• East Asian Journal of Business Economics (EAJBE)
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• v.5 no.4
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• pp.39-49
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• 2017

Purpose - This study is to propose a creative idea for constant business growth and development by examining characteristics of business outcomes by phase, which are "growth" and "erosion and stagnation," respectively. Research design, data, methodology - It is necessary to identify an occurrence of crisis and its diffusion with a dynamic model in order to identify a success and failure of businesses in an organic way, not on a binary structure. The static perspective is to understand a crisis as a simply one-time event or as a linear causation. Thus, it has a limited understanding of the overall situation and has limits to investigating a foundational cause and developing long-term countermeasures. On the contrary, the dynamic perspective is to understand the crisis as circulation process of the overall system. Thus, it divides elements of the crisis as external and internal ones to understand it as the causal relationship of each element. Results - During the growth period of Burger King, the company promoted its brand very successfully with aggressive and creative marketing activities. However, due to the founder's disposal of management rights and the following changes in the management, the company had no choice but to lose focus on its business philosophy and brand management, and eventually it had to face the big crisis (resonance) which was delisting from the stock market because of the external threat; well-being trend. However, Burger King resumed lifting on the stock exchange by making great efforts to clearly identify the current issues and seek solutions. Under the spirit of "perseverance" and its slogan "Have it your way" the company is now going head to head with McDonald's in the North American region and emerging countries. Conclusions - Then, what is the most crucial factor in the success and failure of businesses? Answers may vary, however, as learned from the case study of Burger King, corporations should inspect the present and focus on developing a long-term strategy for the future and actively fulfill the actions. McDonald's may not be able to innovate by itself in the future as it may become routinized to the growth. There will be chances of winning if we change conditions of individuals or organizations to an organic system in terms of being creative. There is a hopeful message here that an individual or small business may have more advantages in the era of the idea and innovation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.293-303
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• 2017

Thus study examined the possible the link between social enterprises and lifelong education for the underprivileged. To this end, this study searched for the definition and position of social enterprises emerging from the welfare system under the influence of neoliberalism and overcoming the problems in terms of creating social jobs and providing welfare services. In addition, the lifelong education for the underprivileged was examined according to the subjects, such as the disabled, migrant women, young and adult low-income group, and senior citizens. The plan was as follows. First, the expansion of the proportion of community-affiliated social enterprises was analyzed. Second, it provides a differentiated support and protection market for social enterprise. Third, the development and dissemination of social entrepreneur training programs was examined. The results showed that the entire society should have a sense of responsibility for the support of the underprivileged. This provides implications for the linkage of lifelong education and social enterprise in the expansion possibility to improve the quality of life and expand lifelong education for the underprivileged.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.581-592
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• 2019

This study investigates the factors that stimulate or suppress the use of food delivery applications. As potential antecedent factors, the present research examined the review diagnosticity, descriptive norms, and multidimensional risk perception. Based on this, users' data were collected from major metropolitan cities where the food delivery application business is most active. The results of structural equation modeling confirmed that users' approach to food delivery apps becomes more favorable when the review diagnosticity and descriptive norms were improved and when the perceived multidimensional risk expected to be associated with app use is mitigated. Additionally, we found that the positive influence of these attitudes on the actual intention to accept delivery applications became weaker at higher levels of perceived risk. These empirical results may contribute to the formation of strategic and systematic guidelines for promoting the expansion of the recently emerging O2O service platform across diverse sectors. Namely, the significance of this study lies in that it has raised awareness regarding the strategic considerations that such new O2O service providers should take into account for their market positions, in addition to discovering factors that could aid the prompt expansion of the applications' user base.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.3
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• pp.290-298
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• 2019

The proportion of farm households in the total population is decreasing every year. The aging of rural areas is expected to deepen. The aging of agriculture is continuing due to the aging of the aged population and the decline of the young population, and agricultural manpower shortage is emerging as a threat to agriculture and rural areas. The existing facility cultivation was concentrated on the production / yield per unit area. However, nowadays, not only production but also crop quality should be good so that the quality of crops must be improved because they can secure competitiveness in the market. Therefore, the government plans to increase the productivity by hi-techization of ICT infrastructure horticulture and to plan the dissemination of energy saving smart greenhouse. Therefore, it is necessary to develop a Smart Farm convergence service system based on a hybrid algorithm to enhance diversity and connectivity. Therefore, this study aims to develop smart farm convergence service system which collects data of growth environment of the rhizosphere environment of crops by wireless and monitor smartphone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• The Journal of Bigdata
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• v.5 no.2
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• pp.121-133
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• 2020

