• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1244-1244
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from mastitic and healthy cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from mastitic and healthy cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA and FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference, thereby providing a useful means for spectroscopy-based clinic applications.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• The Journal of Korean Academy of Prosthodontics
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• v.55 no.2
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• pp.198-204
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• 2017

Maxillofacial defect comes from congenital defect, trauma and surgical resection. Patients with intraoral defect are commonly related to maxillary defect and they need prosthetic rehabilitation. Functional reconstruction of partially edentulous mandible has many limitations. However, if both condyles are intact, maxillofacial prosthesis using partial denture give competent results. In this case, a patient of 58 year-old male has a defect on palate and left mandibular posterior teeth from gunshot. The maxillary defect of this patient is Class IV according to Aramany classification and the mandibular one is Type V according to Cantor and Curtis classification. For retention of the obturator, remaining teeth are fully utilized and artificial teeth are arranged harmoniously to provide stable occlusion. Mandibular RPD covered limited range of deformed soft tissue derived from mandibular resection surgery. With these treatments, the patient in this case showed improvements in mastication, swallowing and speech.

• Advances in pediatric surgery
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• v.12 no.2
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• pp.137-146
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• 2006

Pediatric surgery could establish a definitive position in the medical field on the basis of a stable patient population. Neonatal surgery, the core of pediatric surgery, requires highly skilled surgeons. However, recent advancement of prenatal diagnosis followed by intervention and decreased birth rate has resulted in a significant decrease in the neonatal surgical population and the number of surgical operations. The purpose of this study is to examine the outcome of neonatal surgeries and to propose a guide for the future surgeries. A total of 359 neonatal surgical patients operated upon at the Department of Surgery, Ewha Medical Center, during past 21 years were studied. The study period hasbeen divided into two time periods: from 1983 to 1993 and from 1994 to 2004. Analysis was based on the Clinical Classification System and mortality pattern, frequency of disorders, occurrence and cause of death, and other changes. Neonatal surgery was 6.4 % of all pediatric surgery during the total 21 year period, 9.9 % in the first period and 4.8 % in the second. Male to female ratio increased from 2.7:1 to 2.1:1. The overall mortality was 6.7 %, and there was significant decrease from 7.4 % in the first period to 6.0 % in the second. The clinical classification system (CCS) for death cases included class II 2, III 4, and IV 7 during the first period and class III 3, and IV 8 during the second, respectively. According to the mortality pattern by Hazebroek, there were 6 preventable death cases during the first period, and only one in the second, and 2 non-preventable death cases during the first period and 8 in second, respectively. Although the patients in the second period had more serious diseases, surgical mortality has been decreased in the second period, which may be the result of improved surgery methods for newborns and advanced patient care.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.112-122
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• 2022

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two new orthodontists in order to compare their diagnosis to the artificial intelligence (AI) model's performance using weighted kappa and Cohen's kappa statistical analyses. Results: The model's validation and test accuracy for the six-class CVM diagnosis were 62.63% and 61.62%, respectively. Moreover, the model's validation and test accuracy for the three-class classification were 75.76% and 82.83%, respectively. Furthermore, substantial agreements were observed between the two orthodontists as well as one of them and the AI model. Conclusions: The newly developed AI model had reasonable accuracy in detecting the CVM stage and high reliability in detecting the pubertal stage. However, its accuracy was still less than that of human observers. With further improvements in data quality, this model should be able to provide practical assistance to practicing dentists in the future.

