• IE interfaces
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• v.12 no.3
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• pp.374-381
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• 1999

In this paper, we propose an architecture of the DNC system for Shop Floor Control/Point of Production(SFC/POP). The DNC system to be presented this paper retrieves line-up sheets which include the drawing information, making a index database for line-up sheets, NC programs and tool adjustment data. And it is interface with a raw material, jig and tool information. Also, the DNC system transmits operation information to real workers rapidly, and supports realtime monitoring by collecting the state information of machines directly. In the analysis and design phases, this paper models realtime events using the state transition diagrams. In the implementation phase, we use the ORACLE DBMS(Database Management System) as the DBMS and Developer 2000 and Microsoft Visual C++ 5.0 as the programming tools.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.442-445
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• 1997

A challenging activity in the manufacturing industry is to perform in real time the continuous monitoring of the process state, the situation assessment and identification of the problem on line and diagnosis of the cause and importance of the problem if he process does not work properly. This paper describes LAT(Ladder Analysis Tool) system for fault tree generation to improving the fault diagnosis of CNC machine tools. The system consists of 4 steps which can automatically ladder analysis from ladder diagram to two diagnosis function models. The two diagnostic models based on he ladder diagram is switching function model and step switching function model. This system tries to overcome diagnosis deficiencies present machine tool.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.5
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• pp.1176-1181
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• 1995

Microdrilling is one of the most difficult operations because of the poor chip discharge and the weakness of tool. This study is concerned about the development of a microdrilling monitoring system that is useful for minimizing the tool breakage and enhancing the machinability in the air spindle based microdrilling. The system is composed of a drilling state detection unit and an adaptive step-feed control unit that controls the micro-stepping motor driven spindle axis. Drilling states such as overload, tood breakage are recognized by the change of the air spindle speed which is measured via the reflective photo sensor. Based on the monitoring results, the adaptive step-feed control algorithm adjusts the step increment to keep the decrease of spindle speed within a specified range. The results of evaluation tests have shown that the developed system is very effective to prevent the breakage of microdrill and improves the productivity in comparison with the conventional microdrilling.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.9
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• pp.359-364
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• 2006

In modern EMS, state estimation is used as a tool for monitoring how the power system operates. A state estimator iteratively calculates the voltage profile of the currently operating power system with voltage, current, and power measurements gathered from the entire system. It is usually assumed that all the measurements are obtained simultaneously. It, however, is not practically possible to maintain the synchronism of the measurements data. Recently, phasor measurements synchronized by satellites are used for the operation of the power systems. This paper describes the state estimator modified to support the processing of synchronized phasor measurements. Synchronized phasor measurements are found to provide synchronism of measurement data and improve the nccuracy/redundancy of the results of running it are presented.

• Journal of Korea Game Society
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• v.8 no.4
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• pp.65-73
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• 2008

In this paper, we designed and implemented edutainment platform that can be effectively applied to developmental disabilities for their education and treatment of sensibility and intelligence training. We developed embedded hardware and contents authoring tool to make multimedia contents operated on the hardware, a management tool to provide result of training, and a real-time monitoring tool for observing the state of study. The hardware is designed by considering the characteristics of developmental disabilities and provides visual, auditory and tactile sense to assist sensibility training for their attention. User-friendly and easy-to-use authoring tool enable teachers and non-specialist to make educational contents. Also the real-time monitoring tool make us to observe user's status even in the outside of classroom. The management tool stores result of training and make us to review the result for further steps. Using this edutainment platform, efficient repetitive training is possible without restriction of time and location. Also when it applied to practical education, we can recognize that our system is effective on improving the ability of attention and studying.

• Journal of the Korean Geophysical Society
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• v.8 no.1
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• pp.7-14
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• 2005

Early detection in real-time response of slope movements ensures tremendous saving of lives and repair costs from catastrophic disaster. Therefore, it is essential to constantly monitor the performance and integrity of slope-stabilizing structures such as Rock bolt, Nail and Pile during or after installation. We developed a novel monitoring system using Fiber Bragg Grating (FBG) sensor. It's advantages are highly sensitivity, small dimension and electro-magnetic immunity. capability of multiplexing, system integrity, remote sensing - these serve real-time health monitoring of the structures. Real-time strain measurement by the signal processing program is shown graphically and it gives a warning sound when the monitored strain state exceeds a given threshold level so that any sign of abnormal disturbance on the spot can be easily perceived.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.310-314
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• 2023

