A novel design and implementation of a cognitive methodology for the on-line auto-tuning robust PID controller in a real heating system is presented in this paper. The aim of the proposed work is to construct a cognitive control methodology that gives optimal control signal to the heating system, which achieve the following objectives: fast and precise search efficiency in finding the on- line optimal PID controller parameters in order to find the optimal output temperature response for the heating system. The cognitive methodology (CM) consists of three engines: breeding engine based Routh-Hurwitz criterion stability, search engine based particle
swarm optimization (PSO) and aggregation knowledge engine based cultural algorithm (CA)

        Which was entitled : Aesthetic and dramatic dimensions of silence in the feature film , and the researcher clearly define after removing the confusion existing in some authorized sources , as for the concept of silence , adopted in this research is : the death of the audio stream , Hence the researcher shed a light on the aesthetic and the dramatic role of silence in the feature film , through the handing of the silent scenes ( absolute silence ) in the film research divided this research into four chapters . This first Chapter includes : methodological framework , which represents the research problem , which came with the following question : what is the mechanism of productive silence to the

Abstract Background: Dne of the key component of nasal tipplasty is effecter control of naral tip projection. Several cartilage grafts have been decreased for this purpose each had its own advantage and disadvantage. Aim: To evaluate using of double teostrut graft for controlling of tip projection. Patients and Methods: A total number of 170 patients were subjected to primary and secondary rhino plaster between January 2020 to January 2023. Those patients had double Teostrut banner graft for support of their nasal tip and maintaining tip projection after operation. Results: The follow period was ranging between 6-12 months. The shape of the nose was evaluating by patents vernal analogues scale. The average score for patients satisfaction wa

Simulation of direct current (DC) discharge plasma using
COMSOL Multiphysics software were used to study the uniformity
of deposition on anode from DC discharge sputtering using ring and
disc cathodes, then applied it experimentally to make comparison
between film thickness distribution with simulation results. Both
simulation and experimental results shows that the deposition using
copper ring cathode is more uniformity than disc cathode

ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

 

This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20