• Title/Summary/Keyword: regression characteristics

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Loss of Acquired Skills: Regression in Young Children With Autism Spectrum Disorders

  • Ye Rim Kim;Da-Yea Song;Guiyoung Bong;Jae Hyun Han;Hee Jeong Yoo
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
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    • v.34 no.1
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    • pp.51-56
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    • 2023
  • Objectives: Regression, while not a core symptom of autism spectrum disorder (ASD), has been suggested to be a distinct subtype by previous studies. Therefore, this study aimed to explore the prevalence and clinical differences between those with and without regression in children with ASD. Methods: This study includes data from toddlers and young children aged 2-7 years acquired from other projects at Seoul National University Bundang Hospital. The presence and characteristics of regression were explored using question items #11-28 from the Autism Diagnostic Interview-Revised. Chi-square and independent t-tests were used to compare various clinical measurements such as autistic symptoms, adaptative behavior, intelligence, and perinatal factors. Results: Data from 1438 young children (1020 with ASD) were analyzed. The overall prevalence rate of regression, which was mainly related to language-related skills, was 10.2% in the ASD group, with an onset age of 24 months. Regarding clinical characteristics, patients with ASD and regression experienced ASD symptoms, especially restricted and repetitive interests and behaviors, with greater severity than those without regression. Furthermore, there were significant associations between regression and hypertension/placenta previa. Conclusion: In-depth surveillance and proactive interventions targeted at young children with ASD and regression should focus on autistic symptoms and other areas of functioning.

Prediction of Pitting Corrosion Characteristics of AL-6XN Steel with Sensitization and Environmental Variables Using Multiple Linear Regression Method (다중선형회귀법을 활용한 예민화와 환경변수에 따른 AL-6XN강의 공식특성 예측)

  • Jung, Kwang-Hu;Kim, Seong-Jong
    • Corrosion Science and Technology
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    • v.19 no.6
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    • pp.302-309
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    • 2020
  • This study aimed to predict the pitting corrosion characteristics of AL-6XN super-austenitic steel using multiple linear regression. The variables used in the model are degree of sensitization, temperature, and pH. Experiments were designed and cyclic polarization curve tests were conducted accordingly. The data obtained from the cyclic polarization curve tests were used as training data for the multiple linear regression model. The significance of each factor in the response (critical pitting potential, repassivation potential) was analyzed. The multiple linear regression model was validated using experimental conditions that were not included in the training data. As a result, the degree of sensitization showed a greater effect than the other variables. Multiple linear regression showed poor performance for prediction of repassivation potential. On the other hand, the model showed a considerable degree of predictive performance for critical pitting potential. The coefficient of determination (R2) was 0.7745. The possibility for pitting potential prediction was confirmed using multiple linear regression.

The Effect of Personal Characteristics, Loan Characteristics and Interest Rate Characteristics on the Delinquency Possibility (개인특성·대출특성·금리특성이 연체가능성에 미치는 영향)

  • Park, Sang-Bong;Oh, Young-Ho
    • Asia-Pacific Journal of Business
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    • v.11 no.3
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    • pp.63-77
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    • 2020
  • Purpose - The purpose of this study is to examine the effects of personal characteristics, loan characteristics, and interest rate characteristics of 2,653 borrowers on the delinquency possibility. In doing so, this study applies both multiple regression and logistic regression models to the data of credit unions in the city of Daegu. Design/Methodology/Approach - The major results of multiple regression analysis using SPSS are as follows. Findings - As for the results of testing the significance of the regression coefficients, it has been found that among the personal characteristics variables membership, credit rating, credit rating changes, and LTV have significant positive (+) effects on the delinquency possibility. Also it has been shown that among the loan characteristics variables loan amount, loan balance, total debt amount, collateral type, collateral amount, and repayment method have significant positive (+) effects on the delinquency possibility. Furthermore it has been found that among the interest rate characteristics variables both overdue interest rate and interest rate spread have positive (+) effects on the delinquency possibility. However, it has been shown that among the personal characteristics variables equity and membership do not have significant effects on the delinquency possibility, and that normal interest rate among the interest rate characteristics variables also do not have a significant effect on the delinquency possibility. Research Implications - By systematically analyzing the variables affecting delinquency possibility based on the results of this study, credit unions might get positive help in improving the system of managing receivables. Furthermore, the results of this study could be extended and applied to other types of financial institutions, so that financial institutions in general will also get some help to systematically manage the delinquency possibility.

