• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.91-105
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• 2002

The attackers on Internet-connected systems we are seeing today are more serious and technically complex than those in the past. So it is beyond the scope of amy one system to deal with the intrusions. That the multiple IDSes (Intrusion Detection System) coordinate by sharing attacker's information for the effective detection of the intrusion is the effective method for improving the intrusion detection performance. The system which uses BBA (BlackBoard Architecture) for the information sharing can be easily expanded by adding new agents and increasing the number of BB (BlackBoard) levels. Moreover the subdivided levels of blackboard enhance the sensitivity of the intrusion detection. For the simulation, security models are constructed based on the DEVS (Discrete EVent system Specification) formalism. The intrusion detection agent uses the ES (Expert System). The intrusion detection system detects the intrusions using the blackboard and the firewall responses these detection information.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.373-376
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• 2014

최근 모바일 기기 및 무선기기의 발달로 인하여 센서 네트워크가 다양한 분야에서 응용되고 있다. 따라서 센서에서 실시간으로 발생하는 스트리밍 데이터에서 이벤트를 감지하고 분석하는 것은 중요한 연구 분야로 부각되고 있다. 단순 이벤트의 발생 조건을 빠르게 판별하기 위해 비트맵 인덱스 기반 복합 이벤트 검출 기법 등 여러 가지 방법들이 사용되고 있지만, 아직까지 이기종 센서에서 발생하는 각기 다른 형태의 데이터를 융합하여 이벤트를 검출하는 복합 이벤트 처리에 대한 연구는 미비한 실정이다. 본 논문에서는 각기 다른 형태를 가지는 스트리밍 데이터에 멤버쉽 함수를 적용하여 퍼지화 함으로서 이기종 센서에서 발생하는 데이터를 융합 처리가능하며, Quine-Mccluskey 감축기법을 통하여 규칙의 신뢰도 및 속도가 향상된 의사결정을 하는 고속 이벤트 탐지기법을 제안한다.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.233-240
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• 2024

In this study, we introduce a system for real-time monitoring of field conditions within an industrial complex using a 5G network UAV (: Unmanned Aerial Vehicle). When a monitoring event occurs in a sensor mounted on a UAV (detection of fire, harmful gas, or industrial disaster type human accident), key information from the sensor is transmitted to the UAS (: Unmanned Aerial System) application server. As a result of this information transmission and processing, managers or operators of the Industrial Complex Corporation were able to secure legal basis data for fatal accidents, fires, and detection of harmful gases at sites within the Industrial Complex Corporation through trigger processing for each accident risk situation.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.330-339
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• 2015

Power quality (PQ) problems are becoming a big issue, since delicate complex electronic devices are widely used. We present a new denoising technique using discrete wavelet transform (DWT), where a modified correlation thresholding is used in order to reliably detect the PQ disturbances. We consider various PQ disturbances on the basis of IEEE-1159 standard over noisy environments, including voltage swell, voltage sag, transient, harmonics, interrupt, and their combinations. These event signals are decomposed using DWT for the detection of disturbances. We then evaluate the PQ disturbance detection ratio of the proposed denoising scheme over Gaussian noise channels. Simulation results also show that the proposed scheme has an improved signal-to-noise ratio (SNR) over existing scheme.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.41-58
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• 2023

As naval warfare changes to composite warfare that includes simultaneous engagements against surface, underwater, and air enemies, performance and tactical analysis are required to respond to naval warfare. In particular, for practical analysis of composite warfare, it is necessary to study engagement simulations that can appropriately utilize the limited performance resources of the detection system. This paper proposes a DEVS (Discrete Event Systems Specifications)-based simulation model for composite warfare analysis. The proposed model contains generalized models of combat platforms and armed objects to simulate various complex warfare situations. In addition, we propose a detection performance allocation algorithm that can be applied to a detection system model, considering the characteristics of composite warfare in which missions must be performed using limited detection resources. We experimented with the effectiveness of composite warfare according to the strength of the detection system's resource allocation, the enemy force's size, and the friendly force's departure location. The simulation results showed the effect of the resource allocation function on engagement time and success. Our model will be used as an engineering basis for analyzing the tactics of warships in various complex warfare situations in the future.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.05
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• pp.288-292
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• 1996

