Exploring Technostress: Results of a Large Sample Factor Analysis

Directory of Open Access Journals (Sweden)

Steponas Jonušauskas

2016-06-01

Full Text Available With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ answers, revealing technostress causes and consequences as well as technostress prevalence in the population in a statistically validated pattern. A key elements of technostress based on factor analysis can serve for the construction of technostress measurement scales in further research.

Risk factors for radiation-induced hypothyroidism: A Literature-Based Meta-Analysis

DEFF Research Database (Denmark)

Vogelius, Ivan R; Bentzen, Søren; Maraldo, Maja V

2011-01-01

BACKGROUND: A systematic overview and meta-analysis of studies reporting data on hypothyroidism (HT) after radiation therapy was conducted to identify risk factors for development of HT. METHODS: Published studies were identified from the PubMed and Embase databases and by hand-searching published...... reviews. Studies allowing the extraction of odds ratios (OR) for HT in 1 or more of several candidate clinical risk groups were included. A meta-analysis of the OR for development of HT with or without each of the candidate risk factors was performed. Furthermore, studies allowing the extraction......% risk of HT at a dose of 45 Gy but with considerable variation in the dose response between studies. Chemotherapy and age were not associated with risk of HT in this analysis. CONCLUSIONS: Several clinical risk factors for HT were identified. The risk of HT increases with increasing radiation dose...

Analysis on influence factors of China's CO2 emissions based on Path-STIRPAT model

International Nuclear Information System (INIS)

Li Huanan; Mu Hailin; Zhang Ming; Li Nan

2011-01-01

With the intensification of global warming and continued growth in energy consumption, China is facing increasing pressure to cut its CO 2 (carbon dioxide) emissions down. This paper discusses the driving forces influencing China's CO 2 emissions based on Path-STIRPAT model-a method combining Path analysis with STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The analysis shows that GDP per capita (A), industrial structure (IS), population (P), urbanization level (R) and technology level (T) are the main factors influencing China's CO 2 emissions, which exert an influence interactively and collaboratively. The sequence of the size of factors' direct influence on China's CO 2 emission is A>T>P>R>IS, while that of factors' total influence is A>R>P>T>IS. One percent increase in A, IS, P, R and T leads to 0.44, 1.58, 1.31, 1.12 and -1.09 percentage change in CO 2 emission totally, where their direct contribution is 0.45, 0.07, 0.63, 0.08, 0.92, respectively. Improving T is the most important way for CO 2 reduction in China. - Highlights: → We analyze the driving forces influencing China's CO 2 emissions. → Five macro factors like per capita GDP are the main influencing factors. → These factors exert an influence interactively and collaboratively. → Different factors' direct and total influence on China's CO 2 emission is different. → Improving technology level is the most important way for CO 2 reduction in China.

Designing a User-Friendly Microcomputer-Based Laboratory Package through the Factor Analysis of Teacher Evaluations

Science.gov (United States)

Lavonen, Jari; Juuti, Kalle; Meisalo, Veijo

2003-01-01

In this study we analyse how the experiences of chemistry teachers on the use of a Microcomputer-Based Laboratory (MBL), gathered by a Likert-scale instrument, can be utilized to develop the new package "Empirica 2000." We used exploratory factor analysis to identify the essential features in a large set of questionnaire data to see how…

Analysis of Learning Environment Factors Based on Maslow’s Hierarchy of Needs

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Košir Katja

2013-09-01

Full Text Available This paper provides a new analysis of some learning environment factors from the point of view of one of the most established motivational models, i.e. Maslow’s hierarchy of needs. For a teacher, this model can represent a meaningful tool for the analysis of the potential factors of pupils’ inadequate school adjustment. Some psychological constructs that can be conceptualized as learning environment factors are presented at specific levels of needs. As regards the level of physiological needs, this paper provides an overview of research studies on ergonomic factors of learning environment. As for safety needs, the paper outlines the concepts of classroom management and peer-to-peer violence, and presents some main research findings in both fields. The analysis regarding the level of love and belonging includes aspects of positive classroom climate and the concept of pupils’ social acceptance. Contemporary findings about the development of pupil’s academic self-concept are presented within the self-esteem and achievements needs. Flow is considered to be one of key factors that help teacher satisfy the self-actualization needs and stimulate pupils’ personal development. On the basis of this analysis, some implications and recommendations are given to help teachers efficiently encourage an integrated approach to pupil development.

Anatomical specificity of vascular endothelial growth factor expression in glioblastomas: a voxel-based mapping analysis

Energy Technology Data Exchange (ETDEWEB)

Fan, Xing [Capital Medical University, Department of Neurosurgery, Beijing Tiantan Hospital, Beijing (China); Wang, Yinyan [Capital Medical University, Department of Neurosurgery, Beijing Tiantan Hospital, Beijing (China); Capital Medical University, Department of Neuropathology, Beijing Neurosurgical Institute, Beijing (China); Wang, Kai; Ma, Jun; Li, Shaowu [Capital Medical University, Department of Neuroradiology, Beijing Tiantan Hospital, Beijing (China); Liu, Shuai [Chinese Academy of Medical Sciences and Peking Union Medical College, Departments of Neurosurgery, Peking Union Medical College Hospital, Beijing (China); Liu, Yong [Chinese Academy of Sciences, Brainnetome Center, Institute of Automation, Beijing (China); Jiang, Tao [Capital Medical University, Department of Neurosurgery, Beijing Tiantan Hospital, Beijing (China); Beijing Academy of Critical Illness in Brain, Department of Clinical Oncology, Beijing (China)

2016-01-15

The expression of vascular endothelial growth factor (VEGF) is a common genetic alteration in malignant gliomas and contributes to the angiogenesis of tumors. This study aimed to investigate the anatomical specificity of VEGF expression levels in glioblastomas using voxel-based neuroimaging analysis. Clinical information, MR scans, and immunohistochemistry stains of 209 patients with glioblastomas were reviewed. All tumor lesions were segmented manually and subsequently registered to standard brain space. Voxel-based regression analysis was performed to correlate the brain regions of tumor involvement with the level of VEGF expression. Brain regions identified as significantly associated with high or low VEGF expression were preserved following permutation correction. High VEGF expression was detected in 123 (58.9 %) of the 209 patients. Voxel-based statistical analysis demonstrated that high VEGF expression was more likely in tumors located in the left frontal lobe and the right caudate and low VEGF expression was more likely in tumors that occurred in the posterior region of the right lateral ventricle. Voxel-based neuroimaging analysis revealed the anatomic specificity of VEGF expression in glioblastoma, which may further our understanding of genetic heterogeneity during tumor origination. This finding provides primary theoretical support for potential future application of customized antiangiogenic therapy. (orig.)

Anatomical specificity of vascular endothelial growth factor expression in glioblastomas: a voxel-based mapping analysis

International Nuclear Information System (INIS)

Fan, Xing; Wang, Yinyan; Wang, Kai; Ma, Jun; Li, Shaowu; Liu, Shuai; Liu, Yong; Jiang, Tao

2016-01-01

The expression of vascular endothelial growth factor (VEGF) is a common genetic alteration in malignant gliomas and contributes to the angiogenesis of tumors. This study aimed to investigate the anatomical specificity of VEGF expression levels in glioblastomas using voxel-based neuroimaging analysis. Clinical information, MR scans, and immunohistochemistry stains of 209 patients with glioblastomas were reviewed. All tumor lesions were segmented manually and subsequently registered to standard brain space. Voxel-based regression analysis was performed to correlate the brain regions of tumor involvement with the level of VEGF expression. Brain regions identified as significantly associated with high or low VEGF expression were preserved following permutation correction. High VEGF expression was detected in 123 (58.9 %) of the 209 patients. Voxel-based statistical analysis demonstrated that high VEGF expression was more likely in tumors located in the left frontal lobe and the right caudate and low VEGF expression was more likely in tumors that occurred in the posterior region of the right lateral ventricle. Voxel-based neuroimaging analysis revealed the anatomic specificity of VEGF expression in glioblastoma, which may further our understanding of genetic heterogeneity during tumor origination. This finding provides primary theoretical support for potential future application of customized antiangiogenic therapy. (orig.)

Foundations of factor analysis

CERN Document Server

Mulaik, Stanley A

2009-01-01

Introduction Factor Analysis and Structural Theories Brief History of Factor Analysis as a Linear Model Example of Factor AnalysisMathematical Foundations for Factor Analysis Introduction Scalar AlgebraVectorsMatrix AlgebraDeterminants Treatment of Variables as Vectors Maxima and Minima of FunctionsComposite Variables and Linear Transformations Introduction Composite Variables Unweighted Composite VariablesDifferentially Weighted Composites Matrix EquationsMulti

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

Science.gov (United States)

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

Science.gov (United States)

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Factor Economic Analysis at Forestry Enterprises

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M.Yu. Chik

2018-03-01

Full Text Available The article studies the importance of economic analysis according to the results of research of scientific works of domestic and foreign scientists. The calculation of the influence of factors on the change in the cost of harvesting timber products by cost items has been performed. The results of the calculation of the influence of factors on the change of costs on 1 UAH are determined using the full cost of sold products. The variable and fixed costs and their distribution are allocated that influences the calculation of the impact of factors on cost changes on 1 UAH of sold products. The paper singles out the general results of calculating the influence of factors on cost changes on 1 UAH of sold products. According to the results of the analysis, the list of reserves for reducing the cost of production at forest enterprises was proposed. The main sources of reserves for reducing the prime cost of forest products at forest enterprises are investigated based on the conducted factor analysis.

Text mining factor analysis (TFA) in green tea patent data

Science.gov (United States)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Confirmatory Factor Analysis of the School-Based Assessment Evaluation Scale Among Teachers

Directory of Open Access Journals (Sweden)

Nor Hasnida Che Md. Ghazali

2016-09-01

Full Text Available The school-based assessment (SBA system is a holistic assessment system that is conducted in schools by subject teachers in assessing the students cognitive (intellect, affective (emotional and spiritual and psychomotor (physical aspects. It is in line with the National Philosophy of Education and the Standards-based School Curriculum in Malaysia. In order to evaluate the implementation of SBA, a measurement scale was validated. Questionnaire was used as an instrument for data collection. 776 primary and secondary school teachers were selected as respondents using stratified random sampling. The data was analyzed with SPSS and AMOS version 18. The aim of this paper was to explore different factor structures of the SBA evaluation scale by using the second-order Confirmatory Factor Analysis. Results indicated that the SBA evaluation model was a valid and reliable scale. The input measurement model was validated with two factors (personnel qualifications and physical infrastructure, process measurement model was validated with six factors (‘attitude’, ‘understanding’, ‘skills’, ‘challenges’, ‘moderation’ and ‘monitoring’ and product measurement model was validated with two factors (‘students’ attitude’ and ‘students’ motivation’. This study provides support for using a valid instrument in evaluating the implementation of SBA in schools. Furthermore, the CFA procedures used supported the conceptual framework set out earlier. Thus, it presents clearly the importance of the evaluation process of any education system to follow all the dimensions outlined in the evaluation model proposed by Daniel Stufflebeam.       Sistem Penilaian Berbasis Sekolah (SBA adalah sistem penilaian holistik yang dilakukan di sekolah-sekolah oleh guru mata pelajaran dalam menilai kognitif (kecerdasan, afektif (emosional dan spiritual dan psikomotorik (fisik siswa. Hal ini sejalan dengan Filsafat Pendidikan Nasional dan Kurikulum

Human factor analysis and preventive countermeasures in nuclear power plant

International Nuclear Information System (INIS)

Li Ye

2010-01-01

Based on the human error analysis theory and the characteristics of maintenance in a nuclear power plant, human factors of maintenance in NPP are divided into three different areas: human, technology, and organization. Which is defined as individual factors, including psychological factors, physiological characteristics, health status, level of knowledge and interpersonal skills; The technical factors including technology, equipment, tools, working order, etc.; The organizational factors including management, information exchange, education, working environment, team building and leadership management,etc The analysis found that organizational factors can directly or indirectly affect the behavior of staff and technical factors, is the most basic human error factor. Based on this nuclear power plant to reduce human error and measures the response. (authors)

Exploring Technostress: Results of a Large Sample Factor Analysis

OpenAIRE

Jonušauskas, Steponas; Raišienė, Agota Giedrė

2016-01-01

With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ an...

Comparison of Skin Moisturizer: Consumer-Based Brand Equity (CBBE Factors in Clusters Based on Consumer Ethnocentrism

Directory of Open Access Journals (Sweden)

Yossy Hanna Garlina

2014-09-01

Full Text Available This research aims to analyze relevant factors contributing to the four dimensions of consumer-based brand equity in skin moisturizer industry. It is then followed by the clustering of female consumers of skin moisturizer based on ethnocentrism and differentiating each cluster’s consumer-based brand equity dimensions towards a domestic skin moisturizer brand Mustika Ratu, skin moisturizer. Research used descriptive survey method analysis. Primary data was obtained through questionnaire distribution to 70 female respondents for factor analysis and 120 female respondents for cluster analysis and one way analysis of variance (ANOVA. This research employed factor analysis to obtain relevant factors contributing to the five dimensions of consumer-based brand equity in skin moisturizer industry. Cluster analysis and one way analysis of variance (ANOVA were to see the difference of consumer-based brand equity between highly ethnocentric consumer and low ethnocentric consumer towards the same skin moisturizer domestic brand, Mustika Ratu skin moisturizer. Research found in all individual dimension analysis, all variable means and individual means show distinct difference between the high ethnocentric consumer and the low ethnocentric consumer. The low ethnocentric consumer cluster tends to be lower in mean score of Brand Loyalty, Perceived Quality, Brand Awareness, Brand Association, and Overall Brand Equity than the high ethnocentric consumer cluster. Research concludes consumer ethnocentrism is positively correlated with preferences towards domestic products and negatively correlated with foreign-made product preference. It is, then, highly ethnocentric consumers have positive perception towards domestic product.

Comparison of cardiovascular risk factors in maintenance hemodialysis patients based on phase angle of bioimpedance analysis

Science.gov (United States)

Muzasti, R. A.; Lubis, H. R.

2018-03-01

Mortality and morbidity rate, especially from cardiovascular disease in hemodialysis patients in Indonesia is still quite high. One of indicator to assess the predictive value of mortality is the phase angle (PhA) of bioimpedance analysis (BIA) scan examination. Determining the comparison of BMI and laboratory data as cardiovascular risk factors in hemodialysis patients based on PhA.A cross-sectional analytical study was done on 155 outpatientsin RasyidaRenal Hospital, Medan in 2016. Patients were two groups, namely PhAcardiovascular risk factors of hemodialysis patients were determined by age, BMI, and hemoglobin.

Factor Analysis for Clustered Observations.

Science.gov (United States)

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

Analysis of Influence Factors of PM2.5 in Chengdu Based on VAR Model

Science.gov (United States)

Mingzhi, Luo

2017-05-01

Air pollution and smog are the serious harms to public health and has attracted public attention. Based on the vector auto-regressive (VAR) model, we analysed the influence factors of PM2.5 in Chengdu, investigated the effect of other kinds of air pollutants and meteorological factors onthe PM2.5 by using the methods of generalized impulse response function, variance decomposition analysis, Granger causality test and therelated daily data from December 1, 2013 to November 14, 2016 in Chengdu city to the empirical study. The resultsshow that the influence factors of PM2.5 were stable;the increase of nitrogen dioxide, ozone,precipitation and temperature difference led to the increase of PM2.5 concentration while the increase ofthe wind speed, PM10, sulphur dioxide and carbon monoxide resulted in the decrease of PM2.5 concentration.Climate conditions,nitrogen dioxide and ozone are Granger causes for PM2.5.It is suggestedthat the key for the control of PM2.5 must be based on the cause and formation rules of PM2.5.A further study on nitrogen dioxide and ozone may play an important role in finding out the real source and formation reasons of PM2.5.

Cost Analysis of Universal Screening vs. Risk Factor-Based Screening for Methicillin-Resistant Staphylococcus aureus (MRSA.

Directory of Open Access Journals (Sweden)

Virginia R Roth

Full Text Available The literature remains conflicted regarding the most effective way to screen for MRSA. This study was designed to assess costs associated with universal versus risk factor-based screening for the reduction of nosocomial MRSA transmission.The study was conducted at The Ottawa Hospital, a large multi-centre tertiary care facility with approximately 47,000 admissions annually. From January 2006-December 2007, patients underwent risk factor-based screening for MRSA on admission. From January 2008 to August 2009 universal MRSA screening was implemented. A comparison of costs incurred during risk factor-based screening and universal screening was conducted. The model incorporated probabilities relating to the likelihood of being tested and the results of polymerase chain reaction (PCR testing with associated effects in terms of MRSA bacteremia and true positive and negative test results. Inputted costs included laboratory testing, contact precautions and infection control, private room costs, housekeeping, and length of hospital stay. Deterministic sensitivity analyses were conducted.The risk factor-based MRSA screening program screened approximately 30% of admitted patients and cost the hospital over $780 000 annually. The universal screening program screened approximately 83% of admitted patients and cost over $1.94 million dollars, representing an excess cost of $1.16 million per year. The estimated additional cost per patient screened was $17.76.This analysis demonstrated that a universal MRSA screening program was costly from a hospital perspective and was previously known to not be clinically effective at reducing MRSA transmission. These results may be useful to inform future model-based economic analyses of MRSA interventions.

Identification of important phenomena under sodium fire accidents based on PIRT process with factor analysis in sodium-cooled fast reactor

International Nuclear Information System (INIS)

Aoyagi, Mitsuhiro; Uchibori, Akihiro; Kikuchi, Shin; Takata, Takashi; Ohno, Shuji; Ohshima, Hiroyuki

2016-01-01

The PIRT (Phenomena Identification and Ranking Table) process is an effective method to identify key phenomena involved in safety issues in nuclear power plants. The present PIRT process is aimed to validate sodium fire analysis codes. Because a sodium fire accident in sodium-cooled fast reactor (SFR) involves complex phenomena, various figures of merit (FOMs) could exist in this PIRT process. In addition, importance evaluation of phenomena for each FOM should be implemented in an objective manner under the PIRT process. This paper describes the methodology for specification of FOMs, identification of associated phenomena and importance evaluation of each associated phenomenon in order to complete a ranking table of important phenomena involved in a sodium fire accident in an SFR. The FOMs were specified through factor analysis in this PIRT process. Physical parameters to be quantified by a sodium fire analysis code were identified by considering concerns resulting from sodium fire in the factor analysis. Associated phenomena were identified through the element- and sequence-based phenomena analyses as is often conducted in PIRT processes. Importance of each associated phenomenon was evaluated by considering the sequence-based analysis of associated phenomena correlated with the FOMs. Then, we complete the ranking table through the factor and phenomenon analyses. (author)

Factor Analysis of the Aggregated Electric Vehicle Load Based on Data Mining

Directory of Open Access Journals (Sweden)

Yao Wang

2012-06-01

Full Text Available Electric vehicles (EVs and the related infrastructure are being developed rapidly. In order to evaluate the impact of factors on the aggregated EV load and to coordinate charging, a model is established to capture the relationship between the charging load and important factors based on data mining. The factors can be categorized as internal and external. The internal factors include the EV battery size, charging rate at different places, penetration of the charging infrastructure, and charging habits. The external factor is the time-of-use pricing (TOU policy. As a massive input data is necessary for data mining, an algorithm is implemented to generate a massive sample as input data which considers real-world travel patterns based on a historical travel dataset. With the input data, linear regression was used to build a linear model whose inputs were the internal factors. The impact of the internal factors on the EV load can be quantified by analyzing the sign, value, and temporal distribution of the model coefficients. The results showed that when no TOU policy is implemented, the rate of charging at home and range anxiety exerts the greatest influence on EV load. For the external factor, a support vector regression technique was used to build a relationship between the TOU policy and EV load. Then, an optimization model based on the relationship was proposed to devise a TOU policy that levels the load. The results suggest that implementing a TOU policy reduces the difference between the peak and valley loads remarkably.

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

Science.gov (United States)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors

Energy Technology Data Exchange (ETDEWEB)

Liu, Xueqin [State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875 (China); National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China); School of Social Development and Public Policy, Beijing Normal University, Beijing 100875 (China); Li, Ning [State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875 (China); Yuan, Shuai, E-mail: syuan@nmemc.org.cn [National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China); Xu, Ning; Shi, Wenqin; Chen, Weibin [National Marine Environmental Monitoring Center, State Oceanic Administration, Dalian 116023 (China)

2015-12-15

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54 years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10 years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. - Highlights: • A method to estimate the multidimensional joint return periods is presented. • 2D function allows better fitting results at the lower tail of hazard factors. • Three-dimensional simulation has obvious advantages in extreme value fitting. • Joint return periods are closer to the reality

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors

International Nuclear Information System (INIS)

Liu, Xueqin; Li, Ning; Yuan, Shuai; Xu, Ning; Shi, Wenqin; Chen, Weibin

2015-01-01

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54 years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10 years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. - Highlights: • A method to estimate the multidimensional joint return periods is presented. • 2D function allows better fitting results at the lower tail of hazard factors. • Three-dimensional simulation has obvious advantages in extreme value fitting. • Joint return periods are closer to the reality

Study of Sesame (Sesame indicum L. Cultivars based on Morphological Characteristics Under Water Deficit Stress Condition Using Factor Analysis

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A Asghari

2014-03-01

Full Text Available In order to evaluation sesame cultivars based on morphological characteristics under water deficit stress condition using factor analysis, an experiment was conducted as a split plot based on randomized complete block design with three replications during 2009 in Research Center of Agriculture and Natural Resources in Parsabad. In this experiment, irrigation as the main factor at three levels (50, 75 and 100 percent of crop water requirement and ten sesame cultivars as the sub-factor were studied. The water requirement of sesame was calculated using CROPWAT software (Penman-Monteith method according to FAO-56. Results showed significant differences between the cultivars and the irrigation levels for all studied traits. Interaction between cultivars and irrigation levels was significant for some of traits. Comparisons of means showed that in water deficit condition, yield and all of traits reduced. In all traits the greatest amounts observed in complete irrigation treatment. In 50 percent of water requirement treatment, amount of leaf chlorophyll, root length, root branches and root length/plant height ratio were greater than other treatments. The Karaj1, Ultan, Naze and IS cultivars were better than other cultivars in stress and non stress condition. In factor analysis 5 and 4 first factors in non stress and stress condition explained 91.36 and 89.52 percent of trait variance, respectively. Grouping of sesame cultivars based on first and second factors in non stress conditions showed that Karaj1, Ultan and Naze cultivars were better than other cultivars. Also, in stress conditions Karaj1 and Ultan cultivars grouped as water deficit stress and better cultivars.

Single-stage unity power factor based electronic ballast

Indian Academy of Sciences (India)

This paper deals with the design, modeling, analysis and implementation of unity power factor (UPF) based electronic ballast for a fluorescent lamp (FL). The proposed electronic ballast uses a boost AC–DC converter as a power factor corrector (PFC) to improve the power quality at the input ac mains. In this singlestage ...

Influencing Factors of Catering and Food Service Industry Based on Principal Component Analysis

OpenAIRE

Zi Tang

2014-01-01

Scientific analysis of influencing factors is of great importance for the healthy development of catering and food service industry. This study attempts to present a set of critical indicators for evaluating the contribution of influencing factors to catering and food service industry in the particular context of Harbin City, Northeast China. Ten indicators that correlate closely with catering and food service industry were identified and performed by the principal component analysis method u...

Research on Human-Error Factors of Civil Aircraft Pilots Based On Grey Relational Analysis

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Guo Yundong

2018-01-01

Full Text Available In consideration of the situation that civil aviation accidents involve many human-error factors and show the features of typical grey systems, an index system of civil aviation accident human-error factors is built using human factor analysis and classification system model. With the data of accidents happened worldwide between 2008 and 2011, the correlation between human-error factors can be analyzed quantitatively using the method of grey relational analysis. Research results show that the order of main factors affecting pilot human-error factors is preconditions for unsafe acts, unsafe supervision, organization and unsafe acts. The factor related most closely with second-level indexes and pilot human-error factors is the physical/mental limitations of pilots, followed by supervisory violations. The relevancy between the first-level indexes and the corresponding second-level indexes and the relevancy between second-level indexes can also be analyzed quantitatively.

Determining the Number of Factors in P-Technique Factor Analysis

Science.gov (United States)

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

Directory of Open Access Journals (Sweden)

An Gie Yong

2013-10-01

Full Text Available The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.

Analysis of factors that inhibiting implementation of Information Security Management System (ISMS) based on ISO 27001

Science.gov (United States)

Tatiara, R.; Fajar, A. N.; Siregar, B.; Gunawan, W.

2018-03-01

The purpose of this research is to determine multi factors that inhibiting the implementation of the ISMS based on ISO 2700. It is also to propose a follow-up recommendation on the factors that inhibit the implementation of the ISMS. Data collection is derived from questionnaires to 182 respondents from users in data center operation (DCO) at bca, Indonesian telecommunication international (telin), and data centre division at Indonesian Ministry of Health. We analysing data collection with multiple linear regression analysis and paired t-test. The results are multiple factors which inhibiting the implementation of the ISMS from the three organizations which has implement and operate the ISMS, ISMS documentation management, and continual improvement. From this research, we concluded that the processes of implementation in ISMS is the necessity of the role of all parties in succeeding the implementation of the ISMS continuously.

Factor investing based on Musharakah principle

Science.gov (United States)

Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md; Amin, Mohd Nazrul Mohd

2015-10-01

Shariah stock investing has become a widely discussed topic in financial industry as part of today's investment strategy. The strategy primarily applies market capitalization allocations. However, some researchers have argued that market capitalization weighting is inherently flawed and have advocated replacing market capitalization allocations with factor allocations. In this paper, we discuss the rationale for factor investing based on Musharakah principle. The essential elements or factors of Musharakah principle such as business sector, management capability, profitability growth and capital efficiency are embedded in the Shariah-compliant stock. We then transform these factors into indexation for better analysis and performance measurement. Investment universe for this research covers Malaysian stocks for the period of January 2009 to December 2013. We found out that these factor indexes have historically earned excess returns over market capitalization weighted indexes and experienced higher Sharpe Ratios.

Framework Design and Influencing Factor Analysis of a Water Environmental Functional Zone-Based Effluent Trading System

Science.gov (United States)

Chen, Lei; Han, Zhaoxing; Li, Shuang; Shen, Zhenyao

2016-10-01

The efficacy of traditional effluent trading systems is questionable due to their neglect of seasonal hydrological variation and the creation of upstream hot spots within a watershed. Besides, few studies have been conducted to distinguish the impacts of each influencing factor on effluent trading systems outputs. In this study, a water environmental functional zone-based effluent trading systems framework was configured and a comprehensive analysis of its influencing factors was conducted. This proposed water environmental functional zone-based effluent trading systems was then applied for the control of chemical oxygen demand in the Beiyun River watershed, Beijing, China. Optimal trading results highlighted the integration of water quality constraints and different hydrological seasons, especially for downstream dischargers. The optimal trading of each discharger, in terms of pollutant reduction load and abatement cost, is greatly influenced by environmental and political factors such as background water quality, the location of river assessment points, and tradable discharge permits. In addition, the initial permit allowance has little influence on the market as a whole but does impact the individual discharger. These results provide information that is critical to understanding the impact of policy design on the functionality of an effluent trading systems.

Framework Design and Influencing Factor Analysis of a Water Environmental Functional Zone-Based Effluent Trading System.

Science.gov (United States)

Chen, Lei; Han, Zhaoxing; Li, Shuang; Shen, Zhenyao

2016-10-01

The efficacy of traditional effluent trading systems is questionable due to their neglect of seasonal hydrological variation and the creation of upstream hot spots within a watershed. Besides, few studies have been conducted to distinguish the impacts of each influencing factor on effluent trading systems outputs. In this study, a water environmental functional zone-based effluent trading systems framework was configured and a comprehensive analysis of its influencing factors was conducted. This proposed water environmental functional zone-based effluent trading systems was then applied for the control of chemical oxygen demand in the Beiyun River watershed, Beijing, China. Optimal trading results highlighted the integration of water quality constraints and different hydrological seasons, especially for downstream dischargers. The optimal trading of each discharger, in terms of pollutant reduction load and abatement cost, is greatly influenced by environmental and political factors such as background water quality, the location of river assessment points, and tradable discharge permits. In addition, the initial permit allowance has little influence on the market as a whole but does impact the individual discharger. These results provide information that is critical to understanding the impact of policy design on the functionality of an effluent trading systems.

Factors affecting medication adherence in community-managed patients with hypertension based on the principal component analysis: evidence from Xinjiang, China.

Science.gov (United States)

Zhang, Yuji; Li, Xiaoju; Mao, Lu; Zhang, Mei; Li, Ke; Zheng, Yinxia; Cui, Wangfei; Yin, Hongpo; He, Yanli; Jing, Mingxia

2018-01-01

The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis. A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ 2 -test and a binary logistic regression model. This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications. Community management plays an important role in improving the patients' medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers.

[Habitat factor analysis for Torreya grandis cv. Merrillii based on spatial information technology].

Science.gov (United States)

Wang, Xiao-ming; Wang, Ke; Ao, Wei-jiu; Deng, Jin-song; Han, Ning; Zhu, Xiao-yun

2008-11-01

Torreya grandis cv. Merrillii, a tertiary survival plant, is a rare tree species of significant economic value and expands rapidly in China. Its special habitat factor analysis has the potential value to provide guide information for its planting, management, and sustainable development, because the suitable growth conditions for this tree species are special and strict. In this paper, the special habitat factors for T. grandis cv. Merrillii in its core region, i.e., in seven villages of Zhuji City, Zhejiang Province were analyzed with Principal Component Analysis (PCA) and a series of data, such as IKONOS image, Digital Elevation Model (DEM), and field survey data supported by the spatial information technology. The results showed that T. grandis cv. Merrillii exhibited high selectivity of environmental factors such as elevation, slope, and aspect. 96.22% of T. grandis cv. Merrillii trees were located at the elevation from 300 to 600 m, 97.52% of them were found to present on the areas whose slope was less than 300, and 74.43% of them distributed on sunny and half-sunny slopes. The results of PCA analysis indicated that the main environmental factors affecting the habitat of T. grandis cv. Merrillii were moisture, heat, and soil nutrients, and moisture might be one of the most important ecological factors for T. grandis cv. Merrillii due to the unique biological and ecological characteristics of the tree species.

Modeling Indicator Systems for Evaluating Environmental Sustainable Development Based on Factor Analysis

Institute of Scientific and Technical Information of China (English)

WU Hao; CHEN Xiaoling; HE Ying; HE Xiaorong; CAI Xiaobin; XU Keyan

2006-01-01

Indicator systems of environmental sustainable development in the Poyang Lake Basin are established from 51 elementary indexes by factor analysis, which is composed of four steps such as the factor model, the parameter estimation, the factor rotation and the factor score. Under the condition that the cumulative proportion is greater than 85%, 5 explicit factors of environmental sustainable development as well as its factor score by region are carried out. The result indicates some impact factors to the basin environmental in descending sort order are volume of water, volume of waste gas discharge, volume of solid wastes, the degree to comprehensive utilization of waste gas, waste water and solid wastes, the emission volume of waste gas, waste water and solid wastes. It is helpful and important to provide decision support for constituting sustainable development strategies and evaluate the sustainable development status of each city.

An easy guide to factor analysis

CERN Document Server

Kline, Paul

2014-01-01

Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, a

Factors affecting medication adherence in community-managed patients with hypertension based on the principal component analysis: evidence from Xinjiang, China

Directory of Open Access Journals (Sweden)

Zhang YJ

2018-05-01

Full Text Available Yuji Zhang,* Xiaoju Li,* Lu Mao, Mei Zhang, Ke Li, Yinxia Zheng, Wangfei Cui, Hongpo Yin, Yanli He, Mingxia Jing Department of Public Health, Shihezi University School of Medicine, Shihezi, Xinjiang, China *These authors contributed equally to this work Purpose: The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis.Patients and methods: A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ2-test and a binary logistic regression model.Results: This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications.Conclusion: Community management plays an important role in improving the patients’ medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers. Keywords: hypertension, medication adherence, factors, principal component analysis, community management, China

MOOC Success Factors: Proposal of an Analysis Framework

Directory of Open Access Journals (Sweden)

Margarida M. Marques

2017-10-01

Full Text Available Aim/Purpose: From an idea of lifelong-learning-for-all to a phenomenon affecting higher education, Massive Open Online Courses (MOOCs can be the next step to a truly universal education. Indeed, MOOC enrolment rates can be astoundingly high; still, their completion rates are frequently disappointingly low. Nevertheless, as courses, the participants’ enrolment and learning within the MOOCs must be considered when assessing their success. In this paper, the authors’ aim is to reflect on what makes a MOOC successful to propose an analysis framework of MOOC success factors. Background: A literature review was conducted to identify reported MOOC success factors and to propose an analysis framework. Methodology: This literature-based framework was tested against data of a specific MOOC and refined, within a qualitative interpretivist methodology. The data were collected from the ‘As alterações climáticas nos média escolares - Clima@EduMedia’ course, which was developed by the project Clima@EduMedia and was submitted to content analysis. This MOOC aimed to support science and school media teachers in the use of media to teach climate change Contribution: By proposing a MOOC success factors framework the authors are attempting to contribute to fill in a literature gap regarding what concerns criteria to consider a specific MOOC successful. Findings: This work major finding is a literature-based and empirically-refined MOOC success factors analysis framework. Recommendations for Practitioners: The proposed framework is also a set of best practices relevant to MOOC developers, particularly when targeting teachers as potential participants. Recommendation for Researchers: This work’s relevance is also based on its contribution to increasing empirical research on MOOCs. Impact on Society: By providing a proposal of a framework on factors to make a MOOC successful, the authors hope to contribute to the quality of MOOCs. Future Research: Future

Selective Sequential Zero-Base Budgeting Procedures Based on Total Factor Productivity Indicators

OpenAIRE

A. Ishikawa; E. F. Sudit

1981-01-01

The authors' purpose in this paper is to develop productivity-based sequential budgeting procedures designed to expedite identification of major problem areas in bugetary performance, as well as to reduce the costs associated with comprehensive zero-base analyses. The concept of total factor productivity is reviewed and its relations to ordinary and zero-based budgeting are discussed in detail. An outline for a selective sequential analysis based on monitoring of three key indicators of (a) i...

A load factor based mean-variance analysis for fuel diversification

Energy Technology Data Exchange (ETDEWEB)

Gotham, Douglas; Preckel, Paul; Ruangpattana, Suriya [State Utility Forecasting Group, Purdue University, West Lafayette, IN (United States); Muthuraman, Kumar [McCombs School of Business, University of Texas, Austin, TX (United States); Rardin, Ronald [Department of Industrial Engineering, University of Arkansas, Fayetteville, AR (United States)

2009-03-15

Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77-91). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights. (author)

Health-Related Lifestyle Factors and Sexual Dysfunction: A Meta-Analysis of Population-Based Research.

Science.gov (United States)

Allen, Mark S; Walter, Emma E

2018-04-01

-adjusted models and tests of potential moderators using meta-regression. Limitations include low statistical power in models testing diet, caffeine, and cannabis use as risk factors. Results provide compelling evidence that cigarette smoking, alcohol, and physical activity are important for sexual dysfunction. Insufficient research was available to draw conclusions regarding risk factors for premature ejaculation or for cannabis use as a risk factor. These findings should be of interest to clinicians treating men and women with complaints relating to symptoms of sexual dysfunction. Allen MS, Walter EE. Health-Related Lifestyle Factors and Sexual Dysfunction: A Meta-Analysis of Population-Based Research. J Sex Med 2018;15:458-475. Copyright © 2018 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Sustainable Manufacturing Practices in Malaysian Automotive Industry: Confirmatory Factor Analysis

OpenAIRE

Habidin, Nurul Fadly; Zubir, Anis Fadzlin Mohd; Fuz, Nursyazwani Mohd; Latip, Nor Azrin Md; Azman, Mohamed Nor Azhari

2015-01-01

Sustainable manufacturing practices (SMPs) have received enormous attention in current years as an effective solution to support the continuous growth and expansion of the automotive manufacturing industry. This reported study was conducted to examine confirmatory factor analysis for SMP such as manufacturing process, supply chain management, social responsibility, and environmental management based on automotive manufacturing industry. The results of confirmatory factor analysis show that fo...

