Search results for: mediating variable

Authors: S. A. Alotaibi, M. A. Al-Ajmi

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This work introduces a new concept for controlling the mechanical vibrations via variable stiffness coil spring. The concept relies on fitting a screw though the spring to change the number of active spring coils. A prototype has been built and tested with promising results toward an innovation in the field of vibration control.

Keywords: variable stiffness, coil spring, vibration control, computer science

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Authors: I. Algul, G. Akgun, H. Kurtaran

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Dynamic analysis of composite doubly curved panels with variable thickness subjected to different pulse types using Generalized Differential Quadrature method (GDQ) is presented in this study. Panels with variable thickness are used in the construction of aerospace and marine industry. Giving variable thickness to panels can allow the designer to get optimum structural efficiency. For this reason, estimating the response of variable thickness panels is very important to design more reliable structures under dynamic loads. Dynamic equations for composite panels with variable thickness are obtained using virtual work principle. Partial derivatives in the equation of motion are expressed with GDQ and Newmark average acceleration scheme is used for temporal discretization. Several examples are used to highlight the effectiveness of the proposed method. Results are compared with finite element method. Effects of taper ratios, boundary conditions and loading type on the response of composite panel are investigated.

Keywords: differential quadrature method, doubly curved panels, laminated composite materials, small displacement

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Authors: Daniel E. Martin, Chenghai Yang

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Variable-rate aerial application systems are becoming more readily available; however, aerial applicators typically only use the systems for constant-rate application of materials, allowing the systems to compensate for upwind and downwind ground speed variations. Much of the resistance to variable-rate aerial application system adoption in the U.S. pertains to applicator’s trust in the systems to turn on and off automatically as desired. The objectives of this study were to evaluate a commercially available variable-rate aerial application system under field conditions to demonstrate both the response and accuracy of the system to desired application rate inputs. This study involved planting oats in a 35-acre fallow field during the winter months to establish a uniform green backdrop in early spring. A binary (on/off) prescription application map was generated and a variable-rate aerial application of glyphosate was made to the field. Airborne multispectral imagery taken before and two weeks after the application documented actual field deposition and efficacy of the glyphosate. When compared to the prescription application map, these data provided application system response and accuracy information. The results of this study will be useful for quantifying and documenting the response and accuracy of a commercially available variable-rate aerial application system so that aerial applicators can be more confident in their capabilities and the use of these systems can increase, taking advantage of all that aerial variable-rate technologies have to offer.

Keywords: variable-rate, aerial application, remote sensing, precision application

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Authors: Ricky Finzi-Dottan

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The actor–partner interdependence model (APIM) was employed in this study to investigate the mediating effect self-differentiation and spousal caregiving have on the relationship between recollection of parental care and acceptance and couple satisfaction. One hundred and forty-four non-clinical couples (N=288) in enduring relationships were recruited. Results for actor effects revealed two mediating paths whereby, among both partners, recollection of maternal (but not paternal) acceptance was associated with their self-differentiation and responsive spousal caregiving, which, in turn, were linked to their spousal relationship satisfaction. Partner effects revealed three mediating paths: for both partners, recollection of childhood maternal acceptance was associated with responsive caregiving, which, in turn, was linked with their partner’s relationship satisfaction. Interestingly, the husbands’ recollection of maternal acceptance was associated with their partners' responsive spousal caregiving, which was linked to both spouses’ relationship satisfaction. Our results may support the theoretical assumptions regarding intergenerational continuity from perceptions of childhood via self-differentiation effecting couple caregiving to couple relationship, but only on the mother's part.

