• Wind and Structures
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• v.38 no.5
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• pp.355-366
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• 2024

Severe natural multi-hazard events can cause damage to infrastructure and economic losses of billions of dollars. The challenges of modeling these losses include dependency between hazards, cause and sequence of loss, and lack of available data. This paper presents and explores multi-hazard loss modeling in the context of the combined wind and rain vulnerability of mid/high-rise buildings during hurricane events. A component-based probabilistic vulnerability model provides the framework to test and contrast two different approaches to treat the multi-hazards: In one, the wind and rain hazard models are both decoupled from the vulnerability model. In the other, only the wind hazard is decoupled, while the rain hazard model is embedded into the vulnerability model. The paper presents the mathematical and conceptual development of each approach, example outputs from each for the same scenario, and a discussion of weaknesses and strengths of each approach.

• Earthquakes and Structures
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• v.1 no.1
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• pp.109-127
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• 2010

This work aims at introducing structural sensitivity analysis capabilities into existing commercial finite element software codes for the purpose of mapping retrofit strategies for a broad group of structures including heritage-type buildings. More specifically, the first stage sensitivity analysis is implemented for the standard deterministic environment, followed by stochastic structural sensitivity analysis defined for the probabilistic environment in a subsequent, second phase. It is believed that this new generation of software that will be released by the industrial partner will address the needs of a rapidly developing specialty within the engineering design profession, namely commercial retrofit and rehabilitation activities. In congested urban areas, these activities are carried out in reference to a certain percentage of the contemporary building stock that can no longer be demolished to give room for new construction because of economical, historical or cultural reasons. Furthermore, such analysis tools are becoming essential in reference to a new generation of national codes that spell out in detail how retrofit strategies ought to be implemented. More specifically, our work focuses on identifying the minimum-cost intervention on a given structure undergoing retrofit. Finally, an additional factor that arises in earthquake-prone regions across the world is the random nature of seismic activity that further complicates the task of determining the dynamic overstress that is being induced in the building stock and the additional demands placed on the supporting structural system.

• Journal of Soil and Groundwater Environment
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• v.22 no.5
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• pp.30-39
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• 2017

In this study, the predictive toxicity of barley Hordeum vulgare was estimated using a modified terrestrial biotic ligand model (TBLM) to account for the toxic effects of $CuOH^+$ and $CuCO_3(aq)$ generated at pH 7 or higher, and this was compared to that from the original TBLM. At pH values higher than 7, the difference in $EA_{50}\{Cu^{2+}\}$ (half maximal effective activity of $Cu^{2+}$) between the two models increased with increasing pH. As Mg concentration increased from 8.24 to 148 mg/L in the pH range of 5.5 to 8.5, the difference in $EA_{50}\{Cu^{2+}\}$ increased, and it reached its maximum at pH 8. The difference in $EC_{50}[Cu]_T$ (half maximal effective concentration of Cu) between the two models increased as dissolved organic carbon (DOC) concentration increased when pH was above 7. Thus, for soils with alkaline pH, the toxic effect of $CuOH^+$ and $CuCO_3(aq)$ are greater at higher salt and DOC concentrations. The acceptable Cu concentration in soil porewater can be estimated by the modified TBLM through deterministic method at pH levels higher than 7, while combination of TBLM and species sensitivity distribution through the probabilistic method could be utilized at pH levels lower than 7.

• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.95-104
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• 2010

The tap water supply in Korea mainly depends on the surface water. However, the advanced water purification process becomes a necessity due to the deterioration of surface water quality and the risk of accidental spill. High cost of water treatment and public concerns make the decision makers turn to riverbank filtration as an alternative to the surface water. Riverbank filtration has been employed for water supply in many developed countries for more than 150 years. In Korea, riverbank filtration has drawn attention since 1990s as a supply source having potential to stably meet the ever-increasing water demand. Some cities located in the Nakdong River Basin are currently supplying water through riverbank filtration. This work studies the site suitability analysis for riverbank filtration using game theory. Theory of games, which is a branch of applied mathematics used in social sciences (most notably economics), biology, engineering and computer science, was applied to candidate locations for the selection of riverbank filtration site. We proposed a policy game model as a new method adopting a probabilistic approach. The model developed turned out to be an effective tool for site selection.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.140-148
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• 2017

