• Title/Summary/Keyword: modified regression model

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The Study of Classification Body Types of Adults Women and Drawing of Prototype of Clothing (성인여성의 의복 원형 개발에 관한 연구 -성인여성의 체형 분류에 관한 연구의 후속 연구-)

  • 손혜순;손혜정
    • The Research Journal of the Costume Culture
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    • v.5 no.4
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    • pp.130-158
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    • 1997
  • This study outputs calculation of regression of each items for production of torso basic pattern according to 6 body types as the result of another study and intends to present drawing method of torso model by short measure method modified and supplied and supplied by experiments of wearing clothing. SAS(Statistical Analysis System) is used for figures management and methods for analysis used are Frequency Analysis, Means Analysis, Regression Analysis, Correlation Analysis, etc. Results are as follows. 1. Correlation analysis is used to output the size necessary for torso prototype drawing by sort measure method and waist front length, back length, crotch length, shoulder point-cerricale-shoulder point, bust circumference, waist circumference, weight, etc, are set up as representative items calculation of regression of each type is suggested. 2. In the result of experiment of the first wearing clothing intended for 5 in each type and the whole 30, to develop torso prototype drawing method by short measure method, as we find some problems of the shape and propriety of neck root circumference line, the position of shoulder point, pulling or hold armpit parts, waist circumference line, the degree of dissatisfaction is high, so the second experiment of wearing clothing is propriety of each part is improved, all items except the length and quantity of shoulder dart, waist in back bodice, clearance quantity of hip circumference, and the place of shoulder line in side bodice. So, it was modifed and supplied and then the third torso prototyped drawing method by shout measure method was suggested. The third prototype drawing method was suggested, by modifying and supplying.

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MP-Lasso chart: a multi-level polar chart for visualizing group Lasso analysis of genomic data

  • Min Song;Minhyuk Lee;Taesung Park;Mira Park
    • Genomics & Informatics
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    • v.20 no.4
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    • pp.48.1-48.7
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    • 2022
  • Penalized regression has been widely used in genome-wide association studies for joint analyses to find genetic associations. Among penalized regression models, the least absolute shrinkage and selection operator (Lasso) method effectively removes some coefficients from the model by shrinking them to zero. To handle group structures, such as genes and pathways, several modified Lasso penalties have been proposed, including group Lasso and sparse group Lasso. Group Lasso ensures sparsity at the level of pre-defined groups, eliminating unimportant groups. Sparse group Lasso performs group selection as in group Lasso, but also performs individual selection as in Lasso. While these sparse methods are useful in high-dimensional genetic studies, interpreting the results with many groups and coefficients is not straightforward. Lasso's results are often expressed as trace plots of regression coefficients. However, few studies have explored the systematic visualization of group information. In this study, we propose a multi-level polar Lasso (MP-Lasso) chart, which can effectively represent the results from group Lasso and sparse group Lasso analyses. An R package to draw MP-Lasso charts was developed. Through a real-world genetic data application, we demonstrated that our MP-Lasso chart package effectively visualizes the results of Lasso, group Lasso, and sparse group Lasso.

Predicting Mortality in Patients with Tuberculous Destroyed Lung Receiving Mechanical Ventilation

  • Kim, Won-Young;Kim, Mi-Hyun;Jo, Eun-Jung;Eom, Jung Seop;Mok, Jeongha;Kim, Ki Uk;Park, Hye-Kyung;Lee, Min Ki;Lee, Kwangha
    • Tuberculosis and Respiratory Diseases
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    • v.81 no.3
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    • pp.247-255
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    • 2018
  • Background: Patients with acute respiratory failure secondary to tuberculous destroyed lung (TDL) have a poor prognosis. The aim of the present retrospective study was to develop a mortality prediction model for TDL patients who require mechanical ventilation. Methods: Data from consecutive TDL patients who had received mechanical ventilation at a single university-affiliated tertiary care hospital in Korea were reviewed. Binary logistic regression was used to identify factors predicting intensive care unit (ICU) mortality. A TDL on mechanical Ventilation (TDL-Vent) score was calculated by assigning points to variables according to ${\beta}$ coefficient values. Results: Data from 125 patients were reviewed. A total of 36 patients (29%) died during ICU admission. On the basis of multivariate analysis, the following factors were included in the TDL-Vent score: age ${\geq}65$ years, vasopressor use, and arterial partial pressure of oxygen/fraction of inspired oxygen ratio <180. In a second regression model, a modified score was then calculated by adding brain natriuretic peptide. For TDL-Vent scores 0 to 3, the 60-day mortality rates were 11%, 27%, 30%, and 77%, respectively (p<0.001). For modified TDL-Vent scores 0 to ${\geq}3$, the 60-day mortality rates were 0%, 21%, 33%, and 57%, respectively (p=0.001). For both the TDL-Vent score and the modified TDL-Vent score, the areas under the receiver operating characteristic curve were larger than that of other illness severity scores. Conclusion: The TDL-Vent model identifies TDL patients on mechanical ventilation with a high risk of mortality. Prospective validation studies in larger cohorts are now warranted.