Keywords: couple relationship satisfaction, childhood parental acceptance, self-differentiation, couple caregiving, dyadic perspective

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Authors: Gul Jabeen Aizza Anwar, Tadas Sudnickas

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Pakistan’s service sector undeniably assumed a significant economic position that contributed to 58% to the GPD for several years. Yet, recent statistics record a meager growth of 0.86%. Certainly, the sector relies heavily on its workforce as a share dependency and their performance plays a crucial role for sector success. Using the Social Exchange theory (SET), the present study investigated the influence of ethical leadership (EL) on employee performance (EP), employee creativity (EC), and depression among administrative employees working in different fields within the service industry. The study also examined the mediating role of PWB and hope to predict the outcomes. Based on the quantitative, cross-sectional research design, the data was collected using a self-administered questionnaire from administrative staff (n=202) within the service sector of Pakistan. The findings suggested PWB mediates the relationship between EL, EP, and EC whereas depression was found an exception. In addition, hope only mediates EC mediates EC but does not find it mediating EP and depression. This study details important insights and implications for managers and leaders to improve their interactions with employees and create a healthier work environment for long-term sustainability.

Keywords: ethical leadership, employee creativity, Depression, social exchange theory

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Authors: Quiza Pearl Senilla, Hannah Mercado, Francis Angelo Erosa

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Underdog narratives not only provides viewers with models of determination and hard work but that inducing hope may increase the likelihood that viewers will pursue their own goals in life. Although it has been proven that underdog narratives not only create a positive motivational state to the viewers but can also induce hope, little attention has been given to know if this underdog narrative affect the health outcomes or the subjective well-being of the viewers and if their hopefulness mediates on it. To address this gap, using underdog narratives as a predictor and hope as mediator, this study determined the effect of underdog narratives to the subjective well-being of the respondents, the relationship of hope and subjective well-being and last is the mediating effect of hopefulness. This study is an experimental research that uses a between subject design. Purposeful random sampling was used wherein the respondents must meet the following criteria to be part of the study. One hundred and twenty (N=120) Local State University students were assigned to different treatment conditions— underdog narrative, comedy, nature scenes—and a no exposure control group. Results show that there is a minimal difference on the subjective well-being of the respondents when exposed to different treatment condition although it is not significant. A moderate positive correlation between hope and subjective well-being also reveals in this study. And last the result also shows that there is no mediating effect of hopefulness to the subjective well-being of the subjects through exposure to underdog narrative.

Keywords: hope, hope theory, subjective well-being, underdog narratives

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Authors: Norazah Mohd Suki, Norbayah Mohd Suki

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This research aims to examine the influence of mediating effect of corporate social responsibility on the relationship between consumer awareness of green marketing and purchase intentions in the retail setting. Data from 200 valid questionnaires was analyzed using the partial least squares (PLS) approach for the analysis of structural equation models with SmartPLS computer program version 2.0 as research data does not necessarily have a multivariate normal distribution and is less sensitive to sample size than other covariance approaches. PLS results revealed that corporate social responsibility partially mediated the link between consumer awareness of green marketing and purchase intentions of the product in the retail setting. Marketing managers should allocate a sufficient portion of their budget to appropriate corporate social responsibility activities by engaging in voluntary programs for positive return on investment leading to increased business profitability and long run business sustainability. The outcomes of the mediating effects of corporate social responsibility add a new impetus to the growing literature and preceding discoveries on consumer green marketing awareness, which is inadequately researched in the Malaysian setting. Direction for future research is also presented.

Keywords: green marketing awareness, social responsibility, partial least squares, purchase intention

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Authors: Nuray Turan, Maria Karanika-Murray

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In working life, positive behavior and positive mood researches has given importance more and more. Increasing research on the subject sreveals this importance. In this context, positive psychological capital (PsyCap), job crafting (JC), and creativity areamongtheprominentissues in working life. However, it is noteworthy that there is not enough research on the interaction between these three concepts. Therefore, this research has been designed. The question “Does the interaction between JC and PsyCap improve creativity in working life?” has been raised, and“JobCrafting Mediating Effect Between Positive Psychological Capital and Creativity” has been questioned. A questionnaire will be applied using PsyCap, JC and Creativity scales to find answers to the aforementioned questions. Who will be the survey participants is in the process of being determined.

