• Journal of Korea Water Resources Association
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• v.52 no.7
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• pp.475-482
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• 2019

Subseasonal-to-Seasonal (S2S) prediction information which have 2 weeks to 2 months lead time are expected to be used through many parts of industry fields, but utilizability is not reached to expectation because of lower predictability than weather forecast and mid- /long-term forecast. In this study, we used multi-layer perceptron (MLP) which is one of machine learning technique that was built for regression training in order to improve predictability of S2S precipitation data at South Korea through post-processing. Hindcast information of ECMWF was used for MLP training and the original data were compared with trained outputs based on dichotomous forecast technique. As a result, Bias score, accuracy, and Critical Success Index (CSI) of trained output were improved on average by 59.7%, 124.3% and 88.5%, respectively. Probability of detection (POD) score was decreased on average by 9.5% and the reason was analyzed that ECMWF's model excessively predicted precipitation days. In this study, we confirmed that predictability of ECMWF's S2S information can be improved by post-processing using MLP even the predictability of original data was low. The results of this study can be used to increase the capability of S2S information in water resource and agricultural fields.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.2
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• pp.1-11
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• 2024

In the midst of the current turbulent global economy, traditional investment metrics are undergoing a metamorphosis, signaling the onset of what's often referred to as an "Investment cold season". Early-stage startups, despite their boundless potential, grapple with immediate revenue constraints, intensifying their pursuit of critical investments. While financial indicators once took center stage in investment evaluations, a notable paradigm shift is underway. Organizational culture, once relegated to the sidelines, has now emerged as a linchpin in forecasting a startup's resilience and enduring trajectory. Our comprehensive research, integrating insights from CVF and OCAI, unveils the intricate relationship between organizational culture and its magnetic appeal to investors. The results indicate that startups with a pronounced external focus, expertly balanced with flexibility and stability, hold particular allure for investment consideration. Furthermore, the study underscores the pivotal role of adhocracy and market-driven mindsets in shaping investment desirability. A significant observation emerges from the study: startups, whether they secured investment or failed to do so, consistently display strong clan culture, highlighting the widespread importance of nurturing a positive employee environment. Leadership deeply anchored in market culture, combined with an unwavering commitment to innovation and harmonious organizational practices, emerges as a potent recipe for attracting investor attention. Our model, with an impressive 88.3% predictive accuracy, serves as a guiding light for startups and astute investors, illuminating the intricate interplay of culture and investment success in today's economic landscape.

• Korean Journal of Construction Engineering and Management
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• v.1 no.3 s.3
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• pp.101-107
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• 2000

On 1 July, 2000, the Ministry of Construction and Transportation announced the Earned Value Management System(EVMS) will be applied in public sector soon. However the arguments over the EVMS applied to our unique construction environment still exist and create strong concerns and worries among some experts it would be another mistakes proposed by the government. We do know the EVMS comes from C/SCSC which was first released by the United States Department of Defense in December 1967, and proved very powerful and efficient project management tool from a lot of practices. Although it is an excellent tool, we can not ignore our many experienced failures appling foreign system due to the differences of construction culture and law between the Korean and US construction industries. The purpose of the EVMS's success in Korea, therefore, this paper tests and proves the EVMS's adaptability and credibility to our construction environment by EAC model, that is one of the most important functions in the EVMS, using very scare EV data of the Korean construction projects.

• Current Industrial and Technological Trends in Aerospace
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• v.7 no.1
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• pp.11-19
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• 2009

Though the regional airlines have grown consistently with world's economic recovery after 2001, now the future of them is uncertain from the current economic depression since 2007. In the regional aircraft industry, there have been two main trends that larger airplanes and regional jets inroad the market. But, the situational change including radical rise of oil price and worldwide recession induces the managerial damage of airlines and it makes them doubt about the regional jet which has been the main stream of regional aircraft after the success of the ERJ-145 in 1990s. Still, most of being developed or planed regional aircrafts choose turbo fan, the future demands of turboprop increase and it becomes a good alternative of future regional aircraft in many market forecasts. Thus in this paper, current situation and tendency of regional aircraft market are investigated with various market forecast reports.