Risk factors of type 2 diabetes among Korean adults: The 2001 Korean national health and nutrition examination survey

  • Chung, Hae-Rang;Perez-Escamilla, Rafael
    • Nutrition Research and Practice
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    • v.3 no.4
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    • pp.286-294
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    • 2009
  • This study aimed to identify risk factors for type 2 diabetes (T2D) in Korea, a rapidly changing country. Data of 5,132 adults aged 20-85 were used from the 2001 Korean Health and Nutrition Examination Survey. Multiple logistic regression was carried out to identify risk factors for T2D. Three models were specified: (i) socioeconomic and demographic factors (model 1: age, gender, education, poverty income ratio, employment), (ii) behavioral risk factors and covariates (model 2: obesity, physical activity, smoking, alcohol drinking, dietary quality, family history of T2D, co-morbidity) and (iii) socioeconomic, demographic, and behavioral factors (model 3). The prevalence of T2D was 7.4%. Less education (OR 1.41, 95% CI 1.08-1.84), age (OR 2.19, 95% CI 1.56-3.08 in 40-59 yrs, OR 4.05, 95% CI 2.76-5.95 in 60 yrs + comparing to 20-39 yrs) and abdominal obesity (OR 2.24, 95% CI 1.79-2.82) were risk factors for T2D even after controlling for other factors simultaneously. There was a significant association of T2D with ever smoking (OR 1.34, 95% CI 1.06-1.67). The relationship of age with T2D was modified by gender in model 1 and the relationship of smoking with T2D was modified by obesity in model 2. Less educated, older, obese or ever smokers were more likely to have T2D. Gender mediated the relationship of age, and obesity mediated the relationship of smoking, with T2D. Intervention programs for T2D in Korea should take the interactions among risk factors into account.

Beliefs and Behaviors of Breast Cancer Screening in Women Referring to Health Care Centers in Northwest Iran According to the Champion Health Belief Model Scale

  • Fouladi, Nasrin;Pourfarzi, Farhad;Mazaheri, Effat;Asl, Hossein Alimohammadi;Rezaie, Minoo;Amani, Fiouz;Nejad, Masumeh Rostam
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.11
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    • pp.6857-6862
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    • 2013
  • Background: Breast cancer is the most common cancer in women. All ages are susceptible and more than 90% of the patients can be cured with early diagnosis. Breast self-examination (BSE) and mammography can be useful for this aim. In this study we examined the components of the Champion health belief model to identify if they could predict the intentions of women to perform such screening. Materials and Methods: A total of 380 women aged 30 and above who had referred to health-care centers were assessed for use of breast cancer screening over the past year with a modified health belief model questionnaire. Logistic regression was applied to identify leading independent predictors. Results: In this study 27% of the women performed BSE in the last year but only 6.8% of them used mammography as a way of screening. There were significant differences regarding all components of the model except for perceived severity between women that underwent BSE. over the past year and those that did not. Findings were similar for mammography. Regression analysis revealed that intentions to perform BSE were predicted by perceived self-efficacy and perceived barriers to BSE while intentions to perform mammography were predicted by perceived barriers. Conclusions: This study indicated that self-efficacy can support performance of BSE while perceived barriers are important for not performing both BSE and mammography. Thus we must educate women to increase their self-efficacy and decrease their perceived barriers.

Compressive Strength Development Model for Concrete Cured by Microwave Heating Form (마이크로웨이브 발열거푸집으로 양생된 콘크리트의 압축강도발현 모델)

  • Koh, Tae-Hoon;Moon, Do-Young;Bae, Jung-Myung;Yoo, Jung-Hoon
    • Journal of the Korea Concrete Institute
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    • v.27 no.6
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    • pp.669-676
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    • 2015
  • Time dependent model for prediction of compressive strength development of concrete cured by microwave heating form was presented in this study. The presented model is similar to the equation which is given in ACI 209R-92 but the constants which is dependent on cement type and curing method in the presented model are modified by the regression analysis of the experimental data. Laboratory scale concrete specimens were cast and cured by the microwave heating form and drilled cores extracted from the specimens were fractured in compression. The measured core strengths are converted to standard core and in-situ strengths. These in-situ strengths are used for the regression.

