The Degree of Availability of the Standards of the National Framework for Academic Qualifications in Early Childhood in Jordan from the Point of View of female teachers

The current study aimed to identify the most important Standards of the National Framework for Academic Qualifications (SNFAQ) in the Early Childhood Stage in Jordan. The study adopted a descriptive approach to achieve the aim of the study. Further, established a questionnaire for the degree of availability of the criteria for the SNFAQ in early childhood in Jordan. As the final form, the questionnaire consisted of three dimensions and (65) items. The current study sample consisted of 135 kindergarten teachers in the private and public sectors in Amman city. The study results showed that the degree of availability of the SNFAQ in early childhood curricula in Jordan came with a medium degree, with a mean (2.82) and a standard deviation (0.61). Moreover, attributed no statistically significant differences in the degree of availability of the SNFAQ in the early childhood stage in Jordan to kindergarten type and experience. Furthermore, statistically significant differences in the degree of availability of the SNFAQ in Early Childhood in Jordan due to academic qualification and favouring those with postgraduate qualifications. Finally, a set of recommendations were made in light of the results of the study, including Increasing the interest of officials in the Ministry of Education, including leaders of kindergartens, about the importance of the SNFAQ, identifying an executive body to follow up on the inclusion of standards, and conducting studies similar to the current study on kindergarten departments in Jordanian universities. Keywords

Investigation and improvment of noise, vibration and harshness(nvh) properties of automotive panels

ABSTRACT INVESTIGATION AND IMPROVEMENT OF NOISE, VIBRATION AND HARSHNESS (NVH) PROPERTIES OF AUTOMOTIVE PANELS by MOHAMMAD AL-ZUBI July 2012 Advisor: Dr. Emmanuel Ayorinde Major: Mechanical Engineering Degree: Doctor of Philosophy The reduction of noise and vibration in and across several components and modules of the automotive, such as the panels, doors, engine covers, seats, and others, is of primary importance. The NVH performance may be a crucial factor in the purchase decisions of numerous buyers. This work investigates through experimental, analytical and computational methods, six groups of sample materials - fabric, foam, honeycomb, monolithic and sandwich, periodic cellular material structures (PCMS), and generally periodic materials, to assess their suitability for maximum containment of noise and vibration. Various architectural forms have also been considered. State-of-the art instrumentation and adequate analytical and computational methods have been utilized. Five major novel accomplishments have been logged in the work. Vibro-acoustic responses of PCMS materials, and newly-constructed generally periodic materials are explored, and some computer procedures are generated. The results give some suggestions for design directions to follow in order to achieve better performances

The Effectiveness of Cognitive Behavioral Training Program in Reducing the Risk of Diabetes among University Students

This study aimed to build cognitive training program of diabetes prevention of students who have risk elements of diabetes. The sample of the study which consisted of (26) university students was chosen regarding their results of the  accumulative average of sugar in addition to their obesity indicator ,  glucose  and  cholesterol  percent in blood . The sample of the study was divided into two experimental and control groups. The training program which consisted of (16) training sessions based on the cognitive behavioral theory. The results of the study showed that there were statistically significant differences between the two groups in risk elements of diabetes in favor of the experimental group, which its weight and sugar and glucose level in blood decreased.  The study concluded that the training program that based on the cognitive behavioral theory was effective in reducing the experimental risk elements of diabetes. In addition, the study recommended carrying out further studies, which care of the guided and training programs of diabetics in different categories of age. Keywords: training program, diabetes, risk elements

Mathematical and Stochastic Modelling of Molecular Communication Systems for Advanced Drug Delivery Applications

University of Technology Sydney. Faculty of Engineering and Information Technology.Molecular communication (MC) is an emerging nanoscale communication paradigm, biologically inspired by the cellular communications via biochemical molecules in the living organisms. The MC paradigm is highly suitable for modelling and abstraction of the underlying complex processes in the drug delivery systems (DDSs) over wide spatiotemporal scales. Targeted and implantable DDSs are advanced and engineered technologies for effective delivery of anticancer drugs to the cancerous tumors without affecting other healthy parts in the body. This approach offers an efficient alternative or adjunctive therapy to other treatment techniques, such as conventional chemotherapy, thermal ablation, and surgical resection. In-Silico (mathematical and stochastic) models are key tools to understand and quantify the various parameters and processes in the DDSs, including drug transport, release processes, reaction, and other physicochemical interaction processes in the biological microenvironments inside the body. These models play an essential role in the design and development of the DDSs which in order can reduce the animal experiments and can save time and reduce cost. The focus of my Ph.D. research is to develop novel mathematical and stochastic simulation models using MC paradigm for localized targeted and implantable DDSs over nano- and micrometer scales in complex biological microenvironments. Using the MC paradigm, the drug delivery process is abstracted as a communication mechanism where the drug source acts as a transmitter while the target site (e.g., cancer cell) acts as a receiver and the biological environment through which the molecules get transported acts as a propagation channel. The anticancer drug molecules represent the information carriers that contain the physicochemical properties of the drug. We use system analysis approach using the channel impulse response (CIR) coupled with the signal processing technique (convolution) for modelling the targeted and implantable DDSs in tumor microenvironments (TME). This approach provides more general and flexible models compared to other modelling approaches. The thesis made original contributions in the following four major aspects: (1) Generalized mathematical and stochastic simulation models are developed for diffusion-based molecular communications (MC) in complex fluidic microenvironments that include multilayered physical structures, ligand-receptor reaction, anisotropic diffusion, and the effect of reactive obstacles. These generalized models are developed for modelling and design of both the targeted drug delivery systems (TDDS) as well as the molecular communication systems between bio-nanomachines or cells in such complex environments over microscopic scale. (2) The proposed multilayer MC models have been extended for modelling the intravascular TDDS including anticancer drug release from the nanocarriers (NCs) and drug transport across the endothelial barrier of the tumor vasculature in tumor microenvironments. (3) Novel mathematical and stochastic simulation models are developed for modelling the implantable drug delivery system (IDDS) in tumor by predicting and characterizing the release process and drug distribution in the surrounding tumor tissue. (4) Pharmacokinetic /Pharmacodynamics models are developed for modelling the combination therapy using local implantable drug delivery systems in solid tumors following thermal ablation therapy

