• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.639-642
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• 2013

In this paper, proposed NED(nuclear event detectors) for detection of a transient radiation. Nuclear event detector was blocked of power temporary for defence of critical damage at a electric device when a induced transient radiation. Conventional NED consist of BJT, resistors and capacitors. The NED supply voltage of 5V and MCM(Multi Chip Module) structures. The proposed NED were designed for low supply voltage using 0.18um CMOS process. The response time of proposed NED was 34.8ns. In addition, pulse radiation experiments using a electron beam accelerator, the output signal has occurred.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.83.3-84
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• 2017

On 2016 April $13^{th}$ the Jovian satellite Ganymede occulted a $7^{th}$ magnitude star. The predicted occultation track (occultation shadow) crossed the Northern Pacific Ocean, Japan, and South Korea. Hence, it was a very favorable event due to the star brightness in order to be accessible for small-aperture telescopes as well. While no other similar event is expected for the next 10 years, only two occultation events are reported in the literature in the past, from Earth in 1972 and from Voyager, in large disagreement in respect to the atmospheric detection. However, evidence of an exosphere around Ganymede was inferred through H Lyman alpha emission detected by Galileo UVS, through HST/GHRS detection of far-UV atomic O airglow emissions, signature of dissociated molecular oxygen. We organized a short-notice international coordinated occultation monitoring network with the aim to search for a signature of Ganymede's exosphere in the occultation light-curve by using facilities on Mauna Kea (NASA-IRTF) and Sobaeksan Optical Astronomy Observatory (SOAO) in South Korea.

• 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.

• Journal of Korea Water Resources Association
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• v.51 no.8
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• pp.703-711
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• 2018

Water distribution system (WDS) pipe bursts are caused from excessive pressure, pipe aging, and ground shift from temperature change and earthquake. Prompt detection of and response to the failure event help prevent large-scale service interruption and catastrophic sinkhole generation. To that end, this study proposes a improved Western Electric Company (WECO) method to improve the detection effectiveness and efficiency of the original WECO method. The original WECO method is an univariate Statistical Process Control (SPC) technique used for identifying any non-random patterns in system output data. The improved WECO method multiples a threshold modifier (w) to each threshold of WECO sub-rules in order to control the sensitivity of anomaly detection in a water distribution network of interest. The Austin network was used to demonstrated the proposed method in which normal random and abnormal pipe flow data were generated. The best w value was identified from a sensitivity analysis, and the impact of measurement frequency (dt = 5, 10, 15 min etc.) was also investigated. The proposed method was compared to the original WECO method with respect to detection probability, false alarm rate, and averaged detection time. Finally, this study provides a set of guidelines on the use of the WECO method for real-life WDS pipe burst detection.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1171-1180
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• 2010

In wireless sensor networks, reliable event detection is one of the most important research issues. For the reliable event detection, previous works usually assume the events are only individual objects such as tanks and soldiers. Recently, many researches focus on detection of continuous objects such as wild fire and bio-chemical material, but they merely aim at methods to reduce communication costs. Hence, we propose a reliable continuous object detection scheme. However, it might not be trivial. Unlike individual objects that could be referred as a point, a continuous object is shown in a dynamic two-dimensional diagram since it may cover a wide area and it could dynamically alter its own shape according to physical environments, e.g. geographical conditions, wind, and so on. Hence, the continuous object detection reliability can not be estimated by the indicator for individual objects. This paper newly defines the reliability indicator for continuous object detection and proposes an error recovery mechanism relying on the estimation result from the new indicator.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.1036-1042
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• 2011

This paper presents an algorithm that conducts automatic memory scrubbing operated by dedicated hardwares. The proposed algorithm is designed so that it can scrub entire memory in a given scrub period, while minimally affecting the execution of flight softwares. The scrub controller is constructed in a form of state machines, which have two execution modes - normal mode and burst mode. The deadline event generator and period tick generator are designed in a separate way to support the behavior of the scrub controller. The proposed controller is implemented in VHDL code to validate its applicability. A simple version of the controller is also applied to mass memory modules used in STSAT-3.

• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.127-130
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• 2000

Classification of Electroencephalogram(EEG) makes one of key roles in the field of clinical diagnosis, such as detection for epilepsy. Spectrum analysis using the fourier transform(FT) uses the same window to signals, so classification rate decreases for nonstationary signals such as EEG's. In this paper, wavelet power spectrum method using wavelet transform which is excellent in detection of transient components of time-varying signals is applied to the classification of three types of Event Related Potential(EP) and compared with the result by fourier transform. In the experiments, two types of photic stimulation, which are caused by eye opening/closing and artificial light, are used to collect the data to be classified. After choosing a specific range of scales, scale-averaged wavelet spectrums extracted from the wavelet power spectrum is used to find features by Back-Propagation(13P) algorithm. As a result, wavelet analysis shows superiority to fourier transform for nonstationary EEG signal classification.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.11a
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• pp.148-152
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• 2002

This study is to develop the Alzheimers disease (AD) detection and analysis system using event-related potential (ERP) of AD patients. We recorded ERP in an auditory oddball paradigm in mild AD (n=25), severe AD (n=12), age-matched normal aged controls (n=17), and young controls (n=7). The amplitude and latency of target P300 components were compared among 4 groups. The relationship between P300 measures and neuro psychological test (K-DRS) scores were evaluated by correlations. The latency of P300 was prolonged in AD and the effects were correlated with the severity of dementia. The P300 amplitude was not affected significantly in AD. Theres no difference between normal aged group and young group. These results suggest that the P300 component is specifically affected by Alzheimer type dementia.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.141-145
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• 2008

Wireless sensor network (WSN) is expected to be used in many applications. However, sensor nodes still have some secure problems to use them in the real applications. They are typically deployed on open, wide, and unattended environments. An adversary using these features can easily compromise the deployed sensor nodes and use compromised sensor nodes to inject fabricated data to the sensor network (false data injection attack). The injected fabricated data drains much energy of them and causes a false alarm. To detect and drop the injected fabricated data, a filtering-based security method and adaptive methods are proposed. The number of different partitions is important to make event report since they can make a correctness event report if the representative node does not receive message authentication codes made by the different partition keys. The proposed methods cannot guarantee the detection power since they do not consider the filtering scheme. We proposed clustering method for filtering-based secure methods. Our proposed method uses fuzzy system to enhance the detection power of a cluster.

• Journal of the Korea Society of Computer and Information
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• v.24 no.8
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• pp.95-103
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• 2019

According to the Statistics Korea in 2017, the 10 leading causes of death contain a cardiac disorder disease, self-injury. In terms of these diseases, urgent assistance is highly required when people do not move for certain period of time. We propose an unusual event detection algorithm to identify abnormal user behaviors using dust, vision and activity sensors in their houses. Vision sensors can detect personalized activity behaviors within the CCTV range in the house in their lives. The pattern algorithm using the dust sensors classifies user movements or dust-generated daily behaviors in indoor areas. The accelerometer sensor in the smartphone is suitable to identify activity behaviors of the mobile users. We evaluated the proposed pattern algorithms and the fusion method in the scenarios.