• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.207-212
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• 2008

There are several sensors in the liquid cargo ship. In the liquid cargo ship, we can get values from various sensors that are level sensor, temperature sensor, pressure sensor, oxygen sensor, VOCs sensor, high overfill sensor, etc. It is important to guarantee the reliability of sensors. In order to guarantee the reliability of sensors, we have to study the diagnosis of sensor fault. The technology of smart sensor is widely used. In this paper, the technology of smart sensor is applied to diagnosis of level sensor fault for liquid cargo ship. In order to diagnose sensor fault and find the sensor position, in this paper, we proposed algorithms of diagnosis of sensor fault using independent sensor diagnosis unit and self fault diagnosis using sensor modeling. Proposed methods are demonstrated by experiment and simulation. The results show that the proposed approach is useful. Proposed methods are useful to develop smart level sensor.

• Journal of Convergence for Information Technology
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• v.7 no.3
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• pp.165-171
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• 2017

Recently, the development and dissemination of smart devices linked to the network are being actively performed, and IOT(Internet of things) is issued form of mutually cooperative relationship through interoperation within smart devices. In this paper, we propose an innovative intelligent coffee shop management system by sharing and cooperatively controlling smart devices and Internet devices. The system can order smartphones including kiosk orders and beacon-based user identification. And it is a system that can make custom order without grasping user location information using geofence. The paper provides weather, temperature, time and user-based recommendation services based on Big Data. Therefore, the system is increased cost reduction and work efficiency than general coffee shops.

• The Journal of Information Systems
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• v.31 no.2
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• pp.63-88
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• 2022

Purpose The purpose of this study is to empirically analyze the factors affecting the intention to use cloud computing in the smart work environment. This study is meaningful in that it examines the characteristics of smart work and the fit of cloud computing characteristics, and it is a study that reveals the factors affecting the intention to use cloud computing by applying the integrated model of TTF and TAM. Design/methodology/approach In order to understand the factors affecting the intention to use cloud computing in the smart work environment, a research model that integrates TTF and TAM with the hypothesis was proposed. In order to verify the research hypothesis, this study conducted a survey on individuals with experience in smart work and cloud computing. And with the data 280 collected in the survey, path analysis was performed using the PLS structural equation. Findings As a result, it was found that task characteristics and technology characteristics had a positive (+) effect on task-skill fit, and task-skill fit had a positive (+) effect on perceived ease of use and usefulness. Also, task-skill fit, perceived ease of use, and perceived usefulness were found to have a positive (+) effect on intention to use.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.224-226
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• 2021

Recently, in order to increase the efficiency of the product production process, the automation of facilities and devices in the factory is in progress, and a smart factory is being built using ICT and IoT technologies. In order to organically solve many problems occurring in the smart factory, a system for monitoring the wireless communication function between facilities and devices and the manufacturing process environment of the smart factory is required. In this paper, we propose a monitoring system using a Bluetooth module, a temperature/humidity sensor and a fine dust sensor to remotely monitor the process environment of a smart factory. The proposed monitoring system collect Arduino sensor values wirelessly through Bluetooth communication.

• Human Ecology Research
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• v.58 no.1
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• pp.13-29
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• 2020

This study investigated the relationship between preschoolers' smart media usage in regards to cognitive and language development, especially the mediating effect of preschoolers' smart media addiction tendency and the moderated mediating effect of maternal guidance on smart media usage. The study surveyed 273 preschoolers' mothers who lived in Daegu City and Kyungpook Province. The findings of this study were as follows. First, preschoolers' smart media addiction tendency mediated the relationship between smart media usage time in regards to cognitive and language development. Second, maternal active mediation and monitoring moderated the relationship between preschoolers' smart media usage time and smart media addiction tendency. Third, there was a maternal co-use moderated the mediating effect of preschoolers' smart media addiction tendency on language development. In conclusion, preschoolers' smart media addition tendency mediated the effect of smart media usage time on cognitive and language development. Among the mediation pathways, the influence of preschoolers' smart media addiction tendency on language development was moderated by maternal co-use. The findings of this study suggest that maternal guidance should be applied differently depending on preschoolers' smart media addiction tendency. This study examined preschoolers' and maternal smart media-related variables on preschoolers' cognitive and language development in order to provide preliminary data that can be used to explore the maternal guidance on how to use smart media for their preschool children.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1196-1213
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• 2020

