In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.
There are about 400, 000 Korean ethnics living in Central Asia. Most of Koreans in Central Asia are leading a stable middle class life mostly engaged in farm work. With increase of educational attainment of their children, a number of Koreans are launching into political and academic circles as well as in the cultural world or the press. In recent years, however, the countries in this area(Uzbekistan and Kazakstan) for this study advocate an ethnic united policy to stabilize the politics and society and to carry out efficient transformation from the former socialistic economy to a market oriented economy. In addition, they are trying to recover the culture and the language of each nation which has been forgotten in the assimilation of Russia policy. Koreans have difficulty in adaption to this kind of change. In fact, a number of Koreans lost traditional culture and could not speak their mother language - Korean. Although they more or less maintain national consciousness, they recognize Uzbekistan or Kazakstan as their nation politically. They associated with North Korea unilaterally before the launching of the Perestroika policy. But after the Seoul Olympics held in 1998, there was movement to know and understand South Korea. There has been increased in the investment by Korean companies in Central Asia. Now, what is an alternative idea for Korean community consciousness\ulcorner It can be summarized as follows: 1) The increase of aid to Korean education institute : Considering the last few decades of Russia's strong racial assimilation policy, which leads most Koreans to lost their language and national culture, the priority should go to Koreans education. 2) Local Korean press support : Though Korean newspaper are published and Korean broadcasting is on the air currently in Uzbekistan and Kazakstan, they are suffering from qualified staff and poor financial status. Therefore, positive support should be established for these Korean mass communication media outlets to recover their own function and expand their dissemination powers quickly. 3) Research on the actual condition for Korean Community : It is essential to directly examine the local Korean community's regional distribution, population structure, Korean group's formation and operation, social and cultural understanding, racial consciousness, hope for their mother land and much more. 4) Increase of mother land and education opportunity : To stir up national culture and national consciousness within the Korean community, it is necessary to expand continuous opportunities for mother land visits and education training for local Koreans, especially for second and third generations.
There is a large difference between purchasing patterns in an online shopping mall and in an offline market. This difference may be caused mainly by the difference in accessibility of online and offline markets. It means that an interval between the initial purchasing decision and its realization appears to be relatively short in an online shopping mall, because a customer can make an order immediately. Because of the short interval between a purchasing decision and its realization, an online shopping mall transaction usually contains fewer items than that of an offline market. In an offline market, customers usually keep some items in mind and buy them all at once a few days after deciding to buy them, instead of buying each item individually and immediately. On the contrary, more than 70% of online shopping mall transactions contain only one item. This statistic implies that traditional data mining techniques cannot be directly applied to online market analysis, because hardly any association rules can survive with an acceptable level of Support because of too many Null Transactions. Most market basket analyses on online shopping mall transactions, therefore, have been performed by expanding the co-occurrence criteria of traditional association rule mining. While the traditional co-occurrence criteria defines items purchased in one transaction as concurrently purchased items, the expanded co-occurrence criteria regards items purchased by a customer during some predefined period (e.g., a day) as concurrently purchased items. In studies using expanded co-occurrence criteria, however, the criteria has been defined arbitrarily by researchers without any theoretical grounds or agreement. The lack of clear grounds of adopting a certain co-occurrence criteria degrades the reliability of the analytical results. Moreover, it is hard to derive new meaningful findings by combining the outcomes of previous individual studies. In this paper, we attempt to compare expanded co-occurrence criteria and propose a guideline for selecting an appropriate one. First of all, we compare the accuracy of association rules discovered according to various co-occurrence criteria. By doing this experiment we expect that we can provide a guideline for selecting appropriate co-occurrence criteria that corresponds to the purpose of the analysis. Additionally, we will perform similar experiments with several groups of customers that are segmented by each customer's average duration between orders. By this experiment, we attempt to discover the relationship between the optimal co-occurrence criteria and the customer's average duration between orders. Finally, by a series of experiments, we expect that we can provide basic guidelines for developing customized recommendation systems. Our experiments use a real dataset acquired from one of the largest internet shopping malls in Korea. We use 66,278 transactions of 3,847 customers conducted during the last two years. Overall results show that the accuracy of association rules of frequent shoppers (whose average duration between orders is relatively short) is higher than that of causal shoppers. In addition we discover that with frequent shoppers, the accuracy of association rules appears very high when the co-occurrence criteria of the training set corresponds to the validation set (i.e., target set). It implies that the co-occurrence criteria of frequent shoppers should be set according to the application purpose period. For example, an analyzer should use a day as a co-occurrence criterion if he/she wants to offer a coupon valid only for a day to potential customers who will use the coupon. On the contrary, an analyzer should use a month as a co-occurrence criterion if he/she wants to publish a coupon book that can be used for a month. In the case of causal shoppers, the accuracy of association rules appears to not be affected by the period of the application purposes. The accuracy of the causal shoppers' association rules becomes higher when the longer co-occurrence criterion has been adopted. It implies that an analyzer has to set the co-occurrence criterion for as long as possible, regardless of the application purpose period.
Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.
