• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.5
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• pp.1029-1036
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• 2018

This paper is a study on the development of optimal control system for lighting and air conditioning equipment to save the energy in campus environment. In the case of controling system developed through this research, lighting and air conditioner are controlled by both information on the number of people entering and leaving the room through the motion sensor and image processing, and the information on temperature and humidity. In addition, energy saving is enabled by the results that are controlled through data integration monitoring and command execution functions according to the control signals.

• International Journal of Contents
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• v.16 no.1
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• pp.75-86
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• 2020

As the elderly population is becoming an aging society, the elderly are experiencing many problems. Social security costs for the elderly are increasing and the un-linked social phenomenon is emerging. Thus, the social infrastructure and welfare system established in the past economic growth period are in danger of not functioning properly. People socially isolated or with chronic diseases among the elderly are exposed to various accidents. Thus, an active healthcare management service is imperative. Additionally, in the event of a dangerous situation, the system must have ways to notify guardians (family or medical personnel) regarding appropriate action. Thus, in this paper, we propose the smartphone-based healthcare and emergency response service platform. The proposed service platform aggregates movement of relevant data in real-time using a smartphone. Based on aggregated data, it will always recognize the user's movements and current state using the human motion recognition mechanism. Thus, the proposed service platform provides real-time status monitoring, activity reports, a health calendar, location-based hospital information, emergency situation detection, and cloud messaging server-based efficient notification to several subscribers such as family, guardians, and medical personnel. Through this service, users or guardians can augment the level of care for the elderly through the reports. Also, if an emergency situation is detected, the system immediately informs guardians so as to minimize the risk through immediate response.

• Journal of IKEEE
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• v.23 no.1
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• pp.22-28
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• 2019

This paper presents the monitoring method of machining error and quality check to improve the productivity of boring manufacturing process. Machining error usually appears as the offset of spatial location of actual cutting path compared to ideal cutting path. In order to monitor an error of workpiece, multiple factors affecting quality of boring, such as distortion of workpiece, clamping error, radial rotation error of the spindle and motion error of machine tools, were took into account. To verify the productive quality, we propose the quality check system. The system based on IT convergence analyzes the process error rate and saves the analyzed data in memory. Also, these play important roles in detecting an inferior production goods and can decrease the production cost and loss of bearing.

• Radiation Oncology Journal
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• v.32 no.2
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• pp.84-94
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• 2014

Purpose: To quantify the cardiac dose reduction during breathing adapted radiotherapy using Real-time Position Management (RPM) system in the treatment of left-sided breast cancer. Materials and Methods: Twenty-two patients with left-sided breast cancer underwent CT scans during breathing maneuvers including free breathing (FB), deep inspiration breath-hold (DIBH), and end inspiration breath-hold (EIBH). The RPM system was used to monitor respiratory motion, and the in-house self respiration monitoring (SRM) system was used for visual feedback. For each scan, treatment plans were generated and dosimetric parameters from DIBH and EIBH plans were compared to those of FB plans. Results: All patients completed CT scans with different breathing maneuvers. When compared with FB plans, DIBH plans demonstrated significant reductions in irradiated heart volume and the heart $V_{25}$, with the relative reduction of 71% and 70%, respectively (p < 0.001). EIBH plans also resulted in significantly smaller irradiated heart volume and lower heart $V_{25}$ than FB plans, with the relative reduction of 39% and 37%, respectively (p = 0.002). Despite of significant expansion of lung volume using inspiration breath-hold, there were no significant differences in left lung $V_{25}$ among the three plans. Conclusion: In comparison with FB, both DIBH and EIBH plans demonstrated a significant reduction of radiation dose to the heart. In the training course, SRM system was useful and effective in terms of positional reproducibility and patient compliance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.10
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• pp.2071-2078
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• 2009

In this paper, we proposed a non-contact respiration measurement system with ultrasonic proximity sensor. Ultrasonic proximity sensor approach of respiration measurement which respiration signatures and rates can be derived in real-time for long-term monitoring is presented. 240 kHz ultrasonic sensor has been applied for the proposed measurement system. The time of flight of sound wave between the transmitted signal and received signal have been used for a respiration measurement from abdominal area. Respiration rates measured with the ultrasonic proximity sensor were compared with those measured with standard techniques on 5 human subjects. Accurate measurement of respiration rate is shown from the 50 cm measurement distance. The data from the method comparison study is used to confirm the performance of the proposed measurement system. The current version of respiratory rate detection system using ultrasonic can successfully measure respiration rate. The proposed measurement method could be used for monitoring unconscious persons from a relatively close range, avoiding the need to apply electrodes or other sensors in the correct position and to wire the subject to the monitor. Monitoring respiration using ultrasonic sensor offers a promising possibility of non-contact measurement of respiration rates. Especially, this technology offers a potentially inexpensive implementation that could extend applications to consumer home-healthcare and mobile-healthcare products. Further advances in the sensor design, system design and signal processing can increase the range of the measurement and quality of the rate-finding for broadening the potential application areas of this technology.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.519-522
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• 2006