In this paper, we show that the limitations of Holter monitoring and Wearable Electrocardiogarphy Devices and their arrhythmia detection. Sudden death caused by cardiovascular disease, often referred to as the "silent killer" due to its unpredictable nature, is a major health concern. Electrocardiography (ECG) is a basic diagnostic tool for detecting heart disease, but its limitations make it difficult to detect arrhythmia, a significant indicator of an irregular heart state. To address this limitation, a long-term continuous ECG recording device has been developed, Holter ECG device and wearable device. A significant number of studies have focused on the differences between Holter monitoring and wearable devices. The Holter tests were useful for detecting regularly occurring arrhythmias, whereas wearable patches were better at detecting random and infrequent arrhythmias. Wearable patches were effective in detecting episodes of arrhythmia and myocardial ischemia. Despite the concern, wearable devices had less signal loss than Holter monitoring and patients also preferred wearable devices over Holter monitoring due to convenience. These results could mean that the wearable devices can perfectly replace the Holter test.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.3
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• pp.701-707
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• 2024

Industry 4.0 has brought about significant changes in the roles of workers through the introduction of innovative technologies. In smart factory environments, workers are required to interact seamlessly with robots and automated systems, often utilizing equipment enhanced by Virtual Reality (VR) and Augmented Reality (AR) technologies. This study aims to systematically analyze recent research literature on monitoring the physical and mental states of workers in Industry 4.0 environments. Relevant literature was collected using the Web of Science database, employing a comprehensive keyword search strategy involving terms related to Industry 4.0 and health monitoring. The initial search yielded 1,708 documents, which were refined to 923 journal articles. The analysis was conducted using VOSviewer, a tool for visualizing bibliometric data. The study identified general trends in the publication years, countries of authors, and research fields. Keywords were clustered into four main areas: 'Industry 4.0', 'Internet of Things', 'Machine Learning', and 'Monitoring'. The findings highlight that research on health monitoring of workers in Industry 4.0 is still emerging, with most studies focusing on using wearable devices to monitor mental and physical stress and risks. This study provides a foundational overview of the current state of research on health monitoring in Industry 4.0, emphasizing the need for continued exploration in this critical area to enhance worker well-being and productivity.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.171-178
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• 2017

Data mashup is a web technology that combines information from multiple sources into a single web application. Mashup applications create a new horizon for new services, like environmental monitoring. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations utilize a data mashup to merge datasets from different Internet of multimedia things (IoMT) context-based services in order to leverage its data analytics performance and the accuracy of the predictions. However, mashup different datasets from multiple sources is a privacy hazard as it might reveal citizens specific behaviors in different regions. The ability to preserve privacy in mashuped datasets and at the same time provide accurate insights becomes a key success for the spread of mashup services. In this paper, we present our efforts to build a fog-based middleware for private data mashup (FMPM) to serve a centralized environmental monitoring service. The proposed middleware is equipped with concealment mechanisms to preserve the privacy of the merged datasets from multiple IoMT networks involved in the mashup application. Also, these mechanisms preserve the aggregates in the dataset to maximize the usability of information to attain accurate analytical results. We also provide a scenario for IoMT-enabled data mashup service and experimentation results.

• Smart Structures and Systems
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• v.11 no.4
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• pp.331-348
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• 2013

Effective monitoring, reliable data analysis, and rational data interpretations are challenges for engineers who are specialized in bridge health monitoring. This paper demonstrates how to use the Global Positioning System (GPS) and accelerometer data to accurately extract static and quasi-static displacements of the bridge induced by ambient effects. To eliminate the disadvantages of the two separate units, based on the characteristics of the bias terms derived from the GPS and accelerometer respectively, a wavelet based multi-step filtering method by combining the merits of the continuous wavelet transform (CWT) with the discrete stationary wavelet transform (SWT) is proposed so as to address the GPS deformation monitoring application more efficiently. The field measurements are carried out on an existing suspension bridge under the normal operation without any traffic interference. Experimental results showed that the frequencies and absolute displacements of the bridge can be accurate extracted by the proposed method. The integration of GPS and accelerometer can be used as a reliable tool to characterize the dynamic behavior of large structures such as suspension bridges undergoing environmental loads.