• Journal of Sericultural and Entomological Science
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• v.13 no.1
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• pp.61-67
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• 1971

This experiment was conducted to know the effects of abnormal cocoons on the silk quality during the silk reeling process. The results obtained are summarized as follows: 1. The length, the width, the weight, the layer weight, and the layer ratio of abnormal cocoons are in every case 0.83∼4.65% less than those of normal cocoons. 2. The thickness of the abnormal cocoon layer is at)out 20.62∼22.4% less than that of the normal cocoon. 3. The sericin solubility of tile abnormal cocoon layer is about 11.75∼30% more than that of the normal cocoon layer. 4. The degumming ratio of the abnormal cocoon layer is about 6.51∼9.32% more than that of the normal cocoon layer. 5. The length of a have, the weight of a tave and percentage of raw silk yield of the abnormal cocoon are decreased 9.43%, 8.53% and 6.72% each as compared with those of the normal cocoon. 6. The percentage of reelability of abnormal cocoons is decreased 9.58％ as compared with that of normal cocoons. 7. The neatness of abnormal cocoons is 3 per cent lower than that of normal cocoons. 8. In the cleanness test of abnormal cocoons, the number of split ends i9 about 1.5∼3.8 times as much as that of normal cocoons. Especially cleanness of abnormal cocoons is 16,3 per cent lower than that of normal cocoons. 9. The number of non-reelable cocoons of abnormal cocoons is increased 1.4∼5.5 times as much as that of normal cocoons. In abnormal cocoon, the number of knot which resulted in the breaking of silk end is increased 1.9∼3.5 times as much as that in normal cocoon.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.466-470
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• 2011

This paper proposes the new method based on fuzzy logic which recognizes between normal and abnormal. The object image was the Thyroid Gland cell image that was diagnosed as normal and abnormal(two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. The nuclei were successfully diagnosed as normal and abnormal. The multiple feature parameters (pre-obtained 16 feature parameters of image data) were used to extract the features of each nucleus. As a consequence of using fuzzy logic algorithm, proposed in this paper, average recognition rate of 98.25% was obtained.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.27 no.2
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• pp.113-124
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• 2024

Purpose: Alarm symptoms (red flag signs) are crucial indications for management decisions on pediatric gastrointestinal endoscopy. We aimed to identify items in the alarm symptoms and pre-endoscopic investigations that predict abnormal endoscopy results. Methods: A retrospective descriptive study was conducted among children aged under 18 years undergoing endoscopy. The patients were classified into normal and abnormal endoscopic groups. The incidence of alarm symptoms and pre-endoscopic investigations were compared between the groups. Univariate and multivariate logistic regression analyses were performed to determine independent risk factors for abnormal endoscopy. Results: Of 148 participants, 66 were classified in the abnormal endoscopy group. Compared with the normal group, the abnormal group had a significantly higher prevalence of alarm symptoms. Moreover, hematemesis/hematochezia, anemia, low hemoglobin level, hypoalbuminemia, rising erythrocyte sedimentation rate, increased serum lipase, and blood urea nitrogen/creatinine ratio were significantly higher in the abnormal endoscopy group than in the normal group. Multivariate logistic regression analysis indicated that hematemesis/hematochezia and low hemoglobin level were independent risk factors for abnormal endoscopy. Conclusion: The alarm symptoms and pre-endoscopic investigations were evaluated using predictive factors for abnormal pediatric endoscopic findings. According to multivariate logistic regression analysis, hematemesis/hematochezia and low hemoglobin levels were independent risk factors for abnormal endoscopy.

• The Journal of Korean Obstetrics and Gynecology
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• v.24 no.1
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• pp.99-108
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• 2011

Objectives: The purpose of this study is to recognize the relation of menstrual pattern and dysmenorrhea affected by obesity of first-year female college students. Methods: From March 22th to April 2nd, 2010 we researched 251 first-year female students at OOcollege, aged 19(born after March 1991 to February 1992) by questionnaires to investigate their Body Mass Index(BMI), menstruation and dysmenorrhea. The BMI range of normal group is 18.5~25, abnormal group is over 25. Results: 1. The normal group was 227 people(90.4%) and the abnormal group(over BMI 25) was 24 people(9.6%). 2. In the mean of BMI, the normal group was $21.08{\pm}1.64$ and the abnormal group was $27.94{\pm}2.19$. 3. There was no statistical difference between the normal group and the abnormal group in menstrual cycle, menstrual amount, menstrual color and menstrual blood clot. 4. There was statistical difference between the normal group and the abnormal group in menarcheal age, menstrual duration and dysmenorrhea. 5. In the mean of VAS, the normal group was $3.68{\pm}2.45$ and the abnormal group was $3.21{\pm}2.05$, and two groups were not different statistically. Conclusion: This study showed the relation of menstrual pattern and dysmenorrhea affected by obesity. The normal group and the abnormal group were different statistically in menarcheal age, menstrual duration and dysmenorrhea. In consequence of this study, it was supposed that obesity had an effect on menstruation.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.2
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• pp.112-119
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• 2003

This paper proposes a model of SP(silent period) generation in masseter muscle by means of computer simulation. The model is based on the anatomical and physiological properties of trigeminal nervous system. In determining the SP generation pathway, evoked SPs of masseter muscle after mechanical stimulation to the chin are divided into normal and abnormal group. Normal SP is produced by the activation of mechanoreceptors in periodontal ligament. The activation of nociceptors contributes to the latter part of normal SP, abnormal extended SP is produced. As a result, the EMG signal generated by a proposed SP generation model is similar to both real EMG signal including normal SP and abnormal extended SP with TMJ patients. The result of this study have shown differences of SP generation mechanism between subjects both with and without TMJ dysfunction.

