• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.65-76
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• 2023

In the field of technology entrepreneurship and startups, the development of Artificial Intelligence(AI) has emerged as a key topic for business model innovation. As a result, venture firms are making various efforts centered on AI to secure competitiveness(Kim & Geum, 2023). The purpose of this study is to analyze the relationship between the development of GenAI technology and the startup ecosystem by analyzing domestic news articles to identify trends in the technology startup field. Using BIG Kinds, this study examined the changes in GenAI-related news articles, major issues, and trends in Korean news articles from 1990 to August 10, 2023, focusing on the emergence of ChatGPT before and after, and visualized the relevance through network analysis and keyword visualization. The results of the study showed that the mention of GenAI gradually increased in the articles from 2017 to 2023. In particular, OpenAI's ChatGPT service based on GPT-3.5 was highlighted as a major issue, indicating the popularization of language model-based GenAI technologies such as OpenAI's DALL-E, Google's MusicLM, and VoyagerX's Vrew. This proves the usefulness of GenAI in various fields, and since the launch of ChatGPT, Korean companies have been actively developing Korean language models. Startups such as Ritten Technologies are also utilizing GenAI to expand their scope in the technology startup field. This study confirms the connection between GenAI technology and startup entrepreneurship activities, which suggests that it can support the construction of innovative business strategies, and is expected to continue to shape the development of GenAI technology and the growth of the startup ecosystem. Further research is needed to explore international trends, the utilization of various analysis methods, and the possibility of applying GenAI in the real world. These efforts are expected to contribute to the development of GenAI technology and the growth of the startup ecosystem.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.143-161
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• 2022

The government is promoting policies to increase policy efficiency by supporting corporate growth through corporate support and establishing the Ministry of SMEs and Startups as a control tower for corporate support projects. However, opinions on the efficiency of the government's corporate support project are divided, and this study aims to check how the government's corporate support project affects corporate performance and how absorption capacity and satisfaction, which are internal factors, affect corporate growth. Research was conducted on companies receiving government corporate support projects, and previous studies focused on financial support among government corporate support projects, while the effect of government corporate support was analyzed by dividing government support projects into financial and non-financial support, and absorption capabilities and corporate support satisfaction were analyzed. Through this, the effect on corporate financial performance and non-financial performance was empirically analyzed according to the mediating effect of absorption capacity and corporate support satisfaction in the government's corporate support project. As a result, both the government's financial and non-financial support had a positive effect on financial and non-financial performance, and it was confirmed that both absorption capacity and corporate support satisfaction mediate both financial and non-financial performance, and it was analyzed that it had a positive (+) effect. In order to improve the absorption capacity of a company, it is expected that it will be meaningful to improve the efficiency of the business by defining the problems faced by the company and suggesting solutions through the establishment of a supplier and consumer network.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.

• Trans-
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• v.16
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• pp.1-31
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• 2024

The advent of digital media has facilitated easy access for adolescents to environments conducive to the purchase of narcotics. In particular, there's an increasing trend in the purchase and consumption of narcotics mediated through Social Network Services (SNS) and messenger services. Adolescents, sensitive to such environments, are at risk of experiencing neurological and mental health issues due to narcotic addiction, increasing their exposure to criminal activities, hence necessitating national-level management and support. Consequently, the quest for sustainable treatment methods for adolescents exposed to narcotics emerges as a critical challenge. In the context of high relapse rates in narcotic addiction, the necessity for cost-effective and user-friendly treatment programs is emphasized. This study conducts a literature review aimed at utilizing digital platforms to create an environment where adolescents can voluntarily participate, focusing on the development of therapeutic content through art. Specifically, it reviews societal perceptions and treatment statuses of adolescent drug addiction, analyzes the impact of narcotic addiction on adolescent brain activity and cognitive function degradation, and explores approaches for developing digital therapeutics to promote the rehabilitation of the addicted brain through analysis of precedential case studies. Moreover, the study investigates the benefits that the integration of digital therapeutic approaches and art therapy can provide in the treatment process and proposes the possibility of enhancing therapeutic effects through various treatment programs such as drama therapy, music therapy, and art therapy. The application of art therapy methods is anticipated to offer positive effects in terms of tool expansion, diversification of expression, data acquisition, and motivation. Through such approaches, an enhancement in the effectiveness of treatments for adolescent narcotic addiction is anticipated. Overall, this study undertakes foundational research for the development of digital therapeutics and related applications, offering economically viable and sustainable treatment options in consideration of the societal context of adolescent narcotic addiction.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Journal of Distribution Research
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• v.17 no.1
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• pp.87-115
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• 2012

