• Title/Summary/Keyword: Building Performance

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Fire Risk Prediction and Fire Risk Rating Evaluation of Four Wood Types by Comparing Chung's Equation-IX and Chung's Equation-XII (Chung's Equation-IX과 Chung's Equation-XII의 비교에 의한 목재 4종의 화재위험성 예측 및 화재위험성 등급 평가)

  • JiSun You;Yeong-Jin Chung
    • Applied Chemistry for Engineering
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    • v.35 no.3
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    • pp.200-208
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    • 2024
  • Chung's equations-IX and Chung's equation-XII were utilized to predict the fire risk and evaluate fire risk ratings for four types of wood: camphor, cherry, rubber, and elm trees. The combustion tests were conducted using a cone calorimeter test method by ISO 5660-1 standards. The fire risk and fire risk rating (FRR) were compared for Fire Risk Index-IX (FRI-IX) and Fire Risk Index-XII (FRI-XII). The results yielded Fire Performance Index-XI (FPI-XI) ranging from 0.08 to 11.48 and Fire Growth Index-XI (FGI-XI) ranging from 0.67 to 111.89. The Fire Risk Index-XII (FRI-XII), indicating fire risk rating, exhibited an increasing order of cherry (0.45): Grade A (Ranking 5) < PMMA (1): Grade A (Ranking 4) < elm (1.23): Grade A (Ranking 3) < rubber (1.56): Grade A (Ranking 2) << camphor (148.23): Grade G (Ranking 1). Additionally, the fire risk index-IX (FRI-IX) was cherry (0): Grade A (Ranking 3) ≈ rubber (0): Grade A (Ranking 3) ≈ elm tree (0): Grade A (Ranking 3) < PMMA (1): Grade A (Ranking 2) << camphor tree (66.67): Grade G (Ranking 1). In general, camphor was found to have the highest fire risk. In conclusion, although the expression of the index is different as shown based on the standards of FRI-IX and FRI-XII, predictions based on fire risk assessment of combustible materials showed similar trends.

Conceptual Understanding of Heritage Archives (헤리티지 아카이브의 개념적 이해)

  • Jong Chul Lim
    • Journal of Korean Society of Archives and Records Management
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    • v.24 no.3
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    • pp.85-104
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    • 2024
  • While there have been ongoing discussions and attempts to utilize archives for marketing purposes in various organizations, including businesses, there has been a lack of clarity regarding what should be archived and what should be considered as marketing targets within an organization's history. Consequently, historical marketing has often been past-oriented, with results varying significantly based on the capabilities of those in charge. To introduce and effectively utilize archives in organizational settings, it is crucial to demonstrate that archives can positively impact organizational performance. The Heritage Archives is a utilization plan that offers an approach to digitizing and preserving the valuable heritage and assets of a business, explaining them to various stakeholders through records, serving as a foundation for building trust in the business, and linking them to marketing, branding, and other applications. This study focuses on fundamental concepts for constructing and utilizing heritage archives by defining and interpreting key concepts such as the affordance of records, organizational heritage, and heritage assets. To this end, the study incorporates Geoffrey Yeo's affordance and John M.T. Balmer's concept of heritage. In addition, it compares definitions of assets in KS Q ISO 55000:2021, KS X ISO 15489-1:2016, and KS X ISO 30300:2020. Through the study's findings, insights can be obtained for organizations seeking to implement heritage archives and leverage them for marketing, branding, and related purposes.

The Effect of the Verbal Emotional Context on the Serial Position Effect (음성으로 제시되는 감정 맥락이 서열 위치 효과에 미치는 영향)

  • Jinsun Suhr;Eunmi Oh;Kwanghee Han
    • Science of Emotion and Sensibility
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    • v.27 no.2
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    • pp.3-14
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    • 2024
  • An understanding of the influence of emotional context on memory retrieval is crucial to our comprehensive understanding of human cognition. While previous research focused primarily on visual stimuli to address this relationship, this study ventures into the realm of speech-based emotional contexts. Building on previous findings, we examine the effects of arousal and the valence of verbal contexts on memory, with particular focus on mitigating the serial position effect. In Study 1, we investigated how the arousal level of verbal context in the middle of a word list affects memory retention. Our results demonstrated detriment to the memory of later parts of the word list when exposed to low-arousal contexts. In Study 2, we controlled for arousal levels and examined the impact of valence on memory. We found that negative verbal contexts impair the memory of the word when presented together. Our findings suggest that speech-based emotional contexts do not facilitate verbal memory processing. In particular, negative emotional contexts were found to reinforce the serial position effect. Negative emotional contexts tend to disrupt task performance and fail to elicit memory-enhancing effects, especially when both the context and memory stimulus are verbal. These insights offer a valuable contribution to our understanding of the nuances of auditorily delivered emotional context in verbal memory processes.

