The main objective of this work is to propose a new routing protocol for wireless sensor network employed to serve IoT systems. The routing protocol has to adapt with different requirements in order to enhance the performance of IoT applications. The link quality, node depth and energy are used as metrics to make routing decisions. Comparison with other protocols is essential to show the improvements achieved by this work, thus protocols designed to serve the same purpose such as AODV, REL and LABILE are chosen to compare the proposed routing protocol with. To add integrative and holistic, some of important features are added and tested such as actuating and mobility. These features are greatly required by some of IoT applications and improving the routing protocol to support them makes it more suitable for IoT systems.
The proposed routing protocol is simulated using Castalia-3.2 and all the cases are examined to show the enhancement that achieved by each case. The proposed routing protocol shows better performance than other protocols do regarding Packet Delivery Ratio (PDR) and latency. It preserves network reliability since it does not generate routing or data packets needlessly. Routing protocol with added features (actuating and mobility) shows good performance. But that performance is affected by increasing the speed of mobile nodes.
Background: Angiogenesis is defined as the formation of new blood vessels. However, angiogenesis in cancer will lead to tumour growth and metastasis. Therefore, anti-angiogenesis is one of the ways to slow down growth and spreading of tumour. Moringa oleifera is also known as a “Miracle tree” which has high nutritive value and various therapeutics effect in different parts of the plant. This study aims to determine the anti-angiogenic property of Moringa oleifera leaves extract by using chick chorioallantoic membrane (CAM) assay. Materials and Methods: The extracts were prepared by decoction method using methanol and water. The qualitative phytochemical screening was carried out for
... Show MoreAtorvastatin (ATR) is poorly soluble anti-hyperlipidemic drug; it belongs to the class II group according to the biopharmaceutical classification system (BCS) with low bioavailability due to its low solubility. Solid dispersions adsorbate is an effective technique for enhancing the solubility and dissolution of poorly soluble drugs.
The present study aims to enhance the solubility and dissolution rate of ATR using solid dispersion adsorption technique in comparison with ordinary solid dispersion. polyethylene glycol 4000 (PEG 4000), polyethylene glycol 6000 (PEG 6000), Poloxamer188 and Poloxam
... Show MoreIn this paper, we build a fuzzy classification system for classifying the nutritional status of children under 5 years old in Iraq using the Mamdani method based on input variables such as weight and height to determine the nutritional status of the child. Also, Classifying the nutritional status faces a difficult challenge in the medical field due to uncertainty and ambiguity in the variables and attributes that determine the categories of nutritional status for children, which are relied upon in medical diagnosis to determine the types of malnutrition problems and identify the categories or groups suffering from malnutrition to determine the risks faced by each group or category of children. Malnutrition in children is one of the most
... Show MoreAlthough the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t
... Show More<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121
... Show MoreThis research aims at identifying the communicative habits and content reflections on the communication process, especially the young audience which is one of the main group for whom the announcements are made. Because young people face life with passion and aspiration making them respond to each effect used by the media in the design of the advertising using all the effective techniques, attractive methods for young children like depending on drama, technical tricks, music and logos easily to be remembered and responded to the desires of the young in their entertainment. This research also aims at identifying the impact of the internet as a channel of commercial advertising on the purchasing behavior of young people at the universities
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In this work, the modified Lyapunov-Schmidt reduction is used to find a nonlinear Ritz approximation of Fredholm functional defined by the nonhomogeneous Camassa-Holm equation and Benjamin-Bona-Mahony. We introduced the modified Lyapunov-Schmidt reduction for nonhomogeneous problems when the dimension of the null space is equal to two. The nonlinear Ritz approximation for the nonhomogeneous Camassa-Holm equation has been found as a function of codimension twenty-four.
A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga
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