Introduction: In these days, a loyalty program is one of the most common marketing mechanisms (Lacey & Sneath, 2006; Nues & Dreze, 2006; Uncles et al., 20003). In recent years, Coalition Loyalty Program is more noticeable as one of progressed forms. In the past, loyalty program was operating independently by single product brand or single retail channel brand. Now, companies using Coalition Loyalty Program share their programs as one single service and companies to participate to this program continue to have benefits from their existing program as well as positive spillover effect from the other participating network companies. Instead of consumers to earn or spend points from single retail channel or brand, consumers will have more opportunities to utilize their points and be able to purchase other participating companies products. Issues that are related to form of loyalty programs are essentially connected with consumers' perceived view on convenience of using its program. This can be a problem for distribution companies' strategic marketing plan. Although Coalition Loyalty Program is popular corporate marketing strategy to most companies, only few researches have been published. However, compared to independent loyalty program, coalition loyalty program operated by third parties of partnership has following conditions: Companies cannot autonomously modify structures of program for individual companies' benefits, and there is no guarantee to operate and to participate its program continuously by signing a contract. Thus, it is important to conduct the study on how coalition loyalty program affects companies' success and its process as much as conducting the study on effects of independent program. This study will complement the lack of coalition loyalty program study. The purpose of this study is to find out how consumer loyalty affects affiliated brands, its cause and mechanism. The past study about loyalty program only provided the variation of performance analysis, but this study will specifically focus on causes of results. In order to do these, this study is designed and to verify three primary objects as following; First, based on opinions of Switching Barriers (Fornell, 1992; Ping, 1993; Jones, et at., 2000) about causes of loyalty of coalition brand, 'brand attractiveness' and 'brand switching cost' are antecedents and causes of change in 'brand loyalty' will be investigated. Second, influence of consumers' perception and attitude prior to joining coalition loyalty program, influence of program in retail brands, brand attractiveness and spillover effect of switching cost after joining coalition program will be verified. Finally, the study will apply 'prior brand preference' as a variable and will provide a relationship between effects of coalition loyalty program and prior preference level. Hypothesis Hypothesis 1. After joining coalition loyalty program, more preferred brand (compared to less preferred brand) will increase influence on brand attractiveness to brand loyalty. Hypothesis 2. After joining coalition loyalty program, less preferred brand (compared to more preferred brand) will increase influence on brand switching cost to brand loyalty. Hypothesis 3. (1)Brand attractiveness and (2)brand switching cost of more preferred brand (before joining the coalition loyalty program) will influence more positive effects from (1)program attractiveness and (2)program switching cost of coalition loyalty program (after joining) than less preferred brand. Hypothesis 4. After joining coalition loyalty program, (1)brand attractiveness and (2)brand switching cost of more preferred brand will receive more positive impacts from (1)program attractiveness and (2)program switching cost of coalition loyalty program than less preferred brand. Hypothesis 5. After joining coalition loyalty program, (1)brand attractiveness and (2)brand switching cost of more preferred brand will receive less impacts from (1)brand attractiveness and (2)brand switching cost of different brands (having different preference level), which joined simultaneously, than less preferred brand. Method : In order to validate hypotheses, this study will apply experimental method throughout virtual scenario of coalition loyalty program if consumers have used or available for the actual brands. The experiment is conducted twice to participants. In a first experiment, the study will provide six coalition brands which are already selected based on prior research. The survey asked each brand attractiveness, switching cost, and loyalty after they choose high preference brand and low preference brand. One hour break was provided prior to the second experiment. In a second experiment, virtual coalition loyalty program "SaveBag" was introduced to participants. Participants were informed that "SaveBag" will be new alliance with six coalition brands from the first experiment. Brand attractiveness and switching cost about coalition program were measured and brand attractiveness and switching cost of high preference brand and low preference brand were measured as same method of first experiment. Limitation and future research This study shows limitations of effects of coalition loyalty program by using virtual scenario instead of actual research. Thus, future study should compare and analyze CLP panel data to provide more in-depth information. In addition, this study only proved the effectiveness of coalition loyalty program. However, there are two types of loyalty program, which are Single and Coalition, and success of coalition loyalty program will be dependent on market brand power and prior customer attitude. Therefore, it will be interesting to compare effects of two programs in the future.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.47-55
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• 2015

