Alzheimer's disease is an age-associated, irreversible, progressive neurodegenerative disease that is characterized by severe memory loss, unusual behavior, personality changes and a decline in memory function. It is the most common form of dementia and affects an estimated 10 million people worldwide. Alzheimer’s disease demolishes the vital brain cells, causing trouble with memory, thinking and behavior, brutal enough to affect work, lifelong hobbies and social life. Recognized factors in Alzheimer's disease include acetylcholine deficiency, free radicals and inflammation of the brain tissue. There is no cure for Alzheimer's disease, but drugs designed to slow down the disease progression are available. Some herbs may help to improve brain function, but scientific evidence to prove that they can treat Alzheimer's disease. Medicinal plants have been the single most productive source of leads for the development of drugs, and over a hundred new products are already in clinical development. Indeed, several scientific studies have described the use of various medicinal plants and their constituents for treatment of Alzheimer's disease. This review gathers research on various medicinal plants that have shown promise in reversing the Alzheimer's disease pathology. The report summarizes information concerning applications of these various plants in order to provide sufficient baseline information that could be used in drug discovery campaigns and development process, thereby providing new functional leads for Alzheimer's disease.

Effective cooling is required in power generation, processing, and distribution to avoid failure that could occur during operations. As heat loads continue to increase, manufacturers of wind turbines are turning to improve the cooling system to remove high intensity heat loads from many active parts particularly in the generator part. Wind generators need an effective cooling system due to the large amount of heat that is released during power production. Many large wind turbines (more than 5MW rated power) particularly offshore wind turbines where the water is available, heat exchangers with water-air cooling system is used, in which the water is utilized to cool the hot air. This type of heat exchangers are desired, since they are more efficient and reliable than the air-air heat exchangers, which are used in small wind turbines. Because of the growing number of failures that occurred in wind turbine generators due to high generator’s temperatures owing to power losses of generator, applying condition monitoring system on wind generators depending on heat transfer analysis through the heat exchangers of wind generators plays an effective role. This helps avoid failures and maintain wind turbines to be protected. In this paper new methodology has been applied by considering the heat transfer and fluid mechanics analysis through a heat exchanger of wind generator, which uses water to air cooling system. Case study based on data collected from actual measurements demonstrates the adequacy of the proposed model. 

Abstract With the explosive growth of the World Wide Web, Information Retrieval Systems (IRS) have recently become a focus of research. Query expansion is defined as the process of supplementing additional terms or phrases to the original query to improve the information retrieval performance. Arabic is highly inflectional and derivational language which makes the query expansion process a hard task. In this paper, the well known approach, Pseudo Relevance Feedback (PRF) is adopted to be applied on Arabic. Prior to applying PRF, first; datasets (three collections of Arabic documents) are pre-processed to create documents inverted index vocabularies, then, the normal indexing process is carried out. The PRF is applied to create a modified (expanded) query of the original one and the target collection is indexed once more. To judge the enhancement of retrieval process, the results of normal indexing and those of applying PRF are evaluated against each other using precision and recall measures. The results have shown that the PRF method has significantly enhanced the performance of the Arabic Information Retrieval (AIR) System. As the number of expansion terms increases up to a certain extent (35 terms), the performance has been improved. On the other hand, the performance will not be affected, or grow insignificantly as the number of expansion terms exceeds this limit. 

Abstract: Nowadays, enormous amounts of accessible textual information available on the Internet are phenomenal. Automatic text classification is considered an important application in natural language processing. It is the process of assigning a document to predefined categories based on its content. In this paper, the well-known Centroid-based technique developed for text classification is considered to be applied on Arabic text. Arabic language is highly inflectional and derivational which makes text processing a complex and challenging task. In the proposed work, the Centroid-based Algorithm is adopted and adapted to be applied to classify Arabic documents. The implemented algorithm is evaluated using a corpus containing a set of Arabic documents. The experimental results against a dataset of 1400 Arabic text documents covering seven distinct categories reveal that the adapted Centroid-based algorithm is applicable to classify Arabic documents. The performance criteria of the implemented Arabic classifier achieved roughly figures of 90.7%, 87.1%, 88.9%, 94.8%, and 5.2% of Micro-averaging recall, precision, F measure, accuracy, and error rates respectively.

The building projects are differentiated, each building project is unique in terms of size, the level of complexity, procurement systems required. The characteristics of building projects could have major influence on overall project performance. Building projects that incorporate green designs, which are complicated to understand or manage adequately and are more complex compared with typical building projects. Therefore, To achieve high-green design performance, understand crucial characteristics of building projects that may have affect performance level of green design is required. The propose of this study to identify key project characteristics of building projects influencing green design performance. To achieve mentioned aim a questionnaire survey was conducted to collect dada required. A sample of 274 respondents has been covered under the study, including architects and engineers practicing design and consultancy building sectors. Prior to analysis of data WINSTEPS software were used to determine validity and reliability of date. Descriptive analysis data includes quantitative and qualitative. The results revealed that the Project Size can influence the Green Design Performance. The type of Building and size of the project are the key factors influencing Green Design Performance. The Availability of Design Information was moderate. The Reused and Recycled Materials were hard to find, while Regional Materials were available in the market.