• Title/Summary/Keyword: False alarm reducing

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Alarm-Guided Locally Relational Post-Analysis for Reducing False Alarms (분석 경보 주위에만 관계 분석을 적용하여 거짓경보를 줄이는 방법)

  • Lee, Woo-Suk;Oh, Hak-Joo;Kim, You-Il;Yi, Kwang-Keun
    • Proceedings of the Korean Information Science Society Conference
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    • 2011.06c
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    • pp.450-453
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    • 2011
  • 분석 경보에 따른 점층적인 분석을 수행하는 버퍼 오버런 분석 기법을 제안한다. 구간 도메인을 사용한 분석은 비용이 낮지만 정확도도 낮다. 변수들 간의 관계를 고려하는 팔각형 도메인을 사용한 분석은 정확도가 높지만 비용도 높다. 점층적인 분석 방법으로 정적 분석기의 비용과 정확도 사이에서 균형을 잡을 수 있다. 먼저 (비용이 낮은) 구간 도메인을 사용한 분석을 수행하고, 증명하지 못한 부분 코드에 대해서만 (정확도가 높은) 관계 도메인을 사용한 분석을 적용한다. 정확도가 높은 분석이 필요한 부분에만 관계 분석을 적용함으로써, 낮은 분석 비용을 유지하면서 정확도를 높일 수 있다.

A Video Smoke Detection Algorithm Based on Cascade Classification and Deep Learning

  • Nguyen, Manh Dung;Kim, Dongkeun;Ro, Soonghwan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.12
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    • pp.6018-6033
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    • 2018
  • Fires are a common cause of catastrophic personal injuries and devastating property damage. Every year, many fires occur and threaten human lives and property around the world. Providing early important sign for early fire detection, and therefore the detection of smoke is always the first step in fire-alarm systems. In this paper we propose an automatic smoke detection system built on camera surveillance and image processing technologies. The key features used in our algorithm are to detect and track smoke as moving objects and distinguish smoke from non-smoke objects using a convolutional neural network (CNN) model for cascade classification. The results of our experiment, in comparison with those of some earlier studies, show that the proposed algorithm is very effective not only in detecting smoke, but also in reducing false positives.

Reducing False Alarm and Shortening Worm Detection Time in Virus Throttling (Virus Throttling의 웜 탐지오판 감소 및 탐지시간 단축)

  • Shim Jae-Hong;Kim Jang-bok;Choi Hyung-Hee;Jung Gi-Hyun
    • The KIPS Transactions:PartC
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    • v.12C no.6 s.102
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    • pp.847-854
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    • 2005
  • Since the propagation speed of the Internet worms is quite fast, worm detection in early propagation stage is very important for reducing the damage. Virus throttling technique, one of many early worm detection techniques, detects the Internet worm propagation by limiting the connection requests within a certain ratio.[6, 7] The typical throttling technique increases the possibility of false detection by treating destination IP addresses independently in their delay queue managements. In addition, it uses a simple decision strategy that determines a worn intrusion if the delay queue is overflown. This paper proposes a two dimensional delay queue management technique in which the sessions with the same destination IP are linked and thus a IP is not stored more than once. The virus throttling technique with the proposed delay queue management can reduce the possibility of false worm detection, compared with the typical throttling since the proposed technique never counts the number of a IP more than once when it chicks the length of delay queue. Moreover, this paper proposes a worm detection algorithm based on weighted average queue length for reducing worm detection time and the number of worm packets, without increasing the length of delay queue. Through deep experiments, it is verified that the proposed technique taking account of the length of past delay queue as well as current delay queue forecasts the worn propagation earlier than the typical iuぉ throttling techniques do.

