Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.14
no.1
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pp.1-15
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2019
The purpose of this study is to analyze the relationship between entrepreneurship and entrepreneurial intention. This relationship has been conceptually addressed in many previous studies and has been empirically tested. However, this study is different from the previous studies in the following four points. First, we measured entrepreneurial intention by manipulating launching a start-up as a relative concept for employment, which is consistent with the conceptual definition of entrepreneurial intention (i.e. entrepreneurial decision making in the process of career choice). Second, it is distinguished from previous researches in that it uses the question of preference for "action" with regard to job choice. Third, we expanded the opportunity for discussion using the youth panel data of the Korea Employment Information Service. Fourth, the altruistic purpose is included in the category of entrepreneurship. Empirical results showed that intentions of entrepreneurship were stronger when the need for achievement was intense, internal control tendency was intended, risk-taking propensity was sturdy, and autonomous tendency was high. However, innovation and aggressiveness are not statistically related to entrepreneurial intention. On the other hand, the altruistic tendency was found to have a negative correlation with entrepreneurial intention. The results of this study can provide meaningful implications for both private sector investors and government policy makers.
The purpose of this study is to classify the lifelong learning policy implementation process of lifelong learning in Korea according to the policy making decision models and to suggest developmental tasks. Korea's lifelong learning policy came to a full-fledged start with the enactment of the Lifelong Education Act in 2000. The Lifelong Education Act proposed the establishment of an open educational system as a strategy to realize the lifelong learning society. According to the Lifelong Education Act, the Korean government has developed several lifelong education policies such as providing learning opportunity for the underprivileged, facilitating lifelong learning city project, building lifelong learning culture, recognizing of experiential learning result, funding lifelong learning hub university, launching lifelong learning supporting administrative etc. The Korean lifelong system is characterized as Allison's (1971) governmental/bureaucratic, Ziegler and Johnson's (1972) legislative, Griffin's(1987) social control and Green's (2000) state-led models which make policy through the coordination between the government and the parliament and control bureaucratic power and educational qualifications. Lifelong learning policies should be managed in terms of supply and demand at the learning market. In addition, the state has to strengthen lifelong learning through supporting NGOs' activities and adult learners' tuition fee for the disadvantaged group of people.
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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v.37
no.1
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pp.29-42
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2019
In order to expand the qualitative aspects of public facility, this study used SNS data to derive user-oriented preference factors for public facilities and then were quantified in terms of supply side and demand side. To derive preference factor, LDA, one of topic modeling, was used and attraction index was calculated for each facility. In addition we analyzed spatial accessibility to measure the degree of service experience of users by using 2SFCA model. The study area covered public libraries of Seoul, Korea. As a result of study, five topics were extracted as preference factors for the public library: Circumstance, Scale of facility, Cultural program, Parenting, Books and materials. In particular topic of circumstance and parenting were newly derived preference factors unknown in previous studies. As a result of calculating attraction index for each library, the index of Songpa Library, Jungdok Library, and Namsan Library was high. Songpa library has received good evaluation in parenting factor, and Jungdok & Namsan library in circumstance factor. The accessibility of each region seems to better in center of Seoul where public libraries are crowded, but shrinking toward the outskirts. We expect that the proposed method will contribute to user-oriented public facility evaluation and policy decision making.
In this study, a novel virtual reality (VR) experience environment is proposed for enabling walking adaptation of visually impaired people. The core of proposed VR environment is based on immersive walking interactions and deep learning based braille blocks recognition. To provide a realistic walking experience from the perspective of visually impaired people, a tracker-based walking process is designed for determining the walking state by detecting marching in place, and a controller-based VR white cane is developed that serves as the walking assistance tool for visually impaired people. Additionally, a learning model is developed for conducting comprehensive decision-making by recognizing and responding to braille blocks situated on roads that are followed during the course of directions provided by the VR white cane. Based on the same, a VR application comprising an outdoor urban environment is designed for analyzing the VR walking environment experience. An experimental survey and performance analysis were also conducted for the participants. Obtained results corroborate that the proposed VR walking environment provides a presence of high-level walking experience from the perspective of visually impaired people. Furthermore, the results verify that the proposed learning algorithm and process can recognize braille blocks situated on sidewalks and roadways with high accuracy.
Journal of the Korea Society of Computer and Information
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v.26
no.4
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pp.1-9
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2021
In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.
This study applied the e-PBL (e-Project-based learning) method for "Urban Forest Management" courses in the Department of Forest Science at S University to progress in university forest education. e-PBL effectively motivates self-directed learning, problem-solving, communication skills, and learners' responsibility by enabling them to choose, design, and perform their projects. Due to the COVID-19 pandemic in 2020, learners were encouraged to use online media to carry out projects and submit presentations for the campus forest. Learners' educational effects were subsequently investigated through a five-point Likert scale. This study discovered a positive effect on learners' motivation and interest (4.17) through e-PBL. Learners responded that e-PBL also helped their understanding regarding the subject (4.17). In addition, this study provided evidence that the e-PBL method was helpful in problem-solving (4.25), communication (4.33), and decision-making skills (4.21). According to learners' responses, there are positive indications that learners were satisfied with e-PBL. Learners responded that interactions and communications with team members could improve their understanding of the subject. Hence, there is scope for improving an efficient and successful e-PBL model suitable for university forest education by providing more efficient instructional time management, e-PBL method guidelines, and institutional support.
