• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.369-376
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• 2021

The purpose of this study is to develop a coaching model which can enhance teaching ability of lifelong educator. To achieve this purpose, this study verifies and analyzes several documentary records related with diverse teaching capabilities, operation reality and coaching method run by lifelong educator. Furthermore, an in-depth interview about teaching capability was undertaken for field experts who have worked at the institutions of lifelong education for more than 10 years. As a result, the study could develop a coaching model to identify teaching capability of lifelong educator by conducting matrix analysis. First, according to the documentary studies, the paradigm for lifelong education has been shifted to centralize learner's demand with the advent of 4th industrial revolution and it suggests coaching capability which could enhance educator's capability should come first. A lifelong educator should have capabilities including identification of vision and goal, creation of mission declaration, development of coaching skill and procedure, management of crisis and coaching capability as an expert in the lifelong education field. Second, a model which can centralize learners could be developed for lifelong teaching capability by adopting a teaching capability suggested by field experts, According to the experts, it is essential to develop a program model to acquire professional knowledge, communication capability, understanding of adult learner, personal relations capability. If there is a model which can develop such capabilities, it is able to strengthen lifelong teaching capability to focus on learner's demand, mainly adult learners, a major consumer of the field. Third, a coaching model to enhance teaching capability for an educator is to acquire and implement sufficient step-by-step teaching capability which has been suggested from a procedure comprised of entrance, progress, critique and return. This, present study suggests, after the critique, a lifelong educator oneself can newly develop and extend a teaching capability basis on pursuing teaching capability as a lifelong educator through the return process.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.1-17
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• 2024

One of the most important decisions for managers in the online banner advertising industry, is to choose the best banner alternative for exposure to customers. Since it is difficult to know the click probability of each banner alternative in advance, managers must experiment with multiple alternatives, estimate the click probability of each alternative based on customer clicks, and find the optimal alternative. In this reinforcement learning process, the main decision problem is to find the optimal balance between the level of exploitation strategy that utilizes the accumulated estimated click probability information and exploration strategy that tries new alternatives to find potentially better options. In this study we analyze the impact of word-of-mouth effects and the number of alternatives on the optimal exploration-exploitation strategies. More specifically, we focus on the word-of-mouth effect, where the click-through rate of the banner increases as customers promote the related product to those around them after clicking the exposed banner, and add it to the overall reinforcement learning process. We analyze our problem by employing the Multi-Armed Bandit model, and the analysis results show that the larger the word-of-mouth effect and the fewer the number of banner alternatives, the higher the optimal exploration level of advertising reinforcement learning. We find that as the probability of customers clicking on the banner increases due to the word-of-mouth effect, the value of the previously accumulated estimated click-through rate knowledge decreases, and therefore the value of exploring new alternatives increases. Additionally, when the number of advertising alternatives is small, a larger increase in the optimal exploration level was observed as the magnitude of the word-of-mouth effect increased. This study provides meaningful academic and managerial implications at a time when online word-of-mouth and its impact on society and business is becoming more important.

• The Korean Society of Law and Medicine
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• v.24 no.4
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• pp.67-101
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• 2023

The utilization of generative AI in the medical field is also being rapidly researched. Access to vast data sets reduces the time and energy spent in selecting information. However, as the effort put into content creation decreases, there is a greater likelihood of associated issues arising. For example, with generative AI, users must discern the accuracy of results themselves, as these AIs learn from data within a set period and generate outcomes. While the answers may appear plausible, their sources are often unclear, making it challenging to determine their veracity. Additionally, the possibility of presenting results from a biased or distorted perspective cannot be discounted at present on ethical grounds. Despite these concerns, the field of generative AI is continually advancing, with an increasing number of users leveraging it in various sectors, including biomedical and life sciences. This raises important legal considerations regarding who bears responsibility and to what extent for any damages caused by these high-performance AI algorithms. A general overview of issues with generative AI includes those discussed above, but another perspective arises from its fundamental nature as a large-scale language model ('LLM') AI. There is a civil law concern regarding "the memorization of training data within artificial neural networks and its subsequent reproduction". Medical data, by nature, often reflects personal characteristics of patients, potentially leading to issues such as the regeneration of personal information. The extensive application of generative AI in scenarios beyond traditional AI brings forth the possibility of legal challenges that cannot be ignored. Upon examining the technical characteristics of generative AI and focusing on legal issues, especially concerning the protection of personal information, it's evident that current laws regarding personal information protection, particularly in the context of health and medical data utilization, are inadequate. These laws provide processes for anonymizing and de-identification, specific personal information but fall short when generative AI is applied as software in medical devices. To address the functionalities of generative AI in clinical software, a reevaluation and adjustment of existing laws for the protection of personal information are imperative.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• Journal of Technology Innovation
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• v.19 no.1
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• pp.111-144
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• 2011

This study is to confirm the core factors of innovative capabilities and technological entrepreneurship affecting the performance of technology management and business management of small and medium-sized enterprises (SMEs). Through the consideration about the complex natures of technological innovation affecting by multidimensional factors, this study designs the research model that innovative capabilities, the performances of technology and business management are arranged in accordance with the innovation process; input-output-outcome. To meet this research purpose, the hypothesis are set up based on the previous research studies and the research samples are selected from members of the Innovative Business (INNO-BIZ) Association, located in Seoul and Geyonggi province. As a result of regression analysis to the responses gathered from 360 firms, the performance of business management is influenced positively by the technology superiority, market growth and business profitability which are the dominant factors of performance of technology management. In addition, three sub-variables of innovative capabilities such as R&D, strategic planning and learning capability, have positive effects on both the managerial performances. Innovativeness and progressiveness of technological entrepreneurship affect both the performances positively. Moreover, the co-relation between technological entrepreneurship of an innovation leader and innovative capabilities of organizational members are identified. Lastly, technological entrepreneurship has the mediating effect on the path of leading innovative capabilities to the managerial performances. In conclusion, the research results imply that technological innovation-type firms should periodically evaluate the performance of technology management which are the output of technological innovations and the reinvestment for ultimate business success. And improving and developing innovative capabilities and technological entrepreneurship is required to continuously and consistently investing and supporting resources on technological innovations at the firm-and government-level. It is considered that these are the crucial methods for securing the technologically competitive advantage of SMEs with less resources and narrow innovation range.

