Hasil untuk "Modern"

M. Richards, J. Scheer, W. Holm

M. Ferdman, Almutaz Adileh, Yusuf Onur Koçberber et al.

Kai Li, Christian Bienia

M. McLeay, Amar Radia, Ryland Thomas

M. Duverger

J. Als-Nielsen, D. McMorrow

G. Laumon, L. Moret-Bailly, Champs Alg ebriques

R. O'handley

R. Freeman, M. Clarkson

K. Rothman, S. Greenland, T. Lash

S. Lee, K. Pomeranz

A. Szabó

Wilfred J. Ethier

Zhou Wang, A. Bovik

This book is about objective image quality assessmentwhere the aim is to provide computational models that can automatically predict perceptual image quality. The early years of the 21st century have witnessed a tremendous growth in the use of digital images as a means for representing and communicating information. A considerable percentage of this literature is devoted to methods for improving the appearance of images, or for maintaining the appearance of images that are processed. Nevertheless, the quality of digital images, processed or otherwise, is rarely perfect. Images are subject to distortions during acquisition, compression, transmission, processing, and reproduction. To maintain, control, and enhance the quality of images, it is important for image acquisition, management, communication, and processing systems to be able to identify and quantify image quality degradations. The goals of this book are as follows; a) to introduce the fundamentals of image quality assessment, and to explain the relevant engineering problems, b) to give a broad treatment of the current state-of-the-art in image quality assessment, by describing leading algorithms that address these engineering problems, and c) to provide new directions for future research, by introducing recent models and paradigms that significantly differ from those used in the past. The book is written to be accessible to university students curious about the state-of-the-art of image quality assessment, expert industrial R&D engineers seeking to implement image/video quality assessment systems for specific applications, and academic theorists interested in developing new algorithms for image quality assessment or using existing algorithms to design or optimize other image processing applications.

J. Swim, K. Aikin, W. Hall et al.

John D. Anderson

K. Velusamy, Muralidharan Sunandhini, K. VasudevanShriram

W. Ziegler

Harikrishna VJ, Vittal Rao, Srikrishna Bhat

The $π$-series is attributed to Madhava, Gregory and Leibniz based on the chronology of its discovery. While this acknowledges the fact that Madhava of Sangamagrama an Indian mathematician who lived in Kerala in the 14th century along the banks of river Nila, was the first to discover the series, the modern day proof for the $π$-series is based on the outline of the proof given by the famous German mathematician Gottfried Wilhelm Leibniz in the 17th century, using concepts and rigorous definitions of Calculus many of which were developed after his lifetime. We extend the same benefit to Madhava's ideas and present Madhava's upapatti i.e proof for the $π$-series as given in Jyesthadeva's Yuktibhasha using modern notation and definitions. We elaborate Madhava's proof at three places (a) to prove that the arc-bit sum is same as the sum of arc-bit approximations (b) to prove convergence and (c) to concisely prove by iteration the power sum approximation. Madhava's method with appropriate changes can be applied to derive the sine and cosine series as well. Madhava also provides the correction terms to accelerate the convergence of the $π$-series. We compare the two proofs i.e Madhava's and the popular proof for $π$ which is based on Leibniz's ideas and observe that they are different since Madhava's is based on the length of the arc where as Leibniz's relies on the area under the arc and in terms of the number of concepts from advanced calculus used in the the two proofs Madhava's proof stands out for its simplicity, thus making a case for it to be appreciated, popularised and taught as the original proof of the $π$-series.

M. Fishwick

The article examines the values of education in the 21st century, characterizes the main provisions of the modern socio-cultural environment, reveals the essence of the sociocultural approach to creating an education strategy, analyzes new forms and types of education, focuses on massive open online courses, characterizes the main directions of development of Russian education: humanization, humanitarization, informatization. The article notes that one of the priority trends in the development of higher education is the preparation of students for self-education and self-organization on a student-centered (STS) basis, which corresponds to the requirements of the approach of the International Community, it is emphasized that the problem of changing educational paradigms towards a student-centered nature is being actively discussed in the world educational space. educational process, especially in the era of digitalization. The concept of SCL is part of the project “Time for a new paradigm in education: student-centered learning”. The article emphasizes that on the basis of the ideology of competence, personality and practice-oriented approaches, the choice of forms, means and methods of teaching is carried out. A special role in solving this issue is assigned to the organization of independent work of students, which contributes to the formation of an active student personality and his motivation, the development of the ability to self-education and self-organization. As for school education, it was previously noted in the literature: in the lower grades, the volume of independent work is small, the main part of the lesson is under the guidance of the teacher, and in the senior grades the amount of independent work is large, and a small part of the lesson is carried out under the guidance of the teacher. Currently, it is noted that the amount of independent work is large in all classes. If earlier we were talking about the leading teaching method explanatory and illustrative, now the new standards are proclaimed as the leading method - the activity method.