Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

Nowadays, the use of natural bio-products in pharmaceuticals is gaining popularity as safe alternatives to chemicals and synthetic drugs. Algal products are offering a pure, healthy and sustainable choice for pharmaceutical applications. Algae are photosynthetic microorganisms that can survive in different environmental conditions. Algae have many outstanding properties that make them excellent candidate for use in therapeutics. Algae grow in fresh and marine waters and produce in their cells a wide range of biologically active chemical compounds. These bioactive compounds are offering a great source of highly economic bio-products. The prese

     Increasing need for our youth to effective dialogue at the present time, due to the nature of the era in which live, as it abounded risk of intellectual and cultural invasion.Moreover, the need to ensure that the dialogue between the members of the community to confront the many issues of contemporary society in various fields, politically, socially and economically, culturally and religiouslyThe absence of effective dialogue, or the consequent rejection of many of the negative aspects of social and cultural Kaezzlh coup and inertia and ignore the mental capacity of some non-existent among others.The importance of effective dialogue in being the most important foundations of social life a

<p>Energy and memory limitations are considerable constraints of sensor nodes in wireless sensor networks (WSNs). The limited energy supplied to network nodes causes WSNs to face crucial functional limitations. Therefore, the problem of limited energy resource on sensor nodes can only be addressed by using them efficiently. In this research work, an energy-balancing routing scheme for in-network data aggregation is presented. This scheme is referred to as Energy-aware and load-Balancing Routing scheme for Data Aggregation (hereinafter referred to as EBR-DA). The EBRDA aims to provide an energy efficient multiple-hop routing to the destination on the basis of the quality of the links between the source and destination. In