Smart cities have recently undergone a fundamental evolution that has greatly increased their potentials. In reality, recent advances in the Internet of Things (IoT) have created new opportunities by solving a number of critical issues that are allowing innovations for smart cities as well as the creation and computerization of cutting-edge services and applications for the many city partners. In order to further the development of smart cities toward compelling sharing and connection, this study will explore the information innovation in smart cities in light of the Internet of Things (IoT) and cloud computing (CC). IoT data is first collected in the context of smart cities. The data that is gathered is uniform. The Internet of Things,

The inhibitive effect of imidazol on the dissolution of Zn in (1M) HCl has been studied. The inhibion effect of imidazol ,protection efficiency and the corrosion rate of Zn in (1M) HCl were investigated at various concentrations (1x 10-3 – 5x10-3) M and tempearture range (285-328) K. The corrosion inhibitive of Zn by imidazol was studied using weight loss measurement and analytical titration of the amounts of dissolved zinc in acidic solution in presence and absent of imidazol. It was observed that imidazol led to protection efficiency reached to (88.93)% when (10)mM imidazol concentration was used. A linear relationship came true between (C/?) and (C); where (?) is the coverage of Zn surface by imidazol which could be obtained from

There is a correlation between the occurrence of anxiety and the production of inflammatory mediators, and red ginger rhizome is a well-known herbal product with a high content of phenolic and flavonoid compounds that can be used as anti-inflammatories and antioxidants. The aim of study to evaluate the effect of red ginger as antianxiety in mice (Mus musculus) BALB/c strain by measuring levels of TNF-α, IL-6 and IL-10.  Anxiety model mice were carried out by giving treatment with the Forced Swimming Test (FST) for 7 days then assessed by carrying out the Elevated Plus Maze for Mice (EPM) test for one day. After the treatment, the anxiety mice model was made, followed by administration of red ginger ethanol extract therapy for 14 days.

In this work Study effect of annealing temperature on the Structure
of a-Se and electrical properties of a-Se/c-Si hetrojunction have been
studied.The hetrojunction fabricated by deposition of a-Se film on c-
Si using thermal evaporation.
Electrical properties of a-Se/ c-Si heterojunction include I-V
characteristics, in dark at different annealing temperature and C-V
characteristics are considered in the present work.
C-V characteristics suggested that the fabricated diode was
abrupt type, built in potential determined by extrapolation from
1/C2-V curve. The built - in potential (Vbi) for the Se/ Si System
was found to be increase from 1.21 to 1.62eV with increasing of
annealing temperature

This 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

The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlatio

Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

Experimental investigations had been done in this research to demonstrate the effect of carbon fiber and Ceramic fillers contents on the tribological behaviour of (15% volume fraction) carbon-epoxy composite system under varying volume fraction, load, time and sliding distance. The wear resistance were investigated according to ASTM G99-05standard using pin on disc machine to present the composite tribological behaviour. The influence of three ceramic fillers, granite, perlite and calcium carbonate (CaCO₃), on the wear of the carbon fabric reinforced epoxy composites under dry sliding conditions has been investigated. The effect of variants in volume fraction, applied load, time and sliding distance on the wear behaviour of po