• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.23-34
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• 2009

In the railroad rolling stock depot, long-term maintenance tasks is done regularly every two or four year basis to maintain the functionality of equipments and rolling stock body or for the repair operation of the heavily damaged rolling stocks by fatal accidents. This paper addresses the computer simulation model building for the rolling stock maintenance shop for the CDC(Commuter Diesel Car) and Generator Car planned to be constructed at Daejon Rolling Stock Depot, which will be moved from Yongsan Rolling Stock Depot. We evaluated the processing capacity of two layout design alternatives based on the maintenance process chart through the developed simulation models. The performance measures are the number of processed cars per year, the cycle time, shop utilization, work in process and the average number waiting car for input. The simulation result shows that one design alternative outperforms another design alternative in every aspect and superior design alternative can process total 340 number of trains per year 15% more than the proposed target within the current average cycle time.

• The Mathematical Education
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• v.63 no.1
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• pp.35-61
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• 2024

The purpose of this study is to examine changes in Korean middle school students' affective attitudes toward mathematics over the past 5 cycles of TIMSS. To this end, we first analyzed the changes in students' affective attitudes towards mathematics in five major countries, and then analyzed the changes in Korean students' affective attitudes toward mathematics by item. As a result of the study, there were positive changes in Korean students' interest, confidence, and value perception of mathematics during the recent 5 cycle of TIMSS. Korean male students' affective attitude toward mathematics is higher than that of female students, and the gender gap has been increasing recently. There was a large difference in the affective attitudes toward mathematics among Korean students, depending on their achievement level, and in particular, the affective attitudes toward mathematics of students at the lower achievement level remained significantly low. Item-level analysis revealed a decrease in Korean students' awareness of the necessity of mathematics in daily life. Based on these results, we discussed the implications for cultivating Korean students' affective attitudes. It is hoped that the results of this study will be meaningfully used as basic data for examining the performance of mathematics education in Korea and contribute to developing measures to foster students' positive attitudes toward mathematics.

• Journal of Venture Innovation
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• v.7 no.3
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• pp.183-228
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• 2024

This study aimed to develop a competency evaluation scale tailored to the specific needs of key talent in the ICT startup sector. Existing competency assessment tools are mostly designed for environments in large corporations or traditional small and medium-sized enterprises, failing to adequately reflect the dynamic requirements of rapidly evolving startups. For startups, where a small number of individuals directly impact company success, key talent is a critical asset. Accordingly, this study sought to create a scale that measures the competencies suited to the challenges and opportunities faced by startups, helping domestic startups establish more effective talent management strategies. The research initially selected 71 items through a literature review and in-depth interviews. Based on expert feedback that emphasized the need for more precise and clear descriptions, the item descriptions were revised, and a total of 65 items were developed through four rounds of content validation. Following preliminary and main surveys, a final set of 58 items was developed. The main survey conducted further factor analysis based on the three broad competency factors?knowledge, skills, and attitude?identified in the preliminary survey. As a result, 10 latent factors emerged: 6 items for task comprehension, 6 items for practical experience (tacit knowledge), 6 items for collaboration, 9 items for management and problem-solving, 9 items for practical skills, 4 items for self-direction, 5 items for goal orientation, 5 items for adaptability, 5 items for relationship orientation, and 3 items for organizational loyalty. The developed scale comprehensively covers the multifaceted nature of competencies, allowing for a thorough evaluation of essential skills such as technical ability, teamwork, innovation, and leadership, which are critical for startups. Therefore, the scale provides a tool that helps startup managers objectively and accurately assess candidates' competencies. It also supports the growth of employees within startups, maximizing the overall organizational performance. By utilizing this tool, startups can build a strong internal talent pool and continuously enhance employees' competencies, thereby strengthening organizational competitiveness. In conclusion, the competency evaluation scale developed in this study is a customized tool that aligns with the characteristics of startups and plays a crucial role in securing sustainable competitiveness in rapidly changing market environments. Additionally, it offers practical guidance to support the successful growth of domestic startups and help them maintain their competitive edge in the market, contributing to the development of the startup ecosystem and the growth of the national economy.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.98-108
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• 2013

The number of Hi-Pass lanes became 793 lanes at 316 expressway tollgates in 2011 due to the increase in the Hi-Pass use. In spite of the increase in the number of Hi-Pass lanes, there have been increased potential risks in tollgates where vehicles using a Hi-Pass lane must weave with other vehicles using a TCS lane. Therefore, there is a need for study on the safety in tollgates. To this end, this study aims at developing a methodology to evaluate the performance measures of diverse location countermeasures of Hi-Pass lanes in an efficient and systematic way. This study measured the mobility, safety and the convenience of installation and operation of Hi-Pass lanes using a microscopic traffic simulation tool, the surrogate safety assessment model and survey. In addition, this study aggregated the above three performance indexes using weight factors estimated using the AHP technique. For the test site, Dongsuwon interchange was selected. After building the microscopic traffic simulation model for the test site, the location countermeasures of Hi-Pass lanes applicable to the test site were compared with each other in terms of the mobility, safety and installing and operating convenience. As a result, there has been no apparent difference in mobility index based on delays. However, the countermeasures where Hi-Pass lanes are located in inside lanes generally showed better safety performance based on the number of conflicts. In addition, countermeasures with neighboring Hi-Pass lanes were favorable in terms of the safety and the convenience of installation and operation. The methodology proposed in this study was found to be useful to support decision makings by providing critical and quantitative information regarding the mobility, safety and the convenience of installation and operation.

