Introduction: An aneurysmal bone cyst are enigmatic lesion of unknown cause and presentation and are difficult to distinguish from other lesions, it is a benign, but expansible tumor like lesion that generally occurs in the long bones. An aneurysmal bone cyst arising from the flat bone like clavicle is rare . Case presentation: We report a 12-year-old girl child with an aneurysmal bone cyst of the lateral third of left clavicle treated with enblock resection. The pathologic findings confirmed the diagnosis of aneurysmal bone cyst. The patient has been followed up for one year with no evidence of recurrence . Conclusion: En bloc resection can be curative and provide good results for this rare type of clavicle tumour.

Introduction: An aneurysmal bone cyst are enigmatic lesionof unknown cause and presentation and are difficult todistinguish from other lesions, it is a benign, but expansibletumor like lesion that generally occurs in the long bones. Ananeurysmal bone cyst arising from the flat bone like clavicleis rare .Case presentation: We report a 12-year-old girl child with ananeurysmal bone cyst of the lateral third of left clavicletreated with enblock resection. The pathologic findingsconfirmed the diagnosis of aneurysmal bone cyst. Thepatient has been followed up for one year with no evidenceof recurrence .Conclusion: En bloc resection can be curative and provide good results for this rare type of clavicle tumour.

In this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.

 

            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

        Corruption is a phenomenon that exists in all times and places, they appear in the developing countries and in developed countries, and in all political systems. And its repercussions and economic repercussions on the society in which it is rampant, and lead to the undermining of economic development and obstruction, is also working on increasing poverty and unemployment, as well as its role in the worsening of social problems, and political instability. And corruption is deviant behavior is illegal and contrary to the teachings of the religious and moral values. The emergence of this phenomenon is due to several reasons, including political, economic, social and cultura

Background: Cardiopulmonary resuscitation (CPR) is a technique or procedure that combined chest compression and rescue breathing to maintain enough circulation that prevents brain damage until other essential steps are taken to control the main cause of cardiac and respiratory arrest. The health care personnel should be qualified in the performing of cardiopulmonary resuscitation (CPR) to improve the survival rate of the victims. Therefore; it is necessary to use new methods for learning [1]. Objectives: the study aims to compare the effectiveness of self-instructional teaching strategy and traditional teaching approach on student’s knowledge toward cardiopulmonary resuscitation. Methods: A randomized comparative trial (RCT) design was ca

          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina