• The Journal of Society for e-Business Studies
• /
• v.25 no.4
• /
• pp.77-109
• /
• 2020

In this paper, we build a gradient Boosting model to predict government SME R&D subsidy, select features of high importance, and measure the impact of each features to the predicted subsidy using PDP and SHAP value. Unlike previous empirical researches, we focus on the effect of the R&D subsidy distribution pattern to the incentive of the firms participating subsidy competition. We used the firm data constructed by KISTEP linking government R&D subsidy record with financial statements provided by NICE, and applied a Gradient Boosting model to predict R&D subsidy. We found that firms with higher R&D performance and larger R&D investment tend to have higher R&D subsidies, but firms with higher operation profit or total asset turnover rate tend to have lower R&D subsidies. Our results suggest that current government R&D subsidy distribution pattern provides incentive to improve R&D project performance, but not business performance.

• Journal of the Korean School Mathematics Society
• /
• v.24 no.1
• /
• pp.39-57
• /
• 2021

In this study, mathematical analysis is conducted by focusing to the 'size' of the 'point' and the 'line'. The textbook descriptions of the 'point' and the 'line' in the geometry content area of middle school mathematics 1 by the 2015 revised Korean mathematics curriculum and US geometry textbooks were compared and analyzed between. First, as a result of mathematical analysis of' 'the size of a point and a segment', it was found that the mathematical perspectives could be different according to 1) the size of a point is based on the recognition and exclusion of 'infinitesimal', and 2) the size of the segment is based on the 'measure theory' and 'set theory'. Second, as a result of analyzing textbook descriptions of the 'point' and the 'line', 1) in the geometry content area of middle school mathematics 1 by the 2015 revised Korean mathematics curriculum, after presenting a learning activity that draws a point with 'physical size' or line, it was developed in a way that describes the 'relationship' between points and lines, but 2) most of the US geometry textbooks introduce points and lines as 'undefined terms' and explicitly states that 'points have no size' and 'lines have no thickness'. Since the description of points and lines in the geometry content area of middle school mathematics 1 by the 2015 revised Korean mathematics curriculum may potentially generate mathematical intuitions that do not correspond to the perspective of Euclid geometry, this study suggest that attention is needed in the learning process about points and lines.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_1
• /
• pp.1047-1056
• /
• 2022

Sea ice, frozen sea water, in the Artic is a primary indicator of global warming. Due to its importance to the climate system, shipping-route navigation, and fisheries, Arctic sea ice prediction has gained increased attention in various disciplines. Recent advances in artificial intelligence (AI), motivated by a desire to develop more autonomous and efficient future predictions, have led to the development of new sea ice prediction models as alternatives to conventional numerical and statistical prediction models. This study aims to evaluate the performance of the two-stream convolutional long-and short-term memory (TS-ConvLSTM) AI model, which is designed for learning both global and local characteristics of the Arctic sea ice changes, for the minimum September Arctic sea ice from 2001 to 2021, and to show the possibility for an operational prediction system. Although the TS-ConvLSTM model generally increased the prediction performance as training data increased, predictability for the marginal ice zone, 5-50% concentration, showed a negative trend due to increasing first-year sea ice and warming. Additionally, a comparison of sea ice extent predicted by the TS-ConvLSTM with the median Sea Ice Outlooks (SIOs) submitted to the Sea Ice Prediction Network has been carried out. Unlike the TS-ConvLSTM, the median SIOs did not show notable improvements as time passed (i.e., the amount of training data increased). Although the TS-ConvLSTM model has shown the potential for the operational sea ice prediction system, learning more spatio-temporal patterns in the difficult-to-predict natural environment for the robust prediction system should be considered in future work.

• Journal of the Korean Institute of Landscape Architecture
• /
• v.50 no.6
• /
• pp.42-57
• /
• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.