• Information Systems Review
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• v.6 no.2
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• pp.113-135
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• 2004

This paper defines appraisal items and weights of the items for the purpose of developing an appraisal instrument that objectively measures employee's effectiveness of knowledge contribution. Deductive research is used for the development of appraisal items and delphi method for the development of weights of the items. In the deductive research the term, "effectiveness of knowledge contribution" is first defined. Then knowledge contribution activities are classified as "dimension of explicit contribution" and " dimension of tacit contribution" due to the characteristics of knowledge. Each dimension is divided again by components. The dimension of explicit contribution is divided according to the content of knowledge, and the dimension of tacit contribution is divided according to the extent of tacitness of knowledge contribution. The total components of dimensions are 7. The dimension of explicit contribution is composed of factual knowledge and procedural knowledge. The factual knowledge is made up of "procedural knowledge outcome" and "other factual knowledge". The procedural knowledge is made up of "procedural knowledge manual" and "lessons-learned procedural knowledge". The dimension of tacit contribution is composed of "agency", "model" and "Q&A". The basic framework for measuring 7 components of knowledge contribution is quantitative and qualitative approach. This paper is premised on the assumption that the outcomes of employee's knowledge contribution activities are recorded in the knowledge management systems in order to evaluate them objectively. The appraisal items are defined as follows: at the dimension of explicit contribution, in quantitative approach, "the upload number" or "performance number", and in qualitative approach, other employee's "referred number" and other employee's "content and format satisfaction evaluation"; at the dimension of tacit contribution, "demanded number of performance" After the development of appraisal items by the deductive method, delphi method was used for the analysis of the weights of the items with the total degree of knowledge contribution, 100. This research does not include the standard marks of the appraisal items. It is because when companies apply this appraisal instrument, they could use their own standard appraisal marks of the appraisal items considering their present situations and companies' goals. Through this almost desert-like research about the appraisal instrument of employee's knowledge contribution effectiveness, it proposes a cornerstone in the research field of appraisal instrument, which provides a standard for employee's knowledge contribution appraisal, and appraisal items that make organizational knowledge to be managed more systemically in business sites.

• Journal of Korea Water Resources Association
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• v.53 no.8
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• pp.627-636
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• 2020

Debris flow disasters primarily occur in mountainous terrains far from cities. As such, they have been underestimated to cause relatively less damage compared with other natural disasters. However, owing to urbanization, several residential areas and major facilities have been built in mountainous regions, and the frequency of debris flow disasters is steadily increasing owing to the increase in rainfall with environmental and climate changes. Thus, the risk of debris flow is on the rise. However, only a few studies have explored the characteristics of flooding and reduction measures for debris flow in areas designated as steep slopes. In this regard, it is necessary to conduct research on securing independent disaster prevention technology, suitable for the environment in South Korea and reflective of the topographical characteristics thereof, and update and improve disaster prevention information. Accordingly, this study aimed to calculate the amount of debris flow, depending on disaster prevention performance targets for regions designated as steep slopes in South Korea, and develop an independent model to not only evaluate the impact of debris flow but also identify debris barriers that are optimal for mitigating damage. To validate the reliability of the two-dimensional debris flow model developed for the evaluation of debris barriers, the model's performance was compared with that of the hydraulic model. Furthermore, a 2-D debris model was constructed in consideration of the regional characteristics around the steep slopes to analyze the flow characteristics of the debris that directly reaches the damaged area. The flow characteristics of the debris delivered downstream were further analyzed, depending on the specifications (height) and installation locations of the debris barriers employed to reduce the damage. The experimental results showed that the reliability of the developed model is satisfactory; further, this study confirmed significant performance degradation of debris barriers in areas where the barriers were installed at a slope of 20° or more, which is the slope at which debris flows occur.

