameterized fragility model offers a basis for a bridge-specific design tool to explore the influence of design parameter variation on the expected performance of a bridge. When used as part of the design process, these tools can help to transform a prescriptive approach into a more performance-based approach, efficiently providing probabilistic performance information about a new bridge design. An example of the method and resulting fragility estimation is presented.

• Earthquakes and Structures
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• v.13 no.3
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• pp.289-297
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• 2017

This paper presents seismic performance and reliability evaluation on steel-timber hybrid shear wall systems composed of steel moment resisting frames and infill light frame wood shear walls. Based on experimental observations, damage assessment was conducted to determine the appropriate damage-related performance objectives for the hybrid shear wall systems. Incremental time-history dynamic analyses were conducted to establish a database of seismic responses for the hybrid systems with various structural configurations. The associated reliability indices and failure probabilities were calculated by two reliability methods (i.e., fragility analysis and response surface method). Both methods yielded similar estimations of failure probabilities. This study indicated the greatly improved seismic performance of the steel-timber hybrid shear wall systems with stronger infill wood shear walls. From a probabilistic perspective, the presented results give some insights on quantifying the seismic performance of the hybrid system under different seismic hazard levels. The reliability-based approaches also serve as efficient tools to assess the performance-based seismic design methodology and calibration of relative code provisions for the proposed steel-timber hybrid shear wall systems.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.6
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• pp.1331-1345
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• 2017

Binary instrumentation has been developed for monitoring and debugging executables without their source codes. Previous efforts on the binary instrumentation are mainly focused on its capability and accuracy, but not on efficiency for practical application. In particular, criteria and measurement methodologies for evaluating and comparing the efficiency of binary investigation tools and algorithms do not estimated yet. In this paper, we propose the instrumentation primitives which are a unit functionality and measurement methodology. Through the empirical experiments by adopting the proposed methodology on DynamoRIO and Pin, we show the feasibility of the proposal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.769-770
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• 2011

This paper presented a method constructing the ITSoC(Information Technology System-on-Chip). In order to implement the ITSoC, designers are increasing relying on reuse of intellectual property(IP) blocks. Since IP blocks are pre-designed and pre-verified, the designer can concentrate on the complete system without having to worry about the correctness or performance of the individual components. Also, embedded core in an ITSoC access mechanisms are required to test them at the system level. That is the goal, in theory. In practice, assembling an ITSoC using IP blocks is still an error-prone, labor-intensive and time-consuming process. This paper discuss the main challenge in ITSoC designs using IP blocks and elaborates on the methodology and tools being put in place for addressing the problem. It explains ITSoC architecture and gives algorithmic details on the high-level tools being developed for ITSoC design.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.145-150
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• 2010

The paper is describing work being developed in the frame of a 5-year IAEA Coordinated Research Programme (CRP) started in late 2005. Participants gained knowledge of modelling methodologies and experience in the development and use of rather sophisticated simulation tools in support of site characterization and performance assessment calculations. These goals were achieved by a coordinated effort, in which the advantages and limitations of numerical models are examined and demonstrated through a comparative analysis of simplified, illustrative test cases. This knowledge and experience should help them address these issues in their own country's nuclear waste program. Coordination efforts during the first three years of the project aimed at enabling this transfer of expertise and maximizing the learning experience of the participants as a group. This was accomplished by identifying common interests of the participants (i.e., Process Modelling and Total System Performance Assessment methodology), and by defining complementary tasks that are solved by the members. Synthesis of all available results by comparative assessments is planned in the coming months. The project will be completed end of 2010. This paper is summarizing activities up to November 2009.

• The Journal of the Korea Contents Association
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• v.11 no.2
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• pp.113-125
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• 2011

We introduce a media art contents authoring tool called ECAS(Exhibition Contents Authoring System), and methodology employed in its development. ECAS was developed using the graphical user interface to overcome difficulties with existing authoring tools that are text-based. For efficient implementation of graphical user interface, GMF(Graphical Modeling Framework) technique by Eclipse was used. SWT(Standard Widget Toolkit) and JIT(Just-In-Time) were used to improve speed and performance of ECAS. We show convenience and efficiency of ECAS by comparing with existing media art contents authoring tools.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1995.11a
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• pp.51-58
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• 1995

The importance of the risk analysis tool has been recognized and its use also has been emphasized by a number of researchers recently The methodology were examined but neither algorithms nor practical applications have been implemented or practiced in Korea. In this paper, the architecture of the Buddy System, one of the automated risk assessment tools. is analyzed in depth to provide the algorithmic understanding and to promote the development of the risk analysis methodology. The Buddy System mainly uses three main factors of vulnerability, threat and countermeasures as a nucleus of the qualatative analysis with the modified loss expectancy value. These factors are identified and assessed by the separation of duties between the end user and security analyst. The Buddy System uses five axioms as its bases of assessment algorithm and the assessed vulnerability level is strictly within these axioms. Since the In-place countermeasures reduce the vulnerability level up to a certain level. the security analyst may use "what if " model to examine the impact of additional countermeasures by proposing each to reduce the vulnerability level further to within the acceptable range. The emphasis on the qualitative approach on vulnerability leveling is very well balanced with the quantitative analysis that the system performance is prominent.prominent.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.698-701
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• 2004

In many literatures, data mining has been used as a utilization of data warehouse and data collection. The biggest utilizations of data mining are for marketing and researches. This is solely because of the data available for this field is usually in large amount. The usability of the data mining is expandable also to the production process. While the object of research of the data mining in marketing is the customers and products, data mining in the production field is object to the so called 4MlE, man, machine, materials, method (recipe) and environment. All of the elements are important to the production process which determines the quality of the product. Because the final aim of the data mining in production field is the quality of the production, this data mining is commonly recognized as quality data mining. As the variables researched in quality data mining can be hundreds or more, it could take a long time to reveal the information from the data warehouse. Feature selection methodology is proposed to help the research take the best performance in a relatively short time. The usage of available simple statistical tools in this method can help the speed of the mining.

• Journal of Energy Engineering
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• v.29 no.1
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• pp.25-33
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• 2020

Recently, as the mandatory policy of zero energy building is promoted, policies / systems for transition to Zero Energy School are being promoted, but there is no method to systematically analyze and verify the results of energy saving activities for school buildings. For the study of energy performance verification methodology, the current status of related standards was referred to, and the case study of other methodologies was conducted to examine the tools that can analyze the performance in the field. In addition, this study analyzed the current status and characteristics of energy management through domestic school visits. In this paper, we presented various energy saving projects such as air conditioning and heating facilities, lighting, insulation, change operation behavior, and improve operation methods in new and existing school buildings, and M & V methods for verifying energy savings before and after implementation of energy conservation projects.