• International journal of advanced smart convergence
• /
• v.11 no.3
• /
• pp.132-141
• /
• 2022

We look at the rocket life stages of NaverZ's metaverse platform scaling and investigate the ignition and scale-up stage of its metaverse platform brand, Zepeto based on the Rocket Model (RM). The results are derived as follows: Firstly, NaverZ shows the event strategy by collaborating with K-pops, the piggybacking strategy by utilizing other SNSs, and the VIP strategy by investing in game and entertainment content genres in the 'attract' function. In the second 'match' function, based on the matching rule of Zepeto, the users can generate their own characters and "World" with Zepeto Studio. However, for strengthening the matching quality, NaverZ is investing in the artificial intelligence (AI) based companies consistently. In the 'connect' function, NaverZ's maximization of the positive interaction is possible by inducing feed activities in Zepeto & other SNSs and by uploading attractive content for viral effects in the ignition. For facilitating this, NaverZ expands the scale to other continents like Southeast Asia and Middle East with the localization strategy inclusive investment. Lastly, in the 'transact' function, based on three monetization experiments like Coin & ZEM, user generated content (UGC) fee, and advertising revenue in the ignition, NaverZ starts to invest in NFT platforms and abroad blockchain companies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.8
• /
• pp.2316-2332
• /
• 2024

In this paper, we introduce a web-based system that leverages the capabilities of the ρ(rho)-algorithm, which is a Structure Information Control Net (SICN)-oriented process mining algorithm, with open-source platforms, including Django, Graphviz, and Cytoscape, to facilitate the rediscovery and visualization of business process models. Our approach involves discovering SICN-oriented process models from process instances from the IEEE XESformatted process enactment event logs dataset. This discovering process is facilitated by the ρ-algorithm, and visualization output is transformed into either a JSON or DOT formatted file, catering to the compatibility requirements of Cytoscape or Graphviz, respectively. The proposed system utilizes the robust Django platform, which enables the creation of a userfriendly web interface. This interface offers a clear, concise, modern, and interactive visualization of the rediscovered business processes, fostering an intuitive exploration experience. The experiment conducted on our proposed web-based process discovery system demonstrates its ability and efficiency showing that the system is a valuable tool for discovering business process models from process event logs. Its development not only contributes to the advancement of process mining but also serves as an educational resource. Readers, students, and practitioners interested in process mining can leverage this system as a completely free process miner to gain hands-on experience in rediscovering and visualizing process models from event logs.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.15 no.3
• /
• pp.1-14
• /
• 2019

The 4th Industrial Revolution, intelligent automobile application technology is evolving beyond the limit of the mobile device to a variety of application software and multi-media collective technology with big data-based AI(artificial intelligence) technology. with the recent commercialization of 5G mobile communication service, artificial intelligent automobile technology, which is a fusion of automobile and IT technology, is evolving into more intelligent automobile service technology, and each multimedia platform service and application developed in such distributed environment is being developed Accordingly, application software technology developed with a single system SoC of a portable terminal device through various service technologies is absolutely required. In this paper, smart device design for ontology design of intelligent automobile open platform enables to design intelligent automobile middleware software design technology such as Android based SVC Codec and real time video and graphics processing that is not expressed in single ASIC application software technology as SoC based application designWe have experimented in smart device environment through researches, and newly designed service functions of various terminal devices provided as open platforms and application solutions in SoC environment and applied standardized interface analysis technique and proved this experiment.

• The Journal of the Korea Contents Association
• /
• v.18 no.6
• /
• pp.88-101
• /
• 2018

The collective narratives on global crisis such as the displaced, uneven distribution of resources, invasion of human rights is more than a recurring theme or polemics in the fields of contemporary arts. In the latest projects from Olafur Eliasson, Rirkrit Tiravanija and Ai WeiWei, art works are presented as performative 'platforms' for tackling these undiscriminating reality of human conditions. Here, 'the users' as driving forces of possible change, are postulated as prospective actors/players who lead and collaborate to defy the status-quo. Crossing over the on/off lines, the everyday-activities of exchanging, sharing and networking are strategically deployed and its meaning reconfigured within the context of post/production discourse. This historical, yet unsettling juncture between art and life, dystopian reality and utopian idealism has its formal-conceptual links to Russian Constructivism, Brechtian Learning-Play and Joseph Beuys' Social Sculpture. Based on Nicolas Bourriaud's notion of Postproduction, this paper aims to provide a diachronic analysis on collaborative dispositions of participatory arts practices.

