• Proceedings of the Korean Geotechical Society Conference
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• 2000.11b
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• pp.60-76
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• 2000

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.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5588-5613
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• 2018

Virtualization technology has been widely applied in the area of computer security research that provides a new method for system protection. It has been a hotspot in system security research at present. Virtualization technology brings new risk as well as progress to computer operating system (OS). A multi-level perception security model using virtualization is proposed to deal with the problems of over-simplification of risk models, unreliable assumption of secure virtual machine monitor (VMM) and insufficient integration with virtualization technology in security design. Adopting the enhanced isolation mechanism of address space, the security perception units can be protected from risk environment. Based on parallel perceiving by the secure domain possessing with the same privilege level as VMM, a mechanism is established to ensure the security of VMM. In addition, a special pathway is set up to strengthen the ability of information interaction in the light of making reverse use of the method of covert channel. The evaluation results show that the proposed model is able to obtain the valuable risk information of system while ensuring the integrity of security perception units, and it can effectively identify the abnormal state of target system without significantly increasing the extra overhead.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1280-1290
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• 2016

This paper presents an advanced estimation method for obtaining the probability density functions of a damage parameter for valve leakage detection in a reciprocating pump. The estimation method is based on a comparison of model data which are simulated by using a mathematical model, and experimental data which are measured on the inside and outside of the reciprocating pump in operation. The mathematical model, which is simplified and extended on the basis of previous models, describes not only the normal state of the pump, but also its abnormal state caused by valve leakage. The pressure in the cylinder is expressed as a function of the crankshaft angle, and an additional volume flow rate due to the valve leakage is quantified by a damage parameter in the mathematical model. The change in the cylinder pressure profiles due to the suction valve leakage is noticeable in the compression and expansion modes of the pump. The damage parameter value over 300 cycles is calculated in two ways, considering advance or delay in the opening and closing angles of the discharge valves. The probability density functions of the damage parameter are compared for diagnosis and prognosis on the basis of the probabilistic features of valve leakage.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.559-562
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• 2003

In this paper, we introduce a new method detecting thyristor faults of the power converter module in Control Rod Control System. When we control the currents in each coil of Control Rod Drive Mechanism by using the current control method, the current value can follow the current reference despite the faults like the missing phase or the diode acting. Comparing the fault current values with the normal current values, the bad transient characteristics of the abnormal current can make the operations of control rods incorrect. In this case, the information from the current trends cannot be enough to detect the fault occurrence in thyristors. Instead of the coil currents, the state of thyristors can be watched by measuring the coil voltages. In the existing system of Westinghouse type, the ripple detector takes charge of this task. But this detector has some shortcomings in the point of time for fault detection, we come to devise a new fault detection method solving the problems which belong to the ripple detector.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.84-93
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• 2021

Airline schedule is the most basic data for flight operations and has significant importance to an airline's management. It is crucial to know the airline's current schedule status in order to effectively manage the company and to be prepared for abnormal situations. In this study, machine learning techniques were applied to actual schedule data to examine the possibility of whether the airline's fleet state could be artificially learned without prior information. Given that the schedule is in categorical form, One Hot Encoding was applied and t-SNE was used to reduce the dimension of the data and visualize them to gain insights into the airline's overall fleet status. Interesting results were discovered from the experiments where the initial findings are expected to contribute to the fields of airline schedule health monitoring, anomaly detection, and disruption management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• Fire Science and Engineering
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• v.23 no.2
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• pp.1-5
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• 2009

We studies wish to investigated establishment form of cabinet board, and confirm possibility of electrical disaster prevention through reappearance experiment of odor detection system. Established breaker consists of MCCB, RCD order in cabinet board for house, but industry is used together with. When imposed shock using shaker to terminal block that contact becomes in appropriate, flame was made sure. According to result that experiment attaching odor capsule in terminal block, capsule commissioned exactly by occurred heat. According to establishment position of sensor, difference of inspection time was about 10 seconds. Estimate odor inspection system by thing which electrical device accident prevention is available. When there is abnormal generated heat in connection of electric wire, accident prevention estimates that is possible by giving an alarm state of overheat to administrator.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1674-1688
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• 2023

The remarkable advancement of quantum steganography offers enhanced security for quantum communications. However, there is a significant concern regarding the potential misuse of this technology. Moreover, the current research on identifying malicious quantum steganography is insufficient. To address this gap in steganalysis research, this paper proposes a specialized quantum steganalysis algorithm. This algorithm utilizes quantum machine learning techniques to detect steganography in general quantum secure communication schemes that are based on pure states. The algorithm presented in this paper consists of two main steps: data preprocessing and automatic discrimination. The data preprocessing step involves extracting and amplifying abnormal signals, followed by the automatic detection of suspicious quantum carriers through training on steganographic and non-steganographic data. The numerical results demonstrate that a larger disparity between the probability distributions of steganographic and non-steganographic data leads to a higher steganographic detection indicator, making the presence of steganography easier to detect. By selecting an appropriate threshold value, the steganography detection rate can exceed 90%.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.51-57
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• 2016

Many kinds of telemetry should be monitored to check the state of spacecraft and it leads the time consumption. However, it is very important to define the status of satellite in short time because the contact number and time of low earth orbit satellite is limited. Also, on-board fault management should be prepared for non-contact operation because of the sever space environment. In this paper, on-board and ground autonomous operation method for the safety enhancement is described. Immediate fault detection and response is possible in ground by explicit anomaly detection through satellite event and error information. Also, satellite operation assistant system is proposed for ground autonomy that collect event sequence in accordance with related telemetry and recommend or execute an appropriate action for abnormal state. Critical parameter monitoring method with checking rate, mode and threshold is developed for on-board autonomous fault management. If the value exceeds the limit, pre-defined command sequence is executed.