• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2156-2170
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• 2020

This paper presents a fire detection algorithm with a minimal false detection rate, intended for a thermal imaging surveillance environment, whose properties vary depending on temporal conditions of day or night and environmental changes. This algorithm was designed to minimize the false detection alarm rate while ensuring a high detection rate, as required in fire detection applications. It was necessary to reduce false fire detections due to non-flame elements occurring when existing fixed threshold-based fire detection methods were applied. To this end, adaptive flame thresholds that varied depending on the characteristics of input images, as well as the center of gravity of the heat-source and hot-source regions, were analyzed in an attempt to minimize such non-flame elements in the phase of selecting flame candidate blocks. Also, to remove any false detection elements caused by camera shaking, one of the most frequently raised issues at outdoor sites, preliminary decision thresholds were adaptively set to the motion pixel ratio of input images to maximize the accuracy of the preliminary decision. Finally, in addition to the preliminary decision results, the texture correlation and intensity of the flame candidate blocks were averaged for a specific period of time and tested for their conformity with the fire decision conditions before making the final decision. To verify the fire detection performance of the proposed algorithm, a total of ten test videos were subjected to computer simulation. As a result, the fire detection accuracy of the proposed algorithm was determined to be 94.24%, with minimum false detection, demonstrating its improved performance and practicality compared to previous fixed threshold-based algorithms.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1194-1199
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• 2009

Heart rate may be a very important parameter in human health. To extract heart rate, the electrocardiogram(ECG) is commonly used. But the ECG acquisition procedure is very complex. On the other hand, the acquisition of pulse wave or photoplethysmogram(PPG) is very easy. However, the peak of PPG is not so sharp as ECG. This study tries to enhance the performance of peak detection in PPG signal. The method uses the average slopes around the main peak. The crossing point of the increasing and the decreasing slopes is selected as the peak point of heart rate period. The proposed method showed smoothed heart rate graph and reduced irregularity in heart rate values.

• Korean Journal of Veterinary Service
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• v.13 no.2
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• pp.189-195
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• 1990

During 9 months (March-November, 1989), observation of Leucocytozoon infection rate to blood and parenchymatous viscera (spleen, liver, heart) in Pusan, Gyeongnam (Kimhae, Yangsan) districts slaughtered chicken and the results obtained were as follow : 1. Among the blood smear sample of 213 heads of the chicken, 43 heads (20.2%) were infected with Leucocytozoon 2nd stage gametocyte and 4 heads (1.9%) were mixed infected with Leucocytozoon 5th stage gametocyte. 2. In histopathological detection of schizont in tissues section of spleen, liver and heart, there were 16.7% in spleen, 5.6％ in liver and 9.1％ in heart, mean detection rate were 10.6%. Spleen had the highest detection rate of schizont. 3. In seasonal-related Infection rate, summer was higher than spring.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.68-77
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• 2013

This study suggested experimental study results of congestion detection method for intruding vehicle enforcement system. This congestion detection method is developed to determine optimal operation criteria of intruding vehicle enforcement system as detecting traffic congestion. In ITS sector, traffic management systems generally have used a sectional travel speed for congestion detection. However, image sensors have high error rate of congestion detection because of speed error. This study suggested comprehensive congestion detection criteria based on speed and occupancy rate using field studies. As field study results, the proposed intruding vehicle enforcement system using image sensor is capable of accurately detecting the traffic congestion using sectional speed of 20km/h and occupancy rate of 60% as congestion detection criteria.

• Journal of Microbiology and Biotechnology
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• v.28 no.3
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• pp.465-472
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• 2018

Our aim was to determine the detection rate of respiratory viruses (RVs) in feces of patients with acute viral respiratory infection (AVRI) and the detection rate of diarrheal viruses (DVs) in nasopharyngeal samples from patients with acute viral gastroenteritis. The relationships between the presence of fecal RVs or nasopharyngeal DVs and their impacts on the clinical severity were also investigated. A total of 144 fecal specimens were collected from AVRI patients and 95 nasopharyngeal specimens were collected from acute viral gastroenteritis patients. Clinical characteristics and laboratory profiles were compared between subgroups on the basis of the presence or absence of virus in the specimens. The detection rate of RVs in feces was 17.4% (25/144), whereas the detection rate for viruses identical to the respiratory pathogen was 10.4% (identical group, 15/144). Within the identical group, adenovirus (86.7%, 13/15) was most commonly found. Patients in the identical group showed statistically higher values for C-reactive protein, mean age, increased frequency of vomiting, and decreased frequency of chest film involvement and cough (p < 0.05). The detection rate of nasopharyngeal DVs among acute viral gastroenteritis patients was 19.0% (18/95), and in the identical group it was 15.8% (15/95). Norovirus group II and enteric adenovirus were the major pathogens detected in the identical group. There were no significant differences in clinical characteristics and laboratory profiles between the subgroups. In conclusion, the major pathogens of fecal RV and nasopharyngeal DV were adenovirus and norovirus group II, respectively. However, their relationship with the clinical symptoms or disease severity is unclear.