• Childhood Kidney Diseases
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• v.7 no.2
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• pp.150-156
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• 2003

Purpose : Efforts to predict the clinicopathological outcome of IgA nephropathy have been made but have yielded conflicting results and have not helped in deciding the appropriate timing of the renal biopsy. In this study, we reviewed the predictive factors of clinicopathological outcome for finding out the criteria of renal biopsy timing of IgA nephropathy. Methods : Forty children diagnosed with biopsy proven IgA nephropathy at Wonju Christian Hospital were studied retrospectively, based on medical records. Results : Among 39 patients, 2 children progressed to higher serum creatinine level. One of them reached to the end stage renal disease within 2 year 7 months. According to WHO histopathological classification, there were 15 cases of class I, 14 cases of class II, 7 cases of class III, and 3 cases of class IV. In the mild histological classes(class I, II), gross hematuria was shown in 23 out of 29 children(P=0.02). In the severe histological classes(class III, IV), gross hematuria was noted in 4 out of 10(P>0.05). The tubulointerstitial changes were grade 1 in 24 cases, grade 2 in 4 cases, grade 3 in 8 cases, and grade 4 in 3 cases. With an increase in the tubulointerstitial grade, the 24 hour urine protein/albumin ratio increased. Serum creatinine less than 0.79 mg/dL could predict the lower grade(grade 1 and 2) of tubulointerstitial changes. But serum creatinine greater than 1.13 mg/dL could predict the higher grade(grade 3 and 4) of tubulointerstitial changes. In children with gross hematuria(n=27), serum creatinine was lower(0.78 vs 1.09 mg/dL, P=0.027), serum IgA was higher(316.3 vs 198.8 mg/dL), and the cases of lower WHO classification(I and II) were more common(23 vs 4, P=0.029) than the children with microscopic hematuria. Conclusion : Serum creatinine less than 0.79 mg/dL, macroscopic hematuria, and higher 24 hour urine protein/albumin ratio would predict the lower grade glomerulo tubulointerstitial lesion in IgA nephropathy and could be used as the criteria delaying the renal biopsy.

• The korean journal of orthodontics
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• v.23 no.4 s.43
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• pp.633-644
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• 1993

There has been so much controversies about the position of upper and lower jaws, and their first permanent molars in normal occlusion and Angle's class $I{\cdot}II{\cdot}III$ malocclusions. So, the purpose of this study is to compare the position of upper and lower jaws, and their first molars in normal occlusion and Angle's class $I{\cdot}II{\cdot}III$ malocclusions by lateral cephalometric analysis. The sample consisted of one hundred and twenty girls(thirty in each group) who had completed growth. The findings of this study were as follows : 1. In class I malocclusion, both maxilla and mandible were slightly posterior position than normal occlusion, but they showed harmonious relationship. 2. In class II malocclusion, the mandible was greatly retruded, and the maxilla was also slightly retruded to the cranial base as compared with normal occlusion. 3. In class III malocclusion, the maxilla was significantly retruded to the cranial base, but no significant difference was found in mandibular position as compared with normal occlusion. 4. The maxillary first molar was located at posterior position in class II malocclusion, and anterior position in class III malocclusion to the cranium, so that the rotation of mandible was influenced by that. 5. The mandibular first molar showed constant relationship to the mandible in all four groups, but different position to the cranial base in direct proportion to the mandibular position. 6. On the treatment planning of class III malocclusion, it seems to be better to promote the mandibular horizontal growth by inhibiting the vertical growth of maxillary molar area, and on the treatment planning of class III malocclusion, it seems to be better to promote the antero-inferior growth of maxilla mi to promote the mandibular vertical growth by inducing the vertical growth of maxillary molar area.

• The Korea Journal of Herbology
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• v.32 no.4
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• pp.33-38
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• 2017

Objectives : Termitomyces albuminosus (Berk.) Heim is one of the famous wild edible mushrooms in the southern part of China. It is known that Termitomyces albuminosus, like Aconitum koreanum used in Korean traditional medicine, contains a kind of cerebroside, termitomycesphin, causing a pharmacologic effect on the neuron system. The pharmacologic effect of Termitomyces albuminosus can be used to possibly replace Aconitum koreanum. However, It needs to be certified as safe before it can be used. Here, a single-oral toxicity test and safety classification was conducted to obtain acute information of the toxicity of dried-Termitomyces albuminosus powder and to secure its safety in clinical applications. Methods : In order to calculate approximate lethal dose(ALD), test substance was orally administered to male and female SD-rat at dose levels of 5,000 and 0 (vehicle control) mg/kg (body weight). Based on the result of this toxicity, also the estimation of safety classification was calculated using the HED-based (human equivalent dose) MOS (margin of safety). Results : There were no mortalities, test substances treatment-related clinical signs, no changes in the body or organ weights, and no gross or histopathological findings at 14 days after treatment with test substance. Thus, the approximate lethal dose of dried-Termitomyces albuminosus powder was considered over 5,000 mg/kg in both female and male mice. Conclusions : Based on the limit dose, 5000 mg/kg, it was estimated that dried-Termitomyces albuminosus powder is classified as "Specified class B" indicating that clinical dose is not limited to patients as safe as food.