This paper describes far the detection of heart event that is, QRS complex and P wave which are result from heart activity. The proposed QRS detection method by using the spatial velocity was identified as having the 99.6% detection accuracy as well as fast processing time. Atrial flutter, coupled P wave, and noncoupled P wave as well as atrial fibrillation could be detected correctly by three different algorithms according to their origination farm. About 99.6% correction accuracy coupled P wave could be obtained and we could be found that most detection errors are caused by establishing wrong search interval.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.637-640
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• 2023

This paper presents multimodal image fusion with human pose for detecting abnormal human behaviors in low illumination conditions. Detecting human behaviors in low illumination conditions is challenging due to its limited visibility of the objects of interest in the scene. Multimodal image fusion simultaneously combines visual information in the visible spectrum and thermal radiation information in the long-wave infrared spectrum. We propose an abnormal event detection scheme based on the multimodal fused image and the human poses using the keypoints to characterize the action of the human body. Our method assumes that human behaviors are well correlated to body keypoints such as shoulders, elbows, wrists, hips. In detail, we extracted the human keypoint coordinates from human targets in multimodal fused videos. The coordinate values are used as inputs to train a multilayer perceptron network to classify human behaviors as normal or abnormal. Our experiment demonstrates a significant result on multimodal imaging dataset. The proposed model can capture the complex distribution pattern for both normal and abnormal behaviors.

• Journal of Sensor Science and Technology
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• v.31 no.1
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• pp.16-23
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• 2022

Cardiac disease is the most common cause of death worldwide. Therefore, detection and classification of electrocardiogram (ECG) signals are crucial to extend life expectancy. In this study, we aimed to implement an artificial intelligence signal recognition system in field programmable gate array (FPGA), which can recognize patterns of bio-signals such as ECG in edge devices that require batteries. Despite the increment in classification accuracy, deep learning models require exorbitant computational resources and power, which makes the mapping of deep neural networks slow and implementation on wearable devices challenging. To overcome these limitations, spiking neural networks (SNNs) have been applied. SNNs are biologically inspired, event-driven neural networks that compute and transfer information using discrete spikes, which require fewer operations and less complex hardware resources. Thus, they are more energy-efficient compared to other artificial neural networks algorithms.

• Geophysics and Geophysical Exploration
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• v.16 no.4
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• pp.234-239
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• 2013

The $M_W$ 9.0 thrust-fault earthquake has occurred in the Pacific coast of Tohoku, Japan, on March 11, 2011. We present the detection of the great earthquake and analyze T-waves associated with the main event and two other big aftershocks ($M_W$ > 7) recorded in a hydroacoustic array (H11N) in the Pacific Ocean by performing array and spectral analysis to examine characteristics of T-waves generated from the big events. The complex rupture process of the main event directly influences on the shape of the T-waves, and the peak locates on where T-waves excited from fast rupturing process arrive. We compare the two aftershocks with different fault type and show that the fault type and the source depth change shape and spectral contents of T-waves.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.6
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• pp.95-100
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• 2009

Nowadays there are many studies and there's huge development about USN/RFID which have great developmental potential to many kinds of applications. More and more real time application apply USN/RFID technology to identify data collect and locate objects. Wide deployment of USN/RFID will generate an unprecedented volume of primitive data in a short time. Duplication and redundancy of primitive data will affect real time performance of application. Thus, security applications must filter primitive data and correlate them for complex pattern detection and transform them to events that provide meaningful, actionable information to end application. In this paper, we design a ECA Rule system for security monitoring of exhibition. This system will process USN/RFID primitive data and event and perform data transformation. It's had applied each now in exhibition hall through this study and efficient data transmission and management forecast that is possible.