Testing of technology readiness index model based on exploratory factor analysis approach

Science.gov (United States)

Ariani, AF; Napitupulu, D.; Jati, RK; Kadar, JA; Syafrullah, M.

2018-04-01

SMEs readiness in using ICT will determine the adoption of ICT in the future. This study aims to evaluate the model of technology readiness in order to apply the technology on SMEs. The model is tested to find if TRI model is relevant to measure ICT adoption, especially for SMEs in Indonesia. The research method used in this paper is survey to a group of SMEs in South Tangerang. The survey measures the readiness to adopt ICT based on four variables which is Optimism, Innovativeness, Discomfort, and Insecurity. Each variable contains several indicators to make sure the variable is measured thoroughly. The data collected through survey is analysed using factor analysis methodwith the help of SPSS software. The result of this study shows that TRI model gives more descendants on some indicators and variables. This result can be caused by SMEs owners’ knowledge is not homogeneous about either the technology that they are used, knowledge or the type of their business.

Factor analysis

CERN Document Server

Gorsuch, Richard L

2013-01-01

Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and sufficient discussion of applications for effective use. This includes not only theory but also the empirical evaluations of the importance of mathematical distinctions for applied scientific analysis.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

Science.gov (United States)

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a population-based survey

NARCIS (Netherlands)

Fens, Niki; van Rossum, Annelot G. J.; Zanen, Pieter; van Ginneken, Bram; van Klaveren, Rob J.; Zwinderman, Aeilko H.; Sterk, Peter J.

2013-01-01

Classification of COPD is currently based on the presence and severity of airways obstruction. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical,

Exploratory Bi-factor Analysis: The Oblique Case

OpenAIRE

Jennrich, Robert L.; Bentler, Peter M.

2011-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bi-factor rotation criterion designed to produce a rotated loading mat...

An information value based analysis of physical and climatic factors affecting dengue fever and dengue haemorrhagic fever incidence

Directory of Open Access Journals (Sweden)

Tripathi Nitin

2005-06-01

Full Text Available Abstract Background Vector-borne diseases are the most dreaded worldwide health problems. Although many campaigns against it have been conducted, Dengue Fever (DF and Dengue Haemorrhagic Fever (DHF are still the major health problems of Thailand. The reported number of dengue incidences in 1998 for the Thailand was 129,954, of which Sukhothai province alone reported alarming number of 682. It was the second largest epidemic outbreak of dengue after 1987. Government arranges the remedial facilities as and when dengue is reported. But, the best way to control is to prevent it from happening. This will be possible only when knowledge about the relationship of DF/DHF with climatic and physio-environmental agents is discovered. This paper explores empirical relationship of climatic factors rainfall, temperature and humidity with the DF/DHF incidences using multivariate regression analysis. Also, a GIS based methodology is proposed in this paper to explore the influence of physio-environmental factors on dengue incidences. Remotely sensed data provided important data about physical environment and have been used for many vector borne diseases. Information Values (IV method was utilised to derive influence of various factors in the quantitative terms. Researchers have not applied this type of analysis for dengue earlier. Sukhothai province was selected for the case study as it had high number of dengue cases in 1998 and also due to its diverse physical setting with variety of land use/land cover types. Results Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF/DHF. A composite analysis of these three factors with dengue incidences was carried out using multivariate regression analysis. Three empirical models ER-1, ER-2 and ER-3 were evaluated. It was found that these three factors have significant relation with DF/DHF incidences and can be related to

An SPSSR -Menu for Ordinal Factor Analysis

Directory of Open Access Journals (Sweden)

Mario Basto

2012-01-01

Full Text Available Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calculations. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It offers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper offers an SPSS dialog written in theR programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

A factor analysis to detect factors influencing building national brand

Directory of Open Access Journals (Sweden)

Naser Azad

Full Text Available Developing a national brand is one of the most important issues for development of a brand. In this study, we present factor analysis to detect the most important factors in building a national brand. The proposed study uses factor analysis to extract the most influencing factors and the sample size has been chosen from two major auto makers in Iran called Iran Khodro and Saipa. The questionnaire was designed in Likert scale and distributed among 235 experts. Cronbach alpha is calculated as 84%, which is well above the minimum desirable limit of 0.70. The implementation of factor analysis provides six factors including “cultural image of customers”, “exciting characteristics”, “competitive pricing strategies”, “perception image” and “previous perceptions”.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

Science.gov (United States)

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

Directory of Open Access Journals (Sweden)

Daniel Bartz

Full Text Available Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Factor analysis of multivariate data

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, A.A.; Mahadevan, R.

A brief introduction to factor analysis is presented. A FORTRAN program, which can perform the Q-mode and R-mode factor analysis and the singular value decomposition of a given data matrix is presented in Appendix B. This computer program, uses...

Recurrent Neural Network Based Boolean Factor Analysis and its Application to Word Clustering

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.

2009-01-01

Roč. 20, č. 7 (2009), s. 1073-1086 ISSN 1045-9227 R&D Projects: GA MŠk(CZ) 1M0567 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.889, year: 2009

Analysis of Human Error Types and Performance Shaping Factors in the Next Generation Main Control Room

International Nuclear Information System (INIS)

Sin, Y. C.; Jung, Y. S.; Kim, K. H.; Kim, J. H.

2008-04-01

Main control room of nuclear power plants has been computerized and digitalized in new and modernized plants, as information and digital technologies make great progresses and become mature. Survey on human factors engineering issues in advanced MCRs: Model-based approach, Literature survey-based approach. Analysis of human error types and performance shaping factors is analysis of three human errors. The results of project can be used for task analysis, evaluation of human error probabilities, and analysis of performance shaping factors in the HRA analysis

Factor analysis and scintigraphy

International Nuclear Information System (INIS)

Di Paola, R.; Penel, C.; Bazin, J.P.; Berche, C.

1976-01-01

The goal of factor analysis is usually to achieve reduction of a large set of data, extracting essential features without previous hypothesis. Due to the development of computerized systems, the use of largest sampling, the possibility of sequential data acquisition and the increase of dynamic studies, the problem of data compression can be encountered now in routine. Thus, results obtained for compression of scintigraphic images were first presented. Then possibilities given by factor analysis for scan processing were discussed. At last, use of this analysis for multidimensional studies and specially dynamic studies were considered for compression and processing [fr

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

Science.gov (United States)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Coloured Letters and Numbers (CLaN): A reliable factor-analysis based synaesthesia questionnaire

OpenAIRE

Rothen Nicolas; Tsakanikos Elias; Meier Beat; Ward Jamie

2013-01-01

Synaesthesia is a heterogeneous phenomenon even when considering one particular sub type. The purpose of this study was to design a reliable and valid questionnaire for grapheme colour synaesthesia that captures this heterogeneity. By the means of a large sample of 628 synaesthetes and a factor analysis we created the Coloured Letters and Numbers (CLaN) questionnaire with 16 items loading on 4 different factors (i.e. localisation automaticity/attention deliberate use and longitudinal changes)...

Risk factors for financial hardship in patients receiving adjuvant chemotherapy for colon cancer: a population-based exploratory analysis.

Science.gov (United States)

Shankaran, Veena; Jolly, Sanjay; Blough, David; Ramsey, Scott D

2012-05-10

Characteristics that predispose patients to financial hardship during cancer treatment are poorly understood. We therefore conducted a population-based exploratory analysis of potential factors associated with financial hardship and treatment nonadherence during and following adjuvant chemotherapy for colon cancer. Patients diagnosed with stage III colon cancer between 2008 and 2010 were identified from a population-based cancer registry representing 13 counties in Washington state. Patients were asked to complete a comprehensive survey on treatment-related costs. Patients were considered to have experienced financial hardship if they accrued debt, sold or refinanced their home, borrowed money from friends or family, or experienced a 20% or greater decline in their annual income as a result of treatment-related expenses. Logistic regression analysis was used to investigate factors associated with financial hardship and treatment nonadherence. A total of 284 responses were obtained from 555 eligible patients (response rate, 51.2%). Nearly all patients in the final sample were insured during treatment. In this sample, 38% of patients reported one or more financial hardships as a result of treatment. The factors most closely associated with treatment-related financial hardship were younger age and lower annual household income. Younger age, lower income, and unemployment or disability (which occurred in most instances following diagnosis) were most closely associated with treatment nonadherence. A significant proportion of patients undergoing adjuvant chemotherapy for stage III colon cancer may experience financial hardship, despite having health insurance coverage. Interventions to help at-risk patients early on during therapy may prevent long-term financial adverse effects.

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

Ku, J.Y.; Chang, L.K.; Mohr, D.

1994-01-01

Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype, Experimental Breeder Reactor II. The uncertainty factors were applied to the channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A ''semistatistical horizontal method'' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

Ku, J.Y.; Chang, L.K.; Mohr, D.

2004-01-01

Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype. Experimental Breeder Reactor II. The uncertainty factors were applied to the hot channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A 'semistatistical horizontal method' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived. (author)

Multiple timescale analysis and factor analysis of energy ecological footprint growth in China 1953-2006

International Nuclear Information System (INIS)

Chen Chengzhong; Lin Zhenshan

2008-01-01

Scientific analysis of energy consumption and its influencing factors is of great importance for energy strategy and policy planning. The energy consumption in China 1953-2006 is estimated by applying the energy ecological footprint (EEF) method, and the fluctuation periods of annual China's per capita EEF (EEF cpc ) growth rate are analyzed with the empirical mode decomposition (EMD) method in this paper. EEF intensity is analyzed to depict energy efficiency in China. The main timescales of the 37 factors that affect the annual growth rate of EEF cpc are also discussed based on EMD and factor analysis methods. Results show three obvious undulation cycles of the annual growth rate of EEF cpc , i.e., 4.6, 14.4 and 34.2 years over the last 53 years. The analysis findings from the common synthesized factors of IMF1, IMF2 and IMF3 timescales of the 37 factors suggest that China's energy policy-makers should attach more importance to stabilizing economic growth, optimizing industrial structure, regulating domestic petroleum exploitation and improving transportation efficiency

A social work study using factor analysis on detecting important factors creating stress: A case study of hydro-power employees

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Batoul Aminjafari

2012-08-01

Full Text Available The study performs an empirical study based on the implementation of factor analysis to detect different factors influencing people to have more stress in a hydropower unit located in city of Esfahan, Iran. The study performed the survey among all 81 people who were working for customer service section of this company and consisted of two parts, in the first part; we gather all private information such as age, gender, education, job experience, etc. through seven important questions. In the second part of the survey, there were 66 questions, which included all the relevant factors impacting employees' stress. Cronbach alpha was calculated as 0.946, which is well above the minimum acceptable level. The implementation of factor analysis has detected 16 important groups of factors and each factor is determined by an appropriate name. The results of our factor analysis show that among different factors, difficulty of working condition as well as work pressure are two most important factors increasing stress among employees.

A human factor analysis of a radiotherapy accident

International Nuclear Information System (INIS)

Thellier, S.

2009-01-01

Since September 2005, I.R.S.N. studies activities of radiotherapy treatment from the angle of the human and organizational factors to improve the reliability of treatment in radiotherapy. Experienced in nuclear industry incidents analysis, I.R.S.N. analysed and diffused in March 2008, for the first time in France, the detailed study of a radiotherapy accident from the angle of the human and organizational factors. The method used for analysis is based on interviews and documents kept by the hospital. This analysis aimed at identifying the causes of the difference recorded between the dose prescribed by the radiotherapist and the dose effectively received by the patient. Neither verbal nor written communication (intra-service meetings and protocols of treatment) allowed information to be transmitted correctly in order to permit radiographers to adjust the irradiation zones correctly. This analysis highlighted the fact that during the preparation and the carrying out of the treatment, various factors led planned controls to not be performed. Finally, this analysis highlighted the fact that unsolved areas persist in the report over this accident. This is due to a lack of traceability of a certain number of key actions. The article concluded that there must be improvement in three areas: cooperation between the practitioners, control of the actions and traceability of the actions. (author)

An Analysis of the Factors Influencing the Adoption of Activity Based Costing (ABC in the Financial Sector in Jamaica

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Phillip C. James

2013-07-01

Full Text Available Financial institutions are increasingly operating in a highly competitively environment and therefore cost management has become an imperative. This paper investigates the factors influencing the adoption of activity-based costing (ABC methodology within the financial sector in Jamaica. Quantitative analysis was done using the generalized linear logistic regression model. The results show that there are three main factors that are statistically significant in the decision to implement an ABC system, these are: companies perception of the ability of ABC to assist in cost control, the proportion of overhead to total cost and finally, the action of competitors, that is, whether a competitor adopts the ABC methodology

Risk analysis-based food safety policy: scientific factors versus socio-cultural factors

NARCIS (Netherlands)

Rosa, P.; Knapen, van F.; Brom, F.W.A.

2008-01-01

The purpose of this article is to illustrate the importance of socio-cultural factors in risk management and the need to incorporate these factors in a standard, internationally recognized (wto) framework. This was achieved by analysing the relevance of these factors in 3 cases
The purpose of

Identification of advanced human factors engineering analysis, design and evaluation methods

International Nuclear Information System (INIS)

Plott, C.; Ronan, A. M.; Laux, L.; Bzostek, J.; Milanski, J.; Scheff, S.

2006-01-01

NUREG-0711 Rev.2, 'Human Factors Engineering Program Review Model,' provides comprehensive guidance to the Nuclear Regulatory Commission (NRC) in assessing the human factors practices employed by license applicants for Nuclear Power Plant control room designs. As software based human-system interface (HSI) technologies supplant traditional hardware-based technologies, the NRC may encounter new HSI technologies or seemingly unconventional approaches to human factors design, analysis, and evaluation methods which NUREG-0711 does not anticipate. A comprehensive survey was performed to identify advanced human factors engineering analysis, design and evaluation methods, tools, and technologies that the NRC may encounter in near term future licensee applications. A review was conducted to identify human factors methods, tools, and technologies relevant to each review element of NUREG-0711. Additionally emerging trends in technology which have the potential to impact review elements, such as Augmented Cognition, and various wireless tools and technologies were identified. The purpose of this paper is to provide an overview of the survey results and to highlight issues that could be revised or adapted to meet with emerging trends. (authors)

Influencing Factors and Development Trend Analysis of China Electric Grid Investment Demand Based on a Panel Co-Integration Model

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Jinchao Li

2018-01-01

Full Text Available Electric grid investment demand analysis is significant to reasonably arranging construction funds for the electric grid and reduce costs. This paper used the panel data of electric grid investment from 23 provinces of China between 2004 and 2016 as samples to analyze the influence between electric grid investment demand and GDP, population scale, social electricity consumption, installed electrical capacity, and peak load based on co-integration tests. We find that GDP and peak load have positive influences on electric grid investment demand, but the impact of population scale, social electricity consumption, and installed electrical capacity on electric grid investment is not remarkable. We divide different regions in China into the eastern region, central region, and western region to analyze influence factors of electric grid investment, finally obtaining key factors in the eastern, central, and western regions. In the end, according to the analysis of key factors, we make a prediction about China’s electric grid investment for 2020 in different scenarios. The results offer a certain understanding for the development trend of China’s electric grid investment and contribute to the future development of electric grid investment.

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

Exploratory Bi-Factor Analysis: The Oblique Case

Science.gov (United States)

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

Human factor analysis and preventive countermeasures of maintenance in nuclear power plant

International Nuclear Information System (INIS)

Zhang Li; Hu Chao

2008-01-01

Based on the human error analysis theory and the characteristics of maintenance in a nuclear power plant, human factors of maintenance in NPP are divided into three different areas: human, technology, and organization, in which human refers to the individual factors, mainly including psychological quality, physiological characteristic, state of health, knowledge, skill level, and interpersonal relationship. Technology includes the maintenance technology, maintenance strategy, maintenance tool, maintenance interface, maintenance regulation, and work environment. Organization includes task arrangement, information communication, training, personnel external environment, team construction, and leadership. The analysis also reveals that the organization factors, which can indirectly influence personnel performance, are the primary initiators of human error. Based on these, some countermeasures are brought forward in order to reduce human errors. (authors)

Analysis and design of permanent magnet biased magnetic bearing based on hybrid factor

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Jinji Sun

2016-03-01

Full Text Available In this article, hybrid factor is proposed for hybrid magnetic bearing. The hybrid factor is defined as the ratio of the force produced by the permanent magnet and the forces produced by the permanent magnet and current in hybrid magnetic bearing. It is deduced from a certain radial hybrid magnetic bearing using its important parameters such as the current stiffness and displacement stiffness at first and then the dynamic model of magnetically suspended rotor system is established. The relationship between structural parameters and control system parameters is analyzed based on the hybrid factor. Some influencing factors of hybrid factor in hybrid magnetic bearing, such as the size of the permanent magnet, length of air gap, and area of the stator poles, are analyzed in this article. It can be concluded that larger hybrid factor can be caused by the smaller power loss according to the definition of hybrid factor mentioned above. Meanwhile, the hybrid factor has a maximum value, which is related to control system parameters such as proportional factor expect for structural parameters. Finally, the design steps of parameters of hybrid magnetic bearing can be concluded.

Human factor analysis related to new symptom based procedures used by control room crews during treatment of emergency states

International Nuclear Information System (INIS)

Holy, J.

1999-01-01

New symptom based emergency procedures have been developed for Nuclear Power Plant Dukovany in the Czech Republic. As one point of the process of verification and validation of the procedures, a specific effort was devoted to detailed analysis of the procedures from human factors and human reliability point of view. The course and results of the analysis are discussed in this article. Although the analyzed procedures have been developed for one specific plant of WWER-440/213 type, most of the presented results may be valid for many other procedures recently developed for semi-automatic control of those technological units which are operated under measurable level of risk. (author)

The curative effects of radiotherapy-based therapies for human epidermal growth factor receptor 2-positive breast cancer: A meta-analysis.

Science.gov (United States)

Shao, Minghai; Zhang, Chi; Qin, Qin; Zhang, Zhaoyue; Zhu, Hongcheng; Di, Xiaoke; Sun, Xinchen

2017-09-01

This meta-analysis was designed to fully assess the curative effects of radiotherapy-based therapies for human epidermal growth factor receptor 2-positive (HER2+) breast cancer (BC). English articles were retrieved through searching Cochrane library, PubMed, and Embase databases updated to February 2017. Studies were selected based on the inclusion and exclusion criteria. The curative effects of radiotherapy-based therapies forHER2+ BC patients were assessed using hazard rates (HRs) or odds ratios (ORs), as well as their 95% confidence intervals (CIs). In addition, Egger test was used to assess publication bias, followed by sensitivity analysis. All statistic methods were conducted using R 3.12 software. A total of 9 eligible studies were included into this meta-analysis, which involved 2236 HER2+ BC patients. Egger test showed that the eligible studies had no publication bias (t = 2.198, P = .05918). Sensitivity analysis demonstrated that the results were stable. HER2+ BC patients in radiotherapy group had lower locoregional recurrences than those in other groups. Moreover, meta-analysis showed that no significant difference was found between HER2+ BC patients in radiotherapy group and other groups on the 1-year overall survival (P = 0.5263, I = 65.4%), 3-year overall survival (P = 0.4591, I = 0), and 5-year overall survival (P = 0.06277, I = 0). Radiotherapy-based therapies might have certain advantages in treating HER2+ BC patients.

Risk factor analysis of equine strongyle resistance to anthelmintics

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G. Sallé

2017-12-01

Full Text Available Intestinal strongyles are the most problematic endoparasites of equids as a result of their wide distribution and the spread of resistant isolates throughout the world. While abundant literature can be found on the extent of anthelmintic resistance across continents, empirical knowledge about associated risk factors is missing. This study brought together results from anthelmintic efficacy testing and risk factor analysis to provide evidence-based guidelines in the field. It involved 688 horses from 39 French horse farms and riding schools to both estimate Faecal Egg Count Reduction (FECR after anthelmintic treatment and to interview farm and riding school managers about their practices. Risk factors associated with reduced anthelmintic efficacy in equine strongyles were estimated across drugs using a marginal modelling approach. Results demonstrated ivermectin efficacy (96.3% ± 14.5% FECR, the inefficacy of fenbendazole (42.8% ± 33.4% FECR and an intermediate profile for pyrantel (90.3% ± 19.6% FECR. Risk factor analysis provided support to advocate for FEC-based treatment regimens combined with individual anthelmintic dosage and the enforcement of tighter biosecurity around horse introduction. The combination of these measures resulted in a decreased risk of drug resistance (relative risk of 0.57, p = 0.02. Premises falling under this typology also relied more on their veterinarians suggesting practitionners play an important role in the sustainability of anthelmintic usage. Similarly, drug resistance risk was halved in premises with frequent pasture rotation and with stocking rate below five horses/ha (relative risk of 0.53, p < 0.01. This is the first empirical risk factor analysis for anthelmintic resistance in equids. Our findings should guide the implementation of more sustained strongyle management in the field. Keywords: Horse, Nematode, Anthelmintic resistance, Strongyle, Cyathostomin

Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

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Hesse Morten

2005-05-01

Full Text Available Abstract Background Personality disorders are common in substance abusers. Self-report questionnaires that can aid in the assessment of personality disorders are commonly used in assessment, but are rarely validated. Methods The Danish DIP-Q as a measure of co-morbid personality disorders in substance abusers was validated through principal components factor analysis and canonical correlation analysis. A 4 components structure was constructed based on 238 protocols, representing antagonism, neuroticism, introversion and conscientiousness. The structure was compared with (a a 4-factor solution from the DIP-Q in a sample of Swedish drug and alcohol abusers (N = 133, and (b a consensus 4-components solution based on a meta-analysis of published correlation matrices of dimensional personality disorder scales. Results It was found that the 4-factor model of personality was congruent across the Danish and Swedish samples, and showed good congruence with the consensus model. A canonical correlation analysis was conducted on a subset of the Danish sample with staff ratings of pathology. Three factors that correlated highly between the two variable sets were found. These variables were highly similar to the three first factors from the principal components analysis, antagonism, neuroticism and introversion. Conclusion The findings support the validity of the DIP-Q as a measure of DSM-IV personality disorders in substance abusers.

Systems competing for mobile factors: decision making based on hard vs. soft locational factors

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Clodnițchi Roxana

2017-12-01

Full Text Available The paper explores the links between capital relocation and soft locational factors addressing the quality of the business environment and the quality of life within the European Union. System competition is viewed as a competition between countries for the mobile factors capital and labour. The issue of systems competition is topical and insufficiently explored by contemporary literature. The scarcity of scientific papers describing the links between system competition theories and contemporary corporate geography theories, especially of the ones including the analysis of soft location factors, is a challenging aspect, which motivates the choice of this subject. This paper’s primary aim is to deliver an overview of the basic corporate geography conceptions, stressing the importance of soft location factors in today’s competition between systems for the mobile factors capital and labour. The paper further contains an analysis of the correlations between indicators regarding the institutional design of countries as developed by the World Bank (Ease of Doing Business, the Happiness Scale and the latest available data of FDI Stocks for the EU countries (2016. The relevance of such a study is based on the evidence that the contemporary business education relies on an extensive knowledge of the business environment. In the circumstance of similar infrastructural conditions, the main difference between locations is made by soft location factors. Since developed economies are characterised by a high degree of ubiquity of soft factors, the paper concludes that developing and emerging economies should foster the development of their soft location factors.

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

Science.gov (United States)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

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Maryam Kheirollahpour

2014-01-01

Full Text Available The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA was applied to reveal the hidden (secondary effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model.

Factor analysis for imperfect maintenance planning at nuclear power plants by cognitive task analysis

International Nuclear Information System (INIS)

Takagawa, Kenichi; Iida, Hiroyasu

2011-01-01

Imperfect maintenance planning was frequently identified in domestic nuclear power plants. To prevent such an event, we analyzed causal factors in maintenance planning stages and showed the directionality of countermeasures in this study. There is a pragmatic limit in finding the causal factors from the items based on report descriptions. Therefore, the idea of the systemic accident model, which is used to monitor the performance variability in normal circumstances, is taken as a new concept instead of investigating negative factors. As an actual method for analyzing usual activities, cognitive task analysis (CTA) was applied. Persons who experienced various maintenance activities at one electric power company were interviewed about sources related to decision making during maintenance planning, and then usual factors affecting planning were extracted as performance variability factors. The tendency of domestic events was analyzed using the classification item of those factors, and the directionality of countermeasures was shown. The following are critical for preventing imperfect maintenance planning: the persons in charge should fully understand the situation of the equipment for which they are responsible in the work planning and maintenance evaluation stages, and they should definitely understand, for example, the maintenance bases of that equipment. (author)

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

Science.gov (United States)

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

Science.gov (United States)

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

An analysis of main factors in electron beam flue gas purification

International Nuclear Information System (INIS)

Zhang Ming; Xu Guang

2003-01-01

Electron beam flue gas purification method is developing very quickly in recent years. Based on the experiment setting for electron beam flue gas purification in Institute of Nuclear Energy and Technology, Tsinghua University, how the technique factors affect the ratio of desulphurization and denitrogenation are described. Radiation dose (D), temperature (T), humidity (H), pour ammonia quantity (α) and initial concentration of SO 2 (C SO 2 ) and NO x (C NO x ) are main factors influencing flue gas purification. Using the methods of correlation analysis and regression analysis, the primary effect factors are found out and the regression equations are set to optimize the system process, predigest the system structure and to forecast the experimental results. (authors)

Genome wide analysis of stress responsive WRKY transcription factors in Arabidopsis thaliana

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Shaiq Sultan

2016-04-01

Full Text Available WRKY transcription factors are a class of DNA-binding proteins that bind with a specific sequence C/TTGACT/C known as W-Box found in promoters of genes which are regulated by these WRKYs. From previous studies, 43 different stress responsive WRKY transcription factors in Arabidopsis thaliana, identified and then categorized in three groups viz., abiotic, biotic and both of these stresses. A comprehensive genome wide analysis including chromosomal localization, gene structure analysis, multiple sequence alignment, phylogenetic analysis and promoter analysis of these WRKY genes was carried out in this study to determine the functional homology in Arabidopsis. This analysis led to the classification of these WRKY family members into 3 major groups and subgroups and showed evolutionary relationship among these groups on the base of their functional WRKY domain, chromosomal localization and intron/exon structure. The proposed groups of these stress responsive WRKY genes and annotation based on their position on chromosomes can also be explored to determine their functional homology in other plant species in relation to different stresses. The result of the present study provides indispensable genomic information for the stress responsive WRKY transcription factors in Arabidopsis and will pave the way to explain the precise role of various AtWRKYs in plant growth and development under stressed conditions.

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

Science.gov (United States)

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

Exploring Context and the Factors Shaping Team-Based Primary Healthcare Policies in Three Canadian Provinces: A Comparative Analysis.

Science.gov (United States)

Misfeldt, Renée; Suter, Esther; Mallinson, Sara; Boakye, Omenaa; Wong, Sabrina; Nasmith, Louise

2017-08-01

This paper discusses findings from a high-level scan of the contextual factors and actors that influenced policies on team-based primary healthcare in three Canadian provinces: British Columbia, Alberta and Saskatchewan. The team searched diverse sources (e.g., news reports, press releases, discussion papers) for contextual information relevant to primary healthcare teams. We also conducted qualitative interviews with key health system informants from the three provinces. Data from documents and interviews were analyzed qualitatively using thematic analysis. We then wrote narrative summaries highlighting pivotal policy and local system events and the influence of actors and context. Our overall findings highlight the value of reviewing the context, relationships and power dynamics, which come together and create "policy windows" at different points in time. We observed physician-centric policy processes with some recent moves to rebalance power and be inclusive of other actors and perspectives. The context review also highlighted the significant influence of changes in political leadership and prioritization in driving policies on team-based care. While this existed in different degrees in the three provinces, the push and pull of political and professional power dynamics shaped Canadian provincial policies governing team-based care. If we are to move team-based primary healthcare forward in Canada, the provinces need to review the external factors and the complex set of relationships and trade-offs that underscore the policy process. Copyright © 2017 Longwoods Publishing.

Evaluation of chemical transport model predictions of primary organic aerosol for air masses classified by particle-component-based factor analysis

OpenAIRE

C. A. Stroud; M. D. Moran; P. A. Makar; S. Gong; W. Gong; J. Zhang; J. G. Slowik; J. P. D. Abbatt; G. Lu; J. R. Brook; C. Mihele; Q. Li; D. Sills; K. B. Strawbridge; M. L. McGuire

2012-01-01

Observations from the 2007 Border Air Quality and Meteorology Study (BAQS-Met 2007) in Southern Ontario, Canada, were used to evaluate predictions of primary organic aerosol (POA) and two other carbonaceous species, black carbon (BC) and carbon monoxide (CO), made for this summertime period by Environment Canada's AURAMS regional chemical transport model. Particle component-based factor analysis was applied to aerosol mass spectrometer measurements made at one urban site (Windsor, ON) and two...

The Infinitesimal Jackknife with Exploratory Factor Analysis

Science.gov (United States)

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Molecular genetic analysis of activation-tagged transcription factors thought to be involved in photomorphogenesis

Energy Technology Data Exchange (ETDEWEB)

Neff, Michael M.

2011-06-23

This is a final report for Department of Energy Grant No. DE-FG02-08ER15927 entitled “Molecular Genetic Analysis of Activation-Tagged Transcription Factors Thought to be Involved in Photomorphogenesis”. Based on our preliminary photobiological and genetic analysis of the sob1-D mutant, we hypothesized that OBP3 is a transcription factor involved in both phytochrome and cryptochrome-mediated signal transduction. In addition, we hypothesized that OBP3 is involved in auxin signaling and root development. Based on our preliminary photobiological and genetic analysis of the sob2-D mutant, we also hypothesized that a related gene, LEP, is involved in hormone signaling and seedling development.

Left ventricular wall motion abnormalities evaluated by factor analysis as compared with Fourier analysis

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Ikuno, Yoshiyasu; Nishikimi, Toshio

1986-01-01

Factor analysis was applied to multigated cardiac pool scintigraphy to evaluate its ability to detect left ventricular wall motion abnormalities in 35 patients with old myocardial infarction (MI), and in 12 control cases with normal left ventriculography. All cases were also evaluated by conventional Fourier analysis. In most cases with normal left ventriculography, the ventricular and atrial factors were extracted by factor analysis. In cases with MI, the third factor was obtained in the left ventricle corresponding to wall motion abnormality. Each case was scored according to the coincidence of findings of ventriculography and those of factor analysis or Fourier analysis. Scores were recorded for three items; the existence, location, and degree of asynergy. In cases of MI, the detection rate of asynergy was 94 % by factor analysis, 83 % by Fourier analysis, and the agreement in respect to location was 71 % and 66 %, respectively. Factor analysis had higher scores than Fourier analysis, but this was not significant. The interobserver error of factor analysis was less than that of Fourier analysis. Factor analysis can display locations and dynamic motion curves of asynergy, and it is regarded as a useful method for detecting and evaluating left ventricular wall motion abnormalities. (author)

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

Science.gov (United States)

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

Analysis on Pollution Factors in Asparagus Production and Research on Safety Production Technology

OpenAIRE

Ma, Liping; Hao, Bianqing; Qiao, Xiongwu

2013-01-01

Based on the analysis on the infection degree, infection law and influencing factors of the main diseases on asparagus and the analysis on the pollution factors in asparagus production such as blind pesticide use, atmospheric pollution and acid rain, the pollution of soil and fertilizer, this article proposes asparagus safety production technologies which include the selection of disease-resistant variety and suitable planting field, scientific and reasonable disease control, balanced fertili...

A Confirmatory Factor Analysis of Reilly's Role Overload Scale

Science.gov (United States)

Thiagarajan, Palaniappan; Chakrabarty, Subhra; Taylor, Ronald D.

2006-01-01

In 1982, Reilly developed a 13-item scale to measure role overload. This scale has been widely used, but most studies did not assess the unidimensionality of the scale. Given the significance of unidimensionality in scale development, the current study reports a confirmatory factor analysis of the 13-item scale in two samples. Based on the…

A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

International Nuclear Information System (INIS)

Shen, Chen-Hua

2015-01-01

To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

A new detrended semipartial cross-correlation analysis: Assessing the important meteorological factors affecting API

Energy Technology Data Exchange (ETDEWEB)

Shen, Chen-Hua, E-mail: shenandchen01@163.com [College of Geographical Science, Nanjing Normal University, Nanjing 210046 (China); Jiangsu Center for Collaborative Innovation in Geographical Information Resource, Nanjing 210046 (China); Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing 210046 (China)

2015-12-04

To analyze the unique contribution of meteorological factors to the air pollution index (API), a new method, the detrended semipartial cross-correlation analysis (DSPCCA), is proposed. Based on both a detrended cross-correlation analysis and a DFA-based multivariate-linear-regression (DMLR), this method is improved by including a semipartial correlation technique, which is used to indicate the unique contribution of an explanatory variable to multiple correlation coefficients. The advantages of this method in handling nonstationary time series are illustrated by numerical tests. To further demonstrate the utility of this method in environmental systems, new evidence of the primary contribution of meteorological factors to API is provided through DMLR. Results show that the most important meteorological factors affecting API are wind speed and diurnal temperature range, and the explanatory ability of meteorological factors to API gradually strengthens with increasing time scales. The results suggest that DSPCCA is a useful method for addressing environmental systems. - Highlights: • A detrended multiple linear regression is shown. • A detrended semipartial cross correlation analysis is proposed. • The important meteorological factors affecting API are assessed. • The explanatory ability of meteorological factors to API gradually strengthens with increasing time scales.

Lithuanian Population Aging Factors Analysis

Directory of Open Access Journals (Sweden)

Agnė Garlauskaitė

2015-05-01

Full Text Available The aim of this article is to identify the factors that determine aging of Lithuania’s population and to assess the influence of these factors. The article shows Lithuanian population aging factors analysis, which consists of two main parts: the first describes the aging of the population and its characteristics in theoretical terms. Second part is dedicated to the assessment of trends that influence the aging population and demographic factors and also to analyse the determinants of the aging of the population of Lithuania. After analysis it is concluded in the article that the decline in the birth rate and increase in the number of emigrants compared to immigrants have the greatest impact on aging of the population, so in order to show the aging of the population, a lot of attention should be paid to management of these demographic processes.

An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

Science.gov (United States)

Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

2017-12-01

For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

SUPERPIXEL BASED FACTOR ANALYSIS AND TARGET TRANSFORMATION METHOD FOR MARTIAN MINERALS DETECTION

Directory of Open Access Journals (Sweden)

X. Wu

2018-04-01

Full Text Available The Factor analysis and target transformation (FATT is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

Human factors review for Severe Accident Sequence Analysis (SASA)

International Nuclear Information System (INIS)

Krois, P.A.; Haas, P.M.; Manning, J.J.; Bovell, C.R.

