• Journal of Yeungnam Medical Science
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• v.5 no.2
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• pp.47-52
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• 1988

The intradermal(ID) test has been widely used in Korea and several reports about the results of the ID test are known. We examined the egg of Clonorchis sinensis(C. s.) by ID test in 443, stool's egg-counting technique in 79 and direct smear(cellophane thick smear technique) in 1304 subjects. The results are as follows.: 1. The positive rate of C. s. was 3.8% out of 1304 persons. 2. The sensitivity of ID test was 82.1% out of 39 persons and, the specificity was 64.6% out of 404 persons. 3. The false positive of ID test 35.4% out of 404 persons and, the false negative was 17.9% out of 39 persons. Intradermal test is a rapid, sensitive and useful supplementary diagnostic tool for the detection of Clonorchiasis infection and must be used as screening test with direct smear of stool but cross reaction with other helminth infections and moderate false reaction are the main disadvantages in its practical application.

• Journal of Dairy Science and Biotechnology
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• v.39 no.1
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• pp.9-19
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• 2021

Enterobacter sakazakii (Cronobacter spp.) causes meningitis, necrotizing enterocolitis, sepsis, and bacteremia in neonates and children and has a high mortality rate. For rapid E. sakazakii detection, various differential and selective media containing α-glucosidase substrates, such as 5-bromo-4-chloro-3-indolyl-α-D-glucopyranoside (BCIG) or 4-methylumbelliferyl-α-D-glucoside (α-MUG), have been developed as only E. sakazakii exhibits α-glucosidase activity in the genus Enterobacter. However, Escherichia vulneris (family: Enterobacteriaceae) can also utilize α-glucosidase substrates, thereby resulting in false positives. Various iron sources are known to promote the growth of gram-negative bacteria. This study aimed to develop a selective medium containing α-glucosidase substrates for E. sakazakii detection that would eliminate false positives, such as those of E. vulneris, and to determine the role of iron source in the medium. Three previously developed (TPD) media, i.e., Oxoid, OK, and VRBG, and the medium developed in this study, i.e., NGTE, were evaluated using 58 E. sakazakii and 5 non-E. sakazakii strains. Fifty-four E. sakazakii strains appeared as fluorescent or chromogenic colonies on all four media that were assessed. Two strains showed colonies on NGTE medium and not on TPD media. In contrast, the remaining two strains showed colonies on TPD media and not on NGTE medium. None of the non-E. sakazakii strains showed fluorescent or chromogenic colonies on any of the evaluated media except E. vulneris, which showed colonies on TPD media and not on NGTE medium. This study demonstrated that the newly developed NGTE medium was not only equally efficient in promoting the growth of bacterial colonies when compared with the currently available media but also eliminated false positives, such as E. vulneris.

• Korean Journal of Veterinary Research
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• v.24 no.1
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• pp.91-98
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• 1984

A total of 466 foremilk from dairy farms in Chonnam district was examined for the subclinical mastitis over a period of one year, using a method of the electrical conductivities(EC); absolute conductivity(AC) and differential conductivity(DC) and quarter difference value(QD), in relation to the California mastitis test(CMT) and the direct somatic cell count(DSCC). The compatibility and efficiency rating between the EC values and the other screening tests was conducted. Obtained results are summarized as follows. 1. A linear relationship was found between the EC values and the CMT scores and direct somatic cell counts and it was found that electrical conductivity measurements were comparable with other screening tests for diagnosing animals with mastitis. 2. Compatibilities between the EC and CMT were 70.4% in AC, 74.6% in DC and 70.7% in QD, and that of the EC and DSCC were 53.0% in AC, 63.1% in DC and 53.2% in QD. On the other hand, relative efficiency ratings of Postle's equation between EC and CMT were 37.3% in AC, 26.5% in DC and 13.6% in QD, and that of the EC and DSCC were 33.1% in AC, 20.2% in DC and 11.9% in QD. 3. In the foremilk samples collected from damaged quarters determined by EC, the false positive rate wart higher than the false negative rate, and consequently tests of EC produced lower compatibility or efficiency rating scores. These tendencies suggested that any factors other than the mastitic condition influencing the EC values might be existed.

• Journal of The Korean Society of Inherited Metabolic disease
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• v.14 no.2
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• pp.150-155
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• 2014

The measurement of $17{\alpha}$-hydroxyprogesterone ($17{\alpha}$-OHP) in a dried blood spot on filter paper is an important for screening of congenital adrenal hyperplasia (CAH). Since high levels of $17{\alpha}$-OHP are frequently observed in premature infants without congenital adrenal hyperplasia, we evaluated cuts-off based on birth weight and performed validation. Birth weight and $17{\alpha}$-OHP concentration data of 292,204 newborn screening subjects in Greencross labopratories were analyzed. The cut-off values based on birth weight were newly evaluated and validated with the original data. The mean $17{\alpha}$-OHP concentration were 7.25 ng/mL in very low birth weight (VLBW) group, 4.02 ng/mL in low birth weight (LBW) group, 2.53 g/mL in normal birth weight (NBW) group, and 2.24 ng/mL in heavy birth weight (HBW) group. The cut-offs for CAH were decided as follows: 21.12 ng/mL for VLBW and LBW groups and 11.14 ng/mL for NBW and HBW groups. When applied new cut-offs for original data, positive rates in VLBW and LBW groups were decreased and positive rates in NBW and HBW groups were increased. The cut-offs based on birth weight should be used in the screening for CAH. We believe that our new cut-off reduce the false positive rate and false negative rate and our experience for cut-off set up and validation will be helpful for other laboratories doing newborn screening test.

• Korean Journal of Head & Neck Oncology
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• v.10 no.2
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• pp.91-101
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• 1994

Nodular thyroid disease is a common clinical problem. The problem in clinical practice is to distinguish malignant or potentially malignant tumor from harmless nodules. The cases of thyroid nodule surgically managed at Department of General Surgery, Soon Chun Hyang Univ. Hospital during the period Jan. 1985 to July. 1992 were reviewed retrospectively. To assess method of distinguishing malignant from benign lesions of the thyroid gland, we reviewed 162 patients with thyroid nodule. There were 61(37.7%) malignant nodules and 101(62.3%) benign nodules. According to the review, distinguishing the benign from the malignant nodule with history, physical examination, clinical manifestation, and duration of illness was not suggested sufficiently. In ultrasonogram of 73 cases, 57.5% of nodules were solid, 20.6% were cystic, 21.9% were mixed solid and cystic. Of these, 28.5% of the operated solid lesions, 12.5% of the mixed lesions, and only 6.7% of the cystic lesions were malignant. Thyroid scanning of 82 cases revealed cold nodules in 60 patients(73.2%), of which 26 cases were malignant(36.6%) 137 patients underwent fine needle aspiration cytology(FNAC), and these results were as follow: sensitiviey was 70.6%, specificity was 93.0%, false-positive rate was 14.3%, and false-negative rate was 15.8%. 41 patients underwent frozen biopsy, and the results as follow: sensitivity was 80.0%, specificity was 89.7%. Neither scintigraphy nor ultrasonogram has sufficient specificity to distinguish benign from malignant nodule. But FNAC and frozen biopsy have sufficient accuracy to differentiate benign from malignant nodule. In the benign nodules, the most common type of operation was total lobectomy (60.4%). Of the malignant nodules, total thyroidectomy with or without modified radical neck dissection was performed in 30 cases(49.2%). We conclude that the single technique used to determine the differential diagnosis of a thyroid nodule are unrealiable. It is therefore essential to combine all avaiable clinical and laboratory information.

