Nanofluids are solid-liquid composite material consisting of solid nanoparticles suspended in liquid with enhanced thermal properties. This book introduces basic fluid mechanics, conduction and convection in fluids, along with nanomaterials for nanofluids, property characterization, and outline applications of nanofluids in solar technology, machining and other special applications. Recent experiments on nanofluids have indicated significant increase in thermal conductivity compared with liquids without nanoparticles or larger particles, strong temperature dependence of thermal conductivity, and significant increase in critical heat flux in boiling heat transfer, all of which are covered in the book. Key Features Exclusive title focusing on niche engineering applications of nanofluids Contains high technical content especially in the areas of magnetic nanofluids and dilute oxide based nanofluids Feature examples from research applications such as solar technology and heat pipes Addresses heat transfer and thermodynamic features such as efficiency and work with mathematical rigor Focused in content with precise technical definitions and treatment
Master text-taming techniques and build effective text-processing applications with R About This Book Develop all the relevant skills for building text-mining apps with R with this easy-to-follow guide Gain in-depth understanding of the text mining process with lucid implementation in the R language Example-rich guide that lets you gain high-quality information from text data Who This Book Is For If you are an R programmer, analyst, or data scientist who wants to gain experience in performing text data mining and analytics with R, then this book is for you. Exposure to working with statistical methods and language processing would be helpful. What You Will Learn Get acquainted with some of the highly efficient R packages such as OpenNLP and RWeka to perform various steps in the text mining process Access and manipulate data from different sources such as JSON and HTTP Process text using regular expressions Get to know the different approaches of tagging texts, such as POS tagging, to get started with text analysis Explore different dimensionality reduction techniques, such as Principal Component Analysis (PCA), and understand its implementation in R Discover the underlying themes or topics that are present in an unstructured collection of documents, using common topic models such as Latent Dirichlet Allocation (LDA) Build a baseline sentence completing application Perform entity extraction and named entity recognition using R In Detail Text Mining (or text data mining or text analytics) is the process of extracting useful and high-quality information from text by devising patterns and trends. R provides an extensive ecosystem to mine text through its many frameworks and packages. Starting with basic information about the statistics concepts used in text mining, this book will teach you how to access, cleanse, and process text using the R language and will equip you with the tools and the associated knowledge about different tagging, chunking, and entailment approaches and their usage in natural language processing. Moving on, this book will teach you different dimensionality reduction techniques and their implementation in R. Next, we will cover pattern recognition in text data utilizing classification mechanisms, perform entity recognition, and develop an ontology learning framework. By the end of the book, you will develop a practical application from the concepts learned, and will understand how text mining can be leveraged to analyze the massively available data on social media. Style and approach This book takes a hands-on, example-driven approach to the text mining process with lucid implementation in R.
The archetype of 'my enemy's enemy is my friend', India's political and economic presence in Afghanistan is often viewed as a Machiavellian ploy aimed against Pakistan. Challenging deeply held beliefs about an India-Pakistan proxy war, this work offers a nuanced explanation of India's strategic intent and actions, which is critical to resolving the seemingly unending war in Afghanistan, as well as wider bilateral disputes between the two South Asian rivals
India’s near east encompasses Bangladesh, Myanmar and the Indian states of the ‘Northeast’—Arunachal Pradesh, Sikkim, Assam, Nagaland, Manipur, Meghalaya, Tripura and Mizoram. Celebrated as a theatre of geo-economic connectivity typified by India’s ‘Act East’ policy, the region is key not only to India’s great-power rivalry with China, which first boiled over in the 1962 war, but to the idea(s) of India itself. It is also one of the most intricately partitioned lands anywhere on Earth. Rent by communal and class violence, the region has birthed extreme forms of religious and ethnic nationalisms and communist movements. The Indian state’s survival instinct and pursuit of regional hegemony have only accentuated such extremes. This book scripts a new history of India’s eastward-looking diplomacy and statecraft. Narrated against the backdrop of separatist resistance within India’s own northeastern states, as well as rivalry with Beijing and Islamabad in Yangon and Dhaka, it offers a simple but compelling argument. The aspirations of ‘Act East’ mask an uncomfortable truth: India privileges political stability over economic opportunity in this region. In his chronicle of a state’s struggle to overcome war, displacement and interventionism, Avinash Paliwal lays bare the limits of independent India’s influence in its near east.
Besides Physical, Physiological, Biological, Sociological And Technical Aspects, Success In Sports Also Requires Some Psychological Conditioning In Order To Perform At The Highest Level. In A Highly Competitive Environment Of Modern Sporting World, The Psychological Characteristic Of A Player Is Equally Important For Achieving Success. It Is Believed That Sports Performance Is Dependent Upon So Many Factors In Which Psychological Preparedness Is One Of The Most Important Feature Identified Through Various Research Which Plays A Major Part In Sporting Success.