1984-01-01

The paper will discuss work being conducted during this human factors review including: (1) support of the Severe Accident Sequence Analysis (SASA) Program based on an assessment of operator actions, and (2) development of a descriptive model of operator severe accident management. Research by SASA analysts on the Browns Ferry Unit One (BF1) anticipated transient without scram (ATWS) was supported through a concurrent assessment of operator performance to demonstrate contributions to SASA analyses from human factors data and methods. A descriptive model was developed called the Function Oriented Accident Management (FOAM) model, which serves as a structure for bridging human factors, operations, and engineering expertise and which is useful for identifying needs/deficiencies in the area of accident management. The assessment of human factors issues related to ATWS required extensive coordination with SASA analysts. The analysis was consolidated primarily to six operator actions identified in the Emergency Procedure Guidelines (EPGs) as being the most critical to the accident sequence. These actions were assessed through simulator exercises, qualitative reviews, and quantitative human reliability analyses. The FOAM descriptive model assumes as a starting point that multiple operator/system failures exceed the scope of procedures and necessitates a knowledge-based emergency response by the operators. The FOAM model provides a functionally-oriented structure for assembling human factors, operations, and engineering data and expertise into operator guidance for unconventional emergency responses to mitigate severe accident progression and avoid/minimize core degradation. Operators must also respond to potential radiological release beyond plant protective barriers. Research needs in accident management and potential uses of the FOAM model are described. 11 references, 1 figure

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

Science.gov (United States)

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR

Directory of Open Access Journals (Sweden)

James Baglin

2014-06-01

Full Text Available Exploratory factor analysis (EFA methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many guidelines have been proposed with the aim to improve application. Unfortunately, implementing recommended EFA practices has been restricted by the range of options available in commercial statistical packages and, perhaps, due to an absence of clear, practical - how-to' demonstrations. Consequently, this article describes the application of methods recommended to get the most out of your EFA. The article focuses on dealing with the common situation of analysing ordinal data as derived from Likert-type scales. These methods are demonstrated using the free, stand-alone, easy-to-use and powerful EFA package FACTOR (http://psico.fcep.urv.es/utilitats/factor/, Lorenzo-Seva & Ferrando, 2006. The demonstration applies the recommended techniques using an accompanying dataset, based on the Big 5 personality test. The outcomes obtained by the EFA using the recommended procedures through FACTOR are compared to the default techniques currently available in SPSS.

Correlation analysis of lung cancer and urban spatial factor: based on survey in Shanghai.

Science.gov (United States)

Wang, Lan; Zhao, Xiaojing; Xu, Wangyue; Tang, Jian; Jiang, Xiji

2016-09-01

The density of particulate matter (PM) in mega-cities in China such as Beijing and Shanghai has exceeded basic standards for health in recent years. Human exposure to PMs has been identified as traceable and controllable factor among all complicated risk factors for lung cancer. While the improvement of air quality needs tremendous efforts and time, certain revision of PM's density might happen associated with the adjustment of built environment. It is also proved that urban built environment is directly relevant to respiratory disease. Studies have respectively explored the indoor and outdoor factors on respiratory diseases. More comprehensive spatial factors need to be analyzed to understand the cumulative effect of built environment upon respiratory system. This interdisciplinary study examines the impact of both indoor (including age of housing, interval after decoration, indoor humidity etc.) and outdoor spatial factors (including density, parking, green spaces etc.) on lung cancer. A survey of lung cancer patients and a control group has been conducted in 2014 and 2015. A total of 472 interviewees are randomly selected within a pool of local residents who have resided in Shanghai for more than 5 years. Data are collected including their socio-demographic factors, lifestyle factors, and external and internal residential area factors. Regression models are established based on collected data to analyze the associations between lung cancer and urban spatial factors. Regression models illustrate that lung cancer presents significantly associated with a number of spatial factors. Significant outdoor spatial factors include external traffic volume (P=0.003), main plant type (P=0.035 for trees) of internal green space, internal water body (P=0.027) and land use of surrounding blocks (P=0.005 for residential areas of 7-9 floors, P=0.000 for residential areas of 4-6 floors, P=0.006 for business/commercial areas over 10 floors, P=0.005 for business/commercial areas of

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

Science.gov (United States)

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sensitivity analysis practices: Strategies for model-based inference

Energy Technology Data Exchange (ETDEWEB)

Saltelli, Andrea [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (Vatican City State, Holy See,) (Italy)]. E-mail: andrea.saltelli@jrc.it; Ratto, Marco [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Tarantola, Stefano [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy); Campolongo, Francesca [Institute for the Protection and Security of the Citizen (IPSC), European Commission, Joint Research Centre, TP 361, 21020 Ispra (VA) (Italy)

2006-10-15

Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA.

Sensitivity analysis practices: Strategies for model-based inference

International Nuclear Information System (INIS)

Saltelli, Andrea; Ratto, Marco; Tarantola, Stefano; Campolongo, Francesca

2006-01-01

Fourteen years after Science's review of sensitivity analysis (SA) methods in 1989 (System analysis at molecular scale, by H. Rabitz) we search Science Online to identify and then review all recent articles having 'sensitivity analysis' as a keyword. In spite of the considerable developments which have taken place in this discipline, of the good practices which have emerged, and of existing guidelines for SA issued on both sides of the Atlantic, we could not find in our review other than very primitive SA tools, based on 'one-factor-at-a-time' (OAT) approaches. In the context of model corroboration or falsification, we demonstrate that this use of OAT methods is illicit and unjustified, unless the model under analysis is proved to be linear. We show that available good practices, such as variance based measures and others, are able to overcome OAT shortcomings and easy to implement. These methods also allow the concept of factors importance to be defined rigorously, thus making the factors importance ranking univocal. We analyse the requirements of SA in the context of modelling, and present best available practices on the basis of an elementary model. We also point the reader to available recipes for a rigorous SA

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis

Science.gov (United States)

Park, In-Hee; Venable, John D.; Steckler, Caitlin; Cellitti, Susan E.; Lesley, Scott A.; Spraggon, Glen; Brock, Ansgar

2015-01-01

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure and dynamics. More recently, Hydrogen Exchange Mass Spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from Molecular Dynamics (MD) simulation snapshots is used to determine partitioning over bonded and non-bonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for Fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of

47 CFR 69.502 - Base factor allocation.

Science.gov (United States)

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that is...

Institutional and Actor-Oriented Factors Constraining Expert-Based Forest Information Exchange in Europe: A Policy Analysis from an Actor-Centred Institutionalist Approach

Directory of Open Access Journals (Sweden)

Tanya Baycheva-Merger

2018-03-01

Full Text Available Adequate and accessible expert-based forest information has become increasingly in demand for effective decisions and informed policies in the forest and forest-related sectors in Europe. Such accessibility requires a collaborative environment and constant information exchange between various actors at different levels and across sectors. However, information exchange in complex policy environments is challenging, and is often constrained by various institutional, actor-oriented, and technical factors. In forest policy research, no study has yet attempted to simultaneously account for these multiple factors influencing expert-based forest information exchange. By employing a policy analysis from an actor-centred institutionalist perspective, this paper aims to provide an overview of the most salient institutional and actor-oriented factors that are perceived as constraining forest information exchange at the national level across European countries. We employ an exploratory research approach, and utilise both qualitative and quantitative methods to analyse our data. The data was collected through a semi-structured survey targeted at forest and forest-related composite actors in 21 European countries. The results revealed that expert-based forest information exchange is constrained by a number of compound and closely interlinked institutional and actor-oriented factors, reflecting the complex interplay of institutions and actors at the national level. The most salient institutional factors that stand out include restrictive or ambiguous data protection policies, inter-organisational information arrangements, different organisational cultures, and a lack of incentives. Forest information exchange becomes even more complex when actors are confronted with actor-oriented factors such as issues of distrust, diverging preferences and perceptions, intellectual property rights, and technical capabilities. We conclude that expert-based forest information

The mathematical pathogenetic factors analysis of acute inflammatory diseases development of bronchopulmonary system among infants

Directory of Open Access Journals (Sweden)

G. O. Lezhenko

2017-10-01

Full Text Available The purpose. To study the factor structure and to establish the associative interaction of pathogenetic links of acute diseases development of the bronchopulmonary system in infants.Materials and methods. The examination group consisted of 59 infants (average age 13.8 ± 1.4 months sick with acute inflammatory bronchopulmonary diseases. Also we tested the level of 25-hydroxyvitamin D (25(ОНD, vitamin D-binding protein, hBPI, cathelicidin LL-37, ß1-defensins, lactoferrin in blood serum with the help of immunoenzymometric analysis. Selection of prognostically important pathogenetic factors of acute bronchopulmonary disease among infants was conducted using ROC-analysis. The procedure for classifying objects was carried out using Hierarchical Cluster Analysis by the method of Centroid-based clustering. Results. Based on the results of the ROC-analysis were selected 15 potential predictors of the development of acute inflammatory diseases of the bronchopulmonary system among infants. The factor analysis made it possible to determine the 6 main components . The biggest influence in the development of the disease was made by "the anemia factor", "the factor of inflammation", "the maternal factor", "the vitamin D supply factor", "the immune factor" and "the phosphorus-calcium exchange factor” with a factor load of more than 0.6. The performed procedure of hierarchical cluster analysis confirmed the initial role of immuno-inflammatory components. The conclusions. The highlighted factors allowed to define a group of parameters, that must be influenced to achieve a maximum effect in carrying out preventive and therapeutic measures. First of all, it is necessary to influence the "the anemia factor" and "the calcium exchange factor", as well as the "the vitamin D supply factor". In other words, to correct vitamin D deficiency and carry out measures aimed at preventing the development of anemia. The prevention and treatment of the pathological course of

Investigating product development strategy in beverage industry using factor analysis

Directory of Open Access Journals (Sweden)

Naser Azad

2013-03-01

Full Text Available Selecting a product development strategy that is associated with the company's current service or product innovation, based on customers’ needs and changing environment, plays an important role in increasing demand, increasing market share, increasing sales and profits. Therefore, it is important to extract effective variables associated with product development to improve performance measurement of firms. This paper investigates important factors influencing product development strategies using factor analysis. The proposed model of this paper investigates 36 factors and, using factor analysis, we extract six most influential factors including information sharing, intelligence information, exposure strategy, differentiation, research and development strategy and market survey. The first strategy, partnership, includes five sub-factor including product development partnership, partnership with foreign firms, customers’ perception from competitors’ products, Customer involvement in product development, inter-agency coordination, customer-oriented approach to innovation and transmission of product development change where inter-agency coordination has been considered the most important factor. Internal strengths are the most influential factors impacting the second strategy, intelligence information. The third factor, introducing strategy, introducing strategy, includes four sub criteria and consumer buying behavior is the most influencing factor. Differentiation is the next important factor with five components where knowledge and expertise in product innovation is the most important one. Research and development strategy with four sub-criteria where reducing product development cycle plays the most influential factor and finally, market survey strategy is the last important factor with three factors and finding new market plays the most important role.

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

Science.gov (United States)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

First course in factor analysis

CERN Document Server

Comrey, Andrew L

2013-01-01

The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the mathematical basis of the most common factor analytic models and several methods used in factor analysis. On the application side, considerable attention is given to the extraction problem, the rotation problem, and the interpretation of factor analytic results. Hence, readers are given a background of

Scalable group level probabilistic sparse factor analysis

DEFF Research Database (Denmark)

Hinrich, Jesper Løve; Nielsen, Søren Føns Vind; Riis, Nicolai Andre Brogaard

2017-01-01

Many data-driven approaches exist to extract neural representations of functional magnetic resonance imaging (fMRI) data, but most of them lack a proper probabilistic formulation. We propose a scalable group level probabilistic sparse factor analysis (psFA) allowing spatially sparse maps, component...... pruning using automatic relevance determination (ARD) and subject specific heteroscedastic spatial noise modeling. For task-based and resting state fMRI, we show that the sparsity constraint gives rise to components similar to those obtained by group independent component analysis. The noise modeling...... shows that noise is reduced in areas typically associated with activation by the experimental design. The psFA model identifies sparse components and the probabilistic setting provides a natural way to handle parameter uncertainties. The variational Bayesian framework easily extends to more complex...

Factor analysis of the contextual fine motor questionnaire in children.

Science.gov (United States)

Lin, Chin-Kai; Meng, Ling-Fu; Yu, Ya-Wen; Chen, Che-Kuo; Li, Kuan-Hua

2014-02-01

Most studies treat fine motor as one subscale in a developmental test, hence, further factor analysis of fine motor has not been conducted. In fact, fine motor has been treated as a multi-dimensional domain from both clinical and theoretical perspectives, and therefore to know its factors would be valuable. The aim of this study is to analyze the internal consistency and factor validity of the Contextual Fine Motor Questionnaire (CFMQ). Based on the ecological observation and literature, the Contextual Fine Motor Questionnaire (CFMQ) was developed and includes 5 subscales: Pen Control, Tool Use During Handicraft Activities, the Use of Dining Utensils, Connecting and Separating during Dressing and Undressing, and Opening Containers. The main purpose of this study is to establish the factorial validity of the CFMQ through conducting this factor analysis study. Among 1208 questionnaires, 904 were successfully completed. Data from the children's CFMQ submitted by primary care providers was analyzed, including 485 females (53.6%) and 419 males (46.4%) from grades 1 to 5, ranging in age from 82 to 167 months (M=113.9, SD=16.3). Cronbach's alpha was used to measure internal consistency and explorative factor analysis was applied to test the five factor structures within the CFMQ. Results showed that Cronbach's alpha coefficient of the CFMQ for 5 subscales ranged from .77 to .92 and all item-total correlations with corresponding subscales were larger than .4 except one item. The factor loading of almost all items classified to their factor was larger than .5 except 3 items. There were five factors, explaining a total of 62.59% variance for the CFMQ. In conclusion, the remaining 24 items in the 5 subscales of the CFMQ had appropriate internal consistency, test-retest reliability and construct validity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Multiple factor analysis by example using R

CERN Document Server

Pagès, Jérôme

2014-01-01

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The

Network based transcription factor analysis of regenerating axolotl limbs

Directory of Open Access Journals (Sweden)

Cameron Jo Ann

2011-03-01

Full Text Available Abstract Background Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. Results We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets. Network analysis showed that TGF-β1 and fibronectin (FN lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1. Conclusions Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem

Liquidity indicator for the Croatian economy – Factor analysis approach

Directory of Open Access Journals (Sweden)

Mirjana Čižmešija

2014-12-01

Full Text Available Croatian business surveys (BS are conducted in the manufacturing industry, retail trade and construction sector. In all of these sectors, manager´s assessments of liquidity are measured. The aim of the paper was to form a new composite liquidity indicator by including business survey liquidity measures from all three covered economic sectors in the Croatian economy mentioned above. In calculating the leading indicator, a factor analysis approach was used. However, this kind of indicator does not exist in a Croatia or in any other European economy. Furthermore, the issue of Croatian companies´ illiquidity is highly neglected in the literature. The empirical analysis consists of two parts. In the first part the new liquidity indicator was formed using factor analysis. One factor (representing the new liquidity indicator; LI was extracted out of the three liquidity variables in three economic sectors. This factor represents the new liquidity indicator. In the second part, econometric models were applied in order to investigate the forecasting properties of the new business survey liquidity indicator, when predicting the direction of changes in Croatian industrial production. The quarterly data used in the research covered the period from January 2000 to April 2013. Based on econometric analysis, it can be concluded that the LI is a leading indicator of Croatia’s industrial production with better forecasting properties then the standard liquidity indicators (formed in a manufacturing industry.

Minerals sampling: sensibility analysis and correction factors for Pierre Gy's equation

International Nuclear Information System (INIS)

Vallebuona, G.; Niedbalski, F.

2005-01-01

Pierre Gy's equation is widely used in ore sampling. This equation is based in four parameters: shape factor, size distribution factor, mineralogical factor and liberation factor. The usual practice is to consider fixed values for the shape and size distribution factors. This practice does not represent well several important ores. The mineralogical factor considers only one specie of interest and the gangue, leaving out other cases such as polymetallic ores where there are more than one species of interest. A sensibility analysis to the Gy's equation factors was done and a procedure to determine specific values for them was developed and presented in this work. mean ore characteristics, associated with an insecure use of the actual procedure, were determined. finally, for a case study, the effects of using each alternative were evaluated. (Author) 4 refs

Confidence ellipses: A variation based on parametric bootstrapping applicable on Multiple Factor Analysis results for rapid graphical evaluation

DEFF Research Database (Denmark)

Dehlholm, Christian; Brockhoff, Per B.; Bredie, Wender L. P.

2012-01-01

A new way of parametric bootstrapping allows similar construction of confidence ellipses applicable on all results from Multiple Factor Analysis obtained from the FactoMineR package in the statistical program R. With this procedure, a similar approach will be applied to Multiple Factor Analysis r...... in different studies performed on the same set of products. In addition, the graphical display of confidence ellipses eases interpretation and communication of results....

Towards factor analysis exploration applied to positron emission tomography functional imaging for breast cancer characterization

International Nuclear Information System (INIS)

Rekik, W.; Ketata, I.; Sellami, L.; Ben slima, M.; Ben Hamida, A.; Chtourou, K.; Ruan, S.

2011-01-01

This paper aims to explore the factor analysis when applied to a dynamic sequence of medical images obtained using nuclear imaging modality, Positron Emission Tomography (PET). This latter modality allows obtaining information on physiological phenomena, through the examination of radiotracer evolution during time. Factor analysis of dynamic medical images sequence (FADMIS) estimates the underlying fundamental spatial distributions by factor images and the associated so-called fundamental functions (describing the signal variations) by factors. This method is based on an orthogonal analysis followed by an oblique analysis. The results of the FADMIS are physiological curves showing the evolution during time of radiotracer within homogeneous tissues distributions. This functional analysis of dynamic nuclear medical images is considered to be very efficient for cancer diagnostics. In fact, it could be applied for cancer characterization, vascularization as well as possible evaluation of response to therapy.

Analysis of mineral phases in coal utilizing factor analysis

International Nuclear Information System (INIS)

Roscoe, B.A.; Hopke, P.K.

1982-01-01

The mineral phase inclusions of coal are discussed. The contribution of these to a coal sample are determined utilizing several techniques. Neutron activation analysis in conjunction with coal washability studies have produced some information on the general trends of elemental variation in the mineral phases. These results have been enhanced by the use of various statistical techniques. The target transformation factor analysis is specifically discussed and shown to be able to produce elemental profiles of the mineral phases in coal. A data set consisting of physically fractionated coal samples was generated. These samples were analyzed by neutron activation analysis and then their elemental concentrations examined using TTFA. Information concerning the mineral phases in coal can thus be acquired from factor analysis even with limited data. Additional data may permit the resolution of additional mineral phases as well as refinement of theose already identified

Meta-Analysis of Comparing Personal and Environmental Factors Effective in Addiction Relapse (Iran, 2004 -2012

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s Safari

2014-12-01

Full Text Available Objective: This As a meta-analysis, this study aimed to integrate different studies and investigate the impact of individual and environmental factors on the reappearance of addiction in quitted people. Method: This study is a meta-analysis which uses Hunter and Schmidt approach. For this purpose, 28 out of 42 studies enjoying acceptable methodologies were selected, upon which the meta-analysis was conducted. A meta-analysis checklist was the research instrument. Using summary of the study results, the researcher manually calculated effect size and interpreted it based on the meta-analysis approach and Cohen’s table. Findings: Results revealed that the effect size of environmental factors on addiction relapse was 0.64 while it was obtained 0.41 for individual factors on addiction relapse. Conclusion: According to Cohen’s table, the effect sizes are evaluated as moderate and high for individual factors and environmental factors on addiction relapse, respectively.

Factors Affecting Green Residential Building Development: Social Network Analysis

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Xiaodong Yang

2018-05-01

Full Text Available Green residential buildings (GRBs are one of the effective practices of energy saving and emission reduction in the construction industry. However, many real estate developers in China are less willing to develop GRBs, because of the factors affecting green residential building development (GRBD. In order to promote the sustainable development of GRBs in China, this paper, based on the perspective of real estate developers, identifies the influential and critical factors affecting GRBD, using the method of social network analysis (SNA. Firstly, 14 factors affecting GRBD are determined from 64 preliminary factors of three main elements, and the framework is established. Secondly, the relationships between the 14 factors are analyzed by SNA. Finally, four critical factors for GRBD, which are on the local economy development level, development strategy and innovation orientation, developer’s acknowledgement and positioning for GRBD, and experience and ability for GRBD, are identified by the social network centrality test. The findings illustrate the key issues that affect the development of GRBs, and provide references for policy making by the government and strategy formulation by real estate developers.

A ORACLE-based system for data collection, storage and analysis of main equipment load factors in NPPs and TPPs

International Nuclear Information System (INIS)

Ivanova, L.

1993-01-01

This data base is developed by the National Electricity Company, Sofia (BG) as an aid to supervision, analysis and administration decision making in a variety of operational situations in NPPs and TPPs. As major indicators of the equipment condition the following primary data are stored: steam or electricity production per month; operation hours per month; equipment stand-by outages; planned outages; unplanned permitted maintenance outages; unplanned emergency maintenance outages; number of outages of the unit per month. These data cover the period from the putting of the corresponding equipment into operation till the present moment, i.e. or about 32 years. The data up to 1990 are annual and for the last three years - monthly. Based on these primary data, the following quantities are calculated: average capacity; average load factors; operation time factors - total and accounting for the planned and the permitted unplanned outages; unpermitted outages factors - total and accounting for the planned and the permitted outages. All the factors are calculated on user's request for a chosen time period, by summing up correspondingly the major indicators (production, operation hours and various outages) for the given period. The system operates on an IBM 4341 under VM/SP and DB ORACLE V.5. The input is entered directly from the TPP and NPP by telex lines from PCs, operating also as telex machines, into the mainframe of Energokibernetika Ltd. They are available to all authorised users from local terminals or PCs, connected to the computer by synchronous or asynchronous lines. A system for data transmission to remote users along commutated telephone lines is also developed. (R. Ts.)

Pin-wise Reactor Analysis Based on the Generalized Equivalence Theory

Energy Technology Data Exchange (ETDEWEB)

Yu, Hwan Yeal; Heo, Woong; Kim, Yong Hee [KAIST, Daejeon (Korea, Republic of)

2016-05-15

In this paper, a pin-wise reactor analysis is performed based on the generalized equivalence theory. From the conventional fuel assembly lattice calculations, pin-wise 2-group cross sections and pin DFs are generated. Based on the numerical results on a small PWR benchmark, it is observed that the pin-wise core analysis provide quite accurate prediction on the effective multiplication factor and the peak pin power error is bounded by about 3% in peripheral fuel assemblies facing the baffle-reflector. Also, it was found that relatively large pin power errors occur along the interface between clearly different fuel assemblies. It is expected that the GET-based pin-by-pin core calculation can be further developed as an advanced method for reactor analysis via improving the group constants and discontinuity factors. Recently, high-fidelity multi-dimensional analysis tools are gaining more attention because of their accurate prediction of local parameters for core design and safety assessment. In terms of accuracy, direct whole-core transport is quite promising. However, it is clear that it is still very costly in terms of the computing time and memory requirements. Another possible solution is the pin-by-pin core analysis in which only small fuel pins are homogenized and the 3-D core analysis is still performed using a low-order operator such as the diffusion theory. In this paper, a pin-by-pin core analysis is performed using the hybrid CMFD (HCMFD) method. Hybrid CMFD is a new global-local iteration method that has been developed for efficient parallel calculation of pinby-pin heterogeneous core analysis. For the HCMFD method, the one-node CMFD scheme is combined with a local two-node CMFD method in a non-linear way. Since the SPH method is iterative and SPH factors are not direction dependent, it is clear that SPH method takes more computing cost and cannot take into account the different heterogeneity and transport effects at each pin interface. Unlike the SPH

Perception on obesity among university students: A case study using factor analysis

Science.gov (United States)

Hassan, Suriani; Rahman, Nur Amira Abdol; Ghazali, Khadizah; Ismail, Norlita; Budin, Kamsia

2014-07-01

The purpose of this study was to examine the university students' perceptions on obesity and to compare the difference in mean scores factor based on demographic factors. Data was collected randomly using questionnaires. There were 321 university students participated in this study. Descriptive statistics, factor analysis, normality test, independent t test, one-way ANOVA and non-parametric tests were used in this study. Factor analysis results managed to retrieve three new factors namely impact of the health, impact of the physical appearance and personal factors. The study found that Science students have higher awareness and perceptions than Art students on Factor 1, impact of the health towards overweight problems and obesity. The findings of the study showed students, whose family background has obesity problem have higher awareness and perceptions than students' whose family background has no obesity problem on Factor 1, impact of the health towards overweight problems and obesity. The study also found that students' whose father with primary school level had the lowest awareness and perceptions on Factor 2, impact of the physical appearance towards overweight problems and obesity than other students whose father with higher academic level.

Identification of Key Success Factors in the Marketing of Cosmetics Based on Knowledge, Attitude and Practice (KAP Analysis Using Topsis Technique (The Case of Iran

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Mehdi Mohammadzadeh, Shirin Hashemi, Faranak Salmannejad, Tayebeh Ghari

2017-09-01

Full Text Available Background: Cosmetic products are one of the most important fields of consumer market. Strategic marketing plan and creating competitive advantages through recognizing of key success factors has become as a main core competency of active firms in this area. Based on this, the aim of our study was to identify the key success factors of cosmetic products' marketing in the Iran's market. Methods: To do this, knowledge, attitude, and practice (KAP of consumers in Iran were evaluated and key success factors were identified based on the mix marketing theory. Deep interviews and closed-ended questionnaires were used to collect data. The randomized sample population of this study was 1200 people. Results of KAP analysis were classified in seven clusters and then Topsis technique was used to analysis each cluster. Results: Results showed that there are a significant relationship between attitude and practice and also between knowledge and practice because of t-values greater than 1.96 and path coefficient greater than 0.1. Moreover, the results indicated that the most and the least important factors for success of cosmetics' marketing are place (distribution and dispensing and price, with sorted Cli of 0.9 and 0.1 respectively. Conclusion: It demonstrates that appropriate sales and distribution strategies, scientific and enough information and strong marketing at the point of purchase are the most important key success factors in the marketing of cosmetics, and price has a minimum drawing effect on cosmetics' marketing.

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

Science.gov (United States)

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Spatial econometric analysis of factors influencing regional energy efficiency in China.

Science.gov (United States)

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China.

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Chengjing Nie

Full Text Available BACKGROUND: In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. METHODS: Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. RESULTS: The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

Modified friction factor correlation for CICC's based on a porous media analogy

Science.gov (United States)

Lewandowska, Monika; Bagnasco, Maurizio

2011-09-01

A modified correlation for the bundle friction factor in CICC's based on a porous media analogy is presented. The correlation is obtained by the analysis of the collected pressure drop data measured for 23 CICC's. The friction factors predicted by the proposed correlation are compared with those resulting from the pressure drop data for two CICC's measured recently using cryogenic helium in the SULTAN test facility at EPFL-CRPP.

Methods for Engineering Enterprise Management Based on the Inter-factor Productive-Economic Relations

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O. A. Naydis

2015-01-01

Full Text Available The article analyzes the current state of engineering enterprises in the Russian Federation. It conducts a review and analysis of existing methods for business management using indicators to characterize enterprise activities by means of the scalars, functional dependencies of one factor value on the other (function one, wherein the magnitude of one factor value corresponds to a single magnitude of the other value - a dependent factor, as well as by means of data tables, and, as an example, by balance list and articulation statement used in accounting. The paper gives statements of need for taking into account the mutual influences and system interrelation of factors diversity and for special methods of their identification. The article is aimed at development of methods for business management of engineering enterprises taking into account a variety of factors and their interdependencies. The relevance of the issue stems from the fact that the analysis of existing methods of business management has shown that it is impossible to have the requested information about a considerable number of productive-economic factors in their system-based interrelation. There is a proposal for the management objects wherein multiple factors and their interactions are taken into consideration to be called inter-factor productive-economic relations (IPER. The paper presents the IPER-based structure of the business management system. It describes a method to identify controlled productive-economic factors and provides allocation and justification of the significant ones for the IPER control. Described methods of business management are distinguished by a large amount of control information, and data form rather complex structures. Therefore, it is proposed to use them in automatic control systems. The paper describes principles of information support for business management through binding IPER to organizational structures of the enterprise. It offers an

SCOR based key success factors in cooking oil supply chain buyers perspective in Padang City

Science.gov (United States)

Zahara, Fatimah; Hadiguna, Rika Ampuh

2017-11-01

Supply chain of cooking oil is a network of companies from palm oil as raw material to retailers which work to create the value and deliver products into the end consumers. This paper is aimed to study key success factors based on consumer's perspective as the last stage in the supply chain. Consumers who are examined in this study are restaurants management or owners. Restaurant is the biggest consumption of cooking oil. The factors is studied based on Supply Chain Operation Reference (SCOR) version 10.0. Factors used are formulated based on the third-level metrics of SCOR Model. Factors are analyzed using factors analysis. This study found factors which become key success factors in managing supply chain of cooking oil encompass reliability, responsiveness and agility. Key success factors can be applied by governments as policy making and cooking oil companies as formulation of the distribution strategies.

Human Factors Engineering and Ergonomics Analysis for the Canister Storage Building (CSB) Results and Findings

International Nuclear Information System (INIS)

GARVIN, L.J.

1999-01-01

The purpose for this supplemental report is to follow-up and update the information in SNF-3907, Human Factors Engineering (HFE) Analysis: Results and Findings. This supplemental report responds to applicable U.S. Department of Energy Safety Analysis Report review team comments and questions. This Human Factors Engineering and Ergonomics (HFE/Erg) analysis was conducted from April 1999 to July 1999; SNF-3907 was based on analyses accomplished in October 1998. The HFE/Erg findings presented in this report and SNF-3907, along with the results of HNF-3553, Spent Nuclear Fuel Project, Final Safety Analysis Report. Annex A, ''Canister Storage Building Final Safety Analysis Report,'' Chapter A3.0, ''Hazards and Accidents Analyses,'' provide the technical basis for preparing or updating HNF-3553, Annex A, Chapter A13.0, ''Human Factors Engineering.'' The findings presented in this report allow the HNF-3553 Chapter 13.0, ''Human Factors,'' to respond fully to the HFE requirements established in DOE Order 5480.23, Nuclear Safety Analysis Reports

Human Factors Engineering and Ergonomics Analysis for the Canister Storage Building (CSB): Results and Findings

International Nuclear Information System (INIS)

GARVIN, L.J.

1999-01-01

The purpose for this supplemental report is to follow-up and update the information in SNF-3907, Human Factors Engineering (HFE) Analysis: Results and Findings. This supplemental report responds to applicable U.S. Department of Energy Safety Analysis Report review team comments and questions. This Human Factors Engineering and Ergonomics (HFE/Erg) analysis was conducted from April 1999 to July 1999; SNF-3907 was based on analyses accomplished in October 1998. The HFE/Erg findings presented in this report and SNF-3907, along with the results of HNF-3553, Spent Nuclear Fuel Project, Final Safety Analysis Report, Annex A, ''Canister Storage Building Final Safety Analysis Report,'' Chapter A3.0, ''Hazards and Accidents Analyses,'' provide the technical basis for preparing or updating HNF-3553. Annex A, Chaptex A13.0, ''Human Factors Engineering.'' The findings presented in this report allow the HNF-3553 Chapter 13.0, ''Human Factors,'' to respond fully to the HFE requirements established in DOE Order 5480.23, Nuclear Safety Analysis Reports

[Cultural regionalization for Notopterygium incisum based on 3S technology platform. I. Evaluation for growth suitability for N. incisum based on ecological factors analysis by Maxent and ArcGIS model].

Science.gov (United States)

Sun, Hong-bing; Sun, Hui; Jiang, Shun-yuan; Zhou, Yi; Cao, Wen-long; Ji, Ming-chang; Zhy, Wen-tao; Yan, Han-jing

2015-03-01

Growth suitability as assessment indicators for medicinal plants cultivation was proposed based on chemical quality determination and ecological factors analysis by Maxent and ArcGIS model. Notopterygium incisum, an endangered Chinese medicinal plant, was analyzed as a case, its potential distribution areas at different suitability grade and regionalization map were formulated based on growth suitability theory. The results showed that the most suitable habitats is Sichuan province, and more than 60% of the most suitable areawas located in the western Sichuan such as Aba and Ganzi prefectures for N. incisum. The results indicated that habitat altitude, average air temperature in September, and vegetation types were the dominant factors contributing to the grade of plant growth, precipitation and slope were the major factors contributing to notopterol accumulation in its underground parts, while isoimperatorin in its underground parts was negatively corelated with precipitation and slope of its habitat. However, slope as a factor influencing chemical components seemed to be a pseudo corelationship. Therefore, there were distinguishing differences between growth suitability and quality suitability for medicinal plants, which was helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants.

Diagnostic throughput factor analysis for en-route airspace and optimal aircraft trajectory generation based on capacity prediction and controller workload

Science.gov (United States)

Shin, Sanghyun

Today's National Airspace System (NAS) is approaching its limit to efficiently cope with the increasing air traffic demand. Next Generation Air Transportation System (NextGen) with its ambitious goals aims to make the air travel more predictable with fewer delays, less time sitting on the ground and holding in the air to improve the performance of the NAS. However, currently the performance of the NAS is mostly measured using delay-based metrics which do not capture a whole range of important factors that determine the quality and level of utilization of the NAS. The factors affecting the performance of the NAS are themselves not well defined to begin with. To address these issues, motivated by the use of throughput-based metrics in many areas such as ground transportation, wireless communication and manufacturing, this thesis identifies the different factors which majorly affect the performance of the NAS as demand (split into flight cancellation and flight rerouting), safe separation (split into conflict and metering) and weather (studied as convective weather) through careful comparison with other applications and performing empirical sensitivity analysis. Additionally, the effects of different factors on the NAS's performance are quantitatively studied using real traffic data with the Future ATM Concepts Evaluation Tool (FACET) for various sectors and centers of the NAS on different days. In this thesis we propose a diagnostic tool which can analyze the factors that have greater responsibility for regions of poor and better performances of the NAS. Based on the throughput factor analysis for en-route airspace, it was found that weather and controller workload are the major factors that decrease the efficiency of the airspace. Also, since resources such as air traffic controllers, infrastructure and airspace are limited, it is becoming increasingly important to use the available resources efficiently. To alleviate the impact of the weather and controller

Assessing Heterogeneity for Factor Analysis Model with Continuous and Ordinal Outcomes

Directory of Open Access Journals (Sweden)

Ye-Mao Xia

2016-01-01

Full Text Available Factor analysis models with continuous and ordinal responses are a useful tool for assessing relations between the latent variables and mixed observed responses. These models have been successfully applied to many different fields, including behavioral, educational, and social-psychological sciences. However, within the Bayesian analysis framework, most developments are constrained within parametric families, of which the particular distributions are specified for the parameters of interest. This leads to difficulty in dealing with outliers and/or distribution deviations. In this paper, we propose a Bayesian semiparametric modeling for factor analysis model with continuous and ordinal variables. A truncated stick-breaking prior is used to model the distributions of the intercept and/or covariance structural parameters. Bayesian posterior analysis is carried out through the simulation-based method. Blocked Gibbs sampler is implemented to draw observations from the complicated posterior. For model selection, the logarithm of pseudomarginal likelihood is developed to compare the competing models. Empirical results are presented to illustrate the application of the methodology.

Factors explaining user loyalty in a social media-based brand community

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Louis M. Potgieter

2017-02-01

Full Text Available Background: Marketers are interested in taking advantage of the capabilities of social media-based brand communities to develop long-term relationships with their customers. This research investigated the usage of a South African Facebook page to understand user attitudes and attendant pressures on users related to social norms and user loyalty. Objectives: The research investigated the extent to which perceived value, service quality and social factors influenced the customer’s intention to continue using a global motor vehicle firm’s social media-based online brand community (OBC. Method: We used an online voluntary survey to collect data from social media-based brand community members. In total, 303 responses were collected over a period of 4 weeks from a population of 3100 members. We analysed the relationship between trust, perceived responsiveness, perceived usefulness, perceived ease of use, social norms and the members’ intention to continue using the firm’s OBC. 293 usable observations were subjected to descriptive, correlation and regression analysis. Results: The age of the respondents varied from 18 to 58 years with a mean age of 32 years. Of these, 60% were men and 40% women. About 86.7% of the respondents reported having at least some form of tertiary education. The results of the multiple regression analysis indicate that service quality factors such as trust (25.5% and social influence factors such as social norms (12.5% explain a greater part of the variance in OBC continuance intention compared with utility factors such as perceived usefulness (18.2%. The effects for responsiveness and ease of use were not statistically significant. Conclusion: Social media-based brand communities are playing an important role in enhancing the overall trust relationship, value offering, sociality, knowledge and information sharing between customers and firms. Practitioners should note that the loyalty of customers using a firm�

Human factors and fuzzy set theory for safety analysis

International Nuclear Information System (INIS)

Nishiwaki, Y.