Influence analysis of Internet buzz to corporate performance : Individual stock price prediction using sentiment analysis of online news (온라인 언급이 기업 성과에 미치는 영향 분석 : 뉴스 감성분석을 통한 기업별 주가 예측)

  • Jeong, Ji Seon;Kim, Dong Sung;Kim, Jong Woo
    • Journal of Intelligence and Information Systems
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    • v.21 no.4
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    • pp.37-51
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    • 2015
  • Due to the development of internet technology and the rapid increase of internet data, various studies are actively conducted on how to use and analyze internet data for various purposes. In particular, in recent years, a number of studies have been performed on the applications of text mining techniques in order to overcome the limitations of the current application of structured data. Especially, there are various studies on sentimental analysis to score opinions based on the distribution of polarity such as positivity or negativity of vocabularies or sentences of the texts in documents. As a part of such studies, this study tries to predict ups and downs of stock prices of companies by performing sentimental analysis on news contexts of the particular companies in the Internet. A variety of news on companies is produced online by different economic agents, and it is diffused quickly and accessed easily in the Internet. So, based on inefficient market hypothesis, we can expect that news information of an individual company can be used to predict the fluctuations of stock prices of the company if we apply proper data analysis techniques. However, as the areas of corporate management activity are different, an analysis considering characteristics of each company is required in the analysis of text data based on machine-learning. In addition, since the news including positive or negative information on certain companies have various impacts on other companies or industry fields, an analysis for the prediction of the stock price of each company is necessary. Therefore, this study attempted to predict changes in the stock prices of the individual companies that applied a sentimental analysis of the online news data. Accordingly, this study chose top company in KOSPI 200 as the subjects of the analysis, and collected and analyzed online news data by each company produced for two years on a representative domestic search portal service, Naver. In addition, considering the differences in the meanings of vocabularies for each of the certain economic subjects, it aims to improve performance by building up a lexicon for each individual company and applying that to an analysis. As a result of the analysis, the accuracy of the prediction by each company are different, and the prediction accurate rate turned out to be 56% on average. Comparing the accuracy of the prediction of stock prices on industry sectors, 'energy/chemical', 'consumer goods for living' and 'consumer discretionary' showed a relatively higher accuracy of the prediction of stock prices than other industries, while it was found that the sectors such as 'information technology' and 'shipbuilding/transportation' industry had lower accuracy of prediction. The number of the representative companies in each industry collected was five each, so it is somewhat difficult to generalize, but it could be confirmed that there was a difference in the accuracy of the prediction of stock prices depending on industry sectors. In addition, at the individual company level, the companies such as 'Kangwon Land', 'KT & G' and 'SK Innovation' showed a relatively higher prediction accuracy as compared to other companies, while it showed that the companies such as 'Young Poong', 'LG', 'Samsung Life Insurance', and 'Doosan' had a low prediction accuracy of less than 50%. In this paper, we performed an analysis of the share price performance relative to the prediction of individual companies through the vocabulary of pre-built company to take advantage of the online news information. In this paper, we aim to improve performance of the stock prices prediction, applying online news information, through the stock price prediction of individual companies. Based on this, in the future, it will be possible to find ways to increase the stock price prediction accuracy by complementing the problem of unnecessary words that are added to the sentiment dictionary.

Basic Research on the Possibility of Developing a Landscape Perceptual Response Prediction Model Using Artificial Intelligence - Focusing on Machine Learning Techniques - (인공지능을 활용한 경관 지각반응 예측모델 개발 가능성 기초연구 - 머신러닝 기법을 중심으로 -)

  • Kim, Jin-Pyo;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.3
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    • pp.70-82
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    • 2023
  • The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

PRC Maritime Operational Capability and the Task for the ROK Military (중국군의 해양작전능력과 한국군의 과제)

  • Kim, Min-Seok
    • Strategy21
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    • s.33
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    • pp.65-112
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    • 2014
  • Recent trends show that the PRC has stepped aside its "army-centered approach" and placed greater emphasis on its Navy and Air Force for a wider range of operations, thereby reducing its ground force and harnessing its economic power and military technology into naval development. A quantitative growth of the PLA Navy itself is no surprise as this is not a recent phenomenon. Now is the time to pay closer attention to the level of PRC naval force's performance and the extent of its warfighting capacity in the maritime domain. It is also worth asking what China can do with its widening naval power foundation. In short, it is time to delve into several possible scenarios I which the PRC poses a real threat. With this in mind, in Section Two the paper seeks to observe the construction progress of PRC's naval power and its future prospects up to the year 2020, and categorize time frame according to its major force improvement trends. By analyzing qualitative improvements made over time, such as the scale of investment and the number of ships compared to increase in displacement (tonnage), this paper attempts to identify salient features in the construction of naval power. Chapter Three sets out performance evaluation on each type of PRC naval ships as well as capabilities of the Navy, Air Force, the Second Artillery (i.e., strategic missile forces) and satellites that could support maritime warfare. Finall, the concluding chapter estimates the PRC's maritime warfighting capability as anticipated in respective conflict scenarios, and considers its impact on the Korean Peninsula and proposes the directions ROK should steer in response. First of all, since the 1980s the PRC navy has undergone transitions as the focus of its military strategic outlook shifted from ground warfare to maritime warfare, and within 30 years of its effort to construct naval power while greatly reducing the size of its ground forces, the PRC has succeeded in building its naval power next to the U.S.'s in the world in terms of number, with acquisition of an aircraft carrier, Chinese-version of the Aegis, submarines and so on. The PRC also enjoys great potentials to qualitatively develop its forces such as indigenous aircraft carriers, next-generation strategic submarines, next-generation destroyers and so forth, which is possible because the PRC has accumulated its independent production capabilities in the process of its 30-year-long efforts. Secondly, one could argue that ROK still has its chances of coping with the PRC in naval power since, despite its continuous efforts, many estimate that the PRC naval force is roughly ten or more years behind that of superpowers such as the U.S., on areas including radar detection capability, EW capability, C4I and data-link systems, doctrines on force employment as well as tactics, and such gap cannot be easily overcome. The most probable scenarios involving the PRC in sea areas surrounding the Korean Peninsula are: first, upon the outbreak of war in the peninsula, the PRC may pursue military intervention through sea, thereby undermining efforts of the ROK-U.S. combined operations; second, ROK-PRC or PRC-Japan conflicts over maritime jurisdiction or ownership over the Senkaku/Diaoyu islands could inflict damage to ROK territorial sovereignty or economic gains. The PRC would likely attempt to resolve the conflict employing blitzkrieg tactics before U.S. forces arrive on the scene, while at the same time delaying and denying access of the incoming U.S. forces. If this proves unattainable, the PRC could take a course of action adopting "long-term attrition warfare," thus weakening its enemy's sustainability. All in all, thiss paper makes three proposals on how the ROK should respond. First, modern warfare as well as the emergent future warfare demonstrates that the center stage of battle is no longer the domestic territory, but rather further away into the sea and space. In this respect, the ROKN should take advantage of the distinct feature of battle space on the peninsula, which is surrounded by the seas, and obtain capabilities to intercept more than 50 percent of the enemy's ballistic missiles, including those of North Korea. In tandem with this capacity, employment of a large scale of UAV/F Carrier for Kill Chain operations should enhance effectiveness. This is because conditions are more favorable to defend from sea, on matters concerning accuracy rates against enemy targets, minimized threat of friendly damage, and cost effectiveness. Second, to maintain readiness for a North Korean crisis where timely deployment of US forces is not possible, the ROKN ought to obtain capabilities to hold the enemy attack at bay while deterring PRC naval intervention. It is also argued that ROKN should strengthen its power so as to protect national interests in the seas surrounding the peninsula without support from the USN, should ROK-PRC or ROK-Japan conflict arise concerning maritime jurisprudence. Third, the ROK should fortify infrastructures for independent construction of naval power and expand its R&D efforts, and for this purpose, the ROK should make the most of the advantages stemming from the ROK-U.S. alliance inducing active support from the United States. The rationale behind this argument is that while it is strategically effective to rely on alliance or jump on the bandwagon, the ultimate goal is always to acquire an independent response capability as much as possible.

