• Tribology and Lubricants
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• v.36 no.6
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• pp.297-306
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• 2020

This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.199-206
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• 1991

As the development of modern technology, human works shift whose roll from physical conditions to the system monitoring tasks. In this paper, safety-presentation configuration is discussed instead of well-known fault-warning configuration. Safety-presentation configuration is verified as superior to the fault-warning configuration in hazard prevention. The estimation of system states involves the decision making environments which lack of required in formations and most of all the informations are not precise too. And the limitation of human information processing show doubtful results. So the estimation of system states is regardes as fuzzy number, and its operation produces the parameter that explain the discriminability(d), decision criterion ($\beta$) of system operator's behaviors. These two values served as performance indices. Especially the $\beta$ is a good milestone of the operator's altitude degree of caution.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.45-46
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• 2018

This paper focuses on human activities monitoring problem using onboard smartphone sensors as data generator. Monitoring such activities can be very important to detect anomalies and prevent disease from patients. Machine learning (ML) algorithms appear to be ideal approaches to use for processing data from smartphone to get sense of how to classify human activities. ML algorithms depend on quality, the quantity and even more important, the properties or features, that can be learnt from data. This paper proposes a mobile virtual reality visualization system that helps to view data representation in a very immersive way so that its quality and discriminative characteristics may be evaluated and improved. The proposed system comes as well with a handy data collecting application that can be accessed directly by the VR visualization part.

• Analytical Science and Technology
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• v.36 no.1
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• pp.12-21
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• 2023

Protein glycation is vital to aging and disease. However, glycated proteins are low-abundant in plasma, rendering them difficult to identify using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Many studies have analyzed glycated peptides with high reproducibility. Here, glycated peptides in human serum were analyzed by LC-MS/MS using data-dependent acquisition (DDA) and parallel reaction monitoring (PRM). Boronic acid (BA) enrichment of in vitro glycated human serum peptides was performed. BA enrichment identified the most glycated peptides, and the glycated peptides of the more diversified proteins, excluding albumin, were analyzed. In PRM, glycated albumin PSMs were the most common, and this method exhibited the best reproducibility. The results of this study could help compare methods for identifying glycation-related biomarkers.

• Journal of the Korean Society of Costume
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• v.65 no.1
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• pp.118-135
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• 2015

In recent years, smart clothing had been developed in order to better detect and monitor physical movement of the patient, so that such activities such as location identification and biometric recognition could be done. However, most of the sensing devices of smart clothing were limited to smart sensing sports clothing and the designs did not consider the physical characteristics and the behavior of the wearer. Therefore, this study aimed to create an open protection system by developing a wearable sensing device for health monitoring and location information. For this purpose, this study developed eleven types of wearable sensing design that could be commercially sold and worn by people who needed their biological information to be constantly monitored. The study conducted four tests in order to develop three types of sensing devices for various sensing wears. The purpose of this study was to expand the user rang of smart sensing wears, and provide a foundation for the development of distinctive wearable sensing devices reflecting the user. Furthermore, contribute to the design for the person subject to protection.

• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.165-168
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• 2002

This paper has been studied about the real time monitoring system development using TCP/IP ethernet and RS-422 serial communication link in general communication methods that rocket fire control agents could be monitoring about real time Rocket fire event procedures and be managing total rocket fire courses. Also, this paper has been studied the HMI(Human Machine Interface) control program and algorithm that guarantee confidential control for the Fire Display System.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.50-59
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• 2006

This paper proposes an automatic video monitoring system and its application to emergency detection by analyzing human behavior using neural network. The object area is identified by subtracting the statistically constructed background image from the input image. The identified object area then is transformed to the feature vector. Neural network has been adapted for analyzing the human behavior using the feature vector, and is designed to classify the behavior in rather simple numerical calculation. The system proposed in this paper is able to classify the three human behavior: stand, faint, and squat. Experiment results shows that the proposed algorithm is very efficient and useful in detecting the emergency situation.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.194-200
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• 2020

Human detection is an important aspect in many video-based sensing and monitoring systems. Studies have been actively conducted for the automatic detection of humans in camera images, and various methods have been proposed. However, there are still problems in terms of performance and computational cost. In this paper, we describe a method for efficient human detection in the field of view of a camera, which may be static or moving, through multiple processing steps. A detection line is designated at the position where a human appears first in a sensing area, and only the one-dimensional gray pixel values of the line are monitored. If any noticeable change occurs in the detection line, corner detection and optical flow computation are performed in the vicinity of the detection line to confirm the change. When significant changes are observed in the corner numbers and optical flow vectors, the final determination of human presence in the monitoring area is performed using the Histograms of Oriented Gradients method and a Support Vector Machine. The proposed method requires processing only specific small areas of two consecutive gray images. Furthermore, this method enables operation not only in a static condition with a fixed camera, but also in a dynamic condition such as an operation using a camera attached to a moving vehicle.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.313-316
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• 2015

Construction is one of the most dangerous job sectors, which reports tens of thousands of time-loss injuries and deaths every year. These disasters incur delays and additional costs to the projects. The safety management needs to be on the top primary tasks throughout the construction to avoid fatal accidents and to foster safe working environments. One of the safety regulations that are frequently violated is the wearing of personal protection equipment (PPE). In order to facilitate monitoring of the compliance of the PPE wearing regulations, this paper proposes a vision based method that automatically identifies whether workers wear hard hats and safety vests. The method involves three modules - human body detection, identification of safety vest wearing, and hard hat detection. First, human bodies are detected in the video frames captured by real-time on-site construction cameras. The detected human bodies are classified into with/without wearing safety vests based on the color features of their upper parts. Finally, hard hats are detected on the nearby regions of the detected human bodies and the locations of the detected hard hats and human bodies are correlated to reveal their corresponding matches. In this way, the proposed method provides any appearance of the workers without wearing hard hats or safety vests. The method has been tested on onsite videos and the results signify its potential to facilitate site safety monitoring.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.717-722
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• 2013

The wastewater reclamation and reusing system has been rising as an alternative of water resource exhaustion that the whole world is experiencing. In order to be able to bring about improvement of the existing wastewater reclamation and reusing system, this research has developed of Conversion-Human Machine Interaction (C-HMI) based real-time control and monitoring system such as a sensor module and gate module, web monitoring system. This system was communication almost-error-free in various environment and situation. As a result, we have achieved our goal that has to doing work correctly as a sensor and gateway module that communication error is less than 0.2% throughout the embodied system and add that it can be easily controled and configured as an interface equipment to a complex sensor of water quality. According to this, the construction of a database capable of analyzing and assessing collection, storage and various elements of reliable water quality and flow rate data can be possible.