1987-01-01

Human reliability and performance is affected by many factors: medical, physiological and psychological, etc. The uncertainty involved in human factors may not necessarily be probabilistic, but fuzzy. Therefore, it is important to develop a theory by which both the non-probabilistic uncertainties, or fuzziness, of human factors and the probabilistic properties of machines can be treated consistently. In reality, randomness and fuzziness are sometimes mixed. From the mathematical point of view, probabilistic measures may be considered a special case of fuzzy measures. Therefore, fuzzy set theory seems to be an effective tool for analysing man-machine systems. The concept 'failure possibility' based on fuzzy sets is suggested as an approach to safety analysis and fault diagnosis of a large complex system. Fuzzy measures and fuzzy integrals are introduced and their possible applications are also discussed. (author)

Knowledge-base for the new human reliability analysis method, A Technique for Human Error Analysis (ATHEANA)

International Nuclear Information System (INIS)

Cooper, S.E.; Wreathall, J.; Thompson, C.M., Drouin, M.; Bley, D.C.

1996-01-01

This paper describes the knowledge base for the application of the new human reliability analysis (HRA) method, a ''A Technique for Human Error Analysis'' (ATHEANA). Since application of ATHEANA requires the identification of previously unmodeled human failure events, especially errors of commission, and associated error-forcing contexts (i.e., combinations of plant conditions and performance shaping factors), this knowledge base is an essential aid for the HRA analyst

Train integrity detection risk analysis based on PRISM

Science.gov (United States)

Wen, Yuan

2018-04-01

GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

Science.gov (United States)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis

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Renfu Jia

2016-01-01

Full Text Available This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR and principal component analysis (PCA to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

The integration of expert-defined importance factors to enrich Bayesian Fault Tree Analysis

International Nuclear Information System (INIS)

Darwish, Molham; Almouahed, Shaban; Lamotte, Florent de

2017-01-01

This paper proposes an analysis of a hybrid Bayesian-Importance model for system designers to improve the quality of services related to Active Assisted Living Systems. The proposed model is based on two factors: failure probability measure of different service components and, an expert defined degree of importance that each component holds for the success of the corresponding service. The proposed approach advocates the integration of expert-defined importance factors to enrich the Bayesian Fault Tree Analysis (FTA) approach. The evaluation of the proposed approach is conducted using the Fault Tree Analysis formalism where the undesired state of a system is analyzed using Boolean logic mechanisms to combine a series of lower-level events.

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

Science.gov (United States)

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (Pregression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher Mc

Structural Analysis of Correlated Factors: Lessons from the Verbal-Performance Dichotomy of the Wechsler Scales.

Science.gov (United States)

Macmann, Gregg M.; Barnett, David W.

1994-01-01

Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

EXPLORATORY FACTOR ANALYSIS (EFA IN CONSUMER BEHAVIOR AND MARKETING RESEARCH

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Marcos Pascual Soler

2012-06-01

Full Text Available Exploratory Factor Analysis (EFA is one of the most widely used statistical procedures in social research. The main objective of this work is to describe the most common practices used by researchers in the consumer behavior and marketing area. Through a literature review methodology the practices of AFE in five consumer behavior and marketing journals(2000-2010 were analyzed. Then, the choices made by the researchers concerning factor model, retention criteria, rotation, factors interpretation and other relevant issues to factor analysis were analized. The results suggest that researchers routinely conduct analyses using such questionable methods. Suggestions for improving the use of factor analysis and the reporting of results are presented and a checklist (Exploratory Factor Analysis Checklist, EFAC is provided to help editors, reviewers, and authors improve reporting exploratory factor analysis.

Analysis on factors affecting consumers decision on purchasing simple-type houses

Science.gov (United States)

Rumintang, A.; Sholichin, I.

2018-01-01

In line with the increase of the population and the need of comfortable houses, as affected by modernization era, the house demand is getting higher. Hence, conducting a research on consumers need and want in buying a house should be seriously attempted to succeed marketing activity. Using an analysis consumers’ behavior, the researcher will know few affecting factors related to consumers’ satisfaction in buying a house. Among other, the factors in question include: house price, house condition, facilities, location and accessability. The sample of this research was drawn from the residents of Graha Asri Housing, Taman Bulang Permai, and Sukodono Permai. Based on the analysis and discussion, some conclusions are made as follow: the factors and variables affecting the consumers’ decision on each choice of house is different and also the same variables on three sources of data include housing atmosphere, cleaning service, ease of access to shopping center, health clinics or hospitals, tourism spot, schools, and the bus station.

Resources based factors of competitiveness of agricultural enterprises

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Matyja Małgorzata

2016-05-01

Full Text Available Among many different definitions of competitiveness it is difficult to pinpoint the most appropriate one. In the paper it was defined as the ability to be profitable by effective use of available resources. The profitability ratios (ROS, ROA, ROE and value index were proposed as measures of competitiveness and resources were indicated as one of the group of factors that has an impact on it. Precisely, the purpose of the paper was to examine the relationship between selected resourced based factors and competitiveness of agricultural enterprises. The study was done with the use of correlation analysis on the basis of statistical data on selected Polish companies operating in agriculture. The main finding was that the analyzed resources (the level of labour, size and quality of agricultural land and size of assets were weakly correlated with competitiveness. This observation means that other factors have stronger impact on agricultural company’s competitiveness. They can refer to intangible resources (such as relational capital, know-how, managerial competencies, technological resources etc. and external conditions (such as climate, legal issues of agricultural enterprises.

Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis

Science.gov (United States)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. The college students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. However, the results of the exploratory factor analysis indicated that the questionnaire could be revised to improve its construct validity. The goal of this study was to revise the questionnaire and establish its construct validity through a confirmatory factor analysis. In addition, a Rasch analysis was applied to the data to better understand the psychometric properties of the inventory and to further evaluate the construct validity. Results indicated that the final, revised inventory is a valid, reliable, and efficient tool for assessing student metacognition for physics problem solving.

An Analysis of Losses to the Southern Commercial Timberland Base

Science.gov (United States)

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

Identity of organizational conflict framework: Evaluating model factors based on demographic characteristics in Iran

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Kaveh Hasani

2014-10-01

Full Text Available Normal 0 false false false EN-US X-NONE FA Purpose: The purpose of this study was to Identity of organizational conflict framework:  Evaluating model factors based on demographic characteristics in Iran. Design/methodology/approach: Research method is descriptive - applied. The statistical population includes all of the employees in Iran`s Azad Universites with 600 individuals at the time of the study and statistical sample included 234 individuals who were selected using Morgan table. Beside this study, descriptive and inferential statistics were used. Also, reliability approved through Cronbach alpha (0.87. Then, to detect the dimensions causes of organizational conflict, factor analysis in line with the main components was used. Through exploratory analysis, ten principal factors identified. Thereafter, confirmatory factor analysis reconfirmed these factors. Findings and originality/value: The results of study showed that there is no significant difference between the causes of organizational conflict based on the gender. Also, there are significant differences among the causes of organizational conflict based on the variables of age, education and work experience. Research limitations/implications: we adopt a cross sectional research design and as a result inferences regarding causality cannot be drawn. Future studies following a longitudinal design could provide a more dynamic perspective and contribute further to this stream of research. Originality/value: A lot of researches about the conflict management styles, organizational conflict's effects, etc. are conducted by different researchers, but a handful of researches have been conducted in the field of resources and causes of organizational conflict and this is one of the reasons that it is important for researchers to address this issue.

Human Factors Engineering and Ergonomics Analysis for the Canister Storage Building (CSB) Results and Findings

Energy Technology Data Exchange (ETDEWEB)

GARVIN, L.J.

1999-09-20

The purpose for this supplemental report is to follow-up and update the information in SNF-3907, Human Factors Engineering (HFE) Analysis: Results and Findings. This supplemental report responds to applicable U.S. Department of Energy Safety Analysis Report review team comments and questions. This Human Factors Engineering and Ergonomics (HFE/Erg) analysis was conducted from April 1999 to July 1999; SNF-3907 was based on analyses accomplished in October 1998. The HFE/Erg findings presented in this report and SNF-3907, along with the results of HNF-3553, Spent Nuclear Fuel Project, Final Safety Analysis Report, Annex A, ''Canister Storage Building Final Safety Analysis Report,'' Chapter A3.0, ''Hazards and Accidents Analyses,'' provide the technical basis for preparing or updating HNF-3553. Annex A, Chaptex A13.0, ''Human Factors Engineering.'' The findings presented in this report allow the HNF-3553 Chapter 13.0, ''Human Factors,'' to respond fully to the HFE requirements established in DOE Order 5480.23, Nuclear Safety Analysis Reports.

Risk Analysis Method Based on FMEA for Transmission Line in Lightning Hazards

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You-Yuan WANG

2014-05-01

Full Text Available Failure rate of transmission line and reliability of power system are significantly affected by Lightning meteorological factor. In view of the complexity and variability of Lightning meteorological factors, this paper presents lightning trip-out rate model of transmission line in considering distribution of ground flash density and lightning day hours. Meanwhile, presents a failure rate model of transmission line in different condition, and a risk analysis method for transmission line considering multiple risk factors based on risk quantification. This method takes Lightning meteorological factor as the main evaluation standard, and establishes risk degree evaluation system for transmission line including another five evaluation standard. Put forward the risk indicators by quantify the risk factors based on experience date of transmission line in service. Based on the risk indexes comprehensive evaluation is conducted, and the evaluation result closer to practice is achieved, providing basis for transmission line risk warning and maintenance strategy. Through the risk analysis for 220 kV transmission line in a certain power supply bureau, the effectiveness of the proposed method is validated.

A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context

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Valavanis Ioannis K

2010-09-01

Full Text Available Abstract Background Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD. The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total, gender, and nutrition (38 in total, e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI as normal (BMI ≤ 25 or overweight (BMI > 25. Two artificial neural network (ANN based methods were designed and used towards the analysis of the available data. These corresponded to i a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN, and ii a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN which combines genetic algorithms and the popular back-propagation training algorithm. Results PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context.

Science.gov (United States)

Valavanis, Ioannis K; Mougiakakou, Stavroula G; Grimaldi, Keith A; Nikita, Konstantina S

2010-09-08

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm. PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV) resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets. The ANN based methods revealed factors

Setting Standards for Medically-Based Running Analysis

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Vincent, Heather K.; Herman, Daniel C.; Lear-Barnes, Leslie; Barnes, Robert; Chen, Cong; Greenberg, Scott; Vincent, Kevin R.

2015-01-01

Setting standards for medically based running analyses is necessary to ensure that runners receive a high-quality service from practitioners. Medical and training history, physical and functional tests, and motion analysis of running at self-selected and faster speeds are key features of a comprehensive analysis. Self-reported history and movement symmetry are critical factors that require follow-up therapy or long-term management. Pain or injury is typically the result of a functional deficit above or below the site along the kinematic chain. PMID:25014394

An empirical analysis of macroeconomic and bank-specific factors affecting liquidity of Indian banks

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Anamika Singh

2016-06-01

Full Text Available This paper investigates bank-specific and macroeconomic factors that determine the liquidity of Indian banks. To explore the association, we perform OLS, fixed effect and random effect estimates on a data set of 59 banks from 2000 to 2013. Studied bank-specific factors include bank size, profitability, cost of funding, capital adequacy and deposits. GDP, inflation and unemployment are the macroeconomic factors considered. We also perform liquidity trend analysis of Indian banks based on ownership. Findings reveal that bank ownership affects liquidity of banks. Based on panel data analysis, we suggest that bank-specific (except cost of funding and macroeconomic (except unemployment factors significantly affect bank liquidity. These include bank size, deposits, profitability, capital adequacy, GDP and inflation. Further, bank size and GDP were found to have a negative effect on bank liquidity. On the other hand, deposits, profitability, capital adequacy and inflation showed a positive effect on bank liquidity. Cost of funding and unemployment showed an insignificant effect on bank liquidity. Our paper highlights new facts for enhanced understanding of liquidity in emerging economies like India.

Research on the relationship between the elements and pharmacological activities in velvet antler using factor analysis and cluster analysis

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Zhou, Libing

2017-04-01

Velvet antler has certain effect on improving the body's immune cells and the regulation of immune system function, nervous system, anti-stress, anti-aging and osteoporosis. It has medicinal applications to treat a wide range of diseases such as tissue wound healing, anti-tumor, cardiovascular disease, et al. Therefore, the research on the relationship between pharmacological activities and elements in velvet antler is of great significance. The objective of this study was to comprehensively evaluate 15 kinds of elements in different varieties of velvet antlers and study on the relationship between the elements and traditional Chinese medicine efficacy for the human. The factor analysis and the factor cluster analysis methods were used to analyze the data of elements in the sika velvet antler, cervus elaphus linnaeus, flower horse hybrid velvet antler, apiti (elk) velvet antler, male reindeer velvet antler and find out the relationship between 15 kinds of elements including Ca, P, Mg, Na, K, Fe, Cu, Mn, Al, Ba, Co, Sr, Cr, Zn and Ni. Combining with MATLAB2010 and SPSS software, the chemometrics methods were made on the relationship between the elements in velvet antler and the pharmacological activities. The first commonality factor F1 had greater load on the indexes of Ca, P, Mg, Co, Sr and Ni, and the second commonality factor F2 had greater load on the indexes of K, Mn, Zn and Cr, and the third commonality factor F3 had greater load on the indexes of Na, Cu and Ba, and the fourth commonality factor F4 had greater load on the indexes of Fe and Al. 15 kinds of elements in velvet antler in the order were elk velvet antler>flower horse hybrid velvet antler>cervus elaphus linnaeus>sika velvet antler>male reindeer velvet antler. Based on the factor analysis and the factor cluster analysis, a model for evaluating traditional Chinese medicine quality was constructed. These studies provide the scientific base and theoretical foundation for the future large-scale rational

Classification analysis of organization factors related to system safety

International Nuclear Information System (INIS)

Liu Huizhen; Zhang Li; Zhang Yuling; Guan Shihua

2009-01-01

This paper analyzes the different types of organization factors which influence the system safety. The organization factor can be divided into the interior organization factor and exterior organization factor. The latter includes the factors of political, economical, technical, law, social culture and geographical, and the relationships among different interest groups. The former includes organization culture, communication, decision, training, process, supervision and management and organization structure. This paper focuses on the description of the organization factors. The classification analysis of the organization factors is the early work of quantitative analysis. (authors)

Time Series Factor Analysis with an Application to Measuring Money

NARCIS (Netherlands)

Gilbert, Paul D.; Meijer, Erik

2005-01-01

Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the

A comparison study on detection of key geochemical variables and factors through three different types of factor analysis

Science.gov (United States)

Hoseinzade, Zohre; Mokhtari, Ahmad Reza

2017-10-01

Large numbers of variables have been measured to explain different phenomena. Factor analysis has widely been used in order to reduce the dimension of datasets. Additionally, the technique has been employed to highlight underlying factors hidden in a complex system. As geochemical studies benefit from multivariate assays, application of this method is widespread in geochemistry. However, the conventional protocols in implementing factor analysis have some drawbacks in spite of their advantages. In the present study, a geochemical dataset including 804 soil samples collected from a mining area in central Iran in order to search for MVT type Pb-Zn deposits was considered to outline geochemical analysis through various fractal methods. Routine factor analysis, sequential factor analysis, and staged factor analysis were applied to the dataset after opening the data with (additive logratio) alr-transformation to extract mineralization factor in the dataset. A comparison between these methods indicated that sequential factor analysis has more clearly revealed MVT paragenesis elements in surface samples with nearly 50% variation in F1. In addition, staged factor analysis has given acceptable results while it is easy to practice. It could detect mineralization related elements while larger factor loadings are given to these elements resulting in better pronunciation of mineralization.

Factors associated with the implementation of community-based peer-led health promotion programs: A scoping review.

Science.gov (United States)

Lorthios-Guilledroit, Agathe; Richard, Lucie; Filiatrault, Johanne

2018-06-01

Peer education is growing in popularity as a useful health promotion strategy. However, optimal conditions for implementing peer-led health promotion programs (HPPs) remain unclear. This scoping review aimed to describe factors that can influence implementation of peer-led HPPs targeting adult populations. Five databases were searched using the keywords "health promotion/prevention", "implementation", "peers", and related terms. Studies were included if they reported at least one factor associated with the implementation of community-based peer-led HPPs. Fifty-five studies were selected for the analysis. The method known as "best fit framework synthesis" was used to analyze the factors identified in the selected papers. Many factors included in existing implementation conceptual frameworks were deemed applicable to peer-led HPPs. However, other factors related to individuals, programs, and implementation context also emerged from the analysis. Based on this synthesis, an adapted theoretical framework was elaborated, grounded in a complex adaptive system perspective and specifying potential mechanisms through which factors may influence implementation of community-based peer-led HPPs. Further research is needed to test the theoretical framework against empirical data. Findings from this scoping review increase our knowledge of the optimal conditions for implementing peer-led HPPs and thereby maximizing the benefits of such programs. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multiple Statistical Models Based Analysis of Causative Factors and Loess Landslides in Tianshui City, China

Science.gov (United States)

Su, Xing; Meng, Xingmin; Ye, Weilin; Wu, Weijiang; Liu, Xingrong; Wei, Wanhong

2018-03-01

Tianshui City is one of the mountainous cities that are threatened by severe geo-hazards in Gansu Province, China. Statistical probability models have been widely used in analyzing and evaluating geo-hazards such as landslide. In this research, three approaches (Certainty Factor Method, Weight of Evidence Method and Information Quantity Method) were adopted to quantitively analyze the relationship between the causative factors and the landslides, respectively. The source data used in this study are including the SRTM DEM and local geological maps in the scale of 1:200,000. 12 causative factors (i.e., altitude, slope, aspect, curvature, plan curvature, profile curvature, roughness, relief amplitude, and distance to rivers, distance to faults, distance to roads, and the stratum lithology) were selected to do correlation analysis after thorough investigation of geological conditions and historical landslides. The results indicate that the outcomes of the three models are fairly consistent.

Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors

Science.gov (United States)

Lou, Ping; Hu, Jianmin

2018-01-01

Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets. PMID:29462908

Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis

Science.gov (United States)

Afzal, Peyman; Mirzaei, Misagh; Yousefi, Mahyar; Adib, Ahmad; Khalajmasoumi, Masoumeh; Zarifi, Afshar Zia; Foster, Patrick; Yasrebi, Amir Bijan

2016-07-01

Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.

Using BMDP and SPSS for a Q factor analysis.

Science.gov (United States)

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Internal and external environmental factors affecting the performance of hospital-based home nursing care.

Science.gov (United States)

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

Bayesian analysis of factors associated with fibromyalgia syndrome subjects

Science.gov (United States)

Jayawardana, Veroni; Mondal, Sumona; Russek, Leslie

2015-01-01

Factors contributing to movement-related fear were assessed by Russek, et al. 2014 for subjects with Fibromyalgia (FM) based on the collected data by a national internet survey of community-based individuals. The study focused on the variables, Activities-Specific Balance Confidence scale (ABC), Primary Care Post-Traumatic Stress Disorder screen (PC-PTSD), Tampa Scale of Kinesiophobia (TSK), a Joint Hypermobility Syndrome screen (JHS), Vertigo Symptom Scale (VSS-SF), Obsessive-Compulsive Personality Disorder (OCPD), Pain, work status and physical activity dependent from the "Revised Fibromyalgia Impact Questionnaire" (FIQR). The study presented in this paper revisits same data with a Bayesian analysis where appropriate priors were introduced for variables selected in the Russek's paper.

A Quantitative Analysis of the Extrinsic and Intrinsic Turnover Factors of Relational Database Support Professionals

Science.gov (United States)

Takusi, Gabriel Samuto

2010-01-01

This quantitative analysis explored the intrinsic and extrinsic turnover factors of relational database support specialists. Two hundred and nine relational database support specialists were surveyed for this research. The research was conducted based on Hackman and Oldham's (1980) Job Diagnostic Survey. Regression analysis and a univariate ANOVA…

Phasor analysis of binary diffraction gratings with different fill factors

International Nuclear Information System (INIS)

MartInez, Antonio; Sanchez-Lopez, Ma del Mar; Moreno, Ignacio

2007-01-01

In this work, we present a simple analysis of binary diffraction gratings with different slit widths relative to the grating period. The analysis is based on a simple phasor technique directly derived from the Huygens principle. By introducing a slit phasor and a grating phasor, the intensity of the diffracted orders and the grating's resolving power can be easily obtained without applying the usual Fourier transform operations required for these calculations. The proposed phasor technique is mathematically equivalent to the Fourier transform calculation of the diffraction order amplitude, and it can be useful to explain binary diffraction gratings in a simple manner in introductory physics courses. This theoretical analysis is illustrated with experimental results using a liquid crystal device to display diffraction gratings with different fill factors

Quantitative Analysis of the Factors Influencing Soil Heavy Metal Lateral Migration in Rainfalls Based on Geographical Detector Software: A Case Study in Huanjiang County, China

Directory of Open Access Journals (Sweden)

Pengwei Qiao

2017-07-01

Full Text Available Quantitative analysis of the factors influencing heavy metal migration could be useful for controlling heavy metal migration. In this paper, a geographical detector was used to calculate the contributions of and interactions among factors in Huanjiang County, South China, covering an area of 273 km2. In this paper, nine factors were analyzed. The results showed that, among these factors, soil type was the main factor influencing the migration of As, Pb and Cd; the other eight factors did not have big differences and were lower than soil type. In addition, there were obvious synergistic effects between the soil type and concentration of water-soluble heavy metals (CWS and the concentration of water-insoluble heavy metals (CWI and NDVI. Therefore, these factors of the study area were especially focused on. Furthermore, the results of the key factor identification and the high-risk region identification in the nine factors were reliable, based on the geographical detector software. Therefore, the geographical detector software could be used as an effective tool to quantitatively analyze the contribution of the factors, and identify the high-risk regions for the factors influencing soil heavy metal lateral migration in rainfalls.

Factors influencing societal response of nanotechnology: an expert stakeholder analysis

International Nuclear Information System (INIS)

Gupta, Nidhi; Fischer, Arnout R. H.; Lans, Ivo A. van der; Frewer, Lynn J.

2012-01-01

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

Factors influencing societal response of nanotechnology: an expert stakeholder analysis

Science.gov (United States)

Gupta, Nidhi; Fischer, Arnout R. H.; van der Lans, Ivo A.; Frewer, Lynn J.

2012-05-01

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

Factor analysis improves the selection of prescribing indicators

DEFF Research Database (Denmark)

Rasmussen, Hanne Marie Skyggedal; Søndergaard, Jens; Sokolowski, Ineta

2006-01-01

OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was us...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

Analysis of bus passenger comfort perception based on passenger load factor and in-vehicle time.

Science.gov (United States)

Shen, Xianghao; Feng, Shumin; Li, Zhenning; Hu, Baoyu

2016-01-01

Although bus comfort is a crucial indicator of service quality, existing studies tend to focus on passenger load and ignore in-vehicle time, which can also affect passengers' comfort perception. Therefore, by conducting surveys, this study examines passengers' comfort perception while accounting for both factors. Then, using the survey data, it performs a two-way analysis of variance and shows that both in-vehicle time and passenger load significantly affect passenger comfort. Then, a bus comfort model is proposed to evaluate comfort level, followed by a sensitivity analysis. The method introduced in this study has theoretical implications for bus operators attempting to improve bus service quality.

Human factors analysis of incident/accident report

International Nuclear Information System (INIS)

Kuroda, Isao

1992-01-01

Human factors analysis of accident/incident has different kinds of difficulties in not only technical, but also psychosocial background. This report introduces some experiments of 'Variation diagram method' which is able to extend to operational and managemental factors. (author)

Energy and entropy analysis of closed adiabatic expansion based trilateral cycles

International Nuclear Information System (INIS)

Garcia, Ramon Ferreiro; Carril, Jose Carbia; Gomez, Javier Romero; Gomez, Manuel Romero

2016-01-01

Highlights: • The adiabatic expansion based TC surpass Carnot factor at low temperatures. • The fact of surpassing Carnot factor doesn’t violate the 2nd law. • An entropy analysis is applied to verify the fulfilment of the second law. • Correction of the exergy transfer associated with heat transferred to a cycle. - Abstract: A vast amount of heat energy is available at low cost within the range of medium and low temperatures. Existing thermal cycles cannot make efficient use of such available low grade heat because they are mainly based on conventional organic Rankine cycles which are limited by Carnot constraints. However, recent developments related to the performance of thermal cycles composed of closed processes have led to the exceeding of the Carnot factor. Consequently, once the viability of closed process based thermal cycles that surpass the Carnot factor operating at low and medium temperatures is globally accepted, research work will aim at looking into the consequences that lead from surpassing the Carnot factor while fulfilling the 2nd law, its impact on the 2nd law efficiency definition as well as the impact on the exergy transfer from thermal power sources to any heat consumer, including thermal cycles. The methodology used to meet the proposed objectives involves the analysis of energy and entropy on trilateral closed process based thermal cycles. Thus, such energy and entropy analysis is carried out upon non-condensing mode trilateral thermal cycles (TCs) characterised by the conversion of low grade heat into mechanical work undergoing closed adiabatic path functions: isochoric heat absorption, adiabatic heat to mechanical work conversion and isobaric heat rejection. Firstly, cycle energy analysis is performed to determine the range of some relevant cycle parameters, such as the operating temperatures and their associated pressures, entropies, internal energies and specific volumes. In this way, the ranges of temperatures within which

Reliability Analysis and Calibration of Partial Safety Factors for Redundant Structures

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

1998-01-01

Redundancy is important to include in the design and analysis of structural systems. In most codes of practice redundancy is not directly taken into account. In the paper various definitions of a deterministic and reliability based redundancy measure are reviewed. It is described how reundancy can...... be included in the safety system and how partial safety factors can be calibrated. An example is presented illustrating how redundancy is taken into account in the safety system in e.g. the Danish codes. The example shows how partial safety factors can be calibrated to comply with the safety level...

The development of human factors technologies -The development of human behaviour analysis techniques-

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Woon; Lee, Yong Heui; Park, Keun Ok; Chun, Se Woo; Suh, Sang Moon; Park, Jae Chang [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1995-07-01

In order to contribute to human error reduction through the studies on human-machine interaction in nuclear power plants, this project has objectives to develop SACOM(Simulation Analyzer with a Cognitive Operator Model) and techniques for human error analysis and application. In this year, we studied the followings: (1) Site investigation of operator tasks, (2) Development of operator task micro structure and revision of micro structure, (3) Development of knowledge representation software and SACOM prototype, (4) Development of performance assessment methodologies in task simulation and analysis of the effects of performance shaping factors. analysis and application techniques> (1) Classification of error shaping factors(ESFs) and development of software for ESF evaluation, (2) Analysis of human error occurrences and revision of analysis procedure, (3) Experiment for human error data collection using a compact nuclear simulator, (4) Development of a prototype data base system of the analyzed information on trip cases. 55 figs, 23 tabs, 33 refs. (Author).

[Delirium in stroke patients : Critical analysis of statistical procedures for the identification of risk factors].

Science.gov (United States)

Nydahl, P; Margraf, N G; Ewers, A

2017-04-01

Delirium is a relevant complication following an acute stroke. It is a multifactor occurrence with numerous interacting risk factors that alternately influence each other. The risk factors of delirium in stroke patients are often based on limited clinical studies. The statistical procedures and clinical relevance of delirium related risk factors in adult stroke patients should therefore be questioned. This secondary analysis includes clinically relevant studies that give evidence for the clinical relevance and statistical significance of delirium-associated risk factors in stroke patients. The quality of the reporting of regression analyses was assessed using Ottenbacher's quality criteria. The delirium-associated risk factors identified were examined with regard to statistical significance using the Bonferroni method of multiple testing for forming incorrect positive hypotheses. This was followed by a literature-based discussion on clinical relevance. Nine clinical studies were included. None of the studies fulfilled all the prerequisites and assumptions given for the reporting of regression analyses according to Ottenbacher. Of the 108 delirium-associated risk factors, a total of 48 (44.4%) were significant, whereby a total of 28 (58.3%) were false positive after Bonferroni correction. Following a literature-based discussion on clinical relevance, the assumption of statistical significance and clinical relevance could be found for only four risk factors (dementia or cognitive impairment, total anterior infarct, severe infarct and infections). The statistical procedures used in the existing literature are questionable, as are their results. A post-hoc analysis and critical appraisal reduced the number of possible delirium-associated risk factors to just a few clinically relevant factors.

Factor analysis methods and validity evidence: A systematic review of instrument development across the continuum of medical education

Science.gov (United States)

Wetzel, Angela Payne

Previous systematic reviews indicate a lack of reporting of reliability and validity evidence in subsets of the medical education literature. Psychology and general education reviews of factor analysis also indicate gaps between current and best practices; yet, a comprehensive review of exploratory factor analysis in instrument development across the continuum of medical education had not been previously identified. Therefore, the purpose for this study was critical review of instrument development articles employing exploratory factor or principal component analysis published in medical education (2006--2010) to describe and assess the reporting of methods and validity evidence based on the Standards for Educational and Psychological Testing and factor analysis best practices. Data extraction of 64 articles measuring a variety of constructs that have been published throughout the peer-reviewed medical education literature indicate significant errors in the translation of exploratory factor analysis best practices to current practice. Further, techniques for establishing validity evidence tend to derive from a limited scope of methods including reliability statistics to support internal structure and support for test content. Instruments reviewed for this study lacked supporting evidence based on relationships with other variables and response process, and evidence based on consequences of testing was not evident. Findings suggest a need for further professional development within the medical education researcher community related to (1) appropriate factor analysis methodology and reporting and (2) the importance of pursuing multiple sources of reliability and validity evidence to construct a well-supported argument for the inferences made from the instrument. Medical education researchers and educators should be cautious in adopting instruments from the literature and carefully review available evidence. Finally, editors and reviewers are encouraged to recognize

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objectives of this analysis are to develop BDCFs for the

Environmental determinants of cardiovascular diseases risk factors: a qualitative directed content analysis.

Science.gov (United States)

Sabzmakan, Leila; Mohammadi, Eesa; Morowatisharifabad, Mohammad Ali; Afaghi, Ahmad; Naseri, Mohammad Hassan; Mirzaei, Masoud

2014-05-01

Cardiovascular diseases (CVDs) are the number one cause of death in the world. In most analyses of health problems, environment plays a significant and modifiable role in causing the problem either directly or indirectly through behavior. This study aims to understand the patients and healthcare providers' experiences about the environmental determinants of CVD risk factors based on the Precede Model. This qualitative study conducted over six months in 2012 at Diabetes Units of Health Centers associated with Alborz University of Medical Sciences and Health Services which is located in Karaj, Iran. The data were collected based on individual semi-structured interviews with 50 patients and 12 healthcare providers. Data analysis was performed simultaneous with data collection using the content analysis directed method. Lack of behaviors like stress control, healthy eating and physical activity were the roots of the risk factors for CVD. The environmental factor is one of the barriers for conducting these behaviors. The environmental barriers included of structural environment including "availability and accessibility of health resources", "new skills", and "law and policies" which are located in enabling category and social environment including "social support", "motivation to comply" and "consequences of behavior" which are located in reinforcing category. The most barriers to performing health behaviors were often structural. The environmental factors were barriers for doing healthy behaviors. These factors need to be considered to design health promotion interventions. Policymakers should not only focus on patients' education but also should provide specific facilities to enhance economic, social and cultural status.

A meta-analysis of factors affecting trust in human-robot interaction.

Science.gov (United States)

Hancock, Peter A; Billings, Deborah R; Schaefer, Kristin E; Chen, Jessie Y C; de Visser, Ewart J; Parasuraman, Raja

2011-10-01

We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI). To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice. Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes. The overall correlational effect size for trust was r = +0.26,with an experimental effect size of d = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role. Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

Analysis of technological, institutional and socioeconomic factors ...

African Journals Online (AJOL)

Analysis of technological, institutional and socioeconomic factors that influences poor reading culture among secondary school students in Nigeria. ... Proliferation and availability of smart phones, chatting culture and social media were identified as technological factors influencing poor reading culture among secondary ...

Exploratory Analysis of the Factors Affecting Consumer Choice in E-Commerce: Conjoint Analysis

Directory of Open Access Journals (Sweden)

Elena Mazurova

2017-05-01

Full Text Available According to previous studies of online consumer behaviour, three factors are the most influential on purchasing behavior - brand, colour and position of the product on the screen. However, a simultaneous influence of these three factors on the consumer decision making process has not been investigated previously. In this particular work we aim to execute a comprehensive study of the influence of these three factors. In order to answer our main research questions, we conducted an experiment with 96 different combinations of the three attributes, and using statistical analysis, such as conjoint analysis, t-test analysis and Kendall analysis we identified that the most influential factor to the online consumer decision making process is brand, the second most important attribute is the colour, which was estimated half as important as brand, and the least important attribute is the position on the screen. Additionally, we identified the main differences regarding consumers stated and revealed preferences regarding these three attributes.

A factor analysis to find critical success factors in retail brand

Directory of Open Access Journals (Sweden)

Naser Azad

2013-03-01

Full Text Available The present exploratory study aims to find critical components of retail brand among some retail stores. The study seeks to build a brand name in retail level and looks to find important factors affecting it. Customer behavior is largely influenced when the first retail customer experience is formed. These factors have direct impacts on customer experience and satisfaction in retail industry. The proposed study performs an empirical investigation on two well-known retain stores located in city of Tehran, Iran. Using a sample of 265 people from regular customers, the study uses factor analysis and extracts four main factors including related brand, product benefits, customer welfare strategy and corporate profits using the existing 31 factors in the literature.

An automated Monte-Carlo based method for the calculation of cascade summing factors

Energy Technology Data Exchange (ETDEWEB)

Jackson, M.J., E-mail: mark.j.jackson@awe.co.uk; Britton, R.; Davies, A.V.; McLarty, J.L.; Goodwin, M.

2016-10-21

A versatile method has been developed to calculate cascade summing factors for use in quantitative gamma-spectrometry analysis procedures. The proposed method is based solely on Evaluated Nuclear Structure Data File (ENSDF) nuclear data, an X-ray energy library, and accurate efficiency characterisations for single detector counting geometries. The algorithm, which accounts for γ–γ, γ–X, γ–511 and γ–e{sup −} coincidences, can be applied to any design of gamma spectrometer and can be expanded to incorporate any number of nuclides. Efficiency characterisations can be derived from measured or mathematically modelled functions, and can accommodate both point and volumetric source types. The calculated results are shown to be consistent with an industry standard gamma-spectrometry software package. Additional benefits including calculation of cascade summing factors for all gamma and X-ray emissions, not just the major emission lines, are also highlighted. - Highlights: • Versatile method to calculate coincidence summing factors for gamma-spectrometry analysis. • Based solely on ENSDF format nuclear data and detector efficiency characterisations. • Enables generation of a CSF library for any detector, geometry and radionuclide. • Improves measurement accuracy and reduces acquisition times required to meet MDA.

Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

Science.gov (United States)

Xu, Qiang; Ding, Shuai; An, Jingwen

2017-12-01

This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

The Experiences of Patients´ Close Relatives with Risk Factors of Gastric Cancer and Health-Therapeutic Personnel from the Determinants of Nutritional Behaviors: A Theory-based Qualitative Content Analysis

Directory of Open Access Journals (Sweden)

MH Baghiani Moghadam

2016-03-01

Full Text Available Introduction: Cancers are one of the most common causes of death at age groups above 50 years old that Life style modification has an important role in prevention of them. Diets are the most important factor at the risk of gastric cancer. The aim of present study was explanation of the Experiences of Patients´ Close Relatives with Risk Factors of Gastric Cancer and Health-Therapeutic Personnel from the Determinants of Nutritional Behaviors based on protection motivation theory. Methods: The present qualitative study was done with content analysis method application at Babol health-therapeutic centers covered by Babol University of Medical Sciences for eight months in 2013. semi-structure d face to face interview were used to collect the data with 9 participants from Patients´ Close Relatives with Risk Factors of Gastric Cancer and 19 participants from Health-Therapeutic Personnel. Data analysis and collection were simultaneously done by using the method of theory-based (directed or conductive content analysis. Results:From data analysis 487initial codes and after integration,186 main codes were extracted .This codes were pasted at 2 pre-determined categories and 7 pre-determined sub-categories related to protection motivation theory(perceived sensitivity, perceived severity, reward, fear, perceived response-efficacy, self-efficacy and perceived cost-benefit. The most main perceived problem, was the low level of awareness, attitude and practice at people about nutritional risk factors related to gastric cancer and a result the low level of disease fear. Conclusion: The findings of present study are the indicator of effective determinants on nutritional behaviors that can help to health-therapeutic policy –makers to provide and approve the most appropriate solutions and strategies with aim of changing these determinants in order to reduce nutritional risk factors related to gastric cancer.

Variance-based sensitivity analysis for wastewater treatment plant modelling.

Science.gov (United States)

Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

2014-02-01

Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

Energy Technology Data Exchange (ETDEWEB)

Konstandinidou, Myrto [Institute of Nuclear Technology-Radiation Protection, National Center for Scientific Research ' Demokritos' , Aghia Paraskevi 15310 (Greece); Nivolianitou, Zoe, E-mail: zoe@ipta.demokritos.gr [Institute of Nuclear Technology-Radiation Protection, National Center for Scientific Research ' Demokritos' , Aghia Paraskevi 15310 (Greece); Kefalogianni, Eirini; Caroni, Chrys [School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 9 Iroon Polytexneiou Str., Zografou Campus, 157 80 Athens (Greece)

2011-11-15

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents. - Highlights: > The research work is original, based on field data collected directly from the petrochemical industry. > It deals with the in-depth statistical analysis of accident data on human-organizational causes. > It researches underlying causes of accidents and the parameters affecting them. > The causal factors that are considered cover four big taxonomies. > Near misses are worth recording for comparing their causal factors with more serious incidents.

Factor analysis for exercise stress radionuclide ventriculography

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Yasuda, Mitsutaka; Oku, Hisao; Ikuno, Yoshiyasu; Takeuchi, Kazuhide; Takeda, Tadanao; Ochi, Hironobu

1987-01-01

Using factor analysis, a new image processing in exercise stress radionuclide ventriculography, changes in factors associated with exercise were evaluated in 14 patients with angina pectoris or old myocardial infarction. The patients were imaged in the left anterior oblique projection, and three factor images were presented on a color coded scale. Abnormal factors (AF) were observed in 6 patients before exercise, 13 during exercise, and 4 after exercise. In 7 patients, the occurrence of AF was associated with exercise. Five of them became free from AF after exercise. Three patients showing AF before exercise had aggravation of AF during exercise. Overall, the occurrence or aggravation of AF was associated with exercise in ten (71 %) of the patients. The other three patients, however, had disappearance of AF during exercise. In the last patient, none of the AF was observed throughout the study. In view of a high incidence of AF associated with exercise, the factor analysis may have the potential in evaluating cardiac reverse from the viewpoint of left ventricular wall motion abnormality. (Namekawa, K.)

Risk factors for chronic and recurrent otitis media-a meta-analysis.

Science.gov (United States)

Zhang, Yan; Xu, Min; Zhang, Jin; Zeng, Lingxia; Wang, Yanfei; Zheng, Qing Yin

2014-01-01

Risk factors associated with chronic otitis media (COM) and recurrent otitis media (ROM) have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database) from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs) could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001). An upper respiratory tract infection (URTI) significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; Pmedia (AOM)/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04). Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04). Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03). Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

Phasor analysis of binary diffraction gratings with different fill factors

Energy Technology Data Exchange (ETDEWEB)

MartInez, Antonio [Departamento de Ciencia de Materiales, Optica y TecnologIa Electronica, Universidad Miguel Hernandez, 03202 Elche (Spain); Sanchez-Lopez, Ma del Mar [Instituto de BioingenierIa y Departamento de Fisica y Arquitectura de Computadores, Universidad Miguel Hernandez, 03202 Elche (Spain); Moreno, Ignacio [Departamento de Ciencia de Materiales, Optica y TecnologIa Electronica, Universidad Miguel Hernandez, 03202 Elche (Spain)

2007-09-11

In this work, we present a simple analysis of binary diffraction gratings with different slit widths relative to the grating period. The analysis is based on a simple phasor technique directly derived from the Huygens principle. By introducing a slit phasor and a grating phasor, the intensity of the diffracted orders and the grating's resolving power can be easily obtained without applying the usual Fourier transform operations required for these calculations. The proposed phasor technique is mathematically equivalent to the Fourier transform calculation of the diffraction order amplitude, and it can be useful to explain binary diffraction gratings in a simple manner in introductory physics courses. This theoretical analysis is illustrated with experimental results using a liquid crystal device to display diffraction gratings with different fill factors.

Risk Factors for Post-stroke Depression: A Meta-analysis

Directory of Open Access Journals (Sweden)

Yu Shi

2017-07-01

Full Text Available Background: Stroke not only impacts patients physically but also economically. Post-stroke depression (PSD, as a common complication of stroke, always obstructs the process of stroke rehabilitation. Accordingly, defining the risk factors associated with PSD has extraordinary importance. Although there have been many studies investigating the risk factors for PSD, the results are inconsistent.Objectives: The objectives of this study were to identify the risk factors for PSD by evidence-based medicine.Data sources: A systematic and comprehensive database search was performed of PubMed, Medline, CENTRAL, EMBASE.com, the Cochrane library and Web of Science for Literature, covering publications from January 1, 1998 to November 19, 2016.Study Selection: Studies on risk factors for PSD were identified, according to inclusion and exclusion criteria. The risk of bias tool, described in the Cochrane Handbook version 5.1.0, was used to assess the quality of each study. Meta-analysis was performed using RevMan 5.3 software.Results: Thirty-six studies were included for review. A history of mental illness was the highest ranking modifiable risk factor; other risk factors for PSD were female gender, age (<70 years, neuroticism, family history, severity of stroke, and level of handicap. Social support was a protective factor for PSD.Conclusion: There are many factors that have effects on PSD. The severity of stroke is an important factor in the occurrence of PSD. Mental history is a possible predictor of PSD. Prevention of PSD requires social and family participation.

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2003-07-25

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports (BSC 2003 [DIRS 160964]; BSC 2003 [DIRS 160965]; BSC 2003 [DIRS 160976]; BSC 2003 [DIRS 161239]; BSC 2003 [DIRS 161241]) contain detailed description of the model input parameters. This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs and conversion factors for the TSPA. The BDCFs will be used in performance assessment for calculating annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose from beta- and photon-emitting radionuclides.

Chapter 11. Community analysis-based methods

Energy Technology Data Exchange (ETDEWEB)

Cao, Y.; Wu, C.H.; Andersen, G.L.; Holden, P.A.

2010-05-01

Microbial communities are each a composite of populations whose presence and relative abundance in water or other environmental samples are a direct manifestation of environmental conditions, including the introduction of microbe-rich fecal material and factors promoting persistence of the microbes therein. As shown by culture-independent methods, different animal-host fecal microbial communities appear distinctive, suggesting that their community profiles can be used to differentiate fecal samples and to potentially reveal the presence of host fecal material in environmental waters. Cross-comparisons of microbial communities from different hosts also reveal relative abundances of genetic groups that can be used to distinguish sources. In increasing order of their information richness, several community analysis methods hold promise for MST applications: phospholipid fatty acid (PLFA) analysis, denaturing gradient gel electrophoresis (DGGE), terminal restriction fragment length polymorphism (TRFLP), cloning/sequencing, and PhyloChip. Specific case studies involving TRFLP and PhyloChip approaches demonstrate the ability of community-based analyses of contaminated waters to confirm a diagnosis of water quality based on host-specific marker(s). The success of community-based MST for comprehensively confirming fecal sources relies extensively upon using appropriate multivariate statistical approaches. While community-based MST is still under evaluation and development as a primary diagnostic tool, results presented herein demonstrate its promise. Coupled with its inherently comprehensive ability to capture an unprecedented amount of microbiological data that is relevant to water quality, the tools for microbial community analysis are increasingly accessible, and community-based approaches have unparalleled potential for translation into rapid, perhaps real-time, monitoring platforms.

Hand function evaluation: a factor analysis study.

Science.gov (United States)

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

Salivary SPECT and factor analysis in Sjoegren's syndrome

International Nuclear Information System (INIS)

Nakamura, T.; Oshiumi, Y.; Yonetsu, K.; Muranaka, T.; Sakai, K.; Kanda, S.; National Fukuoka Central Hospital

1991-01-01

Salivary SPECT and factor analysis in Sjoegren's syndrome were performed in 17 patients and 6 volunteers as controls. The ability of SPECT to detect small differences in the level of uptake can be used to separate glands from background even when uptake is reduced as in the patients with Sjoegren's syndrome. In control and probable Sjoegren's syndrome groups the uptake ratio of the submandibular gland to parotid gland on salivary SPECT (S/P ratio) was less than 1.0. However, in the definite Sjoergren's syndrome group, the ratio was more than 1.0. Moreover, the ratio in all patients with sialectasia, which is characteristic of Sjoegren's syndrome, was more than 1.0. Salivary factor analysis of normal parotid glands showed slowly increasing patterns of uptake and normal submandibular glands had rapidly increasing patterns of uptake. However, in the definite Sjoegren's syndrome group, the factor analysis patterns were altered, with slowly increasing patterns dominating both in the parotid and submandibular glands. These results suggest that the S/P ratio in salivary SPECT and salivary factor analysis provide additional radiologic criteria in diagnosing Sjoegren's syndrome. (orig.)

Worldwide analysis of marine oil spill cleanup cost factors

International Nuclear Information System (INIS)

Etkin, D.S.

2000-01-01

The many factors that influence oil spill response costs were discussed with particular emphasis on how spill responses differ around the world because of differing cultural values, socio-economic factors and labor costs. This paper presented an analysis of marine oil spill cleanup costs based on the country, proximity to shoreline, spill size, oil type, degree of shoreline oiling and cleanup methodology. The objective was to determine how each factor impacts per-unit cleanup costs. Near-shore spills and in-port spills were found to be 4-5 times more expensive to clean than offshore spills. Responses to spills of heavy fuels also cost 10 times more than for lighter crudes and diesel. Spill responses for spills under 30 tonnes are 10 times more costly than on a per-unit basis, for spills of 300 tonnes. A newly developed modelling technique that can be used on different types of marine spills was described. It is based on updated cost data acquired from case studies of more than 300 spills in 40 countries. The model determines a per-unit cleanup cost estimation by taking into consideration oil type, location, spill size, cleanup methodology, and shoreline oiling. It was concluded that the actual spill costs are totally dependent on the actual circumstances of the spill. 13 refs., 10 tabs., 3 figs

What Factors Affect Voluntary Uptake of Community-Based Health Insurance Schemes in Low- and Middle-Income Countries? A Systematic Review and Meta-Analysis.

Directory of Open Access Journals (Sweden)

David Mark Dror

Full Text Available This research article reports on factors influencing initial voluntary uptake of community-based health insurance (CBHI schemes in low- and middle-income countries (LMIC, and renewal decisions.Following PRISMA protocol, we conducted a comprehensive search of academic and gray literature, including academic databases in social science, economics and medical sciences (e.g., Econlit, Global health, Medline, Proquest and other electronic resources (e.g., Eldis and Google scholar. Search strategies were developed using the thesaurus or index terms (e.g., MeSH specific to the databases, combined with free text terms related to CBHI or health insurance. Searches were conducted from May 2013 to November 2013 in English, French, German, and Spanish. From the initial search yield of 15,770 hits, 54 relevant studies were retained for analysis of factors influencing enrolment and renewal decisions. The quantitative synthesis (informed by meta-analysis and the qualitative analysis (informed by thematic synthesis were compared to gain insight for an overall synthesis of findings/statements.Meta-analysis suggests that enrolments in CBHI were positively associated with household income, education and age of the household head (HHH, household size, female-headed household, married HHH and chronic illness episodes in the household. The thematic synthesis suggests the following factors as enablers for enrolment: (a knowledge and understanding of insurance and CBHI, (b quality of healthcare, (c trust in scheme management. Factors found to be barriers to enrolment include: (a inappropriate benefits package, (b cultural beliefs, (c affordability, (d distance to healthcare facility, (e lack of adequate legal and policy frameworks to support CBHI, and (f stringent rules of some CBHI schemes. HHH education, household size and trust in the scheme management were positively associated with member renewal decisions. Other motivators were: (a knowledge and understanding of

What Factors Affect Voluntary Uptake of Community-Based Health Insurance Schemes in Low- and Middle-Income Countries? A Systematic Review and Meta-Analysis

Science.gov (United States)

Hossain, S. A. Shahed; Pérez Koehlmoos, Tracey Lynn; John, Denny

2016-01-01

Introduction This research article reports on factors influencing initial voluntary uptake of community-based health insurance (CBHI) schemes in low- and middle-income countries (LMIC), and renewal decisions. Methods Following PRISMA protocol, we conducted a comprehensive search of academic and gray literature, including academic databases in social science, economics and medical sciences (e.g., Econlit, Global health, Medline, Proquest) and other electronic resources (e.g., Eldis and Google scholar). Search strategies were developed using the thesaurus or index terms (e.g., MeSH) specific to the databases, combined with free text terms related to CBHI or health insurance. Searches were conducted from May 2013 to November 2013 in English, French, German, and Spanish. From the initial search yield of 15,770 hits, 54 relevant studies were retained for analysis of factors influencing enrolment and renewal decisions. The quantitative synthesis (informed by meta-analysis) and the qualitative analysis (informed by thematic synthesis) were compared to gain insight for an overall synthesis of findings/statements. Results Meta-analysis suggests that enrolments in CBHI were positively associated with household income, education and age of the household head (HHH), household size, female-headed household, married HHH and chronic illness episodes in the household. The thematic synthesis suggests the following factors as enablers for enrolment: (a) knowledge and understanding of insurance and CBHI, (b) quality of healthcare, (c) trust in scheme management. Factors found to be barriers to enrolment include: (a) inappropriate benefits package, (b) cultural beliefs, (c) affordability, (d) distance to healthcare facility, (e) lack of adequate legal and policy frameworks to support CBHI, and (f) stringent rules of some CBHI schemes. HHH education, household size and trust in the scheme management were positively associated with member renewal decisions. Other motivators were: (a

A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

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Burhanuddin M. A.

2011-01-01

Full Text Available Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for

Can an Internet-based health risk assessment highlight problems of heart disease risk factor awareness? A cross-sectional analysis.

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Dickerson, Justin B; McNeal, Catherine J; Tsai, Ginger; Rivera, Cathleen M; Smith, Matthew Lee; Ohsfeldt, Robert L; Ory, Marcia G

2014-04-18

Health risk assessments are becoming more popular as a tool to conveniently and effectively reach community-dwelling adults who may be at risk for serious chronic conditions such as coronary heart disease (CHD). The use of such instruments to improve adults' risk factor awareness and concordance with clinically measured risk factor values could be an opportunity to advance public health knowledge and build effective interventions. The objective of this study was to determine if an Internet-based health risk assessment can highlight important aspects of agreement between respondents' self-reported and clinically measured CHD risk factors for community-dwelling adults who may be at risk for CHD. Data from an Internet-based cardiovascular health risk assessment (Heart Aware) administered to community-dwelling adults at 127 clinical sites were analyzed. Respondents were recruited through individual hospital marketing campaigns, such as media advertising and print media, found throughout inpatient and outpatient facilities. CHD risk factors from the Framingham Heart Study were examined. Weighted kappa statistics were calculated to measure interrater agreement between respondents' self-reported and clinically measured CHD risk factors. Weighted kappa statistics were then calculated for each sample by strata of overall 10-year CHD risk. Three samples were drawn based on strategies for treating missing data: a listwise deleted sample, a pairwise deleted sample, and a multiple imputation (MI) sample. The MI sample (n=16,879) was most appropriate for addressing missing data. No CHD risk factor had better than marginal interrater agreement (κ>.60). High-density lipoprotein cholesterol (HDL-C) exhibited suboptimal interrater agreement that deteriorated (eg, κInternet-based health risk assessments such as Heart Aware may contribute to public health surveillance, but they must address selection bias of Internet-based recruitment methods.

Analysis of factors affecting satisfaction level on problem based learning approach using structural equation modeling

Science.gov (United States)

Hussain, Nur Farahin Mee; Zahid, Zalina

2014-12-01

Nowadays, in the job market demand, graduates are expected not only to have higher performance in academic but they must also be excellent in soft skill. Problem-Based Learning (PBL) has a number of distinct advantages as a learning method as it can deliver graduates that will be highly prized by industry. This study attempts to determine the satisfaction level of engineering students on the PBL Approach and to evaluate their determinant factors. The Structural Equation Modeling (SEM) was used to investigate how the factors of Good Teaching Scale, Clear Goals, Student Assessment and Levels of Workload affected the student satisfaction towards PBL approach.

Uncertainty Evaluation of the SFR Subchannel Thermal-Hydraulic Modeling Using a Hot Channel Factors Analysis

International Nuclear Information System (INIS)

Choi, Sun Rock; Cho, Chung Ho; Kim, Sang Ji

2011-01-01

In an SFR core analysis, a hot channel factors (HCF) method is most commonly used to evaluate uncertainty. It was employed to the early design such as the CRBRP and IFR. In other ways, the improved thermal design procedure (ITDP) is able to calculate the overall uncertainty based on the Root Sum Square technique and sensitivity analyses of each design parameters. The Monte Carlo method (MCM) is also employed to estimate the uncertainties. In this method, all the input uncertainties are randomly sampled according to their probability density functions and the resulting distribution for the output quantity is analyzed. Since an uncertainty analysis is basically calculated from the temperature distribution in a subassembly, the core thermal-hydraulic modeling greatly affects the resulting uncertainty. At KAERI, the SLTHEN and MATRA-LMR codes have been utilized to analyze the SFR core thermal-hydraulics. The SLTHEN (steady-state LMR core thermal hydraulics analysis code based on the ENERGY model) code is a modified version of the SUPERENERGY2 code, which conducts a multi-assembly, steady state calculation based on a simplified ENERGY model. The detailed subchannel analysis code MATRA-LMR (Multichannel Analyzer for Steady-State and Transients in Rod Arrays for Liquid Metal Reactors), an LMR version of MATRA, was also developed specifically for the SFR core thermal-hydraulic analysis. This paper describes comparative studies for core thermal-hydraulic models. The subchannel analysis and a hot channel factors based uncertainty evaluation system is established to estimate the core thermofluidic uncertainties using the MATRA-LMR code and the results are compared to those of the SLTHEN code

Pedestrian-Vehicle Accidents Reconstruction with PC-Crash®: Sensibility Analysis of Factors Variation

Energy Technology Data Exchange (ETDEWEB)

Martinez Gala, F.

2016-07-01

This paper describes the main findings of a study performed by INSIA-UPM about the improvement of the reconstruction process of real world vehicle-pedestrian accidents using PC-Crash® software, aimed to develop a software tool for the estimation of the variability of the collision speed due to the lack of real values of some parameters required during the reconstruction task. The methodology has been based on a sensibility analysis of the factors variation. A total of 9 factors have been analyzed with the objective of identifying which ones were significant. Four of them (pedestrian height, collision angle, hood height and pedestrian-road friction coefficient) were significant and were included in a full factorial experiment with the collision speed as an additional factor in order to obtain a regression model with up to third level interactions. Two different factorial experiments with the same structure have been performed because of pedestrian gender differences. The tool has been created as a collision speed predictor based on the regression models obtained, using the 4 significant factors and the projection distance measured or estimated in the accident site. The tool has been used on the analysis of real-world reconstructed accidents occurred in the city of Madrid (Spain). The results have been adequate in most cases with less than 10% of deviation between the predicted speed and the one estimated in the reconstructions. (Author)

Using exploratory factor analysis in personality research: Best-practice recommendations

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Sumaya Laher

2010-11-01

Research purpose: This article presents more objective methods to determine the number of factors, most notably parallel analysis and Velicer’s minimum average partial (MAP. The benefits of rotation are also discussed. The article argues for more consistent use of Procrustes rotation and congruence coefficients in factor analytic studies. Motivation for the study: Exploratory factor analysis is often criticised for not being rigorous and objective enough in terms of the methods used to determine the number of factors, the rotations to be used and ultimately the validity of the factor structure. Research design, approach and method: The article adopts a theoretical stance to discuss the best-practice recommendations for factor analytic research in the field of psychology. Following this, an example located within personality assessment and using the NEO-PI-R specifically is presented. A total of 425 students at the University of the Witwatersrand completed the NEO-PI-R. These responses were subjected to a principal components analysis using varimax rotation. The rotated solution was subjected to a Procrustes rotation with Costa and McCrae’s (1992 matrix as the target matrix. Congruence coefficients were also computed. Main findings: The example indicates the use of the methods recommended in the article and demonstrates an objective way of determining the number of factors. It also provides an example of Procrustes rotation with coefficients of agreement as an indication of how factor analytic results may be presented more rigorously in local research. Practical/managerial implications: It is hoped that the recommendations in this article will have best-practice implications for both researchers and practitioners in the field who employ factor analysis regularly. Contribution/value-add: This article will prove useful to all researchers employing factor analysis and has the potential to set the trend for better use of factor analysis in the South African context.

Prognostic factors in nodular lymphomas: a multivariate analysis based on the Princess Margaret Hospital experience

International Nuclear Information System (INIS)

Gospodarowicz, M.K.; Bush, R.S.; Brown, T.C.; Chua, T.

1984-01-01

A total of 1,394 patients with non-Hodgkin's lymphoma were treated at the Princess Margaret Hospital between January 1, 1967 and December 31, 1978. Overall actuarial survival of 525 patients with nodular lymphomas was 40% at 12 years; survival of patients with localized (Stage I and III) nodular lymphomas treated with radical radiation therapy was 58%. Significant prognostic factors defined by multivariate analysis included patient's age, stage, histology, tumor bulk, and presence of B symptoms. By combining prognostic factors, distinct prognostic groups have been identified within the overall population. Patients with Stage I and II disease, small or medium bulk, less than 70 years of age achieved 92% 12 year actuarial survival and a 73% relapse-free rate in 12 years of follow-up. These patients represent groups highly curable with irradiation

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2005-04-28

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis

The development of human factors technologies -The development of human behaviour analysis techniques-

International Nuclear Information System (INIS)

Lee, Jung Woon; Lee, Yong Heui; Park, Keun Ok; Chun, Se Woo; Suh, Sang Moon; Park, Jae Chang

1995-07-01

In order to contribute to human error reduction through the studies on human-machine interaction in nuclear power plants, this project has objectives to develop SACOM(Simulation Analyzer with a Cognitive Operator Model) and techniques for human error analysis and application. In this year, we studied the followings: 1) Site investigation of operator tasks, 2) Development of operator task micro structure and revision of micro structure, 3) Development of knowledge representation software and SACOM prototype, 4) Development of performance assessment methodologies in task simulation and analysis of the effects of performance shaping factors. 1) Classification of error shaping factors(ESFs) and development of software for ESF evaluation, 2) Analysis of human error occurrences and revision of analysis procedure, 3) Experiment for human error data collection using a compact nuclear simulator, 4) Development of a prototype data base system of the analyzed information on trip cases. 55 figs, 23 tabs, 33 refs. (Author)

Factors influencing a problem-based learning implementation: A case study of IT courses

Science.gov (United States)

Darus, Norida Muhd; Mohd, Haslina; Baharom, Fauziah; Saip, Mohamed Ali; Puteh, Nurnasran; Marzuki @ Matt, Zaharin; Husain, Mohd Zabidin; Yasin, Azman

2016-08-01

IT students must be trained to work efficiently as teamwork. One of the techniques that can be used to train them is through Problem-Based Learning (PBL) approach. The PBL implementation can be influenced by various factors depending on the ultimate goal of the study. This study is focusing on the IT students' perception of the PBL implementation. The student's perception is important to ensure the successfulness of the PBL implementation. Therefore, it is important to identify the factors that might influence the implementation of PBL of IT courses. This study aims to identify some catalyst factors that may influence the PBL implementation of IT courses. The study involved three (3) main phases: identifying PBL implementation factors, constructing a PBL model, and PBL model validation using statistical analysis. Four main factors are identified: PBL Characteristics, PBL Course Assessment, PBL Practices, and PBL Perception. Based on these four factors, a PBL model is constructed. Then, based on the proposed PBL model, four hypotheses are formulated and analyzed to validate the model. All hypotheses are significantly acceptable. The result shows that the PBL Characteristics and PBL Course Assessment factors are significantly influenced the PBL Practices and indirectly influenced the Students' Perception of the PBL Implementation for IT courses. This PBL model can assist decision makers in enhancing the PBL teaching and learning strategy for IT courses. It is also can be tested to other courses in the future.

A computational intelligent approach to multi-factor analysis of violent crime information system

Science.gov (United States)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Using exploratory factor analysis of FFQ data to identify dietary patterns among Yup'ik people.

Science.gov (United States)

Ryman, Tove K; Austin, Melissa A; Hopkins, Scarlett; Philip, Jacques; O'Brien, Diane; Thummel, Kenneth; Boyer, Bert B

2014-03-01

An FFQ developed by the Center for Alaska Native Health Research for studies in Yup'ik people includes market foods and subsistence foods such as moose, seal, waterfowl and salmon that may be related to disease risk. Because the FFQ contains >100 food items, we sought to characterize dietary patterns more simply for use in ongoing pharmacogenomics studies. Exploratory factor analysis was used to derive a small number of 'factors' that explain a substantial amount of the variation in the Yup'ik diet. We estimated factor scores and measured associations with demographic characteristics and biomarkers. South-west Alaska, USA. Yup'ik people (n 358) aged ≥18 years. We identified three factors that each accounted for ≥10 % of the common variance: the first characterized by 'processed foods' (e.g. salty snacks, sweetened cereals); the second by 'fruits and vegetables' (e.g. fresh citrus, potato salad); and the third by 'subsistence foods' (seal or walrus soup, non-oily fish). Participants from coastal communities had higher values for the 'subsistence' factor, whereas participants from inland communities had higher values for the 'fruits and vegetables' factor. A biomarker of marine intake, δ 15N, was correlated with the 'subsistence' factor, whereas a biomarker of corn- and sugarcane-based market food intake, δ 13C, was correlated with 'processed foods'. The exploratory factor analysis identified three factors that appeared to reflect dietary patterns among Yup'ik based on associations with participant characteristics and biomarkers. These factors will be useful for chronic disease studies in this population.

[Cultural regionalization for Coptis chinensis based on 3S technology platform Ⅰ. Study on growth suitability for Coptis chinensis based on ecological factors analysis by Maxent and ArcGIS model].

Science.gov (United States)

Liu, Xin; Yang, Yan-Fang; Song, Hong-Ping; Zhang, Xiao-Bo; Huang, Lu-Qi; Wu, He-Zhen

2016-09-01

At the urgent request of Coptis chinensis planting,growth suitability as assessment indicators for C. chinensis cultivation was proposed and analyzed in this paper , based on chemical quality determination and ecological fators analysis by Maxent and ArcGIS model. Its potential distribution areas at differernt suitability grade and regionalization map were formulated based on statistical theory and growth suitability theory. The results showed that the most suitable habitats is some parts of Chongqing and Hubei province, such as Shizhu, Lichuan, Wulong, Wuxi, Enshi. There are seven ecological factor is the main ecological factors affect the growth of Coptidis Rhizoma, including altitude, precipitation in February and September and the rise of precipitation and altitude is conducive to the accumulation of total alkaloid content in C. chinensis. Therefore, The results of the study not only illustrates the most suitable for the surroundings of Coptidis Rhizoma, also helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants. Copyright© by the Chinese Pharmaceutical Association.

A preliminary survey of M. hyopneumoniae virulence factors based on comparative genomic analysis

Directory of Open Access Journals (Sweden)

Henrique Bunselmeyer Ferreira

2007-01-01

Full Text Available Mycoplasma hyopneumoniae is the etiological agent of porcine enzootic pneumonia (PEP, a major problem for the pig industry. The mechanisms of M. hyopneumoniae pathogenicity allow to predict the existence of several classes of virulence factors, whose study has been essentially restricted to the characterization of adhesion-related and major antigenic proteins. The now available complete sequences of the genomes of two pathogenic and one non-pathogenic strain of M. hyopneumoniae allowed to use a comparative genomics approach to putatively identify virulence genes. In this preliminary survey, we were able to identify 118 CDSs encoding putative virulence factors, based on specific criteria ranging from predicted cell surface location or variation between strains to previous functional studies showing antigenicity or involvement in host-pathogen interaction. This survey is expected to serve as a first step towards the functional characterization of new virulence genes/proteins that will be important not only for a better comprehension of M. hyopneumoniae biology, but also for the development of new and improved protocols for PEP vaccination, diagnosis and treatment.

Phosphoproteomics-based systems analysis of signal transduction networks

Directory of Open Access Journals (Sweden)

Hiroko eKozuka-Hata

2012-01-01

Full Text Available Signal transduction systems coordinate complex cellular information to regulate biological events such as cell proliferation and differentiation. Although the accumulating evidence on widespread association of signaling molecules has revealed essential contribution of phosphorylation-dependent interaction networks to cellular regulation, their dynamic behavior is mostly yet to be analyzed. Recent technological advances regarding mass spectrometry-based quantitative proteomics have enabled us to describe the comprehensive status of phosphorylated molecules in a time-resolved manner. Computational analyses based on the phosphoproteome dynamics accelerate generation of novel methodologies for mathematical analysis of cellular signaling. Phosphoproteomics-based numerical modeling can be used to evaluate regulatory network elements from a statistical point of view. Integration with transcriptome dynamics also uncovers regulatory hubs at the transcriptional level. These omics-based computational methodologies, which have firstly been applied to representative signaling systems such as the epidermal growth factor receptor pathway, have now opened up a gate for systems analysis of signaling networks involved in immune response and cancer.

SPATIAL VARIETY AND DISTRIBUTION OF TRADITIONAL MARKETS IN SURAKARTA AS POTENTIAL FACTORS IN IMPROVING SPATIAL-BASED MANAGEMENT

Directory of Open Access Journals (Sweden)

Istijabatul Aliyah

2017-02-01

Full Text Available Traditional markets function as trading place, socio-culture interaction, and recreation facility either in regional or urban scope. Distribution and variety of spatial condition influence traditional markets’ planning both physically and non-physically. Therefore, this research aimed to conduct a mapping of traditional markets’ spatial distribution and variety as potential factors to improve spatial-based management. Analysis methods including: (1 Mapping by employing Geographic Information System, (2 Category Based Analysis (CBA, and (3 Interactive Analysis were applied in Surakarta City as the research location. The result of this research signifies that spatial variety and distribution of traditional markets in Surakarta had similar pattern between one market to others; overlapping service function; specific commodity types in accordance with the market’s characteristics; diverse operating hours. Spatial variety and distribution could be potential factors to improve traditional market management as shopping service. This result was contrasted with Central Place Theory by Christaller and NÆss & Jensen’s research finding stating that distance became a key factor influencing accessibility to a number of activity facilities. Therefore, distance toward the service center is not considered as the main factor in traditional market management. The main factor in managing and controlling traditional markets’ development includes service function, commodity specification, and operating hour’s flexibility.

Obesity as a risk factor for developing functional limitation among older adults: A conditional inference tree analysis

Science.gov (United States)

Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to con...

The effect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling

Science.gov (United States)

Sulistyo, Bambang

2016-11-01

The research was aimed at studying the efect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling of The USLE using remote sensing data and GIS technique. Methods applied was by analysing all factors affecting erosion such that all data were in the form of raster. Those data were R, K, LS, C and P factors. Monthly R factor was evaluated based on formula developed by Abdurachman. K factor was determined using modified formula used by Ministry of Forestry based on soil samples taken in the field. LS factor was derived from Digital Elevation Model. Three C factors used were all derived from NDVI and developed by Suriyaprasit (non-linear) and by Sulistyo (linear and non-linear). P factor was derived from the combination between slope data and landcover classification interpreted from Landsat 7 ETM+. Another analysis was the creation of map of Bulk Density used to convert erosion unit. To know the model accuracy, model validation was done by applying statistical analysis and by comparing Emodel with Eactual. A threshold value of ≥ 0.80 or ≥ 80% was chosen to justify. The research result showed that all Emodel using three formulae of C factors have coeeficient of correlation value of > 0.8. The results of analysis of variance showed that there was significantly difference between Emodel and Eactual when using C factor formula developed by Suriyaprasit and Sulistyo (non-linear). Among the three formulae, only Emodel using C factor formula developed by Sulistyo (linear) reached the accuracy of 81.13% while the other only 56.02% as developed by Sulistyo (nonlinear) and 4.70% as developed by Suriyaprasit, respectively.

Factors influencing societal response of nanotechnology: an expert stakeholder analysis

Energy Technology Data Exchange (ETDEWEB)

Gupta, Nidhi, E-mail: nidhi.gupta@wur.nl; Fischer, Arnout R. H., E-mail: arnout.fischer@wur.nl; Lans, Ivo A. van der, E-mail: Ivo.vanderLans@wur.nl [Wageningen University, Marketing and Consumer Behaviour Group (Netherlands); Frewer, Lynn J., E-mail: lynn.frewer@newcastle.ac.uk [Newcastle University, School of Agriculture, Food and Rural Development (United Kingdom)

2012-05-15

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

Adjusting for multiple prognostic factors in the analysis of randomised trials

Science.gov (United States)

2013-01-01

Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not

Risk factors for chronic and recurrent otitis media-a meta-analysis.

Directory of Open Access Journals (Sweden)

Yan Zhang

Full Text Available Risk factors associated with chronic otitis media (COM and recurrent otitis media (ROM have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001. An upper respiratory tract infection (URTI significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; P<0.00001. Snoring appeared to be a significant risk factor for COM/ROM (OR, 1.96; 95% CI, 1.78-2.16; P<0.00001. A patient history of acute otitis media (AOM/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04. Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04. Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03. Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

Analysis on nuclear power plant control room system design and improvement based on human factor engineering

International Nuclear Information System (INIS)

Gao Feng; Liu Yanzi; Sun Yongbin

2014-01-01

The design of nuclear power plant control room system is a process of improvement with the implementation of human factor engineering theory and guidance. The method of implementation human factor engineering principles into the nuclear power plant control room system design and improvement was discussed in this paper. It is recommended that comprehensive address should be done from control room system function, human machine interface, digital procedure, control room layout and environment design based on the human factor engineering theory and experience. The main issues which should be paid more attention during the control room system design and improvement also were addressed in this paper, and then advices and notices for the design and improvement of the nuclear power plant control room system were afforded. (authors)

Analysis and optimization of the TWINKLE factoring device

NARCIS (Netherlands)

Lenstra, A.K.; Shamir, A.; Preneel, B.

