• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.915-926
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• 2020

Outlier detection methods help one to identify unusual instances in data that may correspond to erroneous, exceptional, or surprising events or behaviors. This work studies conditional outlier detection, a special instance of the outlier detection problem, in the context of incorrect data label identification. Unlike conventional (unconditional) outlier detection methods that seek abnormalities across all data attributes, conditional outlier detection assumes data are given in pairs of input (condition) and output (response or label). Accordingly, the goal of conditional outlier detection is to identify incorrect or unusual output assignments considering their input as condition. As a solution to conditional outlier detection, this paper proposes the ratio-based outlier scoring (ROS) approach and its variant. The propose solutions work by adopting conventional outlier scores and are able to apply them to identify conditional outliers in data. Experiments on synthetic and real-world image datasets are conducted to demonstrate the benefits and advantages of the proposed approaches.

• Journal of Korea Multimedia Society
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• v.19 no.5
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• pp.865-873
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• 2016

In recent years, Tracking-Learning-Detection(TLD) system has been widely used as a detection and tracking algorithm for vision sensors. While conventional algorithms are vulnerable to occlusion, and changes in illumination and appearances, TLD system is capable of robust tracking by conducting tracking, detection, and learning in real time. However, the detection and tracking algorithms of TLD system utilize rotation-variant features, and the margin of tracking error becomes greater when an object makes a full out-of-plane rotation. Thus, we propose a rotation-invariant TLD system(RI-TLD). we propose a simplified average orientation histogram and rotation matrix for a rotation inference algorithm. Experimental results with various tracking tests demonstrate the robustness and efficiency of the proposed system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.306-308
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• 2018

This paper proposes a variant malicious code detection algorithm in a mobile environment using a deep learning algorithm. In order to solve the problem of malicious code detection method based on Android, we have proved high detection rate through signature based malicious code detection method and realtime malicious file detection algorithm using machine learning method.

• The Plant Pathology Journal
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• v.33 no.1
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• pp.34-42
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• 2017

Grapevine rupestris stem pitting-associated virus (GRSPaV) is a worldwide-distributed pathogen in grapevines with a high genetic variability. Our study revealed differences in the complexity of GRSPaV population in a single host. A single-variant GRSPaV infection was detected from the SK30 grapevine plant. On the contrary, SK704 grapevine was infected by three different GRSPaV variants. Variant-specific RT-PCR detection protocols have been developed in this work to study distribution of the three different variants in the same plant during the season. This study showed their randomized distribution in the infected SK704 grapevine plant. Comparative analysis of full-length genome sequences of four Slovak GRSPaV isolates determined in this work and 14 database sequences showed that population of the virus cluster into four major phylogenetic lineages. Moreover, our analyses suggest that genetic recombination along with point mutations could play a significant role in shaping evolutionary history of GRSPaV and contributed to its extant genetic diversification.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.6
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• pp.679-689
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• 2014

In this paper, an analysis of the effect of time-variant reflected impedance and its detection method on wireless power transfer(WPT) systems are presented. The reflected resistance at WPT systems is very important parameter as it indicates how well matched antenna is and will exhibit high efficiency. Proposed detection method is based on transmitter current variation analysis with respect to frequency sweep. Using the proposed design method, a wireless power transfer system operating at the frequency of 125 kHz, is design and detect reflected impedance variation. The proposed design method provides good agreements between measured and simulated results. Therefore, The proposed detecting method provides a nonintrusive method to detect harmful object in WPT system.

• Journal of Genetic Medicine
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• v.17 no.1
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• pp.27-33
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• 2020

Purpose: Duchenne muscular dystrophy (DMD) is the most common lethal muscular dystrophy and is caused by the genetic variants of DMD gene. Because DMD is X-linked recessive and shows familial aggregates, prenatal diagnosis is an important role in the management of DMD family. We present our experience of prenatal molecular diagnosis and carrier detection based on multiplex polymerase chain reaction (PCR), multiplex ligation-dependent probe amplification (MLPA), and linkage analysis. Materials and Methods: During study period, 34 cases of prenatal diagnosis and 21 cases of carrier detection were performed at the Seoul National University Hospital. Multiplex PCR and MLPA was used to detect the exon deletions or duplications. When the DMD pathogenic variant in the affected males is unknown and no DMD pathogenic variant is detected in atrisk females, linkage analysis was used. Results: The prenatal molecular diagnosis was offered to 34 fetuses. Twenty-five fetuses were male and 6 fetuses (24.0%) were affected. Remaining cases had no pathogenic mutation. We had 24 (80.0%) cases of known proband results; exon deletion mutation in 19 (79.2%) cases and duplication in 5 (20.8%) cases. Linkage analysis was performed in 4 cases in which 2 cases (50.0%) were found to be affected. In the carrier testing, among 21 cases including 15 cases of mother and 6 cases of female relative, 9 (42.9%) cases showed positive results and 12 (57.1%) cases showed negative results. Conclusion: Prenatal molecular diagnosis and carrier detection of DMD are effective and feasible. They are useful in genetic counseling for DMD families.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.45-52
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• 2021

Although many studies have been conducted to identify unknown attacks in cyber security intrusion detection systems, studies based on outliers are attracting attention. Accordingly, we identify outliers by defining categories for unknown attacks. The unknown attacks were investigated in two categories: first, there are factors that generate variant attacks, and second, studies that classify them into new types. We have conducted outlier studies that can identify similar data, such as variants, in the category of studies that generate variant attacks. The big problem of identifying anomalies in the intrusion detection system is that normal and aggressive behavior share the same space. For this, we applied a technique that can be divided into clear types for normal and attack by discrete wavelet transformation and detected anomalies. As a result, we confirmed that the outliers can be identified through One-Class SVM in the data reconstructed by discrete wavelet transform.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.133-141
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• 2023

This work take deeper analysis of Adaptive Moment Estimation (Adam) and Adam with Weight Decay (AdamW) implementation in real world text classification problem (DGA Malware Detection). AdamW is introduced by decoupling weight decay from L2 regularization and implemented as improved optimizer. This work introduces a novel implementation of AdamW variant as AdamW+ by further simplifying weight decay implementation in AdamW. DGA malware detection LSTM models results for Adam, AdamW and AdamW+ are evaluated on various DGA families/ groups as multiclass text classification. Proposed AdamW+ optimizer results has shown improvement in all standard performance metrics over Adam and AdamW. Analysis of outcome has shown that novel optimizer has outperformed both Adam and AdamW text classification based problems.

• Journal of Microbiology
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• v.34 no.3
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• pp.236-240
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• 1996

Rifampin is the most powerful drug for treating leprosy and tuberculosis today. It inhibits initiation and elongation of RNA transcription by binding to $\beta$-subunit of RNA polymerase, leading to kill mycobacteria. We isolated one variant strain of Mycobacterium leprae from 24 Korean leprosy patients who are less susceptible to rifampin or have suffered from relapse by polymerase chain reaction and single strand conformation polymorphism (PCR-SSCP) of the rpoB gene. Direct sequencing of the rpoB region of M. leprae variant revealed missense mutations which altered the amino acids sequenceof RpoB to Ser-464, Arg-465, Arg-467 and Ala-468. This is the first finding on rpoB gene mutation of M. leprae from Korean patients ; moreover the mutant type was found to be different from the previously reported cases in other countries.