• Journal of Gifted/Talented Education
• /
• v.11 no.3
• /
• pp.131-153
• /
• 2001

The importance of identifying gifted children during early childhood is becoming recognized. Nonetheless, most researchers preferred to study the primary and secondary levels where children are already and more clearly demonstrating what talents they have, and where more reliable predictions of gifted may be made. Comparatively lisle work has been done in this area. When we identify giftedness during early childhood, we have to consider the potential of the young children rather than on actual achievement. Giftedness during early childhood is still developing and less stable than that of older children and this prevents us from making firm and accurate predictions based on children's actual achievement. Dynamic assessment, based on Vygotsky's concept of the zone of proximal development(ZPD), suggests a new idea in the way the gifted young children are identified. In light of dynamic assessment, for identifying the potential giftedness of young children. we need to involve measuring both unassisted and assisted performance. Dynamic assessment usually consists of a test-intervene-retest format that focuses attention on the improvement in child performance when an adult provides mediated assistance on how to master the testing task. The advantages of the dynamic assessment are as follows: First, the dynamic assessment approach can provide a useful means for assessing young gifted child who have not demonstrated high ability on traditional identification method. Second, the dynamic assessment approach can assess the learning process of young children. Third, the dynamic assessment can lead an individualized education by the early identification of young gifted children. Fourth, the dynamic assessment can be a more accurate predictor of potential by linking diagnosis and instruction. Thus, it can make us provide an educational treatment effectively for young gifted children.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.61 no.6
• /
• pp.111-121
• /
• 2019

Evapotranspiration (ET) of vegetation is one of the major components of the hydrologic cycle, and its accurate estimation is important for hydrologic water balance, irrigation management, crop yield simulation, and water resources planning and management. For agricultural crops, ET is often calculated in terms of a short or tall crop reference, such as well-watered, clipped grass (reference crop evapotranspiration, $ET_o$). The Penman-Monteith equation recommended by FAO (FAO 56-PM) has been accepted by researchers and practitioners, as the sole $ET_o$ method. However, its accuracy is contingent on high quality measurements of four meteorological variables, and its use has been limited by incomplete and/or inaccurate input data. Therefore, this study evaluated the applicability of Backpropagation Neural Network (BPNN) model for estimating $ET_o$ from less meteorological data than required by the FAO 56-PM. A total of six meteorological inputs, minimum temperature, average temperature, maximum temperature, relative humidity, wind speed and solar radiation, were divided into a series of input groups (a combination of one, two, three, four, five and six variables) and each combination of different meteorological dataset was evaluated for its level of accuracy in estimating $ET_o$. The overall findings of this study indicated that $ET_o$ could be reasonably estimated using less than all six meteorological data using BPNN. In addition, it was shown that the proper choice of neural network architecture could not only minimize the computational error, but also maximize the relationship between dependent and independent variables. The findings of this study would be of use in instances where data availability and/or accuracy are limited.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
• /
• v.18 no.3
• /
• pp.142-161
• /
• 2013

In order to enhance scientific interest and a sense of affinity about ocean, the programs of the oceanic camp 'oceanic summer school' were developed and applied to $4^{th}$ and $9^{th}$-grade elementary and middle school students for 9 years from 2004 to 2012. It was composed of oceanic training for snorkeling, a tour to oceanic institutes and museums near the camp academy place, experimental learning in oceanic-related field, field trips for ocean and earth sciences, and lectures on various subjects of ocean. We developed and implemented 9-kinds of inquiry surveys to evaluate changes in cognitive and affective characteristics, and ocean literacy of students participated at the present oceanic summer camp. Based on the statistical analysis, affective characteristics such as interest, inquisitiveness, passion, and so on, were enhanced. Analysis of ocean literacy revealed that cognitive characteristics of the students were increased by 40%. We presented parents' responses on the programs of oceanic summer school. Some students with less initial interest of ocean have positively changed to make up their minds to be a oceanographer in several years later. In light of this, the summer school can be evaluated to be successfully functioned as a long-term support system for potentially young-talented students in the field of ocean science. This study addresses that long-term implementation of the summer oceanic camp may trigger students with potential talent toward in-depth science in the near future even though it could not bring positive effect immediately. This addresses the necessity of policy supports in order that various programs like the scientific camp should be more constructively developed and executed for next-generation manpower in oceanographic fields.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.9 no.1
• /
• pp.25-32
• /
• 2014

