The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

Human action recognition has gained popularity because of its wide applicability, such as in patient monitoring systems, surveillance systems, and a wide diversity of systems that contain interactions between people and electrical devices, including human computer interfaces. The proposed method includes sequential stages of object segmentation, feature extraction, action detection and then action recognition. Effective results of human actions using different features of unconstrained videos was a challenging task due to camera motion, cluttered background, occlusions, complexity of human movements, and variety of same actions performed by distinct subjects. Thus, the proposed method overcomes such problems by using the fusion of featur

In this paper an authentication based finger print biometric system is proposed with personal identity information of name and birthday. A generation of National Identification Number (NIDN) is proposed in merging of finger print features and the personal identity information to generate the Quick Response code (QR) image that used in access system. In this paper two approaches are dependent, traditional authentication and strong identification with QR and NIDN information. The system shows accuracy of 96.153% with threshold value of 50. The accuracy reaches to 100% when the threshold value goes under 50.

Digital forensic is part of forensic science that implicitly covers crime related to computer and other digital devices. It‟s being for a while that academic studies are interested in digital forensics. The researchers aim to find out a discipline based on scientific structures that defines a model reflecting their observations. This paper suggests a model to improve the whole investigation process and obtaining an accurate and complete evidence and adopts securing the digital evidence by cryptography algorithms presenting a reliable evidence in a court of law. This paper presents the main and basic concepts of the frameworks and models used in digital forensics investigation.

Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

Automatic Programming Assessment (APA) has been gaining lots of attention among researchers mainly to support automated grading and marking of students’ programming assignments or exercises systematically. APA is commonly identified as a method that can enhance accuracy, efficiency and consistency as well as providing instant feedback on students’ programming solutions. In achieving APA, test data generation process is very important so as to perform a dynamic testing on students’ assignment. In software testing field, many researches that focus on test data generation have demonstrated the successful of adoption of Meta-Heuristic Search Techniques (MHST) so as to enhance the procedure of deriving adequate test data for efficient t