This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,

فقدان الزوج يعد حدثًا يغير حياة النساء، مما يضطرهن إلى السباحة في عالم جديد مليء بالحزن والوحدة والشكوك. مع الوقت، تطورت طريقة تصوير الأرامل بشكل كبير تعكس التغييرات في الآراء والقيم الثقافية. تُمثل الأرامل تقليديًا بأنهن ضعيفات ومعتمدات في الأدب، مستندة إلى افتراض أنهن يفتقدن الدعم المالي بعد وفاة شركائهن. ومع ذلك، فإن هذا التصوير لا يعترف بتأثير الأرملة على الرفاهية والهوية الشخصية. يسعى هذا النص إلى

Knowledge of literature is an integral part of learning any spoken language. Learning literature expands the learner’s ability to understand the language studied. The field of literature is wide and cannot be limited to poems. It includes the etiquettes of a language and its environment, customs, and traditions etc. The Arabic language is among the languages with a centuries old history. It has achieved remarkable record accomplishments since the pre-Islamic era through to the present. This development is clear evidence of the great importance of literature in the revival of the Arabic language through different eras. As such, in Malaysia and other non-Arabic speaking countries, literature is taught in most schools, institutions and un

Ensuring security, integrity, and reliability of the election process consider as the main challenges in the electronic voting system. This paper describes the e-voting system by integrating the biometric authentication, advanced encryption, and watermarking techniques towards meeting such challenges. The system employs the fingerprint authentication by utilizing the Scale-Invariant Feature Transform (SIFT) for verifying the identity of the voter to ensure genuineness and non-repudiation of the service. The vote will be encrypted with the AES-GCM technique to be employed in securing the voting process, thus ensuring both data privacy and integrity. Hybrid Blind Watermarking employs the technique of Discrete Wavelet Transform (DWT) a

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

Portable devices such as smartphones, tablet PCs, and PDAs are a useful combination of hardware and software turned toward the mobile workers. While they present the ability to review documents, communicate via electronic mail,  appointments management, meetings, etc. They usually lack a variety of essential security features. To address the security concerns of sensitive data, many individuals and organizations, knowing the associated threats mitigate them through improving authentication of users, encryption of content, protection from malware, firewalls,  intrusion prevention, etc. However, no standards have been developed yet to determine whether such mobile data management systems adequately provide the fu