• ETRI Journal
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• 제41권2호
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• pp.176-183
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• 2019

Spectrum sensing plays an important role in spectrum sharing. Energy detection is generally used because it does not require a priori knowledge of primary user (PU) signals; however, it is sensitive to noise uncertainty. An order statistics (OS) detector provides inherent protection against nonhomogeneous background signals. However, no analysis has been conducted yet to apply OS detection to spectrum sensing in a wireless channel to solve noise uncertainty. In this paper, we propose a robust spectrum sensing scheme based on generalized order statistics (GOS) and analyze the exact false alarm and detection probabilities under noise uncertainty. From the equation of the exact false alarm probability, the threshold value is calculated to maintain a constant false alarm rate. The detection probability is obtained from the calculated threshold under noise uncertainty. As a fusion rule for cooperative spectrum sensing, we adopt an OR rule, that is, a 1-out-of-N rule, and we call the proposed scheme GOS-OR. The analytical results show that the GOS-OR scheme can achieve optimum performance and maintain the desired false alarm rates if the coefficients of the GOS-OR detector can be correctly selected.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.669-670
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• 2008

In this paper, we present a real-time system to detect abnormal events on gas pipes, based on the signals which are observed through the audio sensors attached on them. First, features are extracted from these signals so that they are robust to noise and invariant to the distance between a sensor and a spot at which an abnormal event like an attack on the gas pipes occurs. Then, a classifier is constructed to detect abnormal events using neural networks. It is a combination of two neural network models, a Gaussian mixture model and a multi-layer perceptron, for the reduction of miss and false alarms. The former works for miss alarm prevention and the latter for false alarm prevention. The experimental result with real data from the actual gas system shows that the proposed system is effective in detecting the dangerous events in real-time with an accuracy of 92.9%.

• 한국항해항만학회지
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• 제38권6호
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• pp.645-653
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• 2014

A Bridge Navigational Watch Alarm System (hereafter 'BNWAS') is to monitor and detect if an officer of watch(hereafter 'OOW') keeps a sharp lookout on the bridge. The careless lookout of an OOW could lead to marine accidents. For this reason on June 5th, 2009, IMO decided that a ship is equipped with a BNWAS. However, an existing BNWAS gives the OOW a lot of inconvenience and stress in its operation. It requires that the OOW should press reset buttons to confirm their alert watch on the bridge at every three to twelve minute. Many OOWs have complained that at some circumstances they cannot focus on their bridge activities including watch-keeping due to a lots of resetting inputs of BNWAS. Accordingly, IMO has allowed the use of a motion sensor as a resetting device. The motion sensor detects the movements of human body on the bridge and subsequently sends reset signals directly to BNWAS automatically. As a result, OOWs can work uninterrupted. However, some of classification societies and flag authorities have a slightly different stance on the use of motion sensor as a resetting method for BNWAS. The reason is that the motion sensor may trigger false reset signals caused by the motion of objects on the bridge, especially a slight movement such as toss and turn of human body which can extend the period of careless watch. As a basic study to minimize the false reset signals, this paper proposes a simple configuration of BNWAS, which consists of only three motion sensors associated with 'AND' and 'OR' logic gates. Additionally, several considerations are also proposed for the implementation of motion sensors. This study found that the proposed configuration which consists of three motion sensors is better than an existing one by reducing false reset signals caused by a slight movement of human body in one's sleep. The proposed configuration in this paper filters false reset signals and is simple to be implemented on existing vessels. In addition, it can be easily installed just by a basic electrical knowledge.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2005년도 춘계학술발표회
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• pp.7-12
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• 2005

선박은 하나의 거대한 인간-기계시스템으로써 작업자와 시스템간의 상호 작용이 얼마나 잘 이루어지는가에 따라 수행하고자 하는 직무와 수행도에 영항을 미치게 된다. 선교 내에는 시각 표시 장치뿐만 아니라 청각 표시 장치로부터 나오는 많은 신호들이 존재한다. 그 중 장비의 알람(alarm)에 대한 인간의 인지능력에 대한 연구는 부족한 상태이다. 본 연구에서는 auditory icons과 sounds의 비교 평가를 통하여 알람에 대한 작업자의 인지에 대한 연구를 하였다. 실험결과 auditory icons를 사용한 경우 sounds 보다 더 빠르고 정확하게 인지 할 수 있는 것으로 나타났다 선교 내 청각적 표시장치의 성능 기준 그리고 현재 논의 되고 있는 통합 선교 알람 시스템을 위한 기초 자료로 본 연구의 결과가 이용될 수 있을 것이라 생각된다.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.760-767
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• 2022

This paper introduces alert fatigue and presents methods to measure alert fatigue by using physiological signals. Alert fatigue is a phenomenon that which an individual is constantly exposed to frequent alarms and becomes desensitized to them. Blind spots are one leading cause of struck-by accidents, which is one most common causes of fatal accidents on construction sites. To reduce such accidents, construction equipment is equipped with an alarm system. However, the frequent alarm is inevitable due to the dynamic nature of construction sites and the situation can lead to alert fatigue. This paper introduces alert fatigue and proposes methods to use physiological signals such as electroencephalography, electrodermal activity, and event-related potential for the measurement of alert fatigue. Specifically, this paper presents how raw data from the physiological sensors measuring such signals can be processed to measure alert fatigue. By comparing the processed physiological data to behavioral data, validity of the measurement is tested. Using preliminary experimental results, this paper validates that physiological signals can be useful to measure alert fatigue. The findings of this study can contribute to investigating alert fatigue, which will lead to lowering the struck-by accidents caused by blind spots.

