• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.31-37
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• 2021

Recently, in the market of home appliances, the technical differentiation of products using convergence technology has been receiving a lot of response to satisfy consumer demand. However, air-conditioner products are an area that requires research and development in the early stages of convergence technology. In this paper, it is developed that a non-contact bio-signal(respiration, movement) collection technology using IR-UWB(Impulse-Radio Ultra Wideband) technology, which controls the air-conditioner direction according to the user's location and also monitors sleep to provide an optimal sleep environment. In addition, emotional lighting and ASMR are developed to provide a comfortable and emotional place of life. Finally, based on the developed convergence technology, we develop intelligent smart air-conditioning services for the convenience of daily life and a comfortable resting space.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.791-797
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• 2022

Through recent metaverse marketing case studies, success factors and activation methods were analyzed from the perspective of content, platform, network, and device of the metaverse ecosystem in each industry. The importance of contents and platform of metaverse could be found in entertainment, fashion, office space and real estate, education, advertisement and commerce industries. In order to vitalize the metaverse, firstly, it is necessary to strengthen active participation and retention by providing a stable revenue model for market participants. Secondly, the importance of attractive content to expand subscribers is a key trigger for metaverse activation. Thirdly, it is necessary to increase the convenience of using metaverse service by using a light and simple device for the user. Fourthly, a win-win cooperation strategy should be supported in the value chain of the industry through ecosystem scalability. In addition, business opportunities for market participants and additional revenue models should be continuously provided.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.272-275
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• 2022

Large-scale online platforms such as MOOCs-Massive Open Online Courses, which provide a variety of educational contents, have provided a learning environment that allows students to freely access and learn anytime and anywhere. Currently, the proportion of online lectures and home-based learning is increasing, and portfolio or experience-based learning such as bootcamp, field activities, and team project-based group learning are also being actively carried out for educational outcomes. At present, interest in nano or microdegree focused on core technology in units of hours or credits is increasing significantly because such strategic intensive education enables effective learning in terms of continuity and efficiency of education. In an era of large changes in job market due to the reorganization of the industrial structure by new technologies, intensive education in specialized new technology fields such as smart mobility, big data, and artificial intelligence is much more conducive to finding a job. With this reason it is attracting attention as an alternative to lifelong learning are receiving In this paper we propose an educational platform that can efficiently and effectively support the purpose learning for the personalized microdegree education in the online learning era.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.4
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• pp.745-754
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• 2019

As GeoWeb 2.0 technologies are widely used, various kinds of services that mashup spatial data and user data are being developed. In particular, various spatial information platforms such as Google Maps, OpenStreetMap, Daum Map, Naver Map, olleh Map, and VWorld based on GeoWeb 2.0 technologies support mashup service. The mashup service which is supported through the Open APIs of the platforms, provides various kinds of spatial data such as 2D map, 3D map, and aerial image. Also, application fields using the mashup service are greatly expanded. Recently, as user data for mashup have been greatly increased, there was a problem in mashup performance. However, the research on the mashup performance improvement is currently insufficient, even the research on the mashup performance comparison of various platforms has not been performed. In this paper, we perform comparative analysis of the mashup performance for large amounts of user data and spatial data using various spatial information platforms available in Korea. Specifically, we propose two performance analysis indexes of mashup time and user interaction time in order to analyze the mashup performance efficiently. Also, we implement a system for the performance analysis. Finally, from the performance analysis result, we propose a spatial information platform that can be efficiently applied to cases when user data increases greatly and user interaction occurs frequently.

• The Journal of Bigdata
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• v.3 no.2
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• pp.79-85
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• 2018

As the utilization of chatbots grows and the AI market grows, many companies are interested. And everybody is spurring growth by offering chatbot build services so that they can create chatbots. This makes chatbots easier to service on the messenger platform, which is changing the existing application market. In this paper, we present a methodology for designing and implementing existing DB-based applications as instant messenger platform-based applications, and summarize what to consider in actual implementation to provide an optimal system structure. According to this methodology, we design and implement a chatbot that serves as an teaching advisor who provides information to the students in the curriculum. The implemented application objectively visualizes the user's desired information from the user's point of view and delivers it through the interactive interface quickly and intuitively. By implementing these services and real service, it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. it is predicted that DB-based information providing applications will be implemented as chatbots and will be changed to bi-directional communication through an interactive interface. Enterprise legacy application will take chatbot technology as one of important digital transformation initiative.

