• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.149-163
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• 2012

Logistics systems provide their service to customers by coordinating the resources with limited capacity throughout the underlying processes involved to each other. To maintain the high level of service under such complicated condition, it is essential to carry out the real-time monitoring and continuous management of logistics processes. In this study, we propose a method of estimating the service completion time of key processes based on process-state information collected in real time. We first identify the factors that influence the process completion time by modeling and analyzing an influence diagram, and then suggest algorithms for quantifying the factors. We suppose the container terminal logistics and the process of discharging and loading containers to a vessel. The remaining service time of a vessel is estimated using a decision tree which is the result of machine-learning using historical data. We validated the estimation model using container terminal simulation. The proposed model is expected to improve competitiveness of logistics systems by forecasting service completion in real time, as well as to prevent the waste of resources.

• Journal of Satellite, Information and Communications
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• v.9 no.4
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• pp.87-90
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• 2014

Recently, environment facilities are able to manage real-time data collection and record management through integrated broadband modem LAN switching technology. Therefore, it need more stable and efficient facility management. So, we required practical use of environmental facilities convergence based on broadband integrated modem. In this paper, we proposed an integrated broadband modem LAN switching technology which can applicable to the environment facility. Also, we presented integrated broadband modem of design plan and communication system. And it received data inside of environment facility using the two communication methods(IEEE802.11x and IEEE802.15.4x). Then, our proposed integrated broadband modem LAN switching technology will prioritize processing data when emergency happen through collecting data, analysis data and processing. Lastly, we proved usefulness by experiment and simulation analysis.

• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.15-20
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• 2019

Music therapy has shown many benefits in the treatment of disabled children and the mind. Today's music therapy system is a situation where no specific treatment system has been built. In order for the music therapist to make an accurate treatment, various music therapy cases and treatment history data must be analyzed. Although the most appropriate treatment is given to the client or patient, in reality a number of difficulties are followed due to several factors. In this paper, we propose a music therapy knowledge management model which convergence the existing therapy data and text mining technology. By using the proposed model, similar cases can be searched and accurate and effective treatment can be made for the patient or the client based on specific and reliable data related to the patient. This can be expected to bring out the original purpose of the music therapy and its effect to the maximum, and is expected to be useful for treating more patients.

• Journal of Wetlands Research
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• v.21 no.2
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• pp.157-162
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• 2019

Recently, the occurrence of unusual heavy snow and cold are increasing due to the unusual global climate change. In particular, the temperature dropped to minus 69 degrees Celsius in the United States on January 8, 2018. In Korea, on February 17, 2014, the auditorium building in Gyeongju Mauna Resort was collapsed due to the heavy snowfall. Because of the tragic accident many studies on the reduction of snow damage is being conducted, but it is difficult to predict the exact damage due to the lack of historical damage data, and uncertainty of meteorological data due to the long distance between the damaged area and the observatory. Therefore, in this study, available data were collected from factors that are thought to be corresponding to snow damage, and the amount of snow damage was estimated categorically using a random forest. At present, the prediction accuracy was not sufficient due to lack of historical damage data and changes of the design code for green houses. However, if accurate weather data are obtained in the affected areas. the accuracy of estimates would increase enough for being used for be the degree preparedness of disaster management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.320-326
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• 2021

AVTE(Air Vehicle Test Equipment) is an equipment to inspect and check the status of on-board aircraft LRUs(Line Replacement Units) before and after flight for performing successful UAV(Unmanned Aerial Vehicle) missions. This paper suggests utilization of the AVTE as an operation support-equipment by implementing several critical functions for UAV-operation on the AVTE. The AVTE easily sets initialization(default) data and compensates for the installation and position errors of the LRUs which provide critical mission data and situation image with pilots without additional individual operation support-equipment. Major fault list and situation image data could be downloaded after flight using the AVTE in the event of UAV emergency situation or unusual occurrence on duty as well. We anticipate the suggested operational approach of the AVTE could dramatically reduce the cost and man power for design and manufacture of additional operation support equipment and effectively diminish workload of the operator.

• Journal of Digital Policy
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• v.1 no.2
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• pp.1-8
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• 2022

In case of a dangerous situation, the roof, which serves as an emergency exit, must be open in case of fire according to the Fire Act. However, when the roof door is opened, it has become a place of various incidents and accidents such as illegal entry, crime, and suicide. As a result, it is a reality to close the roof door in terms of facility management to prevent crime, various incidents, and accidents. Accordingly, the government is pushing to legislate regulations on housing construction standards, etc. that mandate the installation of electronic automatic opening and closing devices on rooftop doors. Therefore, in this paper, an intelligent emergency door opening/closing device system is proposed. To this end, an intelligent emergency door opening and closing system was developed by linking wired and wireless access counting and AI image analysis. Finally, it is possible to build a wireless communication-based integrated management platform that provides remote control and history management in a centralized method of device status real-time monitoring and event alarm.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.134-134
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• 2023

