Earth’s climate changes rapidly due to the increases in human demands and rapid economic growth. These changes will affect the entire biosphere, mostly in negative ways. Predicting future changes will put us in a better position to minimize their catastrophic effects and to understand how humans can cope with the new changes beforehand. In this research, previous global climate data set observations from 1961-1990 have been used to predict the future climate change scenario for 2010-2039. The data were processed with Idrisi Andes software and the final Köppen-Geiger map was created with ArcGIS software. Based on Köppen climate classification, it was found that areas of Equator, Arid Steppes, and Snow will decrease by 3.9 %, 2.96%, an

Form naming system Simiaúaa can not be studied in isolation from the dimensionality of social and psychological , no doubt that names carry data psyche during social interaction , deflagration volunteered her body signifier in formats that meet the margin emotional part of the signified , Vtngams forms functions in coordinated trading to function as semantic double , it operates on coding , as well as carry emotional charge .
The science of semiotics cares Pettmvsal indications and forms of circulation, and is made form the semantic patterns , and pattern of production , and methods of functioning . Stop quite a few specialists and critics and researchers at Dalia ignorant poet and knight known ( Duraid bin embolism Jashmi ) ; it rep

         Vocational education is the basis of contemporary educational movement that aims at satisfying human needs. Societies can develop their human resources via setting programs for the working class as an aspect of the comprehensive national development. Vocational education is the main source of technical cadres the Iraqi labor market requires of the vocational preparatory schools to provide after three years of schooling.

        The vocational schools of the governorate of Basra have a number of problems that lead to the lack of proficiency of their graduates. This study is an attempt to identify these problems or obstacles

Objectivity is the common denominator between the qualities and elements of a news story that is described as the mother of journalistic arts. When there is doubt about the authenticity of the information contained in the press, whether readable, audible or visual, it means that there is an imbalance in objectivity. When, furthermore, there is an incorrect and intentional use of words in order to influence readers, it means to move away from objectivity as a necessary element in the success of the media institution; and the success of its editorial material.

But the objective interpretation may take several dimensions to the liaison. For the purpose of grasping the interpretation of objectivity among those liaisons working in the

The methods used by the print media (press) is varied in conveying its messages and its orientations to the readers. But language takes the leading method among these methods, or a real competitor - so far - due to the characteristics and advantages of languages, including: ease, abbreviation, and development, etc.

In the midst of such events, political tensions, and what they carry of the global developments, and among which was the most important the fall of the former Iraqi regime in the spring of 2003, the press had the greatest share, and a large portion on the level of monitoring, analyzing, and interpreting the various consequences of the event. The interpreting of the news varies according to the evolving political trends

One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our ca

Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.