• The Journal of the Korea Contents Association
• /
• v.21 no.11
• /
• pp.135-144
• /
• 2021

Recently, data-driven decision-making technology has become a key technology leading the data industry, and machine learning technology for this requires high-quality training datasets. However, real-world data contains missing values for various reasons, which degrades the performance of prediction models learned from the poor training data. Therefore, in order to build a high-performance model from real-world datasets, many studies on automatically imputing missing values in initial training data have been actively conducted. Many of conventional machine learning-based imputation techniques for handling missing data involve very time-consuming and cumbersome work because they are applied only to numeric type of columns or create individual predictive models for each columns. Therefore, this paper proposes a new data imputation technique called 'Denoising Self-Attention Network (DSAN)', which can be applied to mixed-type dataset containing both numerical and categorical columns. DSAN can learn robust feature expression vectors by combining self-attention and denoising techniques, and can automatically interpolate multiple missing variables in parallel through multi-task learning. To verify the validity of the proposed technique, data imputation experiments has been performed after arbitrarily generating missing values for several mixed-type training data. Then we show the validity of the proposed technique by comparing the performance of the binary classification models trained on imputed data together with the errors between the original and imputed values.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.8
• /
• pp.331-338
• /
• 2022

Successor representation (SR) is a model of human reinforcement learning (RL) mimicking the underlying mechanism of hippocampal cells constructing cognitive maps. SR utilizes these learned features to adaptively respond to the frequent reward changes. In this paper, we evaluated the performance of SR under the context where changes in latent variables of environments trigger the reward structure changes. For a benchmark test, we adopted SR-Dyna, an integration of SR into goal-driven Dyna RL algorithm in the 2-stage Markov Decision Task (MDT) in which we can intentionally manipulate the latent variables - state transition uncertainty and goal-condition. To precisely investigate the characteristics of SR, we conducted the experiments while controlling each latent variable that affects the changes in reward structure. Evaluation results showed that SR-Dyna could learn to respond to the reward changes in relation to the changes in latent variables, but could not learn rapidly in that situation. This brings about the necessity to build more robust RL models that can rapidly learn to respond to the frequent changes in the environment in which latent variables and reward structure change at the same time.

• Korean Journal of Culture and Social Issue
• /
• v.17 no.4
• /
• pp.435-459
• /
• 2011

The present study explored Korean parents' perceptions of and behavior toward game use among teenagers in Korea. A total of 600 Korean mothers of teenagers residing in Seoul and five other metropolitan areas participated in the survey. The survey was constructed based on five categories of variables, including the overall perception of games and game use, specific attitudes toward game use, cognitions about and attitudes toward game addiction, factors predicting parental monitoring of children's game use, and views and opinions about what needs to be done to promote healthy game cultures as well as to prevent problematic game use among teenagers in Korea. Results indicate that the respondents' overall perceptions of and attitudes toward games and game use are negative. In contrast, attitudes toward game use of the respondent's own child are contingent upon various comparison standards. Results also indicate that the respondents tend to overestimate the possibility that their own child is addicted to games, and their perceptions of game addiction are based on a narrow range of behavioral symptoms. Additional analyses indicate that parental monitoring of teenagers' game use can be predicted by the theoretical model driven from Ajzen(1991)'s theory of planned behavior. Finally, results also indicate that, in order to deal with the problems associated with teenagers' game use, proactive approaches to promote healthy game cultures as well as various initiatives to prevent problematic game use are necessary. Implications of the findings and future direction were discussed.

• The Journal of Bigdata
• /
• v.6 no.2
• /
• pp.71-84
• /
• 2021

Since small and medium-sized enterprises fell short of the securement of technological competitiveness in the field of big data and artificial intelligence (AI) field-core technologies of the Fourth Industrial Revolution, it is important to strengthen the competitiveness of the overall industry through technology commercialization. In this study, we aimed to propose a priority related to technology transfer and commercialization for practical use of public research results. We utilized public research performance information, improving missing values of 6T classification by deep learning model with an ensemble method. Then, we conducted topic modeling to derive the converging fields of big data and AI. We classified the technology fields into four different segments in the technology portfolio based on technology activity and technology efficiency, estimating the potential of technology commercialization for those fields. We proposed a priority of technology commercialization for 10 detailed technology fields that require long-term investment. Through systematic analysis, active utilization of technology, and efficient technology transfer and commercialization can be promoted.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.4D
• /
• pp.469-476
• /
• 2008

