• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4D
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• pp.499-507
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• 2009

A median barrier in the road is to separate driver and passenger the traffic flow in the 4-line over highway. In order to keep thee safety of and minimize the traffic jam in the traffic accidents, the ubiquitous intelligent median barrier system is proposed in this paper. This system is required to develop the sensor node fields in the median barrier, which detects the traffic accident using vibration sensors and wireless communication network. Free space test to sensing & receiving radio frequency, verification of middleware to report and countermeasure the accident intelligently to police and hospital are carried out.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.211-212
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• 2022

지구온난화에 따른 우리나라 주변 환경의 변화와 최근 중국 불법어선의 연근해 어업자원의 고갈 등으로 인해 우리나라 연근해 어족자원을 보호할 필요성이 증대되고 있으며, 지속 가능한 어업을 위해서는 어획물의 종류와 양을 정확히 파악하고 불법 어업에 대한 철저한 감시 및 관리가 필요하다. 시공간적으로 다양하게 변하는 생태 및 어장 환경 정보와 선박에 대한 정보를 통해 해양관측과 위성 원격탐사를 동시에 이용함으로써 근해와 원양 생물자원 실태를 관측하는 것이 가능하다. 본 연구에서는 야간 불빛 위성 Suomi-NPP (Suomi National Polar-orbiting Partnership) 및 후속위성인 NOAA-20의 VIIRS (Visible Infrared Imaging Radiometer Suite) DNB (Day & Night Band) 영상을 이용하여 야간 불빛을 활용하고자 한다. 이 불빛 위성 자료를 이용하여 야간에 조업하는 어선 선단의 공간 분포를 분석할 수 있다. 또한 이 불빛 위성 자료와 AIS 자료를 상호 비교하여, 불빛 위성 자료를 통해 실제 선박의 위치 정보를 검색하는 것이 가능함을 검증하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.269-272
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• 2023

본 논문은 디지털 플랫폼과 헬스케어 서비스를 통합한 병원 애플리케이션(병원 앱)의 개발 및 활용에 초점을 맞춘다. 목표는 환자와 의료 제공자 간의 의사 소통과 효율성을 향상시키는 것이다. 이 연구는 병원 앱의 주요 기능과 이점을 탐색하고, React Native를 사용하여 기술적 측면과 디자인 원칙을 제공하고, 적절한 사용 및 보안을 위한 지침을 검토한다. 이 연구는 병원 앱의 잠재력과 장점을 평가하고 의료 서비스 효율성과 품질을 향상시키기 위한 실용적인 지침을 제공하고 있다. 병원 앱의 통합으로 환자 치료, 커뮤니케이션을 개선하고 의료 프로세스를 간소화할 수 있다. React Native와 같은 기술을 활용하여 약속 일정, 예약 확인, 의료 정보 액세스, 의료 전문가 디렉토리와 같은 기능을 구현하여 포괄적인 사용자 경험을 제공할 수 있다. 지침과 규정을 준수하는 것은 의료 데이터의 적절한 사용과 보호를 보장하는 데 필수적이다. 향후 연구에서는 인공 지능 및 원격 의료와 같은 신기술을 병원 앱에 통합하고 장기적인 영향을 평가할 수 있다. 이 분야의 지속적인 개발과 혁신은 디지털 시대에 의료 서비스를 변화시킬 잠재력을 가지고 있다.

• Smart Media Journal
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• v.13 no.2
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• pp.136-144
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• 2024

In recent years, with the rapid development of IT technology and the aging of the population, various solutions to the labor shortage have emerged. In the livestock industry, there are an increasing number of management systems that utilize artificial intelligence technology. The Metaverse Smart Farm is a system that combines the digital virtual world with advanced agricultural technology. With this system, farmers can monitor the health of their animals in real time without having to visit the barns, and analyze the data collected through sensors and cameras for more efficient agricultural management. In addition, the barn environment can be adjusted through a remote control function, which is expected to reduce labor and revitalize the livestock industry.

• Journal of Engineering Education Research
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• v.27 no.4
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• pp.3-11
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• 2024

This study classified domestic and international systems by type, presenting their key features and examples, with the aim of outlining future directions for system development and research. AI-based learning assistance systems can be categorized into instructional-learning evaluation types and academic recommendation types, depending on their purpose. Instructional-learning evaluation types measure learners' levels through initial diagnostic assessments, provide customized learning, and offer adaptive feedback visualized based on learners' misconceptions identified through learning data. Academic recommendation types provide personalized academic pathways and a variety of information and functions to assist with overall school life, based on the big data held by schools. Based on these characteristics, future system development should clearly define the development purpose from the planning stage, considering data ethics and stability, and should not only approach from a technological perspective but also sufficiently reflect educational contexts.