The Effect of Supporting Activities for Win-win Partnership Between Franchisees and Franchisers on Re-contract Intention and Management Performance through Dynamic Trust (프랜차이즈 가맹본부와 가맹사업자간 상생을 위한 지원활동이 동적신뢰를 통해 경영성과 및 재계약의도에 미치는 영향)

  • Lee, Myung Jin;Lee, Sang Won
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.15 no.4
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    • pp.245-261
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    • 2020
  • The aim of this study is to investigate the correlation between the support activities provided by the franchiser and how they affect the intention of the contract renewal and business performances made by franchisees, developing dynamic trust between these transactional partners. Various supportive activities between franchiser and franchisees were divided into financial and non-financial activities and dynamic trust into Transitional-based trust, Calculative-based trust, Relational-based trust, and Balanced-based trust. These trust types, which are variable and adjustable based on the opportunistic behaviors of business parties, were applied to define the impact of the support activities on the contract renewal intention and the performances. This study was developed around domestic franchisees. An investigator visited business owners and manager level-employees, explained the purpose of the survey prior to the response, and the answers were directly written by hands. A total of 348 copies were used for the analysis. As the results of the analysis, first, financial support activities were found to have a positive(+) effect on transitional-based trust, calculative-based trust, and balanced-based trust. On the other hand, non-financial support activities were found to have a positive(+) effect on calculative-based trust, relational-based trust, and balanced-based trust, and there was no significant relationship on transitional-based trust. Second, the dynamic trust had a statistically significant positive(+) effect on inducing the contract renewal. Lastly, in the relationship between the dynamic trust and its impact on business performances, only transitional-based trust, and relational-based trust were found to have a positive(+) effect on the financial performances. In addition, relational-based trust showed a meaningful positive(+) relationship on the non-financial performances, and non-financial performace showed a meaningful positive(+) relationship on the re-contract intention. From the results, it can be concluded that the financial and non-financial activities for a win-win partnership between franchiser and franchisees are essential in not only forming dynamic trust but also boosting business performances as well as maintaining the business relationship. Thus, it suggests that building a win-win partnership can be promoted more efficiently by specifying activities best suitable for a particular relationship. In addition, a specific set of activities could be presented for establishing the level of trust that is formed in situations that vary depending on transaction risks and interdependency arising from having the transactional relationship based on the contract as the franchise industry features. Eventually, it is expected that this study can provide a way to promote the qualitative improvement of the franchise industry by identifying factors essential to establishing a sustainable win-win system and relationships that can improve the business performance of franchisees.

Value of Information Technology Outsourcing: An Empirical Analysis of Korean Industries (IT 아웃소싱의 가치에 관한 연구: 한국 산업에 대한 실증분석)

  • Han, Kun-Soo;Lee, Kang-Bae
    • Asia pacific journal of information systems
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    • v.20 no.3
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    • pp.115-137
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    • 2010
  • Information technology (IT) outsourcing, the use of a third-party vendor to provide IT services, started in the late 1980s and early 1990s in Korea, and has increased rapidly since 2000. Recently, firms have increased their efforts to capture greater value from IT outsourcing. To date, there have been a large number of studies on IT outsourcing. Most prior studies on IT outsourcing have focused on outsourcing practices and decisions, and little attention has been paid to objectively measuring the value of IT outsourcing. In addition, studies that examined the performance of IT outsourcing have mainly relied on anecdotal evidence or practitioners' perceptions. Our study examines the contribution of IT outsourcing to economic growth in Korean industries over the 1990 to 2007 period, using a production function framework and a panel data set for 54 industries constructed from input-output tables, fixed-capital formation tables, and employment tables. Based on the framework and estimation procedures that Han, Kauffman and Nault (2010) used to examine the economic impact of IT outsourcing in U.S. industries, we evaluate the impact of IT outsourcing on output and productivity in Korean industries. Because IT outsourcing started to grow at a significantly more rapid pace in 2000, we compare the impact of IT outsourcing in pre- and post-2000 periods. Our industry-level panel data cover a large proportion of Korean economy-54 out of 58 Korean industries. This allows us greater opportunity to assess the impacts of IT outsourcing on objective performance measures, such as output and productivity. Using IT outsourcing and IT capital as our primary independent variables, we employ an extended Cobb-Douglas production function in which both variables are treated as factor inputs. We also derive and estimate a labor productivity equation to assess the impact of our IT variables on labor productivity. We use data from seven years (1990, 1993, 2000, 2003, 2005, 2006, and 2007) for which both input-output tables and fixed-capital formation tables are available. Combining the input-output tables and fixed-capital formation tables resulted in 54 industries. IT outsourcing is measured as the value of computer-related services purchased by each industry in a given year. All the variables have been converted to 2000 Korean Won using GDP deflators. To calculate labor hours, we use the average work hours for each sector provided by the OECD. To effectively control for heteroskedasticity and autocorrelation present in our dataset, we use the feasible generalized least squares (FGLS) procedures. Because the AR1 process may be industry-specific (i.e., panel-specific), we consider both common AR1 and panel-specific AR1 (PSAR1) processes in our estimations. We also include year dummies to control for year-specific effects common across industries, and sector dummies (as defined in the GDP deflator) to control for time-invariant sector-specific effects. Based on the full sample of 378 observations, we find that a 1% increase in IT outsourcing is associated with a 0.012~0.014% increase in gross output and a 1% increase in IT capital is associated with a 0.024~0.027% increase in gross output. To compare the contribution of IT outsourcing relative to that of IT capital, we examined gross marginal product (GMP). The average GMP of IT outsourcing was 6.423, which is substantially greater than that of IT capital at 2.093. This indicates that on average if an industry invests KRW 1 millon, it can increase its output by KRW 6.4 million. In terms of the contribution to labor productivity, we find that a 1% increase in IT outsourcing is associated with a 0.009~0.01% increase in labor productivity while a 1% increase in IT capital is associated with a 0.024~0.025% increase in labor productivity. Overall, our results indicate that IT outsourcing has made positive and economically meaningful contributions to output and productivity in Korean industries over the 1990 to 2007 period. The average GMP of IT outsourcing we report about Korean industries is 1.44 times greater than that in U.S. industries reported in Han et al. (2010). Further, we find that the contribution of IT outsourcing has been significantly greater in the 2000~2007 period during which the growth of IT outsourcing accelerated. Our study provides implication for policymakers and managers. First, our results suggest that Korean industries can capture further benefits by increasing investments in IT outsourcing. Second, our analyses and results provide a basis for managers to assess the impact of investments in IT outsourcing and IT capital in an objective and quantitative manner. Building on our study, future research should examine the impact of IT outsourcing at a more detailed industry level and the firm level.

