• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.335-346
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• 2016

This study produced the parameter maps of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall generation model across South Korea and developed and validated the web application that automates the process of rainfall generation based on the produced parameter maps. To achieve this purpose, three deferent sets of parameters of the MBLRP model were estimated at 62 ground gage locations in South Korea depending on the distinct purpose of the synthetic rainfall time series to be used in hydrologic modeling (i.e. flood modeling, runoff modeling, and general purpose). The estimated parameters were spatially interpolated using the Ordinary Kriging method to produce the parameter maps across South Korea. Then, a web application has been developed to automate the process of synthetic rainfall generation based on the parameter maps. For validation, the synthetic rainfall time series has been created using the web application and then various rainfall statistics including mean, variance, autocorrelation, probability of zero rainfall, extreme rainfall, extreme flood, and runoff depth were calculated, then these values were compared to the ones based on the observed rainfall time series. The mean, variance, autocorrelation, and probability of zero rainfall of the synthetic rainfall were similar to the ones of the observed rainfall while the extreme rainfall and extreme flood value were smaller than the ones derived from the observed rainfall by the degree of 16%-40%. Lastly, the web application developed in this study automates the entire process of synthetic rainfall generation, so we expect the application to be used in a variety of hydrologic analysis needing rainfall data.

• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.54-63
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• 2006

In this paper we will propose a domain analysis methodology that uses an extended workflow mechanism based on dynamic modeling to solve problems of a traditional domain analysis on legacy systems. This methodology is called WODA(Workflow Oriented Domain Analysis). Following procedures on WODA, we can identify common/uncommon component, and also extract the cluster of components. It will be effectively reusable on developing new systems with these components. With our proposed component testing metrics, we can determine highly reusable component/scenario on identifying possible scenarios of the particular system. We can also recognize most critical/most frequent reusable components and prioritize possible component scenarios of the system. This paper contains one application of UPS that illustrates our autonomous modeling tool, WODA.

• Earthquakes and Structures
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• v.9 no.5
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• pp.957-981
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• 2015

Earthquakes occur as a cluster in many regions around the world where complex fault systems exist. The repeated shaking usually induces accumulative damage to affected structures. Damage accumulation in structural systems increases their level of degradation in stiffness and also reduces their strength. Many existing analytical tools of modeling RC structures lack the salient damage features that account for stiffness and strength degradation resulting from repeated earthquake loading. Therefore, these tools are inadequate to study the response of structures in regions prone to multiple earthquakes hazard. The objective of this paper is twofold: (a) develop a tool that contains appropriate damage features for the numerical analysis of RC structures subjected to more than one earthquake; and (b) conduct a parametric study that investigates the effects of multiple earthquakes on the response of RC moment resisting frame systems. For this purpose, macroscopic constitutive models of concrete and steel materials that contain the aforementioned damage features and are capable of accurately capturing materials degrading behavior, are selected and implemented into fiber-based finite element software. Furthermore, finite element models that utilize the implemented concrete and steel stress-strain hysteresis are developed. The models are then subjected to selected sets of earthquake sequences. The results presented in this study clearly indicate that the response of degrading structural systems is appreciably influenced by strong-motion sequences in a manner that cannot be predicted from simple analysis. It also confirms that the effects of multiple earthquakes on earthquake safety can be very considerable.

• Bulletin of the Korean Chemical Society
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• v.33 no.3
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• pp.869-880
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• 2012

Identification of the selective chemical features for Aurora-B inhibitors gained much attraction in drug discovery for the treatment of cancer. Hence to identify the Aurora-B critical features various techniques were utilized such as pharmacophore generation, virtual screening, homology modeling, molecular dynamics, and docking. Top ten hypotheses were generated for Aurora-B and Aurora-A. Among ten hypotheses, HypoB1 and HypoA1 were selected as a best hypothesis for Aurora-B and Aurora-A based on cluster analysis and ranking score, respectively. Test set result revealed that ring aromatic (RA) group in HypoB1 plays an essential role in differentiates Aurora-B from Aurora-A inhibitors. Hence, HypoB1 used as 3D query in virtual screening of databases and the hits were sorted out by applying drug-like properties and molecular docking. The molecular docking result revealed that 15 hits have shown strong hydrogen bond interactions with Ala157, Glu155, and Lys106. Hence, we proposed that HypoB1 might be a reasonable hypothesis to retrieve the structurally diverse and selective leads from various databases to inhibit Aurora-B.