• Journal of Korea Technology Innovation Society
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• v.16 no.4
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• pp.954-977
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• 2013

This paper investigates the factors to affect the consumer selection of machine-to-machine (M2M) technology in the purchase and utilization of home appliances. M2M technology, based on mobile internet, allows for automatic operation and remote control of home appliances and equipment. The introduction of M2M technology could lead to the saving of domestic housework and of active social participation for women. With a view to focusing on the liberating potential of M2M technology, this paper analyzes the correlation between four independent variables (gender, income, employment status of married woman, and possession of mobile internet devices) and two dependent variables (intention for purchase and utilization of M2M household appliances). The possession of mobile internet devices such as smart phone and tablet PC turns out to be the most significant factor to affect both the purchase and utilization of M2M household appliances. The employment status (employed or not-employed) affects only the intention for purchase. Neither the income level nor gender has significant correlation with the intention for purchase or utilization. The results differ from the conventional wisdom that the consumer selection of household technology is substantially affected by gender, income and employment of housewife.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.205-227
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• 2002

Our study is focused on a multiple-agent system to provide efficient collaborative work by automating the conference calling process with the help of intelligent agents. Automating the meeting scheduling requires a careful consideration of the individual official schedule as well as the privacy and personal preferences. Therefore, the automation of conference calling needs the distributed processing task where a separate calendar management process is associated for increasing the reliability and inherent parallelism. This paper describes in detail the design and implementation issues of a multiple-agent system for conference calling that allows the convener and participants to minimize their efforts in creating a meeting. Our system is based on the client-sewer model. In the sewer side, a scheduling agent, a negotiating agent, a personal information managing agent, a group information managing agent, a session managing agent, and a coordinating agent are operating. In the client side, an interface agent, a media agent, and a collaborating agent are operating. Agents use a standardized knowledge manipulation language to communicate amongst themselves. Communicating through a standardized knowledge manipulation language allows the system to overcome heterogeneity which is one of the most important problems in communication among agents for distributed collaborative computing. The agents of our system propose the dates on which as many participants as possible are available to attend the conference using the forward chaining algorithm and the back propagation network algorithm.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.203-209
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• 2021

In this study, a prototype design model was proposed for developing an online recruitment system through multi-dimensional data crawling and social media analysis, and validates text information and video interview in job application process. This study includes a comparative analysis process through text mining to verify the authenticity of job application paperwork and to effectively hire and allocate workers based on the potential job capability. Based on the prototype system, we conducted performance tests and analyzed the result for key performance indicators such as text mining accuracy and interview STT(speech to text) function recognition rate. If commercialized based on design specifications and prototype development results derived from this study, it may be expected to be utilized as the intelligent online recruitment system technology required in the public and private recruitment markets in the future.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.38-43
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• 2022

Smart sewage treatment plant means creating a safe and clean water environment by establishing an ICT-based real-time monitoring, remote control management and intelligent system for the entire sewage treatment process. The core technology of such a smart sewage treatment plant can be operation control technology using measuring instruments. This research team analyzed and suggested the operation control technologies necessary for the establishment of the intelligent business by referring to the intelligent research projects of the sewage treatment plant in progress in Korea. As a result of the analysis, a total of six removal technologies were presented, including control by scale, reflow water control, linked treated water control, chemical quantity control, winter operation control, and total organic carbon control. By size, standards that can be classified into small and medium-sized large-scale are presented, and in the case of reflow water control, the location of water quality and flow sensors capable of managing reflow water is suggested. In the case of the linked treated water control, the influence and control points of the linked treated water on the sewage treatment plant were presented, and in the case of the chemical injection volume control, a system capable of optimizing the amount of chemical injection according to the introduction of an intelligent sewage treatment plant was presented. In the case of winter operation, the sensors and pumps to be controlled are suggested when considering the decrease in nitrification due to the decrease in water temperature. In the case of total organic carbon control, an interlocking system considering the total amount of pollution in the future was proposed. These operation control scenarios are expected to be used as basic data to be used in intelligent sewage treatment algorithms and scenarios in the future.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.