• Informatization Policy
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• v.30 no.1
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• pp.89-108
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• 2023

Science, technology and innovation (STI) has expanded the activity of actors from the traditional physical territory to the cyberspace. Data-driven platform services and markets advance new discussions on cross-border cooperation and cyber security, as well as discourse on sovereignty in cyberspace. These changes are also affecting the hegemony competition between the US and China. In particular, competition for aid to developing countries that are located along major resource transportation routes, such as natural gas and deep sea resources, is fierce. ASEAN is not only a geopolitical military and security point where the US and China powers collide, but its population of 600 million has great potential for the development of the digital economy due to its data resources. In this regard, this article aims to connect the discourse of liberalism and authoritarianism with data regulation and cybersecurity in international development cooperation, and derive implications for ASEAN integration through this. This study has significance as a convergence study that links international political issues related to big data in terms of global governance.

• Korean Chemical Engineering Research
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• v.58 no.4
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• pp.565-572
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• 2020

This study developed a software platform using machine learning of artificial intelligence to optimize the distillation column system. The distillation column is representative and core process in the petrochemical industry. Process stabilization is difficult due to various operating conditions and continuous process characteristics, and differences in process efficiency occur depending on operator skill. The process control based on the theoretical simulation was used to overcome this problem, but it has a limitation which it can't apply to complex processes and real-time systems. This study aims to develop an empirical simulation model based on machine learning and to suggest an optimal process operation method. The development of empirical simulations involves collecting big data from the actual process, feature extraction through data mining, and representative algorithm for the chemical process. Finally, the platform for the distillation column was developed with verification through a developed model and field tests. Through the developed platform, it is possible to predict the operating parameters and provided optimal operating conditions to achieve efficient process control. This study is the basic study applying the artificial intelligence machine learning technique for the chemical process. After application on a wide variety of processes and it can be utilized to the cornerstone of the smart factory of the industry 4.0.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.5
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• pp.715-721
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• 2018

With the spread of mobile devices, the users of social network services or e-commerce sites have increased dramatically, and the amount of data produced by the users has increased exponentially. E-commerce companies have faced a task regarding how to extract useful information from a vast amount of data produced by the users. To solve this problem, there are various studies applying big data processing technique. In this paper, we propose a collaborative filtering method that applies the tag weight in the Apache Spark platform. In order to elevate the accuracy of recommendation, the proposed method refines the tag data in the preprocessing process and categorizes the items and then applies the information of periods and tag weight to the estimate rating of the items. After generating RDD, we calculate item similarity and prediction values and recommend items to users. The experiment result indicated that the proposed method process large amounts of data quickly and improve the appropriateness of recommendation better.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.667-680
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• 2016

As distributed computing platforms like Hadoop MapReduce have been developed, it is necessary to perform the conventional query processing techniques, which have been executed in a single computing machine, in distributed computing environments efficiently. Especially, studies on similarity join query processing in distributed computing environments have been done where similarity join means retrieving all data pairs with high similarity between given two data sets. But the existing similarity join query processing schemes for distributed computing environments have a problem of skewed computing load balance between clusters because they consider only the data transmission cost. In this paper, we propose Matrix-based Load-balancing Algorithm for efficient similarity join query processing in distributed computing environment. In order to uniform load balancing of clusters, the proposed algorithm estimates expected computing cost by using matrix and generates partitions based on the estimated cost. In addition, it can reduce computing loads by filtering out data which are not used in query processing in clusters. Finally, it is shown from our performance evaluation that the proposed algorithm is better on query processing performance than the existing one.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1670-1675
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• 2021

The adoption of smart construction technology in the construction industry is progressing rapidly. By utilizing smart construction technologies such as BIM (Building Information Modeling), drones, artificial intelligence, big data, and Internet of Things technology, it has the effect of lowering the accident rate at the construction site and shortening the construction period. In order to introduce a digital twin platform for construction site management, real-time construction site management is possible in real time by constructing the same virtual space. The digital twin virtual space construction method collects and processes data from the entire construction cycle and visualizes it using a 3D model file. In this paper, we introduce a modeling automation technique that constructs an efficient digital twin space by automatically generating 3D modeling that composes a digital twin space based on 3D spatial data.