The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices

In this paper, some chalcone derivatives (C1, C2) were synthesized based on the reaction of equal amount of substituted acetophenone and substituted banzaldehyde in basic medium. Oxazine and thiazine derivatives were prepared from the reaction of chalcones (C1-C2) with urea and thiourea respectively in a basic medium. Pyrazole derivatives were prepared based on the reaction of chalcones with hydrazine mono hydrate or phenyl hydrazine in the presence of glacial acetic acid as a catalyst. The new synthesized compounds were identified using various physical techniques like1 H-NMR and FT-IR spectra.

Herein, the interfacial polymerization method has been used for the synthesis of PPy/NaVO3 composites with different compositions of NaVO3 (10 %, 20 %, 30 %, 40 % and 50 %) as an efficient electrode material for supercapacitors. The successful formation and composition of the as-prepared composites (PV1-PV5) were confirmed by FTIR, XRD, EDX, and SEM analysis. The electrochemical properties were investigated by cyclic voltammetry (CV), galvanometric charge–discharge measurement (GCD), and electrochemical impedance spectroscopy (EIS) in 0.5 M H2SO4 electrolyte. As compared to other, the PV4 composite exhibit excellent specific capacitance of 391 F g−1 at a current density of 0.75 A/g with good cycling stability of ∼59 % after 1000 cycle

A novel azo dye ligand namely (2-(pyridin-3-yldiazenyl)naphthalen-1-ol (HPYNA), was synthesized by the coupling reaction of diazonium salt of 3-aminopyridine with naphthol. The palladium(II) complex for HPYNA ligand was prepared by reacting palladium(II) ions with the HPYNA ligand. These synthesized compounds were characterized using different techniques, including mass, 1H-NMR, infrared, and UV-Vis spectroscopy. The infrared results show that the azo ligand reacts as a bidentate via the oxygen atom of phenol and nitrogen atom of the azo group. The palladium(II) complex is square-planer with diamagnetic properties depending on the results of electronic transitions and magnetic sensitivity. The HPYNA ligand and palladium complex show

Transforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr