• International Journal of Control, Automation, and Systems
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• v.1 no.3
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• pp.368-375
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• 2003

Data fusion approach is investigated to avoid suction in the left ventricular assist system (LVAS) using a nonpulsatile pump. LVAS requires careful control of pump speed to support the heart while preventing suction in the left ventricle and providing proper cardiac output at adequate perfusion pressure to the body. Since the implanted sensors are usually unreliable for long-term use, a sensorless approach is adopted to detect suction. The pump model is developed to provide the load coefficient as a necessary signal to the data fusion system without the implanted sensors. The load coefficient of the pump mimics the pulsatility property of the actual pump flow and provides more comparable information than the pump flow after suction occurs. Four signals are generated from the load coefficient as inputs to the data fusion system for suction detection and a neural fuzzy method is implemented to construct the data fusion system. The data fusion approach has a good ability to classify suction status and it can also be used to design a controller for LVAS.

• Journal of the Semiconductor & Display Technology
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• v.14 no.1
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• pp.45-49
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• 2015

Process gases with vapor or liquid phase as well as gas phase may experience alteration in itself or be contaminated in the fluid pipe to the process chamber. And thus it result in as particles or defects on the substrates in semiconductor, LCD, LED manufacturing. Purifiers and filters are used for control of contamination. However, none of detection device is available in the delivery line. In this paper, we propose simple device with lighting and sensing in order to predict contamination of the fluid or the tube wall. For some general purpose gases, it showed constant voltage output regardless of the flow rates. But, the smoke and the moisture in the air lowered the figure due to its concentration. Numerical values for several solid and liquid media were obtained. And, the operating temperature tendency was investigated.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.348-357
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• 2018

The topic of anomaly detection is one of the emerging research themes in computer vision, computer interaction, video analysis and monitoring. Observers focus attention on behaviors that vary in the magnitude or direction of the motion and behave differently in rules of motion with other objects. In this paper, we use this information and propose a system that detects abnormal behavior by using simple features extracted by optical flow. Our system can be applied in real life. Experimental results show high performance in detecting abnormal behavior in various videos.

• Journal of Communications and Networks
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• v.14 no.3
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• pp.310-318
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• 2012

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.

• Transactions of the Korean Society of Automotive Engineers
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• v.8 no.2
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• pp.41-49
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• 2000

To understand the signal fluctuation of a wide-range oxygen sensor installed at the exhaust confluence point, when a misfiring is triggered in a cylinder, the steady state and the transient response characteristics of the sensor to the flow of the misfired gas were investigated quantitatively. It was recognized that the steady state output voltage of the sensor increased higher when it contacted the misfired gas even though the fueling condition was the same as the normal combustion case and this characteristic enabled the application of the wide-range oxygen sensor for the misfire detection. The transient response was compared at different engine speeds and it was found that the response speed increased with the engine speed. The signal fluctuation was also estimated quantitatively, using these steady state and transient response of the sensor, and the estimated signal showed satisfactory correlation with the measurements.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.258-264
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• 2014

In terms of chemical detection performance related with chemical material sampling, this investigation shows optimized values, resulted from minimizing loss from air turbulence and other reasons when pressure changes on the basis of sampling flow rate Based on simulations and pressure control of the outside conditions it became possible to obtain ion mobility detection optimum values, and to derive standard pressure conditions that is appropriate for DMS characteristic.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.25-34
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• 2020

As leakage in nuclear power plants could cause a variety of problems, it is very critical to monitor leakage from the safety point of view. Accordingly, a new type of leak detection system is currently being developed and flow characteristics of the sampling and transportation system are investigated by using numerical analysis as a part of the development process in this study. The results showed that the steam mass fraction varied according to the effect of the gap between the insulation and piping component, transportation velocity, and material properties of porous media during the sampling and transportation process. The results of this study should be useful for understanding flow characteristics of the sampling and transportation system and its design and application.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.205-211
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• 2024

The increasing number of botnet attacks incorporating new evasion techniques making it infeasible to completely secure complex computer network system. The botnet infections are likely to be happen, the timely detection and response to these infections helps to stop attackers before any damage is done. The current practice in traditional IP networks require manual intervention to response to any detected malicious infection. This manual response process is more probable to delay and increase the risk of damage. To automate this manual process, this paper proposes to automatically select relevant countermeasures for detected botnet infection. The propose approach uses the concept of flow trace to detect botnet behavior patterns from current and historical network activity. The approach uses the multiclass machine learning based approach to detect and classify the botnet activity into IRC, HTTP, and P2P botnet. This classification helps to calculate the risk score of the detected botnet infection. The relevant countermeasures selected from available pool based on risk score of detected infection.

• Journal of KIISE:Information Networking
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• v.37 no.4
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• pp.263-271
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• 2010

SIP/RTP-based VoIP services are being popular. Recently, however, VoIP anomaly traffic such as delay, interference and termination of call establishment, and degradation of voice quality has been reported. An attacker could intercept a packet, and obtain user and header information so as to generate an anomaly traffic, because most Korean VoIP applications do not use standard security protocols. In this paper, we propose three VoIP anomaly traffic generation methods for CANCEL;BYE DoS and RTP flooding, and a detection method through flow-based traffic measurement. From our experiments, we showed that 97% of anomaly traffic could be detected in real commercial VoIP networks in Korea.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.2
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• pp.159-167
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• 2019

In this paper the potential of the principal component analysis(PCA) technique for the application of detecting leaks in water pipe networks was evaluated. For this purpose the PCA was conducted to evaluate the relevance of the calculated outliers of a PCA model utilizing the recorded pipe flows and the recorded pipe leak incidents of a case study water distribution system. The PCA technique was enhanced by applying the computational algorithms developed in this study which were designed to extract a partial set of flow data from the original 24 hour flow data so that the effective outlier detection rate was maximized. The relevance of the calculated outliers of a PCA model and the recorded pipe leak incidents was analyzed. The developed algorithm may be applied in determining further leak detection field work for water distribution blocks that have more than 70% of the effective outlier detection rate. However, the analysis suggested that further development on the algorithm is needed to enhance the applicability of the PCA in detecting leaks by considering series of leak reports happening in a relatively short period.