• Journal of Ecology and Environment
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• 제30권1호
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• pp.9-15
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• 2007

Black-tailed gulls (Larus crassirostris) produce alarm calls apparently related to their anti-predator behaviors, but the hypothesis that the calls are actually used as functionally referential alarm signals has not yet been tested. In this study, we performed a series of experiments using visual (a stuffed goshawk: Accipiter gentilis) and acoustic (alarm calls and a control vocalization) stimuli at 15 sites in Sinjindo-ri and Dowhang-ri, Taean-gun, Chungnam province to examine anti-predator responses of the gulls to alarm calls in playback trials. We found that the gulls' visual recognition of a perched hawk model in the absence of alarm vocalizations was weak or absent because the model was noticed in only two out of 16 trials. The gulls' responses to playbacks of the alarm call only and the alarm call with a visual stimulus differed from responses to the control vocalization in latency to approach, time mobbing, and the percentage of gulls responding, while the responses to alarm call only differed from alarm call with a visual stimulus in latency to first fly, latency to call, and time mobbing. The results of this study suggest that alarm calls of black-tailed gulls are used to elicit appropriate anti-predator behaviors that are intensified when a predator is detected visually.

• 천문학회보
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• 제39권2호
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• pp.107.1-107.1
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• 2014

We apply a machine learning algorithm, artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts. The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability is improved by the artificial neural network in comparison to the conventional detection statistic. Therefore, this algorithm increases the distance at which a gravitational-wave signal could be observed in coincidence with a gamma-ray burst. We also evaluate the gravitational-wave data within a few seconds of the selected short gamma-ray bursts' event times using the trained networks and obtain the false alarm probability. We suggest that artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short gamma-ray bursts.

• 정보처리학회논문지C
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• 제11C권3호
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• pp.301-308
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• 2004

전문가의 침입 분석 지식을 기반으로 한 Misuse IDS는 침입 탐지 비율은 우수하지만 도한 오경보를 생성하여 관리 효율성이 낮다. 우리는 패킷 정보 중심의 사례 기반 학습을 Misuse IDS와 결합하여 그 행동 특성에 따라 오경보를 줄이는 모형을 제안하고 실험하였다. 또 기존의 IBL(교stance Based Learner)을 개선한 XIBL(Extended Instance Based Learner)을 이용하여 Snort의 alarm을 패킷 수준에서 역 추적 분석하여, 그 alarm이 실제로 보내질 가치가 있는지를 검사한다. 실험 결과 진성경보와 오경보 사이에는 XIBL의 행동상 분명한 차이가 드러나며, 네트워크 상의 공격이 비록 여러 패킷의 결합된 형태로 나타나지만, 개별 패킷에 대한 정상/비정상 의사 결정도 Misuse IDS와 결합하면 전체 시스템의 성능을 향상하는 데에 기여할 수 있음을 실증적으로 보여주었다.

• 해양환경안전학회지
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• 제11권1호
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• pp.11-16
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• 2005

선박은 하나의 거대한 인간-기계시스템으로써 작업자와 시스템간의 상호 작용이 얼마나 잘 이루어지는가에 따라 수행하고자 하는 직무와 수행도에 영향을 미치게 된다. 선교 내에는 시각표시장치뿐만 아니라 청각표시장치로부터 나오는 많은 신호들이 존재한다. 그 중 장비의 알람에 대한 인간의 인지능력에 대한 연구는 미흡한 상태이다. 본 연구에서는 청각적 아이콘과 함축적 소리를 비교$\cdot$평가하여 알람에 대한 작업자의 인지에 대해 연구 하였다. 실험결과 청각적 아이콘이 함축적 소리를 사용한 경우 보다 더 빠르고 정확하게 인지 할 수 있는 것으로 나타났다. 본 연구의 결과는 선교 내 청각표시장치의 성능 기준 그리고 현재 논의 되고 있는 통합선교알람시스템을 위한 기초 자료로 이용될 수 있을 것이라 생각된다.

• 한국지능시스템학회논문지
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• 제24권6호
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• pp.634-639
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• 2014

본 논문에서는 근접거리측정이 가능한 적외선 거리 센서를 사용하여 다양한 물체 및 로봇과 이동 로봇 메커니즘간의 충돌 위험성을 확인할 수 있는 충돌 경보기를 제시하고, 이 경보기의 효과적인 산업 응용을 위하여 중요한 신호의 생성 과정 및 동작 특성을 분석하고자 한다. 이를 위하여 제시된 충돌 경보기를 탑재한 이동 로봇 시스템이 전형적인 주차 동작을 수행하는 상황을 고려한다. 결과적으로, 제시된 충돌 경보기는 다양한 이동 로봇이나 차량 메커니즘의 충돌 회피 및 안전 운행을 위하여 유용하게 활용될 수 있음을 보인다.