• Title/Summary/Keyword: Cut-off Classification

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Size Classification of Airborne Nanoparticles Using Electrically Tunable Virtual Impactor (전기적으로 분류 입경의 제어가 가능한 가상 임팩터을 이용한 대기 중 나노 입자의 분류)

  • Kwon, Soon-Myung;Kim, Yong-Ho;Park, Dong-Ho;Hwang, Jung-Ho;Kim, Yong-Jun
    • Journal of the Korean Society for Precision Engineering
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    • v.26 no.2
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    • pp.118-125
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    • 2009
  • This paper reports the size classification of nanoparticles as well as electrical tuning techniques for the cut-off diameter and collection efficiency. Classifying particles < 100 nm in diameter is quite a technical challenge using a virtual impactor with the cut-off diameter being determined geometrically. However, the proposed virtual impactor can classify particles <100 nm and tune the cut-off diameter by electrically accelerating the particles. The cut-off diameter of the proposed device was tuned from 15 to 50nm.

Differential Diagnosis of Benign and Malignant Thyroid Nodules Using the K-TIRADS Scoring System in Thyroid Ultrasound (갑상샘 초음파 검사에서 K-TIRADS 점수화 체계를 사용한 양성과 악성 갑상샘 결절의 감별진단)

  • An, Hyun;Im, In Cheol;Lee, Hyo-Yeong
    • Journal of the Korean Society of Radiology
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    • v.13 no.2
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    • pp.201-207
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    • 2019
  • This study has evaluated whether the method of using the combination of different risk group, according to K-TIRADS classification and K-TIRADS classification in thyroid ultrasonography is useful in a differential diagnosis of benign and malignant nodules. The subject was patients underwent thyroid ultrasonography and retrospective analysis were performed based on the results of fine needle aspiration cytology. A chi-square test was performed for the difference analysis of the score system in K-TIRADS and different risk group according to the benign and malignant of thyroid nodule. The optimized cut off value was determined by the K-TIRADS score and different risk group to predict malignant nodule through ROC curve analysis. In the differential verification result of K-TIRADS and different risk group, according to the classification of benign and malignant nodule group each showed significant difference statistically(p=.001). In the point classification according to K-TIRADS for the prediction of benign and malignant in ROC curve analysis showed AUC 0.786, Cut-off value>2(p=.001), and in the different risk group, it was decided as AUC 0.640, Cut-off value>2(p=.001). When discovering the nodule in thyroid ultrasound, it is considered that the K-TIRADAS which helps in identifying benign and malignant thyroid nodules, it is considered to be helpful in the differential diagnosis of thyroid nodules, than the classification system according to Different risk group, and when applying the classification system according to K-TIRADS, it is considered that it can reduce unnecessary fine needle aspiration cytology and could be helpful in finding the malignant nodules early.

Calculation and Regulation Proposal of Light Pollution from Road Lightings (도로조명의 빛공해 계산 및 규제안 제안)

  • Cho, Sook-Hyun;Lee, Min-Wook;Choi, Hyeon-Seok;Kim, Hoon
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.25 no.12
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    • pp.21-26
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    • 2011
  • This is a study to establish regulations against light pollution for lighting on roads. Many kinds of light pollution by luminaire on roads was calculated and analyzed by applying the classification method of luminaires(Cut-off classification of IDA-IESNA, BUG Rating Classification) and the calculation method of Upward Lighting Ratio of CIE among measures to prevent light pollution that international lighting organizations suggest. As a result of the analysis, it was found that the regulation by Cutoff of IESNA and ULR classification of CIE could be one for scattered light of light pollution compared to BUG classification but is not sufficient for the regulation of light tresspass or glare. BUG classification by each lighting zone was suggested as threshold value of the light pollution regulation considering domestic conditions.