• Journal of Ecology and Environment
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• v.41 no.12
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• pp.345-350
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• 2017

Background: Ecological research often requires monitoring of a specific individual over an extended period of time. To enable non-invasive re-identification, consistent external marking is required. Treefrogs possess lateral lines for crypticity. While these patterns decrease predator detection, they also are individual specific patterns. In this study, we tested the use of lateral lines in captive and wild populations of Dryophytes japonicus as natural markers for individual identification. For the purpose of the study, the results of visual and software assisted identifications were compared. Results: In normalized laboratory conditions, a visual individual identification method resulted in a 0.00 rate of false-negative identification (RFNI) and a 0.0068 rate of false-positive identification (RFPI), whereas Wild-ID resulted in RFNI = 0.25 and RFNI = 0.00. In the wild, female and male data sets were tested. For both data sets, visual identification resulted in RFNI and RFPI of 0.00, whereas the RFNI was 1.0 and RFPI was 0.00 with Wild-ID. Wild-ID did not perform as well as visual identification methods and had low scores for matching photographs. The matching scores were significantly correlated with the continuity of the type of camera used in the field. Conclusions: We provide clear methodological guidelines for photographic identification of D. japonicus using their lateral lines. We also recommend the use of Wild-ID as a supplemental tool rather the principal identification method when analyzing large datasets.

• Convergence Security Journal
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• v.18 no.5_1
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• pp.45-51
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• 2018

As data utilization and importance becomes important, data-related accidents and damages are gradually increasing. Especially, insider threats are the most harmful threats. And these insider threats are difficult to detect by traditional security systems, so rule-based abnormal behavior detection method has been widely used. However, it has a lack of adapting flexibly to changes in new attacks and new environments. Therefore, in this paper, we propose an adaptive anomaly movement detection framework based on a statistical Markov model to detect insider threats in advance. This is designed to minimize false positive rate and false negative rate by adopting environment factors that directly influence the behavior, and learning data based on statistical Markov model. In the experimentation, the framework shows good performance with a high F2-score of 0.92 and suspicious behavior detection, which seen as a normal behavior usually. It is also extendable to detect various types of suspicious activities by applying multiple modeling algorithms based on statistical learning and environment factors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.1
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• pp.37-46
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• 1998

The purpose of this study was to evaluate the diagnostic performance of the senior dental students for the proximal dental caries on intraoral radiographs and to compare it with the dental hospital residents, the reference group. It was also investigated the diagnostic performance according to the carious lesion depth. Thirty-five intraoral periapical and bitewing radiographs with 213 proximal surfaces included in this study were selected from the dental patients at Chonnam National University Hospital. The observers were 181 senior dental students from 5 dental schools and 40 dentists who were second year resident from 5 dental hospitals. They were asked to evaluate the presence or the absence of the proximal dental caries. The results were as follows: 1. The mean of the hitting rate for the overall observers was 184.51 surfaces and the diagnostic accuracy was 86.62％. 2. The diagnostic performance of the sound proximal tooth surfaces was very high, i.e., 91.5％ true negative rate and 8.5％ false positive rate. 3. The diagnostic performance of the dentist group was higher than the student group(P<0.05). 4. The proximal dental caries perceptibility increased as the lesion depth increased significantly(P<0.001) except no difference between the carious lesion depth III and IV (P>0.001).

• ETRI Journal
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• v.39 no.5
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• pp.621-631
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• 2017

Abnormal samples are usually difficult to obtain in production systems, resulting in imbalanced training sample sets. Namely, the number of positive samples is far less than the number of negative samples. Traditional Support Vector Machine (SVM)-based anomaly detection algorithms perform poorly for highly imbalanced datasets: the learned classification hyperplane skews toward the positive samples, resulting in a high false-negative rate. This article proposes a new imbalanced SVM (termed ImSVM)-based anomaly detection algorithm, which assigns a different weight for each positive support vector in the decision function. ImSVM adjusts the learned classification hyperplane to make the decision function achieve a maximum GMean measure value on the dataset. The above problem is converted into an unconstrained optimization problem to search the optimal weight vector. Experiments are carried out on both Cloud datasets and Knowledge Discovery and Data Mining datasets to evaluate ImSVM. Highly imbalanced training sample sets are constructed. The experimental results show that ImSVM outperforms over-sampling techniques and several existing imbalanced SVM-based techniques.