Non-vocalized Arabic words are ambiguous words, because non-vocalized words may have different meanings. Therefore, these words may have more than one root. Many Arabic root extraction algorithms have been conducted to extract the roots of non-vocalized Arabic words. However, most of them return only one root and produce lower accuracy than reported when they are tested on different datasets. Arabic root extraction algorithm is an urgent need for applications like information retrieval systems, indexing, text mining, text classification, data compression, spell checking, text summarization, question answering systems and machine translation. In this work, a new rule-based Arabic root extraction algorithm is developed and focuses to overcome the limitation of previous works. The proposed algorithm is compared to the algorithm of Khoja, which is a well-known Arabic root extraction algorithm that produces high accuracy. The testing process was conducted on the corpus of Thalji, which is mainly built to test and compare Arabic roots extraction algorithms. It contains 720,000 word-root pairs from 12000 roots, 430 prefixes, 320 suffixes, and 4320 patterns. The experimental result shows that the algorithm of Khoja achieved 63%, meanwhile the proposed algorithm achieved 94% of accuracy.

Abstract-Many studies have focused recently on building, evaluating and comparing Arabic root extracting algorithm. The main challenges facing root extraction algorithms are the absence of standard data set for testing, comparing and enhancing different Arabic root extraction algorithms. In addition, the absence of complete lists of roots prefixes suffixes and patterns. In this paper, we describe the development of a new corpus driven from traditional Arabic dictionaries "mu'jams". The goal is to use the corpus, as a new gold standard data set for testing, comparing and enhancing different Arabic root extraction algorithms. This data set covers all types of words and all roots. It contains each word and its root as a pair to avoid the consultation of a human expert needed to verify the correct roots of words used in the testing or comparing process. We describe the individual phases of the corpus construction, i.e. normalisation, reading derivation words and roots as a pair, and reading each root and its definition part. We have automatically extracted (12000) roots, (430) prefixes, (320) suffixes, (4320) patterns, and (720,000) word-root pair. Konja's and Garside Arabic root extraction algorithm was tested on this corpus; the accuracy was (63%), then we test it after supplying it with our lists of roots prefixes suffixes and patterns, the accuracy of it became 84%.

Insomnia is a common sleep-related neuropsychological disorder that can lead to a range of problems, including cognitive deficits, emotional distress, negative thoughts, and a sense of insufficient sleep. Insomnia can also worsen or lead to other medical conditions. Despite the existence of various insomnia-related cognitive models, clinical studies, and guidelines, there appears to be a lack of an evidence-based dynamic model for a personalized approach to treating insomnia .This study proposes a providing computational dynamic cognitive model (PCDCM) insight into providing cognitive mechanisms of insomnia and consequent cognitive deficits. Since the support providing is significantly dynamic and it includes substantial changes as demanding condition happen. From this perspective the underlying model covers integrating of both coping strategies, provision preferences and adaptation concepts. The model was found to produce realistic behavior that could clarify conditions for providing support to handle insomnia individuals, which was done by employing simulation experiments under various negative events, personality resources, altruistic attitude and personality attributes. Simulation results show that, a person with bonadaptation and either problem focused or emotion focused coping can provide different social support based on his personality resources, personality attributes, and knowledge level, whereas a person with maladaptation regardless the coping strategies cannot provide any type of social support. Moreover, person with close tie tends to provide instrumental, emotional, and companionship support than from weak tie. These results were similar to those with the model’s mathematical analysis. Finally, a mathematical analysis was used to examine the possible equilibria of the model.