Information Technology is one of the fastest evolving and widely spreading disciplines impacting our personal and professional lives across business, and social domains. Customers are looking for hassle-free, better, faster and cost effective IT solutions to solve their problems. Lean has emerged as an innovative business management system capable to deliver higher customer value. After grand success of lean in manufacturing and various service sectors, now Lean IT is being adopted by progressive IT organizations to enhance their global competitiveness and growth. Lean IT is the extension of lean manufacturing and lean service principles to the development and management of IT services. Its central concern, in the context of IT is to create value for the customers and wealth for IT organizations through elimination of waste by improving processes, people, and work culture. This book is written by a team of two management consultants; one with hands-on expertise of Lean in manufacturing and service organizations and another with expertise in IT Management implementation. The purpose of this book is to trigger lean thinking in IT professionals.
Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer estimators. Further, it explains how to use TensorFlow 2.0 API to build machine learning and deep learning models for image classification using the standard as well as custom parameters. You'll review sequence predictions, saving, serving, deploying, and standardized datasets, and then deploy these models to production. All the code presented in the book will be available in the form of executable scripts at Github which allows you to try out the examples and extend them in interesting ways. What You'll LearnReview the new features of TensorFlow 2.0Use TensorFlow 2.0 to build machine learning and deep learning models Perform sequence predictions using TensorFlow 2.0Deploy TensorFlow 2.0 models with practical examples Who This Book Is For Data scientists, machine and deep learning engineers.
This book presents novel research techniques, algorithms, methodologies and experimental results for high level power estimation and power aware high-level synthesis. Readers will learn to apply such techniques to enable design flows resulting in shorter time to market and successful low power ASIC/FPGA design.
Plastic is one of the widely used polymers around the globe since its discovery. It is highly impossible to think the ease of life without the aid of plastic. Every year billion tons of plastic waste gets accumulated in the environment and leads to death of both marine and terrestrial animals. Plastic is very durable and needs around 1000 years to degrade under the natural environment. The present book illustrates the importance and significance of the bioremediation to tackle the problem of plastic waste. Previously, we have reported elite rhizobacterial isolates (Lysinibacillus fusiformis strain VASB14/WL and Bacillus cereus strain VASB1/TS) of Avicennia marina Vierh (Forsk.) from the West Coast of India with the potential to degrade plastic (polythene). The present book attempted to address the bioremediation scenario of plastic waste (including micro plastic) using microbes with bacteria in particular. Various strategies used to tackle with the plastic waste were highlighted with case studies of plastic waste management, including in vitro, in situ and ex situ with a special reference to biodegradation technology. After the biodegradation of the plastic using microbes, the generated plastic (polythene) degradation products (PE-DPs) were also documented using GC-MS technique followed by their deleterious effect on both animal and plant systems. The book also enhances the awareness of the plastic-free society and also suggests some alternative materials to be used instead of plastic. Lastly, the book suggests/recommends the strategies to be followed by the lawmakers in the government organizations/non-government organizations/social organizations to frame the regulations and guidelines to implement at mass level to reduce the generation of plastic waste.
The author explores and analyzes the digital and social media dynamics for virtual world, including the mechanism involved in bringing targeted traffic and increasing brand awareness in the real-time programmatic and algorithmic world of communication, where the new digital world is progressively being propelled by the blockchain-enabled social media platforms. The intelligent corporates are becoming data-driven and AI-powered enterprises to compete, differentiate, and successfully reach consumers. This book develops a critical understanding of the digital marketing landscape. The author explores and examines the various aspects of digital marketing process and their implications. It takes an in-depth look at what firms can do to pioneer and successfully execute the digital marketing innovations in a mobile-synchronized and mobile-optimized world for building and sustaining the online customer relationship and loyalty. The author explores and analyzes the digital and social media dynamics for virtual world, including the mechanism involved in bringing targeted traffic and increasing brand awareness in the real-time programmatic and algorithmic world of communication, where the new digital world is progressively being propelled by the blockchain-enabled social media platforms. In this connected world, the consumers are connected with portals of interactive multi-smart shared interfaces. Kapoor discusses and demonstrates that the practitioners should direct their endeavors more toward fostering the positive brand image and the consumer-based brand equity than short-range transactions. This book is intended for a broad audience including students and professors in graduate business schools, and practicing business executives. The goal is to inform management practice and help current and future business leaders navigate through the competitive storms unleashed by digital technology for reaching market segments, for conducting market research, and for managing content, no matter what industry it is.
The book contains the full concept of seed industry in India. Right from what is seed, how it is propagated and how seed is developed as foundation or certified seed for production. The book contains guide to history of seed industry, allotment of breeder seed, seed multiplication, plant and machinery detail, how do they work. what is seed processing, seed storage, seed testing, certified seed packing and the important thing that how to calculate the processing expenditure on the finished material, i.e. certified or foundation seed. Contains Contract farming, seed testing, seed Act, Seed Rule, notified verities and their notification Seed Control Order addresses of state seed certification agencies, State seeds Corporations, Registered seed processing plants under different certification agencies and their codes India wide. Project on development of new processing plant. Over all it is viewed as the complete detail on seed industry.
