This is an exploratory study of the Situational Theory of Problem Solving applied to the context of climate change communication. Selective exposure to politically slanted media is explored as a referent criterion and framing effects are also tested. Relationships between consumption of media characterized as conservative or liberal with referent criterion, Situational Motivation in Problem Solving, problem recognition, involvement recognition, and constraint recognition are tested.

Theoretical developments of emotional intelligence (EI) are jeopardized by the inability of empirical studies to keep pace with its intense surge to the forefront of both lay and academic communities. Due to the paucity of empirical evidence, claims of the contributions of EI are met with speculation in the scientific community. Furthermore, EI is conceptualized and measured in a variety and often, diverging ways. Subsequent to indications from previous literature that EI shows promise to be linked to the field of health and psychological well-being (Austin, Saklofske, & Egan, 2005), the primary aim of this study was to investigate the concurrent criterion validity of a mixed model conceptualization of EI with self-reported exercise attitudes by comparing two subsamples of university students, (Mean Age = 22 years; 72% Female, 28% Male; NonKinesiology n1 = 271, Kinesiology n2 = 127). The finding of a weak overall correlation fails to provide concurrent criterion validity to the BarOn (2002) conceptualization of EI with exercise attitudes as measured by HBQ (Austin, unpublished), r(398) = .13, p = .013. This finding is further substantiated by the lack of significant findings in an ANOVA and a lack of practical significance in a MANOVA. While the criterion group had significantly stronger beliefs of the benefits of exercise, F(1, 394) = 47.54, p < .001, Å2 = .11; no significant difference between the means of the Composite EI was found between the subsamples for the main effect (field of study) or for the interaction effect (field of study ~ sex): F(1, 394) = 0.08, p = .78; F(1, 394) = 1.82, p = .18, respectively. Additionally, the MANOVA findings determined that only 1.6% of the overall variance could be attributed to the model effect of self-reported activity level and exercise attitude with EI. The secondary purpose of this study was to examine the sex differences in the relationship of EI and exercise attitudes. The scales for the female subsample were not significantly correlated, r(287) = .07, p = .25; whereas, a low and significant correlation was found in the male subsample, r(111) = .37, p = .001. The finding is noteworthy and appears to suggest that the contributing factor to the significant, but weak overall correlation, was obtained from the male sector. Although, the study does find the BarOn EQ-i:S instrument to be a good measure with strong internal consistency reliability and large intercorrelations with its components, the findings point to concerns as to what is being measured and the degree to which the measure overlaps with the personality domain.

<p>Disturbances in power systems are common and they result in electromechanical oscillations called power swing. The power swings could be severe and it may lead to loss of synchronism among the interconnected generators. This is referred to as out-of-step condition. The voltage and current swings during an out-of-step condition damage power system equipments and also cause unwanted operations of various protective devices. The protection systems require an effective algorithm for fast and accurate detection of out-of-step condition. </p> <p>This research is focused on the development of a simple and effective out-of-step relay capable of detecting out-of-step condition in a complex power system. To achieve this, the research has gone through four distinct stages: development of an algorithm, simulation, hardware implementation and its testing. </p> <p>An out-of-step algorithm is proposed based on equal area criterion in time domain. The equal area criterion in time domain is obtained by modifying the traditional equal area criterion in power angle domain. A single machine infinite bus system, a two machine infinite bus system and a three machine infinite bus system and a 17-bus multiple machines system are used as case studies and are modeled using simulation tool(PSCAD). </p> <p>To test the effectiveness of the proposed algorithm, various out-of-step conditions are simulated by applying disturbances at various locations in the above chosen power system configurations. For hardware implementation and testing of the algorithm, a digital signal processing board (ADSP-BF533 from Analog Devices ) is used. To test the performance of the developed digital relay in a closed loop, real time power system signals are necessary and therefore for this purpose, a Real Time Digital Simulator (RTDS) available in the power research laboratory is used. The RTDS simulator mimics the actual power systems in real time. The signals required by the relays can be tapped from the RTDS and the signals coming from relay can be fed back into the RTDS, which makes the closed loop testing of the digital relay possible. This research has yielded a simple out-of-step algorithm and unlike the other out-of-step detection techniques proposed in the literature does not need offline system studies to arrive at a solution.The developed digital out-of-step relay is capable of making decisions based only on the information available from its point of installation, thus it avoids the communication devices which is advantageous for the out-of-step protection of a complex power system. Finally, the simulation results show that the proposed algorithm can be applied to any power configurations and is faster compared to the conventional concentric rectangle schemes used in the literature.</p>

