Modeling And Optimization Of Signals Using Machine Learning Techniques

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Modeling and Optimization of Signals Using Machine Learning Techniques

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Author : Chandra Singh
Publisher : John Wiley & Sons
ISBN 13 : 1119847699
Total Pages : 421 pages
Book Rating : 4.1/5 (198 download)

Book Synopsis Modeling and Optimization of Signals Using Machine Learning Techniques by : Chandra Singh

Download or read book Modeling and Optimization of Signals Using Machine Learning Techniques written by Chandra Singh and published by John Wiley & Sons. This book was released on 2024-08-23 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the power of machine learning to revolutionize signal processing and optimization with cutting-edge techniques and practical insights in this outstanding new volume from Scrivener Publishing. Modeling and Optimization of Signals using Machine Learning Techniques is designed for researchers from academia, industries, and R&D organizations worldwide who are passionate about advancing machine learning methods, signal processing theory, data mining, artificial intelligence, and optimization. This book addresses the role of machine learning in transforming vast signal databases from sensor networks, internet services, and communication systems into actionable decision systems. It explores the development of computational solutions and novel models to handle complex real-world signals such as speech, music, biomedical data, and multimedia. Through comprehensive coverage of cutting-edge techniques, this book equips readers with the tools to automate signal processing and analysis, ultimately enhancing the retrieval of valuable information from extensive data storage systems. By providing both theoretical insights and practical guidance, the book serves as a comprehensive resource for researchers, engineers, and practitioners aiming to harness the power of machine learning in signal processing. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.

Fluorescent Nanodiamonds

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Author : Huan-Cheng Chang
Publisher : John Wiley & Sons
ISBN 13 : 1119477085
Total Pages : 294 pages
Book Rating : 4.1/5 (194 download)

Book Synopsis Fluorescent Nanodiamonds by : Huan-Cheng Chang

Download or read book Fluorescent Nanodiamonds written by Huan-Cheng Chang and published by John Wiley & Sons. This book was released on 2018-11-12 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: The most comprehensive reference on fluorescent nanodiamond physical and chemical properties and contemporary applications Fluorescent nanodiamonds (FNDs) have drawn a great deal of attention over the past several years, and their applications and development potential are proving to be manifold and vast. The first and only book of its kind, Fluorescent Nanodiamonds is a comprehensive guide to the basic science and technical information needed to fully understand the fundamentals of FNDs and their potential applications across an array of domains. In demonstrating the importance of FNDs in biological applications, the authors bring together all relevant chemistry, physics, materials science and biology. Nanodiamonds are produced by powerful cataclysmic events such as explosions, volcanic eruptions and meteorite impacts. They also can be created in the lab by high-pressure high-temperature treatment of graphite or detonating an explosive in a reactor vessel. A single imperfection can give a nanodiamond a specific, isolated color center which allows it to function as a single, trapped atom. Much smaller than the thickness of a human hair, a nanodiamond can have a huge surface area that allows it to bond with a variety of other materials. Because of their non-toxicity, nanodiamonds may be useful in biomedical applications, such as drug delivery and gene therapy. The most comprehensive reference on a topic of rapidly increasing interest among academic and industrial researchers across an array of fields Includes numerous case studies and practical examples from many areas of research and industrial applications, as well as fascinating and instructive historical perspectives Each chapter addresses, in-depth, a single integral topic including the fundamental properties, synthesis, mechanisms and functionalisation of FNDs The first book published by the key patent holder with his research group in the field of FNDs Fluorescent Nanodiamonds is an important working resource for a broad range of scientists and engineers in industry and academia. It will also be a welcome reference for instructors in chemistry, physics, materials science, biology and related fields.

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

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Author : Nilanjan Dey
Publisher : Academic Press
ISBN 13 : 012816087X
Total Pages : 348 pages
Book Rating : 4.1/5 (281 download)

Book Synopsis Machine Learning in Bio-Signal Analysis and Diagnostic Imaging by : Nilanjan Dey

