Mothers\u27 Health and Health Behaviors that Influence Childhod Obesity Maternal BMI and Infant Feeding Methods

The rate of childhood obesity in America continues to climb. Many medical experts believe that childhood obesity can develop as early as prenatal development in the uterus, and infancy. The purpose of this study is to explore the relationships between mothers\u27 health and health behaviors (maternal BMI and infant feeding methods) and childhood obesity. We conducted and analyzed a sample of 307 mothers and their children (307) to examine each mother\u27s maternal BMI and her child or children\u27s BMI. We also examined mothers\u27 feeding methods (bottle vs. breastfeeding).The result of this research did not match with the review of literature. Due to small sample size and limited age of children (0-6 months) in the sample, results were not significant. This study will be an important educational tool for health professions to encourage mothers in regard to maintain maternal healthy weight and promoting breast-feeding

Knowledge-sharing adoption in Saudi Universities' E-learning communities

Technology revolution in recent years has increased the demand for the provision of e-learning. However, academic staff lack the knowledge-sharing attitude in e-learning communities. The aim of this research is to investigate the various factors of knowledge-sharing adoption for e-learning communities in Saudi Arabia. Therefore, a framework aimed at sharing knowledge within the e-learning communities is developed. Data has been collected from public universities in Saudi Arabia. Partial Least Square approach has been applied to analyse the data. The results shows knowledge-sharing individual factors (such as openness in communication, interpersonal trust), technology acceptance factors (perceived usefulness and perceived ease of use) significantly influence knowledge-sharing attitude while the relationship between people self-motivation and knowledge-sharing attitude is insignificant. Among other factors, subjective norm and attitude significantly impact behavioural intention toward knowledgesharing adoption in Saudi universities' e-learning communities

Existence and stability of near-constant solutions of variable-coefficient scalar field equations

This article studies a class of semilinear scalar field equations on the real line with variable coefficients in the linear terms. These coefficients are not necessarily small perturbations of a constant. We prove that under suitable conditions, the non-translation-invariant linear operator leads to steady states that are ``almost constant'' in the spatial variable. The main challenge of the proof is due to a spectral obstruction that cannot be treated perturbatively. Next, we consider stability of constant and near-constant steady states. We establish asymptotic stability for the vacuum state with respect to perturbations in $H^1\times L^2$, without placing any parity assumptions on the coefficients, potential, or initial data. Finally, under a parity assumption, we show asymptotic stability for near-constant steady states.Comment: 25 pages, final accepted version. Previous title: "Asymptotic stability for near-constant solutions of variable-coefficient scalar field equations.

Populating contents of the Saudi eLearning objects repository 'Maknaz' from information technology & knowledge management perspective

© 2014 IEEE. E-Learning is an important tool for current learning and teaching processes. Learning Objects Repository (LOR) has been seen as a key factor in eLearning and knowledge management environment. Universities in Saudi Arabia have prioritized implementing eLearning in their development plans. However, current learning and teaching process in higher education in Saudi Arabia is still mostly traditional. Educational and information technologies adoption is slow due to the lack of awareness about the importance of collaborative learning that is mainly based on LORs knowledge and technical skills that educators and learners should have. There is a need to study the possible technical tools and approaches that can direct eLearning practices in Saudi Arabia to embrace the initiative of the Saudi National Learning Objects Repository 'Maknaz' in order to collaboratively populate and digitalize its knowledge contents. Due to the slow adoption of technologies and knowledge management systems in Saudi higher education, it is important to analyze the academics and students' acceptance toward current eLearning environment implemented so far. This paper investigates what efforts have been made so far to implement eLearning and LORs technologies in Saudi Arabia; and suggests what is required from participants in the higher educational institutions to link these technologies to education and pedagogy practices based on an integrated knowledge management system with eLearning to creatively create and exchange new knowledge localized in LORs

Impact of Knowledge Sharing Adoption on Universities' Virtual Learning Communities.

In new age, knowledge has become a significant source. Knowledge sharing is a substantial component of success in any organisation. In various organisations, knowledge sharing adoption is lacking, especially among academic staff working in Saudi universities. This paper investigates collectivism impact on knowledge-sharing factors among academics in Saudi e-learning communities. A conceptual model that will affect the knowledge sharing behaviour within the e-learning community in Saudi universities is proposed. Hypotheses have been accordingly developed. Data was collected in different Saudi public universities. Partial Least Square approach has been applied to analyse the data. The findings of this study provide key factors affecting the process of knowledge-sharing adoption between academic staff within the virtual learning communities in Saudi universities

Knowledge management and its impact on knowledge sharing adoption in e-learning communites in Saudi Universites

Knowledge sharing is a significant component of success in knowledge management. In most organisations, knowledge management is often lacking when it comes to knowledge sharing adoption, especially between academic staffs who work in Saudi universities. This paper investigates factors affecting knowledge-sharing adoption among academics in Saudi e-learning communities. A model that will affect the process of knowledge sharing within the e-learning community is proposed. Hypotheses have been developed. Data has been collected in Saudi public universities. Partial Least Square approach has been applied to analyse the data. The findings provide key factors affecting knowledge-sharing adoption among academic staff

Forecasting Congestion Severity for Smart City Traffic Management

The future of smart city traffic forecasting is two-way communication between residents and the city infrastructure. Today, Intelligent Transportation Systems (ITS) are essential tools for traffic planning, analysis, and forecasting, which use sensor data to forecast traffic. The emergence of crowdsourced traffic reporting using mobile applications is adding new layers of rich data that can be used to improve ITS systems. Resident mobile applications and sensors are reporting traffic congestions, incidents, accidents, and more. However, utilizing this data in city ITS or processes is not common. There are few studies on how to use and integrate this new layer of data to improve ITS systems and increase its capability. More importantly, the study proposed a model that helps the city to forecast traffic congestion in urban roadways and arterials were there are no traffic sensors. This study proposed several models based on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to forecast traffic severity without the need of traffic sensor data. The model used six months of Google/Waze traffic reports in the San Francisco Bay Area to forecast traffic congestions. The collected crowdsourced data included Waze incident reports, hourly weather, time, and location features. The model is designed to forecast hourly traffic congestion into five congestion levels. It included temporal and spatial dependencies learned using different types of layers. The proposed model will help city traffic engineers and planners forecast urban roadways and arterials traffic where there are no traffic sensors without the need to install one. This innovation will help reduce costs while improving ITS traffic forecasting. Moreover, future autonomous vehicles may also provide more details that can be used to improve traffic conditions