There are about 400, 000 Korean ethnics living in Central Asia. Most of Koreans in Central Asia are leading a stable middle class life mostly engaged in farm work. With increase of educational attainment of their children, a number of Koreans are launching into political and academic circles as well as in the cultural world or the press. In recent years, however, the countries in this area(Uzbekistan and Kazakstan) for this study advocate an ethnic united policy to stabilize the politics and society and to carry out efficient transformation from the former socialistic economy to a market oriented economy. In addition, they are trying to recover the culture and the language of each nation which has been forgotten in the assimilation of Russia policy. Koreans have difficulty in adaption to this kind of change. In fact, a number of Koreans lost traditional culture and could not speak their mother language - Korean. Although they more or less maintain national consciousness, they recognize Uzbekistan or Kazakstan as their nation politically. They associated with North Korea unilaterally before the launching of the Perestroika policy. But after the Seoul Olympics held in 1998, there was movement to know and understand South Korea. There has been increased in the investment by Korean companies in Central Asia. Now, what is an alternative idea for Korean community consciousness\ulcorner It can be summarized as follows: 1) The increase of aid to Korean education institute : Considering the last few decades of Russia's strong racial assimilation policy, which leads most Koreans to lost their language and national culture, the priority should go to Koreans education. 2) Local Korean press support : Though Korean newspaper are published and Korean broadcasting is on the air currently in Uzbekistan and Kazakstan, they are suffering from qualified staff and poor financial status. Therefore, positive support should be established for these Korean mass communication media outlets to recover their own function and expand their dissemination powers quickly. 3) Research on the actual condition for Korean Community : It is essential to directly examine the local Korean community's regional distribution, population structure, Korean group's formation and operation, social and cultural understanding, racial consciousness, hope for their mother land and much more. 4) Increase of mother land and education opportunity : To stir up national culture and national consciousness within the Korean community, it is necessary to expand continuous opportunities for mother land visits and education training for local Koreans, especially for second and third generations.
This study purported to investigate the current state of human rights of older adults residing in rural areas of Korea. The study utilized, as an analytic framework, 4 priority directions (1. "older persons and development", 2. "rural area development", 3. "advancing health and well-being into old age", and 4. "ensuring enabling and supportive environments") with 13 task actions recommended by Madrid International Plan of Action on Ageing (MIPAA). Furthermore, the study examined gender differences in all items included in the analytic framework. Data was collected by the face-to-face survey on 800 subjects aged 65 and over. Statistical analyses were conducted using STATA 13.0 program. The main results were summarized in order of 4 priority directions as follows. First, average working hours per day were 6.2, and men reportedly participated in economic activities and needed job training more than women, while women participated in lifelong education programs more than men. Awareness of fire and disaster prevention facilities was low in both genders. Second, accessibility to the support center for the elderly living alone as well as protective services for the vulnerable elderly was found to be low. IT-based services and networking were used more by men than women, and specifically, IT-based financial transactions and welfare services were least used. Third, medical check-ups and vaccinations were well received, while consistent treatments for chronic illnesses and long-term care services were relatively less given. In addition, accessibility to mental health service centers was considerably low. Fourth, although old house structures and the lack of convenience facilities were found to be circumstantial risk factors for these elders, experiences of receiving housing support services were scarce. The elderly were found to rely more on informal care, and concerns for their care were higher in women than men. Plus, accessibility to elderly abuse services was markedly low. Based on these results, discussed were implications for implementing policies and practical interventions to raise the levels of the human rights for this population.
In this article, I suggest issues and tasks in transmission of Gyeonggi Province folk songs after thorough study of designation of Gyeonggi Province folk songs as intangible cultural asset, reproduction and transmission. Intangible cultural assets are classified into seasonal playing and songs. Originally, category or extension of folk songs is above mere songs and it also embraces personal lives as well as village communities. Intangible assets of folk songs are folk art, group events and non-stage events at the same time based on tradition, history, uniqueness, characters of field value. Gyeonggi Province has 9 intangible assets now because of the revocation of several assets (All Gyeonggi Province, Hwasung, Gwacheon) within five years after initial designation of 13 assets in 1998. They are mostly distributed in the north Gyeonggi region where is close to the DMZ and delay in development seems to have enabled the preservation. Most of the intangible cultural assets are farming songs and weeding which show characteristics of Gyeonggi Province. Most of the designees are who performed excavation, recovery, excluding a few cases without designees on designation, and almost all the designee passed away. Number of cases have been revoked because transmission was not completed or some cases were transmitted to groups rather than specific designees. Subscription concert, the biggest and most representative event, is performed once a year with all of the 9 intangible cultural assets in the original complete forms of the designation. Intangible cultural assets are classified into seasonal playing and songs. In general, current performance of the intangible cultural assets and folk songs are same as the originally designated forms and are not in varied forms other than folk songs like songs for rice-planting and weeding. Funeral songs are transmitted in Yangju and Yangpyeong. In terms of the operation, preservation societies having training centers have been performing more constant activities for preservation including lecture, performance and transmission. Members are quite aged and the societies are suffering from lack of support fund for reproduction and transmission. Problems in reproduction and tasks for the transmission I would like to suggest are like followings. First, preservation and value of the cultural assets. Second, new understanding of designation and revocation of the intangible cultural assets. Third, record of performance and sound source. Fourth, liaison with local communities. Fifth, organization of professional resources and establishment of systematic support and management.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.16
