• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.244-251
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• 2007

Intention reading technique is essential to provide personalized services toward more convenient and human-friendly services in complex ubiquitous environment such as a smart home. If a system has knowledge about an user's intention of his/her behavioral pattern, the system can provide mote qualified and satisfactory services automatically in advance to the user's explicit command. In this sense, learning capability is considered as a key function for the intention reading technique in view of knowledge discovery. In this paper, ore introduce a personalized media control method for a possible application iii a smart home. Note that data pattern such as human behavior contains lots of inconsistent data due to limitation of feature extraction and insufficiently available features, where separable data groups are intermingled with inseparable data groups. To deal with such a data pattern, we introduce an effective engineering approach with the combination of fuzzy logic and probabilistic reasoning. The proposed learning system, which is based on IFCS (Iterative Fuzzy Clustering with Supervision) algorithm, extract probabilistic fuzzy rules effectively from the given numerical training data pattern. Furthermore, an extended architectural design methodology of the learning system incorporating with the IFCS algorithm are introduced. Finally, experimental results of the media contents recommendation system are given to show the effectiveness of the proposed system.

• Journal of Distribution Science
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• v.15 no.8
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• pp.47-54
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• 2017

Purpose - According to agency theory, managers have incentives to adjust firm revenues to meet earnings expectations or delay bad news disclosure because of performance-based compensation and their reputation in the market. When the bad news accumulates, stock prices fail to reflect all available information. Thus, market prices of stocks are higher than their intrinsic value. After all, bad news crosses the tipping point, it comes out all at once. That results in stock crashes. Auditors can decrease stock crash risk by reducing agency costs through their informational role. Especially, stock price crash risk is expected to be lower for firms adopting high-quality audits. We focus on distribution and service industry to examine the relation between audit quality and stock price crash risk. Industry specialization and auditor size are used as proxies for auditor quality. Research design, data and methodology - Our sample contains distribution and service industry firms listed in KOSPI and KOSDAQ during a period of 2004-2011. We use a logistic regression to test whether auditor quality influences crash risk. Auditor quality was measured by industry specialist auditor and Big4 / non-Big4 dichotomy. Following the approach in prior researches, we use firm-specific weekly returns to measure crash risk. Firms experiencing at least one stock price crash in a specific week during year are classified as the high risk group. Results - The result of analyzing 429 companies in distribution and service industry is summarized as follows: Above all, it is shown that higher audit quality has a significant negative(-) effect on the crash risk. Crash risk is alleviated for firms audited by industry specialist auditors and Big 4 audit firms. Therefore, our results show that hypotheses are supported. Conclusions - This study is very meaningful as the first study which investigated the effects of high audit quality on stock price crash risk. We provide evidence that high-quality auditors reduce stock price crash risk. Our finding implies that the risk of extreme losses can be reduced through screening of high-quality auditors. Therefore investors and regulators may utilize our findings in their investment and rule making decisions.

• Journal of the Korean Applied Science and Technology
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• v.34 no.1
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• pp.173-182
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• 2017

This study was conducted to investigate the change of Aaster scaber antioxidative activity, total phenolic compounds and flavonoids during the blanching processes. With two parameters such as blanching time and temperature, response surface methodology and central composite design was used to study the combined effect of blanching time (90 to 162 sec) and blanching temperature (75 to $99^{\circ}C$). We found that antioxidative activity, total phenolic compounds and flavonoids during the blanching processes were influenced by blanching temperature and time. Within process condition, total phenolic compounds and flavonoids were extracted 3.00 - 35.48 mg/g and 2.35 - 8.38 mg/g, respectively. DPPH radical scavenging activity was 42.10 - 67.14%. The change of total phenolic compounds, flavonoids, and DPPH radical scavenging activity was dependent of blanching temperature more than time. The total phenolic compounds was increased as temperature rise, but flavonoids not. However, DPPH radical scavenging activity was increased during the blanching process.