DNA microarrays are capable of measuring expression levels of thousands of genes, even the whole genome, in a single experiment. Based on this, they have been widely used to extend the studies of cancerous tissues to a genomic level. One of the main goals in DNA microarray experiments is to identify a set of relevant genes such that the desired outputs of the experiment mostly depend on this set, to the exclusion of the rest of the genes. This is motivated by the fact that the biological process in cell typically involves only a subset of genes, and not the whole genome. The task of selecting a subset of relevant genes is called feature (gene) selection. Herein, we propose a feature selection algorithm for gene expression data. It is based on the Hilbert-Schmidt independence criterion, and partly motivated by Rank-One Downdate (R1D) and the Singular Value Decomposition (SVD). The algorithm is computationally very fast and scalable to large data sets, and can be applied to response variables of arbitrary type (categorical and continuous). Experimental results of the proposed technique are presented on some synthetic and well-known microarray data sets. Later, we discuss the capability of HSIC in providing a general framework which encapsulates many widely used techniques for dimensionality reduction, clustering and metric learning. We will use this framework to explain two metric learning algorithms, namely the Fisher discriminant analysis (FDA) and closed form metric learning (CFML). As a result of this framework, we are able to propose a new metric learning method. The proposed technique uses the concepts from normalized cut spectral clustering and is associated with an underlying convex optimization problem.

Theoretical developments of emotional intelligence (EI) are jeopardized by the inability of empirical studies to keep pace with its intense surge to the forefront of both lay and academic communities. Due to the paucity of empirical evidence, claims of the contributions of EI are met with speculation in the scientific community. Furthermore, EI is conceptualized and measured in a variety and often, diverging ways. Subsequent to indications from previous literature that EI shows promise to be linked to the field of health and psychological well-being (Austin, Saklofske, & Egan, 2005), the primary aim of this study was to investigate the concurrent criterion validity of a mixed model conceptualization of EI with self-reported exercise attitudes by comparing two subsamples of university students, (Mean Age = 22 years; 72% Female, 28% Male; NonKinesiology n1 = 271, Kinesiology n2 = 127). The finding of a weak overall correlation fails to provide concurrent criterion validity to the BarOn (2002) conceptualization of EI with exercise attitudes as measured by HBQ (Austin, unpublished), r(398) = .13, p = .013. This finding is further substantiated by the lack of significant findings in an ANOVA and a lack of practical significance in a MANOVA. While the criterion group had significantly stronger beliefs of the benefits of exercise, F(1, 394) = 47.54, p < .001, Å2 = .11; no significant difference between the means of the Composite EI was found between the subsamples for the main effect (field of study) or for the interaction effect (field of study ~ sex): F(1, 394) = 0.08, p = .78; F(1, 394) = 1.82, p = .18, respectively. Additionally, the MANOVA findings determined that only 1.6% of the overall variance could be attributed to the model effect of self-reported activity level and exercise attitude with EI. The secondary purpose of this study was to examine the sex differences in the relationship of EI and exercise attitudes. The scales for the female subsample were not significantly correlated, r(287) = .07, p = .25; whereas, a low and significant correlation was found in the male subsample, r(111) = .37, p = .001. The finding is noteworthy and appears to suggest that the contributing factor to the significant, but weak overall correlation, was obtained from the male sector. Although, the study does find the BarOn EQ-i:S instrument to be a good measure with strong internal consistency reliability and large intercorrelations with its components, the findings point to concerns as to what is being measured and the degree to which the measure overlaps with the personality domain.

<p>Disturbances in power systems are common and they result in electromechanical oscillations called power swing. The power swings could be severe and it may lead to loss of synchronism among the interconnected generators. This is referred to as out-of-step condition. The voltage and current swings during an out-of-step condition damage power system equipments and also cause unwanted operations of various protective devices. The protection systems require an effective algorithm for fast and accurate detection of out-of-step condition. </p> <p>This research is focused on the development of a simple and effective out-of-step relay capable of detecting out-of-step condition in a complex power system. To achieve this, the research has gone through four distinct stages: development of an algorithm, simulation, hardware implementation and its testing. </p> <p>An out-of-step algorithm is proposed based on equal area criterion in time domain. The equal area criterion in time domain is obtained by modifying the traditional equal area criterion in power angle domain. A single machine infinite bus system, a two machine infinite bus system and a three machine infinite bus system and a 17-bus multiple machines system are used as case studies and are modeled using simulation tool(PSCAD). </p> <p>To test the effectiveness of the proposed algorithm, various out-of-step conditions are simulated by applying disturbances at various locations in the above chosen power system configurations. For hardware implementation and testing of the algorithm, a digital signal processing board (ADSP-BF533 from Analog Devices ) is used. To test the performance of the developed digital relay in a closed loop, real time power system signals are necessary and therefore for this purpose, a Real Time Digital Simulator (RTDS) available in the power research laboratory is used. The RTDS simulator mimics the actual power systems in real time. The signals required by the relays can be tapped from the RTDS and the signals coming from relay can be fed back into the RTDS, which makes the closed loop testing of the digital relay possible. This research has yielded a simple out-of-step algorithm and unlike the other out-of-step detection techniques proposed in the literature does not need offline system studies to arrive at a solution.The developed digital out-of-step relay is capable of making decisions based only on the information available from its point of installation, thus it avoids the communication devices which is advantageous for the out-of-step protection of a complex power system. Finally, the simulation results show that the proposed algorithm can be applied to any power configurations and is faster compared to the conventional concentric rectangle schemes used in the literature.</p>

