• Title/Summary/Keyword: linear standard model

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Estimation of genetic parameters for temperament in Jeju crossbred horses

  • Kim, Nam Young;Son, Jun Kyu;Cho, In Cheol;Shin, Sang Min;Park, Seol Hwa;Seong, Pil Nam;Woo, Jae Hoon;Park, Nam Geon;Park, Hee Bok
    • Asian-Australasian Journal of Animal Sciences
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    • v.31 no.8
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    • pp.1098-1102
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    • 2018
  • Objective: Temperament can be defined as a type of behavioral tendency that appears in a relatively stable manner in responses to various external stimuli over time. The aim of this study was to estimate genetic parameters for the records of temperament testing that are used to improve the temperament of Jeju crossbred (Jeju${\times}$Thoroughbred) horses. Methods: This study was conducted using 205 horses (101 females and 104 males) produced between 2010 and 2015. The experimental animals were imprinted and tamed according to the Manual for Horse Taming and Evaluation for Therapeutic Riding Horses and evaluated according to the categories for temperament testing (gentleness, patience, aggressiveness, sensitivity, and friendliness) between 15 months and 18 months of age. Each category was scored on a five-point linear scale. Genetic parameters for the test categories were analyzed using a multi-trait mixed model with repeated records. The ASReml program was used to analyze the data. Results: The heritability of gentleness, patience, aggressiveness, sensitivity and friendliness ranged from 0.08 to 0.53. The standard errors of estimated heritability ranged from 0.13 to 0.17. The test categories showed high genetic correlations with each other, ranging from 0.96 to 0.99 and high repeatability, ranging from 0.70 to 0.73. Conclusion: The results of this study showed that the test categories had moderate heritability and high genetic correlations, but additional studies may be necessary to use the results for the improvement programs of the temperament of Jeju crossbred horses.

Chronic Cadmium Intoxication and Renal Injury Among Workers of a Small-scale Silver Soldering Company

  • Choi, Won-Jun;Kang, Seong-Kyu;Ham, Seunghon;Chung, Wookyung;Kim, Ae Jin;Kang, Myunghee
    • Safety and Health at Work
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    • v.11 no.2
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    • pp.235-240
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    • 2020
  • Background: Cadmium exposure may induce chronic intoxication with renal damage. Silver soldering may be a source of cadmium exposure. Methods: We analyzed working environment measurement data and periodic health screening data from a small-scale silver soldering company with ten workers. Concentrations of cadmium in air from working environment measurement data were obtained. Concentrations of blood and urinary cadmium, urine protein, and urine β2-microglobulin (β2M) were obtained. The generalized linear model was used to identify the association between blood and urine cadmium and urine β2M concentrations. Clinical features of chronic cadmium intoxication focused with toxicological renal effects were described. Results: The mean duration of work was 8.5 years (standard deviation [SD] = 6.9, range = 3-20 years). Cadmium concentrations in air were ranged from 0.006 to 0.015 mg/㎥. Blood cadmium concentration was elevated in all ten workers, with a highest level of 34.6 ㎍/L (mean = 21.288 ㎍/L, SD = 11.304, range = 9.641-34.630 ㎍/L). Urinary cadmium concentration was elevated in nine workers, with a highest level of 62.9 ㎍/g Cr (mean = 22.151 ㎍/g creatinine, SD = 19.889, range = 3.228-62.971 ㎍/g creatinine). Urine β2M concentration was elevated in three workers. Urinary cadmium concentration was positively associated with urine protein concentration (beta coefficient = 10.27, 95% confidence interval = [4.36, 16.18]). Other clinical parameters were compatible with renal tubular damage. Conclusion: Cadmium intoxication may occur at quite low air concentrations. Exposure limit may be needed to be lowered.

Nonlinear Inference Using Fuzzy Cluster (퍼지 클러스터를 이용한 비선형 추론)

  • Park, Keon-Jung;Lee, Dong-Yoon
    • Journal of Digital Convergence
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    • v.14 no.1
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    • pp.203-209
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    • 2016
  • In this paper, we introduce a fuzzy inference systems for nonlinear inference using fuzzy cluster. Typically, the generation of fuzzy rules for nonlinear inference causes the problem that the number of fuzzy rules increases exponentially if the input vectors increase. To handle this problem, the fuzzy rules of fuzzy model are designed by dividing the input vector space in the scatter form using fuzzy clustering algorithm which expresses fuzzy cluster. From this method, complex nonlinear process can be modeled. The premise part of the fuzzy rules is determined by means of FCM clustering algorithm with fuzzy clusters. The consequence part of the fuzzy rules have four kinds of polynomial functions and the coefficient parameters of each rule are estimated by using the standard least-squares method. And we use the data widely used in nonlinear process for the performance and the nonlinear characteristics of the nonlinear process. Experimental results show that the non-linear inference is possible.