• Electronics and Telecommunications Trends
• /
• v.36 no.1
• /
• pp.54-63
• /
• 2021

Since the recent COVID-19 pandemic, countries have been strengthening trade protection for their security, and the importance of securing strategic materials, such as food, is drawing attention. In addition to the cultural aspects, the global preference for food produced in Korea is increasing because of the Korean Wave. Thus, the Korean food industry can be developed into a high-value-added export food industry. Currently, Korea has a low self-sufficiency rate for foodstuffs apart from rice. Korea also suffers from problems arising from population decline, aging, rapid climate change, and various animal and plant diseases. It is necessary to develop technologies that can overcome the production structures highly dependent on the outside world of food and foster them into export-type system industries. The global agricultural industry-related technologies are actively being modified via data accumulation, e.g., environmental data, production information, and distribution and consumption information in climate and production facilities, and by actively expanding the introduction of the latest information and communication technologies such as big data and artificial intelligence. However, long-term research and investment should precede the field of living organisms. Compared to other industries, it is necessary to overcome poor production and labor environment investment efficiency in the food industry with respect to the production cost, equipment postmanagement, development tailored to the eye level of field workers, and service models suitable for production facilities of various sizes. This paper discusses the flow of domestic and international technologies that form the core issues of the site centered on the 4th Industrial Revolution in the field of agriculture, livestock, and fisheries. It also explains the environmental awareness production technologies centered on sustainable intelligence platforms that link climate change responses, optimization of energy costs, and mass production for unmanned production, distribution, and consumption using the unstructured data obtained based on detection and growth measurement data.

• Korean Journal of Artificial Intelligence
• /
• v.8 no.2
• /
• pp.11-16
• /
• 2020

Among the innovative companies leading the era of the 4th industrial revolution, the world's largest Internet company is Google. Google has grown by providing convenient services such as Internet search, Android smartphone operating system, and video. Now, Google is leading the global IT industry by continuing to develop in various new business fields based on open service platforms, artificial intelligence, and big data. In this study, an exploratory discussion was conducted on Google's success factors and future directions. The purpose of the research is to understand the development process of the IT field from the successfactors of Google and to analyze the development direction of the future IT industry. Google's success factors were its open platform policy and successful acquisitions of external companies. In fact, most of the services Google offers come from companies that have acquired and acquired them. In addition, there was a corporate culture that values and supportsthe spirit of challenge and autonomy of members who are not afraid of failure. Based on this study's review of Google's direction analysis, the follow-up study will infer the direction of the IT industry in depth and look at the future technologies that IT majors need to prepare.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.17 no.4
• /
• pp.190-197
• /
• 2024

The O2O store model dissolves the boundaries between online and offline platforms, providing significant convenience to customers. To effectively operate such platforms, small business owners must provide necessary information in digital format. Specifically, the process of digitizing Korean menus manually can lead to multiple issues, and the use of OCR technology often results in high error rates due to the low accuracy in recognizing Korean. In response, this paper proposes an enhanced OCR model based on the popular EasyOCR framework, aimed at improving the recognition accuracy of Korean. The proposed model integrates the structural advantages of VGG and ResNet, and incorporates an attention mechanism to significantly improve the recognition performance of Korean. Moreover, experimental results indicate that the proposed model achieved approximately a 3.5% improvement in accuracy and around a 1% improvement in both confidence score and normalized edit distance compared to EasyOCR. Therefore, this demonstrates that the proposed method effectively addresses the existing challenges.

• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.21-41
• /
• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of the Korean earth science society
• /
• v.44 no.4
• /
• pp.331-341
• /
• 2023

The goal of this study was to examine the PCK required for science teachers and PCK required for university teacher educators in terms of school science knowledge, science teaching and learning, and the role of science educators, which are the main axes of science education in future schools, and to explore the relationship between them. This study is a follow-up to a previous stage of research that explored the prospects for changes in schools in the future (2040-2050) in terms of school knowledge, educational methods, and teacher roles. Based on in-depth interviews, qualitative and semantic network analyses were conducted to derive and compare the characteristics of PCK and PCK. As for the main research results, science teacher PCK in future schools should include expertise in organizing science classes centered on convergence topics, expertise in digital platforms and ICT use, and expertise in building a network of learning communities and resources, as part of the expertise of human teachers differentiated from AI. Teacher educators' PCK includes expertise in the research and development of T-L methods using AI, expertise in the knowledge construction process and practice, and expertise in developing preservice teachers' research competencies. Discussed in the conclusion is the change in teacher PCK and teacher educator PCK with changes in science knowledge, such as convergence-type knowledge and cognition-value integrated knowledge; and the need to emphasize values, attitudes, and ethical judgments for the coexistence of humans and non-humans as school science knowledge in the post-humanism future society.

• Journal of Internet of Things and Convergence
• /
• v.10 no.1
• /
• pp.53-58
• /
• 2024

IoT, Big-data, AI, and Cloud technologies, which are core technologies of the 4th Industrial Revolution, have recently been applied to various fields and are being used as core technologies for new growth engines. Accordingly, these core technologies are applied to the agricultural field without exception, contributing to solving the problem of labor shortage, reducing production costs, and reducing environmental burden through remote and automated production without time and space constraints. However, as these core technologies are utilized, security incidents are occurring in the agricultural field as well. Accordingly, this study divides smart farms into three stages(Basic, Middle, and High) and presents the characteristics and security threats of each stage. In particular, as the number of container-based services and research increases under cloud platforms, we would like to suggest countermeasures focusing on security threats.