Rapid increase in the use of smart mobile phones and the proliferation of social media networking programs such as facebook, tweeter, whatsapp and viber etc. affects the learning attitude of second language. This research aims to investigate the effects of emoticons provided by Viber application on Iraqi students in context of vocabulary acquisition. 60 Iraqi students are randomly selected from X international school with the average of age 7 to 9 years. All the subjects are given 50 English words for five weeks, 25 English words were written on papers and the rest Viber stickers laden with English words. The results show that students recognize the vocabularies given by Viber stickers better than the written vocabulary. In general, student

African-American writers during the 19th century wrote in the shadow of the prominent romance, sentimental, and domestic fiction. Harriet Wilson’s Our Nig (1859) reflects an “alternative social character”, for the female protagonist suffers racism in the free North, because she is a mulatto child. Through depicting the life of free blacks, who supposedly lives a better life than Southern slaves, Wilson exposes how she has actually lived and sensed life in antebellum America. According to Raymond Williams (2011), there are two kinds of literary writings. The first represents the general tendency of the age, and he calls it “dominant social character”; representing the majority content of both the public writing and speaking. But, a

In recent years, the means of communication have achieved a great generality that made them occupy, in a short time, the first ranks among the most widely used social networks in the world, due to the many services and advantages offered by this network to its users. It has led to a leap in the field of visual communication, especially since it relies mainly on the image Its dimensions make it a means of communication and transfer of ideas and meanings between the peoples of the world, and it also allows the inclusion of digital advertising content using multimedia with a degree of professionalism in other social networks, which allowed the various segments of society the opportunity to invest this network in their businesses of differen

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

Since the beginning of this century, a new communication map has been formed that foretells to get mankind to enter into a media environment in which the media is mixed with communication, which is technically and even intellectually known as integration.

This environment and its features are no different from the environment in its natural physical incision. If the level and temperature in the physical nature is a specific issue in the natural ecological balance, the level of freedoms, especially the transfer of information and views and circulation in society is also a determinant in the extent of media balance in the world on the one hand and in each country on the other.

There is also a special environment for nature,

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

A solid Phase Extraction (SPE) followed by HPLC-UV method is described for the simultaneous quantitative determination of nine priority pollutant phenols : Phenol, 2- and 4-Nitrophenol, 2,4-Dimethylphenol, 2-, 2,4-Di-, 2,4,6-Tri-, and Penta- chlorophenol, 4 Chloro-3-methylphenol. The phenols were separated using a C-18 column with UV detector at wave length of 280nm. The Flow of mobile phase was isocratic consisted of 50:50 Acetonitrile: phosphate buffer pH=7.1, column temperature 45 C°, Flow Rate 0.7 ml/min. Calibration curves were linear (R2 = 0.9961-0.9995). The RSDs (1.301-5.805)%, LOD(39.1- 412.4) µg/L, LOQ(118.5-1250.8) µg/L, the Robustness (1.55-4.89), Ruggedness (2.82-4.00), Repeatability (2.1-4.95), Recoveries%