تعلیم نسواں: اسلامی روایت اور عصری تحدیات

Religion Islam has given equal rights to men and women in the field of education. For men education was compulsory and women were encouraged to seek education. Both males and females have been referred to using polygamous section for education while women are often encouraged and especially emphasized. The Prophet(SAW)arranged special seats for the gender critical in order to highlight the importance of women education. That was way the passion for special education in women grew so much that women discussed global issues with men and solved to reject men’s judgement. It was the influence of this academic moment that many Muslim women not only made a name for themselves, but also wrote books on various research topic in the field of Hadith, Commentary, Iftaa and many other Sciences. Thanks for this global revolution Muslim rulers not only provided a learning environment for their children but also established large educational institutions for ordinary women. The astonishing thing is that despite this wonderful past today Muslims are unable to provide a safe and secure opportunity for education to women.

A Novel Architecture to Integrate Multi-Sourcedatain Distributed Environment

The amount of data has been increasing over the last few years due to the emergence of various end-user applications. These applications utilize cloud computing infrastructure in the data centers. Apart from the increasing volume of data, there are other factors such as variety, velocity, and veracity of the data which result in the problem of big data. Traditional database management systems are not efficient to handle big data. The use of big data platform is necessary to resolve the big data problem. Hadoop is one of the platforms which resolve the problem of big data. Hadoop uses a distributed storage system. Hive and HBase are some of the big data tools for storing big data in Hadoop. They run on top of Hadoop distributed file system (HDFS). Hive is a data warehouse framework for querying and analysis of data that is stored in HDFS.?Hive?is an open-source software that lets programmers analyze large data sets on Hadoop. HBase is a column-oriented, distributed and high fault-tolerant database. It is used to store and manage big data. It can store billions of rows at a time. Both Hive and HBase can be used to store the big data in Hadoop. When the data comes from multiple sources, it is stored into multiple tables in Hive and HBase. As a result, its performance degrades when there is a need to perform join operations. In this thesis, we propose an architecture which stores data from multiple sources into a single HBase table. A new table schema with a unique row key is designed which integrates multi-source data in a table. There is no need to perform join operation in the proposed technique as the data is integrated into a single HBase table. We evaluated the proposed technique using a real testbed by considering a dataset of two publishers. We compare the performance by storing data into Hive and also in the proposed HBase table. Results show improved query performance of the proposed technique as compared to the traditional approach of using join operations in multiple tables in Hive.