The efforts in designing and developing lightweight cryptography (LWC) started a decade ago. Many scholarly studies in literature report the enhancement of conventional cryptographic algorithms and the development of new algorithms. This significant number of studies resulted in the rise of many review studies on LWC in IoT. Due to the vast number of review studies on LWC in IoT, it is not known what the studies cover and how extensive the review studies are. Therefore, this article aimed to bridge the gap in the review studies by conducting a systematic scoping study. It analyzed the existing review articles on LWC in IoT to discover the extensiveness of the reviews and the topics covered. The results of the study suggested that many review studies are classified as overview-types of review focusing on generic LWC. Further, the topics of the reviews mainly focused on symmetric block cryptography, while limited reviews were found on asymmetric-key and hash in LWC. The outcomes of this study revealed that the reviews in LWC in IoT are still in their premature stage and researchers are encouraged to explore by conducting review studies in the less-attended areas. An extensive review of studies that cover these two topics is deemed necessary to establish a balance of scholarly works in LWC for IoT and encourage more empirical research in the area.
Back ground: In the present study Pinealoctomy
was used to study the sympathetic innervations of
the pineal gland by the superior cervical ganglion
(SCG) of the albino rat.
Objective: Following Pinealoctomy, it is
expected to observe the Chromatolysis reaction in
some neurons of the SCG if they were to innervate
the pineal gland (i.e. retrograde Chromatolysis
changes).
Methods: Fifty albino rats were used in this study,
Pinealoctomy was done, then after a different time
interval ganglionectomy was done, in order to
study the Chromatolysis in their cell body.
Result: The present study has demonstrated that
the most obvious Chromatolysis reaction in the
neurons which innervate the pineal gland a
Variable selection is an essential and necessary task in the statistical modeling field. Several studies have triedto develop and standardize the process of variable selection, but it isdifficultto do so. The first question a researcher needs to ask himself/herself what are the most significant variables that should be used to describe a given dataset’s response. In thispaper, a new method for variable selection using Gibbs sampler techniqueshas beendeveloped.First, the model is defined, and the posterior distributions for all the parameters are derived.The new variable selection methodis tested usingfour simulation datasets. The new approachiscompared with some existingtechniques: Ordinary Least Squared (OLS), Least Absolute Shrinkage
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... Show MoreThis paper presents an improved technique on Ant Colony Optimization (ACO) algorithm. The procedure is applied on Single Machine with Infinite Bus (SMIB) system with power system stabilizer (PSS) at three different loading regimes. The simulations are made by using MATLAB software. The results show that by using Improved Ant Colony Optimization (IACO) the system will give better performance with less number of iterations as it compared with a previous modification on ACO. In addition, the probability of selecting the arc depends on the best ant performance and the evaporation rate.
Abstract: Stars whose initial masses are between (0.89 - 8.0) M☉ go through an Asymptotic Giant Branch (AGB) phase at the end of their life. Which have been evolved from the main sequence phase through Asymptotic Giant Branch (AGB). The calculations were done by adopted Synthetic Model showed the following results: 1- Mass loss on the AGB phase consists of two phases for period (P <500) days and for (P>500) days; 2- the mass loss rate exponentially increases with the pulsation periods; 3- The expansion velocity VAGB for our stars are calculated according to the three assumptions; 4- the terminal velocity depends on several factors likes metallicity and luminosity. The calculations indicated that a super wind phase (S.W) developed on the A
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... Show MoreThe governmental projects are considers the prevailing in Iraq, as most of the projects implemented by the Government, the major role played by governmental projects in the provision of services to citizens and improve the economic situation in the country in general, in addition to the huge number of these projects implemented by the governmental organizations and the large failure rates of it , and because of the fact that these projects are stumbled before they reach the stage of failure, The aim of this research to identify the main factors for the stumble projects in addition to identifying the most influential factor on the causes and consequences of it , like (cost overruns , time overruns , delay and scope
... Show MoreIn the present study, composites were prepared by Hand lay-up molding and investigated. The composites constituents were epoxy resin as the matrix, 6% volume fractions of Glass Fibers (G.F) as reinforcement and 3%, 6% of industrial powder (Calcium Carbonate CaCO3, Potassium Carbonate K2CO3 and Sodium Carbonate Na2CO3) as filler. Density, water absorption, hardness test, flexural strength, shear stress measurements and tests were conducted to reveal their values for each type of composite material. The results showed that the non – reinforced epoxy have lower properties than composites material. Measured density results had show an incremental increase with volume fraction increase
... Show MoreThis paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n
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