• Journal of Species Research
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• v.8 no.2
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• pp.197-214
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• 2019

The taxonomic hierarchy of the phylum Proteobacteria was assessed, after which the isolation and classification state of Proteobacteria species with valid names for Korean indigenous isolates were studied. The hierarchical taxonomic system of the phylum Proteobacteria began in 1809 when the genus Polyangium was first reported and has been generally adopted from 2001 based on the road map of Bergey's Manual of Systematic Bacteriology. Until February 2018, the phylum Proteobacteria consisted of eight classes, 44 orders, 120 families, and more than 1,000 genera. Proteobacteria species isolated from various environments in Korea have been reported since 1999, and 644 species have been approved as of February 2018. In this study, all novel Proteobacteria species from Korean environments were affiliated with four classes, 25 orders, 65 families, and 261 genera. A total of 304 species belonged to the class Alphaproteobacteria, 257 species to the class Gammaproteobacteria, 82 species to the class Betaproteobacteria, and one species to the class Epsilonproteobacteria. The predominant orders were Rhodobacterales, Sphingomonadales, Burkholderiales, Lysobacterales and Alteromonadales. The most diverse and greatest number of novel Proteobacteria species were isolated from marine environments. Proteobacteria species were isolated from the whole territory of Korea, with especially large numbers from the regions of Chungnam/Daejeon, Gyeonggi/Seoul/Incheon, and Jeonnam/Gwangju. Most Halomonadaceae species isolated from Korean fermented foods and solar salterns were halophilic or halotolerant. Air-borne members of the genera Microvirga, Methylobacterium, and Massilia had common characteristics in terms of G+C content, major respiratory quinones, and major polar lipids.

• The korean journal of orthodontics
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• v.52 no.2
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• pp.85-101
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• 2022

Objective: To classify facial asymmetry (FA) phenotypes in adult patients with skeletal Class III (C-III) malocclusion. Methods: A total of 120 C-III patients who underwent orthognathic surgery (OGS) and whose three-dimensional computed tomography images were taken one month prior to OGS were evaluated. Thirty hard tissue landmarks were identified. After measurement of 22 variables, including cant (°, mm), shift (mm), and yaw (°) of the maxilla, maxillary dentition (Max-dent), mandibular dentition, mandible, and mandibular border (Man-border) and differences in the frontal ramus angle (FRA, °) and ramus height (RH, mm), K-means cluster analysis was conducted using three variables (cant in the Max-dent [mm] and shift [mm] and yaw [°] in the Manborder). Statistical analyses were conducted to characterize the differences in the FA variables among the clusters. Results: The FA phenotypes were classified into five types: 1) non-asymmetry type (35.8%); 2) maxillary-cant type (14.2%; severe cant of the Max-dent, mild shift of the Man-border); 3) mandibular-shift and yaw type (16.7%; moderate shift and yaw of the Man-border, mild RH-difference); 4) complex type (9.2%; severe cant of the Max-dent, moderate cant, severe shift, and severe yaw of the Man-border, moderate differences in FRA and RH); and 5) maxillary reverse-cant type (24.2%; reverse-cant of the Max-dent). Strategic decompensation by pre-surgical orthodontic treatment and considerations for OGS planning were proposed according to the FA phenotypes. Conclusions: This FA phenotype classification may be an effective tool for differential diagnosis and surgical planning for Class III patients with FA.