Trickle irrigation is one of the most conservative irrigation techniques since it implies supplying water directly on the soil through emitters. Emitters dissipate energy of water at the end of the trickle irrigation system and provide water at emission points. The area wetted by an emitter depends upon the discharge of emitter, soil texture, initial soil water content, and soil permeability. The objectives of this research were to predict water distribution profiles through different soils for different conditions and quantify the distribution profiles in terms of main characteristics of soil and emitter. The wetting patterns were simulated at the end of each hour for a total time of application of 12 hrs, emitter disch

Among the available chaotic modulation schemes, differential chaos shift keying (DSCK) offers the perfect noise performance. The power consumption of DCSK is high since it sends chaotic signal in both of 1 and 0 transmission, so it does not represent the optimal choice for some applications like indoor wireless sensing where power consumption is a critical issue. In this paper a novel noncoherent chaotic communication scheme called differential chaos on-off keying (DCOOK) is proposed as a solution of this problem. With the proposed scheme, the DCOOK signal have a structure similar to chaos on-off keying (COOK) scheme with improved performance in noisy and multipath channels by introducing the concept of differential coherency used in DCS

The CdS quantum dots were prepared by chemical reaction
of cadmium oleylamine (Cd –oleylamine complex) with the
sulfite-oleylamine (S-oleylamine) with 1:6 mole ratios. The
optical properties structure and spectroscopy of the product
quantum dot were studied. The results show the dependence of the
optical properties on the crystal dimension and the formation of
the trap states in the energy band gap.

Objective: To determine the effectiveness of a dietary educational program upon the hypertensive client’s
information.
Methodology: The sample of the study consists of (60) hypertensive clients who attended Al Anbar Health Office –Al
Andalus Health Center during the period of the study from the14th of March 2010 to the 30th of September 2010. The
sample is divided into two groups; study group (30) hypertensive clients who received dietary educational program
and control group (30) hypertensive clients who received a routine care from the center. Three major instruments
were used; these instruments included (1) knowledge test which was applied on both groups pretest and eight weeks
post-test (2) questions to know

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime

Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal

Increasing requests for modified and personalized pharmaceutics and medical materials makes the implementation of additive manufacturing increased rapidly in recent years. 3D printing has been involved numerous advantages in case of reduction in waste, flexibility in the design, and minimizing the high cost of intended products for bulk production of. Several of 3D printing technologies have been developed to fabricate novel solid dosage forms, including selective laser sintering, binder deposition, stereolithography, inkjet printing, extrusion-based printing, and fused deposition modeling. The selection of 3D printing techniques depends on their compatibility with the printed drug products. This review intent to provide a perspecti