• ETRI Journal
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• v.37 no.3
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• pp.502-511
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• 2015

Intrusion detection plays a key role in detecting attacks over networks, and due to the increasing usage of Internet services, several security threats arise. Though an intrusion detection system (IDS) detects attacks efficiently, it also generates a large number of false alerts, which makes it difficult for a system administrator to identify attacks. This paper proposes automatic fuzzy rule generation combined with a Wiener filter to identify attacks. Further, to optimize the results, simplified swarm optimization is used. After training a large dataset, various fuzzy rules are generated automatically for testing, and a Wiener filter is used to filter out attacks that act as noisy data, which improves the accuracy of the detection. By combining automatic fuzzy rule generation with a Wiener filter, an IDS can handle intrusion detection more efficiently. Experimental results, which are based on collected live network data, are discussed and show that the proposed method provides a competitively high detection rate and a reduced false alarm rate in comparison with other existing machine learning techniques.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5A
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• pp.527-536
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• 2004

A novel hybrid multiple access system, TD-BCDMA, where Binary CDMA that maintains a constant amplitude by clipping the summation of input signals multiplied by the orthogonal codes is transmitted over a TDMA frame structure, was Nosed. In every time slot of TDMA, binary CDMA modulated multiple channel signals are transmitted with the same waveform of TDMA. TD-BCDMA has all the advantages of TDMA. Flexible adjustment of the data transmission rate In demand is possible by adjusting the number of codes and time slots assigned to each user. This property was used to show an example of Ad Hoc network applications. To obtain a proper synchronization scheme for TD-BCDMA, the Receiver Operating Characteristics performance and the false alarm probability and false dismissal probability under various channel environment of two different schemes, a preamble scheme as in TDMA and a synchronization channel scheme as in CDMA were compared. It was proved that the preamble scheme is more practical and suitable than the synchronization channel scheme for the hybrid multiple access system.

• Journal of Computing Science and Engineering
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• v.10 no.3
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• pp.75-84
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• 2016

Medical cyber-physical systems (MCPS) integrate sensors, actuators, and software to improve patient safety and quality of healthcare. These systems introduce major challenges to safety analysis because the patient's physiology is complex, nonlinear, unobservable, and uncertain. To cope with the challenge that unidentified physiological parameters may exhibit short-term variances in certain clinical scenarios, we propose a novel run-time predictive safety monitoring technique that leverages a maximal model coupled with online training of a computational virtual subject (CVS) set. The proposed monitor predicts safety-critical events at run-time using only clinically available measurements. We apply the technique to a surgical glucose control case study. Evaluation on retrospective real clinical data shows that the algorithm achieves 96% sensitivity with a low average false alarm rate of 0.5 false alarm per surgery.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1968-1976
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• 2007

This paper proposes a hybrid pseudo-noise (PN) code acquisition scheme for Multicarrier Direct Sequence - Code Division Multiple Access (MC DS-CDMA) mobile communication systems on the code acquisition performance for Nakagami-m fading channel. The hybrid acquisition scheme combines parallel search with serial search to cover the whole uncertainty region of the input code phase. It has a much simpler acquisition hardware structure than the total parallel acquisition and can achieve the mean acquisition time (MAT) slightly inferior to that of the total parallel acquisition. The closed-form expressions of the detection and false-alarm probabilities are derived.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.16-23
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• 2022

This study aims to provide a fundamental material for identifying fire and no-fire signals using the detection signal characteristics of IoT-based fire-detection systems. Unlike analog automatic fire-detection equipment, IoT-based fire-detection systems employ wireless digital communication and are connected to a server. If a detection signal exceeds a threshold value, the measured values are saved to a server within seconds. This study was conducted with the detection data saved from seven fire accidents that took place in traditional markets from 2020 to 2021, in addition to 233 fire alarm data that have been saved in the K institute from 2016 to 2020. The saved values demonstrated variable and continuous VC-Signals. Additionally, we discovered that the detection signals of two fire accidents in the K institution had a VC-Signal. In the 233 fire alarms that took place over the span of 5 years, 31% of smoke alarms and 30% of temperature alarms demonstrated a VC-Signal. Therefore, if we selectively recognize VC-Signals as fire signals, we can reduce about 70% of false alarms.