• Journal of Distribution Science
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• v.12 no.11
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• pp.77-83
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• 2014

Purpose - The National Agricultural Cooperative Federation of Korea and National Fisheries Cooperative Federation of Korea have prosecuted both financial and retail businesses. As cooperatives are public institutions and receive government support, their sound management is required by the Financial Supervisory Service in Korea. This is mainly managed by CAEL, which is changed by CAMEL. However, NFFC's business section, managing the finance and retail businesses, is unified and evaluated; the CAEL model has an insufficient classification to evaluate the retail industry. First, there is discrimination power as regards CAEL. Although the retail business sector union can receive a higher rating on a CAEL model, defaults have often been reported. Therefore, a default prediction model is needed to support a CAEL model. As we have the default prediction model using a subdivision of indexes and statistical methods, it can be useful to have a prevention function through the estimation of the retail sector's default probability. Second, separating the difference between the finance and retail business sectors is necessary. Their businesses have different characteristics. Based on various management indexes that have been systematically managed by the National Fisheries Cooperative Federation of Korea, our model predicts retail default, and is better than the CAEL model in its failure prediction because it has various discriminative financial ratios reflecting the retail industry situation. Research design, data, and methodology - The model to predict retail default was presented using logistic analysis. To develop the predictive model, we use the retail financial statements of the NFCF. We consider 93 unions each year from 2006 to 2012 to select confident management indexes. We also adapted the statistical power analysis that is a t-test, logit analysis, AR (accuracy ratio), and AUROC (Area Under Receiver Operating Characteristic) analysis. Finally, through the multivariate logistic model, we show that it is excellent in its discrimination power and higher in its hit ratio for default prediction. We also evaluate its usefulness. Results - The statistical power analysis using the AR (AUROC) method on the short term model shows that the logistic model has excellent discrimination power, with 84.6%. Further, it is higher in its hit ratio for failure (prediction) of total model, at 94%, indicating that it is temporally stable and useful for evaluating the management status of retail institutions. Conclusions - This model is useful for evaluating the management status of retail union institutions. First, subdividing CAEL evaluation is required. The existing CAEL evaluation is underdeveloped, and discrimination power falls. Second, efforts to develop a varied and rational management index are continuously required. An index reflecting retail industry characteristics needs to be developed. However, extending this study will need the following. First, it will require a complementary default model reflecting size differences. Second, in the case of small and medium retail, it will need non-financial information. Therefore, it will be a hybrid default model reflecting financial and non-financial information.

• Journal of Distribution Science
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• v.12 no.11
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• pp.55-65
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• 2014

Purpose - This study aims to investigate the process of political changes in Japan, which has introduced regulatory policies for large-scale retail stores since the 1930s, as well as the examples, and suggests improvement schemes for our policies in Korea, which imposes restrictions on business hours and forced holidays in accordance with the current Distribution Industry Development Act. Research design, data, and methodology - After examining the political change processes related to large-scale retail stores in japan, this study analyzes individually regulated cases based on the ordinances enacted by each local government. Through case analysis in Japan, this study makes political suggestions that may be helpful for our country substantially. Results - Since there is an obvious possibility that our economic restrictions on business hours and mandatory holidays do not coincide with WTO GATS, it is necessary for large-scale distributors to introduce new social and environmental regulations similar to Japan, rather than imposing controls to restrict free competition and also introduce a policy to induce cooperation with small businesses for the advancement of the distribution industry. Thus, it is desirable to take measures on noise, waste, traffic, and parking for the preservation of the living environment in the surroundings when building new large-scale retail stores. It is also important to establish measures to improve the welfare of neighborhood residents and consumers, create a pleasant urban environment, and make it mandatory to make presentations at public hearings among residents. Furthermore, it should be mandatory to establish regional contribution plans when a retail store is established, and take measures to solve various civil complaints or problems that may occur after entering the market. Moreover, it is desirable for large-scale retail stores that entered the market to induce cooperation in performing various activities in the area with a strong sense that they are all members of the local economy. Conclusions - If introducing social regulations like in Japan, there is probably an advantage that the conflicts seen when large-scale retail stores enter the market are absorbed by adjusting the persons concerned within the established institution in order to establish a field to solve such conflicts systematically. In contrast, there are still concerns regarding chaotic operation without any active attempts to have a conversation with large-scale retail stores and local small merchants due to a sharp conflict among the persons concerned, and if it is a briefing session without any decision of the restrictions on their opening itself, there may be doubts with regard to their effectiveness. Moreover, if the de facto opening is restricted by the introduction of such a briefing session procedure, the choice of whether to protect the existing rights of large-scale retail stores might become problematic. However, such problems could be minimized in a way by forming a separate consultative group for all persons concerned including residents, local governments, professionals, civic organizations, small merchants, and massive retail store-related persons.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• Korean Journal of Construction Engineering and Management
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• v.12 no.6
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• pp.79-92
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• 2011

Quantity take-off is one of the critical tasks that determine the cost of a construction project, and its result should be accurate and reliable. BIM-based quantity take-off is a very attractive process for practitioners since the quantity take-off can be done automatically in a fast and accurate way. However, the result of BIM-based quantity take-off can be varied depending on how BIM was modeled. As a project progresses, more detailed design information is getting available, and it can be expected that the degree of completeness and accuracy for the BIMbased quantity take-off is going to be improved as well. However, when estimation is performed at each stage of a project life-cycle, there is no way to measure or forecast how accurate of the quantity take-off result from the BIM data given at the current stage. Therefore, this research derived factors that affect the BIM-based quantity takeoff and developed a methodology and framework to measure and forecast the completeness of BIM-based quantity take-off. The measurement framework and index that are proposed by this research was verified and validated for their consistency and feasibility through six pilot projects.

