• Journal of Korean Society of Water and Wastewater
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• v.18 no.6
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• pp.758-769
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• 2004

The trends and seasonalities of most time series have a large variability. The result of the Singular Spectrum Analysis(SSA) processing is a decomposition of the time series into several components, which can often be identified as trends, seasonalities and other oscillatory series, or noise components. Generally, forecasting by the SSA method should be applied to time series governed (may be approximately) by linear recurrent formulae(LRF). This study examined forecasting ability of SSA-LRF model. These methods are applied to daily water demand data. These models indicate that most cases have good ability of forecasting to some extent by considering statistical and visual assessment, in particular forecasting validity shows good results during 15 days.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.7
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• pp.654-661
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• 2013

The dynamic characteristics of a free-piston stirling engine(FPSE) with regard to the working frequency is investigated from theoretical and experimental studies. The FPSE is modeled as a two degree-of-freedom linear vibration system. A theoretical expression on the working frequency is derived from the instability condition for self-excitation based on the linear vibration model. A ${\gamma}$-type free-piston stirling engine is fabricated for experimental studies, and its working frequency is measured on various heater temperatures. Comparisons between the theoretical and experimental results reveal that the working frequency of the test FPSE depends on both the temperature of the compression space and the temperature difference between the expansion and compression spaces.

• Earthquakes and Structures
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• v.6 no.1
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• pp.71-87
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• 2014

Interaction between closely-spaced buildings subject to earthquake induced strong ground motions, termed in the literature as "seismic pounding", occurs commonly during major seismic events in contemporary congested urban environments. Seismic pounding is not taken into account by current codes of practice and is rarely considered in practice at the design stage of new buildings constructed "in contact" with existing ones. Thus far, limited research work has been devoted to quantify the influence of slab-to-slab pounding on the inelastic seismic demands at critical locations of structural members in adjacent structures that are not aligned in series. In this respect, this paper considers a typical case study of a "new" reinforced concrete (R/C) EC8-compliant, torsionally sensitive, 7-story corner building constructed within a block, in bi-lateral contact with two existing R/C 5-story structures with same height floors. A non-linear local plasticity numerical model is developed and a series of non-linear time-history analyses is undertaken considering the corner building "in isolation" from the existing ones (no-pounding case), and in combination with the existing ones (pounding case). Numerical results are reported in terms of averages of ratios of peak inelastic rotation demands at all structural elements (beams, columns, shear walls) at each storey. It is shown that seismic pounding reduces on average the inelastic demands of the structural members at the lower floors of the 7-story building. However, the discrepancy in structural response of the entire block due to torsion-induced, bi-directionally seismic pounding is substantial as a result of the complex nonlinear dynamics of the coupled building block system.

• Advances in Computational Design
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• v.8 no.1
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• pp.13-36
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• 2023

The Puebla-Morelos Earthquake (Mw 7.1) occurred in Mexico in 2017 causing 44 buildings to collapse in Mexico City. This work evaluates the non-linear response of a 6-story reinforced concrete (RC) frame prototype model with masonry infill walls on upper floors. The prototype model was designed using provisions prescribed before 1985 and was subjected to seismic excitations recorded during the earthquakes of 1985 and 2017 in different places in Mexico City. The building response was assessed through a damage index (DI) that considers low-cycle fatigue of the steel reinforcement in columns of the first floor, where the steel was modeled including buckling as was observed in cases after the 2017 earthquake. Isocurves were generated with 72 seismic records in Mexico City representing the level of iso-demand on the structure. These isocurves were compared with the location of 16 collapsed (first-floor column failure) building cases consistent with the prototype model. The isocurves for a value greater than 1 demarcate the location where fatigue failure was expected, which is consistent with the location of 2 of the 16 cases studied. However, a slight increase in axial load (5%) or decrease in column cross-section (5%) had a significant detrimental effect on the cumulated damage, increasing the intensity of the isocurves and achieving congruence with 9 of the 16 cases, and having the other 7 cases less than 2 km away. Including column special detailing (tight stirrup spacing and confined concrete) was the variable with the greatest impact to control the cumulated damage, which was consistent with the absence of severe damage in buildings built in the 70s and 80s.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.4
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• pp.179-188
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• 2017

It is very challenging to analyze the traffic flow in the city because there are lots of traffic accidents, intersections, and pedestrians etc. Now, even in mid-size cities Bus Information Systems(BIS) have been deployed, which have offered the forecast of arriving times at the stations to passengers. BIS also provides more informations such as the current locations, departure-arrival times of buses. In this paper, we perform the time-series analysis of the traffic flow using the data of the average trvel time and the average speed between stations extracted from the BIS. In the mid size cities, the data from BIS will have a important role on prediction and analysis of the traffic flow. We used the Dynamic Linear Model(DLM) for how to make the time series forecasting model to analyze and predict the average speeds at the given locations, which seem to show the representative of traffics in the city. Especially, we analysis travel times for weekdays and weekends separately. We think this study can help forecast the traffic jams, congestion areas and more accurate arrival times of buses.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.5_2
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• pp.151-162
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• 2010

This research aimed at measuring Park and Green Satisfaction (PGS) using subjective indicators of 'surface, line and spot' green evaluated by citizens. Also frequency of visits to park and green measured using objective indicators (number of visits) to find the relationship with PGS. A conceptual model of PGS was developed to relate evaluation to satisfaction and finally to utilization of open spaces. A sample of 500 questionnaire survey was employed for Uijeongbu City in Korea. A Structual Equation Modeling (AMOS) techniques was used to test the hypothesized relationship among factors (construct). As a result, first, PGS was explained by three latent factors of 'urban park' (${\gamma}=0.54$), 'linear facilities' (${\gamma}=0.25$), and 'surface green' (${\gamma}=0.15$) respectively. These three exogenous construct was found very useful classification system for open spaces of cities. Second, PGS (${\gamma}=0.34$) was found as a mediating variable to utilization of open spaces and also PGS was closely related to citizens Environmental Quality Satisfaction (EQS), such concept as, 'livability' and 'aesthetic quality'. The more satisfied with park and green the more people use the space. The PGS was an important QOL indicator together with the subjective indicator of 'livability'. Third, jogging and walking trails and bike ways along the river corridor was the most important green facilities contribute to the PGS and EQS. The near the distance (within 500m) the more number of visit to river corridor (green way). The river corridor promote accessibility to nature and other parks.

• Health Policy and Management
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• v.30 no.3
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• pp.376-385
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• 2020

Background: The purpose of this study is to investigate the factors affecting the healthy living practice rate such as non-smoking, moderate drinking, walking, and low-salt diet by elementary municipality (so called, 'si-gun-hu'). Methods: The 2016 Korean Community Health Survey was used for the analysis. The theoretical model is founded upon the Anderson model, and both the multiple linear regression analysis and the beta regression analysis was performed for estimation. Results: As a result of the beta regression analysis, healthy living practice rate was found to be significantly higher in the areas with a less number of cigarette retailers, participating in healthy city projects, a low proportion of people who perceive their body type as obesity, a higher proportion of women, and a lower proportion of spouses. Conclusion: In order to improve healthy living practices, the regulations on health risk businesses, the spread of Healthy City project, and policy efforts awaring obesity are recommended.

• Advances in environmental research
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• v.7 no.2
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• pp.109-120
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• 2018

In the present study research air quality analyses for $PM_{10}$, were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The averages concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of $PM_{10}$ occurs generally in the night while the least concentration was found at the afternoon. Monthly concentrations of $PM_{10}$ showed highest value in August, while least value was found in January. The seasonal concentrations showed the least amounts in autumn while the highest amounts in summer. Relations between the air pollutant and some meteorological parameters were calculated statistically using the daily average data. The wind data (velocity, direction), relative humidity, temperature, sunshine periods, evaporation, dew point and rainfall were considered as independent variables. The relationships between concentration of pollutant and meteorological parameters were expressed by multiple linear regression equations for both annual and seasonal conditions SPSS software. RMSE test showed that among different prediction models, stepwise model is the best option.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6860-6868
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• 2015

In this study, we consider a problem of forecasting daily city gas demand of Korea. Forecasting daily gas demand is a daily routine for gas provider, and gas demand needs to be forecasted accurately in order to guarantee secure gas supply. In this study, we analyze the time series of city gas demand in several ways. Data analysis shows that primary factors affecting the city gas demand include the demand of previous day, temperature, day of week, and so on. Incorporating these factors, we developed a multiple linear regression model. Also, we devised a sampling procedure that selectively collects the past data considering the characteristics of the city gas demand. Test results on real data exhibit that the MAPE (Mean Absolute Percentage Error) obtained by the proposed method is about 2.22%, which amounts to 7% of the relative improvement ratio when compared with the existing method in the literature.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.3
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• pp.53-62
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• 2020

The study aims to provide some plausible explanation for why Vietnamese listed companies only stop at the level of truthful presentation of information related to accounting data through the opinion of independent auditors. The information is only at the level of compliance with the requirements of Circular 155/2015/TT-BTC in form, but in essence is sketchy. What factors affect the level of voluntary disclosure of listed companies in Vietnam? In order to identify the factors affecting voluntary information disclosure on annual reports of listed companies, the study collected data on annual reports of 122 companies listed on the stock market in Ho Chi Minh City in the period 2015-2018 and uses regression analysis methods. The research presents 8 factors affecting the level of voluntary information disclosure including: Firm size, Listed time, Profitability, Solvency, Separation of board of directors and executive director, Board size, Organizational ownership and Foreign ownership. Next, the study conducted descriptive statistical analysis correlation coefficient analysis to examine the correlation and relevance of independent variables measured by the scale ratio, testing multiple linear regression model. The results of the study show that factors listed time, profitability and organizational ownership affecting voluntary information disclosure on annual reports of listed companies in Vietnam.