This study was carried out to set the direction of the new industry policy of Busan city by analyzing the changing trend of artificial intelligence technology that has recently developed rapidly and predicting the direction of future development. The company wanted to draw up support measures to utilize artificial intelligence technology, which has been rapidly emerging in the market, in the region's specialized industry. Artificial intelligence is a key keyword in the fourth industrial revolution and artificial intelligence-based data utilization technology can be used in various fields from manufacturing processes to services, and is entering an era of super-fusion in which barriers between technologies and industries will be broken down. In this study, the direction of promotion for fostering Busan as an artificial intelligence city was derived based on the comparison and analysis of artificial intelligence-related ecosystems among major local governments. In this study, we wanted to present a plan to create an artificial intelligence industrial ecosystem that can be called a key policy to foster Busan as an 'AI City'. Busan's plan to foster the AI industry ecosystem is aimed at establishing a policy direction to ultimately nurture the artificial intelligence industry as Busan's future food source.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.648-656
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• 2022

As environmental regulations such as the International Maritime Organization (IMO)'s strategy to reduce greenhouse gases(GHG) are strengthened, technology development such as eco-friendly ships and alternative fuels is expanding. As part of this, ship propulsion technology using energy reduction and wind propulsion technology is emerging, especially in shipping companies and shipbuilders. By securing wind propulsion technology and introducing empirical research into shipbuilding and shipping, a high value-added market using eco-friendly technology can be created. Moreover, by reducing the fuel consumption rate of operating ships, GHG can be reduced by 6-8%. Rotor Sail (RS) technology is to generate a hydrodynamic lift in the vertical direction of the cylinder when the circular cylinder rotates at a constant speed and passes through the fluid. This is called the Magnus effect, and this study attempted to propose a plan to increase propulsion efficiency through a numerical analysis study on turbulence flow characteristics around RS, a wind power assistance propulsion system installed on a ship. Therefore, C_L and C_D values according to SR and AR changes were derived as parameters that affect the aerodynamic force of the RS, and the flow characteristics around the rotor sail were compared according to EP application.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.103-112
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• 2022

Due to the popularization of smartphones, most of the recorded speech files submitted as evidence of recent crimes are produced by smartphones, and the integrity (forgery) of the submitted speech files based on smartphones is emerging as a major issue in the investigation and trial process. Samsung smartphones with the highest domestic market share are distributed with built-in speech recording applications that can record calls and voice, and can edit recorded speech. Unlike editing through third-party speech (audio) applications, editing by their own builtin speech applications has a high similarity to the original file in metadata structures and attributes, so more precise analysis techniques need to prove integrity. In this study, we constructed a speech file metadata database for speech files (original files) recorded by 34 Samsung smartphones and edited speech files edited by their built-in speech recording applications. We analyzed by comparing the metadata structures and attributes of the original files to their edited ones. As a result, we found significant metadata differences between the original speech files and the edited ones.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.85-95
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• 2021

Currently, we stand between computers as creative tools and computers as creators. A new genre of movies, which can be called a post-cinema situation, is emerging. This paper aims to diagnose the possibility of the emergence of AI cinema. To confirm the possibility of AI cinema, it was examined through a case study whether the creation of a story, narrative, image, and sound, which are necessary conditions for film creation, is possible by artificial intelligence. First, we checked the visual creation of AI painting algorithms Obvious, GAN, and CAN. Second, AI music has already entered the distribution stage in the market in cooperation with humans. Third, AI can already complete drama scripts, and automatic scenario creation programs using big data are also gaining popularity. That said, we confirmed that the filmmaking requirements could be met with AI algorithms. From the perspective of Manovich's 'AI Genre Convention', web documentaries and desktop documentaries, typical trends post-cinema, can be said to be representative genres that can be expected as AI cinemas. The conditions for AI, web documentaries and desktop documentaries to exist are the same. This article suggests a new path for the media of the 4th Industrial Revolution era through research on AI as a creator of post-cinema.

• Journal of Intelligence and Information Systems
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• v.29 no.1
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• pp.41-63
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• 2023

As the online e-commerce market growing, the need for a recommender system that can provide suitable products or services to customer is emerging. Recently, many studies using the sentiment score of online review have been proposed to improve the limitations of study on recommender systems that utilize only quantitative information. However, this methodology has limitation in extracting specific preference information related to customer within online reviews, making it difficult to improve recommendation performance. To address the limitation of previous studies, this study proposes a novel recommendation methodology that applies deep learning technique and uses various linguistic factors within online reviews to elaborately learn customer preferences. First, the interaction was learned nonlinearly using deep learning technique for the purpose to extract complex interactions between customer and product. And to effectively utilize online review, cognitive contents, affective contents, and linguistic style matching that have an important influence on customer's purchasing decisions among linguistic factors were used. To verify the proposed methodology, an experiment was conducted using online review data in Amazon.com, and the experimental results confirmed the superiority of the proposed model. This study contributed to the theoretical and methodological aspects of recommender system study by proposing a methodology that effectively utilizes characteristics of customer's preferences in online reviews.