• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.208-213
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• 2016

In the fourth industrial revolution, customization is becoming a conversation topic in various domains. Industry 4.0 applies cyber-physical systems (CPS), the Internet of Things (IoT), and cloud computing to manufacturing businesses. One of the main phrases in Industry 4.0 is mass customization. Optimized products or services are developed and provided through customization. Therefore, the competitiveness of a product can be enhanced, and satisfaction is improved. In particular, as IoT technology spreads, customization is an essential aspect of smooth service connections between various devices or things. Customized services in mobile applications are assembled and operate in various mobile devices in the mobile environment. Therefore, this paper proposes a method for improving customized cloud server-based mobile architectures, processes, and metrics, and for measuring the performance improvement of the customized architectures operating in various mobile devices based on the Android or IOS platforms. We reduce the total time required for customization in half as a result of applying the proposed customized architectures, processes, and metrics in various devices.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.216-221
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• 2022

The 4th industrial revolution is accelerating the transition to digital innovation in various aspects of our daily lives, and efforts for manufacturing innovation are continuing in the manufacturing industry, such as smart factories. The 4th industrial revolution technology in manufacturing can be used based on AI, big data, IoT, cloud, and robots. Through this, it is required to develop a technology to establish a production facility data collection and analysis system that has evolved from the existing automation and to find the cause of defects and minimize the defect rate. In this paper, we implemented a system that collects power, environment, and status data from production facility sites through IoT devices, quantifies them in real-time in a cloud computing environment, and displays them in the form of MQTT-based real-time infographics using widgets. The real-time sensor data transmitted from the IoT device is stored to the cloud server through a Rest API method. In addition, the administrator could remotely monitor the data on the dashboard and analyze it hourly and daily.

• Journal of Software Engineering Society
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• v.27 no.1
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• pp.8-14
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• 2018

As cloud computing has emerged as a hot trend in the IT industry, various types of cloud services have emerged. In addition, cloud service broker (CSB) technology has emerged to alleviate the complexity of the process of selecting the desired service that user wants among the various cloud services. One of the key features of the CSB is to recommend the best cloud services to users. In general, CSB can use a method to evaluate a service by receiving feedback about a service from users in order to recommend a cloud service. However, since each user has different criteria for giving a rating, there is a problem that reliability of service evaluation can be low when the rating is only used. In this paper, a method is proposed to supplement evaluation of rating based service by applying machine learning based sentiment analysis to cloud service user's review. In addition, the CSB prototype is implemented based on proposed method. Further, the results of comparing the performance of various learning algorithms is proposed that can be used for sentiment analysis through experiments using actual cloud service review as learning data. The proposed service evaluation method complements the disadvantages of the existing rating-based service evaluation and can reflect the service quality in terms of user experience.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.3
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• pp.69-78
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• 2019

The amount of data is increasing significantly as information and communication technology advances, mobile, cloud computing, the Internet of Things and social network services become commonplace. As the data grows exponentially, there is a growing demand for services that recommend the information that users want from large amounts of data. Collaborative filtering method is commonly used in information recommendation methods. One of the problems with collaborative filtering-based recommendation method is the cold start problem. In this paper, we propose a method to improve the cold start problem. That is, it solves the cold start problem by mapping the item evaluation data that does not exist to the initial user to the automatically generated data from the mobile app. We describe the main contents of the proposed method and explain the proposed method through the book recommendation scenario. We show the superiority of the proposed method through comparison with existing methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.733-739
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• 2013

Recently mobile service industry has grown very rapidly. In this paper, I investigated the changes in mobile service industry as well as new direction of human life in future global society. Under these changing market conditions, competition has been also changed into global and ecological competition. But compared to the platform initiatives and ecological strategies of global companies, Korean companies' vision of building ecosystems is still unclear. New directions of mobile service industry are smart phone oriented open market, UCC, QPS and cloud computing. As such, I investigate the structure of mobile service ecosystem in order to gain strategic implications and insights in this paper.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5231-5248
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• 2016

