A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

Knowledge of the distribution of the rock mechanical properties along the depth of the wells is an important task for many applications related to reservoir geomechanics. Such these applications are wellbore stability analysis, hydraulic fracturing, reservoir compaction and subsidence, sand production, and fault reactivation. A major challenge with determining the rock mechanical properties is that they are not directly measured at the wellbore. They can be only sampled at well location using rock testing. Furthermore, the core analysis provides discrete data measurements for specific depth as well as it is often available only for a few wells in a field of interest. This study presents a methodology to generate synthetic-geomechani

     Despite their long successful use, synthetic dyes have several problems due to their carcinogenic and toxic effects. Besides providing bright colors, some natural pigments have shown notable antimicrobial activity; thus, they could be utilized as functional dyes in many applications such as making colored antimicrobial textiles. In this work, a yellow pigment produced by Streptomyces thinghirensis AF7 and has a notable antimicrobial activity was used to produce a colored antimicrobial textile. The extracted yellow pigment was subjected to a purification step using silica gel column eluted with di ethyl ether solvent. The FTIR, GC-MS and NMR analysis showed that the colorings in this type of product are due to t

     The mineralogical study using X-ray diffraction (XRD) supported by scanning electron microscopic (SEM) examination and energy-dispersive spectroscopy (EDS) on the claystone of the Kolosh Formation from northern Iraq was conducted to Shows the provenance history of rocks. Chlorite, montmorillonite, illite, palygorskite, and kaolinite were recorded in different amounts in the study area. The association of montmorillonite and chlorite in the claystone of the Kolosh Formation (Paleocene) refers to the marine environment. Chlorite and montmorillonite are the common minerals in the Kolosh Formation with less common of illite, kaolinite and palygorskite. These clay minerals are of authigenic, detrital and diagenetically origin, which

We are used Bayes estimators for unknown scale parameter  when shape Parameter  is known of Erlang distribution. Assuming different informative priors for unknown scale  parameter. We derived The posterior density with posterior mean and posterior variance using different informative priors for unknown scale parameter  which are the inverse exponential distribution, the inverse chi-square distribution, the inverse Gamma distribution, and the standard Levy distribution as prior. And we derived Bayes estimators based on the general entropy loss function (GELF) is used the Simulation method to obtain the results. we generated different cases for the parameters of the Erlang model, for different sample sizes. The estimates have been comp

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob