Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

Los nombres propios nombran a un ser o a un objeto, distinguiéndolo de los demás seres de su misma clase, se escriben siempre con letra mayúscula a principio de palabra. Los lingüistas hacen mayor hincapié en las divergencias de referencia, entre nombres propios y nombres comunes. Así, suele decirse que el sustantivo propio no tiene como referente ningún concepto. El asunto de la traducción  de los nombres propios parecería una cuestión de gusto personal del traductor pero vemos también que en algunas épocas es más frecuente traducirlos, y en otras, por el contrario, se prefiere dejar esos nombres en su forma original, tal vez con algunas adaptaciones ortográficas. Parecería enton­ces cuestión de modas. Pero, eviden

Activated carbon was Produced from coconut shell and was used for removing sulfate from industrial waste water in batch Processes. The influence of various parameter were studied such as pH (4.5 – 9.) , agitation time (0 – 120)min and adsorbent dose (2 – 10) gm.

The Langmuir and frandlich adsorption capacity models were been investigated where showed there are fitting with langmmuir model with squre regression value ( 0.76). The percent of removal of  sulfate (22% - 38%) at (PH=7) in the isotherm experiment increased  with adsorbent mass increasing. The maximum removal value of sulfate at  different pH experiments is (43%) at pH=7.

The sole aim of the tribe of the Messenger of Allah (PBUH) and his basilica was to revoke the Umayyad heresy and to refute the suspicions through which they climbed to the top of the pyramid of power and legitimized the leadership of Muslims (heresy of hereditary rule) with the sword and blood. Therefore, Imam Hussein (peace be upon him) began his Ashura process with his short divine message in its words and great in its vocabulary and content and even the future of Mohammedan Islam over the times and spaces - what we will see in the folds of research, God willing.

The objective of this study was to isolate and identify the asparaginase-producing bacteria, then purify and characterize the enzyme in order to investigate their properties in the future. Fifteen local bacterial isolates were isolated from various sites in the city of Baghdad, identified by conventional morphological and biochemical procedures, and confirmed using vitek 2 methods, and submitted to primary screening processes for asparaginase production. For secondary screening, eight isolates with the greatest yellow zone ability on a specific solid medium were chosen. Bacillus sp. was reported to have the highest enzyme production (7.5 U/mg proteins). After 24 hours of incubation, submerged fermentation yielded optimal conditi

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

As the process of  estimate for model and variable selection significant is a crucial process in the semi-parametric modeling At the beginning of the modeling process often At there are many explanatory variables to Avoid the loss of any explanatory elements may be important as a result , the selection of significant variables become necessary , so the process of variable selection is not intended to simplifying  model complexity explanation , and also predicting. In this research was to use some of the semi-parametric methods (LASSO-MAVE , MAVE and The proposal method (Adaptive LASSO-MAVE) for variable selection and estimate semi-parametric single index model (SSIM) at the same time .