Pediatricians in the Unites States and around the World continue to face a myriad of global health threats affecting child and adolescent health including: 1) infectious diseases of poverty [e.g. human immunodeficiency virus (HIV), tuberculosis, malaria, and neglected tropical diseases] in low-and middle-income countries (LMIC), especially in sub Saharan Africa; 2) emerging and reemerging infectious diseases (such as Ebola); 3) rise of non-communicable diseases (e.g. common mental disorders); 4) unintentional injuries; and 5) environmental health hazards (e.g. climate change). Despite the promising news about rapid declines in maternal and child mortality in the era of Millennium Development Goals (MDGs), which originated from the United Nation (UN) Millennium Declaration in 2000, only 20% and 7% of LMIC are currently on track to attain the maternal and child mortality targets. For example, 44% of deaths in children younger than 5 years occur in neonates. Besides discovery of life-saving interventions (e.g. development of new and improved vaccines) for maternal and child health, we also need to do a better job at bridging the knowledge-implementation gap and increase the effectiveness of proven interventions. For example, despite the availability of effective vaccines to prevent pneumococcal pneumonia, rotavirus gastroenteritis, and human papilloma virus-related diseases (e.g. cervical cancer), use of these vaccines remain suboptimal in LMIC. We need to recognize that global health is also local public health. For example, improving access, equity and quality of care for orphans and vulnerable children, immigrant and newly arrived refugee children in the U.S. remains a challenge. Timely access to psychiatric care for children and adolescents with mental illness is a major concern. The explosion of new age technology (such as the internet) also poses a considerable risk to children and adolescents. Pediatricians also need to be aware of diverse socio-cultural determinants of health and ethical issues in global health service and delivery. This issue of Pediatric Clinics of North America aims to address the above crucial global health challenges affecting children and adolescents. As practicing pediatricians, we have the unique opportunity to influence local and global public health. In the post-MDG era (beyond 2015), collaborative partnerships between various disciplines and across research, education and service is vital to reduce health inequities in children worldwide.
DESCRIPTION Our book is divided into several useful concepts and techniques of machine learning. This book serves as a valuable resource for individuals seeking to deepen their understanding of advanced topics in this field. Learn about various learning algorithms, including supervised, unsupervised, and reinforcement learning, and their mathematical foundations. Discover the significance of feature engineering and selection for enhancing model performance. Understand model evaluation metrics like accuracy, precision, recall, and F1-score, along with techniques like cross-validation and grid search for model selection. Explore ensemble learning methods along with deep learning, unsupervised learning, time series analysis, and reinforcement learning techniques. Lastly, uncover real-world applications of the machine and deep learning algorithms. After reading this book, readers will gain a comprehensive understanding of machine learning fundamentals and advanced techniques. With this knowledge, readers will be equipped to tackle real-world problems, make informed decisions, and develop innovative solutions using machine and deep learning algorithms. KEY FEATURES ● Basic understanding of machine learning algorithms via MATLAB, R, and Python. ● Inclusion of examples related to real-world problems, case studies, and questions related to futuristic technologies. ● Adding futuristic technologies related to machine learning and deep learning. WHAT YOU WILL LEARN ● Ability to tackle complex machine learning problems. ● Understanding of foundations, algorithms, ethical issues, and how to implement each learning algorithm for their own use/ with their data. ● Efficient data analysis for real-time data will be understood by researchers/ students. ● Using data analysis in near future topics and cutting-edge technologies. WHO THIS BOOK IS FOR This book is ideal for students, professors, and researchers. It equips industry experts and academics with the technical know-how and practical implementations of machine learning algorithms. TABLE OF CONTENTS 1. Introduction to Machine Learning 2. Statistical Analysis 3. Linear Regression 4. Logistic Regression 5. Decision Trees 6. Random Forest 7. Rule-Based Classifiers 8. Naïve Bayesian Classifier 9. K-Nearest Neighbors Classifiers 10. Support Vector Machine 11. K-Means Clustering 12. Dimensionality Reduction 13. Association Rules Mining and FP Growth 14. Reinforcement Learning 15. Applications of ML Algorithms 16. Applications of Deep Learning 17. Advance Topics and Future Directions
Reinventing Financial Regulation offers an analysis of the fundamental flaws that plague the current system of financial regulation, one built around ideas of "risk-sensitivity" and "capital adequacy." Author Avinash Persaud argues that while some sensible reforms have been introduced, a fresh approach—centered on risk capacity—is required. When the entire regime is compromised, simply slapping bandages on each new wound will do nothing to cure the underlying disease. Reinventing Financial Regulation goes beyond an urgent call to fix our profoundly troubled and damaged financial markets. It is a blueprint for an effective financial regulation system that could very well save the future of finance. What would a well-regulated financial system look like? Until now, policymakers, financial experts, and leading academics have been content to avoid facing this question head–on. We have been offered piecemeal reforms that ultimately leave the global financial system exposed to different versions of the same risks that so recently brought it to its knees. The world economy literally cannot afford to dodge this question any longer. Persaud's goal to bring clarity and a powerful simplicity to the financial regulation process results in a systematic and apolitical framework for fixing the world's fractured financial industry and transforming its regulation—not just for today's financial climate, but once and for all.
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