• Journal of the Korean Wood Science and Technology
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• v.45 no.5
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• pp.580-587
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• 2017

Woodfiber insulation board can be considered as a one of the key material for low energy consumption, comfortable and safety construction of residential space because of its eco-friendly and high thermal insulation performance. This study was carried out to investigate the formaldehyde (HCHO) total volatile organic compounds (TVOC) emission properties and combustion shapes by flame test of low density fiberboards (LDFs) prepared with different adhesives. HCHO TVOC emission and combustion properties of LDFs prepared by melamine urea formaldehyde (MUF), phenol formaldehyde (PF), emulsified methylene diphenyl diisocyanate (eMDI) and latex resin adhesives were measured by desiccator method, 20 L chamber method, and flame test, respectively. As results, LDFs manufactured by MUF, eMDI and latex resin adhesives satisfied the Super $E_0$ grade of HCHO emission performance except PF resin. Furthermore, TVOC emission of all LDFs were satisfied the Korean indoor air quality standard (below $400{\mu}g/m^2{\cdot}h$). Especially, LDF with eMDI resin adhesive showed the lowest HCHO and TVOC emissivity, that $0.14mg/{\ell}$, $12{\mu}g/m^2{\cdot}h$, respectively. However, eMDI emitted the small amount ($3{\mu}g/m^2{\cdot}h$) of toluene in VOC components. In the flame test, LDF with MUF resin adhesives showed the most favorable shape after flame test compare to LDFs prepared other adhesives. Based on HCHO and TVOC emission, and combustion shapes, MUF resin adhesive may be recommended to prepare LDF for insulation purpose.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.6
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• pp.69-80
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• 2015

This can be promoted collaboration environment for the system and the system is very important for competitiveness, it is equipped. If so, could work in collaboration with members of the organization to promote collaboration what factors? Organizational collaboration and cooperation of many people working, or worth pursuing common goals by sharing information and processes to improve labor productivity, defined as collaboration. Factors that promote collaboration are shared visions, the organization's principles and rules that reflect the visions, on-line system developments, and communication methods. First, it embodies the vision shared by the more sympathetic members are active and voluntary participation in the activities of the organization can be achieved. Second, the members are aware of all the rules and principles of a united whole is accepted and leads to good performance. In addition, the ability to share sensitive business activities for self-development and also lead to work to make this a regular activity to create a team that can collaborate to help the environment and the atmosphere. Third, a systematic construction of the online collaboration system is made efficient and rapid task. According to Student team and A corporation we knew that Cloud services and social media, low-cost, high-efficiency services could achieve. The introduction of the latest information technology changes, the members of the organization's systems and active participation can take advantage of continuing education must be made. Fourth, the company to inform people both inside and outside of the organization to communicate actively to change the image of the company activities, the creation of corporate performance is very important to figure. Reflects the latest trend to actively use social media to communicate the effort is needed. For development of systematic collaboration promoting model steps to meet the organizational role. First, the Chief Executive Officer to make a firm and clear vision of the organization members to propagate the faith, empathy gives a sense of belonging should be able to have. Second, middle managers, CEO's vision is to systematically propagate the organizers rules and principles to establish a system would create. Third, general operatives internalize the vision of the company stating that the role of outside companies must adhere. The purpose of this study was well done in collaboration organizations promoting factors for strategic alignment model based on the golden circle and collaboration to understand and reflect the latest trends in information technology tools to take advantage of smart work and business know how student teams through case analysis will derive the success factors. This is the foundation for future empirical studies are expected to be present.

