Among the metaheuristic algorithms, population-based algorithms are an explorative search algorithm superior to the local search algorithm in terms of exploring the search space to find globally optimal solutions. However, the primary downside of such algorithms is their low exploitative capability, which prevents the expansion of the search space neighborhood for more optimal solutions. The firefly algorithm (FA) is a population-based algorithm that has been widely used in clustering problems. However, FA is limited in terms of its premature convergence when no neighborhood search strategies are employed to improve the quality of clustering solutions in the neighborhood region and exploring the global regions in the search space. On the

The recognition of handwritten numerals has many applications in automatic identification and cognition. This research contains three experimented scenarios to recognize the handwritten English (i.e. Arabic) numerals. In the first scenario the bilinear interpolation of the image is used, while in the second scenario and after the bilinear interpolation is being applied, the Sobel operators are applied on the resulted interpolated image. In the third scenario which represents the last one, the effect of normalization of image dimensions is tested. 550 images of handwritten numerals were tested. Three types of tests were conducted for each scenario namely: trained-set test, not-trained-set test and comprehensive-set test. Depending on the

       Political speeches are represented in different shapes as political forum, events or as inaugural speech. This research critically analyzes the inaugural Speech of the President Donald Trump which was delivered on 20th ,January, 2017 from the site<www.cnn.com> retrieved on 10th ,May,2017. The objectives of the study are: First: classifying and discussing well known micro structures (linguistic feature) of the speech, and second: classifying the macro structures i.e. the delivered political inaugural speech  in which he includes social structures. To reach to the objectives of the study, the researcher will adopt Norman Fairclough’s three dimensional Analytical Model(1989). Tracing the model, the speech was subm

However, the effects of these ideas are still evident
Think of those who follow the footsteps of Muslim scholars and thinkers.
Intellectual source of Gnostic Gnar
And in dealing with issues of Islamic thought
Annalisa intersecting trends of thought, Minya who melts in Masarya and supported him and believes in Bo and extremist Vue,
 Lea, trying to throw it with a few times, looks at Elya look
There are those who stand in the opposite position
There are those who stand in a selective compromise, but this school of thought remains
 G - the features of Islamic thought that believes in the mind and Imoto in the defense of
An intellectual station and generalized bar
Creed. In his study, the researcher wi

Identification by biological features gets tremendous importance with the increasing of security systems in society. Various types of biometrics like face, finger, iris, retina, voice, palm print, ear and hand geometry, in all these characteristics, iris recognition gaining attention because iris of every person is unique, it never changes during human lifetime and highly protected against damage. This unique feature shows that iris can be good security measure. Iris recognition system listed as a high confidence biometric identification system; mostly it is divide into four steps: Acquisition, localization, segmentation and normalization. This work will review various Iris Recognition systems used by different researchers for each recognit

     Human eye offers a number of opportunities for biometric recognition. The essential parts of the eye like cornea, iris, veins and retina can determine different characteristics. Systems using eyes’ features are widely deployed for identification in government requirement levels and laws; but also beginning to have more space in portable validation world.

The first image was prepared to be used and monitored using CLAHE which means (Contrast Limited Adaptive Histogram Equalization) to improve the contrast of the image, after that the 3D surfac

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

In this paper we investigate the use of two types of local search methods (LSM), the Simulated Annealing (SA) and Particle Swarm Optimization (PSO), to solve the problems ( ) and . The results of the two LSMs are compared with the Branch and Bound method and good heuristic methods. This work shows the good performance of SA and PSO compared with the exact and heuristic methods in terms of best solutions and CPU time.