• Journal of the Korean Society for Precision Engineering
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• v.29 no.12
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• pp.1313-1320
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• 2012

Condition monitoring of the reciprocating compressor is important task. As a traditional method, health monitoring system of refrigerator depends on decision of a skilled person based on his experience. However, the skilled person cannot monitor all the compressors completely. If a sampled compressor is faulty, thousands of compressors manufactured at that place are regarded as faulty compressors. Therefore it is necessary to monitor all compressors in the production line. In the paper real time health monitoring system is developed based on high order time frequency method and artificial neural network. The system is installed in the mass production line. The result of the application has been very successful, and currently the system is working very well on the production line.

• Smart Structures and Systems
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• v.18 no.2
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• pp.317-334
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• 2016

Structural Health Monitoring System (SHMS) works as an efficient platform for monitoring the health status and performance deterioration of engineering structures during long-term service periods. The objective of its installation is to provide reasonable suggestions for structural maintenance and management, and therefore ensure the structural safety based on the information extracted from the real-time measured data. In this paper, the SHMS implemented on a world-famous kilometer-level cable-stayed bridge, named as Sutong Cable-stayed Bridge (SCB), is introduced in detail. The composition and core functions of the SHMS on SCB are elaborately presented. The system consists of four main subsystems including sensory subsystem, data acquisition and transmission subsystem, data management and control subsystem and structural health evaluation subsystem. All of the four parts are decomposed to separately describe their own constitutions and connected to illustrate the systematic functions. Accordingly, the main techniques and strategies adopted in the SHMS establishment are presented and some extension researches based on structural health monitoring are discussed. The introduction of the SHMS on SCB is expected to provide references for the establishment of SHMSs on long-span bridges with similar features as well as the implementation of potential researches based on structural health monitoring.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.62-69
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• 2008

In this paper, we proposed the real-time bio-signals monitoring system that is based on the ZigBee wireless sensor network and SIP. This system makes medical team and user easily confirm user's medical state irrelative to their location and time. The communication between medical sensors and the user's end device uses the ZigBee wireless sensor network. The power consumption was decreased because wireless sensor network does not use the Ad-hoc routing protocol but routing protocol that is based on tree structure. Our proposed system includes a wireless user's end device, monitoring console, SIP server and database server. This real-time bio-signals monitoring system makes possible to implement the U-health care services and improving efficiency of medical treatment services.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.6
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• pp.483-500
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• 2007

Emerging sensor-based structural health monitoring (SHM) technology can play an important role in inspecting and securing the safety of aging civil infrastructure, a worldwide problem. However, implementation of SHM in civil infrastructure faces a significant challenge due to the lack of suitable sensors and reliable methods for interpreting sensor data. This paper reviews recent efforts and advances made in addressing this challenge, with example sensor hardware and software developed in the author's research center. It is proposed to integrate real-time continuous monitoring using on structure sensors for global structural integrity evaluation with targeted NDE inspection for local damage assessment.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.523-523
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• 2012

As the wafer geometric requirements continuously complicated and minutes in tens of nanometers, the expectation of real-time add-on sensors for in-situ plasma process monitoring is rapidly increasing. Various industry applications, utilizing plasma impedance monitor (PIM) and optical emission spectroscopy (OES), on etch end point detection, etch chemistry investigation, health monitoring, fault detection and classification, and advanced process control are good examples. However, process monitoring in semiconductor manufacturing industry requires non-invasiveness. The hypothesis behind the optical monitoring of plasma induced ion current is for the monitoring of plasma induced charging damage in non-invasive optical way. In plasma dielectric via etching, the bombardment of reactive ions on exposed conductor patterns may induce electrical current. Induced electrical charge can further flow down to device level, and accumulated charges in the consecutive plasma processes during back-end metallization can create plasma induced charging damage to shift the threshold voltage of device. As a preliminary research for the hypothesis, we performed two phases experiment to measure the plasma induced current in etch environmental condition. We fabricated electrical test circuits to convert induced current to flickering frequency of LED output, and the flickering frequency was measured by high speed optical plasma monitoring system (OPMS) in 10 kHz. Current-frequency calibration was done in offline by applying stepwise current increase while LED flickering was measured. Once the performance of the test circuits was evaluated, a metal pad for collecting ion bombardment during plasma etch condition was placed inside etch chamber, and the LED output frequency was measured in real-time. It was successful to acquire high speed optical emission data acquisition in 10 kHz. Offline measurement with the test circuitry was satisfactory, and we are continuously investigating the potential of real-time in-situ plasma induce current measurement via OPMS.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.27-31
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• 2023

Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.

