• Wind and Structures
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• v.38 no.3
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• pp.193-202
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• 2024

Modern high-rise tower designs incorporating recessed balcony cavity spaces can be prone to high-frequency and narrow-band Rossiter aerodynamic excitations under glancing incident winds that can harmonize and compete with recessed balcony volume acoustic Helmholtz modes and facade elastic responses. Resulting resonant inertial wind loading to balcony facades responding to these excitations is additive to the peak design wind pressures currently allowed for in wind codes and can present as excessive facade vibrations and sub-audible throbbing in the serviceability range of wind speeds. This paper presents a methodology to determine Cavity Amplification Factors to account for façade resonant inertial wind loads resulting from balcony cavity aero-acoustic-elastic resonances by drawing upon field observations and the results of full-scale monitoring and model-scale wind tunnel tests. Recessed balcony cavities with single orifice type openings and located within curved façade tower geometries appear particularly prone. A Cavity Amplification Factor of 1.8 is calculated in one example representing almost a doubling of local façade design wind pressures. Balcony façade and tower design recommendations to mitigate wind induced aero-acoustic-elastic resonances are provided.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.583-595
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• 2014

Currently, Korean transportation policies are aiming for increase of safety and environment-friendly and efficient operation, by avoiding construction and expansion of roads, and upgrading road alignments and facilities. This is revealed by that there have been 22 road expansion projects (30%) and 50 road improvement projects (70%) under the 3rd Five-Year Plan for National Highways ('11~'15), while there were 53 road expansion projects (71%) and 22 road improvement projects (29%) under the 2nd Five-Year Plan for National Highways. For more effective road improvement projects, there is a need of choosing projects after an objective and scientific safety assessment of each road, and assessing safety improvement depending on projects. This study is intended to develop a model for this road safety analysis and assessment. The major objective of this study is creating a road safety analysis and assessment model appropriate for Korean society, based on the HSM (Highway Safety Manual) of the U.S. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. In order to build up data for model development, the sections thought to have identical geometrical structure factors in 5 lines, Cheonbuk province, were divided as homogeneous sections, and representative values of geometric structures, facilities, traffic volume, climate conditions and land usage were collected from the 1,452 sections divided. The collected data was processed correlation analysis of each road element was implemented to see which factor had a big effect on traffic accidents. On the basis of these results, then, an accident model was established as a negative binomial regression model.Using the developed model, an Crash Modification Factor (CMF) which determines accident frequency changes depending on safety performance function (SPF) predicting the number of accident occurrence through traffic volume and road section expansion, road geometric structure and traffic properties, was extracted.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.6
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• pp.369-376
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• 2013

Finance Information System is critical national infrastructure. Therefore it is important to select variables of defect causal factor for the system defect management effectively. We research and analyze detected errors in A Company's Finance Information System for three years. In the result of research and analysis, we have selected 9 variables of defect factor: the trading volume, the fluctuation of KOSDAQ index, and the number of public announcements, etc. Then we have assumed that these variables affect real system errors and analyzed correlation between the hypothesis and the detected system errors. After analyzing, we have extracted the trading volume, the number of orders and fills, changing tasks, and the fluctuations of NASDAQ index as valid variables of defect factor. These variables are proposed for failure prediction model as the variables to manage defects in the finance information system afterward.

• Korean Journal of Environmental Biology
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• v.29 no.4
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• pp.312-320
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• 2011

In order to estimate a better methodological factor to understand phytoplankton ecology between abundance and bio-volume of phytoplankton, each 1,160 phytoplankton data, including abundance, classification and chlorophyll $a$ concentration were collected in Korean coastal waters of Incheon (Yellow sea), Tongyeong (South sea), and Ulsan (East sea). Based on these data, phytoplankton bio-volume can be calculated through a geometric model. The correlation coefficient between abundance and chlorophyll $a$ concentration was higher than the coefficient between biovolume and chlorophyll $a$ concentration, because a small size phytoplankton has relatively dense chlorophyll contents compared with the proportion of chlorophyll in a large size phytoplankton. Thus, the interpretation using abundance to understand phytoplankton ecology in Korean coastal waters may be more effective than that using bio-volume.