There is a growing interest in the development of smart environments through predicting the behaviors of inhabitants of smart spaces in the recent past. Various smart services are deployed in modern smart cities to facilitate residents and city administration. Prediction algorithms are broadly used in the smart fields in order to well equip the smart services for the future demands. Hence, an accurate prediction technology plays a vital role in the smart services. In this paper, we take out an extensive survey of smart spaces such as smart homes, smart farms and smart cars and smart applications such as smart health and smart energy. Our extensive survey is based on more than 400 articles and the final list of research studies included in this survey consist of 134 research papers selected using Google Scholar database for period of 2008 to 2018. In this survey, we highlight the role of prediction algorithms in each sub-domain of smart Internet of Things (IoT) environments. We also discuss the main algorithms which play pivotal role in a particular IoT subfield and effectiveness of these algorithms. The conducted survey provides an efficient way to analyze and have a quick understanding of state of the art work in the targeted domain. To the best of our knowledge, this is the very first survey paper on main categories of prediction algorithms covering statistical, heuristic and hybrid approaches for smart environments.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.51-58
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• 2013

There is an increasing discussion about new teaching and learning methods in smart education environment due to the dissemination of smart devices. In this trend, in order to understand the smart education system, this study analyzed the domestic and foreign cases in K-12 smart education based on CTLA (Creation Teaching Learning Assessment) model through access to educational contents, environments, methods, and its curriculums. The teaching and learning methods in smart education are analyzed in foreign cases, domestic cases, and teaching-learning models presenting the positive part of the currently being implemented smart education and the further research for its improvement. Accordingly this study contributes to the specific formulation and successful realization of smart education.

• 전기의세계
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• v.60 no.11
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• pp.56-63
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• 2011

In the face of global warming and resource depletion, a smart grid has been suggested as one way of contributing to abating the environment problems and increasing energy efficiency. Smart grids utilize renewable energy which has intermittent and irregular output power depending on weather conditions. In order to maintain stability and reliability of the power system, smart grids need to have complementary measures for the possible unstable system conditions. Cogenerating systems such as Combined Heat and Power(CHP) can be one good solution as it has capability of instantly increasing or decreasing output power. Therefore, this paper investigates the connectivity between Combined Heat and Power systems and smart grid technologies. The smart grid national roadmap formulated by South Korea Ministry of Knowledge and Economy and 'IEC Smart Grid Standardization Roadmap' are analyzed to extract related components of the smart grid for the CHP connection. Also, case studies on demonstration projects for smart grids with CHP systems completed or currently being implementing in the world are presented.

• Journal of Digital Convergence
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• v.9 no.4
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• pp.235-244
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• 2011

According to spread of Smart Work introduction to public organizations & commercial enterprises, its being more focused on how to implement Smart Work effectively. So far current Smart Work, mainly Mobile Office has emphasized the speed & efficiency of management. But future Smart Work, Smart Work 2.0 must focus on the creativity & innovation of companies & people. In order to do that, the new technology like Social networking & Cloud computing should be applied. This study suggests Smart Work 2.0 implementation methodology including critical successful factors & solutions of Smart Work implementation through referencing existing implementation methodology and case study.

• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.17-28
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• 2020

Purpose: The purpose of this study is to confirm the strategic direction of the firm regarding the capabilities of the organization and its employees in order to increase the utilization and business performance of employees by that introduce smart factories in the domestic manufacturing industry. Research design, data, and methodology: This study derived a structured research model to confirm the mediating effect of recognition responses between the quality characteristics of smart factories and dynamic capabilities. For the analysis, a total of 143 valid questionnaires were used for 200 companies that introduced smart factories from domestic SME's. Results: Quality Characteristics of Smart Factory and Dynamic Capabilities had a statistically significant effect on Usefulness. Recognition Response had a statistically mediating on the relationship between quality characteristics of smart factory and business performance. Recognition Response had a statistically significant effect on business performance. Conclusions: It suggests that firms introducing smart factory reflect them in their empowerment strategic because the recognition responses of its employees differ according to the quality characteristics and dynamic capabilities of smart factories. It also means that the information derived from the smart factory system is useful and effective to business performance and employees.