In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N

The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

Three-dimensional (3D) image and medical image processing, which are considered big data analysis, have attracted significant attention during the last few years. To this end, efficient 3D object recognition techniques could be beneficial to such image and medical image processing. However, to date, most of the proposed methods for 3D object recognition experience major challenges in terms of high computational complexity. This is attributed to the fact that the computational complexity and execution time are increased when the dimensions of the object are increased, which is the case in 3D object recognition. Therefore, finding an efficient method for obtaining high recognition accuracy with low computational complexity is essentia

Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M

Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using M

Statistical studies are reported in this article for an active galactic nuclei sample of different type of active galaxies Seyferts 1, Seyferts 2, and Quasars. These sources have been selected from a Catalogue for bright X-ray galaxies. The name of this index is ROSAT Bright Source Catalogue (RBSC) and the NRAO VLA Sky Survey (NVSS). In this research, multi-wavelength observational bands Radio at 1.4 GHz, Optical at 4400 A⁰, and X-ray at energy 0.1-2.4 KeV have been adopted in this study. The behavior of flux density ratios has been studied ,  with respect to the absolute magnitude . Furthermore, the Seyfert1 and Seyfert 2 objects are combined in one group and the QSOs are collectest in another group. Also, it has been fo

Statistical studies are reported in this article for an active galactic nuclei sample of different type of active galaxies Seyferts 1, Seyferts 2, and Quasars. These sources have been selected from a Catalogue for bright X-ray galaxies. The name of this index is ROSAT Bright Source Catalogue (RBSC) and the NRAO VLA Sky Survey (NVSS). In this research, multi-wavelength observational bands Radio at 1.4 GHz, Optical at 4400 A0, and X-ray at energy 0.1-2.4 KeV have been adopted in this study. The behavior of flux density ratios has been studied ,  with respect to the absolute magnitude . Furthermore, the Seyfert1 and Seyfert 2 objects are combined in one group and the QSOs are collectest in another group. Also, it has been found that t

Statistical studies are reported in this article for an active galactic nuclei sample of different type of active galaxies Seyferts 1, Seyferts 2, and Quasars. These sources have been selected from a Catalogue for bright X-ray galaxies. The name of this index is ROSAT Bright Source Catalogue (RBSC) and the NRAO VLA Sky Survey (NVSS). In this research, multi-wavelength observational bands Radio at 1.4 GHz, Optical at 4400 A0, and X-ray at energy 0.1-2.4 KeV have been adopted in this study. The behavior of flux density ratios has been studied ,  with respect to the absolute magnitude . Furthermore, the Seyfert1 and Seyfert 2 objects are combined in one group and the QSOs are collectest in another group. Also, it has been found that t