• Journal of Korean Society for Atmospheric Environment
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• v.13 no.5
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• pp.383-396
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• 1997

Numerical prediction of the pollutant dispersion over a two-dimensional hilly terrain is presented. The dispersion model used in the present work is based on the gradient diffusion theory and the finite-volume method on a non-orthogonal boundary-fitted grid system. The numerical model is validated by comparing the results with the available experimental data for the flat-floor dispersion within a turbulent boundary-layer. The numerical error analysis is performed based on the guideline of Kasibhatla et al.(1988) for the elevated-source dispersion in the flat-floor boundary layer having a power-law velocity and linear eddy-diffusivity profile. The influences of the two-dimensional hilly terrain on the dispersion from a continuously released source are numerically investigated by changing the emission locations and heights. It is found that the distributions of ground-level concentration are strongly influenced by the source location and the emission height. Hence, the terrain amplification factor is greatly enhanced when the pollutant source is located within a flow separation region. Dispersion from a source of short duration is also simulated and the duration time of the pollutant is compared at several downstream locations on a hilly terrain. The results of the numerical prediction are applied to the evaluation of environmental impacts due to the automobile exhausts at the seashore highway with a parallel mountain range.

• Smart Structures and Systems
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• v.19 no.1
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• pp.57-66
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• 2017

Nanocomposites reinforced with carbon nanotube fibers exhibit greater stiffness, strength and damping properties in comparison to conventional composites reinforced with carbon/glass fibers. Consequently, most of the nanocomposite research is focused in understanding the dynamic characteristics, which are highly useful in applications such as vibration control and energy harvesting. It has been observed that those nanocomposites show better stiffness when the geometry of nanotubes is straight as compared to curvilinear although nanotube agglomeration may exist. In this work the damping behavior of the nanocomposite is characterized in terms of loss factor under the presence of nanotube agglomerations. A micro stick-slip damping model is used to compute the damping properties of the nanocomposites with multiwall carbon nanotubes. The present formulation considers the slippage between the interface of the matrix and the nanotubes as well as the slippage between the interlayers in the nanotubes. The nanotube agglomerations model is also presented. Results are computed based on the loss factor expressed in terms of strain amplitude and nanotube agglomerations. The results show that although-among the various factors such as the material properties (moduli of nanotubes and polymer matrix) and the geometric properties (number of nanotubes, volume fraction of nanotubes, and critical interfacial shear stresses), the agglomeration of nanotubes significantly influences the damping properties of the nanocomposites. Therefore the full potential of nanocomposites to be used for damping applications needs to be analyzed under the influence of nanotube agglomerations.

• Geomechanics and Engineering
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• v.33 no.4
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• pp.381-391
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• 2023

The aim of this work is to analyze and predict the wave propagation behavior of the carbon nanotube reinforced composites (CNTRC) beams within the framework of various higher order shear deformation beam theory. Using the Euler-Lagrange principle, the wave equations for CNTRC beams are derived, where the determining factor is to make the determinant equal to zero. Based on the eigenvalue method, the relationship between wave number and circular frequency is obtained. Furthermore, the phase and group velocities during wave propagation are obtained as a function of wave number, and the material properties of CNTRC beams are estimated by the mixture rule. In this paper, various higher order shear beam theory including Euler beam theory, Timoshenko beam theory and other beam theories are mainly adopted to analyze the wave propagation problem of the CNTRC beams, and by this way, we conduct a comparative analysis to verify the correctness of this paper. The mathematical model provided in this paper is verified numerically by comparing it with some existing results. We further investigate the effects of different enhancement modes of CNTs, volume fraction of CNTs, spring factor and other aspects on the wave propagation behaviors of the CNTRC beams.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.6
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• pp.458-467
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• 2019

The purpose of this study is the suggestion of optimized parameters in OI (Optimal Interpolation) by experimental study. The observation of applying optimal interpolation is ADCP (Acoustic Doppler Current Profiler) data at the southwestern sea of Korea. FVCOM (Finite Volume Coastal Ocean Model) is used for the barotropic model. OI is to the estimation of the gain matrix by a minimum value between the background error covariance and the observation error covariance using the least square method. The scaling factor and correlation radius are very important parameters for OI. It is used to calculate the weight between observation data and model data in the model domain. The optimized parameters from the experiments were found by the Taylor diagram. Constantly each observation point requires optimizing each parameter for the best assimilation. Also, a high accuracy of numerical model means background error covariance is low and then it can decrease all of the parameters in OI. In conclusion, it is expected to have prepared the foundation for research for the selection of ocean observation points and the construction of ocean prediction systems in the future.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.2
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• pp.168-174
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• 2008

Diagnosis on setteability based on human operator's experimental knowledge, which could be established by long term operation, is a limit factor to construction of automation control system in wastewater treatment plant. On-line SVI(Sludge Volume Index) analyzer was developed which can measure SV30 automatically by image capture and image analysis method. In this paper, information got by settling process was studied using On-line SVI analyzer for better operation & management of WWTPs. First, SV30 detection algorithm was developed using image capture and image analysis for settling test and it showed that automatic detection is feasible even if deflocculation and bulking was occurred. Second, turbidity assessment model was developed using image analysis.