Download or read book Machine Learning in Bio-Signal Analysis and Diagnostic Imaging written by Nilanjan Dey and published by Academic Press. This book was released on 2018-11-30 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as PCA, SVM, techniques, Naive Bayes, Neural Network, Decision trees, and Association Rule Mining are among the approaches presented. The design of high accuracy decision support systems assists and eases the job of healthcare practitioners and suits a variety of applications. Integrating Machine Learning (ML) technology with human visual psychometrics helps to meet the demands of radiologists in improving the efficiency and quality of diagnosis in dealing with unique and complex diseases in real time by reducing human errors and allowing fast and rigorous analysis. The book's target audience includes professors and students in biomedical engineering and medical schools, researchers and engineers. - Examines a variety of machine learning techniques applied to bio-signal analysis and diagnostic imaging - Discusses various methods of using intelligent systems based on machine learning, soft computing, computer vision, artificial intelligence and data mining - Covers the most recent research on machine learning in imaging analysis and includes applications to a number of domains

Machine Learning for Algorithmic Trading

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Author : Stefan Jansen
Publisher : Packt Publishing Ltd
ISBN 13 : 1839216786
Total Pages : 822 pages
Book Rating : 4.8/5 (392 download)

Book Synopsis Machine Learning for Algorithmic Trading by : Stefan Jansen

Download or read book Machine Learning for Algorithmic Trading written by Stefan Jansen and published by Packt Publishing Ltd. This book was released on 2020-07-31 with total page 822 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This revised and expanded second edition enables you to build and evaluate sophisticated supervised, unsupervised, and reinforcement learning models. This book introduces end-to-end machine learning for the trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. It illustrates this by using examples ranging from linear models and tree-based ensembles to deep-learning techniques from cutting edge research. This edition shows how to work with market, fundamental, and alternative data, such as tick data, minute and daily bars, SEC filings, earnings call transcripts, financial news, or satellite images to generate tradeable signals. It illustrates how to engineer financial features or alpha factors that enable an ML model to predict returns from price data for US and international stocks and ETFs. It also shows how to assess the signal content of new features using Alphalens and SHAP values and includes a new appendix with over one hundred alpha factor examples. By the end, you will be proficient in translating ML model predictions into a trading strategy that operates at daily or intraday horizons, and in evaluating its performance. What you will learnLeverage market, fundamental, and alternative text and image dataResearch and evaluate alpha factors using statistics, Alphalens, and SHAP valuesImplement machine learning techniques to solve investment and trading problemsBacktest and evaluate trading strategies based on machine learning using Zipline and BacktraderOptimize portfolio risk and performance analysis using pandas, NumPy, and pyfolioCreate a pairs trading strategy based on cointegration for US equities and ETFsTrain a gradient boosting model to predict intraday returns using AlgoSeek's high-quality trades and quotes dataWho this book is for If you are a data analyst, data scientist, Python developer, investment analyst, or portfolio manager interested in getting hands-on machine learning knowledge for trading, this book is for you. This book is for you if you want to learn how to extract value from a diverse set of data sources using machine learning to design your own systematic trading strategies. Some understanding of Python and machine learning techniques is required.

Machine Learning for Signal Processing

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Author : Max A. Little
Publisher : Oxford University Press, USA
ISBN 13 : 0198714939
Total Pages : 378 pages
Book Rating : 4.1/5 (987 download)

Book Synopsis Machine Learning for Signal Processing by : Max A. Little

Download or read book Machine Learning for Signal Processing written by Max A. Little and published by Oxford University Press, USA. This book was released on 2019 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.

Mobile Computing and Sustainable Informatics

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Author : Subarna Shakya
Publisher : Springer Nature
ISBN 13 : 9819908353
Total Pages : 792 pages
Book Rating : 4.8/5 (199 download)

Book Synopsis Mobile Computing and Sustainable Informatics by : Subarna Shakya

Download or read book Mobile Computing and Sustainable Informatics written by Subarna Shakya and published by Springer Nature. This book was released on 2023-05-26 with total page 792 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2022) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during January 11–12, 2023. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices to personalized, embedded, and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models, and advanced informatics that support the symbiosis of mobile computing and sustainable informatics.

Financial Signal Processing and Machine Learning

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Author : Ali N. Akansu
Publisher : John Wiley & Sons
ISBN 13 : 1118745639
Total Pages : 312 pages
Book Rating : 4.1/5 (187 download)

Book Synopsis Financial Signal Processing and Machine Learning by : Ali N. Akansu

Download or read book Financial Signal Processing and Machine Learning written by Ali N. Akansu and published by John Wiley & Sons. This book was released on 2016-04-21 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: Highlights signal processing and machine learning as key approaches to quantitative finance. Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.