2000-01-01

We describe an enhanced version of the TWINKLE factoring device and analyse to what extent it can be expected to speed up the sieving step of the Quadratic Sieve and Number Field Sieve factoring al- gorithms. The bottom line of our analysis is that the TWINKLE-assisted factorization of 768-bit

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose

Analysis of psychological factors for quality assessment of interactive multimodal service

Science.gov (United States)

Yamagishi, Kazuhisa; Hayashi, Takanori

2005-03-01

We proposed a subjective quality assessment model for interactive multimodal services. First, psychological factors of an audiovisual communication service were extracted by using the semantic differential (SD) technique and factor analysis. Forty subjects participated in subjective tests and performed point-to-point conversational tasks on a PC-based TV phone that exhibits various network qualities. The subjects assessed those qualities on the basis of 25 pairs of adjectives. Two psychological factors, i.e., an aesthetic feeling and a feeling of activity, were extracted from the results. Then, quality impairment factors affecting these two psychological factors were analyzed. We found that the aesthetic feeling is mainly affected by IP packet loss and video coding bit rate, and the feeling of activity depends on delay time and video frame rate. We then proposed an opinion model derived from the relationships among quality impairment factors, psychological factors, and overall quality. The results indicated that the estimation error of the proposed model is almost equivalent to the statistical reliability of the subjective score. Finally, using the proposed model, we discuss guidelines for quality design of interactive audiovisual communication services.

[Factors and validity analysis of Mini-Mental State Examination in Chinese elderly people].

Science.gov (United States)

Gao, Ming-yue; Yang, Min; Kuang, Wei-hong; Qiu, Pei-yuan

2015-06-18

To examine factors that may have impact on the Mini-Mental State Examination (MMSE) screening validity, which could lead to further establishing the general model of the MMSE score in Chinese health elderly and to improve the screening accuracy of the existing MMSE reference. Based on the data of the Chinese Longitudinal Healthy Longevity Survey (CLHLS), the MMSE scores of 19,117 normal elderly and 137 dementia patients who met the inclusion criteria were used for the analysis. The area under the curve (AUC) and validity indexes were used to compare the screening accuracy of various criteria. Multiple linear regression was used to identify factors that had impact on the MMSE score for both the normal and dementia elderly. Descriptive analysis was performed for differences in the MMSE scores by age trends and gender between the normal and dementia elderly. The AUC of MMSE was ≥0.75(Pvalidity of MMSE in CLHLS is not affected by educational level. The analysis of factors that may impact on the MMSE screening validity are gender, age, vision and residence which with validity identification. These four factors can be used as assist tool of MMSE in the screening of dementia to improve the screening accuracy.

BASE - 2nd generation software for microarray data management and analysis

Directory of Open Access Journals (Sweden)

Nordborg Nicklas

2009-10-01

Full Text Available Abstract Background Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. Results The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. Conclusion BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

BASE--2nd generation software for microarray data management and analysis.

Science.gov (United States)

Vallon-Christersson, Johan; Nordborg, Nicklas; Svensson, Martin; Häkkinen, Jari

2009-10-12

Microarray experiments are increasing in size and samples are collected asynchronously over long time. Available data are re-analysed as more samples are hybridized. Systematic use of collected data requires tracking of biomaterials, array information, raw data, and assembly of annotations. To meet the information tracking and data analysis challenges in microarray experiments we reimplemented and improved BASE version 1.2. The new BASE presented in this report is a comprehensive annotable local microarray data repository and analysis application providing researchers with an efficient information management and analysis tool. The information management system tracks all material from biosource, via sample and through extraction and labelling to raw data and analysis. All items in BASE can be annotated and the annotations can be used as experimental factors in downstream analysis. BASE stores all microarray experiment related data regardless if analysis tools for specific techniques or data formats are readily available. The BASE team is committed to continue improving and extending BASE to make it usable for even more experimental setups and techniques, and we encourage other groups to target their specific needs leveraging on the infrastructure provided by BASE. BASE is a comprehensive management application for information, data, and analysis of microarray experiments, available as free open source software at http://base.thep.lu.se under the terms of the GPLv3 license.

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

International Nuclear Information System (INIS)

Konstandinidou, Myrto; Nivolianitou, Zoe; Kefalogianni, Eirini; Caroni, Chrys

2011-01-01

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents. - Highlights: → The research work is original, based on field data collected directly from the petrochemical industry. → It deals with the in-depth statistical analysis of accident data on human-organizational causes. → It researches underlying causes of accidents and the parameters affecting them. → The causal factors that are considered cover four big taxonomies. → Near misses are worth recording for comparing their causal factors with more serious incidents.

Transforming Rubrics Using Factor Analysis

Science.gov (United States)

Baryla, Ed; Shelley, Gary; Trainor, William

2012-01-01

Student learning and program effectiveness is often assessed using rubrics. While much time and effort may go into their creation, it is equally important to assess how effective and efficient the rubrics actually are in terms of measuring competencies over a number of criteria. This study demonstrates the use of common factor analysis to identify…

Theory of sampling: four critical success factors before analysis.

Science.gov (United States)

Wagner, Claas; Esbensen, Kim H

2015-01-01

Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.

A Factor Analysis of the BSRI and the PAQ.

Science.gov (United States)

Edwards, Teresa A.; And Others

Factor analysis of the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) was undertaken to study the independence of the masculine and feminine scales within each instrument. Both instruments were administered to undergraduate education majors. Analysis of primary first and second order factors of the BSRI indicated…

Identification of noise in linear data sets by factor analysis

International Nuclear Information System (INIS)

Roscoe, B.A.; Hopke, Ph.K.

1982-01-01

A technique which has the ability to identify bad data points, after the data has been generated, is classical factor analysis. The ability of classical factor analysis to identify two different types of data errors make it ideally suited for scanning large data sets. Since the results yielded by factor analysis indicate correlations between parameters, one must know something about the nature of the data set and the analytical techniques used to obtain it to confidentially isolate errors. (author)

"Factor Analysis Using ""R"""

Directory of Open Access Journals (Sweden)

A. Alexander Beaujean

2013-02-01

Full Text Available R (R Development Core Team, 2011 is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free and flexibility (its open-source. This article gives a general introduction to using R (i.e., loading the program, using functions, importing data. Then, using data from Canivez, Konold, Collins, and Wilson (2009, this article walks the user through how to use the program to conduct factor analysis, from both an exploratory and confirmatory approach.

Simulation-Based Approach to Operating Costs Analysis of Freight Trucking

Directory of Open Access Journals (Sweden)

Ozernova Natalja

2015-12-01

Full Text Available The article is devoted to the problem of costs uncertainty in road freight transportation services. The article introduces the statistical approach, based on Monte Carlo simulation on spreadsheets, to the analysis of operating costs. The developed model gives an opportunity to estimate operating freight trucking costs under different configuration of cost factors. Important conclusions can be made after running simulations regarding sensitivity to different factors, optimal decisions and variability of operating costs.

Obesity as a risk factor for developing functional limitation among older adults: A conditional inference tree analysis.

Science.gov (United States)

Cheng, Feon W; Gao, Xiang; Bao, Le; Mitchell, Diane C; Wood, Craig; Sliwinski, Martin J; Smiciklas-Wright, Helen; Still, Christopher D; Rolston, David D K; Jensen, Gordon L

2017-07-01

To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. The conditional inference tree analysis, a data mining approach, was used to construct a risk stratification algorithm for developing functional limitation based on BMI and other potential risk factors for disability in 1,951 older adults without functional limitations at baseline (baseline age 73.1 ± 4.2 y). We also analyzed the data with multivariate stepwise logistic regression and compared the two approaches (e.g., cross-validation). Over a mean of 9.2 ± 1.7 years of follow-up, 221 individuals developed functional limitation. Higher BMI, age, and comorbidity were consistently identified as significant risk factors for functional decline using both methods. Based on these factors, individuals were stratified into four risk groups via the conditional inference tree analysis. Compared to the low-risk group, all other groups had a significantly higher risk of developing functional limitation. The odds ratio comparing two extreme categories was 9.09 (95% confidence interval: 4.68, 17.6). Higher BMI, age, and comorbid disease were consistently identified as significant risk factors for functional decline among older individuals across all approaches and analyses. © 2017 The Obesity Society.

Analysis of risk factors for schizophrenia with two different case definitions: a nationwide register-based external validation study.

Science.gov (United States)

Sørensen, Holger J; Larsen, Janne T; Mors, Ole; Nordentoft, Merete; Mortensen, Preben B; Petersen, Liselotte

2015-03-01

Different case definitions of schizophrenia have been used in register based research. However, no previous study has externally validated two different case definitions of schizophrenia against a wide range of risk factors for schizophrenia. We investigated hazard ratios (HRs) for a wide range of risk factors for ICD-10 DCR schizophrenia using a nationwide Danish sample of 2,772,144 residents born in 1955-1997. We compared one contact only (OCO) (the case definition of schizophrenia used in Danish register based studies) with two or more contacts (TMC) (a case definition of at least 2 inpatient contacts with schizophrenia). During the follow-up, the OCO definition included 15,074 and the TMC 7562 cases; i.e. half as many. The TMC case definition appeared to select for a worse illness course. A wide range of risk factors were uniformly associated with both case definitions and only slightly higher risk estimates were found for the TMC definition. Choosing at least 2 inpatient contacts with schizophrenia (TMC) instead of the currently used case definition would result in almost similar risk estimates for many well-established risk factors. However, this would also introduce selection and include considerably fewer cases and reduce power of e.g. genetic studies based on register-diagnosed cases only. Copyright © 2015 Elsevier B.V. All rights reserved.

The Recoverability of P-Technique Factor Analysis

Science.gov (United States)

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…

Analysis of the flood extent extraction model and the natural flood influencing factors: A GIS-based and remote sensing analysis

International Nuclear Information System (INIS)

Lawal, D U; Matori, A N; Yusuf, K W; Hashim, A M; Balogun, A L

2014-01-01

Serious floods have hit the State of Perlis in 2005, 2010, as well as 2011. Perlis is situated in the northern part of Peninsula Malaysia. The floods caused great damage to properties and human lives. There are various methods used in an attempt to provide the most reliable ways to reduce the flood risk and damage to the optimum level by identifying the flood vulnerable zones. The purpose of this paper is to develop a flood extent extraction model based on Minimum Distance Algorithm and to overlay with the natural flood influencing factors considered herein in order to examine the effect of each factor in flood generation. GIS spatial database was created from a geological map, SPOT satellite image, and the topographical map. An attribute database was equally created from field investigations and historical flood areas reports of the study area. The results show a great correlation between the flood extent extraction model and the flood factors

Analyzing the factors affecting network lifetime cluster-based wireless sensor network

International Nuclear Information System (INIS)

Malik, A.S.; Qureshi, A.

2010-01-01

Cluster-based wireless sensor networks enable the efficient utilization of the limited energy resources of the deployed sensor nodes and hence prolong the node as well as network lifetime. Low Energy Adaptive Clustering Hierarchy (Leach) is one of the most promising clustering protocol proposed for wireless sensor networks. This paper provides the energy utilization and lifetime analysis for cluster-based wireless sensor networks based upon LEACH protocol. Simulation results identify some important factors that induce unbalanced energy utilization between the sensor nodes and hence affect the network lifetime in these types of networks. These results highlight the need for a standardized, adaptive and distributed clustering technique that can increase the network lifetime by further balancing the energy utilization among sensor nodes. (author)

The Analysis of the Contribution of Human Factors to the In-Flight Loss of Control Accidents

Science.gov (United States)

Ancel, Ersin; Shih, Ann T.

2012-01-01

In-flight loss of control (LOC) is currently the leading cause of fatal accidents based on various commercial aircraft accident statistics. As the Next Generation Air Transportation System (NextGen) emerges, new contributing factors leading to LOC are anticipated. The NASA Aviation Safety Program (AvSP), along with other aviation agencies and communities are actively developing safety products to mitigate the LOC risk. This paper discusses the approach used to construct a generic integrated LOC accident framework (LOCAF) model based on a detailed review of LOC accidents over the past two decades. The LOCAF model is comprised of causal factors from the domain of human factors, aircraft system component failures, and atmospheric environment. The multiple interdependent causal factors are expressed in an Object-Oriented Bayesian belief network. In addition to predicting the likelihood of LOC accident occurrence, the system-level integrated LOCAF model is able to evaluate the impact of new safety technology products developed in AvSP. This provides valuable information to decision makers in strategizing NASA's aviation safety technology portfolio. The focus of this paper is on the analysis of human causal factors in the model, including the contributions from flight crew and maintenance workers. The Human Factors Analysis and Classification System (HFACS) taxonomy was used to develop human related causal factors. The preliminary results from the baseline LOCAF model are also presented.

Task-based factors influencing the successful functioning of copreneurial businesses in South Africa

Directory of Open Access Journals (Sweden)

Shelley Farrington

2011-03-01

Full Text Available Globally, evidence exists to suggest that the number of copreneurial businesses or spousal partnerships are on the increase. The primary objectives of this study are to identify the task-based factors influencing the effectiveness of a copreneurial business, to propose a conceptual model based on these factors and to subject the model to empirical testing. The model is empirically tested among copreneurial businesses to assess potential relationships between selected independent variables (shared dream, leadership, personal needs alignment, division of labour, complementary skills, supportive employees, competencies and adequate resources and measures of copreneurial success (perceived success and financial performance. In order to address the primary objective of this study, a questionnaire was administered to a sample of 1548 respondents (spouses in business together of which 380 questionnaires were useable for statistical analysis. The empirical results revealed that apart from division of labour all the other factors investigated exert a significant influence on the successful functioning of copreneurial businesses.

ANALYSIS OF FACTORS CAUSING WATER DAMAGE TO LOESS DOUBLE-ARCHED TUNNEL BASED ON TFN-AHP

Directory of Open Access Journals (Sweden)

Mao Zheng-jun

2017-04-01

Full Text Available In order to analysis the factors causing water damage to loess double-arched tunnel, this paper conducts field investigation on water damage to tunnels on Lishi-Jundu Expressway in Shanxi, China, confirms its development characteristics, builds an index system (covering 36 evaluation indexes for construction condition, design stage, construction stage, and operation stage for the factors causing water damage to loess double-arched tunnel, applies TFN-AHP (triangular fuzzy number-analytic hierarchy process in calculating the weight of indexes at different levels, and obtains the final sequence of weight of the factors causing water seepage to loess double-arched tunnel. It is found out that water damage to loess double-arched tunnel always develops in construction joints, expansion joints, settlement joints, and lining joints of tunnel and even around them; there is dotted water seepage, linear water seepage, and planar water seepage according to the trace and scope of water damage to tunnel lining. The result shows that water damage to loess double-arched tunnel mainly refers to linear water seepage, planar water seepage is also developed well, and partition and equipment box at the entrance and exit of tunnel are prone to water seepage; construction stage is crucial for controlling water damage to loess double-arched tunnel, atmospheric precipitation is the main water source, and the structure defect of double-arched tunnel increases the possibility of water seepage; the final sequence for weight of various factors is similar to the actual result.

Climatic and basin factors affecting the flood frequency curve: PART I – A simple sensitivity analysis based on the continuous simulation approach

Directory of Open Access Journals (Sweden)

A. M. Hashemi

2000-01-01

Full Text Available Regionalized and at-site flood frequency curves exhibit considerable variability in their shapes, but the factors controlling the variability (other than sampling effects are not well understood. An application of the Monte Carlo simulation-based derived distribution approach is presented in this two-part paper to explore the influence of climate, described by simulated rainfall and evapotranspiration time series, and basin factors on the flood frequency curve (ffc. The sensitivity analysis conducted in the paper should not be interpreted as reflecting possible climate changes, but the results can provide an indication of the changes to which the flood frequency curve might be sensitive. A single site Neyman Scott point process model of rainfall, with convective and stratiform cells (Cowpertwait, 1994; 1995, has been employed to generate synthetic rainfall inputs to a rainfall runoff model. The time series of the potential evapotranspiration (ETp demand has been represented through an AR(n model with seasonal component, while a simplified version of the ARNO rainfall-runoff model (Todini, 1996 has been employed to simulate the continuous discharge time series. All these models have been parameterised in a realistic manner using observed data and results from previous applications, to obtain ‘reference’ parameter sets for a synthetic case study. Subsequently, perturbations to the model parameters have been made one-at-a-time and the sensitivities of the generated annual maximum rainfall and flood frequency curves (unstandardised, and standardised by the mean have been assessed. Overall, the sensitivity analysis described in this paper suggests that the soil moisture regime, and, in particular, the probability distribution of soil moisture content at the storm arrival time, can be considered as a unifying link between the perturbations to the several parameters and their effects on the standardised and unstandardised ffcs, thus revealing the

Financial Risk Factor Analysis for Facility Gas Leakages of H2 and NG

Directory of Open Access Journals (Sweden)

In-Bok Lee

2016-09-01

Full Text Available Fuel cells may be the key to a more environmentally-friendly future because they emit low carbon dioxide per unit of energy supplied. However, little work has investigated the potential financial risks pertaining to fuel cell systems. Often used in the analysis of the safety of systems involving flammable or hazardous materials, risk factor analysis has recently been used to analyze the potential financial losses that may occur from industrial hazards. Therefore, this work undertakes a financial risk factor analysis to determine the costs of leakages of hydrogen and natural gas, which are used in fuel cell systems. Total leakage was calculated from an analysis of several leakage rates and modes. The impact of applying appropriate detection and prevention systems was also investigated. The findings were then used to analyze the consequences for various sections of the system and to calculate the overall cost based on facility outage or damage, and the cost of taking safety precautions. This provides a basis for comparison among proposed potential reactionary measures.

Genomic identification of WRKY transcription factors in carrot (Daucus carota) and analysis of evolution and homologous groups for plants.

Science.gov (United States)

Li, Meng-Yao; Xu, Zhi-Sheng; Tian, Chang; Huang, Ying; Wang, Feng; Xiong, Ai-Sheng

2016-03-15

WRKY transcription factors belong to one of the largest transcription factor families. These factors possess functions in plant growth and development, signal transduction, and stress response. Here, we identified 95 DcWRKY genes in carrot based on the carrot genomic and transcriptomic data, and divided them into three groups. Phylogenetic analysis of WRKY proteins from carrot and Arabidopsis divided these proteins into seven subgroups. To elucidate the evolution and distribution of WRKY transcription factors in different species, we constructed a schematic of the phylogenetic tree and compared the WRKY family factors among 22 species, which including plants, slime mold and protozoan. An in-depth study was performed to clarify the homologous factor groups of nine divergent taxa in lower and higher plants. Based on the orthologous factors between carrot and Arabidopsis, 38 DcWRKY proteins were calculated to interact with other proteins in the carrot genome. Yeast two-hybrid assay showed that DcWRKY20 can interact with DcMAPK1 and DcMAPK4. The expression patterns of the selected DcWRKY genes based on transcriptome data and qRT-PCR suggested that those selected DcWRKY genes are involved in root development, biotic and abiotic stress response. This comprehensive analysis provides a basis for investigating the evolution and function of WRKY genes.

Integrating human factors into process hazard analysis

International Nuclear Information System (INIS)

Kariuki, S.G.; Loewe, K.

2007-01-01

A comprehensive process hazard analysis (PHA) needs to address human factors. This paper describes an approach that systematically identifies human error in process design and the human factors that influence its production and propagation. It is deductive in nature and therefore considers human error as a top event. The combinations of different factors that may lead to this top event are analysed. It is qualitative in nature and is used in combination with other PHA methods. The method has an advantage because it does not look at the operator error as the sole contributor to the human failure within a system but a combination of all underlying factors

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.

Science.gov (United States)

Lin, Johnny; Bentler, Peter M

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.

Applications of factor analysis to electron and ion beam surface techniques

International Nuclear Information System (INIS)

Solomon, J.S.

1987-01-01

Factor analysis, a mathematical technique for extracting chemical information from matrices of data, is used to enhance Auger electron spectroscopy (AES), core level electron energy loss spectroscopy (EELS), ion scattering spectroscopy (ISS), and secondary ion mass spectroscopy (SIMS) in studies of interfaces, thin films, and surfaces. Several examples of factor analysis enhancement of chemical bonding variations in thin films and at interfaces studied with AES and SIMS are presented. Factor analysis is also shown to be of great benefit in quantifying electron and ion beam doses required to induce surface damage. Finally, examples are presented of the use of factor analysis to reconstruct elemental profiles when peaks of interest overlap each other during the course of depth profile analysis. (author)

Factor Analysis Based on SPSS Software%基于SPSS软件的因子分析

Institute of Scientific and Technical Information of China (English)

魏威; 王诗雨

2015-01-01

In the daily management work, managers often need to adjust the policy through multiple data, and the data will sometimes contain multiple variables or cases, which is very complex and cumbersome to use artificial analysis. In this paper we will make factor analysis through SPSS software because this software has easy operating interface and many different data analysis functions. Beside of this, through simple steps with SPSS software the re-sult can be clearly generated, which is very helpful to make further analysis, even strategy decision.%在日常管理工作中，管理者经常需要通过各项数据进行策略调整，而数据有时会包含多个变量或案例，用人工进行分析繁琐复杂。本文利用SPSS数据分析软件易于操作的图形界面和数据分析等功能，以德国16个城市的垃圾、街道、水等数据为例，进行因子分析，最后生成结果。

Latent segmentation based count models: Analysis of bicycle safety in Montreal and Toronto.

Science.gov (United States)

Yasmin, Shamsunnahar; Eluru, Naveen

2016-10-01

The study contributes to literature on bicycle safety by building on the traditional count regression models to investigate factors affecting bicycle crashes at the Traffic Analysis Zone (TAZ) level. TAZ is a traffic related geographic entity which is most frequently used as spatial unit for macroscopic crash risk analysis. In conventional count models, the impact of exogenous factors is restricted to be the same across the entire region. However, it is possible that the influence of exogenous factors might vary across different TAZs. To accommodate for the potential variation in the impact of exogenous factors we formulate latent segmentation based count models. Specifically, we formulate and estimate latent segmentation based Poisson (LP) and latent segmentation based Negative Binomial (LNB) models to study bicycle crash counts. In our latent segmentation approach, we allow for more than two segments and also consider a large set of variables in segmentation and segment specific models. The formulated models are estimated using bicycle-motor vehicle crash data from the Island of Montreal and City of Toronto for the years 2006 through 2010. The TAZ level variables considered in our analysis include accessibility measures, exposure measures, sociodemographic characteristics, socioeconomic characteristics, road network characteristics and built environment. A policy analysis is also conducted to illustrate the applicability of the proposed model for planning purposes. This macro-level research would assist decision makers, transportation officials and community planners to make informed decisions to proactively improve bicycle safety - a prerequisite to promoting a culture of active transportation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Behavioral factors predicting response to employment-based reinforcement of cocaine abstinence in methadone patients

OpenAIRE

Holtyn, August F.; Washington, Wendy Donlin; Knealing, Todd W.; Wong, Conrad J.; Kolodner, Ken; Silverman, Kenneth

2016-01-01

We sought to identify behavioral factors associated with response to an employment-based intervention, in which participants had to provide drug-free urine samples to gain access to paid employment. The present secondary analysis included data from a randomized clinical trial. The trial evaluated whether employment-based reinforcement could decrease cocaine use in community methadone patients. Participants (N=56) in the trial worked in a model workplace for 4 hr every weekday and earned about...

Structural equation modeling analysis of factors influencing architects' trust in project design teams

Institute of Scientific and Technical Information of China (English)

DING Zhi-kun; NG Fung-fai; WANG Jia-yuan

2009-01-01

This paper describes a structural equation modeling (SEM) analysis of factors influencing architects' trust in project design teams. We undertook a survey of architects, during which we distributed 193 questionnaires in 29 A-level architectural We used Amos 6.0 for SEM to identify significant personal construct based factors affecting interpersonal trust. The results show that only social interaction between architects significantly affects their interpersonal trust. The explained variance of trust is not very high in the model. Therefore, future research should add more factors into the current model. The practical implication is that team managers should promote the social interactions between team members such that the interpersonal trust level between team members can be improved.

Analysis of Bernstein's factorization circuit

NARCIS (Netherlands)

Lenstra, A.K.; Shamir, A.; Tomlinson, J.; Tromer, E.; Zheng, Y.

2002-01-01

In [1], Bernstein proposed a circuit-based implementation of the matrix step of the number field sieve factorization algorithm. These circuits offer an asymptotic cost reduction under the measure "construction cost x run time". We evaluate the cost of these circuits, in agreement with [1], but argue

Analysis of Factors Influencing Activity-Based Costing Applications in the Hospitality Industry in Yenagoa, Nigeria

OpenAIRE

Appah, Ebimobowei; Bariweni Binaebi

2013-01-01

This research examines the factors influencing activity-based costing application in the hospitality industry in Yenagoa, Nigeria. To achieve this objective, primary and secondary data were used. The secondary data include books, journals, periodicals, unpublished research materials and the internet and the primary data include interview and a well structured questionnaire administered to one hundred and 165 respondents in the 50 hotels sampled from the population. The data collected from the...

The application of factor analysis for whole body gamma spectra work up

Energy Technology Data Exchange (ETDEWEB)

Ragan, P; Fueloep, M [Inst. of Preventive and Clinical Medicine, 83301 Bratislava (Slovakia). Dept. of Radiation Hygiene; Krnac, S [Slovak Technical Univ., 81219 Bratislava (Slovakia). Dept. of Nuclear Physics and Technology

1996-12-31

The results of whole body (WB) counting with small high purity germanium detector were presented. The scaling confirmation factor analysis (SCFA) method based on factorization of the response operator is very sensitive and for this application suitable method how to decrease limits of detection. The minimal detectable activity (MDA, for counting time of person 7200 s, background 58600 s and 99% confidence level) of detector usually used in our laboratory for WB counting (relative efficiency 61.8%) 18.5 Bq and MDA for the SCFA method for small detector 17.9 are very close. The use of SCFA method improves the sensitivity (MDA) by factor of 4.1 and the small detector is comparable in sensitivity with the larger one (J.K). 4 tabs., 5 figs., 3 refs.

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-07-21

This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. A. Wasiolek

2003-01-01

This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in the biosphere. The biosphere process

Identifying and Quantifying Cultural Factors That Matter to the IT Workforce: An Approach Based on Automated Content Analysis

DEFF Research Database (Denmark)

Schmiedel, Theresa; Müller, Oliver; Debortoli, Stefan

2016-01-01

builds on 112,610 online reviews of Fortune 500 IT companies collected from Glassdoor, an online platform on which current and former employees can anonymously review companies and their management. We perform an automated content analysis to identify cultural factors that employees emphasize...

Probability based load factors for design of concrete containment structures

International Nuclear Information System (INIS)

Hwang, H.; Kagami, S.; Reich, M.; Ellingwood, B.; Shinozuka, M.

1985-01-01

This paper describes a procedure for developing probability-based load combinations for the design of concrete containments. The proposed criteria are in a load and resistance factor design (LRFD) format. The load factors and resistance factors are derived for use in limit states design and are based on a target limit state probability. In this paper, the load factors for accident pressure and safe shutdown earthquake are derived for three target limit state probabilities. Other load factors are recommended on the basis of prior experience with probability-based design criteria for ordinary building construction. 6 refs

National Institutes of Health Toolbox Emotion Battery for English- and Spanish-speaking adults: normative data and factor-based summary scores.

Science.gov (United States)

Babakhanyan, Ida; McKenna, Benjamin S; Casaletto, Kaitlin B; Nowinski, Cindy J; Heaton, Robert K

2018-01-01

The National Institutes of Health Toolbox Emotion Battery (NIHTB-EB) is a "common currency", computerized assessment developed to measure the full spectrum of emotional health. Though comprehensive, the NIHTB-EB's 17 scales may be unwieldy for users aiming to capture more global indices of emotional functioning. NIHTB-EB was administered to 1,036 English-speaking and 408 Spanish-speaking adults as a part of the NIH Toolbox norming project. We examined the factor structure of the NIHTB-EB in English- and Spanish-speaking adults and developed factor analysis-based summary scores. Census-weighted norms were presented for English speakers, and sample-weighted norms were presented for Spanish speakers. Exploratory factor analysis for both English- and Spanish-speaking cohorts resulted in the same 3-factor solution: 1) negative affect, 2) social satisfaction, and 3) psychological well-being. Confirmatory factor analysis supported similar factor structures for English- and Spanish-speaking cohorts. Model fit indices fell within the acceptable/good range, and our final solution was optimal compared to other solutions. Summary scores based upon the normative samples appear to be psychometrically supported and should be applied to clinical samples to further validate the factor structures and investigate rates of problematic emotions in medical and psychiatric populations.

Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

Science.gov (United States)

Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

2013-01-01

Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

Factors associated with quality of life in active childhood epilepsy: a population-based study.

Science.gov (United States)

Reilly, Colin; Atkinson, Patricia; Das, Krishna B; Chin, Richard F M; Aylett, Sarah E; Burch, Victoria; Gillberg, Christopher; Scott, Rod C; Neville, Brian G R

2015-05-01

Improving health-related quality of life (HRQOL), rather than just reducing seizures, should be the principal goal in comprehensive management of childhood epilepsy. There is a lack of population-based data on predictors of HRQOL in childhood epilepsy. The Children with Epilepsy in Sussex Schools (CHESS) study is a prospective, population-based study involving school-aged children (5-15 years) with active epilepsy (on one or more AED and/or had a seizure in the last year) in a defined geographical area in the UK. Eighty-five of 115 (74% of eligible population) children underwent comprehensive psychological assessment including measures of cognition, behaviour, and motor functioning. Parents of the children completed the Quality of Life in Childhood Epilepsy (QOLCE).Clinical data on eligible children was extracted using a standardised pro forma. Linear regression analysis was undertaken to identify factors significantly associated with total Quality of Life in this population. Factors independently significantly associated (p QOLCE scores were seizures before 24 months, cognitive impairment (IQ QOLCE when children with IQ < 50 were excluded from analysis. The majority of factors associated with parent reported HRQOL in active childhood epilepsy are related to neurobehavioural and/or psychosocial aspects of the condition. Copyright © 2015 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

A replication of a factor analysis of motivations for trapping

Science.gov (United States)

Schroeder, Susan; Fulton, David C.

2015-01-01

Using a 2013 sample of Minnesota trappers, we employed confirmatory factor analysis to replicate an exploratory factor analysis of trapping motivations conducted by Daigle, Muth, Zwick, and Glass (1998).  We employed the same 25 items used by Daigle et al. and tested the same five-factor structure using a recent sample of Minnesota trappers. We also compared motivations in our sample to those reported by Daigle et el.

Analysis of factors affecting employee satisfaction: A case study from Pakistan.

Science.gov (United States)

Rukh, Lala; Choudhary, Muhammad Abbas; Abbasi, Saddam Akber

2015-01-01

Employee job satisfaction has been a research focal point throughout the world. It is a key factor when measuring the performance of an organization and individuals. A leading engineering goods manufacturing enterprise in Pakistan, has been used in this case study. In Pakistan, very limited research has been done with respect to factors affecting job satisfaction. Some research has been done in medical institutions, banks, universities and the information technology sector but large public sector organizations in Pakistan have not been studied. A theoretical foundation for researching factors affecting job satisfaction in large organizations is outlined. The objective of this research is to analyze various demographic, financial and non-financial factors affecting the satisfaction level of employees and to study the effects across different employee groups. This study is based on quantitative data analysis. The employees of the organization under study have been divided into 10 homogeneous groups based on their departments. Information on job related factors (affecting the satisfaction level) have been collected from subsamples of each group using a self-administered questionnaire. An overall sample of 250 (out of total 1100) employees has been selected. Before conducting the survey, reliability of the questionnaire was measured using Cronbach's alpha. The normality of data was also examined using the Kolmogorov Smirnov test. Hypotheses devised to address the research questions were tested by using non-parametric Spearman correlation and Kruskal-Wallis tests. The response rate was 73.2%. Research findings indicated the significant factors that affect the satisfaction level of employees. Median group differences existed between responses based on age, work experience, salary and designation (i.e. job position/rank) of employees. Job satisfaction was also positively and significantly associated with job related factors such as pay, promotion, relation with employees

A Bayesian Nonparametric Approach to Factor Analysis

DEFF Research Database (Denmark)

Piatek, Rémi; Papaspiliopoulos, Omiros

2018-01-01

This paper introduces a new approach for the inference of non-Gaussian factor models based on Bayesian nonparametric methods. It relaxes the usual normality assumption on the latent factors, widely used in practice, which is too restrictive in many settings. Our approach, on the contrary, does no...

Importance-performance analysis based SWOT analysis

OpenAIRE

Phadermrod, Boonyarat; Crowder, Richard M.; Wills, Gary B.

2016-01-01

SWOT analysis, a commonly used tool for strategic planning, is traditionally a form of brainstorming. Hence, it has been criticised that it is likely to hold subjective views of the individuals who participate in a brainstorming session and that SWOT factors are not prioritized by their significance thus it may result in an improper strategic action. While most studies of SWOT analysis have only focused on solving these shortcomings separately, this study offers an approach to diminish both s...

Analysis of Traffic Crashes Involving Pedestrians Using Big Data: Investigation of Contributing Factors and Identification of Hotspots.

Science.gov (United States)

Xie, Kun; Ozbay, Kaan; Kurkcu, Abdullah; Yang, Hong

2017-08-01

This study aims to explore the potential of using big data in advancing the pedestrian risk analysis including the investigation of contributing factors and the hotspot identification. Massive amounts of data of Manhattan from a variety of sources were collected, integrated, and processed, including taxi trips, subway turnstile counts, traffic volumes, road network, land use, sociodemographic, and social media data. The whole study area was uniformly split into grid cells as the basic geographical units of analysis. The cell-structured framework makes it easy to incorporate rich and diversified data into risk analysis. The cost of each crash, weighted by injury severity, was assigned to the cells based on the relative distance to the crash site using a kernel density function. A tobit model was developed to relate grid-cell-specific contributing factors to crash costs that are left-censored at zero. The potential for safety improvement (PSI) that could be obtained by using the actual crash cost minus the cost of "similar" sites estimated by the tobit model was used as a measure to identify and rank pedestrian crash hotspots. The proposed hotspot identification method takes into account two important factors that are generally ignored, i.e., injury severity and effects of exposure indicators. Big data, on the one hand, enable more precise estimation of the effects of risk factors by providing richer data for modeling, and on the other hand, enable large-scale hotspot identification with higher resolution than conventional methods based on census tracts or traffic analysis zones. © 2017 Society for Risk Analysis.

Analysis of Pre-Analytic Factors Affecting the Success of Clinical Next-Generation Sequencing of Solid Organ Malignancies

International Nuclear Information System (INIS)

Chen, Hui; Luthra, Rajyalakshmi; Goswami, Rashmi S.; Singh, Rajesh R.; Roy-Chowdhuri, Sinchita

2015-01-01

Application of next-generation sequencing (NGS) technology to routine clinical practice has enabled characterization of personalized cancer genomes to identify patients likely to have a response to targeted therapy. The proper selection of tumor sample for downstream NGS based mutational analysis is critical to generate accurate results and to guide therapeutic intervention. However, multiple pre-analytic factors come into play in determining the success of NGS testing. In this review, we discuss pre-analytic requirements for AmpliSeq PCR-based sequencing using Ion Torrent Personal Genome Machine (PGM) (Life Technologies), a NGS sequencing platform that is often used by clinical laboratories for sequencing solid tumors because of its low input DNA requirement from formalin fixed and paraffin embedded tissue. The success of NGS mutational analysis is affected not only by the input DNA quantity but also by several other factors, including the specimen type, the DNA quality, and the tumor cellularity. Here, we review tissue requirements for solid tumor NGS based mutational analysis, including procedure types, tissue types, tumor volume and fraction, decalcification, and treatment effects

Analysis of Pre-Analytic Factors Affecting the Success of Clinical Next-Generation Sequencing of Solid Organ Malignancies

Energy Technology Data Exchange (ETDEWEB)

Chen, Hui [Department of Pathology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030 (United States); Luthra, Rajyalakshmi, E-mail: rluthra@mdanderson.org; Goswami, Rashmi S.; Singh, Rajesh R. [Department of Hematopathology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030 (United States); Roy-Chowdhuri, Sinchita [Department of Pathology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030 (United States)

2015-08-28

Application of next-generation sequencing (NGS) technology to routine clinical practice has enabled characterization of personalized cancer genomes to identify patients likely to have a response to targeted therapy. The proper selection of tumor sample for downstream NGS based mutational analysis is critical to generate accurate results and to guide therapeutic intervention. However, multiple pre-analytic factors come into play in determining the success of NGS testing. In this review, we discuss pre-analytic requirements for AmpliSeq PCR-based sequencing using Ion Torrent Personal Genome Machine (PGM) (Life Technologies), a NGS sequencing platform that is often used by clinical laboratories for sequencing solid tumors because of its low input DNA requirement from formalin fixed and paraffin embedded tissue. The success of NGS mutational analysis is affected not only by the input DNA quantity but also by several other factors, including the specimen type, the DNA quality, and the tumor cellularity. Here, we review tissue requirements for solid tumor NGS based mutational analysis, including procedure types, tissue types, tumor volume and fraction, decalcification, and treatment effects.

