The important device in the Wireless Sensor Network (WSN) is the Sink Node (SN). That is used to store, collect and analyze data from every sensor node in the network. Thus the main role of SN in WSN makes it a big target for traffic analysis attack. Therefore, securing the SN position is a substantial issue. This study presents Security for Mobile Sink Node location using Dynamic Routing Protocol called (SMSNDRP), in order to increase complexity for adversary trying to discover mobile SN location. In addition to that, it minimizes network energy consumption. The proposed protocol which is applied on WSN framework consists of 50 nodes with static and mobile SN. The results havw shown in each round a dynamic change in the route to reach mobi

     This paper describes the application of consensus optimization for Wireless Sensor Network (WSN) system. Consensus algorithm is usually conducted within a certain number of iterations for a given graph topology. Nevertheless, the best Number of Iterations (NOI) to reach consensus is varied in accordance with any change in number of nodes or other parameters of . graph topology. As a result, a time consuming trial and error procedure will necessary be applied
to obtain best NOI. The implementation of an intellig ent optimization can effectively help to get the optimal NOI. The performance of the consensus algorithm has considerably been improved by the inclusion of Particle Swarm Optimization (PSO). As a case s

     MWCNTs-OH was used to prepare a flexible gas sensor by deposition as a network on a filter cake using the method of filtration from suspension (FFS). The morphological and structural properties of the MWCNTs network were characterized before and after exposure to Freon gas using FTIR spectra and X-ray diffractometer, which confirmed that the characteristics of the sensor did not change after exposure to the gas. The sensor was exposed to a pure Freon134a gas as well as to a mixture of Freon gas and air with different ratios at room temperature. The experiments showed that the sensor works at room temperature and the sensitivity values increased with increasing operating temperature, to be 58% unt

Tin dioxide (SnO2) were mixed with (TiO2 and CuO) with concentration ratio (50, 60, 70, 80 and 90) wt% films deposited on single crystal Si and glass substrates at (523 K) by spray pyrolysis technique from aqueous solutions containing tin (II) dichloride Dihydrate (SnCl2, 2H2O), dehydrate copper chloride (CuCl2.2H2O) and Titanium(III) chloride (TiCl3) with molarities (0.2 M). The results of electrical properties and analysis of gas sensing properties of films are presented in this report. Hall measurement showed that films were n-type converted to p- type as titanium and copper oxide added at (50) % ratio. The D.C conductivity measurements referred that there are two mechanisms responsible about the conductivity, hence it possess two act

Optical fibers were produced by the system manufactured for this purpose and then, PMMA core of polymer optical fiber (POF) and PMMA doped Rhodamine B (RhB) claddings were studied and determine their UV–vis absorption and emission. The study adopted the mechanism of lateral pumping of the product polymer optical fiber by using laser with 404 nm excitation to study optical specifications of the factory fiber. It was noted that there were blue shift in maximum peak wavelength in absorption and fluorescence from the doped polymer before use it as clad. The obtained results by using the doping polymer with (RhB) for clad the amplified spontaneous emission ASE seems in fluorescence study. The side excitation shows that there were no an over

Mobile Wireless sensor networks have acquired a great interest recently due to their capability to provide good solutions and low-priced in multiple fields. Internet of Things (IoT) connects different technologies such as sensing, communication, networking, and cloud computing. It can be used in monitoring, health care and smart cities. The most suitable infrastructure for IoT application is wireless sensor networks. One of the main defiance of WSNs is the power limitation of the sensor node. Clustering model is an actual way to eliminate the inspired power during the transmission of the sensed data to a central point called a Base Station (BS). In this paper, efficient clustering protocols are offered to prolong network lifetime. A kern

      The features of plasmonic surface frequency sensor technology, such as the small number of sensor samples required, electromagnetic interference, and high sensitivity, have been found to be highly important.. In this paper, a simulation program was created in Matlab_b2018 by adopting Fresnel equations for calculating the reflectivity of the electromagnetic wave between different media. A surface plasmon resonance sensor based on electromagnetic wavelengths within the range (100 nm to 1000 nm) has been proposed. The transfer matrix was used for a system consisting of four different media. The first medium is a semicircular BK7 glass prism, the second medium is a gold layer (40 nm thick), then a bismuth layer of variable thickne

Ultrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T