Investors mainly use PER and PBR among financial ratios for valuation and investment decision-making. I conduct an analysis of two basic financial ratios from a statistical perspective. Financial ratios contain key accounting numbers which reflect firm fundamentals and are useful for valuation or risk analysis such as enterprise credit evaluation and default prediction. The distribution of financial data tends to be extremely heavy-tailed, and PER and PBR show exceedingly high level of kurtosis and their extreme cases often contain significant information on financial risk. In this respect, Extreme Value Theory is required to fit its right tail more precisely. I introduce not only GPD but exGPD. GPD is conventionally preferred model in Extreme Value Theory and exGPD is log-transformed distribution of GPD. exGPD has recently proposed as an alternative of GPD(Lee and Kim, 2019). First, I conduct a simulation for comparing performances of the two distributions using the goodness of fit measures and the estimation of 90-99% percentiles. I also conduct an empirical analysis of Information Technology firms in Korea. Finally, exGPD shows better performance especially for PBR, suggesting that exGPD could be an alternative for GPD for the analysis of financial ratios.
In this study, the main influencing factors of the occurrence of cyanobacteria at each of the eight Multifunctional weirs were derived using a random forest, and a categorical prediction model based on a Algal bloom warning system was developed. As a result of examining the importance of variables in the random forest, it was found that the upstream points were directly affected by weir operation during the occurrence of cyanobacteria. This means that cyanobacteria can be managed through efficient security management. DO and E.C were indicated as major influencers in midstream. The midstream section is a section where large-scale industrial complexes such as Gumi and Gimcheon are concentrated as well as the emissions of basic environmental facilities have a great influence. During the period of heatwave and drought, E.C increases along with the discharge of environmental facilities discharged from the basin, which promotes the outbreak of cyanobacteria. Those monitoring sites located in the middle and lower streams are areas that are most affected by heat waves and droughts, and therefore require preemptive management in preparation for the outbreak of cyanobacteria caused by drought in summer. Through this study, the characteristics of cyanobacteria at each point were analyzed. It can provide basic data for policy decision-making for customized cyanobacteria management.
The high-tech industry, a leader in the national economy, has a larger investment cost compared to general buildings, a shorter construction period, and requires continuous investment. Therefore, accurate construction cost prediction and quick decision-making are important factors for efficient cost and process management. Overseas, the construction information classification system has been standardized since 1980 and has been continuously developed, improving construction productivity by systematically collecting and utilizing project life cycle information. At domestic construction sites, attempts have been made to standardize the classification system of construction information, but it is difficult to achieve continuous standardization and systematization due to the absence of a standardization body and differences in cost and process management methods for each construction company. Particular, in the case of the high-tech industry, the standardization and systematization level of the construction information classification system for high-tech facility construction is very low due to problems such as large scale, numerous types of work, complex construction and security. Therefore, the purpose of this study is to construct a construction information classification system suitable for high-tech facility construction through collection, classification, and analysis of related project data constructed in Korea. Based on the WBS (Work Breakdown Structure) and CBS (Cost Breakdown Structure) classified and analyzed through this study, a code system through hierarchical classification was proposed, and the cost model of buildings by linking WBS and CBS was three-dimensionalized and the utilized method was presented. Through this, an information classification system based on inter-relationships can be developed beyond the one-way tree structure, which is a general construction information classification system, and effects such as shortening of construction period and cost reduction will be maximized.
Park, Musun;Hwang, Minwoo;Lee, Jeongyun;Kim, Chang-Eop;Kwon, Young-Kyu
Journal of Physiology & Pathology in Korean Medicine
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v.36
no.2
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pp.73-78
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2022
Since Traditional Korean medicine (TKM) doctors use various knowledge systems during treatment, diagnosis results may differ for each TKM doctor. However, it is difficult to explain all the reasons for the diagnosis because TKM doctors use both explicit and implicit knowledge. In this study, an upgraded random forest (RF)-based evaluation tool was proposed to extract clinical knowledge of TKM doctors. Also, it was confirmed to what extent the professor's clinical knowledge was delivered to the trainees by using the evaluation tool. The data used to construct the evaluation tool were targeted at 106 people who visited the Sasang Constitutional Department at Kyung Hee University Korean Medicine Hospital at Gangdong. For explicit knowledge extraction, four TKM doctors were asked to express the importance of symptoms as scores. In addition, for implicit knowledge extraction, importance score was confirmed in the RF model that learned the patient's symptoms and the TKM doctor's constitutional determination results. In order to confirm the delivery of clinical knowledge, the similarity of symptoms that professors and trainees consider important when discriminating constitution was calculated using the Jaccard coefficient. As a result of the study, our proposed tool was able to successfully evaluate the clinical knowledge of TKM doctors. Also, it was confirmed that the professor's clinical knowledge was delivered to the trainee. Our tool can be used in various fields such as providing feedback on treatment, education of training TKM doctors, and development of AI in TKM.
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