• Journal of Microbiology and Biotechnology
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• v.25 no.11
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• pp.1782-1786
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• 2015

A new improved PCR method has been developed for the rapid, reliable, and sensitive detection of Venturia nashicola, a destructive pathogen of scab disease in Japanese pear. The translation elongation factor-1 alpha gene-derived PCR primers specifically amplified a 257-bp-sized DNA band of the target gene from the genomic DNA of V. nashicola. No amplicon was produced from the genomic DNA of other Venturia spp. and reference fungal species tested. With the high detection limit of 10 fg DNA content, our real-time method could be used for the quarantine inspection and field monitoring of V. nashicola.

• Structural Monitoring and Maintenance
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• v.1 no.2
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• pp.213-230
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• 2014

A novel real-time actuator failure detection algorithm is developed in this paper. Actuator fails when the input to the structure is different from the commanded one. Previous research has shown that one error function can be formulated for each actuator through interaction matrix method. For output without noise, non-zero values in the actuator functions indicate the instant failure of the actuator regardless the working status of other actuators. In this paper, it is further demonstrated that the actuator's error function coefficients will be directly calculated from the healthy input of the examined actuator and all outputs. Hence, the need for structural information is no longer needed. This approach is termed as direct method. Experimental results from a NASA eight bay truss show the successful application of the direct method for isolating and identifying the real-time actuator failure. Further, it is shown that the developed method can be used for real-time sensor failure detection.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.4
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• pp.127-135
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• 1986

This paper represents a real time algorithm which improves the some drawbacks in the past methods for detection of the QRS conplexes of ECG signals. In the conventional method we can't detect QRS complex and QRS duration more correctly in case of (1) the contaminated ECG with 60Hz noise, muscle noise. (2) the movement of the baseline for a QRS complex. (3) being abnormal QRS complex with prolonging QRS. Therefore, we have proposed a new algorithm which can detect accurate QRS complex detection in case of the contaminated ECG with 60Hz noise, muscle noise, and movement of baseline for QRS complex. Moreover, in case of prolonging QRS we accomplished to detect not only QRS complex but also a single pulse that has a width proportional to QRS duration. This algorithm which is proposed in our paper in our paper in programmed with 6502 assembly language for real time ECG signal processing.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1662-1665
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• 2002

This paper proposes a novel semantic feature detection (SFD) method for real-time image transmission of sign language and finger spelling. We extract semantic information as an interlingua from input text by natural language processing, and then transmit the semantic feature detection, which actually is a parameterized action representation, to the 3-D articulated humanoid models prepared in each client in remote locations. Once the SFD is received, the virtual human will be animated by the synthesized SFD. The experimental results based on Japanese sign langauge and Chinese sign langauge demonstrate that this algorithm is effective in real-time image delivery of sign language and finger spelling.

• Korean Journal of Clinical Laboratory Science
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• v.46 no.2
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• pp.64-67
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• 2014

Vancomycin-resistant Enterococci (VRE) are a leading cause of a nosocomial infection. While seven glycopeptide resistance genotypes have been found in Enterococci, vanA and vanB are the most common resistance genotypes. Aims of this study were to detect antibiotic susceptibilities of 23 Enterococcus spp, which broke out in a university hospital by the disk diffusion test, to investigate specific genes of vanA and vanB by conventional and real-time PCR. PCR for vanA and vanB was performed on 23 Enterococci, all 23 were positive for vanA type. This study reports the validation of a simple and rapid VRE detection method that can be easily incorporated into the daily routine of a clinical laboratory. Early detection of VRE strains, including those with susceptibility to Vancomycin, is of paramount clinical importance, as it allows a rapid initiation of strict infection control practices as well as a therapeutic guidance for a confirmed infection. The real-time PCR method is a rapid technique to detect vanA in Enterococci. It is simple and reliable for the rapid characterization of VRE.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.4
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• pp.575-580
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• 2019

In biological warfare, it is important to identify biological agents for proper treatment. We focused on developing a real-time RT-PCR kit that can detect multiple species of biological agents. AccuPower(R) Biothreat Real-Time RT-PCR Kit(v3.0) could detect Bacillus anthracis, Yersinia pestis, Vibrio cholerae, Francisella tularensis, Salmonella typhi, Rickettsia prowazekii, Variola virus, Hantaan virus, Yellow fever virus, Brucella spp., Shigella dysenteriae in a single reaction. The results showed that the kit was verified to be able to detect at least 0.005 ng of nucleotide and 10,000 CFU/ml of bacteria. Therefore, the kit is expected to be used as a rapid and sensitive detection kit for 11 species of biological agents within 2 hours.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2348-2360
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• 2023