An important factor in determining the design and treatment efficiency of wastewater treatment plants (WWTPs) is the quantity and quality of influent. These detailed and accurate information is essential for process control, diagnosis and operation, as well as the basis in designing the plant, selecting the process and determining the optimal capacity of each bioreactor. Probabilistic models are used to predict the wastewater quantity and quality of WWTPs, which are widely used to improve the design and operation of WWTPs. In this study, the optimal probability distribution of time series influent data was derived for predicting water quantity and quality, and wastewater influent data were generated using the Monte Carlo simulation analysis. In addition, we estimated various alternatives for the improvement of bioreactor operations based on present operation condition using the generated influent data and activated sludge model, and suggested the alternative that can operate the most effectively. Thus, the influent quantity and quality are highly correlated with the actual operation data, so that the actual WWTPs influent characteristics were well reproduced. Using this will improve the operating conditions of WWTPs, and a proposed improvement plan for the current TMS (Tele Monitoring System) effluent quality standards can be made.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.585-594
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• 2009

Efficient filtering is an important factor in RFID system performance. Because of huge volume of tag data in future ubiquitous environment, if RFID readers transmit tag data without filtering to upper-layer applications, which results in a significant system performance degradation. In this paper, we provide an efficient filtering technique which operates on RFID air protocol. RFID air protocol filtering between tags and a reader has some advantages over filtering in readers and middleware, because air protocol filtering reduces the volume of filtering work before readers and middleware start filtering. Exploiting the air protocol filtering advantage, we introduce a geometrical algorithm for generating air protocol filters and verify their performance through simulation with analytical time models. Results of dense RFID reader environment show that air protocol filtering algorithms reduce almost a half of the total filtering time when compared to the results of linear search.

• Journal of the Korean Society of Groundwater Environment
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• v.5 no.2
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• pp.80-87
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• 1998

Since groundwater flow paths have one of the major roles to transport the radioactive nuclides from the radioactive waste repository to the biosphere, the discrete fracture network model is used for the rock block scale flow instead of the porous continuum model. This study aims to construct a three dimensional discrete fracture network to interpret the groundwater flow system in the study site. The modeling work includes the determination of the probabilistic distribution function from the fracture geometric and hydraulic parameters, three dimensional fracture modeling and model calibration. The results of the constant pressure tests performed in a fixed interval length at boreholes indicate that the flow dimension around boreholes shows mainly radial to spherical flow pattern. The fracture transmissivity value calculated by Cubic law is 6.12${\times}$10$\^$-7/ ㎡/sec with lognormal distribution. The conductive fracture intensity estimated by FracMan code is 1.73. Based on this intensity, the total number of conductive fractures are obtained as 3,080 in the rock block of 100 m${\times}$100 m${\times}$100 m.

• Journal of KIISE:Software and Applications
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• v.34 no.6
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• pp.549-561
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• 2007

Vision-based scene understanding is to infer and interpret the context of a scene based on the evidences by analyzing the images. A probabilistic approach using Bayesian networks is actively researched, which is favorable for modeling and inferencing cause-and-effects. However, it is difficult to gather meaningful evidences sufficiently and design the model by human because the real situations are dynamic and uncertain. In this paper, we propose a learning method of Bayesian network that reduces the computational complexity and enhances the accuracy by searching an efficient BN structure in spite of insufficient evidences and training data. This method represents the domain knowledge as ontology and builds an efficient hierarchical BN structure under constraint rules that come from the ontology. To evaluate the proposed method, we have collected 90 images in nine types of circumstances. The result of experiments indicates that the proposed method shows good performance in the uncertain environment in spite of few evidences and it takes less time to learn.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.907-912
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• 2007

The present level of ubiquitous computing technology have developed to the point where Home-server provides services that user require directly for user in the intelligent space. But it will need intelligent system to provides more active services for user in the near future. In this paper, we define the environment information about situation that user is in as Context, and collect the Context that stereotype as 4W1H form for construct the system that can decision service will be provide from information about a situation that user is in, without user's involvement. Additionally we collect information about user's emotional state, use these informations as nodes of Bayesian network for probabilistic reasoning. From that, we materialize Context Awareness system about it that what kind of situation user is in. And, we propose the Context-based Service reasoning model using Bayesian Network from the result of Context Awareness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.9
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• pp.606-613
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• 2014

The Internet of Things (IoT), which has recently attracted attention as next-generation IT industry, is based on a wired and wireless network platform that can connect various Things. However, it is challenging to implement the IoT platform because of the heterogeneity of the network. Particularly, the ZigBee transmission may be significantly harmed due to Wi-Fi with the relatively much higher power, and this is one of the reason making the platform implementation difficult. In this paper, the ZigBee transmission is measured and analyzed by the BEB algorithm for finding the slot time when ZigBee can transmit, and an actual transmission happens stochastically depending on the network environment. The simulation results show that it guarantees high success rate of the ZigBee transmission by overcoming Wi-Fi interference in the 2.4 GHz frequency band.