Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Applied Research in Uncertainty Modeling and Analysis
The application areas of uncertainty are numerous and diverse, including all fields of engineering, computer science, systems control and finance. Determining appropriate ways and methods of dealing with uncertainty has been a constant challenge. The theme for this book is better understanding and the application of uncertainty theories. This book, with invited chapters, deals with the uncertainty phenomena in diverse fields. The book is an outgrowth of the Fourth International Symposium on Uncertainty Modeling and Analysis (ISUMA), which was held at the center of Adult Education, College Park, Maryland, in September 2003. All of the chapters have been carefully edited, following a review pr...
Pattern Recognition
For more than 40 years, pattern recognition approaches are continuingly improving and have been used in an increasing number of areas with great success. This book discloses recent advances and new ideas in approaches and applications for pattern recognition. The 30 chapters selected in this book cover the major topics in pattern recognition. These chapters propose state-of-the-art approaches and cutting-edge research results. I could not thank enough to the contributions of the authors. This book would not have been possible without their support.
Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining
Augmented intelligence is an alternate approach of artificial intelligence (AI), which emphasizes AI’s assistive role. Augmented intelligence enhances human skills of reasoning in a robotic system or software by simulating expectancy, educational mining, problem solving, recollection, sequencing, and decision-making capabilities. It is based on a combination of techniques such as machine learning, deep learning and cognitive computing. This book explains artificial intelligence models that support assistive processes in different situations. The contributors aim to provide information to a diverse audience with groundbreaking developments in mathematical computing. The book presents 8 chap...
Frontiers in Radiation Oncology
The mode of action by radiation is postulated to be the production of double strand breaks of DNA. The repair of double strand breaks occurs through non homologous end joining through acetylation of histone proteins by histone acetyltransferases (HATs). The fixation of double strand breaks through HAT inhibitors is a promising application for radiation sensitization in the clinic. P53 is a tumour suppressor gene and its mutation has been implicated in 60% of human cancers. As one of the pivotal anticancer genes, P53 controls the transcription and translation of a series of genes. The kinetics of DNA double strand break generation and their co relation to P53 status, ATM and ARF activation are computed and modelled for understanding the potential of such research.
Applied Artificial Higher Order Neural Networks for Control and Recognition
In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.
Neural Information Processing
The four-volume proceedings LNCS 13108, 13109, 13110, and 13111 constitutes the proceedings of the 28th International Conference on Neural Information Processing, ICONIP 2021, which was held during December 8-12, 2021. The conference was planned to take place in Bali, Indonesia but changed to an online format due to the COVID-19 pandemic. The total of 226 full papers presented in these proceedings was carefully reviewed and selected from 1093 submissions. The papers were organized in topical sections as follows: Part I: Theory and algorithms; Part II: Theory and algorithms; human centred computing; AI and cybersecurity; Part III: Cognitive neurosciences; reliable, robust, and secure machine learning algorithms; theory and applications of natural computing paradigms; advances in deep and shallow machine learning algorithms for biomedical data and imaging; applications; Part IV: Applications.
Feature Extraction
This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. Until now there has been insufficient consideration of feature selection algorithms, no unified presentation of leading methods, and no systematic comparisons.
Artificial Higher Order Neural Networks for Modeling and Simulation
"This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Entropy Measures for Data Analysis
Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.
Political Campaigning in the Information Age
Technology and the Internet especially have brought on major changes to politics and are playing an increasingly important role in political campaigns, communications, and messaging. Political Campaigning in the Information Age increases our understanding of aspects and methods for political campaigning, messaging, and communications in the information age. Each chapter analyzes political campaigning, its methods, the effectiveness of these methods, and tools for analyzing these methods. This book will aid political operatives in increasing the effectiveness of political campaigns and communications and will be of use to researchers, political campaign staff, politicians and their staff, political and public policy analysts, political scientists, engineers, computer scientists, journalists, academicians, students, and professionals.