• Journal of Biomedical Engineering Research
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• v.25 no.2
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• pp.129-135
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• 2004

In the home health management system, we often face the situation to handle biological signals that are frequently measured from normal subjects. In such a case, it is necessary to decide whether the signal at a certain moment is normal or abnormal. Since ECC is one of the most frequently measured biological signals, we describe algorithms that detect QRS-complex and decide whether it is normal or abnormal. The developed QRS detection algorithm is a simplified version of the conventional algorithm providing enough performance for the proposed application. The developed classification algorithm that detects abnormal from mostly normal beats is based on QRS width, R-R interval and QRS shape parameter using Karhunen-Loeve transformation. The simplified QRS detector correctly detected about 99% of all beats in the MTT/BIH ECG database. The classification algorithm correctly classified about 96% of beats as normal or abnormal. The QRS detection and classification algorithm described in this paper could be used in home health management system.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.6
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• pp.250-261
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• 1995

In this study, a rapid compression and expansion machine(RCEM) equipped with a swirl generator was designed and developed, in order to clarify normal and abnormal combustion(knocking phenomena). This RCEM is intended to simulate combustion process in actual automotive S.I.engines, having a high reproducibility in the compression stroke. Flame propagation and autoignition processes associated with normal and abnormal combustion were captured by the high speed schlieren photography. And swirl intensity. equivalence ratio and ignition position were varied to investigate the effect of turbulence, concentration in the unburnt gas region and flame propagation length. The knock intensity, knock mass fraction and knock mass fraction after autoignition were calculated by use of history of measured cylinder pressure.

• The Journal of the Acoustical Society of Korea
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• v.40 no.4
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• pp.337-346
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• 2021

Detection of abnormal signal generally can be done by using features of normal signals as main information because of data imbalance. This paper propose an efficient method for abnormal signal detection using parallel AutoEncoder (AE) which can use features of abnormal signals as well. The proposed Parallel AE (PAE) is composed of a normal and an abnormal reconstructors having identical AE structure and train features of normal and abnormal signals, respectively. The PAE can effectively solve the imbalanced data problem by sequentially training normal and abnormal data. For further detection performance improvement, additional binary classifier can be added to the PAE. Through experiments using public acoustic data, we obtain that the proposed PAE shows Area Under Curve (AUC) improvement of minimum 22 % at the expenses of training time increased by 1.31 ~ 1.61 times to the single AE. Furthermore, the PAE shows 93 % AUC improvement in detecting abnormal underwater acoustic signal when pre-trained PAE is transferred to train open underwater acoustic data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.296-304
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• 2005

ATCoP(Abnormal traffic controller based on prediction) is presented to securely support reliable Internet service and to guarantee network survivability, which is deployed in Internet access point. ATCoP is a method to control abnormal traffic that is entering into the network When unknown attack generates excessive traffic, service survivability is guaranteed by giving the priority to normal traffic than abnormal traffic, that is reserving some channels for normal traffic. If the reserved channel number increases, abnormal traffic has lower quality service by ATCoP system and then its service survivability becomes worse. As an analytic result, the proposed scheme maintains the blocking probability of normal traffic on the predefined level in the specific interval of input traffic.

• Korean Journal of Medicinal Crop Science
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• v.21 no.4
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• pp.289-295
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• 2013

This study was carried out to investigate the cause of leaf discoloration occurring frequently in paddy cultivation. Chemical property of soil and inorganic nutrient component of leaf were analyzed on abnormal fields of 7 regions where leaf discoloration occurred severely and normal fields of 7 regions among ginseng garden. The pH of abnormal fields was strong acidic condition (pH 5.51) compare to normal fields of slightly acid condition (pH 6.42). Calcium and magnesium content in abnormal fields were lower distinctly than that of normal fields, while EC, organic matter, phosphate, and potassium content showed not distinct difference between abnormal and normal fields. Whereas calcium and magnesium content were distinctly high in normal fields, both of potassium and iron content of ginseng leaf were distinctly high in abnormal fields. In particular, iron content of abnormal fields was more 1.94 times in soil, and 3.03 times in leaf than that of normal fields. In soil chemical property, there were significant negative correlation between leaf discoloration ratio and soil pH, and there were also significant positive correlation between leaf discoloration ratio and iron content. In ginseng leaf, there were highly significant negative correlation between leaf discoloration ratio and calcium content, and there were also highly significant positive correlation between leaf discoloration ratio and iron content.