• KIISE Transactions on Computing Practices
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• v.21 no.3
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• pp.183-191
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• 2015

Recent developments in IT have made real-time ECG monitoring possible, and this represents a promising application for the emerging HL7 standard for the exchange of clinical information. However, applying the HL7 standard directly to real-time ECG monitoring causes problems, because the partial duplication of data within an HL7 message increases the amount of data to be transmitted, and the time taken to process it. We reduce these overheads by Feature Scaling, by standardizing the range of independent variables or features of data, while nevertheless generating HL7-compliant messages. We also use a De-Duplication algorithm to eliminate the partial repetition of the OBX field in an HL7 ORU message. Our strategy shortens the time required to create messages by 51%, and reduces the size of messages by 1/8, compared to naive HL7 coding.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.9-15
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• 2011

U-healthcare system has an aim to provide reliable and fast medical services for patient regardless of time and space by transmitting to doctors a large quantity of vital signs collected from sensor networks. Existing u-healthcare systems can merely monitoring patients' health status. In this paper, we describe the implementation and validation of a prototype of a u-health monitoring system based on a wireless sensor network. This system is easy to derive physiologically meaningful results by analyzing rapidly vital signs. The monitoring system sends only the abnormal data of examinee to the service provider. This technique can reduces the wireless data packet overload between a monitoring part and service provider. The real-time bio-signal monitoring system makes possible to implement u-health services and improving efficiency of medical services.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.183-191
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• 2014

The software running on avionic system is required to be highly reliable and productive. The air transport industry has developed ARINC Specification 653(ARINC653) as a standardized software requirement of avionics computers. The document specifies the interface boundary between avionics application software and the core executive software. Dependability in ARINC 653 is provided by spatial and temporal partitioning whilst fault-tolerance is provided by health monitoring mechanism. Legacy real-time operating systems are used to support ARINC653 health monitor on integrated modular avionics(IMA). However, legacy real-time operating systems are costly and difficult to modify the kernel. In this paper, we suggest a Linux-based ARINC653 health monitor. Functionalities to support ARINC653 health monitor are implemented as a Linux kernel module and its performance is evaluated.

• Journal of Environmental Science International
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• v.24 no.12
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• pp.1559-1567
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• 2015

This study investigated the association between $PM_{2.5}$ concentrations obtained with portable real-time monitors and those obtained with gravimetric methods in national urban air-quality monitoring sites in Seoul, South Korea. We used the SidePak AM510 Personal Aerosol Monitor (TSI Inc., 500 Cardigan Road Shoreview, MN) and DustTrak DRX 8533 (TSI Inc., 500 Cardigan Road Shoreview, MN) as portable real-time monitors for measuring $PM_{2.5}$ concentrations and compared these values with those measured with the PMS-103 or SEQ 47/50 models operated by Federal Reference Method (FRM) or the European Committee for Standardization(ECS), respectively, in national urban air-quality monitoring sites in Seoul. Measurements were conducted every other day in the winter and spring seasons of 2014. The estimated daily mean concentrations of $PM_{2.5}$ ranged between 13.4 and $161.9{\mu}g/m^3$ using AM 510 and between 22.0 and $156.0{\mu}g/m^3$ using DustTrak. The Spearman correlation coefficient for $PM_{2.5}$ concentrations between AM 510 and gravimetric results was 0.99, and the correlation between DustTrak and gravimetric results was 0.87. The correction factor suggested was 0.42 and 0.29 for AM 510 and DustTrak, respectively. We found that $PM_{2.5}$ concentrations measured with real-time monitors could overestimate true $PM_{2.5}$ concentrations and therefore the application of a correction factor (0.43) is strongly suggested for quantification when Real-time monitors were operated of $PM_{2.5}$ levels at urban atmospheric environment of South Korea.