Design of Sound Quality Index for Laser Printers and Its Application for Improvement Study (프린터의 음질 인덱스 제작과 음질개선에 대한 응용)

  • Kim, Eui-Youl;Lee, Young-Jun;Lee, Sang-Kwon
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.22 no.6
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    • pp.509-523
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    • 2012
  • The sound quality based on design optimization, throughout the development process of various electronic office equipments, needs to be considered in order to respond the increased needs for the emotional satisfaction of customers in terms of psycho-acoustics. This paper focuses on how to describe the characteristics of operating sound radiated from laser printers by using various sound attributes, and to model the sound quality index that can properly evaluate the subjective preference on modification conditions in the improvement study quantitatively. Especially, the proposed verification process, in the form of combining the correlation based method and the decision error based method, was applied to improve the generality and reliability of a group of participants in the jury evaluation. The modified Aures tonality model was also proposed to improve the correlation coefficient with the mean response of participants by optimizing some parameters. As a result, the loudness, articulation index, roughness, tonality, fluctuation strength were used to model the sound quality index for laser printers by using the multiple-linear regression method. Through the improvement study, it was confirmed that replacing the absorbing materials is effective to reduce the tonalness radiated from the side of a reference printer model. Based on above results, it can be concluded that the proposed model has enough usefulness as quantitative evaluation index to evaluate the difference between modification conditions in the improvement study.

Determination of Priority for Improvement Using the Theory of Two-dimensional Quality (품질의 이원론을 이용한 개선의 우선순위 결정)

  • Song, Hae Geun
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.36 no.1
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    • pp.70-77
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    • 2013
  • The theory of two-dimensional quality, in particular, the Kano model that is developed by the analogy with the M-H theory, has been applied in various industry fields for more than three decades. Importance-Performance Analysis (IPA) assumes that the degree of physical fulfilment of quality attributes and the satisfaction of that attribute is linear, and therefore, it is applicable to the traditional one-dimensional attribute, not other quality types defined in the Kano's model such as attractive or must-be attribute. To solve this problem, the current study suggests a new importance-satisfaction analysis using a modified IPA in accordance with the three quality types and a diagonal method introduced by Slack (1999) to determine improvement priority. For this, I investigated 19 smartphone's quality attributes and conducted a survey of 334 university students for the results of Kano's model, which adopted from Song and Park (2012)'s study, and the importance/satisfaction of the quality attributes and the results of the priority for improvement of the 19 quality attributes. The results show that the proposed I-S priority model is better than the conventional IPA based on the comparison results of determination coefficient from the regression analysis of the two models.

Genetically Optimized Fuzzy Polynomial Neural Networks Model and Its Application to Software Process (진화론적 최적 퍼지다항식 신경회로망 모델 및 소프트웨어 공정으로의 응용)

  • Lee, In-Tae;Park, Ho-Sung;Oh, Sung-Kwun;Ahn, Tae-Chon
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.337-339
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    • 2004
  • In this paper, we discuss optimal design of Fuzzy Polynomial Neural Networks by means of Genetic Algorithms(GAs). Proceeding the layer, this model creates the optimal network architecture through the selection and the elimination of nodes by itself. So, there is characteristic of flexibility. We use a triangle and a Gaussian-like membership function in premise part of rules and design the consequent structure by constant and regression polynomial (linear, quadratic and modified quadratic) function between input and output variables. GAs is applied to improve the performance with optimal input variables and number of input variables and order. To evaluate the performance of the GAs-based FPNNs, the models are experimented with the use of Medical Imaging System(MIS) data.

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Modified (Q, r) Model for Discrete Demand

  • Rim, Suk-C.;Noh, Seung-J.;Hyun, Hye-Mi
    • Management Science and Financial Engineering
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    • v.17 no.1
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    • pp.65-78
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    • 2011
  • In the continuous review (Q, r) model one continuously monitors inventory level and places a replenishment order when the inventory position reaches the reorder point. In many business practices, however, inventory decreases in a discrete fashion. As a result, replenishment orders are usually placed after the inventory position gets far below the reorder point. This makes a chance of shortage more likely and the service level lower than designed. Such a discrepancy can be compensated for by raising the reorder point to some extent. The question is how much the reorder point should be raised in order to compensate for a potential shortage. In this study, we present experimental analyses for this question. Regression models are also proposed for on-site use.