• Journal of the Korea institute for structural maintenance and inspection
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• v.18 no.5
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• pp.1-8
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• 2014

Structures requiring chemical resistance are usually coated with surface protecting agents, but the cost for maintenance and re-construction is incurred due to the low durability. Therefore, in this study, sulfur was polymerized and the performance was examined so that it could be used as the concrete surface protecting agents for structures requiring chemical resistance. The evaluation results indicated that for the spray of the sulfur polymer surface coating agents, the application of the gravity type was appropriate; and for the number of coating times, about 3 cycle spray gave the best results. For the surface condition of the concrete to be coated with the surface protecting agents, outstanding quality was obtained above room temperature ($20{\sim}30^{\circ}C$), and the bond strength increased as the temperature increased. The evaluation results of the strength characteristics depending on the filler content of the surface protecting agents indicated that about 20~40% filler mixing contributed to the strength improvement as it reduced the shrinkage of the sulfur polymer. Also, the mixing of silica showed larger increase in the bond strength than the mixing of fly ash, and the most outstanding bond strength characteristics could be obtained by the mixing of both silica and fly ash. In the case of the chemical resistance, the strength reduction was minimized and outstanding chemical resistance was obtained when the fly ash and silica were substituted by 20%, respectively. The performance evaluation of the chloride ion penetration indicated that for the specimens coated with the sulfur polymer surface protecting agents, the chloride ion penetration resistance increased by 29~48% compared to the specimen without the coating of the surface protecting agent. The examination of the coating condition of the surface protecting agents, compressive strength, bond strength, chemical resistance, and salt damage resistance indicated that in the range of this study, the optimal level was when the silica and fly ash were substituted by 20%, respectively, as the filler for the sulfur polymer.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.3
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• pp.57-69
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• 2014

As of 2013, Korean population density is 505 persons per $1km^2$ and is ranked 3rd place in the most densely populated countries exception of city-states. It shows clearly the population is concentrated in the city area. To fulfil this urban concentration population demand, the enlargement and complexation of buildings, subway and other underground spaces connection tendency has been intensified, and it is need to construct the indoor spatial information DB as well as the accurate indoor surveying DB to promote people's safety and social welfare. In this study, Sadang station and Incheon National Airport were aimed for the construction of Wi-Fi AP location DB and RadioMap DB by collecting the indoor AP raw datas by using mobile device and those collected results were ran through the process of verification, supplementation, and analyzation. To evaluate the performance of constructed DB, 10 points in Incheon Airport- 3rd flr in block A, and 9 points in Sadang station-B1 were selected and calculated the estimated points and ran evaluation experiment using survey positioning error, which is distance between real position and the estimated position. The result shows that Incheon international airport's average and standard deviation was separately 17.81m, 17.79m and Sadang station's average and standard deviation was separately 22.64m, 23.74m. In Sadang station's case, the areas near the exit has low performance of surveying position due to fewer visible AP points than other areas. As total datas were examined except those position, it was verified that the user's location was mapping close position in surveying positioning by using constructed DB. It means that constructed DB contains correct Wi-Fi AP locations and radio wave patterns in object region, so it is considered that the indoor spatial information service based on constructed DB would be available.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.123-136
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• 2014

Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.

• Journal of Distribution Science
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• v.10 no.6
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• pp.39-53
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• 2012

It is widely known that knowledge management plays a facilitating role that contributes to upgrading organizational performance. Knowledge management systems (KMS), especially, support the knowledge management process including the sharing, creating, and using of knowledge within a company, and maximize the value of knowledge resources within an organization. Despite this widely held belief, there are few studies that describe how companies actually develop, share, and practice their knowledge. Companies in the domestic small franchise sector, which are in the early stages in terms of knowledge management, need to improve their KMS to manage their franchisees effectively. From this perspective, this study uses a qualitative approach to explore the actual process of knowledge management implementation. This article presents a case study of PB (Paris Baguette) company, which is the first to build a KMS in the franchise industry. The study was able to confirm the following facts through the analysis of target companies. First, the chief executive's support is a critical success factor and this support can increase the participation of organization members. Second, it is important to build a process and culture that actively creates and leverages information in knowledge management activities. The organizational learning culture should be one where the creation, learning, and sharing of new knowledge is developed continuously. Third, a horizontal network organization is needed in order to make relationships within the organization more close-knit. Fourth, in order to connect the diverse processes such as knowledge acquisition, storage, and utilization of knowledge management activities, information technology (IT) capabilities are essential. Indeed, IT can be a powerful tool for improving the quality of work and maximizing the spread and use of knowledge. However, during the construction of an intranet based KMS, research is required to ensure that the most efficient system is implemented. Finally, proper evaluation and compensation are important success factors. In order to develop knowledge workers, an appropriate program of promotion and compensation should be established. Also, building members' confidence in the benefits of knowledge management should be an ongoing activity. The company developed its original KMS to achieve a flexible and proactive organization, and a new KMS to improve organizational and personal capabilities. The PB case shows that there are differences between participants perceptions and actual performance in managing knowledge; that knowledge management is not a matter of formality but a paradigm that assures the sharing of knowledge; and that IT boosts communication skills, thus creating a mutual relationship to enhance the flow of knowledge and information between people. Knowledge management for building organizational capabilities can be successful when considering its focus and ways to increase its acceptance. This study suggests guidelines for major factors that corporate executives of domestic franchises should consider to improve knowledge management and the higher operating activities that can be used.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.347-355
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• 2021