Analysis of Pre-Analytic Factors Affecting the Success of Clinical Next-Generation Sequencing of Solid Organ Malignancies

Directory of Open Access Journals (Sweden)

Hui Chen

2015-08-01

Full Text Available Application of next-generation sequencing (NGS technology to routine clinical practice has enabled characterization of personalized cancer genomes to identify patients likely to have a response to targeted therapy. The proper selection of tumor sample for downstream NGS based mutational analysis is critical to generate accurate results and to guide therapeutic intervention. However, multiple pre-analytic factors come into play in determining the success of NGS testing. In this review, we discuss pre-analytic requirements for AmpliSeq PCR-based sequencing using Ion Torrent Personal Genome Machine (PGM (Life Technologies, a NGS sequencing platform that is often used by clinical laboratories for sequencing solid tumors because of its low input DNA requirement from formalin fixed and paraffin embedded tissue. The success of NGS mutational analysis is affected not only by the input DNA quantity but also by several other factors, including the specimen type, the DNA quality, and the tumor cellularity. Here, we review tissue requirements for solid tumor NGS based mutational analysis, including procedure types, tissue types, tumor volume and fraction, decalcification, and treatment effects.

Factor analysis with a priori knowledge - application in dynamic cardiac SPECT

Energy Technology Data Exchange (ETDEWEB)

Sitek, A.; Di Bella, E.V.R.; Gullberg, G.T. [Medical Imaging Research Laboratory, Department of Radiology, University of Utah, CAMT, 729 Arapeen Drive, Salt Lake City, UT 84108-1218 (United States)

2000-09-01

Two factor analysis of dynamic structures (FADS) methods for the extraction of time-activity curves (TACs) from cardiac dynamic SPECT data sequences were investigated. One method was based on a least squares (LS) approach which was subject to positivity constraints. The other method was the well known apex-seeking (AS) method. A post-processing step utilizing a priori information was employed to correct for the non-uniqueness of the FADS solution. These methods were used to extract {sup 99m}Tc-teboroxime TACs from computer simulations and from experimental canine and patient studies. In computer simulations, the LS and AS methods, which are completely different algorithms, yielded very similar and accurate results after application of the correction for non-uniqueness. FADS-obtained blood curves correlated well with curves derived from region of interest (ROI) measurements in the experimental studies. The results indicate that the factor analysis techniques can be used for semi-automatic estimation of activity curves derived from cardiac dynamic SPECT images, and that they can be used for separation of physiologically different regions in dynamic cardiac SPECT studies. (author)

Analysis of major risk factors affecting those working in the agrarian sector (based on a sociological survey).

Science.gov (United States)

Krekoten, Olena M; Dereziuk, Anatolii V; Ihnaschuk, Olena V; Holovchanska, Svitlana E

Issues related to labour potential, its state and problems have consistently been a focus of attention for the International Labour Organisation (ILO). Its respective analysis shows that labour potential problems remain unresolved in many countries of the world. According to the World Health Organisation (WHO), adverse working conditions are among major factors of occupational disease development in Europe and the reason for disabilities of economically active population during 2.5% of their lifetime. The aim of the present study is to identify and analyse major risk factors, which have a bearing on people working in agriculture in the course of exercising their occupation, with account of forms of ownership of agricultural enterprises. Carried out was a cross-sectional study involving a sociological survey of 412 respondents - those working in agriculture - who made up the primary group and the control group. The study revealed 21 risk factors, 9 of which were work-related. A modified elementary cybernetic model of studying impact efficiency was developed with the view of carrying out a structural analysis of the sample group and choosing relevant methodological approaches. It has been established that harmful factors related to working environment and one's lifestyle are decisive in the agrarian sector, particularly for workers of privately owned businesses. For one out of three respondents harmful working conditions manifested themselves as industrial noise (31.7±3.4), vibration (29.0±2.1) trunk bending and constrained working posture (36.6±3.4). The vast majority of agricultural workers (91.6±2.5) admitted they could not afford proper rest during their annual leave; male respondents abused alcohol (70.6±3.0) and smoking (41.4±2.0 per 100 workers). The research established the structure of risk factors, which is sequentially represented by the following groups: behavioral (smoking, drinking of alcohol, rest during annual leave, physical culture), working

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

Science.gov (United States)

Sediyama, Cristina Y. N.; Moura, Ricardo; Garcia, Marina S.; da Silva, Antonio G.; Soraggi, Carolina; Neves, Fernando S.; Albuquerque, Maicon R.; Whiteside, Setephen P.; Malloy-Diniz, Leandro F.

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS. PMID:28484414

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

Directory of Open Access Journals (Sweden)

Leandro F. Malloy-Diniz

2017-04-01

Full Text Available Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale.Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a urgency, (b lack of premeditation; (c lack of perseverance; (d sensation seeking. In the present study 384 participants (278 women and 106 men, who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis.Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory.Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale.

Science.gov (United States)

Sediyama, Cristina Y N; Moura, Ricardo; Garcia, Marina S; da Silva, Antonio G; Soraggi, Carolina; Neves, Fernando S; Albuquerque, Maicon R; Whiteside, Setephen P; Malloy-Diniz, Leandro F

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach's alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

Factors affecting the HIV/AIDS epidemic: An ecological analysis of ...

African Journals Online (AJOL)

Factors affecting the HIV/AIDS epidemic: An ecological analysis of global data. ... Backward multiple linear regression analysis identified the proportion of Muslims, physicians density, and adolescent fertility rate are as the three most prominent factors linked with the national HIV epidemic. Conclusions: The findings support ...

Analysis of Economic Factors Affecting Stock Market

OpenAIRE

Xie, Linyin

2010-01-01

This dissertation concentrates on analysis of economic factors affecting Chinese stock market through examining relationship between stock market index and economic factors. Six economic variables are examined: industrial production, money supply 1, money supply 2, exchange rate, long-term government bond yield and real estate total value. Stock market comprises fixed interest stocks and equities shares. In this dissertation, stock market is restricted to equity market. The stock price in thi...

Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

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Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.

Deterministic factor analysis: methods of integro-differentiation of non-integral order

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Valentina V. Tarasova

2016-12-01

Full Text Available Objective to summarize the methods of deterministic factor economic analysis namely the differential calculus and the integral method. nbsp Methods mathematical methods for integrodifferentiation of nonintegral order the theory of derivatives and integrals of fractional nonintegral order. Results the basic concepts are formulated and the new methods are developed that take into account the memory and nonlocality effects in the quantitative description of the influence of individual factors on the change in the effective economic indicator. Two methods are proposed for integrodifferentiation of nonintegral order for the deterministic factor analysis of economic processes with memory and nonlocality. It is shown that the method of integrodifferentiation of nonintegral order can give more accurate results compared with standard methods method of differentiation using the first order derivatives and the integral method using the integration of the first order for a wide class of functions describing effective economic indicators. Scientific novelty the new methods of deterministic factor analysis are proposed the method of differential calculus of nonintegral order and the integral method of nonintegral order. Practical significance the basic concepts and formulas of the article can be used in scientific and analytical activity for factor analysis of economic processes. The proposed method for integrodifferentiation of nonintegral order extends the capabilities of the determined factorial economic analysis. The new quantitative method of deterministic factor analysis may become the beginning of quantitative studies of economic agents behavior with memory hereditarity and spatial nonlocality. The proposed methods of deterministic factor analysis can be used in the study of economic processes which follow the exponential law in which the indicators endogenous variables are power functions of the factors exogenous variables including the processes

A theory of planned behaviour-based analysis of TIMSS 2011 to determine factors influencing inquiry teaching practices in high-performing countries

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Pongsophon, Pongprapan; Herman, Benjamin C.

2017-07-01

Given the abundance of literature describing the strong relationship between inquiry-based teaching and student achievement, more should be known about the factors impacting science teachers' classroom inquiry implementation. This study utilises the theory of planned behaviour to propose and validate a causal model of inquiry-based teaching through analysing data relating to high-performing countries retrieved from the 2011 Trends in International Mathematics and Science Study assessments. Data analysis was completed through structural equation modelling using a polychoric correlation matrix for data input and diagonally weighted least squares estimation. Adequate fit of the full model to the empirical data was realised. The model demonstrates that the extent the teachers participated in academic collaborations was positively related to their occupational satisfaction, confidence in teaching inquiry, and classroom inquiry practices. Furthermore, the teachers' confidence with implementing inquiry was positively related to their classroom inquiry implementation and occupational satisfaction. However, perceived student-generated constraints demonstrated a negative relationship with the teachers' confidence with implementing inquiry and occupational satisfaction. Implications from this study include supporting teachers through promoting collaborative opportunities that facilitate inquiry-based practices and occupational satisfaction.

Modification and analysis of engineering hot spot factor of HFETR

International Nuclear Information System (INIS)

Hu Yuechun; Deng Caiyu; Li Haitao; Xu Taozhong; Mo Zhengyu

2014-01-01

This paper presents the modification and analysis of engineering hot spot factors of HFETR. The new factors are applied in the fuel temperature analysis and the estimated value of the safety allowable operating power of HFETR. The result shows the maximum cladding temperature of the fuel is lower when the new factor are in utilization, and the safety allowable operating power of HFETR if higher, thus providing the economical efficiency of HFETR. (authors)

Ranking insurance firms using AHP and Factor Analysis

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Mohammad Khodaei Valahzaghard

2013-03-01

Full Text Available Insurance industry includes a significant part of economy and it is important to learn more about the capabilities of different firms, which are active in this industry. In this paper, we present an empirical study to rank the insurance firms using analytical hierarchy process as well as factor analysis. The study considers four criteria including capital adequacy, quality of earning, quality of cash flow and quality of firms’ assets. The results of the implementation of factor analysis (FA have been verified using Kaiser-Meyer-Olkin (KMO=0.573 and Bartlett's Chi-Square (443.267 P-value=0.000 tests. According to the results FA, the first important factor, capital adequacy, represents 21.557% of total variance, the second factor, quality of income, represents 20.958% of total variance. In addition, the third factor, quality of cash flow, represents 19.417% of total variance and the last factor, quality of assets, represents 18.641% of total variance. The study has also used analytical hierarchy process (AHP to rank insurance firms. The results of our survey indicate that capital adequacy (0.559 is accounted as the most important factor followed by quality of income (0.235, quality of cash flow (0.144 and quality of assets (0.061. The results of AHP are consistent with the results of FA, which somewhat validates the overall study.

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

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Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

A study on critical success factors on building IT based flat organization: A case study of Mellat Bank

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Farajollah Rahnavard

2014-07-01

Full Text Available A flat organization is a firm that has an organizational structure with few or no levels of middle management between employee and executives. The idea is to take advantage of well-trained workers when they are more directly involved in the decision making process, rather than closely supervised by various layers of management. This paper presents an empirical investigation to determine critical success factors on building information technology (IT based flat organization in a case study of banking industry. Using principal component analysis, the study applies factor analysis for two internal and external factors. In terms of internal factors, there are three factors including Processes and the electronic decision making, Teaching and Electronic Learning and Work in IT. In addition, the study has detected four factors including Electronic Supply, IT structure, Appropriate IT usage and Electronic Communication.

Prognostic Factors in Amyotrophic Lateral Sclerosis: A Population-Based Study.

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Moura, Mirian Conceicao; Novaes, Maria Rita Carvalho Garbi; Eduardo, Emanoel Junio; Zago, Yuri S S P; Freitas, Ricardo Del Negro Barroso; Casulari, Luiz Augusto

2015-01-01

To determine the prognostic factors associated with survival in amyotrophic lateral sclerosis at diagnosis. This retrospective population-based study evaluated 218 patients treated with riluzole between 2005 and 2014 and described their clinical and demographic profiles after the analysis of clinical data and records from the mortality information system in the Federal District, Brazil. Cox multivariate regression analysis was conducted for the parameters found. The study sample consisted of 132 men and 86 women with a mean age at disease onset of 57.2±12.3 years; 77.6% of them were Caucasian. The mean periods between disease onset and diagnosis were 22.7 months among men and 23.5 months among women, and the mean survival periods were 45.7±47.0 months among men and 39.3±29.8 months among women. In addition, 80.3% patients presented non-bulbar-onset amyotrophic lateral sclerosis, and 19.7% presented bulbar-onset. Cox regression analysis indicated worse prognosis for body mass index (BMI) 75 years (RR: 12.47, 95% CI: 3.51-44.26), and bulbar-onset (RR: 4.56, 95% CI: 2.06-10.12). Electromyography did not confirm the diagnosis in 55.6% of the suspected cases and in 27.9% of the bulbar-onset cases. The factors associated with lower survival in amyotrophic lateral sclerosis were age >75 years, BMI <25 kg/m2, and bulbar-onset.

The Oswestry Disability Index, confirmatory factor analysis in a sample of 35,263 verifies a one-factor structure but practicality issues remain.

Science.gov (United States)

Gabel, Charles Philip; Cuesta-Vargas, Antonio; Qian, Meihua; Vengust, Rok; Berlemann, Ulrich; Aghayev, Emin; Melloh, Markus

2017-08-01

To analyze the factor structure of the Oswestry Disability Index (ODI) in a large symptomatic low back pain (LBP) population using exploratory (EFA) and confirmatory factor analysis (CFA). Analysis of pooled baseline ODI LBP patient data from the international Spine Tango registry of EUROSPINE, the Spine Society of Europe. The sample, with n = 35,263 (55.2% female; age 15-99, median 59 years), included 76.1% of patients with a degenerative disease, and 23.9% of the patients with various other spinal conditions. The initial EFA provided a hypothetical construct for consideration. Subsequent CFA was considered in three scenarios: the full sample and separate genders. Models were compared empirically for best fit. The EFA indicated a one-factor solution accounting for 54% of the total variance. The CFA analysis based on the full sample confirmed this one-factor structure. Sub-group analyses by gender achieved good model fit for configural and partial metric invariance, but not scalar invariance. A possible two-construct model solution as outlined by previous researchers: dynamic-activities (personal care, lifting, walking, sex and social) and static-activities (pain, sleep, standing, travelling and sitting) was not preferred. The ODI demonstrated a one-factor structure in a large LBP sample. A potential two-factor model was considered, but not found appropriate for constructs of dynamic and static activity. The use of the single summary score for the ODI is psychometrically supported. However, practicality limitations were reported for use in the clinical and research settings. Researchers are encouraged to consider a shift towards newer, more sensitive and robustly developed instruments.

Spousal Violence in 5 Transitional Countries: A Population-Based Multilevel Analysis of Individual and Contextual Factors.

Science.gov (United States)

Ismayilova, Leyla

2015-11-01

I examined the individual- and community-level factors associated with spousal violence in post-Soviet countries. I used population-based data from the Demographic and Health Survey conducted between 2005 and 2012. My sample included currently married women of reproductive age (n = 3932 in Azerbaijan, n = 4053 in Moldova, n = 1932 in Ukraine, n = 4361 in Kyrgyzstan, and n = 4093 in Tajikistan). I selected respondents using stratified multistage cluster sampling. Because of the nested structure of the data, multilevel logistic regressions for survey data were fitted to examine factors associated with spousal violence in the last 12 months. Partner's problem drinking was the strongest risk factor associated with spousal violence in all 5 countries. In Moldova, Ukraine, and Kyrgyzstan, women with greater financial power than their spouses were more likely to experience violence. Effects of community economic deprivation and of empowerment status of women in the community on spousal violence differed across countries. Women living in communities with a high tolerance of violence faced a higher risk of spousal violence in Moldova and Ukraine. In more traditional countries (Azerbaijan, Kyrgyzstan, and Tajikistan), spousal violence was lower in conservative communities with patriarchal gender beliefs or higher financial dependency on husbands. My findings underscore the importance of examining individual risk factors in the context of community-level factors and developing individual- and community-level interventions.

Analysis Of Factors Causing Delays On Harun Nafsi - Hm Rifadin Street In Samarinda East Kalimantan Maintenance Project

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Fadli

2017-12-01

Full Text Available This study aims to identify analyze and describe the factors that affect the project maintenance delay on Harun Nafsi - HM. Rifadin Street in Samarinda East Kalimantan. This research uses qualitative research method by utilizing questionnaires. The 30 participating respondents consist of 14 project implementers and 16 field implementers. The data are analyzed by descriptive statistical technique factor analysis and linear regression analysis. The results show that the factors influencing the delay of maintenance project of Harun Nafis - HM Rifadin Street include 1 time factor and workmanship factor 2 human resources and natural factors 3 geographical conditions late approval plans change and labor strikes and 4 non-optimal working levels and changes in the scope of the project during the work are still ongoing. Based on multiple linear regression analysis coefficient of determination value of 0.824 is obtained. It means that the four factors studied affect 82.4 of project delays and the rest of 27.6 is influenced by other variables out of this study. The results of this study also indicate that the dominant factor for road maintenance project delays is the fourth factor of the factors mentioned. The effort that the contractor needs to undertake is not to expand the employment contract if the project is underway or the contractor does not have the capability to complete another project.

ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

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Carmen BOGHEAN

2013-12-01

Full Text Available Productivity in agriculture most relevantly and concisely expresses the economic efficiency of using the factors of production. Labour productivity is affected by a considerable number of variables (including the relationship system and interdependence between factors, which differ in each economic sector and influence it, giving rise to a series of technical, economic and organizational idiosyncrasies. The purpose of this paper is to analyse the underlying factors of the average work productivity in agriculture, forestry and fishing. The analysis will take into account the data concerning the economically active population and the gross added value in agriculture, forestry and fishing in Romania during 2008-2011. The distribution of the average work productivity per factors affecting it is conducted by means of the u-substitution method.

Item-level factor analysis of the Self-Efficacy Scale.

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Bunketorp Käll, Lina

2014-03-01

This study explores the internal structure of the Self-Efficacy Scale (SES) using item response analysis. The SES was previously translated into Swedish and modified to encompass all types of pain, not exclusively back pain. Data on perceived self-efficacy in 47 patients with subacute whiplash-associated disorders were derived from a previously conducted randomized-controlled trial. The item-level factor analysis was carried out using a six-step procedure. To further study the item inter-relationships and to determine the underlying structure empirically, the 20 items of the SES were also subjected to principal component analysis with varimax rotation. The analyses showed two underlying factors, named 'social activities' and 'physical activities', with seven items loading on each factor. The remaining six items of the SES appeared to measure somewhat different constructs and need to be analysed further.

Analysis of influence mechanism of energy-related carbon emissions in Guangdong: evidence from regional China based on the input-output and structural decomposition analysis.

Science.gov (United States)

Wang, Changjian; Wang, Fei; Zhang, Xinlin; Deng, Haijun

2017-11-01

It is important to analyze the influence mechanism of energy-related carbon emissions from a regional perspective to effectively achieve reductions in energy consumption and carbon emissions in China. Based on the "energy-economy-carbon emissions" hybrid input-output analysis framework, this study conducted structural decomposition analysis (SDA) on carbon emissions influencing factors in Guangdong Province. Systems-based examination of direct and indirect drivers for regional emission is presented. (1) Direct effects analysis of influencing factors indicated that the main driving factors of increasing carbon emissions were economic and population growth. Carbon emission intensity was the main contributing factor restraining carbon emissions growth. (2) Indirect effects analysis of influencing factors showed that international and interprovincial trades significantly affected the total carbon emissions. (3) Analysis of the effects of different final demands on the carbon emissions of industrial sector indicated that the increase in carbon emission arising from international and interprovincial trades is mainly concentrated in energy- and carbon-intensive industries. (4) Guangdong had to compromise a certain amount of carbon emissions during the development of its export-oriented economy because of industry transfer arising from the economic globalization, thereby pointing to the existence of the "carbon leakage" problem. At the same time, interprovincial export and import resulted in Guangdong transferring a part of its carbon emissions to other provinces, thereby leading to the occurrence of "carbon transfer."

Stress and psychological factors before a migraine attack: A time-based analysis

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Makino Mariko

2008-09-01

Full Text Available Abstract Background The objective of this study is to examine the stress and mood changes of Japanese subjects over the 1–3 days before a migraine headache. Methods The study participants were 16 patients with migraines who consented to participate in this study. Each subject kept a headache diary four times a day for two weeks. They evaluated the number of stressful events, daily hassles, domestic and non-domestic stress, anxiety, depressive tendency and irritability by visual analog scales. The days were classified into migraine days, pre-migraine days, buffer days and control days based on the intensity of the headaches and accompanying symptoms, and a comparative study was conducted for each factor on the migraine days, pre-migraine days and control days. Results The stressful event value of pre-migraine days showed no significant difference compared to other days. The daily hassle value of pre-migraine days was the highest and was significantly higher than that of buffer days. In non-domestic stress, values on migraine days were significantly higher than on other days, and there was no significant difference between pre-migraine days and buffer days or between pre-migraine days and control days. There was no significant difference in the values of domestic stress between the categories. In non-domestic stress, values on migraine days were significantly higher than other days, and there was no significant difference between pre-migraine days and buffer days or between pre-migraine days and control days. There was little difference in sleep quality on migraine and pre-migraine days, but other psychological factors were higher on migraine days than on pre-migraine days. Conclusion Psychosocial stress preceding the onset of migraines by several days was suggested to play an important role in the occurrence of migraines. However, stress 2–3 days before a migraine attack was not so high as it has been reported to be in the United States and

Profile and Risk Factor Analysis of Unintentional Injuries in Children.

Science.gov (United States)

Bhamkar, Rahul; Seth, Bageshree; Setia, Maninder Singh

2016-10-01

To study the profile and various risk factors associated with unintentional injuries in children. The study is a cross sectional analysis of data collected from 351 children presenting with unintentional injury to a tertiary care hospital in Navi Mumbai, India. Data were collected about variables based on Haddon Phase Factor Matrix - host, environment and agent factors. Proportions for categorical variables across various groups were compared using Chi square test or Fisher's exact test. Logistic regression model was used to evaluate the factors. Falls (36 %) were the most common injuries followed by bites (23 %). Majority of children were school going children (38 %) followed by preschool children (29 %). Forty-seven percent were from lower socioeconomic class. Commonest place of injury was home (48 %) and the commonest time was evening (49 %). Though there was male predominance in injuries, the difference across gender did not vary significantly (p = 0.15). Poisonings were significantly more common in infants and toddlers and in rural population (p risk of bites compared to urban (p Profile of injuries varies widely as per the variations in agent, host and environmental factors. Socio-environmental, economic conditions and infancy-toddler age groups are predisposing risk factors for bites and poisoning. Although rural areas and lower socioeconomic class population are more vulnerable to serious types of injuries, they still lack essential basic medical care.

Risk factors for new onset diabetes mellitus after liver transplantation: A meta-analysis.

Science.gov (United States)

Li, Da-Wei; Lu, Tian-Fei; Hua, Xiang-Wei; Dai, Hui-Juan; Cui, Xiao-Lan; Zhang, Jian-Jian; Xia, Qiang

2015-05-28

To determine the risk factors for new-onset diabetes mellitus (NODM) after liver transplantation by conducting a systematic review and meta-analysis. We electronically searched the databases of MEDLINE, EMBASE and the Cochrane Library from January 1980 to December 2013 to identify relevant studies reporting risk factors for NODM after liver transplantation. Two authors independently assessed the trials for inclusion and extracted the data. Discrepancies were resolved in consultation with a third reviewer. All statistical analyses were performed with the RevMan5.0 software (The Cochrane Collaboration, Oxford, United Kingdom). Pooled odds ratios (OR) or weighted mean differences (WMD) with 95% confidence intervals (CIs) were calculated using either a fixed effects or a random effects model, based on the presence (I (2) 50%) of significant heterogeneity. Twenty studies with 4580 patients were included in the meta-analysis, all of which were retrospective. The meta-analysis identified the following significant risk factors: hepatitis C virus (HCV) infection (OR = 2.68; 95%CI: 1.92-3.72); a family history of diabetes (OR = 1.69, 95%CI: 1.09-2.63, P diabetes (OR = 1.69; 95%CI: 1.09-2.63; P = 0.02); use of tacrolimus (OR = 1.34; 95%CI: 1.03-1.76; P = 0.03) and body mass index (BMI)(WMD = 1.19, 95%CI: 0.69-1.68, P diabetes, male gender, tacrolimus and BMI are risk factors for NODM after liver transplantation.

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

Science.gov (United States)

Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

Interaction between thermal/hydraulics, human factors and system analysis for assessing feed and bleed risk benefits

International Nuclear Information System (INIS)

Lanore, J.M.; Caron, J.L.

1987-11-01

For probabilistic analysis of accident sequences, thermal/hydraulics, human factors and systems operation problems are frequently closely interrelated. This presentation will discuss a typical example which illustrates this interrelation: total loss of feedwater flow. It will present thermal/hydraulic analysises performed, how the T/H analysises are related to human factors and systems operation, and how, based on this, the failure probability of the feed and bleed cooling mode was evaluated

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this analysis was to develop the BDCFs for the volcanic ash

Cross-Cultural Validation of the Modified Practice Attitudes Scale: Initial Factor Analysis and a New Factor Model.

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Park, Heehoon; Ebesutani, Chad K; Chung, Kyong-Mee; Stanick, Cameo

2018-01-01

The objective of this study was to create the Korean version of the Modified Practice Attitudes Scale (K-MPAS) to measure clinicians' attitudes toward evidence-based treatments (EBTs) in the Korean mental health system. Using 189 U.S. therapists and 283 members from the Korean mental health system, we examined the reliability and validity of the MPAS scores. We also conducted the first exploratory and confirmatory factor analysis on the MPAS and compared EBT attitudes across U.S. and Korean therapists. Results revealed that the inclusion of both "reversed-worded" and "non-reversed-worded" items introduced significant method effects that compromised the integrity of the one-factor MPAS model. Problems with the one-factor structure were resolved by eliminating the "non-reversed-worded" items. Reliability and validity were adequate among both Korean and U.S. therapists. Korean therapists also reported significantly more negative attitudes toward EBTs on the MPAS than U.S. therapists. The K-MPAS is the first questionnaire designed to measure Korean service providers' attitudes toward EBTs to help advance the dissemination of EBTs in Korea. The current study also demonstrated the negative impacts that can be introduced by incorporating oppositely worded items into a scale, particularly with respect to factor structure and detecting significant group differences.

An inter-battery factor analysis of the comrey personality scales and the 16 personality factor questionnaire

OpenAIRE

Gideon P. de Bruin

2000-01-01

The scores of 700 Afrikaans-speaking university students on the Comrey Personality Scales and the 16 Personality Factor Questionnaire were subjected to an inter-battery factor analysis. This technique uses only the correlations between two sets of variables and reveals only the factors that they have in common. Three of the Big Five personality factors were revealed, namely Extroversion, Neuroticism and Conscientiousness. However, the Conscientiousness factor contained a relatively strong uns...

Nonparametric factor analysis of time series

OpenAIRE

Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

1998-01-01

We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

Quantitative EDXS analysis of organic materials using the ζ-factor method

International Nuclear Information System (INIS)

Fladischer, Stefanie; Grogger, Werner

2014-01-01

In this study we successfully applied the ζ-factor method to perform quantitative X-ray analysis of organic thin films consisting of light elements. With its ability to intrinsically correct for X-ray absorption, this method significantly improved the quality of the quantification as well as the accuracy of the results compared to conventional techniques in particular regarding the quantification of light elements. We describe in detail the process of determining sensitivity factors (ζ-factors) using a single standard specimen and the involved parameter optimization for the estimation of ζ-factors for elements not contained in the standard. The ζ-factor method was then applied to perform quantitative analysis of organic semiconducting materials frequently used in organic electronics. Finally, the results were verified and discussed concerning validity and accuracy. - Highlights: • The ζ-factor method is used for quantitative EDXS analysis of light elements. • We describe the process of determining ζ-factors from a single standard in detail. • Organic semiconducting materials are successfully quantified

Effective Factors in Job Motivation of Faculty Members of Shaheed Beheshti University of Medical Sciences Based on Herzberg's Two-Factor Theory of Motivation in 1394

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Somaie Ziar

2017-06-01

Full Text Available Background and objective: The most important factor for success in every organization, s its human resources. Human resources with the power of creativity, imagination, faith and commitment, have a great impact on the performance of the organization. University faculty members are the main pillars of human resources and affect the development of universities to promote academic standing in their communities. In this regard, the role of job motivation of faculty members to further efficiency helps universities. Materials and Methods: To determine the effective factors in job motivation of Shaheed Beheshti University of Medical Sciences’ faculty members, we conducted the study based on Herzberg's two factor motivation theory. In this across-sectional study, a sample of 137, (10% of the population in 12 faculties were selected by random and proportional sampling based on size and gender of faculty members. The instrument used was a questionnaire containing 40 of the 11 areas of external factors and an effective two-factor theory of Herzberg's motivation-based job. The reliability of the questionnaire was calculated using Cronbach's alpha (%86. After collecting data gamma and correlation multipliers Ki-test and logistic regression analysis was carried was with software SPSS16. Results: The internal factors were more important than external factors. Internal factors were more important in younger people. External factors, however, were more important in older people. Three areas, nature of work, professional development and career is also the most importance among the areas of internal factors, respectively. Two areas of occupational safety and connection are the most importance among the external factors. Conclusion: Providing the perfect environment, according to members of academic faculty, job security, moral values, decreasing problems of employment due to age and work experience, training individuals and providing a salary based on ability

Radiotherapy for carcinoma of the vagina. Immunocytochemical and cytofluorometric analysis of prognostic factors

Energy Technology Data Exchange (ETDEWEB)

Blecharz, P. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Gynecological Oncology; Reinfuss, M.; Jakubowicz, J. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Radiation Oncology; Rys, J. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Tumor Pathology Oncology; Skotnicki, P.; Wysocki, W. [Maria Sklodowska-Curie Memorial Institute, Krakow (Poland). Dept. of Oncological Surgery

2013-05-15

Background and purpose: The aim of this study was to assess the potential prognostic factors in patients with primary invasive vaginal carcinoma (PIVC) treated with radical irradiation. Patients and methods: The analysis was performed on 77 patients with PIVC treated between 1985 and 2005 in the Maria Sklodowska-Curie Memorial Institute of Oncology, Cancer Center in Krakow. A total of 36 patients (46.8 %) survived 5 years with no evidence of disease (NED). The following groups of factors were assessed for potential prognostic value: population-based (age), clinical (Karnofsky Performance Score [KPS], hemoglobin level, primary location of the vaginal lesion, macroscopic type, length of the involved vaginal wall, FIGO stage), microscopic (microscopic type, grade, mitotic index, presence of atypical mitoses, lymphatic vessels invasion, lymphocytes/plasmocytes infiltration, focal necrosis, VAIN-3), immunohistochemical (protein p53 expression, MIB-1 index), cytofluorometric (ploidity, index DI, S-phase fraction, proliferation index SG2M) factors. Results: Significantly better 5-year NED was observed in patients: < 60 years, KPS {<=} 80, FIGO stage I and II, grade G1-2, MIB-1 index < 70, S-phase fraction < 10, and proliferation index < 25. Independent factors for better prognosis in the multivariate Cox analysis were age < 60 years, FIGO stage I or II, and MIB-1 index < 70. Conclusion: Independent prognostic factors in the radically irradiated PIVC patients were as follows: age, FIGO stage, MIB-1 index. (orig.)

Human factors evaluation of remote afterloading brachytherapy. Volume 2, Function and task analysis

Energy Technology Data Exchange (ETDEWEB)

Callan, J.R.; Gwynne, J.W. III; Kelly, T.T.; Muckler, F.A. [Pacific Science and Engineering Group, San Diego, CA (United States); Saunders, W.M.; Lepage, R.P.; Chin, E. [University of California San Diego Medical Center, CA (United States). Div. of Radiation Oncology; Schoenfeld, I.; Serig, D.I. [Nuclear Regulatory Commission, Washington, DC (United States). Div. of Systems Technology

1995-05-01

A human factors project on the use of nuclear by-product material to treat cancer using remotely operated afterloaders was undertaken by the Nuclear Regulatory Commission. The purpose of the project was to identify factors that contribute to human error in the system for remote afterloading brachytherapy (RAB). This report documents the findings from the first phase of the project, which involved an extensive function and task analysis of RAB. This analysis identified the functions and tasks in RAB, made preliminary estimates of the likelihood of human error in each task, and determined the skills needed to perform each RAB task. The findings of the function and task analysis served as the foundation for the remainder of the project, which evaluated four major aspects of the RAB system linked to human error: human-system interfaces; procedures and practices; training and qualifications of RAB staff; and organizational practices and policies. At its completion, the project identified and prioritized areas for recommended NRC and industry attention based on all of the evaluations and analyses.

Human factors evaluation of remote afterloading brachytherapy. Volume 2, Function and task analysis

International Nuclear Information System (INIS)

Callan, J.R.; Gwynne, J.W. III; Kelly, T.T.; Muckler, F.A.; Saunders, W.M.; Lepage, R.P.; Chin, E.; Schoenfeld, I.; Serig, D.I.

1995-05-01

A human factors project on the use of nuclear by-product material to treat cancer using remotely operated afterloaders was undertaken by the Nuclear Regulatory Commission. The purpose of the project was to identify factors that contribute to human error in the system for remote afterloading brachytherapy (RAB). This report documents the findings from the first phase of the project, which involved an extensive function and task analysis of RAB. This analysis identified the functions and tasks in RAB, made preliminary estimates of the likelihood of human error in each task, and determined the skills needed to perform each RAB task. The findings of the function and task analysis served as the foundation for the remainder of the project, which evaluated four major aspects of the RAB system linked to human error: human-system interfaces; procedures and practices; training and qualifications of RAB staff; and organizational practices and policies. At its completion, the project identified and prioritized areas for recommended NRC and industry attention based on all of the evaluations and analyses

Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

Science.gov (United States)

Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

2017-12-01

Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

Factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus: decision-curve analysis.

Science.gov (United States)

Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, Tsuyoshi; Tanizawa, Y

2018-04-29

To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Radar-Based Depth Area Reduction Factors for Colorado

Science.gov (United States)

Curtis, D. C.; Humphrey, J. H.; Bare, D.