Keywords: positive psychological capital, job crafting, creativity, working life

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Authors: Kimiyo Shimomai, Mihoko Harada

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This study is a literature review of the psychological reactions that occur in end-of-life cancer patients who are nearing death. It searched electronic databases and selected literature related to psychological studies of end-of-life patients. There was no limit on the search period, and the search was conducted until the second week of December 2021. The keywords were specified as “death and dying”, “terminal illness”, “end-of-life”, “palliative care”, “psycho-oncology” and “research”. These literatures referred to Holly (2017): Comprehensive Systematic Review for Advanced Practice Nursing, P268 Figure 10.3 to ensure quality. These literatures were selected with a dissertation score of 4 or 5. The review was conducted in two stages with reference to the procedure of George (2002). First, these references were searched for keywords in the database, and then relevant references were selected from the psychology and nursing studies of end-of-life patients. The number of literatures analyzed was 76 for overseas and 17 for domestic. As for the independent variables, "physical variable" was the most common in 36 literatures (66.7%), followed by "psychological variable" in 35 literatures (64.8%), "spiritual variable" in 21 literatures (38%), and "social variable" in 17 literatures. (31.5%), "Variables related to medical care / treatment" were 16 literatures (29.6%). To summarize the relationship between these independent variables and the dependent variable, when the dependent variable is "psychological variable", the independent variables are "psychological variable", "social variable", and "physical variable". Among the independent variables, the physical variables were the most common. The psychological responses that occur in end-stage cancer patients who are nearing death are mutually influenced by psychological, social, and physical variables. Therefore, it supported the "total pain" advocated by Cicely Saunders.

Keywords: cancer patient, end-of-life, literature review, psychological process

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Authors: Seung Yeon Son

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Workers (especially, competent personnel) have been recognized as a core contributor to overall organizational effectiveness. Hence, verifying the determinants of turnover intention is one of the most important research issues. This study tested the influence of perceived organizational support and abusive supervision on employee’s turnover intention. In addition, mediating roles of psychological contract and emotional exhaustion were examined. Data from 255 Korean employees supported all hypotheses Implications for research and directions for future research are discussed.

Keywords: abusive supervision, emotional exhaustion, perceived organizational support, psychological contract, turnover intention

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Authors: Priya Kedia, Kiranmoy Das

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There is a rich literature on variable selection in regression setting. However, most of these methods assume normality for the response variable under consideration for implementing the methodology and establishing the statistical properties of the estimates. In many real applications, the distribution for the response variable may be non-Gaussian, and one might be interested in finding the best subset of covariates at some predetermined quantile level. We develop dynamic Bayesian approach for variable selection in quantile regression framework. We use a zero-inflated mixture prior for the regression coefficients, and consider the asymmetric Laplace distribution for the response variable for modeling different quantiles of its distribution. An efficient Gibbs sampler is developed for our computation. Our proposed approach is assessed through extensive simulation studies, and real application of the proposed approach is also illustrated. We consider the data from health and retirement study conducted by the University of Michigan, and select the important predictors when the outcome of interest is out-of-pocket medical cost, which is considered as an important measure for financial risk. Our analysis finds important predictors at different quantiles of the outcome, and thus enhance our understanding on the effects of different predictors on the out-of-pocket medical cost.

Keywords: variable selection, quantile regression, Gibbs sampler, asymmetric Laplace distribution

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Authors: Ehsan Motamedian

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Finding all optimal flux distributions of a metabolic model is an important challenge in systems biology. In this paper, a new algorithm is introduced to identify all alternate optimal solutions of a large scale metabolic network. The algorithm reduces the model to decrease computations for finding optimal solutions. The algorithm was implemented on the Escherichia coli metabolic model to find all optimal solutions for lactate and acetate production. There were more optimal flux distributions when acetate production was optimized. The model was reduced from 1076 to 80 variable fluxes for lactate while it was reduced to 91 variable fluxes for acetate. These 11 more variable fluxes resulted in about three times more optimal flux distributions. Variable fluxes were from 12 various metabolic pathways and most of them belonged to nucleotide salvage and extra cellular transport pathways.