Evaluating Economic Value of Heat Wave Watch/Warning Information in Seoul and Busan in 2016: Focused on a Cost of Heat Wave Action Plan and Sample of Patients (2016년 서울과 부산지역 폭염특보 정보의 경제적 가치 평가 -폭염대책 비용과 환자 자료를 중심으로-)

  • Kim, In-Gyum;Lee, Seung-Wook;Kim, Hye-min;Lee, Dae-Geun
    • The Journal of the Korea Contents Association
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    • v.20 no.5
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    • pp.525-535
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    • 2020
  • This study aims to evaluate the economic value of the heat wave watch/warning (HW/W) forecast provided by the KMA (Korea Meteorological Administration) for the public sector. Local govermenments of Korea currently use the HW/W forecasts as a major input variable to determine the preparative requisite level for reducing potential damage by extreme heat events. To assess the value of the HW/W, which is not a marketable commodity, a decision-making model taking into account the cost and loss was established. The 'cost' variable was defined as the heat wave countermeasures budget for Seoul and Busan in 2016, and the 'loss' variable was set as the amount of health insurance claims for those 65 and older obtained from the Health Insurance Review and Assessment Service. Using this model, the value of the HW/W in 2016 was calculated as KRW 4,133M and KRW1,090M for Seoul and Busan, respectively. In addition, if the KMA reduces the False Alarm of the HW/W by a single instance, the value will be increased by KRW 76.6M and KRW 16.8M for the two cities. The results of this study are useful in quantitatively estimation of the value of the HW/W forthe public sector.

Development of the Algofithm for Gaussian Mixture Models based Traffic Accident Auto-Detection in Freeway (GMM(Gaussian Mixture Model)을 적용한 영상처리기법의 연속류도로 사고 자동검지 알고리즘 개발)

  • O, Ju-Taek;Im, Jae-Geuk;Yeo, Tae-Dong
    • Journal of Korean Society of Transportation
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    • v.28 no.3
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    • pp.169-183
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    • 2010
  • Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a freeway and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, existing technologies, this freeway attribute, velocity changes, volume changes, occupancy changes reflect judge the primary. Furthermore, We pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian Mixture model analytical method which has been considered the best among well-known environmental obstacle reduction methods. Therefore, in this way, the accident was the final decision. Also, environmental factors occur frequently, and with the index finger situations, effectively reducing that can actively and environmentally adaptive techniques through accident final judgment. This implementation of the evaluate performance of the experiment road of 12 incidents in simulated and the jang-hang IC's real-time accident experiment. As a result, the do well detection 93.33%, false alarm 6.7% as showed high reliability.

A neck healthy warning algorithm for identifying text neck posture prevention (거북목 자세를 예방하기 위한 목 건강 경고 알고리즘)

  • Jae-Eun Lee;Jong-Nam Kim;Hong-Seok Choi;Young-Bong Kim
    • Journal of the Institute of Convergence Signal Processing
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    • v.23 no.3
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    • pp.115-122
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    • 2022
  • With the outbreak of COVID-19 a few years ago, video conferencing and electronic document work have increased, and for this reason, the proportion of computer work among modern people's daily routines is increasing. However, as more and more people work on computers in the wrong posture for a long time, the number of patients with poor eyesight and text neck is increasing. Until recently, many studies have been published to correct posture, but most of them have limitations that users may experience discomfort because they have to correct posture by wearing equipment. A posture correction sensor algorithm is proposed to prevent access to the minimum distance between a computer monitor and a person using an ultrasonic sensor device. At this time, an algorithm for minimizing false alarms among warning alarms that sound at the minimum distance is also proposed. Because the ultrasonic sensor device is used, posture correction can be performed without attaching a device to the body, and the user can relieve discomfort. In addition, experimental results showed that accuracy can be improved by reducing false alarms by removing more than half of the noise generated during distance measurement.

OS CFAR Computation Time Reduction Technique to Apply Radar System in Real Time (레이다 시스템 실시간 적용을 위한 OS CFAR 연산 시간 단축 방안)

  • Kong, Young-Joo;Woo, Seon-Keol;Park, Sungho;Shin, Seung-Yong;Jang, Youn Hui;Yang, Eunjung
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.29 no.10
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    • pp.791-798
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    • 2018
  • The CFAR algorithm is mainly used for target detection in radar systems. In particular, OS CFAR is used in a non-uniform noise environment. However, it requires a large amount of computation, because it should sort reference cells in ascending order. This makes it difficult to apply the radar system in real time. In this paper, we describe how to reduce the computational burden of OS CFAR. We compared the power of the test cell and reference cell to determine only the presence or absence of target detection. The common reference cells overlapping in the reference cells of the three test cells are obtained. We first compare the test cell with the highest power value among the three test cells to the common reference cells. Next, we compare each test cell to general reference cells, excluding the common reference cells. The computation time is shortened by reducing the power comparison computation amounts.

