Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could b

Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

Recognizing speech emotions is an important subject in pattern recognition. This work is about studying the effect of extracting the minimum possible number of features on the speech emotion recognition (SER) system. In this paper, three experiments performed to reach the best way that gives good accuracy. The first one extracting only three features: zero crossing rate (ZCR), mean, and standard deviation (SD) from emotional speech samples, the second one extracting only the first 12 Mel frequency cepstral coefficient (MFCC) features, and the last experiment applying feature fusion between the mentioned features. In all experiments, the features are classified using five types of classification techniques, which are the Random Forest (RF),

Natural settings make it challenging to identify facial expressions since head position, illumination level, and ‎‎occlusion vary. Thus, developing a more generic model without front-facing images alone is quite crucial. This ‎research proposes a facial expression ‎recognition model based on pre-trained deep convolutional neural networks ‎with transfer learning. The model was trained ‎on several cases to classify face expressions into seven ‎classifications efficiently. The proposed system used the EfficientNetB0 model ‎that has one dense dropout layer. The model first rescales and norms the input dataset in the input ‎layer that takes images of a larger resolution to get better results. After entering 7 blocks sequential

In cyber security, the most crucial subject in information security is user authentication. Robust text-based password methods may offer a certain level of protection. Strong passwords are hard to remember, though, so people who use them frequently write them on paper or store them in file for computer .Numerous of computer systems, networks, and Internet-based environments have experimented with using graphical authentication techniques for user authentication in recent years. The two main characteristics of all graphical passwords are their security and usability. Regretfully, none of these methods could adequately address both of these factors concurrently. The ISO usability standards and associated characteristics for graphical

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

Newcastle Disease is one of the most important disease world wide distributions which invade the flock in different age resulting in large economic losses. This study aimed to evaluate the effect of treatment with 4 different concentrations (0.25, 0.5, 1.0 and 2.0 %) of Sodium deoxycholate (SDC) on the vaccinal virus (La Sota) using inoculation in the fragments of Chorioallantoic membrane. The treatment with each of the above 4 concentrations of SDC resulted in an increase in the Hemagglutination titer (HA) of the virus (28, 29.6, 211.6, 214.6) respectively as compared to the HA titer value for the untreated virus (26.6). No significant differences were noticed among all concentrations with regard to their effect on the HA titer, except

The researcher, in this academic research, seeks to highlight the role of the semantic production in the dramatic act and to know the extent of its work and importance, because drama is an act and the dramatic work is a group of acts. The dramatic meaning and act are two inseparable concepts that cannot be divided, because each dramatic act is a container of meanings through connotations, signs and symbols. The production of the connotations in the dramatic act is considered one of the important issues in the content language of communication between the sender and recipient in order to get to the intended meaning. These sign connotations engage the spectator in the codifying activity and get him immersed in the events. The research pres

Rheumatoid arthritis is one of the common chronic disease, which lead to great disability and chronic pain, and has a main adverse economic and social effect upon patients. The reason for the addition of quality of life as a pointer for health outcome result is attributed to the affectability of this measure for the evaluation of patient's health status after taken treatment and its health outcome. The purpose of the current study was to assess quality of life among a sample of Iraqi patients with rheumatoid arthritis and to determine the possible association between health’s related quality of life and some patient-certain factors. This study is a cross-sectional study carried out on 250 already diagnosed rheumatoid arthritis pat