• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• Journal of Neurogastroenterology and Motility
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• v.25 no.3
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• pp.343-362
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• 2019

Background/Aims There has been major progress in our understanding of the irritable bowel syndrome (IBS), and novel treatment classes have emerged. The Rome IV guidelines were published in 2016 and together with the growing body of Asian data on IBS, we felt it is timely to update the Asian IBS Consensus. Methods Key opinion leaders from Asian countries were organized into 4 teams to review 4 themes: symptoms and epidemiology, pathophysiology, diagnosis and investigations, and lifestyle modifications and treatments. The consensus development process was carried out by using a modified Delphi method. Results Thirty-seven statements were developed. Asian data substantiate the current global viewpoint that IBS is a disorder of gut-brain interaction. Socio-cultural and environmental factors in Asia appear to influence the greater overlap between IBS and upper gastrointestinal symptoms. New classes of treatments comprising low fermentable oligo-, di-, monosacharides, and polyols diet, probiotics, non-absorbable antibiotics, and secretagogues have good evidence base for their efficacy. Conclusions Our consensus is that all patients with functional gastrointestinal disorders should be evaluated comprehensively with a view to holistic management. Physicians should be encouraged to take a positive attitude to the treatment outcomes for IBS patients.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.6
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• pp.561-568
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• 2020

Wave measurements using X-band radar have many advantages compared to other wave gauges including wave-rider buoy, P-u-v gauge and Acoustic Doppler Current Profiler (ADCP), etc.. For example, radar system has no risk of loss/damage in bad weather conditions, low maintenance cost, and provides spatial distribution of waves from deep to shallow water. This paper presents new methods for estimating significant wave heights of X-band marine radar images using Artificial Neural Network (ANN). We compared the time series of estimated significant wave heights (Hs) using various estimation methods, such as signal-to-noise ratio (${\sqrt{SNR}}$), both and ${\sqrt{SNR}}$ the peak period (TP), and ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k). The estimated significant wave heights of the X-band images were compared with wave measurement using ADCP(AWC: Acoustic Wave and Current Profiler) at Hujeong Beach, Uljin, Korea. Estimation of Hs using ANN with 3 parameters (${\sqrt{SNR}}$, TP, and Rval > k) yields best result.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.6
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• pp.1-26
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• 2020

The term 'Unicorns' in the corporate ecosystem was firstly introduced by Aileen Lee in 2013. It has been actively discussed in South Korea particularly to compare the level of the 'start-up ecosystem' from a global perspective. Accordingly, the Korean government has recently set a policy goal 'to nurture 20 Korean unicorn companies by 2022'. While the phenomenon of 'Unicorn Club Company' has been brought to the level of policy objectives and spread more widely to the public, existing academic research to understand its substantial and underlying implications has been insufficient. First, in this study, the characteristics of 479 'Unicorn Club' companies in 2019 were analyzed in-depth. Previous research has focused on the general status and trend by analyzing the number of unicorn companies by country and industry classifications. However, this study conducted a qualitative exploratory analysis by investigating descriptive statistics about unicorn companies, including their investors, while providing case studies. Also, cluster analysis, ANOVA, and multi-level regression were employed for quantitative exploration. The characteristics of individual companies were examined based on the "ERIS Model (Entrepreneur - Industry(Market) - Resource - Strategy Model)". Secondly, factors influencing its valuations were examined in connection with the previously analyzed characteristic variables and investor characteristics. Finally, based on these, the future direction of the "Unicorn Phenomenon" from the perspective of "Enterprise Ecosystem" and productively using it from the perspective of the public policy is suggested.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.53-59
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• 2021

The marine transport industry generally applies new technologies later than other transport industries, such as airways and railways. Vessels require efficient operation, and their performance and lifespan depend on the level of maintenance and management. Many studies have shown that corrective maintenance (CM) and time-based maintenance (TBM) have restrictions with respect to enabling efficient maintenance of workload and cost to improve operational efficiency. Predictive maintenance (PdM) is an advanced technology that allows monitoring the condition and performance of a target machine to predict its time of failure and helps maintain the key machinery in optimal working conditions at all times. This study presents the development of a marine predictive maintenance (MPdM; maritime predictive maintenance) method based on applying PdM to the marine environment. The MPdM scheme is designed by considering the special environment of the marine transport industry and the extreme marine conditions. Further, results of the study elaborates upon the concept of MPdM and its necessity to advancing marine transportation in the future.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.918-940
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• 2021