Run-to-Run Fault Detection of Reactive Ion Etching Using Support Vector Machine (Support Vector Machine을 이용한 Reactive ion Etching의 Run-to-Run 오류검출 및 분석)

  • Park Young-Kook;Hong Sang-Jeen;Han Seung-Soo
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.5
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    • pp.962-969
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    • 2006
  • To address the importance of the process fault detection for productivity, support vector machines (SVMs) is employed to assist the decision to determine process faults in real-time. The reactive ion etching (RIE) tool data acquired from a production line consist of 59 variables, and each of them consists of 10 data points per second. Principal component analysis (PCA) is first performed to accommodate for real-time data processing by reducing the dimensionality or the data. SVMs for eleven steps or etching m are established with data acquired from baseline runs, and they are further verified with the data from controlled (acceptable) and perturbed (unacceptable) runs. Then, each SVM is further utilized for the fault detection purpose utilizing control limits which is well understood in statistical process control chart. Utilizing SVMs, fault detection of reactive ion etching process is demonstrated with zero false alarm rate of the controlled runs on a run to run basis.

Smoke detection in video sequences based on dynamic texture using volume local binary patterns

  • Lin, Gaohua;Zhang, Yongming;Zhang, Qixing;Jia, Yang;Xu, Gao;Wang, Jinjun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5522-5536
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    • 2017
  • In this paper, a video based smoke detection method using dynamic texture feature extraction with volume local binary patterns is studied. Block based method was used to distinguish smoke frames in high definition videos obtained by experiments firstly. Then we propose a method that directly extracts dynamic texture features based on irregular motion regions to reduce adverse impacts of block size and motion area ratio threshold. Several general volume local binary patterns were used to extract dynamic texture, including LBPTOP, VLBP, CLBPTOP and CVLBP, to study the effect of the number of sample points, frame interval and modes of the operator on smoke detection. Support vector machine was used as the classifier for dynamic texture features. The results show that dynamic texture is a reliable clue for video based smoke detection. It is generally conducive to reducing the false alarm rate by increasing the dimension of the feature vector. However, it does not always contribute to the improvement of the detection rate. Additionally, it is found that the feature computing time is not directly related to the vector dimension in our experiments, which is important for the realization of real-time detection.

Optimization of Classification of Local, Regional, and Teleseismic Earthquakes in Korean Peninsula Using Filter Bank (주파수 필터대역기술을 활용한 한반도의 근거리 및 원거리 지진 분류 최적화)

  • Lim, DoYoon;Ahn, Jae-Kwang;Lee, Jimin;Lee, Duk Kee
    • Journal of the Korean Geotechnical Society
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    • v.35 no.11
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    • pp.121-129
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    • 2019
  • An Earthquake Early Warning (EEW) system is a technology that alerts people to an incoming earthquake by using P waves that are detected before the arrival of more severe seismic waves. P-wave analysis is therefore an important factor in the production of rapid seismic information as it can be used to quickly estimate the earthquake magnitude and epicenter through the amplitude and predominant period of the observed P-wave. However, when a large-magnitude teleseismic earthquake is observed in a local seismic network, the significantly attenuated P wave phases may be mischaracterized as belonging to a small-magnitude local earthquake in the initial analysis stage. Such a misanalysis may be sent to the public as a false alert, reducing the credibility of the EEW system and potentially causing economic losses for infrastructure and industrial facilities. Therefore, it is necessary to develop methods that reduce misanalysis. In this study, the possibility of seismic misclassifying teleseimic earthquakes as local events was reviewed using the Filter Bank method, which uses the attenuation characteristics of P waves to classify local and outside Korean peninsula (regional and teleseismic) events with filtered waveform depending on frequency and epicenter distance. The data used in our analysis were analyzed for maximum Pv values using 463 events with local magnitudes (2 < ML ≦ 3), 44 (3 < ML ≦ 4), 4 (4 < ML ≦ 5), 3 (ML > 5), and 89 outside Korean peninsula earthquakes recorded by the KMA seismic network. The results show that local and telesesimic earthquakes can be classified more accurately when combination of filtering bands of No. 3 (6-12 Hz) and No. 6 (0.75-1.5 Hz) is applied.