The design and implementation of an active router architecture that enables flexible network programmability based on so-called "user components" will be presents. This active router is designed to provide maximum flexibility for the development of future network functionality and services. The designed router concentrated mainly on the use of Windows Operating System, enhancing the Active Network Encapsulating Protocol (ANEP). Enhancing ANEP gains a service composition scheme which enables flexible programmability through integration of user components into the router's data path. Also an extended program that creates and then injects data packets into the network stack of the testing machine will be proposed, we will call this program

Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

Socio-scientific issues provide a great platform to both engage students in scientific topics and assess their understanding of scientific concepts. Nancy R. Singer, Amy Lannin, Maha Kareem, William Romine, and Katie Kline report on the STEM Literacy Project, a three-year National Science Foundation grant that aimed to improve STEM teachers’ knowledge and integration of literacy in their classrooms. They describe teachers’ professional learning, scenario-based assessments and other strategies they incorporated in their STEM classrooms, and how writing enables students to understand real-world issues.

The security of message information has drawn more attention nowadays, so; cryptography has been used extensively. This research aims to generate secured cipher keys from retina information to increase the level of security. The proposed technique utilizes cryptography based on retina information. The main contribution is the original procedure used to generate three types of keys in one system from the retina vessel's end position and improve the technique of three systems, each with one key. The distances between the center of the diagonals of the retina image and the retina vessel's end (diagonal center-end (DCE)) represent the first key. The distances between the center of the radius of the retina and the retina vessel's end (ra

Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

In this study, nickel cobaltite (NC) nanoparticles were created using the sol-gel process and used as an adsorbent to adsorb methyl green dye (MG) from aqueous solutions. The adequate preparation of nickel cobaltite nanoparticles was verified using FT-IR, SEM, and X-ray diffraction (XRD) studies. The crystalline particle size of NC nanoparticles was 10.53 nm. The effects of a number of experimental variables, such as temperature, adsorbent dosage, and contact time, were examined. The optimal contact time and adsorbent dosage were 120 minutes and 4.5 mg/L, respectively. Four kinetic models—an intraparticle diffusion, a pseudo-first-order equation, a pseudo-second-order equation, and the Boyd equation—were employed to monitor the adsorpti

Corrosion of steel reinforcement is one of the biggest problems facing all countries in the world like bridges in the beach area and marine constructions which lead to study these problems and apply some economical solutions. According to the high cost of repair for these constructions, were studied the effect of using kind of chemical compounds sodium nitrite(NaNO₂) and sodium silicate(Na₂SiO₃) as corrosion inhibitors admixture for steel bars that immersed partially in electrolyte solution (water + sodium chloride in 3% conc.) (Approximately similar to the concentration of salt in sea water). The two inhibitors above added each one to the electrolyte solution at concentrations (0.5%, 1% and 2%) for both

Background. Implant insertion in regions with poor bone quantity, such as the posterior maxilla, is potentially associated with an increased rate of implant failure. Calcium sulfate can be used as the coating material for commercially pure titanium (CpTi) and as the bone graft material around implants when bound to eggshell powder to enhance the bone quality and quantity of bone defect regions. This study performed a torque removal test to evaluate the effectiveness of eggshell powder as a bone substitute for filling bone defects around CpTi-coated implants coated with nanocrystalline calcium sulfate. Materials and Methods. Eighty screw implant designs were used in the tibiae of 20 white New Zealand rabbits. A total of uncoated 20 s

Today's smart engineering systems are often faced with situations that are structurally uncertain, informationally incomplete, and non-probabilistically ambiguous, especially for electrical systems. ARDL models are limited in applications in complex computational environments where the uncertainty is due to vagueness, not randomness, and assume the exact parametric representation of the models and the structure of the stochastic uncertainty. This study proposes a new soft-computing paradigm using Fuzzy Autoregressive Distributed Lag (FARDL) models and compares the performance of the Linear Programming (LP) and Quadratic Programming (QP) estimation algorithms using large-scale parallel Monte Carlo simulations to overcome these drawba