Recently, the environment of a hospital information system is a trend to combine various SMART technologies. Accordingly, various smart devices, such as a smart phone, Tablet PC is utilized in the medical information system. Also, these environments consist of various applications executing on heterogeneous sensors, devices, systems and networks. In these hospital information system environment, applying a security service by traditional access control method cause a problems. Most of the existing security system uses the access control list structure. It is only permitted access defined by an access control matrix such as client name, service object method name. The major problem with the static approach cannot quickly adapt to changed situations. Hence, we needs to new security mechanisms which provides more flexible and can be easily adapted to various environments with very different security requirements. In addition, for addressing the changing of service medical treatment of the patient, the researching is needed. In this paper, we suggest a dynamic approach to medical information systems in smart mobile environments. We focus on how to access medical information systems according to dynamic access control methods based on the existence of the hospital's information system environments. The physical environments consist of a mobile x-ray imaging devices, dedicated mobile/general smart devices, PACS, EMR server and authorization server. The software environment was developed based on the .Net Framework for synchronization and monitoring services based on mobile X-ray imaging equipment Windows7 OS. And dedicated a smart device application, we implemented a dynamic access services through JSP and Java SDK is based on the Android OS. PACS and mobile X-ray image devices in hospital, medical information between the dedicated smart devices are based on the DICOM medical image standard information. In addition, EMR information is based on H7. In order to providing dynamic access control service, we classify the context of the patients according to conditions of bio-information such as oxygen saturation, heart rate, BP and body temperature etc. It shows event trace diagrams which divided into two parts like general situation, emergency situation. And, we designed the dynamic approach of the medical care information by authentication method. The authentication Information are contained ID/PWD, the roles, position and working hours, emergency certification codes for emergency patients. General situations of dynamic access control method may have access to medical information by the value of the authentication information. In the case of an emergency, was to have access to medical information by an emergency code, without the authentication information. And, we constructed the medical information integration database scheme that is consist medical information, patient, medical staff and medical image information according to medical information standards.y Finally, we show the usefulness of the dynamic access application service based on the smart devices for execution results of the proposed system according to patient contexts such as general and emergency situation. Especially, the proposed systems are providing effective medical information services with smart devices in emergency situation by dynamic access control methods. As results, we expect the proposed systems to be useful for u-hospital information systems and services.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.35-55
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• 2013

Information technology is a critical resource necessary for any company hoping to support and realize its strategic goals, which contribute to growth promotion and sustainable development. The selection of information technology and its strategic use are imperative for the enhanced performance of every aspect of company management, leading a wide range of companies to have invested continuously in information technology. Despite researchers, managers, and policy makers' keen interest in how information technology contributes to organizational performance, there is uncertainty and debate about the result of information technology investment. In other words, researchers and managers cannot easily identify the independent factors that can impact the investment performance of information technology. This is mainly owing to the fact that many factors, ranging from the internal components of a company, strategies, and external customers, are interconnected with the investment performance of information technology. Using an agent-based simulation technique, this research extracts factors expected to affect investment performance on information technology, simplifies the analyses of their relationship with economic modeling, and examines the performance dependent on changes in the factors. In terms of economic modeling, I expand the model that highlights the way in which product quality moderates the relationship between information technology investments and economic performance (Thatcher and Pingry, 2004) by considering the cost of information technology investment and the demand creation resulting from product quality enhancement. For quality enhancement and its consequences for demand creation, I apply the concept of information quality and decision-maker quality (Raghunathan, 1999). This concept implies that the investment on information technology improves the quality of information, which, in turn, improves decision quality and performance, thus enhancing the level of product or service quality. Additionally, I consider the effect of word of mouth among consumers, which creates new demand for a product or service through the information diffusion effect. This demand creation is analyzed with an agent-based simulation model that is widely used for network analyses. Results show that the investment on information technology enhances the quality of a company's product or service, which indirectly affects the economic performance of that company, particularly with regard to factors such as consumer surplus, company profit, and company productivity. Specifically, when a company makes its initial investment in information technology, the resultant increase in the quality of a company's product or service immediately has a positive effect on consumer surplus, but the investment cost has a negative effect on company productivity and profit. As time goes by, the enhancement of the quality of that company's product or service creates new consumer demand through the information diffusion effect. Finally, the new demand positively affects the company's profit and productivity. In terms of the investment strategy for information technology, this study's results also reveal that the selection of information technology needs to be based on analysis of service and the network effect of customers, and demonstrate that information technology implementation should fit into the company's business strategy. Specifically, if a company seeks the short-term enhancement of company performance, it needs to have a one-shot strategy (making a large investment at one time). On the other hand, if a company seeks a long-term sustainable profit structure, it needs to have a split strategy (making several small investments at different times). The findings from this study make several contributions to the literature. In terms of methodology, the study integrates both economic modeling and simulation technique in order to overcome the limitations of each methodology. It also indicates the mediating effect of product quality on the relationship between information technology and the performance of a company. Finally, it analyzes the effect of information technology investment strategies and information diffusion among consumers on the investment performance of information technology.

• Atmosphere
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• v.33 no.2
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• pp.275-295
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• 2023

In Korea, there are four institutions related to atmospheric science: the university's atmospheric science-related department, the Korea Meteorological Administration (KMA), the ROK Air Force Weather Group, and the Meteorological Industry Association. These four institutions have developed while maintaining a deep cooperative relationship with the Korea Meteorological Society (KMS) for the past 60 years. At the university, 6,986 bachelors, 1,595 masters, and 505 doctors, who are experts in meteorology and climate, have been accredited by 2022 at 7 universities related to atmospheric science. The KMA is carrying out national meteorological tasks to protect people's lives and property and foster the meteorological industry. The ROK Air Force Weather Group is in charge of military meteorological work, and is building an artificial intelligence and space weather support system through cooperation with universities, the KMA, and the KMS. Although the Meteorological Industry Association has a short history, its members, sales, and the number of employees are steadily increasing. The KMS greatly contributed to raising the national meteorological service to the level of advanced countries by supporting the development of universities, the KMA, the Air Force Meteorological Agency, and the Meteorological Industry Association.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.