no.1
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pp.71-85
/
2021
Representative domestic start-up support organizations include the Business Incubator(BI), Korea Institute of Startup & Entrepreneurship Development(KISED), Techno Park(TP), and Center of Creative Economy Innovation(CCEI), and there are about 260 Business incubator nationwide. The Business incubator is operated by universities, research institutes, and private foundations or associations. The organization consists of the center director and the incubating professionals (hereinafter referred to as "manager"), etc., and performs tasks such as center operation management and incubation support services for tenant companies. Until now, research on the operation of Business Incubator has been mainly focused on the performance of tenant companies. Studies on whether the manager's competency characteristics directly or indirectly affect the performance of the tenant companies through psychological mediators such as self-efficacy and organizational commitment were very scarce. The purpose of this study is to explore various factors influencing organizational commitment and job performance by the competence characteristics of Business incubator managers, and to explain the causal relationship among those factors. In particular, the difference in perception was investigated by a manager's survey that influences organizational commitment and work performance at the Business incubator. Through this, we intend to present practical implications for the role of managers in the operation of Business incubators. This study is an exploratory study, and the subject of the study was a survey of about 600 managers working at Business incubator nationwide, of which 116 responses were analyzed. Data analysis included descriptive statistics, exploratory factor analysis, and reliability. Structural equation model analysis was performed for hypothesis tests. As a result of the analysis, it was found that the cognitive characteristics of the Business incubator manager, communication, and situational response as the behavioral characteristics had a positive effect on the manager's self-efficacy, and the behavioral characteristics had a greater effect on the self-efficacy. It was also found that the manager's cognitive and behavioral characteristics, and self-efficacy had a positive effect on organizational commitment and work performance. In particular, a manager's self-efficacy has a positive effect on organizational commitment and work performance. This result showed that the manager's competency characteristics increase the manager's self-efficacy as a mediating factor rather than directly affecting organizational commitment and work performance. This study explains that the manager's competency characteristics are transferred to organizational commitment and work performance. The results of the study are expected to reflect the job standard of the National Competency Standards (NCS) and basic vocational competency to the job competency of managers, and it also provides a guideline for the effective business incubator operation in terms of human resource management. In practice, it is expected that the results of the study can reflect the vocational basic skills of the Business Incubator manager's job competency in the National Competency Standards(NCS) section, and suggest directions for the operation of the Business Incubator and the manager's education and training.
Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.
Asia-Pacific Journal of Business Venturing and Entrepreneurship
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v.18
no.1
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pp.107-124
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2023
As getting in 4th Industrial Revolution Times, Continuing Education Enrolled Students(CEES) trying to find loophole for jepordized current life and need job transfer have surged their interest significantly on starting new business to bring up their post career after retirement through self-improvement. Government and university have actively initiated diverse policies of promoting startup for CEES in kicking off entrepreneurship courses and programs. However, relevant main policy, 'The 2nd University Startup Education Five-Year Plan (draft)' have too chiefly focused on theoretical start-up education rather than practical courses, causing the problem of inappropriate support for implementing real startup and business (Ministry of Education, 2018). This study is brought to empirically investigate the effect of self-efficacy as perspective of the impact of entrepreneurship education on entrepreneurial intention and behavior to come up with problem of poor entrepreneurial environment and entrepreneurship education to CEES. As to empirical research, this paper deliver on-line survey to CEES from September to October 2022, collect 207 effective feedbacks, In order to verify the reliability of the scale, the Cronbach's Alpha Coefficient (Cronbach's α) was calculated, analyzed, and measured. For hypothesis test, this paper utilize the multiple regression analysis statistical analysis method and use the SPSS 22.0 statistical processing program. Empirical results show, first, it was found that self-efficacy had a significant effect on start-up education. Second, start-up education had a significant effect on the intention to start a business of adult learners. Third, start-up education had a significant effect on the start-up behavior of adult learners. Fourth, self-efficacy had a significant effect on the intention of adult learners to start a business. Fifth, self-efficacy had a significant effect on the start-up behavior of adult learners. Sixth, self-efficacy had a mediating effect in the relationship between entrepreneurship education and adult learners' intention to start a business. Seventh, self-efficacy had a complete mediating effect in the relationship between start-up education and adult learners' start-up behavior. This paper is brought three significant implications. First, main consideration developing entrepreneurship education tools for CEES need to falls on defining potential needs of CEES as segmenting as to coming up with diversity of CEES's characteristics such as gender, age, experience, education, and occupation. Second, as to design specific entrepreneurship education program, both practical training program of utilizing CEES's career field experience benchmarking best practice startup and venture cases from domestic and global, and professional startup program of CEES initiating directly startup from ideation to develop business plan with pitching and discussing. Third, entrepreneurship education for CEES should be designed to incubate self-efficacy to enhance entrepreneurial intention of implementing entrepreneurial behavior as a real, eventually leading solid support system of self-improvement for CEES' Retirement life planning.
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