The internet provides a vast amount of data which can be utilised to explore different approaches to solving industry problems. Efficient methods for the retrieval of this information are essential for streamlined business processes. Information Retrieval Methods for Multidisciplinary Applications provides innovative research on information gathering, web data mining, and automation systems. Addressing multidisciplinary applications and focusing on theories and methods with an enterprise-wide perspective, this book is essential for information engineers, scientists, and related professionals.

Mobile Learning is a new trend in pedagogical communities. It matches the speed of fast moving methodologies in pedagogical world. The theories of activity-based learning, problem-based learning, work-based learning, and opinion-based learning, learner-centered learning, and so forth, can be integrated with these tiny handheld devices. Students and teachers communicate effectively and efficiently with these simple clicks to obtain the formative/informative and summative feedbacks. The learning outcomes for both ability and knowledge can be smartly measured and observed through the latest ICT technologies. Learning with Mobile Technologies, Handheld Devices and Smart Phones: Innovative Methods presents a collection of innovative research which focuses on learning in the digital world with advanced mobile technologies. This reference will aim to bring researchers, professors, and lectures and industrial training associations together to introduce a new era of teaching and learning societies.

This book highlights a timely and accurate insight at the endeavour of the bioinformatics and genomics clinicians from industry and academia to address the societal needs. The contents of the book unearth the lacuna between the medication and treatment in the current preventive medicinal and pharmaceutical system. It contains chapters prepared by experts in life sciences along with data scientists for examining the circumstances of health care system for the next decade. It also highlights the automated processes for analyzing data in clinical trial research, specifically for drug development. Additionally, the data science solutions provided in this book help pharmaceutical companies to improve on what had historically been manual, costly and laborious process for cross-referencing research in clinical trials on drug development, while laying the groundwork for use with a full range of other drugs for the conditions ranging from tuberculosis, to diabetes, to heart attacks and many others.