A Study of the Validity of and Cut-Off Scores for the Korean Version of Asperger Syndrome Diagnostic Scale (한국판 아스퍼거 증후군 진단척도의 타당화 및 진단 분할점 산출)

  • Kim, Ha-Na;Shin, Min-Sup
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.22 no.2
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    • pp.81-88
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    • 2011
  • Objectives : This study examined the reliability and validity of the Korean version of Asperger Syndrome Diagnostic Scale (K-ASDS), to calculate the cut-off score in the diagnosis of Asperger syndrome. Further, we examined classification error rate when applying cut-off scores. Methods : One hundred sixty-seven children participated in this study, including 46 with Asperger syndrome, 26 with PDD or PDD NOS, 43 with ADHD, and 52 normal children. Results : An ANCOVA demonstrated no significant differences in the K-ASDS total score between the Asperger and the PDD & PDD NOS groups. However, these groups did show significantly higher scores than the ADHD and normal groups. Among the five subscales on the K-ASDS, the Asperger group obtained significantly higher scores on the language and cognition subscales than the PDD & PDD NOS groups. Two scales were found to be useful in distinguishing the Asperger group from the PDD & PDD NOS group through a discriminant analysis. According to an analysis of ROC curve, the cut-off score on the K-ASDS for the diagnosis of PDD including Asperger syndrome was 121. Conclusion : We discussed that K-ASDS has pretty limit.

Classification-Based Approach for Hybridizing Statistical and Rule-Based Machine Translation

  • Park, Eun-Jin;Kwon, Oh-Woog;Kim, Kangil;Kim, Young-Kil
    • ETRI Journal
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    • v.37 no.3
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    • pp.541-550
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    • 2015
  • In this paper, we propose a classification-based approach for hybridizing statistical machine translation and rulebased machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto-evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut-off method. In our experiments, using the aforementioned cut-off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% - a 5.0% improvement over existing methods.

Comparison of the Pediatric Balance Scale and Fullerton Advanced Balance Scale for Predicting Falls in Children With Cerebral Palsy

  • Kim, Gyoung-mo
    • Physical Therapy Korea
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    • v.23 no.4
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    • pp.63-70
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    • 2016
  • Background: The Pediatric Balance Scale (PBS) and the Fullerton Advanced Balance (FAB) scale were used to assess balance function in patients with balance problem. These multidimensional clinical balance scales provide information about potential risk factors for falls. Objects: The purpose of this study was to investigate and compare the predictive properties of the PBS and FAB scales relative to fall risk in children with cerebral palsy (CP) using a receiver operating characteristic analysis. Methods: In total, 49 children with CP (boy=21, girl=28) who were diagnosed with level 1 or 2 according to the Gross Motor Function Classification System participated in this study. The PBS and FAB were performed, and verified cut-off score, sensitivity, specificity, and the area of under the curve (AUC). Results: In this study, the PBS scale was as a predictive measure of fall risk, but the FAB was not significant in children with CP. A cut-off score of 45.5 points provided optimal sensitivity of .90 and specificity of .69 on the PBS, and a cut-off score of 21.5 points provided optimal sensitivity of .90 and specificity of .62 on the FAB. Both scales showed moderately accurate of AUC with .79 and .76, respectively. Conclusion: The PBS is a useful screening tool for predicting fall risk in children with cerebral palsy, and those who score 45.5 or lower indicate a high risk for falls and are in need of balance intervention.

Analysis of High Volume Slit Type Two-Stage Virtual Impactor for Particle Size Classification (특정크기 입자농축을 위한 대유량 슬릿형 2단 가상충돌기의 성능분석)

  • 박성호;김상수;오명도
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.15 no.1
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    • pp.285-291
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    • 1991
  • A two-stage slit type virtual impactor based on the concept of the single stage virtual impactor has been designed, fabricated, and evaluated for the purpose of concentrating the suspended particles in the air with the size range of 1.8-4.5 .mu.m and handling large flow volume. Monodisperse methylene blue particles have been generated with vibrating orifice aerosol generator (VOAG). The separation efficiency and concentration efficiency have been measured by the UV-visible absorption spectrometry. Previous study for a single stage virtual impactor were used to determine the design parameters such as 50% cut-off sizes and dimensions of the two stage virtual impactor. The separation efficiency curve and 50% cut-off Stokes number(cut-off sizes) are not sensitive to the nozzle Reynolds number, but sensitive to the ratio between the minor flow rate and the total flow rate, The measured concentration efficiency was compared with the maximum concentration efficiency determined by the separation efficiencies of the first and the second stages. The differences between the measured and the maximum concentration efficiencies result from the wall loss due to the deposited particles on the internal walls inside the impactor.

