• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.2
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• pp.33-40
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• 2020

Various studies have been conducted on the structural health monitoring using optical fiber. Optical fibers can be used to measure multiple and distributed strain. Among the optical fiber sensors, FBG sensor has advantages of dynamic response measurement and high precision, but the number of measurement points is limited. Distributed fiber sensors, represented by distributed Brillouin sensors, usually have more than 1000 measurement points, but the low sampling rate makes dynamic measurements impossible. In this study, a hybrid nerve sensor system using only the advantages of the FBG sensor and the distributed Brillouin sensor has been proposed. Laboratory experiments were performed to verify the proposed system, and the accuracy and reproducibility were verified by comparing with commercial sensors. Applying the proposed system, dynamic response ambient measurements are used to evaluate the global state of the structure. When an abnormal condition is detected, the local condition of the structure is evaluated by static response measurement using the distributed measurement system. The proposed system can be used for efficient structural health monitoring.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.25-38
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• 2021

Recently the need for network surveillance to detect abnormal behavior within dynamic social networks has increased. We consider a dynamic version of the degree corrected stochastic block model (DCSBM) to simulate dynamic social networks and to monitor for a significant structural change in these networks. To apply a control charting procedure to network surveillance, in-control model parameters must be estimated from the Phase I data, that is from historical data. In network surveillance, however, there are many situations where sufficient relevant historical data are unavailable. In this paper we propose a self-starting Shewhart control charting procedure for detecting change in the dynamic networks. This procedure can be a very useful option when we have only a few initial samples for parameter estimation. Simulation results show that the proposed procedure has good in-control performance even when the number of initial samples is very small.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.271-284
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• 2008

Self-healing is an approach to evaluating constraints defined in target system and to applying an appropriate strategy when violating he constrains. Today, the computing environment is very complex, so researches that endow a system with the self-healing's ability that recognizes problem arising in a target system are being an important issues. However, most of the existing researches are that self-healing developers need much effort and time to analyze and model constraints. Thus, this paper proposes an automated approach to determine problem arising in external and internal system environment. The approach proposes: 1) Specifying the target system through the models created in design phase of target system. 2) Automatically creating constraints for external and internal system environment, by using the specified contents. 3) Deriving a dependency model of a component based on the created internal state rule. 4) Translating the constraints and dependency model into code evaluating behaviors of the target system, and determinating problem level. 5) Monitoring an internal and external status of system based on the level of problem determination, and applying self-healing strategy when detecting abnormal state caused in the target system. Through these, we can reduce the efforts of self-healing developers to analyze target system, and heal rapidly not only abnormal behavior of target system regarding external and internal problem, but also failure such as system break down into normal state. To evaluate the proposed approach, through video conference system, we verify an effectiveness of our approach by comparing proposed approach's self-healing activities with those of the existing approach.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.55 no.4
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• pp.294-302
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• 2019

As a series of fundamental researches on the development of an automatic identification monitoring system for fishing gear. Firstly, the study on the installation method of automated identification buoy for the coastal improvement net fishing net with many loss problems on the west coast was carried out. Secondly, the study was conducted find out how to install an automatic identification buoy for coastal gill net which has the highest loss rate among the fisheries. GPS for fishing was used six times in the coastal waters around Seogwipo city in Jeju Island to determine the developmental status and underwater behavior to conduct a field survey. Next, a questionnaire was administered in parallel on the type of loss and the quantity and location of fishing gear to be developed and the water transmitter. In the field experiment, the data collection was possible from a minimum of 13 hours, ten minutes to a maximum of 20 hours and ten minutes using GPS, identifying the development status and underwater behavior of the coastal gillnet fishing gear. The result of the survey showed that the loss of coastal net fishing gear was in the following order: net (27.3%), full fishing gear (24.2%), buoys, and anchors (18.2%). The causes were active algae (50.0%), fish catches (33.3%) and natural disasters (12.5%). To solve this problem, the installation method is to attach one and two electronic buoys to top of each end of the fishing gear, and one underwater transmitter at both ends of the float line connected to the anchor. By identifying and managing abnormal conditions such as damage or loss of fishing gear due to external factors such as potent algae and cutting of fishing gear, loss of fishing gear can be reduced. If the lost fishing gear is found, it will be efficiently collected.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.566-575
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• 2010

In recent, artificial immune system has become an important research direction in the anomaly detection of networks. The conventional artificial immune systems are usually based on the negative selection that is one of the computational models of self/nonself discrimination. A main problem with self and non-self discrimination is the determination of the frontier between self and non-self. It causes false positive and false negative which are wrong detections. Therefore, additional functions are needed in order to detect potential anomaly while identifying abnormal behavior from analogous symptoms. In this paper, we design novel network attack detection and response schemes based on artificial immune system, and evaluate the performance of the proposed schemes. We firstly generate detector set and design detection and response modules through adopting the interaction between dendritic cells and T-cells. With the sequence of buffer occupancy, a set of detectors is generated by negative selection. The detection module detects the network anomaly with a set of detectors and generates alarm signal to the response module. In order to reduce wrong detections, we also utilize the fuzzy number theory that infers the degree of threat. The degree of threat is calculated by monitoring the number of alarm signals and the intensity of alarm occurrence. The response module sends the control signal to attackers to limit the attack traffic.

• Korean Journal of Animal Reproduction
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• v.23 no.3
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• pp.247-256
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• 1999

The present study was performed to improve the reproductive disturbance as well as the elimination of microbiological contamination for animals bred under conventional conditions followed by in vitro fertilization and embryo transfer techniques including embryo and sperm freezing, using a mouse strain(M. m. molossinus-tt＠Kist) showing the abnormal behavior disorder derived from Korean wild mice (Mus musculus molossinus). Moreover, hematological and serum biochemical analyses were also carried out to obtain the basic data of this mouse strain The results are summarized as follows: 1. In comparison with hematological data, the numbers of RBC and platelet of this mouse strain were appeared as the higher value those that of the same aged inbred strains such as BALB/c, DBA/2, C57BL/6 and C3H /Hen. However, no differences were found in values of WBC, Hb and Ht. Moreover, total cholesterol of this strain showed a low value but triglyceride, total protein and albumin values were similar as in inbred strains. 2. The average numbers of superovulated oocytes treated with 2.5/2.5 IU and 5.0/5.0 IU of PMSG/hCG were 11.6 and 12.7, respectively. The fertilization rates of 2.5/2.5 IU PMSG /hCG treatment(87.9%) was higher than 5.0/5.0 IU treatment(52.0%) (p＜0.05) and the developmental rate of 2 cell stage embryos were 외 so appeared as higher value 99.0% and 90.6%, respectively. 3. The rates of in vitro fertilization treated with frozen sperm(24.8%) was significantly lower than of that fresh sperm(87.9%), (p＜0.05). 4. The five, six and ten heads of offspring were obtained from frozen-thawed 2 cell embryos by in vitro fertilized, 2 cell embryos from in vitro fertilized by frozen-thawed spermatozoa. and 2 cell embryos by in vitro fertilization, respectively. These offspring developed the expected disease about 2 weeks after birth, which was confirmed that the disease character of this mutant mouse strain was reliably reproduced. 5. MHV(Mouse hepatitis virus) and Staphylococcus aureus were successfully eliminated from conventional animals by in vitro fertilization-embryo transfer and the use of SPF recipient animals.