As a service-oriented paradigm, web service composition has obtained great attention from both academia and industry, especially in the area of cloud service. Nowadays more and more web services providing the same function but different in QoS are available in cloud, so an important mission of service composition strategy is to select the optimal composition solution according to QoS. Furthermore, the selected composition solution should satisfy the service level agreement (SLA) which defines users' request for the performance of composite service, such as price and response time. A composite service is feasible only if its QoS satisfies user's request. In order to obtain composite service with the optimal QoS and avoid SLA violations simultaneously, in this paper we first propose a QoS evaluation method which takes the SLA satisfaction into account. Then we design a service selection algorithm based on our QoS evaluation method. At last, we put forward a parallel running strategy for the proposed selection algorithm. The simulation results show that our approach outperforms existing approaches in terms of solutions' optimality and feasibility. Through our running strategy, the computation time can be reduced to a large extent.

• Journal of Internet of Things and Convergence
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• v.9 no.2
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• pp.55-60
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• 2023

Recently, demand for cloud computing has increased and remote access due to home work and external work has increased. In addition, a new security paradigm is required in the current situation where the need to be vigilant against not only external attacker access but also internal access such as internal employee access to work increases and various attack techniques are sophisticated. As a result, the network security model applying Zero-Trust, which has the core principle of doubting everything and not trusting it, began to attract attention in the security industry. Zero Trust Security monitors all networks, requires authentication in order to be granted access, and increases security by granting minimum access rights to access requesters. In this paper, we explain zero trust and zero trust architecture, and propose a new cloud security system for strengthening access control that overcomes the limitations of existing security systems using zero trust and blockchain and can be used by various companies.

• International journal of advanced smart convergence
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• v.5 no.2
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• pp.59-65
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• 2016

With the recent growth in cloud computing, big data processing and collaboration between businesses are emerging as new paradigms in the IT industry. In an environment where a large amount of data is generated in real time, such as SNS, big data processing techniques are useful in extracting the valid data. MapReduce is a good example of such a programming model used in big data extraction. With the growing collaboration between companies, problems of duplication and heterogeneity among data due to the integration of old and new information storage systems have arisen. These problems arise because of the differences in existing databases across the various companies. However, these problems can be negated by implementing the MapReduce technique. This paper proposes a collaboration system based on Database as a Service, or DBaaS, to solve problems in data integration for collaboration between companies. The proposed system can reduce the overhead in data integration, while being applied to structured and unstructured data.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.40-42
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• 2011

Smart hand-held devices like iPhone, iPad, Andriod and other mobile-OS machines are becoming a well known part of our daily lives. Utilization of these devices has gone beyond the expectations of their inventors. Evolution of Apple's iOS from a mobile phone Operating System to a wholesome platform for Portable Gaming is an adequate proof. Using these smart devices people are downloading applications from numerous online App Stores. Utilizing remote storage facilities and confining themselves to computing power far below than an entry level laptop, netbooks have emerged. Google's idea of Chrome OS coupled with Google's AppEngine is an eye-opener for researchers and developers. Keeping all these industry-proven innovations in mind we are proposing a Context-Driven Cloud-Oriented Application Architecture for smart devices. This architecture enables our smart devices to behave smarter by utilizing very less of local resources.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.480-486
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• 2012

There has been an increasing interest in new industry and demand creations by the convergence and integration between IT and infrastructure and BT, NT, and CT and the convergence of IT and spread of cloud computing have changed the IT service environment. Even in the educational field, the convergence and integration of contents with various IT have rapidly emerged and learning equipments for the educational purpose have expanded to the mobile media platform from PCs so that learning without limitations to time, place and equipment has become possible. Contents necessary for the smart education are under way by research development utilizing cyber reality and simulation, and 3D technologies. The purpose of this study is to propose marine contents use and service plans for the educational purpose in order to produce various types of contents for the marine life and environment, to improve the school achievement by stimulating interest and to provide individually customized learning.