Keywords: flux variability, metabolic network, mixed-integer linear programming, multiple optimal solutions

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

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Authors: Nguyen J. M., Lucas G., Brunner M., Ruan S., Antonioli D.

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Deep learning based on convolutional neural networks (CNN) is a very powerful technique for classifying information from an image. We propose a new method, DeepNic, to transform each variable of a tabular dataset into an image where each pixel represents a set of conditions that allow the variable to make an error-free prediction. The contrast of each pixel is proportional to its prediction performance and the color of each pixel corresponds to a sub-family of NICs. NICs are probabilities that depend on the number of inputs to each neuron and the range of coefficients of the inputs. Each variable can therefore be expressed as a function of a matrix of 2 vectors corresponding to an image whose pixels express predictive capabilities. Our objective is to transform each variable of tabular data into images into an image that can be analysed by CNNs, unlike other methods which use all the variables to construct an image. We analyse the NIC information of each variable and express it as a function of the number of neurons and the range of coefficients used. The predictive value and the category of the NIC are expressed by the contrast and the color of the pixel. We have developed a pipeline to implement this technology and have successfully applied it to genomic expressions on an Affymetrix chip.

Keywords: tabular data, deep learning, perfect trees, NICS

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Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

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Authors: E. Tchandao Mangamana, V. Cariou, E. Vigneau, R. Glele Kakai, E. M. Qannari

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A new definition of a latent variable associated with a dataset makes it possible to propose variants of the PLS2 regression and the multi-block PLS (MB-PLS). We shall refer to these variants as Rd-PLS regression and Rd-MB-PLS respectively because they are inspired by both Redundancy analysis and PLS regression. Usually, a latent variable t associated with a dataset Z is defined as a linear combination of the variables of Z with the constraint that the length of the loading weights vector equals 1. Formally, t=Zw with ‖w‖=1. Denoting by Z' the transpose of Z, we define herein, a latent variable by t=ZZ’q with the constraint that the auxiliary variable q has a norm equal to 1. This new definition of a latent variable entails that, as previously, t is a linear combination of the variables in Z and, in addition, the loading vector w=Z’q is constrained to be a linear combination of the rows of Z. More importantly, t could be interpreted as a kind of projection of the auxiliary variable q onto the space generated by the variables in Z, since it is collinear to the first PLS1 component of q onto Z. Consider the situation in which we aim to predict a dataset Y from another dataset X. These two datasets relate to the same individuals and are assumed to be centered. Let us consider a latent variable u=YY’q to which we associate the variable t= XX’YY’q. Rd-PLS consists in seeking q (and therefore u and t) so that the covariance between t and u is maximum. The solution to this problem is straightforward and consists in setting q to the eigenvector of YY’XX’YY’ associated with the largest eigenvalue. For the determination of higher order components, we deflate X and Y with respect to the latent variable t. Extending Rd-PLS to the context of multi-block data is relatively easy. Starting from a latent variable u=YY’q, we consider its ‘projection’ on the space generated by the variables of each block Xk (k=1, ..., K) namely, tk= XkXk'YY’q. Thereafter, Rd-MB-PLS seeks q in order to maximize the average of the covariances of u with tk (k=1, ..., K). The solution to this problem is given by q, eigenvector of YY’XX’YY’, where X is the dataset obtained by horizontally merging datasets Xk (k=1, ..., K). For the determination of latent variables of order higher than 1, we use a deflation of Y and Xk with respect to the variable t= XX’YY’q. In the same vein, extending Rd-MB-PLS to the path modeling setting is straightforward. Methods are illustrated on the basis of case studies and performance of Rd-PLS and Rd-MB-PLS in terms of prediction is compared to that of PLS2 and MB-PLS.