Participant Characteristic and Educational Effects for Cyber Agricultural Technology Training Courses (사이버농업기술교육 참가자의 특성과 교육효과)

  • Kang, Dae-Koo
    • Journal of Agricultural Extension & Community Development
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    • v.21 no.1
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    • pp.35-82
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    • 2014
  • It was main objectives to find the learners characteristics and educational effects of cyber agricultural technology courses in RDA. For the research, it was followed by literature reviews and internet based survey methods. In internet based survey, two staged stratified sampling method was adopted from cyber training members database in RDA along with some key word as open course or certificate course, and enrollment years. Instrument was composed through literature reviews about cyber education effects and educational effect factors. And learner characteristics items were added in survey documents. It was sent to sampled persons by e-mail and 316 data was returned via google survey systems. Through the data cleaning, 303 data were analysed by chi-square, t-test and F-test. It's significance level was .05. The results of the research were as followed; First, the respondent was composed of mainly man(77.9%), and monthly income group was mainly 2,000,000 or 3,000,000 won(24%), bachelor degree(48%), fifty or forty age group was shared to 75%, and their job was changed after learning(12.2%). So major respondents' job was not changed. Their major was not mainly agriculture. Learners' learning style were composed of two or more types as concrete-sequential, mixing, abstract-random, so e-learning course should be developed for the students' type. Second, it was attended at 3.2 days a week, 53.53 minutes a class, totally 172.63 minutes a week. They were very eager or generally eager to study, and attended two or more subjects. The cyber education motives was for farming knowledge, personal competency development, job performance enlarging. They selected subjects along with their interest. A subject person couldn't choose more subjects for little time, others, non interesting subject, but more subject persons were for job performance benefits and previous subjects effectiveness. Most learner was finished their subject, but a fourth was not finished for busy (26.7%). And their entrying behavior was not enough to learn e-course and computer or internet using ability was middle level as software using. And they thought RDA cyber course was comfort in non time or space limit, knowledge acquisition, and personal competency development. Cyber learning group was composed of open course only (12.5%), certificate only(25.7%), both(36.3%). Third, satisfaction and academic achievement of e-learning learners were good, and educational service offering for doing job in learning application category was good, but effect of cyber education was not good, especially, agricultural income increasing was not good because major learner group was not farmer, so they couldn't apply their knowledge to farming. And content structure and design, content comprehension, content amount were good. The more learning subject group responded to good in effects, and both open course and certificate course group satisfied more than open course only group. Based on the results, recommendation was offered as cyber course specialization before main course in RDA training system, support staff and faculty enlargement, building blended learning system with local RDA office, introducing cyber tutor system.

Selection Model of System Trading Strategies using SVM (SVM을 이용한 시스템트레이딩전략의 선택모형)

  • Park, Sungcheol;Kim, Sun Woong;Choi, Heung Sik
    • 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.