One of the important objectives of the varistor is for a sustainable environment and reduce the pollution resulting from the frequent damage of the electrical devices and power station waste. In present work, the influence of Al2O3 additives on the non –linear electrical features of SnO2 varistors, has been investigated, where SnO2 ceramic powder doped with Al2O3 in three rates (0.005, 0.01, and 0.05), the XRD test improved that SnO2 is the primary phase, while CoCr2O4, and Al2O3 represent the secondary phases. The electrical tests of all prepared samples confirmed that the increasing of Al2O3 rates and sintering temperature improves and increase the electrical features, where the best results obtained at Al2O3 (0.05) and 1000℃, the non

BN Rashid

Levels of the Factors structure of the scale Costa and McCrae applied to the Iraqi environment

      A previously_prepared Iraqi version of Costa & McCrae the big five factor has been adminstered to (200) students at University of Baghdad in order to investigate the hypothesized differences in factor structures between the original version of Costa & McCrae test and the Iraqi version.

    To verify the hypothesized differences , the minieigen value. Factors , maximum likelihood criteria of determining the number of factors , and varimax and promax as methods of rotation have been used.

    The

This research deals with the idea of how the poetic reading can be a
rich field for producing the potential meanings in each text, through observing
the connection of the words and their link with other, thus composes, from the
collection of these interlaced meanings, what is called the poetic significant
(Symbolic) elaboration which deals with the reader of the text by regarding
him as a producer not as a consumer who can read a conscious reading, and
be diligent to solve the problem of the links of the relations among the
inspiring words because the language of poetry is an inspired language which
is capable of diversity and multiplicity of readings which is called the Symbolic
elaboration.

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual info

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