Keywords: multiblock data analysis, partial least squares regression, path modeling, redundancy analysis

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Authors: Farid Saeidi, Serkan Dag

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In this study, fracture analysis of a fibrous composite laminate with variable fiber spacing is carried out using Jk-integral method. The laminate is assumed to be under thermal loading. Jk-integral is formulated by using the constitutive relations of plane orthotropic thermoelasticity. Developed domain independent form of the Jk-integral is then integrated into the general purpose finite element analysis software ANSYS. Numerical results are generated so as to assess the influence of variable fiber spacing on mode I and II stress intensity factors, energy release rate, and T-stress. For verification, some of the results are compared to those obtained using displacement correlation technique (DCT).

Keywords: Jk-integral, Variable Fiber Spacing, Thermoelasticity, T-stress, Finite Element Method, Fibrous Composite.

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Authors: Gultekin Gurcay

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The objective of this study was to examine the relationship between transformational leadership and innovative work behavior and to evaluate the mediating role of leader-member exchange relationships (LMX) on the assumed relationship. This study has focused on the suggestion that LMX might emerge through transformational leadership behaviors and thus could mediate the relationship between transformational leadership and innovative behavior. A cross-sectional survey research has been conducted on the relationship these leadership approaches and their impact on organizational HRM-outcomes has been conducted on two organizations operating in the technical sector in Istanbul-Turkey. The results of the research have supported the hypotheses. Transformational leadership was positively related to the innovative behaviors and LMX emerged to mediate that relationship.

Keywords: innovative leadership, leader-member exchange, transformational leadership, Turkey

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Authors: Maaza Saeed

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The current study examined the mediating roles of emotional intelligence (EI) and resilience in the relationship between mindfulness and life satisfaction among Chinese and Pakistani samples. 450 participants completed the mindful attention awareness scale, resilience scale, wong law emotional intelligence scale, and satisfaction with life scale from both cultures. Path analysis revealed that both emotional intelligence (EI) and resilience fully mediated the relationship between mindfulness and life satisfaction among participants of both cultures. Besides, a multi-group evaluation suggests that Chinese participants with significant EI scores are more likely to sustain greater life satisfaction than their Pakistani counterparts. Insinuation for prospective researches and current study pitfalls are discussed.

Keywords: mindfulness, life satisfaction, resilience, emotional intelligence

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Authors: Georgiana Onicescu, Yuqian Shen

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Due to the complex nature of geo-referenced data, multicollinearity of the risk factors in public health spatial studies is a commonly encountered issue, which leads to low parameter estimation accuracy because it inflates the variance in the regression analysis. To address this issue, we proposed a two-stage variable selection method by extending the least absolute shrinkage and selection operator (Lasso) to the Bayesian spatial setting, investigating the impact of risk factors to health outcomes. Specifically, in stage I, we performed the variable selection using Bayesian Lasso and several other variable selection approaches. Then, in stage II, we performed the model selection with only the selected variables from stage I and compared again the methods. To evaluate the performance of the two-stage variable selection methods, we conducted a simulation study with different distributions for the risk factors, using geo-referenced count data as the outcome and Michigan as the research region. We considered the cases when all candidate risk factors are independently normally distributed, or follow a multivariate normal distribution with different correlation levels. Two other Bayesian variable selection methods, Binary indicator, and the combination of Binary indicator and Lasso were considered and compared as alternative methods. The simulation results indicated that the proposed two-stage Bayesian Lasso variable selection method has the best performance for both independent and dependent cases considered. When compared with the one-stage approach, and the other two alternative methods, the two-stage Bayesian Lasso approach provides the highest estimation accuracy in all scenarios considered.