하천의 유사량 측정은 수량·수질 관리에 있어 유량 자료와 함께 필수적인 자료로 다지점에서 연속적으로 측정된 자료가 필요하다. 하지만 현재 부유사 측정 방법은 부유사채집기를 통해 조사가 이루어져 인력, 비용, 안전의 문제로 지점 확대와 연속 측정이 어려운 상황이다. 이러한 문제를 해결하기 위한 대안으로, 센서 기반의 유사량 측정 기술이 개발되어 실용화를 위한 연구들이 수행되고 있다. 특히, 연속적인 유량측정을 목적으로 사용되고 있는 자동유량관측소에 설치된 H-ADCP의 초음파산란도를 이용한 부유사농도 측정 방법은 기 구축된 인프라를 활용하므로 경제적으로 유리하며, 유량자료를 동시에 측정하므로 실시간의 부유사량 자료를 생산할 수 있는 장점이 있다. 이에 본 연구에서는 국가하천에 설치되어 운영 중인 자동유량관측소 H-ADCP의 초음파산란도를 활용하여 연속적인 부유사농도 측정을 위한 기술 개발과 기술 적용을 위한 기준 및 지침을 마련하고자 하였다. 초음파산란도를 활용한 부유사농도 측정 방법의 적용성 검토를 위해 2015년부터 2022년까지 자동 관측소 기준 유사량 측정이 이루어진 지점을 대상으로 자료를 수집하여 지점별 초음파산란도-부유사농도 관계식을 개발하여 분석을 수행하였다. 그리고 테스트베드에서 실시간 운영을 통해 초음파산란도를 활용한 부유사농도 측정 방법의 기술 개선과 분석 절차 및 기준 등 실무적 고려사항을 검토하여 실용화를 위한 지침 및 표준안을 마련하고자 하였다. 본 연구결과를 통해 기존 부유사채집기와 정확도를 분석한 결과, 기존 부유사대비 약 80%의 측정정확도를 보이는 것으로 나타났으며, 10분 간격의 부유사농도의 측정을 통해 홍수기 유사의 이력현상의 분석이 가능함을 확인 할 수 있었다. 추후에는 본 연구 성과를 통해서 개발한 기술을 시범 확대 적용하여 지속적인 기술의 개선과 측정기준을 제시하고, 유지관리 등에 대한 검토를 수행할 예정이며, 실용화를 통해 유사량 조사지점의 확대와 연속적인 유사량 자료를 생산하는데 기여할 것으로 기대된다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8357-8362
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• 2015

The emergency call device has been installed and operated for the elevator passenger safety, but the call can not be connected or delay to the operator in an emergency. The application of the Internet of Things(IoT) technology is required for the systematic management and reliability of the emergency call device installed in the elevator. To meet these requirements it is necessary to apply the RMS(Remote Management System). Emergency call device periodically reports the operating status information and the emergency call history information of the emergency call device to the RMS in the PSTN(Public Switched Telephone Network) environment, and transmits the call request information in an emergency. RAS(Remote Access Server) plays a role of converting the PSTN signals to TCP / IP. RMS reports a significant outbreak call and abnormal operating conditions to administrators. In this study, we developed optimized protocol to PSTN environment that is required by RMS and implemented its differentiated process. And a RAS-RMS Protocol was added to the Application Layer. Development protocol consisting of simple structure as compared to CoAP, MQTT or HTTP can work properly in low-spec CPU and transmit elevator emergency key information easily.

• Explosives and Blasting
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• v.38 no.4
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• pp.16-25
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• 2020

Multi-setting smart-investigation of the ground and large uncharged hole boring (MSP) method to reduce the blast-induced vibration in a tunnel excavation is carried out over 50m of long-distance boring in a horizontal direction and thus has been accompanied by deviations in boring alignment because of the heavy and one-directional rotation of the rod. Therefore, the deviation has been adjusted through the boring machine's variable setting rely on the previous construction records and expert's experience. However, the geological characteristics, machine conditions, and inexperienced workers have caused significant deviation from the target alignment. The excessive deviation from the boring target may cause a delay in the construction schedule and economic losses. A deep learning-based prediction model has been developed to discover an ideal initial setting of the MSP machine. Dropout, early stopping, pre-training techniques have been employed to prevent overfitting in the training phase and, significantly improved the prediction results. These results showed the high possibility of developing the model to suggest the boring machine's optimum initial setting. We expect that optimized setting guidelines can be further developed through the continuous addition of the data and the additional consideration of the other factors.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.1
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• pp.57-69
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• 2023

In a situation where digital transformation using artificial intelligence is active around the world, the growth of domestic AI companies or AI industrial ecosystems is slow. Where a large amount of government funds related to AI are being invested to overcome the difficult economic situation, systematic research on the effect is insufficient. So, this study aimed to examine the policy effectiveness of the government artificial intelligence solution voucher support project for small and medium-sized enterprises (SMEs) using Propensity Score Matching (PSM) and Difference-in-Differences (DID) on the financial performance of beneficiary companies. For empirical analysis, PSM-DID analysis was performed using sales performance since 2019 for 461 companies with a history of voucher support among the AI SMEs data released by the National IT Industry Promotion Agency. As a result of the analysis, the beneficiary companies' asset growth, salary, and R&D expenses increased overall after government support, and no significant contribution could be confirmed in terms of profits. This study suggests that the voucher policy business directly contributed to the company's growth in the short term, but it requires a certain period of time to generate profits.