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There are numerous conflicts ensuing in the Middle East, but not all are being fought with rockets and rifles. While the Internet has proven invaluable to those who wish to uphold a patriarchal society and spread the message of Islamic fundamentalism, Muslim women have used the Web to build a transnational community intent on growing women’s rights in the Middle East. There is a large disparity between a Muslim woman's role according to the Qur'an and her role as some corners of Muslim society have interpreted it. In Velvet Jihad Faegheh Shirazi reveals the creative strategies Muslim women have adopted to quietly fight against those who would limit their growing rights. Shirazi examines issues that are important to all women, from routine matters such as daily hygiene and clothing to controversial subjects like abortion, birth control, and virginity. As a woman with linguistic expertise and extensive life experience in both Western and Middle Eastern cultures, she is uniquely positioned as an objective observer and reporter of changes and challenges facing Muslim women globally.
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This volume discusses the need to adopt Climate-Resilient Agriculture (CRA) practices to address the increasing global impact that climate change has on agricultural productivity and agriculture-dependent communities. This approach applies technological, policy and economic measures to achieve sustainable agricultural growth in the sectors of grain, fruit, vegetable, fiber, feed, livestock, fisheries and forestry, with the ultimate goal of adapting and building resilience to climate change. The book also uses GIS, crop modeling and remote sensing techniques for future climate resilience applications in agriculture, and covers pest control measures that avoid the use of pesticides to boost crop and livestock productivity for improved food security. The book will be of interest to researchers and students in environmental science, climate science, sustainability and agriculture, as well as policy makers and environmental organizations.
The objective of this book is to provide a source of information and to assist the medical and paramedical team in the management of rare clinical entity called necrotizing fasciitis. It must be emphasized that the necrotizing fasciitis is a limb and life threatening surgical as well as medical emergency. This book will be an asset for acute care physicians, surgeons, intensivists and nursing staff involved in the management of this rare clinical condition. In this book chapters are directed towards early proper diagnosis and management of necrotizing fasciitis, which is the corner stone for better outcome of these suffering patients. The contributors were patiently cooperative, did a hard but great job by compiling these chapters. I extend my deep appreciation to my wife, Dr Firdous for her continuous encouragement and support to write this book.
Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.
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1960/61- map on lining papers.