An Image Segmentation Algorithm using the Shape Space Model (모양공간 모델을 이용한 영상분할 알고리즘)

  • 김대희;안충현;호요성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.2
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    • pp.41-50
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    • 2004
  • Since the MPEG-4 visual standard enables content-based functionalities, it is necessary to extract video objects from video sequences. Segmentation algorithms can largely be classified into two different categories: automatic segmentation and user-assisted segmentation. In this paper, we propose a new user-assisted image segmentation method based on the active contour. If we define a shape space as a set of all possible variations from the initial curve and we assume that the shape space is linear, it can be decomposed into the column space and the left null space of the shape matrix. In the proposed method, the shape space vector in the column space describes changes from the initial curve to the imaginary feature curve, and a dynamic graph search algorithm describes the detailed shape of the object in the left null space. Since we employ the shape matrix and the SUSAN operator to outline object boundaries, the proposed algorithm can ignore unwanted feature points generated by low-level image processing operations and is, therefore, applicable to images of complex background. We can also compensate for limitations of the shape matrix with a dynamic graph search algorithm.

A Study on Characteristic for a Maximum Utilization Factor of Transformer with Regard to Load Characteristics in General Customers (일반용전력사용고객 용도별 부하특성을 고려한 변압기최대이용률 비교 특성 연구)

  • Kim, Se-Dong;Wang, Yong-Peel;Hong, Hyun-Mun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.12
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    • pp.217-223
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    • 2009
  • This paper shows a reasonable contract power conversion factor, that was made by the systematic and statistical way considering actual conditions, such as investigated contract power and peak power for the last 5 years of each customer for 461 general customers as to AMR. In this dissertation, it is necessary to analyze the key features and general trend from the investigated data. It made an analysis of the feature parameters, such as average, standard deviation, median, maximum, minimun and thus it was carried by the linear and nonlinear regression analysis. Therefore, this paper compared characteristics for a contract power conversion factor which is applied to estimate contract power with characteristics for a regression model for customers(office, store, hotel, hospital, wedding hall) which maximum utilization factor of transformer is more than 60[%].

Robust selection rules of k in ridge regression (능형회귀에서의 로버스트한 k의 선택 방법)

  • 임용빈
    • The Korean Journal of Applied Statistics
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    • v.6 no.2
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    • pp.371-381
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    • 1993
  • When the multicollinearity presents in the standard linear regression model, ridge regression might be used to mitigate the effects of collinearity. As the prediction-oriented criterion, the integrated mean sqare error criterion $J_w(k)$ was introduced by Lim, Choi & Park(1980). By noting the equivalent relationship between the $C_k$ criterion and $J_w(k)$ with a special choice of weight function $W(x)$, we propose a more reasonable selection rule of k w.r.t. the $C_k$ criterion than that given in Myers(1986). Next, to find the $\beta(k)$ which behaves reasonably well w.r.t. competing criteria, we adopt the minimax principle in the sense of maximizing the worst relative efficiency of k among competing criteria.

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A Study on the Optimization Model for the Project Portfolio Manpower Assignment Using Genetic Algorithm (유전자 알고리즘을 이용한 프로젝트 포트폴리오 투입인력 최적화 모델에 관한 연구)

  • Kim, Dong-Wook;Lee, Won-Young
    • Journal of Information Technology Services
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    • v.17 no.4
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    • pp.101-117
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    • 2018
  • Companies are responding appropriately to the rapidly changing business environment and striving to lead those changes. As part of that, we are meeting our strategic goals through IT projects, which increase the number of simultaneous projects and the importance of project portfolio management for successful project execution. It also strives for efficient deployment of human resources that have the greatest impact on project portfolio management. In the early stages of project portfolio management, it is very important to establish a reasonable manpower plan and allocate performance personnel. This problem is a problem that can not be solved by linear programming because it is calculated through the standard deviation of the input ratio of professional manpower considering the uniformity of load allocated to the input development manpower and the importance of each project. In this study, genetic algorithm, one of the heuristic methods, was applied to solve this problem. As the objective function, we used the proper input ratio of projects, the input rate of specialist manpower for important projects, and the equal load of workload by manpower. Constraints were not able to input duplicate manpower, Was used as a condition. We also developed a program for efficient application of genetic algorithms and confirmed the execution results. In addition, the parameters of the genetic algorithm were variously changed and repeated test results were selected through the independent sample t test to select optimal parameters, and the improvement effect of about 31.2% was confirmed.