Action learning takes advantage of innovative management tool but not more to small business than five employees. It is difficult to utilize to them. As a case to solve this problem, this study investigates GNTECH(Gyeongnam National University of Science and Technology)'entrepreneurship training and consulting convergence program. This program is applied to the development and operation of the start-up entrepreneur. Project participants are three groups those are graduate students, undergraduate students and professor. Professor has a role as facilitater. This case has the following meanings. First, by participating in entrepreneurship courses, undergraduate students experience entrepreneurship and mindset can be expected. Second, the start-up entrepreneur has the opportunity to directly verify the item. The consumer's perspective is the use of collective intelligence through team activities carried out in the process. Third, students of graduate and undergraduate has a chance learning facilitator function from professor. The results of this study provide conjunction between university educational programs based on entrepreneurship.

• Journal of Elementary Mathematics Education in Korea
• /
• v.19 no.3
• /
• pp.409-434
• /
• 2015

The purpose of this study was to investigate the influences of teaching mathematics for social justice on students'interest towards mathematics and perceptions of mathematical values. Eighteen 6th grade students, at B elementary school in Seocho-gu, Seoul, who wished to involved in the study participated in the 10 hour lessons. During the lessons for social justice, the researchers analyzed the students' reactions in the lessons according to the three categories: Perceiving given problematic situations of social conflicts, searching for problem-solving methods based on mathematical analysis, and changing social behaviors to solve life issues through mathematics. They also examined changes of students' interest towards mathematics and perceptions of mathematical values through the activities and reactions using the preliminary questionnaires, observations of lessons, and students' activity sheets. The research results showed that the students perceived mathematics as a tool for social justice in mathematics lessons, tried to find problem-solving methods based on mathematical analysis, and expressed their active social behaviors by cultivating the will of practice to solve life issues through mathematics. Based on those findings, the study reached the following conclusions. First, the students recognize many of the social problems in their societies as social justice regardless of their economic levels. Second, learning activities need to design in a way that students can accept the social problems as realistic situations in teaching mathematics for social justice. Third, students look at the world from a mathematical perspective, have interest in mathematics, and recognize the values of mathematics in teaching mathematics for social justice.

• Information Systems Review
• /
• v.11 no.3
• /
• pp.125-146
• /
• 2009

The emergence of open source software(OSS) with its most prominent advantages creates a vast interest among practitioners. A study on Linux, the most well-known OSS, estimated that it would cost as 5.4 billion Euros taking over 73,000 person-years if it had been developed by conventional means. However, Linux has achieved only 0.65 percent of the operating system market for individual users while Microsoft windows family counts for nearly 90 percent of the market. Much of the effort being spent in the development of OSS is going to waste and potential value that OSS can bring to users is not being realized. Adoption of OSS is often accompanied by the discontinuance of existing software that is already in place. If users resist changing, they may not adopt OSS. Using the case of Linux, this study examines user resistance to change from the commercial operating software to the free operating system. This study identifies six sub-types of switching costs (uncertainty, emotional, setup, learning, lost benefit, and sunk costs) and tests their effects on user resistance to change based on a survey of 201 users. The results show that user resistance to change has a negative impact on the adoption of OSS. Further, this study shows that uncertainty and emotional costs have significant effects on user resistance to change. Beyond previous research on technology adoption, this research contributes towards an understanding of the switching costs leading to user resistance to change and offers suggestions to OSS practitioners for developing strategies to improve the adoption of OSS.