• Journal of Life Science
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• v.28 no.4
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• pp.483-487
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• 2018

Cypermethrin, a commonly used domestic and agricultural pyrethroid pesticide, is widely considered detrimental to the environment and to many organisms because of its residual property and toxicity. Cellulophaga lytica DAU203, isolated from coastal sediment, was chosen because it degrade cypermethrin. Cellulophaga lytica DAU203 effectively degraded cypermethrin, as the utilized carbon source and substrate, in a mineral salt medium. Effective factors, such as carbon source, nitrogen source, initial pH, and temperature, for cypermethtin biological degradation by Cellulophaga lytica DAU203 were analyzed by one factor at a time method. Temperature ($22{\sim}42^{\circ}C$), initial pH (5~9), and yeast extract concentration (0.1~2.5%[w/v]) were selected as the three most important factors. There were optimized at $33.4^{\circ}C$, pH 7.7, and 2.4%(w/v) by response surface methodology, respectively. The Box- Behnken design consisting of 46 experimental runs with three replicates was used to optimize the independent variables which significantly influenced the cypermethrin biological degradation. This model for cypermethrin degradation by Cellulophaga lytica DAU203 is highly significant (p<0.05). Under the optimized condition, Cellulophaga lytica DAU203 degraded approximately 83.7 % of the cypermethrin within 5 days. These results suggest that Cellulophaga lytica DAU203 may be useful for the biological degradation of cypermethrin in cypermethrin-contaminated environments.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.1 s.11
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• pp.11-17
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• 1998

Recently, 3D GIS based on 3D geo-processing methodology and Internet environment are emerging issues in GIS fields. To design and implement 3D GIS, the strategic linkage of Java and VRML is first regarded: 3D feature format definition in the passion of conventional GIS including aspatial attributes, 3B feature indexing, 3D analytical operators such as selection, buffering, and Near, Metric operation such as distance measurement and statistical description, and 3D visualization. In 3D feature format definition, the following aspects are implemented: spatial information for 3D primitives extended from 2D primitives, multimedia data, object texture or color of VRML specification. DXF-format GIS layers with additional attributes are converted to 3D feature format and imported into this system. While, 3D analytical operators are realized in the form of 3D buffering with respect to user-defined point, line, polygon, and 3D objects, and 3D Near functions; furthermore, 'Lantern operator' is newly introduced in this 3D GIS. Because this system is implemented by Java applet, any client with Java-enable browser including VRML browser plug-in can utilize the new style of 3D GIS function in the virtual space. Conclusively, we present prototype of WWW-based 3D GIS, and this approach will be contribute to development of core modules on the stage of concept establishment and of real application model in future.

• Applied Chemistry for Engineering
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• v.28 no.5
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• pp.559-564
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• 2017

In this study, the optimization process was carried out by using the central composite model of the response surface methodology in waste cooking oil based biodiesel production process. The acid value, reaction time, reaction temperature, methanol/oil molar ratio, and catalyst amount were selected process variables. The response was evaluated by measuring the FAME content (more than 96.5%) and kinematic viscosity (1.9~5.5 cSt). Through basic experiments, the range of optimum operation variables for the central composite model, such as reaction time, reaction temperature and methanol/oil molar ratio, were set as between 45 and 60 min, between 50 and $60^{\circ}C$, and between 8 and 12, respectively. The optimum operation variables, such as biodiesel production reaction time, temperature, and methanol/oil molar ratio deduced from the central composite model were 55.2 min, $57.5^{\circ}C$, and 10, respectively. With those conditions the results deduced from modeling were as followings: the predicted FAME content of the biodiesel and the kinematic viscosity of 97.5% and 2.40 cSt, respectively. We obtained experimental results with deduced operating variables mentioned above as followings: the FAME content and kinematic viscosity of 97.7% and 2.41 cSt, respectively. Error rates for the FAME content and kinematic viscosity were 0.23 and 0.29%, respectively. Therefore, the low error rate could be obtained when the central composite model among surface reaction methods was applied to the optimized production process of waste cooking oil raw material biodiesel.