A Fast Kernel Regression Framework for Video Super-Resolution

  • Yu, Wen-Sen;Wang, Ming-Hui;Chang, Hua-Wen;Chen, Shu-Qing
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.1
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    • pp.232-248
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    • 2014
  • A series of kernel regression (KR) algorithms, such as the classic kernel regression (CKR), the 2- and 3-D steering kernel regression (SKR), have been proposed for image and video super-resolution. In existing KR frameworks, a single algorithm is usually adopted and applied for a whole image/video, regardless of region characteristics. However, their performances and computational efficiencies can differ in regions of different characteristics. To take full advantage of the KR algorithms and avoid their disadvantage, this paper proposes a kernel regression framework for video super-resolution. In this framework, each video frame is first analyzed and divided into three types of regions: flat, non-flat-stationary, and non-flat-moving regions. Then different KR algorithm is selected according to the region type. The CKR and 2-D SKR algorithms are applied to flat and non-flat-stationary regions, respectively. For non-flat-moving regions, this paper proposes a similarity-assisted steering kernel regression (SASKR) algorithm, which can give better performance and higher computational efficiency than the 3-D SKR algorithm. Experimental results demonstrate that the computational efficiency of the proposed framework is greatly improved without apparent degradation in performance.

Polynomial Representation for MAU-Propeller Open Water Characteristics (MAU프로펠러 단독특성의 수식표현)

  • Seo, Jeong-Cheon;Lee, Chang-Seop
    • 한국기계연구소 소보
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    • s.11
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    • pp.95-101
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    • 1984
  • The MAU-series propellers were designed and tested in japan. This report presents the polynomial coefficients of open water Characteristics for each standard MAU-series propellers, obtained by multiple polynomial regression analysis in terms of pitch-diameter ratio and advance coefficient. The limitation of applicability and the accuracy of the regression polynomial are also discussed.

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A Study on Taguchi and VTA Methods for Product Design (제품설계를 위한 다구찌 방법과 VTA방법에 관한 연구)

  • 장현수;김용범;김우열
    • Journal of the military operations research society of Korea
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    • v.27 no.1
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    • pp.101-113
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    • 2001
  • Taguchi and VTA(variation Transmission Analysis) methods have been widely used recently as new methods for product design. In this study, Taguchi method using analysis of variance and VTA method using regression analysis are reviewed and compared with each other in terms of parameter design and tolerance design. In analysis of variance, variation of quality characteristics arises from noise factors, therefore the optimal levels of design factors are selected to minimize the effect of noise factors. n regression analysis, variation of quality characteristics arises from variation of each own design factors. As a method to reduce variation of these quality characteristics, sensitivity analysis was performed for each design factors. An example of calculating tolerance interval for the given defect rate in PPM is also introduced. Especially, the new method is suggested to increase the estimation accuracy of variation of quality characteristics through regression analysis.

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Factors Affecting Usage and Performance of Information Technology in Daedeok Valley and Zhongguancun Venture Firms (한중 벤처기업의 정보기술 활용 및 성과에 관한 연구: 대덕밸리와 중관촌을 중심으로)

  • Hwang, Kyung-Yun;Moon, Hee-Cheol
    • Journal of Information Technology Applications and Management
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    • v.12 no.2
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    • pp.163-184
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    • 2005
  • The purpose of this research is to examine the major determinants affecting the usage and performance of information technologies in Daedeok Valley and Zhongguancun venture firms. The development of the research model is based on the theoretical linkages of IDT (Innovation Diffusion Theory) and TAM(Technology Acceptance Model). Seven hypotheses are derived and tested using regression analysis. The results from regression analysis suggest that the usage of Information technologies is affected by innovation characteristics (perceived usefulness) as well as organizational characteristics (top management support, employee capability on information technology acceptance) in Daedeok Valley venture firms. But, The results from regression analysis suggest that the usage of Information technologies is affected by innovation characteristics (perceived usefulness), organizational characteristics (top management support, employee capability on information technology acceptance), and external pressure (environmental uncertainty, intensity of competition) in Zhongguancun venture firms.

