University of Houston

About: University of Houston is a education organization based out in Houston, Texas, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 23074 authors who have published 53903 publications receiving 1641968 citations.

Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

Abstract: Remote sensing (RS) systems have been collecting massive volumes of datasets for decades, managing and analyzing of which are not practical using common software packages and desktop computing resources. In this regard, Google has developed a cloud computing platform, called Google Earth Engine (GEE), to effectively address the challenges of big data analysis. In particular, this platform facilitates processing big geo data over large areas and monitoring the environment for long periods of time. Although this platform was launched in 2010 and has proved its high potential for different applications, it has not been fully investigated and utilized for RS applications until recent years. Therefore, this study aims to comprehensively explore different aspects of the GEE platform, including its datasets, functions, advantages/limitations, and various applications. For this purpose, 450 journal articles published in 150 journals between January 2010 and May 2020 were studied. It was observed that Landsat and Sentinel datasets were extensively utilized by GEE users. Moreover, supervised machine learning algorithms, such as Random Forest, were more widely applied to image classification tasks. GEE has also been employed in a broad range of applications, such as Land Cover/land Use classification, hydrology, urban planning, natural disaster, climate analyses, and image processing. It was generally observed that the number of GEE publications have significantly increased during the past few years, and it is expected that GEE will be utilized by more users from different fields to resolve their big data processing challenges.

The Structure of Personality Pathology: Both General ('g') and Specific ('s') Factors?

Abstract: Recent editions of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) conceptualize personality disorders (PDs) as categorical constructs, but high PD co-occurrence suggests underlying latent dimensions. Moreover, several borderline PD criteria resemble Criterion A of the new DSM-5 Section III general criteria for personality pathology (i.e., self and interpersonal dysfunction). We evaluated a bifactor model of PD pathology in which a general factor and several specific factors of personality pathology (PD 'g' and 's' factors, respectively) account for the covariance among PD criteria. In particular, we examined the extent to which the borderline PD criteria would load exclusively onto the g-factor versus on both the g- and one or more s-factors. A large (N = 966) sample of inpatients were interviewed for six DSM-IV (American Psychiatric Association, 1994) PDs using the (Structured Clinical Interview for Personality Disorders (SCID-II; First, Spitzer, Gibbon, Williams, & Benjamin, 1994) with no skip-outs. We ran a series of confirmatory, exploratory, and bifactor exploratory factor analyses on the rated PD criteria. The confirmatory analysis largely replicated the DSM PDs, but with high factor correlations. The "standard" exploratory analysis replicated four of the DSM PDs fairly well, but nearly half the criteria cross-loaded. In the bifactor analysis, borderline PD criteria loaded only on the general factor; the remaining PDs loaded either on both the general and a specific factor or largely only on a specific factor. Results are interpreted in the context of several possibilities to define the nature of the general factor.

Technology-Information Processing Fit and the Performance of R&D Project Groups: A Test of Contingency Theory

Abstract: A study of 98 R&D project groups using a longitudinal design found support for the contingency theory hypothesis that the fit between a task technology's nonroutineness and information-processing n...

Determinants of Disciplinary Practices in Low‐Income Black Mothers

Abstract: Disciplinary attitudes and practices of low-income black mothers were examined. Mothers were interviewed about their parenting attitudes and control practices, and their responses were coded in terms of the degree to which they took a parent- versus a child-oriented approach to discipline. Mothers in the sample varied widely in their attitudes toward physical punishment, and mothers who used power-assertive techniques were as likely to take the child's perspective and give input into the socialization process as those who did not. Factors associated with maternal disciplinary styles included: maternal education, father absence, maternal age, and self-reported religious beliefs. Findings are discussed in terms of the variability in disciplinary practices in this population, as well as the factors contributing to these individual differences.