Recently, TOD gains popularity as a traffic solution measure of high density urban regeneration projects. The purpose of this study is to investigate traffic impacts of high density TOD projects, and to identify the issues to be resolved. For a case study, it chooses Gangnamgucheong station in Gangnam area served by two subway lines, and designates 400m radius from the station as a site for high-density development. The MOEs chosen for this study is traffic volume, time, distance, speed, and mode share. The SECOM model is adopted for traffic simulation. The analysis results show that high-density TOD is an effective tool for traffic improvement even with only one station area being implemented. It is found that the traffic volume increases near the station in nature where high-density development occurs, but it declines overall in the rest of Gangam area. The total travel time and distance of passenger vehicles decline, meaning that the traffic condition becomes better than before. With regulation on parking supply, the improvement becomes more vivid. In terms of the changes of traffic speed, both alternatives show 4.1% increase in speed, but the difference between alternatives is not quite noticeable because of the induced vehicle demand driven to the streets with improved traffic condition. The mode share changes occur for the benefit of subway ridership, because the study station is equipped with two subway line services. When mixed with parking supply restriction, the impact becomes clearer.

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

• BMB Reports
• /
• v.57 no.6
• /
• pp.281-286
• /
• 2024

Adult hippocampal neurogenesis plays a pivotal role in maintaining cognitive brain function. However, this process diminishes with age, particularly in patients with neurodegenerative disorders. While small, non-coding microRNAs (miRNAs) are crucial for hippocampal neural stem (HCN) cell maintenance, their involvement in neurodegenerative disorders remains unclear. This study aimed to elucidate the mechanisms through which miRNAs regulate HCN cell death and their potential involvement in neurodegenerative disorders. We performed a comprehensive microarray-based analysis to investigate changes in miRNA expression in insulin-deprived HCN cells as an in vitro model for cognitive impairment. miR-150-3p, miR-323-5p, and miR-370-3p, which increased significantly over time following insulin withdrawal, induced pronounced mitochondrial fission and dysfunction, ultimately leading to HCN cell death. These miRNAs collectively targeted the mitochondrial fusion protein OPA1, with miR-150-3p also targeting MFN2. Data-driven analyses of the hippocampi and brains of human subjects revealed significant reductions in OPA1 and MFN2 in patients with Alzheimer's disease (AD). Our results indicate that miR-150-3p, miR-323-5p, and miR-370-3p contribute to deficits in hippocampal neurogenesis by modulating mitochondrial dynamics. Our findings provide novel insight into the intricate connections between miRNA and mitochondrial dynamics, shedding light on their potential involvement in conditions characterized by deficits in hippocampal neurogenesis, such as AD.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.14 no.2
• /
• pp.63-68
• /
• 1978

A boat seine has been used as a major fishing gear for catching anchovy (Engraulis japonica) in the southern coastal waters of Korea since the 1920s. Since the 1950s some improvement from the original seine has been made; powered boats equipped with net hauler has been used instead of rowing boats with hand-driven capstan, and the seining method has been changed into the trawling method. But even now, there are many problems to be solved in the view point of decreasing man power without decreasing catching efficiency. For the purpose, patti-net has been introduced from Japan and experimented on the commercial base since 1972, and it was known that the patti-net could be operated with man power as half as needed in the coventional net, but catching efficiency was not so desirable. Therefore, the study on the characteristics of it were required. The authors carried out a model experiment with a Qne-twentieth scale model net towed by a powered boat on the sea. The obtained results run as follows: 1. Hydrodynamic resistance of the model net can be explained as $R_p=69.6 V_{I.66}$ $R_h=37 v^2$ where $R_p$ and $R_b$ denote the resistance of the whole gear and the cod end in kg respectively, and v the towing speed in mlsec. 2. Performance of wing and cod end showed no deformation such as observed at the conventional net. 3. The ratio of opening at the entrance of bag net to that of cod end showed about 2: 1. Therefore, when we intend to enlarge the net to be able to operate in the deep fishing ground, the cod end should be enlarged in the same proportion and increased towing power is needed .. Then, it will be better to increase the ratio for increasing fishing efficiency without increasing towing power.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.24 no.2
• /
• pp.63-77
• /
• 2022

Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.5
• /
• pp.91-107
• /
• 2023

Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.