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)

Background: Malignant lymphoma is a term that describes primary tumors of the lymphoreticular system, almost all of which arise from lymphocytes.MMP-1 is the most ubiquitously expressed interstitial collagenase, a subfamily of MMPs that cleaves stromal collagens. It is also called collagenase-1.TIMPs which inhibits MMP activity and thereby restrict extracellular matrix breakdown, TIMP-1 is a stromal factor that has a wide spectrum of functions in different tissues. Material and Methods: This study was performed on (68) formalin-fixed, paraffin-embedded blocks, histopathologically diagnosed as lymphoma (head and neck lesions). Immunohistochemical staining of MMP1and TIMP1 was performed on each case of the study sample. Results: The expressio

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

Objective: To evaluate male patients complaining of
urethritis clinically according to the isolated organisms.
Method: A total of 100 male patients attending to of
Dermatological and Venereal private clinics for the period
April 2003 to November 2003 were included in the study.
Urethral swab was obtained from each male for culture and
direct immunofluorescence examination was done.
Demographic data was obtained, also.
Results: N. gonorrhoea was the predominate cause of
infection in 22%. A peak of infection was reported in the
second decade of age. Highest rate reported among single
males. A significant association was noticed between
profuse discharge and infection with gonorrhoea.
Conclusion: This

Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

The two most popular models inwell-known count regression models are Poisson and negative binomial regression models. Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters. Negative binomial regression is similar to regular multiple regression except that the dependent (Y) variables an observed count that follows the negative binomial distribution. This research studies some factors affecting divorce using Poisson and negative binomial regression models. The factors are unemplo

This article aims to estimate the partially linear model by using two methods, which are the Wavelet and Kernel Smoothers. Simulation experiments are used to study the small sample behavior depending on different functions, sample sizes, and variances. Results explained that the wavelet smoother is the best depending on the mean average squares error criterion for all cases that used.