• Wind and Structures
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• v.38 no.4
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• pp.309-323
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• 2024

The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

• ETRI Journal
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• v.38 no.1
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• pp.70-80
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• 2016

This paper addresses the problem of robust waveform design for distributed multiple-radar systems (DMRSs) based on low probability of intercept (LPI), where signal-to-interference-plus-noise ratio (SINR) and mutual information (MI) are utilized as the metrics for target detection and information extraction, respectively. Recognizing that a precise characterization of a target spectrum is impossible to capture in practice, we consider that a target spectrum lies in an uncertainty class bounded by known upper and lower bounds. Based on this model, robust waveform design approaches for the DMRS are developed based on LPI-SINR and LPI-MI criteria, where the total transmitting energy is minimized for a given system performance. Numerical results show the effectiveness of the proposed approaches.

• Journal of the Korea Institute of Military Science and Technology
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• v.6 no.4
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• pp.38-44
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• 2003

In this paper configuration design is viewed as an engineering discipline that plays a key role in the design integration process at early-stage development of a complex and large-scale product. Taking as an instance an aircraft development program that Korean engineers had experienced in Lockheed-Martin company, the process of early-stage configuration design is recapitulated and then a role model of effective design integration activities is presented.

• BMB Reports
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• v.46 no.5
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• pp.252-257
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• 2013

Fibroblast activation protein (FAP) is a specific serine protease expressed in tumor stroma proven to be a stimulatory factor in the progression of some cancers. The purpose of this study was to investigate the effects of FAP knockdown on tumor growth and the tumor microenvironment. Mice bearing 4T1 subcutaneous tumors were treated with liposome-shRNA complexes targeting FAP. Tumor volumes and weights were monitored, and FAP, collagen, microvessel density (MVD), and apoptosis were measured. Our studies showed that shRNA targeting of FAP in murine breast cancer reduces FAP expression, inhibits tumor growth, promotes collagen accumulation (38%), and suppresses angiogenesis (71.7%), as well as promoting apoptosis (by threefold). We suggest that FAP plays a role in tumor growth and in altering the tumor microenvironment. Targeting FAP may therefore represent a supplementary therapy for breast cancer.

• Journal of Korean Library and Information Science Society
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• v.38 no.4
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• pp.463-480
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• 2007

This study examines the design and utilization of video storyboard surrogates in the digital video libraries. To do this, first we constructed the arrangement model of key-frames for storyboard based on the FRBR model, image communication and PRECIS Indexing theories and evaluated the model using 6 sample videos and 26 participants. The study results show that the video storyboard surrogates based on the arrangement model has a higher accuracy value in terms of summary extraction than that of the sequential video storyboard. Moreover, watching both types of video storyboard one after another, especially browsing the sequential video storyboard first and then the arrangement model-based one, produces a remarkable increase in accuracy value of summary extraction. The study proposes two methods of utilizing the video storyboard surrogates in the digital video libraries: Designing a video browsing interface where users can use the sequential storyboard as a default and then the arrangement model-based one for re-watching; and utilizing the arrangement model-based storyboard as structured match sources of image-based queries.

• International Journal of Automotive Technology
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• v.8 no.1
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• pp.33-38
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• 2007

Since it is difficult to analytically express the Melnikov function when a dynamic system possesses multiple saddle fixed points with homoclinic and/or heteroclinic orbits, this paper investigates a vehicle model with nonlinear suspension spring and hysteretic damping element, which exhibits multiple heteroclinic orbits in the unperturbed system. First, an algorithm for Melnikov integrals is developed based on the Melnikov method. And then the amplitude threshold of road excitation at the onset of chaos is determined. By numerical simulation, the existence of chaos in the present system is verified via time history curves, phase portrait plots and $Poincar{\acute{e}}$ maps. Finally, in order to further identify the chaotic motion of the nonlinear system, the maximal Lyapunov exponent is also adopted. The results indicate that the numerical method of estimating chaotic threshold is an effective one to complicated vehicle systems.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.38 no.3
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• pp.184-195
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• 2005

A preliminary quantitative model of the trophic structure in Gwangyang bay, Korea was obtained using ECOPATH and data from relevant studies to date in the region. The model integrates and analyzes biomass, food spectrum, trophic interactions and the key trophic pathways of the system. The bay model comprises 9 groups of benthic primary producer, phytoplankton, zooplankton, benthos, bivalve, pelagic fish, demersal fish and piscivorous fish. The total system throughput was estimated at $2.4\;kgWW/m^2/yr$, including a consumption of $41\%$, exports of $9\%$, respiratory flows of $24\%$ and flows into detritus of $26\%$. All of which originate from primary producers measured at $52\%$ and detritus of $48\%$. The total biomass was seen to be high compared to the levels of Somme, Delaware, Chesapeake Bays and Seine Estuary. This seems to be possibly due to artificial bivalve aquaculture and overestimation of benthos and benthic primary producer groups. The deviation can be calibrated by neglecting aquaculture and decreasing the habitat area for the groups. The trophic network of the bay shows a low level of recycling and organization as indicated by Finn's cycling index $3.3\%$, Ascendancy $3.1\;kgC/m^2/yr$ bits, Capacity $5.1\;kgC/m^2/yr$ bits and Redundancy $2.2\;kgC/m^2/yr$ bits. A high relative ascendancy of $62\%$ and a low internal relative ascendancy of $18\%$ indicate the system is not fully organized and stable towards disturbances, depending upon external connections. Although the model should be continuously provided with field data and calibrated further in depth, this study is the first trophic model applied to the region. The model can be a useful tool to understand the ecosystem in a quantitative manner.

• Korean Journal of Agricultural Science
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• v.38 no.4
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• pp.769-774
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• 2011

This study aimed at finding the factors impacting customer satisfaction (CS) for conversion farm with $2^{nd}$ and $3^{rd}$ industry, because the most important thing in the conversion farm is enhancing customer satisfaction. The data on CS from 173 pumpkin farm's customers by on-line survey were gathered. The analysis using structural equation model with Amos was carried out. Product, service and purchasing were determined as 3 factors impacting to CS. The result showed that purchasing is the biggiest contributor to CS. It means the customers using on-ine market are very sensitive to farm's brand and logistics. It is also found that conversion with processing and farm experience activity is definitely affecting to building customer's trust. In conclusion, making efforts on enhancing CS in conversion farm is the key to success.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.74-82
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• 2015

Two key challenges in statistical relational learning are uncertainty and complexity. Standard frameworks for handling uncertainty are probability and first-order logic respectively. A Markov logic network (MLN) is a first-order knowledge base with weights attached to each formula and is suitable for classification of dataset which have variables correlated with each other. But we need domain knowledge to construct first-order logics and a computational complexity problem arises when calculating weights of first-order logics. To overcome these problems we suggest a method to generate first-order logics and learn weights using association analysis in this study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.82-90
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• 2015

Location selection of distribution centers is a crucial task for logistics operators and key decision makers of an organization. This is a multi-criteria decision making (MCDM) process which includes both quantitative and qualitative criteria. In order to propose an optimized location selection model, this research suggests a hierarchical group of evaluation criteria : 5 major criteria with 15 sub-criteria. The MCDM approach presented in this research, by integrating Grey Relational Analysis (GRA) with Analytic Hierarchy Process (AHP), tends to rectify the overall quality and uncertainty of the values of evaluation criteria. An example of a location selection case in Korea is illustrated in this study to show the effectiveness of this method.