Engine Modeling and Simulation

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Author : Avinash Kumar Agarwal
Publisher : Springer Nature
ISBN 13 : 9811686181
Total Pages : 368 pages
Book Rating : 4.8/5 (116 download)

Book Synopsis Engine Modeling and Simulation by : Avinash Kumar Agarwal

Download or read book Engine Modeling and Simulation written by Avinash Kumar Agarwal and published by Springer Nature. This book was released on 2021-12-16 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the simulation and modeling of internal combustion engines. The contents include various aspects of diesel and gasoline engine modeling and simulation such as spray, combustion, ignition, in-cylinder phenomena, emissions, exhaust heat recovery. It also explored engine models and analysis of cylinder bore piston stresses and temperature effects. This book includes recent literature and focuses on current modeling and simulation trends for internal combustion engines. Readers will gain knowledge about engine process simulation and modeling, helpful for the development of efficient and emission-free engines. A few chapters highlight the review of state-of-the-art models for spray, combustion, and emissions, focusing on the theory, models, and their applications from an engine point of view. This volume would be of interest to professionals, post-graduate students involved in alternative fuels, IC engines, engine modeling and simulation, and environmental research.

Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation

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Author : Lars Svensson
Publisher : Springer Science & Business Media
ISBN 13 : 3540959475
Total Pages : 474 pages
Book Rating : 4.5/5 (49 download)

Book Synopsis Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation by : Lars Svensson

Download or read book Integrated Circuit and System Design. Power and Timing Modeling, Optimization and Simulation written by Lars Svensson and published by Springer Science & Business Media. This book was released on 2009-02-13 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of 18th International Workshop on Power and Timing Modeling, Optimization and Simulation, PATMOS 2008, featuring Integrated Circuit and System Design, held in Lisbon, Portugal during September 10-12, 2008. The 31 revised full papers and 10 revised poster papers presented together with 3 invited talks and 4 papers from a special session on reconfigurable architectures were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on low-leakage and subthreshold circuits, low-power methods and models, arithmetic and memories, variability and statistical timing, synchronization and interconnect, power supplies and switching noise, low-power circuits; reconfigurable architectures, circuits and methods, power and delay modeling, as well as power optimizations addressing reconfigurable architectures.

Machine Learning Algorithms for Signal and Image Processing

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Author : Suman Lata Tripathi
Publisher : John Wiley & Sons
ISBN 13 : 1119861829
Total Pages : 516 pages
Book Rating : 4.1/5 (198 download)

Book Synopsis Machine Learning Algorithms for Signal and Image Processing by : Suman Lata Tripathi

Download or read book Machine Learning Algorithms for Signal and Image Processing written by Suman Lata Tripathi and published by John Wiley & Sons. This book was released on 2022-12-01 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

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Author : Abdulhamit Subasi
Publisher : Academic Press
ISBN 13 : 0128176733
Total Pages : 458 pages
Book Rating : 4.1/5 (281 download)

Book Synopsis Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques by : Abdulhamit Subasi

Download or read book Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and published by Academic Press. This book was released on 2019-03-16 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. - Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction - Explains how to apply machine learning techniques to EEG, ECG and EMG signals - Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series

Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0

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Author : Dubey, Archi
Publisher : IGI Global
ISBN 13 :
Total Pages : 468 pages
Book Rating : 4.3/5 (693 download)

Book Synopsis Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 by : Dubey, Archi

Download or read book Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 written by Dubey, Archi and published by IGI Global. This book was released on 2024-07-18 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: The healthcare industry is increasingly complex, demanding personalized treatments and efficient operational processes. Traditional research methods need help to keep pace with these demands, often leading to inefficiencies and suboptimal outcomes. Integrating digital twin technology presents a promising solution to these challenges, offering a virtual platform for modeling and simulating complex healthcare scenarios. However, the full potential of digital twins still needs to be explored mainly due to a lack of comprehensive guidance and practical insights for researchers and practitioners. Exploring the Advancements and Future Directions of Digital Twins in Healthcare 6.0 is not just a theoretical exploration. It is a practical guide that bridges the gap between theory and practice, offering real-world case studies, best practices, and insights into personalized medicine, real-time patient monitoring, and healthcare process optimization. By equipping you with the knowledge and tools needed to effectively integrate digital twins into your healthcare research and operations, this book is a valuable resource for researchers, academicians, medical practitioners, scientists, and students.

Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications

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Author : Long Jin
Publisher : Frontiers Media SA
ISBN 13 : 2832552013
Total Pages : 301 pages
Book Rating : 4.8/5 (325 download)

Book Synopsis Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications by : Long Jin

Download or read book Dynamic Neural Networks for Robot Systems: Data-Driven and Model-Based Applications written by Long Jin and published by Frontiers Media SA. This book was released on 2024-07-24 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network control has been a research hotspot in academic fields due to the strong ability of computation. One of its wildly applied fields is robotics. In recent years, plenty of researchers have devised different types of dynamic neural network (DNN) to address complex control issues in robotics fields in reality. Redundant manipulators are no doubt indispensable devices in industrial production. There are various works on the redundancy resolution of redundant manipulators in performing a given task with the manipulator model information known. However, it becomes knotty for researchers to precisely control redundant manipulators with unknown model to complete a cyclic-motion generation CMG task, to some extent. It is worthwhile to investigate the data-driven scheme and the corresponding novel dynamic neural network (DNN), which exploits learning and control simultaneously. Therefore, it is of great significance to further research the special control features and solve challenging issues to improve control performance from several perspectives, such as accuracy, robustness, and solving speed.

Advanced Prognostic Predictive Modelling in Healthcare Data Analytics

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Author : Sudipta Roy
Publisher : Springer Nature
ISBN 13 : 9811605386
Total Pages : 317 pages
Book Rating : 4.8/5 (116 download)

Book Synopsis Advanced Prognostic Predictive Modelling in Healthcare Data Analytics by : Sudipta Roy

Download or read book Advanced Prognostic Predictive Modelling in Healthcare Data Analytics written by Sudipta Roy and published by Springer Nature. This book was released on 2021-04-22 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses major technical advancements and research findings in the field of prognostic modelling in healthcare image and data analysis. The use of prognostic modelling as predictive models to solve complex problems of data mining and analysis in health care is the feature of this book. The book examines the recent technologies and studies that reached the practical level and becoming available in preclinical and clinical practices in computational intelligence. The main areas of interest covered in this book are highest quality, original work that contributes to the basic science of processing, analysing and utilizing all aspects of advanced computational prognostic modelling in healthcare image and data analysis.

Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing

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Author : Rajesh Kumar Tripathy
Publisher : CRC Press
ISBN 13 : 1040028772
Total Pages : 227 pages
Book Rating : 4.0/5 (4 download)

Book Synopsis Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing by : Rajesh Kumar Tripathy

Download or read book Artificial Intelligence Enabled Signal Processing based Models for Neural Information Processing written by Rajesh Kumar Tripathy and published by CRC Press. This book was released on 2024-06-06 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides details regarding the application of various signal processing and artificial intelligence-based methods for electroencephalography data analysis. It will help readers in understanding the use of electroencephalography signals for different neural information processing and cognitive neuroscience applications. The book: Covers topics related to the application of signal processing and machine learning-based techniques for the analysis and classification of electroencephalography signals Presents automated methods for detection of neurological disorders and other applications such as cognitive task recognition, and brain-computer interface Highlights the latest machine learning and deep learning methods for neural signal processing Discusses mathematical details for the signal processing and machine learning algorithms applied for electroencephalography data analysis Showcases the detection of dementia from electroencephalography signals using signal processing and machine learning-based techniques It is primarily written for senior undergraduates, graduate students, and researchers in the fields of electrical engineering, electronics and communications engineering, and biomedical engineering.

Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication

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Author : Anuradha Tomar
Publisher : Springer Nature
ISBN 13 : 9811928282
Total Pages : 774 pages
Book Rating : 4.8/5 (119 download)

Book Synopsis Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication by : Anuradha Tomar

Download or read book Proceedings of 3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication written by Anuradha Tomar and published by Springer Nature. This book was released on 2022-09-17 with total page 774 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers presented at International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication (MARC 2021), held in Krishna Engineering College, Ghaziabad, India, during 10 – 11 December, 2021. This book discusses key concepts, challenges and potential solutions in connection with established and emerging topics in advanced computing, renewable energy and network communications.

Computational Intelligence for Signal and Image Processing

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Author : Baiyuan Ding
Publisher : Frontiers Media SA
ISBN 13 : 2832535461
Total Pages : 134 pages
Book Rating : 4.8/5 (325 download)

Book Synopsis Computational Intelligence for Signal and Image Processing by : Baiyuan Ding

Download or read book Computational Intelligence for Signal and Image Processing written by Baiyuan Ding and published by Frontiers Media SA. This book was released on 2023-10-17 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: