Kim, Chi-Hoon;Ahn, Byung-Lip;Jang, Cheol-Yong;Hong, Won-Hwa
한국태양에너지학회:학술대회논문집
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2009.11a
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pp.231-235
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2009
According to flow of energy, the loss occurs through walls, roofs, windows and so on. Among these case, most of the loss that is about 45% occurs through windows. windows's U-value is six times higher than wall's one according to Building code, so the loss through windows accounts for very much rates. Currently, Exterior wall's U-value about building envelope is 0.35~0.58W/ mK, but windows's one is 3.3W/ mK. It means that the loss through windows occupy very much amounts relatively. Therefore, the solution is required to reduce energy loss and increasing displeasure caused by excessive influx of solar energy through windows, to solve the problems Like decoloration on indoor furniture an clothes by harmful ultraviolet rays, air conditioning and increased cost. Therefore, on this paper, Thermal Performance was evaluated through actual test about high insulation Super Window which can improve thermal performance and the Simulation result was compared with actual resul by using Simulation program WINDOW and THERM.
This study explored an impact of consumer innovativeness on fashion consumption propensity and clothing satisfaction, focusing on female consumers in 20's and 30's. Specifically, the smart phone users had been the subjects of study because they accept new things earlier than others. The collection of data was carried out for one month in September 2011, and a total of 390 copies were used for final analysis. A statistical package SPSS 16.0 was used for analysis of data. First, the impact of innovativeness on fashion consumption propensity was explored. It was found that the innovativeness has impact on ostentation-seeking propensity and personality-seeking propensity. The impact of innovativeness on the clothing satisfaction was explored. It was found that the innovativeness has negative impacts on tangible value satisfaction and intangible value satisfaction. Second, it was found that if an innovative consumer has less ostentation-seeking propensity and less personality-seeking propensity, the innovative consumer gets more satisfaction from tangible value of clothes. On the other hand, if an innovative consumer has less ostentation-seeking propensity, the innovative consumer gets more satisfaction from intangible value of clothes. Third, the differences in consumer innovativeness, fashion consumption propensity and satisfaction dependent on the age of consumers were explored. In innovativeness and fashion consumption propensity, fashion-seeking propensity and personality-seeking propensity had significant differences between different age groups. In satisfaction, tangible value satisfaction had significant difference between different age groups. However, there was no significant differences between different age groups in ostentation-seeking propensity, economy-seeking propensity and intangible value satisfaction.
Journal of the Korean Operations Research and Management Science Society
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v.13
no.1
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pp.1-9
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1988
The purpose of this paper is study the sensitivity analysis of matrix game. Teh sensitivity analysis of matrix is classified into two types. Type one is to find the characteristic region of an element of the pay off matrix in which the value of the current optimal strategy remains as an optimum. Type two is to find that in which the basis of the current optimal strategy does not change. This paper shows the characteristic regions of basic and nonbasic strategies. Further it is found that the characteristic regions of type one and two are same in the case that the element is that of at least one player's nonbasic strategy.
The purpose of this study was to examine the differences in body cathexis, need, clothing value according to the demographic characteristics of women and to clarify the influences of demographic characteristics, body cathexis, and need on the clothing value. For the study, a questionnaire survey was conducted with 436 women in the Kyungnam region. Obtained data were analyzed by one-way ANOVA and $Scheff{\acute{e}}'s$ multiple range for differences in body cathexis, need, clothing value according to the demographic characteristics and multiple regression analysis for influence of demographic characteristics, body cathexis, and need on the clothing value. The results of this study were as follows. The body cathexis, need, clothing value according to the demographic characteristics showed significant differences in part. Among these factors, the media contact was proved to be more important on body cathexis, need, clothing value, but the income and occupation status did not have a difference on any subordinate factors of the clothing value.
Purpose This study builds a prediction model to find stocks that can reach intrinsic value among KOSPI and KOSDAQ-listed companies to improve the stability and profitability of the stock investment. And investment simulations are conducted to verify whether stock investment performance is improved by comparing the prediction model, random stock selection, and the market indexes. Design/methodology/approach Value investment theory and machine learning techniques are applied to build the model. Various experiments find conditions such as the algorithm with the best predictive performance, learning period, and intrinsic value-reaching period. This study selects stocks through the prediction model learned with inventive variables, does not limit the holding period after buying to reach the intrinsic value of the stocks, and targets all KOSPI and KOSDAQ companies. The stock and financial data are collected for 21 years (2001-2021). Findings As a result of the experiment, using the random forest technique, the prediction model's performance was the best with one year of learning period and within one year of the intrinsic value reaching period. As a result of the investment simulation, the cumulative return of the prediction model was up to 1.68 times higher than the random stock selection and 17 times higher than the KOSPI index. The usefulness of the prediction model was confirmed in that the number of intrinsic values reaching the predicted stock was up to 70% higher than the random selection.
The stiffness of a structure is one of several structural signals that are useful indicators of the amount of damage that has been done to the structure. To accurately estimate the stiffness, an equation of motion containing a stiffness parameter must first be established by expansion as a linear series model, a Taylor series model, or a power series model. The model is then used in multivariate autoregressive modeling to estimate the structural stiffness and compare it to the theoretical value. Stiffness assessment for modeling purposes typically involves the use of one of three statistical model refinement approaches, one of which is the efficient Akaike information criterion (AIC) proposed in this paper. If a newly added component of the model results in a decrease in the AIC value, compared to the value obtained with the previously added component(s), it is statistically justifiable to retain this new component; otherwise, it should be removed. This model refinement process is repeated until all of the components of the model are shown to be statistically justifiable. In this study, this model refinement approach was compared with the two other commonly used refinement approaches: principal component analysis (PCA) and principal component regression (PCR) combined with the AIC. The results indicate that the proposed AIC approach produces more accurate structural stiffness estimates than the other two approaches.
Background: Organic carbon stored in coastal wetlands, which comprises the major part of oceanic "blue carbon," is a subject of growing interest and concern. In this study, organic carbon storage in coastal wetlands and its economic value were estimated using the raw data of 25 studies related to soil carbon storage. Data were collected from three tidal flats (one protected and two developed areas) and two estuarine salt marshes (one protected and one restored area). Bulk density, soil organic matter content, and standing biomass of vegetation were all considered, with Monte Carlo simulation applied to estimate the uncertainty. Results: Mean carbon storage in two salt marshes ranged between 14.6 and $25.5kg\;C\;m^{-2}$. Mean carbon storage in tidal flats ranged from 18.2 to $28.6kg\;C\;m^{-2}$, with variability possibly related to soil texture. The economic value of stored carbon was estimated by comparison with the price of carbon in the emission trading market. The value of US $ $6600\;ha^{-1}$ is ~ 45% of previously estimated ecosystem services from fishery production and water purification functions in coastal areas. Conclusions: Although our study sites do not cover all types of large marine ecosystem, this study highlights the substantial contribution of coastal wetlands as carbon sinks and the importance of conserving these habitats to maximize their ecosystem services.
Modal identification based on ambient vibration data has attracted extensive attention in the past few decades. Since the excitation for ambient vibration tests is mainly from the environmental effects such as wind and traffic loading and no artificial excitation is applied, the signal to noise (s/n) ratio of the data acquired plays an important role in mode identifiability. Under ambient vibration conditions, certain modes may not be identifiable due to a low s/n ratio. This paper presents a study on the mode identifiability of an instrumented cable-stayed bridge with the use of acceleration response data measured by a long-term structural health monitoring system. A recently developed fast Bayesian FFT method is utilized to perform output-only modal identification. In addition to identifying the most probable values (MPVs) of modal parameters, the associated posterior uncertainties can be obtained by this method. Likewise, the power spectral density of modal force can be identified, and thus it is possible to obtain the modal s/n ratio. This provides an efficient way to investigate the mode identifiability. Three groups of data are utilized in this study: the first one is 10 data sets including six collected under normal wind conditions and four collected during typhoons; the second one is three data sets with wind speeds of about 7.5 m/s; and the third one is some blind data. The first two groups of data are used to perform ambient modal identification and help to estimate a critical value of the s/n ratio above which the deficient mode is identifiable, while the third group of data is used to perform verification. A couple of fundamental modes are identified, including the ones in the vertical and transverse directions respectively and coupled in both directions. The uncertainty and s/n ratio of the deficient mode are investigated and discussed. A critical value of the modal s/n ratio is suggested to evaluate the mode identifiability of the deficient mode. The work presented in this paper could provide a base for the vibration-based condition assessment in future.
This is a basic study to investigate possibility to application of cohousing model into Korea. Purpose of this study is to grasp respondents' housing value, and its influence on intention to live in cohousing. Research method used for this study was a social survey. Respondents were 214 married people residing in Seoul and its outskirts by accidential sampling. The collected data were analyzed by SPSS 12.0 program using frequency, mean, average, factor analysis, t-test, one-way ANOVA, Duncan's multiple range test, multiple regression and legit analysis. Result of this study was as follows. Housing values were classified into three categories named as individualism oriented housing value, tradition oriented housing value, and economy oriented housing value. Housing values were different by respondents groups. For example, individualism oriented housing value showed difference according to age and housing area. Tradition oriented housing value showed difference according to sex, occupation, and period of residence, while economy oriented housing value showed difference according to housing type, and home ownership. In detail, men than women, single-income family than double-income family, and detached house resident than flat resident had higher tradition oriented housing value. The younger than the elder, and Seoul resident than outskirts resident had higher economy oriented housing value. Also home owner than tenant, and the higher tradition oriented group had stronger intention to live in cohousing than others.
As advertising and promotions are categorized as operating expenses, managers tend to reduce marketing budget to improve their short term profitability. Gauging the value and accountability of marketing spending is therefore considered as a major research priority in marketing. To respond this call, recent studies have documented that financial market reacts positively to a firm's marketing activity or marketing related outcomes such as brand equity and customer satisfaction. However, prior studies focus on the relation of marketing variable and financial market variables. This study suggests a channel about how marketing activity increases firm valuation. Specifically, we propose that a firm's marketing activity increases the level of the firm's product market information and thereby the dispersion in financial analysts' earnings forecasts decreases. With less uncertainty about the firm's future prospect, the firm's managers and shareholders have less information asymmetry, which reduces the firm's cost of capital and thereby increases the valuation of the firm. To our knowledge, this is the first paper to examine how informational benefits can mediate the effect of marketing activity on firm value. To test whether marketing activity contributes to increase in firm value by mitigating information asymmetry, this study employs a longitudinal data which contains 12,824 firm-year observations with 2,337 distinct firms from 1981 to 2006. Firm value is measured by Tobin's Q and one-year-ahead buy-and-hold abnormal return (BHAR). Following prior literature, dispersion in analysts' earnings forecasts is used as a proxy for the information gap between management and shareholders. For model specification, to identify mediating effect, the three-step regression approach is adopted. All models are estimated using Markov chain Monte Carlo (MCMC) methods to test the statistical significance of the mediating effect. The analysis shows that marketing intensity has a significant negative relationship with dispersion in analysts' earnings forecasts. After including the mediator variable about analyst dispersion, the effect of marketing intensity on firm value drops from 1.199 (p < .01) to 1.130 (p < .01) in Tobin's Q model and the same effect drops from .192 (p < .01) to .188 (p < .01) in BHAR model. The results suggest that analysts' forecast dispersion partially accounts for the positive effect of marketing on firm valuation. Additionally, the same analysis was conducted with an alternative dependent variable (forecast accuracy) and a marketing metric (advertising intensity). The analysis supports the robustness of the main results. In sum, the results provide empirical evidence that marketing activity can increase shareholder value by mitigating problem of information asymmetry in the capital market. The findings have important implications for managers. First, managers should be cognizant of the role of marketing activity in providing information to the financial market as well as to the consumer market. Thus, managers should take into account investors' reaction when they design marketing communication messages for reducing the cost of capital. Second, this study shows a channel on how marketing creates shareholder value and highlights the accountability of marketing. In addition to the direct impact of marketing on firm value, an indirect channel by reducing information asymmetry should be considered. Potentially, marketing managers can justify their spending from the perspective of increasing long-term shareholder value.
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