In this study, the concept of eXtended Reality Devices(XR) is defined, how it is applied by industry and how it will develop in the future, and based on the expanded integrated technology acceptance theory and innovation resistance, We tried to confirm through empirical analysis how the influencing variables affect. We carry out the analysis of the hypotheses using PLS Structural Equation Modeling. According to the empirical analysis results, this study confirms that innovativeness has a significant effect on UTAUT2's acceptance variables(performance expectation, effort expectation, hedonic motivation, price value) for XR devices, and these variables affect attitudes and acceptance of XR. and the pace of change of XR has a significant effect on perceived risk, and the perceived risk perceived by consumers mediates the pace of change and innovation resistance, and has a significant effect on innovation resistance. and innovation resistance to XR devices had a significant negative effect on acceptance. This study has its meaning because it found out that it deals expansively and comprehensively with personal innovation, the UTAUT2's acceptance variables, and the effects of perceived risk factors mediating the pace of change and resistance to innovation. In addition, it suggests that in order for innovative technologies such as XR to advance to the stage of market expansion, it is important to present strategies to reduce resistance to new technologies as much as the value to be provided to consumers.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.130-137
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• 2021

This study evaluated newly introduced, commercial super sweet corn hybrids (Zea mays L.) for their potential as breeding materials. Agronomic traits were measured and variance components were obtained using a linear mixed model to estimate the heritability. The trials were carried out in 2018 at two locations (Haenam and Oksan in South Korea). All traits had low heritability, except for mid tasseling and silking days. These traits with low heritability mostly had low genetic variance component estimate. In case of ear height ratio, significant genotype by location appeared to be responsible for low genetic variance, which in turn led to low heritability. Low heritability estimates from the trials with commercial hybrids were perhaps because those hybrids were highly improved for commercial success. Hence, this does not necessarily point to them having poor potential as breeding materials. To overcome low heritability, significant genotype by environment interaction, and achieve high selection efficiency, intermating among hybrids is recommended to create new recombinants before inbred line development.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.3
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• pp.141-148
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• 2022

Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.

• Journal of Korean Library and Information Science Society
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• v.52 no.4
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• pp.229-253
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• 2021

The service strategy of the public library needs to be established based on the users who are the actual beneficiaries of the services, including the perspective of changes in the social environment. This study investigated and analyzed the users' perceptions of the library functions and services currently provided and the demand for future services, targeting public library users in the Busan area. The data were collected through a questionnaire, and the respondents were 733 public library users in Busan. The main result is that first, the role and function of the public library that Busan users consider most important was still in material collection and provision. Second, in the information service type, the demand for cultural/lifelong learning program service was the highest, and in the service program, the demand for new IT technology experience and education was the highest. Third, as a result of ISA analysis of information service type, material provision service and information literacy education service were types to be maintained, and reading related service was type to be managed intensively. Fourth, in the analysis of service demand by age, those aged 41 to 50 years old were the generation with the highest demand in all types except for the information literacy education service type, and the demand for information literacy education was the highest among the elderly generation over 61 years old. And the user group in the western part of Busan was higher than the user group in other regions in demand for almost all service types. The results of this study can be used as basic data when establishing strategies to optimize community public library services for users.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.208-216
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• 2022

Surface morphology and adsorption characteristics of black and white charcoals prepared from Korean traditional kiln were quantitatively analyzed. TGA and elemental analysis of charcoals were different from produced kiln, and thermal degradation temperature and carbon content of white charcoals were apparently higher than those of black charcoals. Surface morphology shows the activation progressed through the longitudinal direction of woods and new micropores were developed to radial direction on the surface of macropores as the furthermore activation resulting in the pore connection. BET adsorption isotherms show that there are low-pressure hysteresis due to the no desorption of adsorbates, which resulted in unique Type of charcoals overlapping Type I and Type IV. Such a low-pressure hysteresis is occurred from expansion of adsorbates, which were embedded in the micropore entrances and did not get out during the desorption run. The characteristics of charcoals such as specific surface area and pore size distribution did not show correct values depending on not only produced company but also sampling sites of one piece of charcoal. Therefore, it is not easy to suggest the quantitative characteristics of charcoals prepared from Korean traditional kiln. On the other hand, preparation the quality standard of charcoal is necessary for their special uses such as adsorbent.