• Neonatal Medicine
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• v.17 no.2
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• pp.245-249
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• 2010

Purpose: Numerous false alarms by pulse oximetry, which is widely used in neonatal intensive care unit, can delay response to true alarms. Masimo $SET^{(R)}$ was introduced lately, to overcome false alarms by motion. We compared the clinical performance of two devices (Nellcor $N-595^{(R)}$ and Masimo $SET^{(R)}$) for the evaluation of the false alarm frequency during usual motion artifacts and stable state. Methods: A total of 20 preterm infants weighing 1,000-2,500 g were enrolled in the study. The sensors of two devices were placed on the different feet on the same infants, and both devices were programmed to emit an alarm for episode of hypoxemia (SpO2$\leq$85%). The false alarms were defined as episodes of poor correlation with ECG heart rate, poor waveforms, and the absence of obvious signs of hypoxia. We compared the frequency of false alarms between the two devices. Results: The mean chronological age was 20.8 days and the mean body weight was 1,668 g on the study day. The frequency of total false alarm was significantly fewer for Masimo $SET^{(R)}$ pulse oximetry (48 in Nellcor $N-595^{(R)}$, 27 in Masimo $SET^{(R)}$) although the false alarm during usual motion artifacts was not significantly between two devices (32 in Nellcor $N-595^{(R)}$, 19 in Masimo $SET^{(R)}$). Conclusion: The Masimo $SET^{(R)}$ pulse oximetry has fewer false alarm rates and identified more true hypoxic events than Nellcor $N-595^{(R)}$ pulse oximetry. Therefore, it is useful for adequate oxygen therapy and helps to decrease unnecessary handling by clinicians and nurses.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.229-239
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• 2008

Most algorithms for detecting incidents have been developed under the premise that congestion must happen whenever an incident occurs. For that reason, the performance of these algorithms could not be guaranteed in cases where congestion did not happen due to traffic operations with low flows despite the occurrence of an incident. The objective of this paper is to develop an automatic incident detection algorithm using a new diagram that can reliably detect the incident under various conditions of traffic operations including a low volume state. Compared with the McMaster Algorithm, the proposed algorithm in this paper was evaluated with three different cases in which the incidents occur in traffic operations with a low volume state, a relatively high volume state, and a recurrent congestion state. It is shown that the new algorithm has a capability to identify the flow characteristics of incidents for all the three cases and is much better than McMaster algorithm in terms of detection rate and false alarm rate.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.447-453
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• 2009

This paper introduces the method for detect voices and exact end point at low SNR by maximizing voice energy. Conventional VAD (Voice Activity Detection) algorithm estimates noise level so it tends to detect the end point inaccurately. Moreover, because it uses relatively long analysis range for reflecting temporal change of noise, computing load too high for application. In this paper, the SEM-VAD (Speech Energy Maximization-Voice Activity Detection) method which uses psycho-acoustical bark scale filter banks to maximize voice energy within frames is introduced. Stable threshold values are obtained at various noise environments (SNR 15 dB, 10 dB, 5 dB, 0 dB). At the test for voice detection in car noisy environment, PHR (Pause Hit Rate) was 100%accurate at every noise environment, and FAR (False Alarm Rate) shows 0% at SNR15 dB and 10 dB, 5.6% at SNR5 dB and 9.5% at SNR0 dB.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.981-999
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• 2017

In the standard control chart assuming a simple random model, we estimate the process variance without considering the between-sample variance. If the between-sample exists in the process, the process variance is under-estimated. When the process variance is under-estimated, the narrower control limits result in the excessive false alarm rate although the sensitivity of the control chart is improved. In this paper, using the variance component model to incorporate the between-sample variance, we set the control limits using both the within- and between-sample variances, and evaluate the efficiency of the control chart in terms of the average run length (ARL). Considering the most widely used control chart types such as ${\bar{X}}$, EWMA and CUSUM control charts, we compared the differences between two cases, Case I and Case II, where the between-sample variance is ignored and considered, respectively. We also considered the two cases when the process parameters are given and estimated. The results showed that the false alarm rate of Case I increased sharply as the between-sample variance increases, while that of Case II remains the same regardless of the size of the between-sample variance, as expected.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1991.10a
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• pp.92-95
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• 1991

Constant false alarm rate(CFAR) processors are useful for detecting radar targets in background for which all parameters in the statistical distribution are not known and may be nonstationary. The well known "cell averging" (CA) CFAR processor is known to yield best performance in homogeneous case, but exhibits severe performance in the presence of an interfering target in the reference window or/and in the region of clutter edges. The "order statistics"(OS) CFAR processor is known to have a good performance above two nonhomogeneous cases. The modified OS-CFAR processor, known as "trimmed mean"(TM) CFAR processor performs somewhat better than the OS-CFAR processor by judiciously trimming the ordered samples. This paper proposes and analyzes the performance of a new CFAR processor called the "maximum trimmed mean"(MX-TM) CFAR processor combining the "greatest of"(GO) CFAR and TM-CFAR processors. The MAX operation is included to control false alarms at clutter edges. Our analyses show that the proposed CFAR processor has similar performance TM- and OS-CFAR processors in homogeneous case and in the precence of interfering targets, but can control the false rate in clutter edges. Simulation results are presented to demonstrate the qualitative effects of various CFAR processors in nonhomogeneous clutter environments.