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.

The aim of this study was to Identifying The Effect of using Linear programming and Branching programming by computer in Learning and Retention of movement concatenation(Linkwork) in parallel bars in Artistic Gymnastics. The searchers have used the experimental method. The search subject of this article has been taken (30) male - students in the second class from the College of Physical Education/University of Baghdad divided into three groups; the first group applied linear programming by computer, and the second group has been applicated branching programming by computer, while precision group used traditional method in the college. The researchers concluded the results by using the statistical bag for social sciences (spss) such as both

     There is poverty because of the difference in capacity and material resources, Previously poverty known on the basis of disparity between income and inadequate income. It realize later that fare wore effects of poverty is the erosion of human capital. The human poverty is the loss of food, education, health care and shelter.

     In order to provide a database that target the poor  , it have been propped a document on the features of poverty and the whereabouts of the poor and the rate of disparity between provinces.

    Here the goal of the research is the identify the factors affecti

The taxonomy of Ficus L., 1753 species is confusing because of the intense morphological variability and the ambiguity of the taxa. This study handled 36 macro-morphological characteristics to clarify the taxonomic identity of the taxa. The study revealed that Ficus is represented in the Egyptian gardens with forty-one taxa; 33 species, 4 subspecies and 4 varieties, and classified into five subgenera: Ficus Corner, 1960; Terega Raf., 1838; Sycomorus Raf., 1838; Synoecia (Miq.) Miq., 1867, and Spherosuke Raf.,1838; out of them seven were misidentified. Amongst, four new Ficus taxa were recently introduced to Egypt namely: F. lingua subsp. lingua Warb. ex De Wild. & T. Durand, 1901; F. pumila L., 1753; F. rumphii Blume, 1825, and F. su

The development of Web 2.0 has improved people's ability to share their opinions. These opinions serve as an important piece of knowledge for other reviewers. To figure out what the opinions is all about, an automatic system of analysis is needed. Aspect-based sentiment analysis is the most important research topic conducted to extract reviewers-opinions about certain attribute, for instance opinion-target (aspect). In aspect-based tasks, the identification of the implicit aspect such as aspects implicitly implied in a review, is the most challenging task to accomplish. However, this paper strives to identify the implicit aspects based on hierarchical algorithm incorporated with common-sense knowledge by means of dimensionality reduction.

This study examines the transformation of political slogans, clichés, and stereotypes in Russia and Iraq during periods of political regime change in the late 20th and early 21st centuries. The main objective of the work is to identify and comparatively analyze the linguistic and cultural changes that accompanied political transformations in both countries. The research is based on theoretical concepts of political myth, framing, and critical discourse analysis. The research methodology includes content analysis of political texts, comparative analysis of linguistic transformations, and analysis of statistical data on cultural consumption. The main hypothesis is that, despite the presence of common trends in linguistic and cultural

Conversation analysis has long been the concern of many linguists who work in the field of discourse analysis. In spite of the fact that there are many researches have been done in the field of short stories but up to the researcher knowledge the investigation of the selected short stories has not been studied yet. Hence, this paper aims at answering the following questions: what are the features of children’s short stories language and the differences between short stories of four years old and those of six years old.  Hence, the devices used by the story tellers in reciting the short stories should be observed. Thus, the researcher has consulted the models presented by Johnson and Fillmore (2010) to show tenses and sentence str

This research provides a new method to study praise poetry that can be used as a course to teach English and Arabic to students in the College of Education. This research answers two questions: Is it possible to examine praise poetry as a tagmeme? Is this analysis of great help in teaching English and Arabic to students in the College of Education? The data that will be chosen for the purpose of analysis are two of Shakespeare's sonnets and two of AL Mulik's poems. The sonnets selected for this purpose are 17 and 18. AL Mulik's poems selected for the same purpose are 8 and 9. Each line in both English and Arabic data is numbered by the researcher herself. Then, those lines are grouped into sentences to facilitat

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