• Journal of the Korean Society of Safety
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• v.38 no.2
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• pp.87-95
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• 2023

On October 29, 2022, a very large number of people gathered in Itaewondong, Yongsan-gu, Seoul, Korea for a Halloween festival, and as crowds pushed through narrow alleys, 159 deaths and 195 injuries occurred, making it the largest crushing incident in Korea. There have been a number of stampede deaths where crowds gathered at large-scale festivals, event venues, and stadiums, both at home and abroad. When the density increases, the physical contact between bodies becomes very strong, and crowd turbulence occurs when the force of the crowd is suddenly added from one body to another; thus, the force is amplified and causes the crowd to behave like a mass of fluid. When crowd turbulence occurs, people cannot control themselves and are pushed into he crowd. To prevent a stampede accident, investigation and management of areas expected to be crowded and congested must be systematically conducted, and related ministries and local governments are planning to establish a crowd management system to prepare safety management measures to prevent accidents involving multiple crowds. In this study, based on national data, a continuous digital topographic map is modeled in 3D to analyze the risk of crowding and present a plan for selecting high-risk walking routes. Areas with a high risk of crowding are selected in advance based on various data (numerical data, floating population, and regional data) in a realistic and feasible way, and the analysis is based on the visible results from 3D modeling of the risk area. The study demonstrates that it is possible to prepare measures to prevent cluster accidents that can reflect the characteristics of the region.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.129-153
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• 2023

This study was conducted in the context of the Covid-19 pandemic by analyzing a large amount of press report frames regarding the Covid-19 vaccine which is of great public interest, in order to explore the role and direction of trusted media as core elements of crisis communication. The study period lasted for eight months beginning in November 2020 when the development of the Covid-19 vaccine was in progress until June 2021. Set-up as research subjects were the Chosun Ilbo, Joongang Ilbo, Dong-A Ilbo and Hankyoreh according to their public confidence rankings and number of readers.The analysis method used structured topic Modeling (STM) and semantic network analysis. As a result, based on a clear cluster of word structures and a central analysis value, a total of 64 relevant frames, 16 for each news company, were gathered. In the third phase a comparative analysis of the four news companies was carried out to verify the organizational degree of the frames and substantial differences.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.12-19
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• 2020

The clustered heterogeneous wireless sensor network is comprised of sensor nodes and cluster heads, which are hierarchically organized for different objectives. In the network, we should especially take care of managing node resources to enhance network performance based on memory and battery capacity constraints. For instances, if some interesting events occur frequently in the vicinity of particular sensor nodes, those nodes might receive massive amounts of data. Data congestion can happen due to a memory bottleneck or link disconnection at cluster heads because the remaining memory space is filled with those data. In this paper, we utilize drones as mobile sinks to resolve data congestion and model the network, sensor nodes, and cluster heads. We also design a cost function and a congestion indicator to calculate the degree of congestion. Then we propose a data congestion map index and a data congestion mapping scheme to deploy drones at optimal points. Using control variable, we explore the relationship between the degree of congestion and the number of drones to be deployed, as well as the number of drones that must be below a certain degree of congestion and within communication range. Furthermore, we show that our algorithm outperforms previous work by a minimum of 20% in terms of memory overflow.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.781-786
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• 1991

This paper introduces a new methodology for multisensor data fusion. The method makes use of fuzzy techniques and possibility distribution as a fuzzy restriction which acts as an elastic constraint on the values that may be assigned to a variable. We propose a simple sensor fuzzy modeling method which can be used for cluster validity analysis. As a result, the feasibility of these multisensor data fusion modules is demonstrated by computer simulation applicable to the problem of object identification.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.12
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• pp.2157-2164
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• 2010

Microgrid is generally defined as cluster of small distributed generators, energy storages and loads. Through monitoring and coordinated control, microgrid can provide various benefits such as reduction of energy cost, peak shaving and power quality improvement. In design stage of microgrid, system dynamic simulation is necessary for optimizing of sizing and siting of DER(distributed energy resources). As number of the system components increases, simulation time will be longer. This problem can restrict optimal design. So we used simplified modeling on energy sources and average switching model on power converters to reduce simulation time. The effectiveness of this method is verified by applying to prototype microgrid system, which is consist of photovoltaic, wind power, diesel engine generators, battery energy storage system and loads installed in laboratory. Simulation by Matlab/Simulink and measurements on prototype microgrid show that the proposed method can reduce simulation time not sacrificing dynamic characteristics.