• Journal of Environmental Science International
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• v.4 no.1
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• pp.91-103
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• 1995

The reaction rate, equilibrium, and flow injection analysis methods were fundamentally evaluated for the determination of aqueous ammonia. The selected indophenol blue method was based on the formation of indophenol blue in which ammonium ion reacted with hypochlorite and phenol in alkaline solution. In the optimized reaction condition, the reaction followed 1st order reaction kinetics and the final product was stable. The absorbance measurements before and after the equilibrium were utilized for the reaction rate and equilibrium methods. The reaction rate methods, based on the relative analytical signals for the possibility of eliminating interferents, were shown to have good linear calibration curves but the detection limit and the calibration sensitivity were poorer than those in the equilibrium method. The detection limits were 32-49 pub and 24 pub for the reaction rate and equilibrium methods, respectively In the flow injection analysis, the absorbance was measured before the equilibrium reached and thus resulted in 30% reduction of calibration sensitivity. However, the detection limit was 11 ppb, indicating that the peak-to-peak noise for the blank was remarkably improved. Compared to the manual methods, the optimized experimental condition in a closed reaction system reduced the blank absorbance and the inclusion of ammonia from the atmosphere was prevented. In addition, highly reproducible mixing of sample and reagents and analytical data extracted from continuous recording showed excellent reproducibility.

• International Journal of Reliability and Applications
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• v.17 no.2
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• pp.149-158
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• 2016

We are enjoying a very comfortable life thanks to modern civilization, however, comfort is not guaranteed to us. Development of software system is a difficult and complex process. Therefore, the main focus of software development is on improving the reliability and stability of a software system. We have become aware of the importance of developing software reliability models and have begun to develop software reliability models. NHPP software reliability models have been developed through the fault intensity rate function and the mean value functions within a controlled testing environment to estimate reliability metrics such as the number of residual faults, failure rate, and reliability of the software. In this paper, we present a new NHPP software reliability model with Burr Type III fault detection rate, and present the goodness-of-fit of the fault detection rate software reliability model and other NHPP models based on two datasets of software testing data. The results show that the proposed model fits significantly better than other NHPP software reliability models.

• Journal of Yeungnam Medical Science
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• v.36 no.2
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• pp.109-114
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• 2019

Background: Transforaminal epidural block (TFEB) is an effective treatment option for radicular pain. To reduce complications from intravascular injection during TFEB, use of imaging modalities such as real-time fluoroscopy (RTF) or digital subtraction angiography (DSA) has been recommended. In this study, we investigated whether DSA improved the detection of intravascular injection during TFEB at the whole spine level compared to RTF. Methods: We prospectively examined 316 patients who underwent TFEB. After confirmation of final needle position using biplanar fluoroscopy, 2 mL of nonionic contrast medium was injected at a rate of 0.5 mL/s under RTF; 30 s later, 2 mL of nonionic contrast medium was injected at a rate of 0.5 mL/s under DSA. Results: Thirty-six intravascular injections were detected for an overall rate of 11.4% using RTF, with 45 detected for a rate of 14.2% using DSA. The detection rate using DSA was statistically different from that using RTF (p=0.004). DSA detected a significantly higher proportion of intravascular injections at the cervical level than at the thoracic (p=0.009) and lumbar (p=0.011) levels. Conclusion: During TFEB at the whole spine level, DSA was better than RTF for the detection of intravascular injection. Special attention is advised for cervical TFEB, because of a significantly higher intravascular injection rate at this level than at other levels.

• Journal of Korean Society of Transportation
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• v.19 no.6
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• pp.7-17
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• 2001

The purpose of this paper is to develop automatic incident detection algorithm using image based detector in freeway management system. This algorithm was developed by using neutral network for high speed roadway and by using speed and occupancy variable for low speed roadway. The image detector system with the developed automatic incident detection algorithm can detect multi-lane as well as several detect areas for each lane. To evaluate this system, field tests to measure the detecting rate of incidents were performed with other systems which have APID and DES algorithm at high speed roadway(freeway) and low speed roadway(national arterial). As the results of field test, it found that the detect rate of this system was highest rate comparing to other two systems.

• 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.