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Analysis for Insulating Degradation Characteristics with Aging Time for Oil-filled Transformers and/or Correlation between using Linear Regression Method (유입식 변압기의 열화시간에 따른 절연 열화특성 및 선형회귀법을 이용한 상관관계 분석)

  • Lee, Seung-Min
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.4
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    • pp.693-699
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    • 2010
  • General transformer's life is known as paper insulation' life. If a transformer is degraded by these aging factors, it is known that electrical, mechanical and chemical characteristics for transformer's oil-paper are changed. When the kraft paper is aged, the cellulose polymer chains break down into shorter lengths. It causes decrease in both tensile strength and degree of polymerization of paper insulation. The paper breakdown is accompanied by an increase in the content of furanic compounds within the dielectric liquid. In this paper it is aimed at analysis on correlation between aging characteristics for insulating diagnosis of thermally aged paper. For investigating the accelerated aging process of oil-paper samples accelerating aging cell was manufactured for estimating variation of paper insulation during 500 hours at $140^{\circ}C$ temperature. To derive the results, it was performed analysis such as tensile strength(TS), depolymerization(DP), dielectric strength(DS), relative permittivity, water content(WC) and furan compound(FC) for aged paper. Also for analyzing correlation between insulating degradation characteristics, we used linear regression method. As as results of linear regression analysis, there was a close correlation between TS and DP. WC, FC. But dielectric strength was a weak correlation with aging time.

Corporate Governance and Performance of Insurance Companies in the Saudi Market

  • OSMAN, Mohamed Abdel Mawla;SAMONTARAY, Durga Prasad
    • The Journal of Asian Finance, Economics and Business
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    • v.9 no.4
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    • pp.213-228
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    • 2022
  • This paper investigates the association between key corporate governance characteristics and the performance of general insurance businesses listed on the Saudi stock exchange (TADAWUL). The methodology for the study is based on a pooled data collection for 11 Saudi general insurance companies from 2011 to 20. The linear regression model and the logarithm regression model are suggested to assess the relationship between performance and corporate governance characteristics. The dependent variable is firm performance measured using ROA, ROE, and Tobin's Q. The independent variables are corporate governance variables consisting of a complete set of board and audit committee characteristics. Insurer-specific control variables are introduced. The empirical results reveal that the characteristics of corporate governance influence the performance of insurance companies. In particular, the board size, board's tenure, the proportion of independent directors in the board, audit committee size, audit committee meeting frequency, and proportion of health insurance premiums have a positive impact. However, audit committee independence, size of the company, and proportion of reinsurance premiums have a negative impact on the performance of the Saudi general insurance companies. Finally, the empirical results indicated also that there is an unclear relationship between the performance and board meeting frequency, compensations of the Board, and the average age of the Board.

A Study on the Influence of Job Characteristics Perceived by Nurses on Their Job Satisfaction and Organizational Commitment : Focusing on Moderating Effect of Individual Personality Characteristics (간호조직에서 직무특성이 간호사의 직무만족과 조직몰입에 미치는 영향 - 성격특성의 조절효과를 중심으로 -)

  • 김명숙;박영배
    • Journal of Korean Academy of Nursing
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    • v.29 no.6
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    • pp.1434-1444
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    • 1999
  • The purpose of this study was to investigate the influence of job characteristics on the nurses' the moderating effect of locus of control on the job satisfaction and organizational commitment and relationship between job characteristics and attitude. The sample for this study consisted of 594 nurses from 8 university hospitals. Factor analysis, Cronbach's alpha analysis, multiple regression analysis and hierarchical multiple regression analysis were used for the statistical methods. The results of this study were found that (1) autonomy among 5 core job characteristics showed positive influence on job satisfaction, (2) task significance and autonomy among 5 core job characteristics had positive influence on organizational commitment, (3) the internals of locus of control moderated the effect of job characteristics on nurses' job satisfaction, and (4) internals and externals of locus of control moderated the effect of job characteristics on nurses' organizational commitment.

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