This paper describes a method by means of FE code DEFORMTM-2D to simulate the formation of central bursting defects in extrusion processes; the effect of various extrusion parameters such as half die angle, reduction in area, friction factor, and strain hardening exponent on the maximum damage value is examined. The differences between various ductile fracture criteria are compared and critical damage value(CDV) of the material AA6061 is found. In addition, we get the strength coefficient(K), strain hardening exponent(n), CDV and friction factor(m) by material tests, such as uniform tensile test, notched tensile test, compression test, and ring compression test. Finally, the cold multistage extrusion experiment was conducted to verify the accuracy of the finite element simulations. From the continuous three pass extrusion experimental data, no fracture in the center of the extruded product was found. From the analytical data, it was known that the maximum damage value 1.0479 for third pass extrusion was small than critical damage value 1.068, thus, central bursting defects didn¡¦t occur in extrusion processes.

ABSTRACT For long, scholars have been using the research tools invented in the western world to examine the leadership styles developed in western societies. With so many cultural differences between western and eastern societies, it¡¦s very difficult to explain the leadership styles and phenomena of Chinese leaders if only the same research tools are applied. In the past, many researches on the relationship between leadership behavior and leadership effectiveness were only focused on leadership behavior before leadership effectiveness was narrated; however, whether a leadership style works or how effectively it works isn¡¦t decided by the leader only. Thus, in this study, 297 pairs of supervisors and subordinates from 30 banks in central Taiwan (2 regional centers and 63 branches) were selected for an empirical study. Their background information was collected for the analysis of chaxu geju¡Xa criterion of categorization for relationship, loyalty and capability. Every subordinate was categorized into an ¡§insider¡¨ or ¡§outsider¡¨ according to the perception of his/her supervisor. Then, the relationship between the performance of every subordinate and the leadership behavior (patriarchal leadership: authoritarianism, benevolence and moral) of his/her supervisor were analyzed for leadership effectiveness. The findings of this study showed the Chinese supervisors would objectively categorize their subordinates into ¡§insiders¡¨ and ¡§outsiders¡¨ according to the rank of relationship, loyalty and capability. The supervisors tended to give ¡§insiders¡¨ better performance evaluation. The insiders felt they were given more benevolence and moral, but less authoritarianism; the outsiders felt just the opposite. The Chinese supervisors had greater personal attachment to the insiders and allocated more resources to them, so the insiders had better work attitude and performance; the outsiders was the contrary. Without equal treatment, the leadership effectiveness in the insiders and in the outsiders was different. Finally a concrete brief on the limitations of the study, further research direction in the future and how the study was related to the management in the real world was presented. Key words: chaxu geju (a multiplicity of individual distinctions of rank and distance), criterion of categorization, leadership behavior, leadership effectiveness

ABSTRACT The objective of this study is to establish the Forming Limit Diagram (FLD) of tubes. An experimental system of tube hydroforming, the electrical chemical etching method and the image process system are used to carry out the sheet metal forming test and the hydraulic bulge-forming test of annealed aluminum alloy tubes. Furthermore, Hill¡¦s new yield criterion is also used to predict the Forming Limit Curves of sheets. The predicted forming limit diagrams are compared with experimental data. The forming limit diagrams of tubes are coincident with those of sheets. Also, the predicted forming limit curves by Hill¡¦s new yield criterion agree quite well with those by experiments. Therefore, Hill¡¦s new yield criterion can be used to establish the forming limit curves of sheets or tubes.

In this dissertation, we propose methodology to analyze high dimensional genomics data, in which the observations have large number of outcome variables, in addition to exposure variables. In the Chapter 1, we investigate methods for genetic pathway analysis, where we have a small number of exposure variables. We propose two Canonical Correlation Analysis based methods, that select outcomes either sequentially or by screening, and show that the performance of the proposed methods depend on the correlation between the genes in the pathway. We also propose and investigate criterion for fixing the number of outcomes, and a powerful test for the exposure effect on the pathway. The methodology is applied to show that air pollution exposure affects gene methylation of a few genes from the asthma pathway. In Chapter 2, we study penalized multivariate regression as an efficient and flexible method to study the relationship between large number of covariates and multiple outcomes. We use penalized likelihood to shrink model parameters to zero and to select only the important effects. We use the Bayesian Information Criterion (BIC) to select tuning parameters for the employed penalty and show that it chooses the right tuning parameter with high probability. These are combined in the “two-stage procedure”, and asymptotic results show that it yields consistent, sparse and asymptotically normal estimator of the regression parameters. The method is illustrated on gene expression data in normal and diabetic patients. In Chapter 3 we propose a method for estimation of covariates-dependent principal components analysis (PCA) and covariance matrices. Covariates, such as smoking habits, can affect the variation in a set of gene methylation values. We develop a penalized regression method that incorporates covariates in the estimation of principal components. We show that the parameter estimates are consistent and sparse, and show that using the BIC to select the tuning parameter for the penalty functions yields good models. We also propose the scree plot residual variance criterion for selecting the number of principal components. The proposed procedure is implemented to show that the first three principal components of genes methylation in the asthma pathway are different in people who did not smoke, and people who did.