As science and technology evolve, object detection of moving objects has been widely used in the context of machine learning and artificial intelligence. Traditional moving object detection algorithms, however, are characterized by relatively poor real-time performance and low accuracy in detecting moving objects. To tackle this issue, this manuscript proposes a modified Kalman filter algorithm, which aims to expand the equations of the system with the Taylor series first, ignoring the higher order terms of the second order and above, when the nonlinear system is close to the linear form, then it uses standard Kalman filter algorithms to measure the situation of the system. which can not only detect moving objects accurately but also has better real-time performance and can be employed to predict the trajectory of moving objects. Meanwhile, the accuracy and real-time performance of the algorithm were experimentally verified.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.1-10
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• 2024

In the era of big data, the growth of e-commerce transactions brings forth both opportunities and risks, including the threat of data theft and fraud. To address these challenges, an automated real-time fraud detection system leveraging machine learning was developed. Four algorithms (Decision Tree, Naïve Bayes, XGBoost, and Neural Network) underwent comparison using a dataset from a clothing website that encompassed both legitimate and fraudulent transactions. The dataset exhibited an imbalance, with 9.3% representing fraud and 90.07% legitimate transactions. Performance evaluation metrics, including Recall, Precision, F1 Score, and AUC ROC, were employed to assess the effectiveness of each algorithm. XGBoost emerged as the top-performing model, achieving an impressive accuracy score of 95.85%. The proposed system proves to be a robust defense mechanism against fraudulent activities in e-commerce, thereby enhancing security and instilling trust in online transactions.

• Journal of Food Hygiene and Safety
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• v.34 no.3
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• pp.277-282
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• 2019

The object of this study is to compare the performance of the 3M Molecular Detection Assay 2 (3M MDA 2) and the Korea Standard Food Codex (KSFC) Method (i.e., isolation media and real-time PCR) in detecting Salmonella Typhimurium and Listeria monocytogenes in traditional Korean foods. Yuk-hwe and Yuk-sashimi (types of raw beef dishes) were artificially inoculated with $10^0-10^4CFU/25g$ of L. monocytogenes and S. Typhimurium. Citrobacter freundii and Listeria innocua were used as competitive microflora. After enrichment, the samples were analyzed using 3M MDA 2 and real-time PCR. All samples inoculated at concentrations of $10^0-10^4CFU/25g$ without competitive microflora were positive for S. Typhimurium and L. monocytogenes, as detected by 3M MDA 2 and Korea Standard Food Codex (KFSC) Method. In addition, part of the samples were positive for the presence of C. freundii and L. innocua. The 3M MDA 2 - Salmonella and Korea Standard Food Codex (KFSC) Method showed similar detection performances in Yuk-hwe and Yuk-sashimi. The 3M MDA 2 method for Salmonella and Listeria, which is a LAMP-based technology, can be used for rapid detection of S. Typhimurium and L. monocytogenes in raw beef. LAMP bioluminescence assays provide results on the subsequent day and are simple to use compared with the Korea Standard Food Codex (KFSC) Method, particularly in terms of DNA preparation.

• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.19-26
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• 2010

This paper proposes a classifier based on rectangular feature to detect face in real time. The goal is to realize a strong detection algorithm which satisfies both efficiency in calculation and detection performance. The proposed algorithm consists of the following three stages: Feature creation, classifier study and real time facial domain detection. Feature creation organizes a feature set with the proposed five rectangular features and calculates the feature values efficiently by using SAT (Summed-Area Tables). Classifier learning creates classifiers hierarchically by using the AdaBoost algorithm. In addition, it gets excellent detection performance by applying important face patterns repeatedly at the next level. Real time facial domain detection finds facial domains rapidly and efficiently through the classifier based on the rectangular feature that was created. Also, the recognition rate was improved by using the domain which detected a face domain as the input image and by using PCA and KNN algorithms and a Class to Class rather than the existing Point to Point technique.