• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1129-1136
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• 2021

A pan-tilt-zoom (PTZ) camera-based monitoring system for efficient monitoring in the engine room of a vessel was designed. A number of places exist where traditional analog instruments are still used in vessel engine rooms, and blind spots closely related to safety exist, for which flooding or fire is a concern. A camera-based monitoring system that guarantees a wide range at a relatively fast cycle for these monitoring points can be an effective alternative to enhance the safety of a vessel. Therefore, a multiview monitoring system is proposed in which the functions of the existing PTZ camera are further strengthened using a software. The monitoring system comprises four modules: camera control, location registration, traversal control, and multiview image reconstruction. The effectiveness of the method was evaluated through a series of experiments in an engine room environment.

• The KIPS Transactions:PartD
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• v.13D no.4 s.107
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• pp.613-618
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• 2006

As the embedded software spreads in various areas, many development tools have been made to minimize the developing time. But these tools cannot be applicable to all the environment because they have been created for the specific platform. As such, this paper proposes an Embedded Monitoring System, which supports the various communication environment and removes the limitation of adaptability to the various platforms. Using the Code Inline technique, this system can perform the monitoring process. However, we should consider the optimization for the monitoring process and monitoring sensors because the technique has the monitoring sensor overhead. As such, this paper proposes an approach for initializing the monitoring process and a bit-masking technique for optimizing the monitoring sensor. The Embedded Monitoring System will be applicable to all the areas using embedded systems.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.196-201
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• 2005

Diseases in the gastro-intestinal tract are on an increasing trend. In order to diagnose a patient, various signals of the digestive organ, such as temperature, pH, and pressure, can offer the helpful information. Among the above mentioned signals, we choose the pressure variation as a monitoring signal. The variation of a pressure signal of the gastro-intestinal tract can offer the information of a digestive trouble or some clues of the diseases. In this paper, a pressure monitoring system for the digestive organs of a living pig is presented. This is why a pig's gastro-intestinal tract is very similar as human's. This system concept is to transmit the measured biomedical signals from a transmitter in a living pig to a wireless receiver that is positioned out of body. The integrated solution includes the swallow type pressure capsule and the receiving set consisting of a receiver, decoder circuit. The merit of the proposed system is that the monitoring system can supply the precise and a durable characteristic to measure and to transmit a signal in the gastro-intestinal tract. We achieved the pressure tracings in digestive organs and verified the validity of system after several in-vivo tests using the pressure monitoring system. Through various experiments, we found each organ has its own characterized pressure fluctuation.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.624-632
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• 2015

A self-diagnostic monitoring system is a system that has the ability to measure various physical quantities such as temperature, pressure, or acceleration from sensors scattered over a mechanical system such as a power plant, in order to monitor its various states, and to make a decision about its health status. We have developed a self-diagnostic monitoring system for an air-operated valve system to be used in a nuclear power plant. In this study, we have tried to improve the self-diagnostic monitoring system to increase its reliability. We have implemented three different machine learning algorithms, i.e., logistic regression, an artificial neural network, and a support vector machine. After each algorithm performs the decision process independently, the decision-making module collects these individual decisions and makes a final decision using a majority vote scheme. With this, we performed some simulations and presented some of its results. The contribution of this study is that, by employing more robust and stable algorithms, each of the algorithms performs the recognition task more accurately. Moreover, by integrating these results and employing the majority vote scheme, we can make a definite decision, which makes the self-diagnostic monitoring system more reliable.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2256-2262
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• 2010

The requirements for automated handing of business process and its monitoring usually have a proprietary form for each enterprise. Unlike the conventional database transaction, business process takes long time for its completion and incorporates very complex handling logics along with business situations. Since those handling logics are frequently changing in accordance with the business policies or environment, enterprises want to integrally capture the whole business semantics while monitoring those process instances. In this paper, we adopted GMA(Grid Monitoring Architecture) for the integrated monitoring of business processes. The GMA(Grid Monitoring Architecture) is a very scalable architecture to effectively monitor and manage monitoring information under the heterogeneous environment. By introducing complex event handling features into GMA to support various processing logics, we could implement a system that enables automated execution and high-level monitoring of business processes.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.409-416
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• 2021

We are invented the movement composition technique that is to check the food adjacent-package status of the wireless-management movement monitoring level (WMMML) on the movement monitoring communication system. The movement monitoring level condition by the movement monitoring communication system is formatted with the adjacent-package system. As to inspection a wireless RFID of the wireless RFID, we are found of the movement value with wireless RFID by the adjacent upper take form. The concept of movement monitoring level is formatted the reference of wireless-management level for composition signal by the movement package communication system. Further symbolizing a food composition of the WMMML of the medium-minimum in terms of the adjacent-package communication system, and the movement wireless RFID package that was the movement value of the far composition of the Mo-MMCS-FA-_φMED-MIN with 5.80±1.20 units, that was the movement value of the convenient composition of the Mo-MMCS-CO-_φMED-MIN with 4.06±(-0.04) units, that was the movement value of the flank composition of the Mo-MMCS-MO-_φMED-MIN with 0.91±0.07 units, that was the movement value of the vicinage composition of the Mo-MMCS-VI-_φMED-MIN with 0.18±(-0.03) units. The adjacent package will be to look into at the food ability of the adjacent-package communication system with wireless RFID by the movement monitoring level on the WMMML that is supply the wireless communication by the movement monitoring level system. We will be possible to make effort of a communication system by the management signal and to put to use of the delivery data of RFID level by the delivery system.

• Journal of information and communication convergence engineering
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• v.13 no.3
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• pp.167-171
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• 2015

A radio over fiber (RoF) system is a kind of analog optical transmission system and considered as a strong candidate for the next-generation fronthaul link in the future mobile network. In RoF systems, nonlinearity compensation is essential to increase the link capacity. In this paper, we propose a nonlinearity detection and compensation scheme using a monitoring channel in RoF systems. A monitoring channel is added at the transmitter site and used for transmitting a reference signal in an RoF transmission. The nonlinearity in the RoF transmission is detected by comparing the received monitoring signal and the original reference signal at the receiver site. Finally, the nonlinearity is compensated at the receiver by giving the reverse function of the detected nonlinearity. Our results show that the proposed scheme can almost remove the error vector magnitude degradation induced by the nonlinearity in the RoF system.

• Smart Structures and Systems
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• v.5 no.4
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• pp.369-379
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• 2009

The sudden collapse of Interstate 35 Bridge in Minneapolis gave a wake-up call to US municipalities to re-evaluate aging bridges. In this situation, structural health monitoring (SHM) technology can provide the essential help needed for monitoring and maintaining the nation's infrastructure. Monitoring long span bridges such as cable-stayed bridges effectively requires the use of a large number of sensors. In this article, we introduce a probabilistic approach to identify optimal locations of sensors to enhance damage detection. Probability distribution functions are established using an artificial neural network trained using a priori knowledge of damage locations. The optimal number of sensors is identified using multi-objective optimization that simultaneously considers information entropy and sensor cost-objective functions. Luling Bridge, a cable-stayed bridge over the Mississippi River, is selected as a case study to demonstrate the efficiency of the proposed approach.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• International Journal of Safety
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• v.8 no.1
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• pp.10-13
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• 2009

In this study, a framework for web-based information system in VDN environment for safety and health monitoring in subway stations is suggested. Since physical variables that describing safety and health need to be closely monitored in multiple locations in subway stations, concept of distributed monitoring network using wireless media needs to be implemented. Connecting remote wireless sensor network and device (LonWorks) networks to the IP network based on the concept of VDN can provide a powerful, integrated and distributed monitoring performance, making a web-based information system possible.