Solution for intra/inter-cluster event-reporting problem in cluster-based protocols for wireless sensor networks

In recent years, wireless sensor networks (WSNs) have been considered one of the important topics for researchers due to their wide applications in our life. Several researches have been conducted to improve WSNs performance and solve their issues. One of these issues is the energy limitation in WSNs since the source of energy in most WSNs is the battery. Accordingly, various protocols and techniques have been proposed with the intention of reducing power consumption of WSNs and lengthen their lifetime. Cluster-oriented routing protocols are one of the most effective categories of these protocols. In this article, we consider a major issue affecting the performance of this category of protocols, which we call the intra/inter-cluster event-reporting problem (IICERP). We demonstrate that IICERP severely reduces the performance of a cluster-oriented routing protocol, so we suggest an effective Solution for IICERP (SIICERP). To assess SIICERP’s performance, comprehensive simulations were performed to demonstrate the performance of several cluster-oriented protocols without and with SIICERP. Simulation results revealed that SIICERP substantially increases the performance of cluster-oriented routing protocols

Experimental and Numerical Analysis of Membrane-Patterned Meta-Materials

ABSTRACT Meta-materials show unconventional properties by virtue of their construction which normally includes physicallyperiodic formations. Various responses of these materials manifest frequencydependent occurrences of significantlyenhanced and significantly-attenuated values, thus facilitating a wealth of design possibilities. The analysis of these structures presents non-trivial challenges, hence only very simple types are presently under analytical study. In this paper, a formation which includes patterned membrane fillings is explored experimentally and numerically to see if and how well such a construction may be utilized for metamaterial applications. AKIF DUNDAR Advanced Composites an

Prediction of rockfill materials’ shear strength using various kernel function-based regression models—a comparative perspective

The mechanical behavior of the rockfill materials (RFMs) used in a dam’s shell must be evaluated for the safe and cost-effective design of embankment dams. However, the characterization of RFMs with specific reference to shear strength is challenging and costly, as the materials may contain particles larger than 500 mm in diameter. This study explores the potential of various kernel function-based Gaussian process regression (GPR) models to predict the shear strength of RFMs. A total of 165 datasets compiled from the literature were selected to train and test the proposed models. Comparing the developed models based on the GPR method shows that the superlative model was the Pearson universal kernel (PUK) model with an R-squared (R2 ) of 0.9806, a correlation coefficient (r) of 0.9903, a mean absolute error (MAE) of 0.0646 MPa, a root mean square error (RMSE) of 0.0965 MPa, a relative absolute error (RAE) of 13.0776%, and a root relative squared error (RRSE) of 14.6311% in the training phase, while it performed equally well in the testing phase, with R2 = 0.9455, r = 0.9724, MAE = 0.1048 MPa, RMSE = 0.1443 MPa, RAE = 21.8554%, and RRSE = 23.6865%. The prediction results of the GPR-PUK model are found to be more accurate and are in good agreement with the actual shear strength of RFMs, thus verifying the feasibility and effectiveness of the model

Conversion of lignocellulose biomass to bioenergy through nanobiotechnology

The growing global demand for energy, particularly petroleum-based fuels, has stimulated a long-term quest for an optimal source of sustainable energy. This barrier is removed by lignocellulosic biomass, which is an economical, easily accessible, and renewable fuel source that fits sustainability standards. However, large-scale use of most of the techniques results in significant handling costs and decontamination of the inhibitors released. Taken together, these limits increase the efficacy of present solutions and create a need for the development of a novel, environmentally sustainable, productive, and cost-effective technology for lignocellulose biomass conversion. In this context, the use of nanotechnology in the treatment of lignocellulose biomass to bioenergy exchange has gained significant attention and has been extensively researched in recent years. This review discussed how nanotechnology can be used to turn biomass into energy. It gives new ideas and tools for developing new industries, which will help the economy, grow in the long run. This careful examination will also shed light on some of the minor details surrounding the different ways of biomass conversion previously explored by other experts