Search results for: Norah A. Elgibreen
4 Dignity and Suffering: Reading of Human Rights in Untouchable by Anand
Authors: Norah A. Elgibreen
Abstract:Cultural stories are political. They register cultural phenomena and their relations with the world and society in term of their existence, function, characteristics by using different context. This paper will provide a new way of rethinking which will help us to rethink the relationship between fiction and politics. It discusses the theme of human rights and it shows the relevance between art and politics by studying the civil society through a literary framework. Reasons to establish a relationship between fiction and politics are the relevant themes and universal issues among the two disciplines. Both disciplines are sets of views and ideas formulated by the human mind to explain political or cultural phenomenon. Other reasons are the complexity and depth of the author-s vision, and the need to explain the violations of human rights in a more active structure which can relate to emotional and social existence.
Keywords: dignity, human rights, politics and literature, Untouchable.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3155
3 Mining Sequential Patterns Using Hybrid Evolutionary Algorithm
Authors: Mourad Ykhlef, Hebah ElGibreen
Abstract:Mining Sequential Patterns in large databases has become an important data mining task with broad applications. It is an important task in data mining field, which describes potential sequenced relationships among items in a database. There are many different algorithms introduced for this task. Conventional algorithms can find the exact optimal Sequential Pattern rule but it takes a long time, particularly when they are applied on large databases. Nowadays, some evolutionary algorithms, such as Particle Swarm Optimization and Genetic Algorithm, were proposed and have been applied to solve this problem. This paper will introduce a new kind of hybrid evolutionary algorithm that combines Genetic Algorithm (GA) with Particle Swarm Optimization (PSO) to mine Sequential Pattern, in order to improve the speed of evolutionary algorithms convergence. This algorithm is referred to as SP-GAPSO.
Keywords: Genetic Algorithm, Hybrid Evolutionary Algorithm, Particle Swarm Optimization algorithm, Sequential Pattern mining.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1913
2 WormHex: A Volatile Memory Analysis Tool for Retrieval of Social Media Evidence
Authors: Norah Almubairik, Wadha Almattar, Amani Alqarni
Social media applications are increasingly being used in our everyday communications. These applications utilise end-to-end encryption mechanisms which make them suitable tools for criminals to exchange messages. These messages are preserved in the volatile memory until the device is restarted. Therefore, volatile forensics has become an important branch of digital forensics. In this study, the WormHex tool was developed to inspect the memory dump files for Windows and Mac based workstations. The tool supports digital investigators by enabling them to extract valuable data written in Arabic and English through web-based WhatsApp and Twitter applications. The results confirm that social media applications write their data into the memory, regardless of the operating system running the application, with there being no major differences between Windows and Mac.
Keywords: Volatile memory, REGEX, digital forensics, memory acquisitionProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 539
1 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children
Authors: Norah Alshahrani, Abdulaziz Almaleh
Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD: Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by SVM, achieving 0.98% in the toddler dataset and 0.99% in the children dataset.
Keywords: Autism Spectrum Disorder, ASD, Machine Learning, ML, Feature Selection, Support Vector Machine, SVM.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 53