Keywords: Lasso, Bayesian analysis, spatial analysis, variable selection

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Authors: Thushel Jayaweera

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In performance evaluation literature, there has been no investigation indicating the impact of job characteristics, working conditions and motivation on the job performance among the hotel workers in Britain. This study tested the relationship between working conditions (physical and psychosocial working conditions) and job performance (task and contextual performance) with motivators (e.g. recognition, achievement, the work itself, the possibility for growth and work significance) as the mediating variable. A total of 254 hotel workers in 25 hotels in Bristol, United Kingdom participated in this study. Working conditions influenced job performance and motivation moderated the relationship between working conditions and job performance. Poor workplace conditions resulted in decreasing employee performance. The results point to the importance of motivators among hotel workers and highlighted that work be designed to provide recognition and sense of autonomy on the job to enhance job performance of the hotel workers. These findings have implications for organizational interventions aimed at increasing employee job performance.

Keywords: hotel workers, working conditions, motivation, job characteristics, job performance

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Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene

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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.

Keywords: differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control

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Authors: Anjali Malik

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This paper presents a review of the literature on behavioral addictions with a particular focus on understanding online gaming habits among adolescents. Extant researches yielded many different sets of antecedent factors for developing pathological online gaming behavior. This paper draws findings from the most-cited publications most closely associated with factors explaining why individuals develop such kind of problematic behavior. What emerges as central to understanding this phenomenon is the presence of multiple variable causes that take into account the individual, the environment and their interaction to explain the risk behavior such as pathological online gaming. In addition to that role of some mediating factors and pull factors has also been discussed, along with the consequences on personal, social and academic performance resulting from such kind of addictive behavior. The paper also makes recommendations for future research including developing a deeper understanding of the phenomena studied here by examining the relative contribution of these multiple-risk contexts.

Keywords: pathological gaming, gaming addiction, adolescents, behavior

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Authors: Esther Yin-Nei Cho

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There is inconsistency among studies about whether there is an association between poverty and the subjective wellbeing of children. Some have found a positive association, though its magnitude could be limited, others have shown no association. One possible explanation for this inconsistency is that household income, an often-adopted measure of child poverty, may not accurately and stably reflect the actual life experience of children. Some studies have suggested, however, that material deprivation covering various dimensions of children’s lives could be a better measure of child poverty. Another possible explanation for the inconsistency is that the link between poverty and subjective wellbeing of children may not be that straightforward, as there could be underlying mechanisms, such as mediation and moderation, influencing its direction or strength. While a mediator refers to the mechanism through which an independent variable affects a dependent variable, a moderator changes the direction or strength of the relationship between an independent variable and a dependent variable. As suggested by empirical evidence, family relationships and friendships could be potential mediators or moderators of the link between poverty and subjective well-being: poverty affects relationships; relationships are an important element in children’s subjective well-being; and economic status affects child outcomes, though not necessarily subjective wellbeing, through relationships. Since the potential links have not been adequately understood, this study fills this gap by examining the possible role of family relationships and friendships as mediators or moderators between poverty (using child-derived material deprivation as measure) and the subjective wellbeing of children. Improving subjective wellbeing is increasingly considered as a policy goal. The finding of no or a limited association between poverty and subjective wellbeing of children could be a justification for less effort to improve poverty in this regard. But if the observed magnitude of that association is due to some underlying mechanisms at work, the effect of poverty may be underestimated and the potentially useful strategies that take into account both poverty and other mediators or moderators for improving children’s subjective well-being may be overlooked. Multiple mediation, and multiple moderation models, based on regression analyses, are performed to a sample of approximately 1,600 children, who are aged 10 to 15, from the wellbeing survey conducted by The Children’s Society in England from 2010 to 2011. Results show that the effect of children’s material deprivation on their subjective well-being is mediated by their family relationships and friendships. Moreover, family relationships are a significant moderator. It is found that the negative impact of child deprivation on subjective wellbeing could be exacerbated if family relationships are not going well, while good family relationships may prevent the further decline in subjective well-being. Policy implications of the findings are discussed. In particular, policy measures that focus on strengthening the family relationships or nurturing home environment through supporting household’s economic security and parental time with children could promote the subjective wellbeing of children.