• Journal of Korean Society of Transportation
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• v.26 no.2
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• pp.135-145
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• 2008

As a fundamental input to the travel demand forecasting, OD has been always a concern in obtaining the accurate link traffic volume. Numerous methods were applied thus far without a complete success. Some existing OD estimation techniques generally extract regular samples and expand those sample into population. These methods, however, leaves some to be desired in terms of accuracy. To complement such problems, research on estimating OD using additional information such as link traffic volume as well as sample link use rate have been accomplished. In this paper, a new approach for estimating static origin-destination (OD) using probe vehicle has been proposed. More specifically, this paper tried to search an effective sample rate which varies over time and space. In a sample test network study, the traffic volume error rate of each link was set as objective function in solving the problem. As a key result the MAE (mean absolute error) between expanded OD and actual OD was identified as about 5.28%. The developed methodology could be applied with similar cases. Some limitations and future research agenda have also been discussed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.3
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• pp.167-173
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• 2017

With increased interest in the fourth industrial revolution represented by artificial intelligence, it has been very active to utilize bigdata and machine learning techniques in almost areas of society. Also, such activities have been realized by development of forecasting systems in various applications. Especially in the movie industry, there have been numerous attempts to predict whether they would be success or not. In the past, most of studies considered only the static factors in the process of prediction, but recently, several efforts are tried to utilize realtime social bigdata produced in SNS. In this paper, we propose the prediction technique utilizing various feedback information such as news articles, blogs and reviews as well as static factors of movies. Additionally, we also experimentally evaluate whether the proposed technique could precisely forecast their revenue targeting on the relatively successful movies.

• Archives of design research
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• v.15 no.1
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• pp.101-112
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• 2002

technologies have now placed high hopes and expectations on the significance of design more than in any other time. This is because under current trends where technically and functionally advanced technologies are equalized, our success in the international markets depends on how we can differentiate designs to meet consumers'needs. In this research, we sought to forecast modern and future trends in automotive design, and thus secure competitiveness in automotive design. We first analyzed the movement of design value in respective times following changes in design trends (one aspect of social change in the 21st century), and consequent changes in consumers' value\ulcorner We further compared and researched design trends for automobiles and products by time and region, through surveys, analysis and collation of automotive design phenomena from various aspects recently occurring in advanced countries such as the U.S.A., European national and Japan.

• Journal of Korea Technology Innovation Society
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• v.9 no.4
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• pp.812-841
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• 2006

Previous studies have shown that the ex-ante financial ratios, mainly used by financial institutions for loan evaluation purpose, are related to the ex-post finn's performance of venture firm's. The main objective of this study is to examine whether non-financial variables such as 'technology', 'marketability', and 'other business indexes' have extra explanatory power in forecasting the ex-post firm's performance of small and medium size venture firm's in Korea. The implications and results of this study are expected to be useful in loan evaluation, investment decision and internal management decisions of venture firms. Among small and medium sized manufacturing firms funded in the year of 1999 through 2005, 416 firms are selected for our analysis. The relationship between evaluation indexes and firm's success/failure is investigated using binary logistic regression analysis and factor analysis with an aid of SPSS program. The summarized results are as follows. First, current evaluation model, used for loan evaluation purpose for small and medium size manufacturing firms show the same discriminatory power as previous prediction model. Second, among the tested additional variables, significant indices are 'technological capability of CEO', 'managerial capability of CEO', and 'business feasibility'. Third, while previous studies on evaluation structure had 3 factors, this study showed that valuation's structure has 6 factors.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.64-73
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• 2019

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.467-474
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• 2013

Construction contactors must continuously seek to improve their cash flows, which reside at the heart of their financial success. They require careful planning, analysis, and optimization to avoid the risk of bankruptcy, remain profitable, and secure long-term growth. Sources of cash include bank loans and retained earnings, which are conceptually similar in that they both incur a cost of capital. Financial management therefore requires accurate yet customizable modeling capabilities that can quantify all expenses, including said cost of capital. However, currently existing cash flow models in construction engineering and management have strongly simplified the manner in which interest is assessed, which may even lead to overstating it at a disadvantage to contractors. The variable nature of cash balances, especially in the early phases of construction projects, contribute to this challenging issue. This research therefore extends a new cash flow model with an accurate interest calculation. It utilizes singularity functions, so called because of their ability to flexibly model changes across any number of different ranges. The interest function is continuous for activity costs of any duration and allows the realistic case that activities may begin between integer time periods, which are often calendar months. Such fractional interest calculation has hitherto been lacking from the literature. It also provides insights into the self-referential behavior of compound interest for variable cash balances. The contribution of this study is twofold; augmenting the corpus of financial analysis theory with a new interest formula, whose strengths include its generic nature and that it can be evaluated at any fractional value of time, and providing construction managers with a tool to help improve and fine-tune the financial performance of their projects.