• Cartoon and Animation Studies
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• s.40
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• pp.367-395
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• 2015

Mobile games have taken 80% of the market sales in smart device application industry that is highly regarded as one of the fast growing pool of cultural content after the distribution of smart devices. One of the most successful mobile games after the smart device's appearance is . created by Gung-ho Online entertainment under Softbank Japan, has gained the sales revenue of one trillion dollars after its release in 2012, just after one year of its exposure to the market. The game also has been the top rank by Worldwide Mobile Game Revenues for 2years achieving 40 million downloads worldwide in 2015. However, there is no place for a Korean game in world mobile game sales ranks yet. Even though the mobile game industry has been expanding every year, Korean games are losing its places in the market. Therefore, the analysis of a successful game such as is vital for diagnosing Korea's game content and its lack of direction. This study utilizes K. Masanao's Matrix for Creating Profit System for analyzing 's factors for its success. First, the game has incorporated puzzle and RPG contents for creating a new genre, which led various age groups to play the game. Second, the developers have applied 'limited time' in-game festivals and collaborations between the game and famous contents such as God Festival and Character Draw system to increase the profit revenue. Third, the company communicated with on and off line players to seek their needs for developing the game's better development. Consequently, the three success factors of deduced from this study not only reflect the related researches and academic values, but also contribute for the search in finding better ways to developing game contents for Korean mobile game industry.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.113-139
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• 2007

This study aims to, looking from a standpoint of network, has investigated the shipping industry's B2B e-marketplace, the characteristics that can earn electronic trust from the users, and characteristics of the web-site. It has examined the mechanism whereby electronic trust be earned and how it affects web-site involvement and service transaction intention. Ultimately, The study attempts to make proposals whereby such trust can lead for a cooperative trading community in the shipping industry's B2B e-marketplace The Covalence structural equation modeling was designed and empirically tested for the shipping industry's B2B e-marketplace. The shipping industry employees were given questionnaires and data were analyzed. Except for perceived security of the three characteristic factors on the web-site, the perceived site quality and characteristics factors in operation only affected co-variables. Transaction Fairness was determined to be the most important factor among exogenous factors increasing electronic trust. With regards to transaction rules, if a transaction is beneficial only to one side, then no long term transaction will not take place. If the concerned parties properly recognize that transaction fairness is crucial to electronic transaction, then it will enormously contribute to successful operations of shipping e-marketplace. Also, Perceived efficiency in transaction also affects electronic trust. This reduces transaction costs and speeds up and simplifies the transaction process. It has reduced greater time and costs than existing off-line transaction, and would positively affect electronic trust. By making an open forum for participants to obtain information for transaction, they can gather useful information, and at the same time, the web-site operator can provide information, which, in turn, will increase electronic trust in electronic transaction. Furthermore, such formation of trust in electronic transaction influences shipping companies in such a way that they will want to continuously participate in the transaction, raising web-site involvement. The result of increased trust is that shipping companies in the future will do business with each other and form a foundation for continuous transactions amongst themselves. Consequently, the formation of trust in electronic transaction greatly influences web-site involvement and service transaction intention. The results of the study have again proved that in order to maintain continuous business relationship with the current clients, electronic trust in virtual space, which operates the shipping industry's B2B e-marketplace, is important for the interested parties.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.7 no.4
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• pp.101-112
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• 2012

Business consulting which aims at advising overall management, comparative advantage in competitive environment, administration and so forth is deemed to be significant so that a credit union may flexibly respond to rapid and complicated financial environment. Accordingly, business consulting has been initiated and implemented in credit union since 2002, which seemingly leads to positive outcome to enhance its competitiveness. However, very few research exists which analyze the credit union's competitiveness and business performance after the business consulting. Thus, the research intends to verify how consulting influences on management performance by its various factors. With the above studies in mind, hypothesis is formed that the characteristics of a consulting comsumer and the characteristics of supplier will give a meaningful impact on management performance. The test shows the result as followings: Firstly, a primary credit union's trust and NACUFOK's expertise demonstrate that they are closely relevant to financial and non financial management performance. Secondly, support and willingness to apply states that they influences on non financial performance, while no direct impact is found to financial performance. Thirdly, NACUFOK's capability is rarely interrelated to financial and non financial performance. The present study implies that the credit union as a consulting beneficiary should participate in the consulting, accept the result, and make effort to solve the management problems. In addition, NACUFOK as a consulting supplier should initiate the organization in exclusive charge, perform the professional group, and foster the professional consultant for the development of consulting method, the improvement of consulting process, and the specialization of consultant including the enhancement of core competencies. When these perspectives are sufficient, it will be connected to the management outcomes, further, it will be boosted up the competitiveness of the Credit Union. Hopefully the present study helps to motivate the consulting of primary credit union, boost up the effectiveness of consulting, further, providing the perspective on consulting the credit union. And these may result in the indication of consulting development direction and the competitiveness of Credit Union.