Keywords: child poverty, mediation, moderation, subjective well-being of children

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Authors: Saba Harati, Nasrin Arian Parsa

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The current research was an attempt to investigate the effect of resilience on mental health and life satisfaction. In one Cross Sectional research, 287 (173 females and 114 males) students of Tehran University were participated their average age was 23.17 years old (SD=4.9). The instruments used for assessing the research variables included: Cutter and Davidson resilience scale (CD-RISC), the short form of the depression-anxiety-stress scale, and life satisfaction scale. The data analysis was done in the form of structural equation model. The results of Simultaneous Hierarchical Multiple Regression Analysis indicated that there was a significant mediating role of the negative emotions (depression, anxiety, and stress), in the relationship between the family resilience (p < 0.001) and satisfaction with life (p < 0.001). Resilience results in life satisfaction by reducing the emotional problems (or increasing the mental health level). The effect of the resilience variable on life satisfaction was indirect.

Keywords: resilience, negative emotion, mental health, life satisfaction

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Authors: Edris Rawashdeh, I. Abu-Falahah, H. M. Jaradat

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The variable-coefficient non-linear dispersive wave equation is investigated with the aid of symbolic computation. By virtue of a newly developed simplified bilinear method, multi-soliton solutions for such an equation have been derived. Effects of the inhomogeneities of media and nonuniformities of boundaries, depicted by the variable coefficients, on the soliton behavior are discussed with the aid of the characteristic curve method and graphical analysis.

Keywords: dispersive wave equations, multiple soliton solution, Hirota Bilinear Method, symbolic computation

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Authors: Bita Mashayekhi, Amin Jahangard, Milad Samavat, Saeid Homayoun

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In the modern competitive business environment, one cannot overstate the importance of corporate social responsibility. The controversial link between the social and financial performance of firms has become a topic of interest for scholars. Hence, this study examines the social and financial performance link by taking into account the mediating role of innovation performance. We conducted the Covariance-based Structural Equation Modeling (CB-SEM) method on an international sample of firms provided by the ASSET4 database. In this research, to explore the black box of the social and financial performance relationship, we first examined the effect of social performance separately on financial performance and innovation; then, we measured the mediation role of innovation in the social and financial performance link. While our results indicate the positive effect of social performance on financial performance and innovation, we cannot document the positive mediating role of innovation. This possibly relates to the long-term nature of benefits from investments in innovation.

Keywords: ESG, financial performance, innovation, social performance, structural equation modeling

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Authors: Bhavna Malik

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The study is build on a theoretical framework that links characteristics of job, key attitudes and intention to leave, why faculty may be disengaging from institutional service. The literature indicates that job characteristics, key attitudes and intention to leave are very important for effective organizational functioning. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attitudes predicted intention to leave negatively. The present study attempted to propose a new integrative model of the relationships among job characteristics, key attitudes, and intention to leave. The main purpose of the present study is to examine the effects of job characteristics on intention to leave. While examining the role of job characteristics, the mediating roles of key attitudes were taken into account in order to better understand how job characteristics affect the exhibition of intention to leave. The secondary purpose is to investigate the effects of job characteristics on key attitudes, and the effects of key attitudes on intention to leave. Job characteristics of remuneration, resource for professional activities, career opportunities were positively associated with the work attitude of job satisfaction. The aggregate job scope was positively associated with the work attitude of organizational commitment although no single job characteristic was significantly associated with organizational commitment. Commitment, however, did not significantly affect time spent on institutional service. Two job characteristics—time spent on research and time spent on teaching—were negatively associated with this behavior. In general, the literature showed that some job characteristics might be the antecedents of job satisfaction and the aggregate variable job scope was positively associated with organizational commitment, and these key attiudes predicted intention to leave negatively. In turn, job satisfaction and organizational commitment were negatively associated with the intention to leave. In addition to these, organizational commitment was negatively associated with the intention to leave. However, no significant direct association was found between job characteristics and intention to leave.

Keywords: Job Characteristics Model, job satisfaction, organizational commitment, intention to leave

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Authors: Sofia Mariani, Irene Leo

Abstract:

The objective of the present study is to define the mediating role of attitudes that objectify and devalue women (hostile sexism, benevolent sexism, and sexual objectification of women) in the indirect correlation between exposure to televised sports and acceptance of rape myths. A second goal is to contribute to research on the topic by defining the role of mediators in exposure to different types of sports, following the traditional gender classification of sports. Data collection was carried out by means of an online questionnaire, measuring television sport exposure, sport type, hostile sexism, benevolent sexism, and sexual objectification of women. Data analysis was carried out using IBM SPSS software. The model used was created using Ordinary Least Squares (OLS) regression path analysis. The predictor variable in the model was television sports exposure, the outcome was rape myths acceptance, and the mediators were (1) hostile sexism, (2) benevolent sexism, and (3) sexual objectification of women. Correlation analyses were carried out dividing by sport type and controlling for the participants’ gender. As seen in existing literature, television sports exposure was found to be indirectly and positively related to rape myth acceptance through the mediating role of: (1) hostile sexism, (2) benevolent sexism, and (3) sexual objectification of women. The type of sport watched influenced the role of the mediators: hostile sexism was found to be the common mediator to all sports type, exposure to traditionally considered feminine or neutral sports showed the additional mediation effect of sexual objectification of women. In line with existing literature, controlling for gender showed that the only significant mediators were hostile sexism for male participants and benevolent sexism for female participants. Given the prevalence of men among the viewers of traditionally considered masculine sports, the correlation between television sports exposure and rape myth acceptance through the mediation of hostile sexism is likely due to the gender of the participants. However, this does not apply to the viewers of traditionally considered feminine and neutral sports, as this group is balanced in terms of gender and shows a unique mediation: the correlation between television sports exposure and rape myth acceptance is mediated by both hostile sexism and sexual objectification. Given that hostile sexism is defined as hostility towards women who oppose or fail to conform to traditional gender roles, these findings confirm that sport is perceived as a non-traditional activity for women. Additionally, these results imply that the portrayal of women in traditionally considered feminine and neutral sports - which are defined as such because of their aesthetic characteristics - may have a strong component of sexual objectification of women. The present research contributes to defining the association between sports exposure and rape myth acceptance through the mediation effects of sexist attitudes and sexual objectification of women. The results of this study have practical implications, such as supporting the feminine sports teams who ask for more practical and less revealing uniforms, more similar to their male colleagues and therefore less objectifying.

Keywords: television exposure, sport, rape myths, objectification, sexism

Procedia PDF Downloads 67

Authors: Selvakumar Ulaganathan, Ivo Couckuyt, Francesco Ferranti, Tom Dhaene, Eric Laermans

Abstract:

Variable-fidelity surrogate modelling offers an efficient way to approximate function data available in multiple degrees of accuracy each with varying computational cost. In this paper, a Kriging-based variable-fidelity surrogate modelling approach is introduced to approximate such deterministic data. Initially, individual Kriging surrogate models, which are enhanced with gradient data of different degrees of accuracy, are constructed. Then these Gradient enhanced Kriging surrogate models are strategically coupled using a recursive CoKriging formulation to provide an accurate surrogate model for the highest fidelity data. While, intuitively, gradient data is useful to enhance the accuracy of surrogate models, the primary motivation behind this work is to investigate if it is also worthwhile incorporating gradient data of varying degrees of accuracy.

Keywords: Kriging, CoKriging, Surrogate modelling, Variable- fidelity modelling, Gradients

Procedia PDF Downloads 527