NTET for AYUSH Teachers Question Bank Book 1500+ MCQ With Detail Explanation As Per Exam Pattern


Book Description

NTET for AYUSH Teachers Question Bank Book 1500+ MCQ With Detail Explanation As Per Exam Pattern Highlight of Book Covered all 8 Units MCQ As Per Prescribe Exam Level Explanation of all mcq in Detail Design by Expert Faculties As Per New Exam Pattern




Shadow Education


Book Description

In all parts of Asia, households devote considerable expenditures to private supplementary tutoring. This tutoring may contribute to students' achievement, but it also maintains and exacerbates social inequalities, diverts resources from other uses, and can contribute to inefficiencies in education systems. Such tutoring is widely called shadow education, because it mimics school systems. As the curriculum in the school system changes, so does the shadow. This study documents the scale and nature of shadow education in different parts of the region. Shadow education has been a major phenomenon in East Asia and it has far-reaching economic and social implications.




Quantitative Aptitude Quantum Cat


Book Description

1. ‘Quantum Cat’- the bestselling study guide for Management entrances 2. The entire syllabus has been divided into 21 Chapters 3. Every chapter is accompanied with CAT Test for quick revision of concepts 4. More than 400 Fundamental Concepts are provided for better understanding 5. More than 1000 Examples are provided with Use-Cases, Twists, Tricks Choices and Lateral Solutions 6. More than 5000 hand crafted problem are given for the practice 7. 2000 New MCQs have been provided for thorough practice Quantitative Aptitude is a core component for getting a winning CAT Score. Out of every section, Quantitative Ability is one of the most unpredictable and time consuming section. Quantitative Aptitude stems an important part of an individuals’ analytical and logical ability for solving complex problems, making it a filtering tool for qualifying CAT and other Management Entrances. The current edition of “Quantum Cat” has been designed by keeping in mind the needs of those who wish to enhance Quantitative Aptitude for CAT and other Management Examinations. The entire syllabus of Quantitative Aptitude section is divided into 21 Chapters and every topic has 2-3 levels of questions that help students to get prepared for the most difficult problems even beyond the CAT Level. At the end of every chapter there is ‘CAT Test’ that contains problems related to the topic that helps in the quick revision of the concepts. This edition has more than 400 Fundamental Concepts to remember, more than 1000 examples are used to give the conceptual clarity with the methods and tricks are used to solve the questions. With the solution oriented approach this book provides more than 5000 hand crafted problems with their respective solution. It also includes more than 2000 MCQs for thorough practice. This book provides the alternative and smarter solutions to get correct answers in lesser time to crack CAT. This book is highly useful for not only for management entrances but for other competitive examinations. With so many features this book is a complete preparatory guide for those who have aim to score high in CAT.










Educative JEE Mathematics


Book Description




The Pearson Guide to Quantitative Aptitude for CAT 2/e


Book Description

The Pearson Guide to Quantitative Aptitude for CAT 2/e has everything you need to secure a top score in the quantitative aptitude papers of the CAT and other MBA entrance examinations. Written in a student-friendly style, this book explains concepts in a concise manner and includes numerous examples and worked-out problems. It also contains ample practice problems, scientifically designed and arranged in four levels (in an increasing order of difficulty). The text also contains a chapter on Vedic mathematics, which provides unique time-saving and easy techniques for complex calculations.




Principles, Methods & Techniques Of Teac


Book Description

This Book attempts to make a comprehensive and critical exposition of all the facets of teaching. It evaluates the comparative soundness of the Principles, Methods, Techniques and Devices of Teaching. The chief accent of the book is on helping teachers to teach better. The objective is strictly utilitarian and is designed to serve as a reliable guide to the work in the classroom. The book also offers practical suggestions for making the teaching-learning process effective, inspirational & interesting. It incorporates the approaches recommended by eminent educational philosophers and practitioners. A detailed survey of the valuable teaching practices followed in India and abroad also find an important place in the book.




Artificial Intelligence in Medical Imaging


Book Description

This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.




Artificial Intelligence in Medicine


Book Description

This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.