More than 95% of the industrial controllers in use today are PID or modified PID controllers. However, the PID is manually tuning to be responsive so that the Process Variable is rapidly and steady moved to track the set point with minimize overshoot and stable output. The paper presents generic teal-time PID controller architecture. The developed architecture is based on the adaption of each of the three controller parameters (PID) to be self- learning using individual least mean square algorithm (LMS). The adaptive PID is verified and compared with the classical PID. The rapid realization of the adaptive PID architecture allows the readily fabrication into a hardware version either ASIC or reconfigurable.

The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

The purpose of this research is to find the estimator of the average proportion of defectives based on attribute samples. That have been curtailed either with rejection of a lot finding the kth defective or with acceptance on finding the kth non defective.

The MLE (Maximum likelihood estimator) is derived. And also the ASN in Single Curtailed Sampling has been derived and we obtain a simplified Formula All the Notations needed are explained.

The nanostructured MnO2 /carbon fiber (CF) composite electrode was prepared using the anodic electrodeposition process. The crystal structure and morphology of MnO2 particles were determined with X-ray diffraction and field-emission scanning electron microscopy. The electrosorptive properties of the prepared electrode were investigated in the removal of cadmium ions from aqueous solution, and the effect of pH, cell voltage, and ionic strength was optimized and modeled using the response surface methodology combined with Box–Behnken design. The results confirm that the optimum conditions to remove Cd(II) ions were: pH of 6.03, a voltage of 2.77 V, and NaCl concentration of 3 g/L. The experimental results showed a good fit for the Freundli

The present work aims to study the effect of using an automatic thresholding technique to convert the features edges of the images to binary images in order to split the object from its background, where the features edges of the sampled images obtained from first-order edge detection operators (Roberts, Prewitt and Sobel) and second-order edge detection operators (Laplacian operators). The optimum automatic threshold are calculated using fast Otsu method. The study is applied on a personal image (Roben) and a satellite image to study the compatibility of this procedure with two different kinds of images. The obtained results are discussed.

In this study, chemical oxidation was employed for the synthesis of polypyrrole (PPy) nanofiber. Furthermore, PPy has been subjected to treatment using nanoparticles of neodymium oxide (Nd2O3), which were produced and added in a certain ratio. The inquiry centered on the structural characteristics of the blend of polypyrrole and neodymium oxide after their combination. The investigation utilises X-ray diffraction (XRD), FTIR, and Field Emission Scanning Electron Microscopy (FE-SEM) for PPy, 10%, 30%, and 50% by volume of Nd2O3. According to the electrochemical tests, it has been noted that the nanocomposites exhibit a substantial amount of pseudocapacitive activity.

In order to save natural resources, recycling necessarily becomes a top priority for all of us, to save exhaustible resources, produce green energy and preserve the environment.
In this perspective, we are trying to valorize a waste of animal origin, largely neglected by the actors of materials, through an industrial transformation into a biological charge to make new sustainable bio-composite materials.
Using a tensile test bench, we try to mechanically characterize this biomaterial of renewable resources that, unlike eco-composites, has been neglected by the material actors.
Obtained from waste, with a high recycling potential and from renewable resources, the bio-charge to be analyzed will be injected, later in different poly