• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.57-70
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• 2023

The investigation delved into 457 pieces of scholarly work, encompassing articles, published theses, and dissertations from the National Research Foundation of Korea, spanning the period of the 1997 IMF financial crisis up to 2022. The materials were sourced using terms such as 'angel investment', 'angel investor', and 'angel investment attraction'. The initial phase involved filtering out redundant entries from the preliminary collection of 267 works, leaving aside pieces that didn't pertain directly to angel investment as indicated in their abstracts. The next stage of the analysis involved a more rigorous selection process. Out of 43 papers earmarked in the preceding cut, only 32 were chosen. The criteria for this focused on the exclusion of conference presentations, articles that were either not submitted or inconclusive, and those that duplicated content under different titles. The final selection of 32 papers underwent a thorough systematic literature review. These documents, all pertinent to angel investment in South Korea, were scrutinized under five distinct categories: 1) publication year, 2) themes of research, 3) strategies employed in the studies, 4) participants involved in the research, and 5) methods of research utilized. This meticulous process illuminated the existing landscape of angel investment studies within Korea. Moreover, this study pinpointed gaps in the current body of research, offering guidance on future scholarly directions and proposing social scientific theories to further enrich the field of angel investment studies and analysis also seeks to pinpoint which areas require additional exploration to energize the field of angel investment moving forward. Through a comprehensive review of literature, this research intends to validate the establishment of future research trajectories and pinpoint areas that are currently and relatively underexplored in Korea's angel investment research stream. This study revealed that current research on domestic angel investment is concentrated on several areas: 1) the traits of angel investors, 2) the motivations behind angel investing, 3) startup ventures, 4) relevant institutions and policies, and 5) the various forms of angel investments. It was determined that there is a need to broaden the scope of research to aid in enhancing and stimulating the scale of domestic angel investing. This includes research into performance analysis of angel investments and detailed case studies in the field. Furthermore, the study emphasizes the importance of diversifying research efforts. Instead of solely focusing on specific factors like investment types, startups, accelerators, venture capital, and regulatory frameworks, there is a call for research that explores a variety of associated variables. These include aspects related to crowdfunding and return on investment in the context of angel investing, ensuring a more holistic approach to research in this domain. Specifically, there's a clear need for more detailed studies focusing on the relationships with variables that serve as dependent variables influencing the outcomes of angel investments. Moreover, it's essential to invigorate both qualitative and quantitative research that delves into the theoretical framework from multiple perspectives. This involves analyzing the structure of variables that have an impact on angel investments and the decisions surrounding these investments, thereby enriching the theoretical foundation of this field. Finally, we presented the direction of development for future research by confirming that the effect on the completeness of the business plan is high or low depending on the satisfaction of the entrepreneurs in addition to the components.

• Cartoon and Animation Studies
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• s.50
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• pp.349-382
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• 2018

China is a great civilization which is a combination of various ethnic groups with long history change. As one of these important components of traditional culture, the lucky shape has been going through the ideological upheaval of the history change of China. Up to now, it has become the important parts which can stimulate the emotion of Chinese nation. The lucky shape becomes the basis of the rich traditional culture by long history of the Chinese nation. Even say it is the centre of this traditional culture resource. The lucky shape is a way of expressing the Chinese history and national emotions. It is the important part of people's living habits, emotion, as well as the cultural background. What's more, it has the value of beliefs of Surname totem. Meanwhile, it also has the function of passing on information. The symbol of information finally was created by the being of lucky shape to indicate its conceptual content. There are various kinds of lucky shapes. It will have its limitations when researching all kinds of them professionally. So, here the lucky shape of FISH will be researched. The shape of fish is the first good shape created by the Chinese nation. It is about 6000 years. Its special shape and lucky meaning embody the peculiar inherent culture and intension of the Chinese nation. It's the important component of the Chinese traditional culture. The traditional shape of fish was focused on the continuation of history and the patterns recognition, etc. It seldom indicated the meaning of the shape into the using of the modern design. So by searching the lucky meaning & the way of fish shape, the purpose of the search is to explore the real analysis of value of the fish shape in the modern enterprise identity design. The way of search is through the development of the history, the evolvement and the meaning of lucky of the traditional fish shape to analyse the symbolic meaning and the cultural meaning from all levels in nation, culture, art and life, etc. And by using the huge living example of the enterprise identity design of the traditional shape of the fish to analyse that how it works in positive way by those enterprise which is based on the trust with good image. In the modern Chinese enterprise identity design, the lucky image will be reinterpreted in the modern way. It will be proofed by the national perceptual knowledge of the consumer and the way of enlarge the goodwill of corporate image. It will be the conclusion. The traditional fish shape is the important core of modern design.So this search is taken through the instance of the design of enterprise image of the traditional fish shape to analysis the idea of the majority Chinese people of the traditional luck and the influence of corporation which based on trust and credibility. In modern image design of Chinese corporation, the auspicious sign reappear. The question survey is taken by people through the perceptual knowledge of the consumer and the cognition the enterprise image. According the result, people can speculate the improvement of consumer's recognition and the possibility of development of traditional concept.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.141-154
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• 2019

Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

• Journal of agricultural medicine and community health
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• v.25 no.2
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• pp.231-244
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• 2000

Classification and research trends were studied to analyze a total of 240 original articles that have been published in 34 volumes of The Korean Journal of Rural Medicine from 1976 to 1999. The results were as follows: 1. A total of 337 articles were published. Among them, 240(71.2%) articles were classified as original articles. This number has been increasing significantly over the years as the number of the articles was 13 in the 1970s, 73 in the 1980s, and 154 in the 1990s. 2. There were 10 authors in the original articles and 55(22.9%) of them were written by 3 of them. There were five research institutions involved in the articles, and 106(44.2%) of the articles were done by one research group. 3. In the original articles. 24(10.0%) were noted to be done using research funds, and only 6(2.5%) were written in English. 4. In the view of the research styles of the original articles, 115(47.9%) used analytical study, 92(38.3%) used technical study, 21(9.2%) used experimental study, and 6(2.5%) used case reports. In the 1970s, 13(100.0%) articles used technical study, and in the 1980s, 47(64.4%) used technical studies and 19(26.0%) used analytical studies. However, in the 1990s, 96(62.8%) articles used analytical studies and 32(20.9%) used technical studies. The statistical methods most commonly used in the articles were technical statistics, the ${\chi}^2$-test, and the t-test respectively. 5. On the classification into three different research fields, 105(43.8%) articles were classified as health management, 96(40.0%) as disease epidemiology, and 39(16.3%) as rural environment and rural occupational disorders. In the 1970s, 12 (92.3 %) of the articles were on disease epidemiology and 1(7.7%) on health management were published. In the 1980s, 33(45.2%) articles on disease epidemiology, 29(39.7%) on health control, and 11(15.1%) on rural environment and rural occupational disorders were recorded. In the 1990s, however, 75(48.7%) articles were on health control, 51(33.1%) on disease control, and 28(18.2%) on the rural environment and rural occupational disorders. 6. According to the research subjects in each research field, the 39 articles in rural environment and rural occupational disorders were composed of 8(20.5%) articles on pesticide intoxication, 7(17,9%) on farmer's diseases, 7(17.9%) on vinyl-house diseases, and 6(15.4%) on accidents. From a total of 96 articles in disease epidemiology 56(58.3%) articles were on parasites, 16(16.7%) on non-infectious diseases, 12(12.5) on infectious diseases. From 105 articles in health control 25(23.8%) articles were on medical care utilization patterns, 18(17.1%) on the health care delivery system, and 13(12.4%) on maternal and child health. In the analysis of the 10 most prevalent subjects dealt in the above articles, 6(46.2%) articles were on parasites and 4(30.8%) on non-infectious diseases were recorded in the 1970s. In the 1980s, 28(38.4%) were on parasites. 9(12.3%) on the health care system, 7(9.6%) on medical care utilization patterns, 5(6.8%) on maternal and child health, and 4(5.5%) were on pesticide intoxication. In the 1990s, 22(14.3%) articles were on parasites. 18(11.7%) on medical care utilization patterns, 16(10.4%) on senile health, 14(9.1%) on the health care system, 10(6.5%) on infectious diseases, arid 10(6.5%) were on non-infectious diseases. In conclusion, the research activity on rural health has been strengthened in this country because the original articles in The Korean Journal of Rural Medicine have significantly increased in the past 24 years. In the 1970s and 1980s, research on disease epidemiology was most prevalent, but in the 1990s papers on health care were most popular. In addition, the articles on parasites were most frequently published in the 1970s, 1980s, and 1990s, showing that parasitic problem was the main theme in those eras. However, in the 1990s, it was evident that the articles on parasites were decreasing and articles on the subject of medical care utilization patterns and senile health increased. Hereafter it was expected that research on health care would be more common in rural health in Korea.