During the earthquake, for multi-story structure, if the first floor is soft, the deformation will concentrate on that floor causing a serious damage to the column members which might leads to the collapse of the whole structure like Piloti structure during the Pohang earthquake in Korea. According to the 2016 National Disaster Management Research Institute's "Investigation of Seismic Reinforcement and Cost Analysis of Domestic Non-seismic Buildings", the rate of seismic resistance of private reinforced concrete buildings was 38.3 %. Among them, it was reported that the seismic-resistance ratio of the two to five-story structures was less than 50 %. Accordingly, the government is trying to improve the seismic rate through support projects, but the conventional seismic reinforcement methods are still expensive, and emergency construction is difficult. Therefore, in this study, the field applicability was evaluated by improving the reinforcement method using Velcro, which was developed through the research project of the Ministry of Land, Transport and Maritime Affairs in 2014. In order to improve the performance of the Velcro reinforcement method, introducing the initial tension of Velcro using high foaming rigid urethane filling between the Velcro and concrete of the columns was applied. Additionally, an experiment was conducted to evaluate the ductility of Velcro specimen from the concrete confinement effect. As a result, the ductility of the Velcro specimen was improved compare to Normal specimen. However, the energy dissipation capacity of VELCRO2 is better than VELCRO1, yet the maximum ductility of those two specimens did not show a significant difference. Therefore, the improvement of the internal filler material is still needed to have a better maximum ductility.

• Clean Technology
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• v.27 no.4
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• pp.332-340
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• 2021

With the recent reinforcement of emission standards, it is necessary to make efforts to reduce NOx from air pollutant-emitting workplaces. The NOx reduction method mainly used in industrial facilities is selective catalytic reduction (SCR), and the most commercial SCR catalyst is the ceramic honeycomb catalyst. This study was carried out to reduce the NOx emitted from steel plants by applying De-NOx catalyst coated on metallic monolith. The De-NOx catalyst was synthesized through the optimized coating technique, and the coated catalyst was uniformly and strongly adhered onto the surface of the metallic monolith according to the air jet erosion and bending test. Due to the good thermal conductivity of metallic monolith, the De-NOx catalyst coated on metallic monolith showed good De-NOx efficiency at low temperatures (200 ~ 250 ℃). In addition, the optimal amount of catalyst coating on the metallic monolith surface was confirmed for the design of an economical catalyst. Based on these results, the De-NOx catalyst of commercial grade size was tested in a semi-pilot De-NOx performance facility under a simulated gas similar to the exhaust gas emitted from a steel plant. Even at a low temperature (200 ℃), it showed excellent performance satisfying the emission standard (less than 60 ppm). Therefore, the De-NOx catalyst coated metallic monolith has good physical and chemical properties and showed a good De-NOx efficiency even with the minimum amount of catalyst. Additionally, it was possible to compact and downsize the SCR reactor through the application of a high-density cell. Therefore, we suggest that the proposed De-NOx catalyst coated metallic monolith may be a good alternative De-NOx catalyst for industrial uses such as steel plants, thermal power plants, incineration plants ships, and construction machinery.