Word Embeddings-Based Pseudo Relevance Feedback Using Deep Averaging Networks for Arabic Document Retrieval

  • Farhan, Yasir Hadi;Noah, Shahrul Azman Mohd;Mohd, Masnizah;Atwan, Jaffar
    • Journal of Information Science Theory and Practice
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    • v.9 no.2
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    • pp.1-17
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    • 2021
  • Pseudo relevance feedback (PRF) is a powerful query expansion (QE) technique that prepares queries using the top k pseudorelevant documents and choosing expansion elements. Traditional PRF frameworks have robustly handled vocabulary mismatch corresponding to user queries and pertinent documents; nevertheless, expansion elements are chosen, disregarding similarity to the original query's elements. Word embedding (WE) schemes comprise techniques of significant interest concerning QE, that falls within the information retrieval domain. Deep averaging networks (DANs) defines a framework relying on average word presence passed through multiple linear layers. The complete query is understandably represented using the average vector comprising the query terms. The vector may be employed for determining expansion elements pertinent to the entire query. In this study, we suggest a DANs-based technique that augments PRF frameworks by integrating WE similarities to facilitate Arabic information retrieval. The technique is based on the fundamental that the top pseudo-relevant document set is assessed to determine candidate element distribution and select expansion terms appropriately, considering their similarity to the average vector representing the initial query elements. The Word2Vec model is selected for executing the experiments on a standard Arabic TREC 2001/2002 set. The majority of the evaluations indicate that the PRF implementation in the present study offers a significant performance improvement compared to that of the baseline PRF frameworks.

Factors influencing the health-related quality of life of postmenopausal women with diabetes and osteoporosis: a secondary analysis of the Seventh Korea National Health and Nutrition Examination Survey (2016-2018) (골다공증이 있는 폐경 후 당뇨 여성의 건강관련 삶의 질 영향요인: 제7기 국민건강영양조사 자료(2016-2018년) 활용)

  • Kim, Hyuk Joon;Kim, Hye Young
    • Women's Health Nursing
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    • v.28 no.2
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    • pp.112-122
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    • 2022
  • Purpose: The prevalence of osteoporosis in postmenopausal women is increasing, and diabetes patients have decreased bone density. Their health-related quality of life (HRQoL) is diminished by the resultant physical dysfunction and depression. The purpose of this study was to identify factors influencing HRQoL in postmenopausal women with diabetes and osteoporosis. Methods: This was a secondary data analysis of the Seventh Korea Health and Nutrition Examination Survey (2016-2018), which utilized a complex, multistage probability sample design. The participants in the study were 237 women with diabetes and osteoporosis. To evaluate the factors that influenced HRQoL, a complex-samples general linear model was constructed, and the Bonferroni correction was performed. Results: In this sample of women aged 45 to 80 years (mean±standard deviation, 71.12±7.21 years), the average HRQoL score was 0.83±0.18 out of 1.0. Factors influencing HRQoL were age (70s: t=-3.74, p<.001; 80s: t=-3.42, p=.001), walking for exercise more than 5 days a week (t=-2.83, p=.005), cerebrovascular disease (t=-8.33, p<.001), osteoarthritis (t=-2.04, p=.014), hypertension (t=2.03, p=.044), higher perceived stress (t=-2.17, p=.032), poor glycemic control (t=3.40, p=.001), waist circumference (t=-2.76, p=.007), sitting time per day (t=-2.10, p=.038), and a longer postmenopausal period (t=3.09, p=.002). Conclusion: In order to improve the HRQoL of postmenopausal women with osteoporosis and diabetes, it is necessary to implement intervention strategies that enable the effective management of chronic diseases, while preventing the complications of diabetes and minimizing stress through physical activity.

Estimating Design Hour Factor Using Permanent Survey (상시 교통량 자료를 이용한 설계시간계수 추정)

  • Ha, Jung Ah;Kim, Sung Hyun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.2D
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    • pp.155-162
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    • 2008
  • This study shows how to estimate the design hour factor when the counting stations don't have all of the hourly volumes such as in a coverage survey. A coverage survey records traffic volume from 1 to 5 times in a year so it lacks the detailed information to calculate the design hour factor. This study used the traffic volumes of permanent surveys to estimate the design hour factor in coverage surveys using correlation and regression analysis. A total 7 independent variables are used : the coefficient of variance of hourly volume, standard deviation of hourly volume, peak hour volume, AADT, heavy traffic volume proprotion, day time traffic volume proportion and D factor. All of variables are plotted on a curve, so it must use non-linear regression to analyze the data. As a result the coefficient of determination and MAE are good at logarith model using AADT.