• Analyses & Alternatives
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• v.6 no.2
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• pp.79-115
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• 2022

This study aims to account for electoral choice in the 2020 presidential election by focusing on social identity which forms the basis for core partisan groups. Two views compete to explain the origins of polarization, policy versus party. One emphasizes policy as more influential in choosing presidential candidates. This follows the tradition of retrospective voting theory in which voters' choice rely on government performance. Incumbent president whose performance proves well are rewarded to be reelected. Policy performance is based on measures around distinctive preferences for government spending. Republican Individuals prefer individual responsibility to government support, while Democratic counterparts support government support. Another perspective put an emphasis on the role partisanship which favors in-party members and disfavors partisan out-groups. Interparty animosity plays the key role in determining electoral behavior. This study relies on the Views of the Electorate Research (VOTER) Survey which provides a panel data of several waves from 2011 to 2020. A comparative evaluation of two views highlights three findings. First, policy matters. Policy preferences of voters are the primary drives of political behavior. Electoral outcomes in 2020 turned out to be the results of policy considerations of voters. 53.7 percent of voters tilted toward individual responsibility voted for Trump, whereas 70.4 percent of those favorable views of government support than individual responsibility voted for Biden. Thus effects of policy correspond to a positive difference of 26.4 percent points. Second, partisanship effects are of similar extent in influencing electoral choice of candidates: Democrats are less likely to vote for Trump by 42.4 percent points, while Republicans are less likely to vote for Biden by 48.7 percent points. Third, animosity of Republicans toward Democrat core groups creates 26.5 percent points of favoring Trump over Biden. Democrat animosity toward Republican core groups creates a positive difference of 13.7 percent points of favoring Biden.

• Journal of Korea Technology Innovation Society
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• v.12 no.4
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• pp.788-818
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• 2009

Renewable energy refers to solar energy, biomass energy, hydrogen energy, wind power, fuel cell, coal liquefaction and vaporization, marine energy, waste energy, and liquidity fuel made out of byproduct of geothermal heat, hydrogen and coal; it excludes energy based on coal, oil, nuclear energy and natural gas. Developed countries have recognized the importance of these energies and thus have set the mid to long term plans to develop and commercialize the technology and supported them with drastic political and financial measures. Considering the growing recognition to the field, it is necessary to analysis up-to-now achievement of the government's related projects, in the standards of type of renewable energy, management of sectional goals, and its commercialization. Korean government is chiefly following suit the USA and British policies of developing and distributing renewable energy. However, unlike Japan which is in the lead role in solar rays industry, it still lacks in state-directed support, participation of enterprises and social recognition. The research regarding renewable energy has mainly examinedthe state of supply of each technology and suitability of specific region for applying the technology. The evaluation shows that the research has been focused on supply and demand of renewable as well as general energy and solution for the enhancement of supply capacity in certain area. However, in-depth study for commercialization and the increase of capacity in industry followed by development of the technology is still inadequate. 'Cost-benefit model for each energy source' is used in analysis of technology development of renewable energy and quantitative and macro economical effects of its commercialization in order to foresee following expand in related industries and increase in added value. First, Investment on the renewable energy technology development is in direct proportion both to the product and growth, but product shows slightly higher index under the same amount of R&D investment than growth. It indicates that advance in technology greatly influences the final product, the energy growth. Moreover, while R&D investment on renewable energy product as well as the government funds included in the investment have proportionate influence on the renewable energy growth, private investment in the total amount invested has reciprocal influence. This statistic shows that research and development is mainly driven by government funds rather than private investment. Finally, while R&D investment on renewable energy growth affects proportionately, government funds and private investment shows no direct relations, which indicates that the effects of research and development on renewable energy do not affect government funds or private investment. All of the results signify that although it is important to have government policy in technology development and commercialization, private investment and active participation of enterprises are the key to the success in the industry.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Economic and Environmental Geology
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• v.49 no.6
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• pp.459-467
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• 2016

Due to the limited areal space for installation, borehole heat exchangers (BHEs) at depths deeper than 300 m are considered for geothermal heating and cooling in the urban area. The deep vertical closed-loop BHEs are unconventional due to the depth and the range of the typical installation depth is between 100 and 200 m in Korea. The BHE in the study consists of 50A (outer diameter 50 mm, SDR 11) PE U-tube pipe in a 150 mm diameter borehole with the depth of 300 m. In order to compensate the buoyancy caused by the low density of PE pipe ($0.94{\sim}0.96g/cm^3$) in the borehole filled with ground water, 10 weight band sets (4.6 kg/set) were attached to the bottom of U-tube. A thermal response test (TRT) and fundamental basic surveys on the thermophysical characteristics of the ground were conducted. Ground temperature measures around $15^{\circ}C$ from the surface to 100 m, and the geothermal gradient represents $1.9^{\circ}C/100m$ below 100 m. The TRT was conducted for 48 hours with 17.5 kW heat injection, 28.65 l/min at a circulation fluid flow rate indicates an average temperature difference $8.9^{\circ}C$ between inlet and outlet circulation fluid. The estimated thermophysical parameters are 3.0 W/mk of ground thermal conductivity and 0.104 mk/W of borehole thermal resistance. In the stepwise evaluation of TRT, the ground thermal conductivity was calculated at the standard deviation of 0.16 after the initial 13 hours. The sensitivity analysis on the borehole thermal resistance was also conducted with respect to the PE pipe diameter and the thermal conductivity of backfill material. The borehole thermal resistivity slightly decreased with the increase of the two parameters.