Accurate modeling of a dynamic system from experimental data is the bases for the model updating or heath monitoring of the system. Modal analysis or modal test is a routine process to get the modal parameters of a dynamic system. The modal parameters include the natural frequencies, damping ratios and mode shapes. This paper presents a new method that can derive the equations of motion for a dynamic system from the modal parameters obtained by the modal analysis or modal test. The present method based on the relation between the eigenvalues and eigenvectors of the state space equation derives the mass, damping and stiffness matrices of the system. The modeling of a cantilevered beam from modal parameters is an example to prove the efficiency and accuracy of the present method. Using the lateral displacements only, not the rotations, gives limited information for the system. The numerical verification up to now gives reasonable results and the verification with the test data is scheduled.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.848-851
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• 2002

Recently, there are lots of concerning on the integration of robot and virtual reality with the trends of the research of intelligent robot and mined reality. In this paper, a 3D GUI system is proposed based on Internet for remote controlling and monitoring of agent robot working for itself. The proposed system is consists of a manager ordering a new position and displaying the motion of robot, an agent robot moving to the destination according to the indication, a positioning module detecting the current position of robot, and a geographical information module. A user can order the robot agent move to a new position in a virtual space and watch the real images captured from the real sites of the robot. Then, the agent robot moves to the position automatically with avoiding collision by using range finding and a path detection algorithm. We demonstrate the proposed 3D GUI system is supporting a more convenient remote control means far the robots.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.760-763
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• 2001

In this study, the graphical design system is developed and the digital mock-up is implemented for designing the spent fuel handling and disassembling processes. This system is used throughout the design stages from the conceptual design to the motion analysis. By using this system, all the processes involved in the spent fuel handling and disassembling precesses are analyzed and optimized. Also, this system is used in developing the on-line graphic simulator to enhance the reliability and safety of the spent fuel handling process by providing the remote monitoring function of the process. The graphical design system and the digital mock-up system can be effectively used for designing the process equipment, as well as the optimization of the main processes and maintenance processes of the spent fuel management.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.395-405
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• 2018

Seakeeping safety module in Korean e-Navigation system is one of the ship remote monitoring services that is employed to ensure the safety of ships by monitoring the ship's real time performance and providing a warning in advance when the abnormal conditions are encountered in seakeeping performance. In general, seakeeping performance has been evaluated by simulating ship motion analysis under specific conditions for its design. However, due to restriction of computation time, it is not realistic to perform simulations to evaluate seakeeping performance under real-time operation conditions. This study aims to introduce a reasonable and faster method to predict a ship's roll motion which is one of the factors used to evaluate a ship's seakeeping performance by using a machine learning-based surrogate model. Through the application of various learning techniques and sampling conditions on training data, it was observed that the difference of roll motion between a given surrogate model and motion analysis was within 1%. Therefore, it can be concluded that this method can be useful to evaluate the seakeeping performance of a ship in real-time operation.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.443-452
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• 2020

Worker's awkward postures and unreasonable physical load can be corrected by monitoring construction activities, thereby increasing the safety and productivity of construction workers and projects. However, manual identification is time-consuming and contains high human variance. In this regard, an automated activity recognition system based on inertial measurement unit can help in rapidly and precisely collecting motion data. With the acceleration data, the machine learning algorithm will be used to train classifiers for automatically categorizing activities. However, input acceleration data are extracted either from designed experiments or simple construction work in previous studies. Thus, collected data series are discontinuous and activity categories are insufficient for real construction circumstances. This study aims to collect acceleration data during long-term continuous work in a construction project and validate the feasibility of activity recognition algorithm with the continuous motion data. The data collection covers two different workers performing formwork at the same site. An accelerator, as well as portable camera, is attached to the worker during the entire working session for simultaneously recording motion data and working activity. The supervised machine learning-based models are trained to classify activity in hierarchical levels, which reaches a 96.9% testing accuracy of recognizing rest and work and 85.6% testing accuracy of identifying stationary, traveling, and rebar installation actions.