Classification accuracy measures with minimum error rate for normal mixture (정규혼합분포에서 최소오류의 분류정확도 측도)

  • Hong, C.S.;Lin, Meihua;Hong, S.W.;Kim, G.C.
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.4
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    • pp.619-630
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    • 2011
  • In order to estimate an appropriate threshold and evaluate its performance for the data mixed with two different distributions, nine kinds of well-known classification accuracy measures such as MVD, Youden's index, the closest-to- (0,1) criterion, the amended closest-to- (0,1) criterion, SSS, symmetry point, accuracy area, TA, TR are clustered into five categories on the basis of their characters. In credit evaluation study, it is assumed that the score random variable follows normal mixture distributions of the default and non-default states. For various normal mixtures, optimal cut-off points for classification measures belong to each category are obtained and type I and II error rates corresponding to these cut-off points are calculated. Then we explore the cases when these error rates are minimized. If normal mixtures might be estimated for these kinds of real data, we could make use of results of this study to select the best classification accuracy measure which has the minimum error rate.

Normative Study of the K-ARS(Korean ADHD Rating Scale) for Parents (한국어판 주의력결핍 과잉행동장애 평가척도의 부모용 규준연구)

  • Jang, Su-Jin;Suh, Dong-Su;Byun, Hee-Jung
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.18 no.1
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    • pp.38-48
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    • 2007
  • Objectives : The K-ARS (Korean ADHD Rating Scale) is one of the most important assessment tool of attention-deficit hyperactivity disorder (ADHD) in Korea. in this study, we presented detailed normative data on the K-ARS for school-aged children in Seoul metropolitan area to put it to practical use. Methods : The subjects were 2,397 students(1,223 boys and 1,174 girls, aged 6-12) from 4 elementary schools in Seoul, and one caretaker of each child completed the K-ARS for parents. Children who showed high scores of the K-ARS for parents were screened, and 2 child psychiatrists interviewed them to make a clinical diagnosis. We compared the mean scores of the K-ARS for parents between ADHD and normal group, and examined the percentage of correct classification. Results : There were some differences in score of the K-ARS for parents according to sex and age, so we presented continuous normative data with T score and subdivided cut-off points for ADHD screening. Interviews with child psychiatrists using DSM-IV criteria were performed to test diagnostic validity, and the difference in every the K-ARS for parents index between ADHD and normal group was significant(p<.001). Using 3 different cut-of points(80th, 90th, 93rd percentage), the accuracies of ADHD correct classification were 67.9, 72.2, 71.1% and all 3 canonical discriminants were significant (p<.05) between ADHD and normal group. Conclusion : The normative data and cut-off points on the K-ARS for parents are useful in screening ADHD children in Seoul metropolitan area.

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Credit Score Modelling in A Two-Phase Mathematical Programming (두 단계 수리계획 접근법에 의한 신용평점 모델)

  • Sung Chang Sup;Lee Sung Wook
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2002.05a
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    • pp.1044-1051
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    • 2002
  • This paper proposes a two-phase mathematical programming approach by considering classification gap to solve the proposed credit scoring problem so as to complement any theoretical shortcomings. Specifically, by using the linear programming (LP) approach, phase 1 is to make the associated decisions such as issuing grant of credit or denial of credit to applicants. or to seek any additional information before making the final decision. Phase 2 is to find a cut-off value, which minimizes any misclassification penalty (cost) to be incurred due to granting credit to 'bad' loan applicant or denying credit to 'good' loan applicant by using the mixed-integer programming (MIP) approach. This approach is expected to and appropriate classification scores and a cut-off value with respect to deviation and misclassification cost, respectively. Statistical discriminant analysis methods have been commonly considered to deal with classification problems for credit scoring. In recent years, much theoretical research has focused on the application of mathematical programming techniques to the discriminant problems. It has been reported that mathematical programming techniques could outperform statistical discriminant techniques in some applications, while mathematical programming techniques may suffer from some theoretical shortcomings. The performance of the proposed two-phase approach is evaluated in this paper with line data and loan applicants data, by comparing with three other approaches including Fisher's linear discriminant function, logistic regression and some other existing mathematical programming approaches, which are considered as the performance benchmarks. The evaluation results show that the proposed two-phase mathematical programming approach outperforms the aforementioned statistical approaches. In some cases, two-phase mathematical programming approach marginally outperforms both the statistical approaches and the other existing mathematical programming approaches.

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