2011-12-01

More than 340,000 fifteen-minute storm cells, nearly 45,000 one-hour cells, and over 20,000 three-hour cells found in 21 months of gage adjusted radar-rainfall estimates (GARR) over El Paso County, CO, were identified and evaluated using TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting) software. TITAN's storm cell identification capability enabled the analysis of the geometric properties of storms, time step by time step. The gage-adjusted radar-rainfall data set was derived for months containing runoff producing events observed in the Fountain Creek Watershed within El Paso County from 1994-2008. Storm centered Depth Area Reduction Factors (DARFs) were computed and compared to DARFs published by the U.S. National Weather Service (NWS) in Technical Paper 29, which are widely used in stormwater infrastructure design. Radar-based storm centered DARFs decay much more sharply than the NWS standard curves. The results suggest lower watershed average rainfall inputs from radar-based storm centered DARFs than from standard NWS DARFs for a given watershed area. The results also suggest that DARFs are variable by return period and, perhaps, by location. Both findings could have significant impacts on design storm standards. Lower design volumes for a given return period translate to lower capacity requirements and lower cost infrastructure. Conversely, the higher volume requirements implied for the NWS DARFs translate to higher capacity requirements, higher costs, but lower risk of failure. Ultimately, a decision about which approach is to use depends on the risk tolerance of the decision maker. However, the growing volume of historical radar rainfall estimates coupled with the type of analysis described herein, supports a better understanding of risk and more informed decision-making by local officials.

Analysis of related risk factors for pancreatic fistula after pancreaticoduodenectomy

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Qi-Song Yu

2016-08-01

Full Text Available Objective: To explore the related risk factors for pancreatic fistula after pancreaticoduodenectomy to provide a theoretical evidence for effectively preventing the occurrence of pancreatic fistula. Methods: A total of 100 patients who were admitted in our hospital from January, 2012 to January, 2015 and had performed pancreaticoduodenectomy were included in the study. The related risk factors for developing pancreatic fistula were collected for single factor and Logistic multi-factor analysis. Results: Among the included patients, 16 had pancreatic fistula, and the total occurrence rate was 16% (16/100. The single-factor analysis showed that the upper abdominal operation history, preoperative bilirubin, pancreatic texture, pancreatic duct diameter, intraoperative amount of bleeding, postoperative hemoglobin, and application of somatostatin after operation were the risk factors for developing pancreatic fistula (P<0.05. The multi-factor analysis showed that the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin were the dependent risk factors for developing pancreatic fistula (OR=4.162, 6.104, 5.613, 4.034, P<0.05. Conclusions: The occurrence of pancreatic fistula after pancreaticoduodenectomy is closely associated with the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin; therefore, effective measures should be taken to reduce the occurrence of pancreatic fistula according to the patients’ own conditions.

A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites

Directory of Open Access Journals (Sweden)

Yunfeng Dong

2017-01-01

Full Text Available The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM, which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. To address these two problems, a cluster and principal component analysis-based optimization method (CPC-based OM is proposed, in which many candidate orbits are gradually randomly generated until the optimal orbit is obtained using a data mining method, that is, cluster analysis based on principal components. Then, the second cluster analysis of the orbital elements is introduced into CPC-based OM to improve the convergence, developing a novel double cluster and principal component analysis-based optimization method (DCPC-based OM. In DCPC-based OM, the cluster analysis based on principal components has the advantage of reducing the human influences, and the cluster analysis based on six orbital elements can reduce the search space to effectively accelerate convergence. The test results from a multiobjective numerical benchmark function and the orbit design results of an Earth observation satellite show that DCPC-based OM converges more efficiently than WSGA-based HM. And DCPC-based OM, to some degree, reduces the influence of human factors presented in WSGA-based HM.

Prognostic factors in pediatric pulmonary arterial hypertension: A systematic review and meta-analysis.

Science.gov (United States)

Ploegstra, Mark-Jan; Zijlstra, Willemijn M H; Douwes, Johannes M; Hillege, Hans L; Berger, Rolf M F

2015-04-01

Despite the introduction of targeted therapies in pediatric pulmonary arterial hypertension (PAH), prognosis remains poor. For the definition of treatment strategies and guidelines, there is a high need for an evidence-based recapitulation of prognostic factors. The aim of this study was to identify and evaluate prognostic factors in pediatric PAH by a systematic review of the literature and to summarize the prognostic value of currently reported prognostic factors using meta-analysis. Medline, EMBASE and Cochrane Library were searched on April 1st 2014 to identify original studies that described predictors of mortality or lung-transplantation exclusively in children with PAH. 1053 citations were identified, of which 25 were included for further analysis. Hazard ratios (HR) and 95% confidence intervals were extracted from the papers. For variables studied in at least three non-overlapping cohorts, a combined HR was calculated using random-effects meta-analysis. WHO functional class (WHO-FC, HR 2.7), (N-terminal pro-) brain natriuretic peptide ([NT-pro]BNP, HR 3.2), mean right atrial pressure (mRAP, HR 1.1), cardiac index (HR 0.7), indexed pulmonary vascular resistance (PVRi, HR 1.3) and acute vasodilator response (HR 0.3) were identified as significant prognostic factors (p ≤ 0.001). This systematic review combined with separate meta-analyses shows that WHO-FC, (NT-pro)BNP, mRAP, PVRi, cardiac index and acute vasodilator response are consistently reported prognostic factors for outcome in pediatric PAH. These variables are useful clinical tools to assess prognosis and should be incorporated in treatment strategies and guidelines for children with PAH. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Factor analysis shows association between family activity environment and children's health behaviour.

Science.gov (United States)

Hendrie, Gilly A; Coveney, John; Cox, David N

2011-12-01

To characterise the family activity environment in a questionnaire format, assess the questionnaire's reliability and describe its predictive ability by examining the relationships between the family activity environment and children's health behaviours - physical activity, screen time and fruit and vegetable intake. This paper describes the creation of a tool, based on previously validated scales, adapted from the food domain. Data are from 106 children and their parents (Adelaide, South Australia). Factor analysis was used to characterise factors within the family activity environment. Pearson-Product Moment correlations between the family environment and child outcomes, controlling for demographic variation, were examined. Three factors described the family activity environment - parental activity involvement, opportunity for role modelling and parental support for physical activity - and explained 37.6% of the variance. Controlling for demographic factors, the scale was significantly correlated with children's health behaviour - physical activity (r=0.27), screen time (r=-0.24) and fruit and vegetable intake (r=0.34). The family activity environment questionnaire shows high internal consistency and moderate predictive ability. This study has built on previous research by taking a more comprehensive approach to measuring the family activity environment. This research suggests the family activity environment should be considered in family-based health promotion interventions. © 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.

Two Expectation-Maximization Algorithms for Boolean Factor Analysis

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.

2014-01-01

Roč. 130, 23 April (2014), s. 83-97 ISSN 0925-2312 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean Factor analysis * Binary Matrix factorization * Neural networks * Binary data model * Dimension reduction * Bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014

Factor analysis of symptom profile in early onset and late onset OCD.

Science.gov (United States)

Grover, Sandeep; Sarkar, Siddharth; Gupta, Gourav; Kate, Natasha; Ghosh, Abhishek; Chakrabarti, Subho; Avasthi, Ajit

2018-04-01

This study aimed to assess the factor structure of early and late onset OCD. Additionally, cluster analysis was conducted in the same sample to assess the applicability of the factors. 345 participants were assessed with Yale Brown Obsessive Compulsive Scale symptom checklist. Patients were classified as early onset (onset of symptoms at age ≤ 18 years) and late onset (onset at age > 18 years) OCD depending upon the age of onset of the symptoms. Factor analysis and cluster analysis of early-onset and late-onset OCD was conducted. The study sample comprised of 91 early onset and 245 late onset OCD subjects. Males were more common in the early onset group. Differences in the frequency of phenomenology related to contamination related, checking, repeating, counting and ordering/arranging compulsions were present across the early and late onset groups. Factor analysis of YBOCS revealed a 3 factor solution for both the groups, which largely concurred with each other. These factors were named as hoarding and symmetry (factor-1), contamination (factor-2) and aggressive, sexual and religious factor (factor-3). To conclude this study shows that factor structure of symptoms of OCD seems to be similar between early-onset and late-onset OCD. Copyright © 2017 Elsevier B.V. All rights reserved.

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan; Spell, Gregory; Carin, Lawrence

2017-04-20

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

Influence factors and corrections of low-energy γ-ray penetration in ash analysis

International Nuclear Information System (INIS)

Cheng Bo; Tuo Xianguo; Zhou Jianbin; Tong Yunfu

2002-01-01

The author introduces the system of the coal ash analyzer. This system is based on the low-energy γ-ray source 241 Am emitted two kinds of energy peaks 26.4 keV and 59.6 keV to analyze the ash in coal with the penetration way. The author also offers the factors to influence the accuracy of ash analysis, such as the size of coal, the environmental temperature, the important elements in coal, and water in coal too. At the same time, depending on the cause of the factors, it offer some methods of correction such as the way of the auto-hold energy peak, the way of the auto-compensation way, and so on. The author also mentions the other influence factors of the measurement accuracy to be noticed during the experiment. All these aim at clearing off the influence factors of measurement accuracy through the experiments

Crashworthiness uncertainty analysis of typical civil aircraft based on Box–Behnken method

OpenAIRE

Ren Yiru; Xiang Jinwu

2014-01-01

The crashworthiness is an important design factor of civil aircraft related with the safety of occupant during impact accident. It is a highly nonlinear transient dynamic problem and may be greatly influenced by the uncertainty factors. Crashworthiness uncertainty analysis is conducted to investigate the effects of initial conditions, structural dimensions and material properties. Simplified finite element model is built based on the geometrical model and basic physics phenomenon. Box–Behnken...

Multivariate factor analysis of Girgentana goat milk composition

Directory of Open Access Journals (Sweden)

Pietro Giaccone

2010-01-01

Full Text Available The interpretation of the several variables that contribute to defining milk quality is difficult due to the high degree of  correlation among them. In this case, one of the best methods of statistical processing is factor analysis, which belongs  to the multivariate groups; for our study this particular statistical approach was employed.  A total of 1485 individual goat milk samples from 117 Girgentana goats, were collected fortnightly from January to July,  and analysed for physical and chemical composition, and clotting properties. Milk pH and tritable acidity were within the  normal range for fresh goat milk. Morning milk yield resulted 704 ± 323 g with 3.93 ± 1.23% and 3.48±0.38% for fat  and protein percentages, respectively. The milk urea content was 43.70 ± 8.28 mg/dl. The clotting ability of Girgentana  milk was quite good, with a renneting time equal to 16.96 ± 3.08 minutes, a rate of curd formation of 2.01 ± 1.63 min-  utes and a curd firmness of 25.08 ± 7.67 millimetres.  Factor analysis was performed by applying axis orthogonal rotation (rotation type VARIMAX; the analysis grouped the  milk components into three latent or common factors. The first, which explained 51.2% of the total covariance, was  defined as “slow milks”, because it was linked to r and pH. The second latent factor, which explained 36.2% of the total  covariance, was defined as “milk yield”, because it is positively correlated to the morning milk yield and to the urea con-  tent, whilst negatively correlated to the fat percentage. The third latent factor, which explained 12.6% of the total covari-  ance, was defined as “curd firmness,” because it is linked to protein percentage, a30 and titatrable acidity. With the aim  of evaluating the influence of environmental effects (stage of kidding, parity and type of kidding, factor scores were anal-  ysed with the mixed linear model. Results showed significant effects of the season of

Implementation and Optimization of GPU-Based Static State Security Analysis in Power Systems

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Yong Chen

2017-01-01

Full Text Available Static state security analysis (SSSA is one of the most important computations to check whether a power system is in normal and secure operating state. It is a challenge to satisfy real-time requirements with CPU-based concurrent methods due to the intensive computations. A sensitivity analysis-based method with Graphics processing unit (GPU is proposed for power systems, which can reduce calculation time by 40% compared to the execution on a 4-core CPU. The proposed method involves load flow analysis and sensitivity analysis. In load flow analysis, a multifrontal method for sparse LU factorization is explored on GPU through dynamic frontal task scheduling between CPU and GPU. The varying matrix operations during sensitivity analysis on GPU are highly optimized in this study. The results of performance evaluations show that the proposed GPU-based SSSA with optimized matrix operations can achieve a significant reduction in computation time.

Confirmatory factor analysis using Microsoft Excel.

Science.gov (United States)

Miles, Jeremy N V

2005-11-01

This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

Boolean Factor Analysis by Attractor Neural Network

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

2007-01-01

Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

Factors affecting public prejudice and social distance on mental illness: analysis of contextual effect by multi-level analysis.

Science.gov (United States)

Jang, Hyeongap; Lim, Jun-Tae; Oh, Juhwan; Lee, Seon-Young; Kim, Yong-Ik; Lee, Jin-Seok

2012-03-01

While there have been many quantitative studies on the public's attitude towards mental illnesses, it is hard to find quantitative study which focused on the contextual effect on the public's attitude. The purpose of this study was to identify factors that affect the public's beliefs and attitudes including contextual effects. We analyzed survey on the public's beliefs and attitudes towards mental illness in Korea with multi-level analysis. We analyzed the public's beliefs and attitudes in terms of prejudice as an intermediate outcome and social distance as a final outcome. Then, we focused on the associations of factors, which were individual and regional socio-economic factors, familiarity, and knowledge based on the comparison of the intermediate and final outcomes. Prejudice was not explained by regional variables but was only correlated with individual factors. Prejudice increased with age and decreased by high education level. However, social distance controlling for prejudice increased in females, in people with a high education level, and in regions with a high education level and a high proportion of the old. Therefore, social distance without controlling for prejudice increased in females, in the elderly, in highly educated people, and in regions with a high education and aged community. The result of the multi-level analysis for the regional variables suggests that social distance for mental illness are not only determined by individual factors but also influenced by the surroundings so that it could be tackled sufficiently with appropriate considering of the relevant regional context with individual characteristics.

Assessment of children with suspected auditory processing disorder: a factor analysis study.

Science.gov (United States)

Ahmmed, Ansar U; Ahmmed, Afsara A; Bath, Julie R; Ferguson, Melanie A; Plack, Christopher J; Moore, David R

2014-01-01

To identify the factors that may underlie the deficits in children with listening difficulties, despite normal pure-tone audiograms. These children may have auditory processing disorder (APD), but there is no universally agreed consensus as to what constitutes APD. The authors therefore refer to these children as children with suspected APD (susAPD) and aim to clarify the role of attention, cognition, memory, sensorimotor processing speed, speech, and nonspeech auditory processing in susAPD. It was expected that a factor analysis would show how nonauditory and supramodal factors relate to auditory behavioral measures in such children with susAPD. This would facilitate greater understanding of the nature of listening difficulties, thus further helping with characterizing APD and designing multimodal test batteries to diagnose APD. Factor analysis of outcomes from 110 children (68 male, 42 female; aged 6 to 11 years) with susAPD on a widely used clinical test battery (SCAN-C) and a research test battery (MRC Institute of Hearing Research Multi-center Auditory Processing "IMAP"), that have age-based normative data. The IMAP included backward masking, simultaneous masking, frequency discrimination, nonverbal intelligence, working memory, reading, alerting attention and motor reaction times to auditory and visual stimuli. SCAN-C included monaural low-redundancy speech (auditory closure and speech in noise) and dichotic listening tests (competing words and competing sentences) that assess divided auditory attention and hence executive attention. Three factors were extracted: "general auditory processing," "working memory and executive attention," and "processing speed and alerting attention." Frequency discrimination, backward masking, simultaneous masking, and monaural low-redundancy speech tests represented the "general auditory processing" factor. Dichotic listening and the IMAP cognitive tests (apart from nonverbal intelligence) were represented in the "working

Factors influencing the demand of the service of community based animal health care in Zimbabwe.

Science.gov (United States)

Mutambara, J; Dube, I; Matangi, E; Majeke, F

2013-11-01

This study was done to find out about animal health service providers and factors that determined demand for community based veterinary service delivery in smallholder sector of Zimbabwe. Focus group discussions and a questionnaire was used to collect data on veterinary services providers and socio-economic factors related to animal health from a sample (N=333) smallholder livestock farmers from Gutu district of Masvingo province in Zimbabwe. Analytical techniques used were descriptive statistics, K-mean cluster analysis and Tobit regression model. Results showed that the majority of farmers (45%) obtained services from both Community Based Animal Health Workers (CBAHWs) and Department of Veterinary Service (DVS), 25% DVS only, 20% used CBAHWs while 10% did not seek any services. Further analysis showed that distance to CBAHW, distance to AHMC and employment status were significantly related to demand for CBAHWs with coefficients of -1.5, 0.7 and -10.3, respectively. The study thus concluded that CBAHW is an alternative animal health service delivery approach already practiced in smallholder farming sectors of Zimbabwe. Socio-economic factors significantly influenced the demand for CBAHW services. Given limited resources by state sponsored veterinary services, it is recommended that the CBAHWs approach should be encouraged as supplementary service provider especially in areas further DVS. These community organizations can be empowered by the state to deliver more improved services based on hygiene and modern science at a relatively low cost to farmers. Copyright © 2013 Elsevier B.V. All rights reserved.

Animal and management factors influencing grower and finisher pig performance and efficiency in European systems: a meta-analysis.

Science.gov (United States)

Douglas, S L; Szyszka, O; Stoddart, K; Edwards, S A; Kyriazakis, I

2015-07-01

A meta-analysis on the effects of management and animal-based factors on the performance and feed efficiency of growing pigs can provide information on single factor and interaction effects absent in individual studies. This study analysed the effects of such factors on average daily gain (ADG), feed intake (FI) and feed conversion ratio (FCR) of grower and finisher pigs. The multivariate models identified significant effects of: (1) bedding (Panimals with the least amount of floor space having a higher FI when given a feed with a low metabolisable energy (ME) content, in contrast to all other pigs, which showed a higher FI with increased ME content. The meta-analysis confirmed the significant effect of several well-known factors on the performance and efficiency of grower and finisher pigs, the effects of some less established ones and, importantly, the interactions between such factors.

DISRUPTIVE EVENT BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objective of this analysis was to develop the BDCFs for the volcanic

Measuring coalition functioning: refining constructs through factor analysis.

Science.gov (United States)

Brown, Louis D; Feinberg, Mark E; Greenberg, Mark T

2012-08-01

Internal and external coalition functioning is an important predictor of coalition success that has been linked to perceived coalition effectiveness, coalition goal achievement, coalition ability to support evidence-based programs, and coalition sustainability. Understanding which aspects of coalition functioning best predict coalition success requires the development of valid measures of empirically unique coalition functioning constructs. The goal of the present study is to examine and refine the psychometric properties of coalition functioning constructs in the following six domains: leadership, interpersonal relationships, task focus, participation benefits/costs, sustainability planning, and community support. The authors used factor analysis to identify problematic items in our original measure and then piloted new items and scales to create a more robust, psychometrically sound, multidimensional measure of coalition functioning. Scales displayed good construct validity through correlations with other measures. Discussion considers the strengths and weaknesses of the refined instrument.

Eating Behaviour in the General Population: An Analysis of the Factor Structure of the German Version of the Three-Factor-Eating-Questionnaire (TFEQ and Its Association with the Body Mass Index.

Directory of Open Access Journals (Sweden)

Antje Löffler

Full Text Available The Three-Factor-Eating-Questionnaire (TFEQ is an established instrument to assess eating behaviour. Analysis of the TFEQ-factor structure was based on selected, convenient and clinical samples so far. Aims of this study were (I to analyse the factor structure of the German version of the TFEQ and (II--based on the refined factor structure--to examine the association between eating behaviour and the body mass index (BMI in a general population sample of 3,144 middle-aged and older participants (40-79 years of the ongoing population based cohort study of the Leipzig Research Center for Civilization Diseases (LIFE Health Study. The factor structure was examined in a split-half analysis with both explorative and confirmatory factor analysis. Associations between TFEQ-scores and BMI values were tested with multiple regression analyses controlled for age, gender, and education. We found a three factor solution for the TFEQ with an 'uncontrolled eating', a 'cognitive restraint' and an 'emotional eating' domain including 29 of the original 51 TFEQ-items. Scores of the 'uncontrolled eating domain' showed the strongest correlation with BMI values (partial r = 0.26. Subjects with scores above the median in both 'uncontrolled eating' and 'emotional eating' showed the highest BMI values (mean = 29.41 kg/m², subjects with scores below the median in all three domains showed the lowest BMI values (mean = 25.68 kg/m²; F = 72.074, p<0.001. Our findings suggest that the TFEQ is suitable to identify subjects with specific patterns of eating behaviour that are associated with higher BMI values. Such information may help health care professionals to develop and implement more tailored interventions for overweight and obese individuals.

Contextual risk factors for low birth weight: a multilevel analysis.

Directory of Open Access Journals (Sweden)

Gbenga A Kayode

Full Text Available Low birth weight (LBW remains to be a leading cause of neonatal death and a major contributor to infant and under-five mortality. Its prevalence has not declined in the last decade in sub-Saharan Africa (SSA and Asia. Some individual level factors have been identified as risk factors for LBW but knowledge is limited on contextual risk factors for LBW especially in SSA.Contextual risk factors for LBW in Ghana were identified by performing multivariable multilevel logistic regression analysis of 6,900 mothers dwelling in 412 communities that participated in the 2003 and 2008 Demographic and Health Surveys in Ghana.Contextual-level factors were significantly associated with LBW: Being a rural dweller increased the likelihood of having a LBW infant by 43% (OR 1.43; 95% CI 1.01-2.01; P-value <0.05 while living in poverty-concentrated communities increased the risk of having a LBW infant twofold (OR 2.16; 95% CI 1.29-3.61; P-value <0.01. In neighbourhoods with a high coverage of safe water supply the odds of having a LBW infant reduced by 28% (OR 0.74; 95% CI 0.57-0.96; P-value <0.05.This study showed contextual risk factors to have independent effects on the prevalence of LBW infants. Being a rural dweller, living in a community with a high concentration of poverty and a low coverage of safe water supply were found to increase the prevalence of LBW infants. Implementing appropriate community-based intervention programmes will likely reduce the occurrence of LBW infants.

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

Directory of Open Access Journals (Sweden)

Hong Xue

2018-01-01

Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

Testing all six person-oriented principles in dynamic factor analysis.

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Molenaar, Peter C M

2010-05-01

All six person-oriented principles identified by Sterba and Bauer's Keynote Article can be tested by means of dynamic factor analysis in its current form. In particular, it is shown how complex interactions and interindividual differences/intraindividual change can be tested in this way. In addition, the necessity to use single-subject methods in the analysis of developmental processes is emphasized, and attention is drawn to the possibility to optimally treat developmental psychopathology by means of new computational techniques that can be integrated with dynamic factor analysis.

[Analysis of virulence factors of Porphyromonas endodontalis based on comparative proteomics technique].

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Li, H; Ji, H; Wu, S S; Hou, B X

2016-12-09

Objective: To analyze the protein expression profile and the potential virulence factors of Porphyromonas endodontalis (Pe) via comparison with that of two strains of Porphyromonas gingivalis (Pg) with high and low virulences, respectively. Methods: Whole cell comparative proteomics of Pe ATCC35406 was examined and compared with that of high virulent strain Pg W83 andlow virulent strain Pg ATCC33277, respectively. Isobaric tags for relative and absolute quantitation (iTRAQ) combined with nano liquid chromatography-tandem mass spectrometry (Nano-LC-MS/MS) were adopted to identify and quantitate the proteins of Pe and two strains of Pg with various virulences by using the methods of isotopically labeled peptides, mass spectrometric detection and bioinformatics analysis. The biological functions of similar proteins expressed by Pe ATCC35406 and two strains of Pg were quantified and analyzed. Results: Totally 1 210 proteins were identified while Pe compared with Pg W83. There were 130 proteins (10.74% of the total proteins) expressed similarly, including 89 known functional proteins and 41 proteins of unknown functions. Totally 1 223 proteins were identified when Pe compared with Pg ATCC33277. There were 110 proteins (8.99% of the total proteins) expressed similarly, including 72 known functional proteins and 38 proteins of unknown functions. The similarly expressed proteins in Pe and Pg strains with various virulences mainly focused on catalytic activity and binding function, including recombination activation gene (RagA), lipoprotein, chaperonin Dnak, Clp family proteins (ClpC and ClpX) and various iron-binding proteins. They were involved in metabolism and cellular processes. In addition, the type and number of similar virulence proteins between Pe and high virulence Pg were higher than those between Pe and low virulence Pg. Conclusions: Lipoprotein, oxygen resistance protein, iron binding protein were probably the potential virulence factors of Pe ATCC35406. It was

Exploratory factor analysis and reliability analysis with missing data: A simple method for SPSS users

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Bruce Weaver

2014-09-01

Full Text Available Missing data is a frequent problem for researchers conducting exploratory factor analysis (EFA or reliability analysis. The SPSS FACTOR procedure allows users to select listwise deletion, pairwise deletion or mean substitution as a method for dealing with missing data. The shortcomings of these methods are well-known. Graham (2009 argues that a much better way to deal with missing data in this context is to use a matrix of expectation maximization (EM covariances(or correlations as input for the analysis. SPSS users who have the Missing Values Analysis add-on module can obtain vectors ofEM means and standard deviations plus EM correlation and covariance matrices via the MVA procedure. But unfortunately, MVA has no /MATRIX subcommand, and therefore cannot write the EM correlations directly to a matrix dataset of the type needed as input to the FACTOR and RELIABILITY procedures. We describe two macros that (in conjunction with an intervening MVA command carry out the data management steps needed to create two matrix datasets, one containing EM correlations and the other EM covariances. Either of those matrix datasets can then be used asinput to the FACTOR procedure, and the EM correlations can also be used as input to RELIABILITY. We provide an example that illustrates the use of the two macros to generate the matrix datasets and how to use those datasets as input to the FACTOR and RELIABILITY procedures. We hope that this simple method for handling missing data will prove useful to both students andresearchers who are conducting EFA or reliability analysis.

LU factorization for accelerator-based systems

KAUST Repository

Agullo, Emmanuel

2011-12-01

Multicore architectures enhanced with multiple GPUs are likely to become mainstream High Performance Computing (HPC) platforms in a near future. In this paper, we present the design and implementation of an LU factorization using tile algorithm that can fully exploit the potential of such platforms in spite of their complexity. We use a methodology derived from previous work on Cholesky and QR factorizations. Our contributions essentially consist of providing new CPU/GPU hybrid LU kernels, studying the impact on performance of the looking variants as well as the storage layout in presence of pivoting, tuning the kernels for two different machines composed of multiple recent NVIDIA Tesla S1070 (four GPUs total) and Fermi-based S2050 GPUs (three GPUs total), respectively. The hybrid tile LU asymptotically achieves 1 Tflop/s in single precision on both hardwares. The performance in double precision arithmetic reaches 500 Gflop/s on the Fermi-based system, twice faster than the old GPU generation of Tesla S1070. We also discuss the impact of the number of tiles on the numerical stability. We show that the numerical results of the tile LU factorization will be accurate enough for most applications as long as the computations are performed in double precision arithmetic. © 2011 IEEE.

Identification of dietary patterns using factor analysis in an epidemiological study in São Paulo

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Dirce Maria Lobo Marchioni

Full Text Available CONTEXT AND OBJECTIVE: Diet and nutrition are environmental factors in health/disease relationships. From the epidemiological viewpoint, diet represents a complex set of highly correlated exposures. Our objective was to identify patterns of food intake in a group of individuals living in São Paulo, and to develop objective dietary measurements for epidemiological purposes. DESIGN AND LOCAL: Exploratory factor analysis of data in a case-control study in seven teaching hospitals in São Paulo. METHODS: The participants were 517 patients (260 oral cancer cases and 257 controls admitted to the study hospitals between November 1998 and March 2001. The weekly intake frequencies for dairy products, cereals, meat, processed meat, vegetables, pulses, fruits and sweets were assessed by means of a semi-quantitative food frequency questionnaire. Dietary patterns were identified by factor analysis, based on the intake of the eight food groups, using principal component analysis as an extraction method followed by varimax rotation. RESULTS: Factor analysis identified three patterns that accounted for 55% of the total variability within the sample. The first pattern ("prudent" was characterized by vegetable, fruit and meat intake; the second ("traditional" by cereals (mainly rice and pulses (mainly beans; and the third ("snacks" by dairy products and processed meat. CONCLUSION: This study identified food intake patterns through an a posteriori approach. Such analysis may be useful for nutritional intervention programs and, after computing scores for each individual according to the patterns identified, for establishing a relationship between diet and other epidemiological measurements of interest.

Use of Language Sample Analysis by School-Based SLPs: Results of a Nationwide Survey

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Pavelko, Stacey L.; Owens, Robert E., Jr.; Ireland, Marie; Hahs-Vaughn, Debbie L.

2016-01-01

Purpose: This article examines use of language sample analysis (LSA) by school-based speech-language pathologists (SLPs), including characteristics of language samples, methods of transcription and analysis, barriers to LSA use, and factors affecting LSA use, such as American Speech-Language-Hearing Association certification, number of years'…

Human factors evaluation of teletherapy: Function and task analysis. Volume 2

Energy Technology Data Exchange (ETDEWEB)

Kaye, R.D.; Henriksen, K.; Jones, R. [Hughes Training, Inc., Falls Church, VA (United States); Morisseau, D.S.; Serig, D.I. [Nuclear Regulatory Commission, Washington, DC (United States). Div. of Systems Technology

1995-07-01

As a treatment methodology, teletherapy selectively destroys cancerous and other tissue by exposure to an external beam of ionizing radiation. Sources of radiation are either a radioactive isotope, typically Cobalt-60 (Co-60), or a linear accelerator. Records maintained by the NRC have identified instances of teletherapy misadministration where the delivered radiation dose has differed from the radiation prescription (e.g., instances where fractions were delivered to the wrong patient, to the wrong body part, or were too great or too little with respect to the defined treatment volume). Both human error and machine malfunction have led to misadministrations. Effective and safe treatment requires a concern for precision and consistency of human-human and human-machine interactions throughout the course of therapy. The present study is the first part of a series of human factors evaluations for identifying the root causes that lead to human error in the teletherapy environment. The human factors evaluations included: (1) a function and task analysis of teletherapy activities, (2) an evaluation of the human-system interfaces, (3) an evaluation of procedures used by teletherapy staff, (4) an evaluation of the training and qualifications of treatment staff (excluding the oncologists), (5) an evaluation of organizational practices and policies, and (6) an identification of problems and alternative approaches for NRC and industry attention. The present report addresses the function and task analysis of teletherapy activities and provides the foundation for the conduct of the subsequent evaluations. The report includes sections on background, methodology, a description of the function and task analysis, and use of the task analysis findings for the subsequent tasks. The function and task analysis data base also is included.

Human factors evaluation of teletherapy: Function and task analysis. Volume 2

International Nuclear Information System (INIS)

Kaye, R.D.; Henriksen, K.; Jones, R.; Morisseau, D.S.; Serig, D.I.

1995-07-01

As a treatment methodology, teletherapy selectively destroys cancerous and other tissue by exposure to an external beam of ionizing radiation. Sources of radiation are either a radioactive isotope, typically Cobalt-60 (Co-60), or a linear accelerator. Records maintained by the NRC have identified instances of teletherapy misadministration where the delivered radiation dose has differed from the radiation prescription (e.g., instances where fractions were delivered to the wrong patient, to the wrong body part, or were too great or too little with respect to the defined treatment volume). Both human error and machine malfunction have led to misadministrations. Effective and safe treatment requires a concern for precision and consistency of human-human and human-machine interactions throughout the course of therapy. The present study is the first part of a series of human factors evaluations for identifying the root causes that lead to human error in the teletherapy environment. The human factors evaluations included: (1) a function and task analysis of teletherapy activities, (2) an evaluation of the human-system interfaces, (3) an evaluation of procedures used by teletherapy staff, (4) an evaluation of the training and qualifications of treatment staff (excluding the oncologists), (5) an evaluation of organizational practices and policies, and (6) an identification of problems and alternative approaches for NRC and industry attention. The present report addresses the function and task analysis of teletherapy activities and provides the foundation for the conduct of the subsequent evaluations. The report includes sections on background, methodology, a description of the function and task analysis, and use of the task analysis findings for the subsequent tasks. The function and task analysis data base also is included

Training department's role in human factor analysis during post-trip reviews

International Nuclear Information System (INIS)

Goodman, D.

1987-01-01

Provide training is a frequent corrective action specified in a post-trip review report. This corrective action is most often decided upon by technical and operational staff, not training staff, without a detailed analysis of whether training can resolve the immediate problem or enhance employees' future performance. A more specific human factor or performance problem analysis would often reveal that training cannot impact or resolve the concern to avoid future occurrences. This human factor analysis is similar to Thomas Gilbert's Behavior Engineering Model (Human Competence, McGraw-Hill, 1978) or Robert Mager's/Peter Pipe's Performance Analysis (Analyzing Performance Problems, Pitman Learning, 1984). At Palo Verde Nuclear Generating Station, training analysts participate in post-trip reviews in order to conduct or provide input to this type of human factor and performance problem analysis. Their goal is to keep provide training out of corrective action statements unless training can in fact impact or resolve the problem. The analysts follow a plant specific logic diagram to identify human factors and to identify whether changes to the environment or to the person would best resolve the concern

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

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Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

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Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-01-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

Confirmatory factor analysis applied to the Force Concept Inventory

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Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

Derivation and application of mathematical model for well test analysis with variable skin factor in hydrocarbon reservoirs

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Pengcheng Liu

2016-06-01

Full Text Available Skin factor is often regarded as a constant in most of the mathematical model for well test analysis in oilfields, but this is only a kind of simplified treatment with the actual skin factor changeable. This paper defined the average permeability of a damaged area as a function of time by using the definition of skin factor. Therefore a relationship between a variable skin factor and time was established. The variable skin factor derived was introduced into existing traditional models rather than using a constant skin factor, then, this newly derived mathematical model for well test analysis considering variable skin factor was solved by Laplace transform. The dimensionless wellbore pressure and its derivative changed with dimensionless time were plotted with double logarithm and these plots can be used for type curve fitting. The effects of all the parameters in the expression of variable skin factor were analyzed based on the dimensionless wellbore pressure and its derivative. Finally, actual well testing data were used to fit the type curves developed which validates the applicability of the mathematical model from Sheng-2 Block, Shengli Oilfield, China.

Detectability Factors for Earth-based Imaging of the LCROSS Ejecta Plume

Science.gov (United States)

Strycker, Paul D.; Schotte, Jonathan M.; Temme, Ruth L.; Chanover, Nancy J.

2017-10-01

NASA’s Lunar Crater Observation and Sensing Satellite (LCROSS) mission delivered a kinetic impactor into Cabeus Crater on 9 October 2009 [1, 2]. Observing campaigns from Earth-based telescopes at multiple facilities attempted to obtain temporally-resolved imaging of the ejecta plume [3], but no Earth-based imaging detections were reported until 2013 after processing images with Principal Component Analysis (PCA) filtering [4]. Subsequently, PCA filtering has revealed plume detections in two additional cameras and also confirmed a non-detection from one telescope [5, 6]. This combination of detection and non-detection data is useful in determining the criteria for detectability in future observations of transient events. The goal of this work is to identify factors contributing to detectability and to establish thresholds applicable to the LCROSS event. We take the data containing detections and then degrade a specific factor in them until the plume is no longer detectable. These derived thresholds for factors (e.g., scattered light, temporal resolution, spatial resolution, field of view, and signal-to-noise of the illuminated foreground of Cabeus) can be compared to the properties of the actual non-detection data to identify problems specific to its observing conditions or observational setup. The percent differences between the thresholds and both the detection data and non-detection data may also reveal the relative importance of these detectability factors. This work was supported by NASA’s Lunar Data Analysis Program through grant number NNX15AP92G. Observations reported here were obtained at the MMT Observatory, a joint facility of the Smithsonian Institution and the University of Arizona.References: [1] Colaprete, A. et al. (2010) Science, 330, 463-468. [2] Schultz, P. H. et al. (2010) Science, 330, 468-472. [3] Heldmann, J. L. et al. (2012) Space Sci. Rev., 167:93-140, doi:10.1007/s11214-011-9759-y. [4] Strycker, P. D. et al. (2013) Nat. Commun., 4