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Bioinformatics and Computational Biology Solutions Using R and Bioconductor
Bioconductor is a widely used open source and open development software project for the analysis and comprehension of data arising from high-throughput experimentation in genomics and molecular biology. Bioconductor is rooted in the open source statistical computing environment R. This volume's coverage is broad and ranges across most of the key capabilities of the Bioconductor project, including: Importation and preprocessing of high-throughput data from microarray, proteomic, and flow cytometry platforms / Curation and delivery of biological metadata for use in statistical modeling and interpretation. / Statistical analysis of high-throughput data, including machine learning and visualization,modeling and visualization of graphs and networks. This book is a dynamic document. Code underlying all of the computations that are shown is made available on a companion website, and readers can reproduce every number, figure, and table on their own computers.
Big Data Intelligence for Smart Applications
Presents the latest discoveries in the field of machine intelligence and big data Proposes many case studies and applications of computational and Big data Combines theory and practice so that readers of the few books (beginners or experts)
Big data and artificial intelligence in digital finance : Increasing personalization and trust in digital finance using big data and AI
This book presents how cutting-edge digital technologies like Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTechs, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also introduces some of the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data.
Big data analytics and machine intelligence in biomedical and health informatics : Concepts, methodologies, tools and applications
Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. Covers the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).
Big Data – BigData 2020; 9th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Bézier and Splines in image processing and machine vision
Digital image processing and machine vision have grown considerably during the last few decades. Of the various techniques, developed so far splines play a positive and significant role in many of them. This book deals with various image processing and machine vision problems efficiently with splines.
Beyond the Worst-Case Analysis of Algorithms
There are no silver bullets in algorithm design, and no single algorithmic idea is powerful and flexible enough to solve every computational problem. Nor are there silver bullets in algorithm analysis, as the most enlightening method for analyzing an algorithm often depends on the problem and the application. However, typical algorithms courses rely almost entirely on a single analysis framework, that of worst-case analysis, wherein an algorithm is assessed by its worst performance on any input of a given size. The purpose of this book is to popularize several alternatives to worst-case analysis and their most notable algorithmic applications, from clustering to linear programming to neural network training. Forty leading researchers have contributed introductions to different facets of this field, emphasizing the most important models and results, many of which can be taught in lectures to beginning graduate students in theoretical computer science and machine learning.
Beginning deep learning with TensorFlow : Work with Keras, MNIST data sets, and advanced neural networks
Stats with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks and working with a wide variety of neural network types such as GANs and RNNs. Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer! You will: Develop using deep learning algorithms Build deep learning models using TensorFlow 2 Create classification systems and other, practical deep learning applications
Bearing Witness : Ruth Harrison and British Farm Animal Welfare (1920–2000)
This book is the biography of one of Britain’s foremost animal welfare campaigners and of the world of activism, science, and politics she inhabited. In 1964, Ruth Harrison’s bestseller Animal Machines triggered a gear change in modern animal protection by popularising the term ‘factory farming’ alongside a new way of thinking about animal welfare.
Basic Python for Data Management, Finance, and Marketing : Advance Your Career by Learning the Most Powerful Analytical Tool
Learn how to gather, manipulate, and analyze data with Python. This book is a practical guide to help you get started with Python from ground zero and to the point where you can use coding for everyday tasks. Python is used in all aspects of financial industry, from algo trading, reporting and risk management to building valuations models and predictive machine learning programs. You will: Get started with Python from square one / Extend what's possible on excel with Python / Automate tasks with Python / Analyze data more precisely
Axial flux permanent magnet brushless machines
This book deals with the analysis, construction, design, control and applications of AFPM machines. The authors present their own research results, as well as significant research contributions made by others.
Axial flux permanent magnet brushless machines
Axial Flux Permanent Magnet (AFPM) brushless machines are modern electrical machines with a lot of advantageous merits over their conventional counterparts. They are increasingly used in power generation, domestic appliances, industrial drives, electric vehicles, and marine propulsion drives and many other applications. This book deals with the analysis, construction, design, optimisation, control and applications of AFPM machines. The authors present their own research results, as well as significant research contributions made by others. This monograph will be of interest to electrical engineers and other engineers involved in the design and application of AFPM brushless machine drives. It will be an important resource for researchers and graduate students in the field of electrical machine and drives.
Automatic Autocorrelation and Spectral Analysis
It takes advantage of greater computing power and robust algorithms to produce enough candidate models to be sure of providing a suitable candidate for given data. Improved order selection quality guarantees that one of the best (and often the best) will be selected automatically. The data themselves suggest their best representation. Should the analyst wish to intervene, alternatives can be provided. Written for graduate signal processing students and for researchers and engineers using time series analysis for practical applications ranging from breakdown prevention in heavy machinery to measuring lung noise for medical diagnosis.
Automated technology for verification and analysis ; 18th International Symposium, ATVA 2020, Hanoi, Vietnam, October 19–23, 2020, Proceedings
This book constitutes the refereed proceedings of the 18th International Symposium on Automated Technology for Verification and Analysis, ATVA 2020, held in Hanoi, Vietnam, in October 2020. The 27 regular papers presented together with 5 tool papers and 2 invited papers were carefully reviewed and selected from 75 submissions.
Automated machine learning : Methods, systems, challenges
This book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself.
Assistive technologies, robotics, and automated machines in the health domain
The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.
Assembly language for x86 processors ; 8th ed.
Focuses on its primary goal, to teach students how to write and debug programs at the machine level. It will never replace a complete book on computer architecture, but it does give students the first-hand experience of writing software in an environment that teaches them how a computer works. Our premise is that students retain knowledge better when theory is combined with experience. In an engineering course, students construct prototypes; in a computer architecture course, students should write machine-level programs.
Assembly Language for x86 Processors ; 7th ed.
Focuses on its primary goal, to teach students how to write and debug programs at the machine level. It will never replace a complete book on computer architecture, but it does give students the first-hand experience of writing software in an environment that teaches them how a computer works. Our premise is that students retain knowledge better when theory is combined with experience. In an engineering course, students construct prototypes; in a computer architecture course, students should write machine-level programs.
Artificial neural networks in Pattern Recognition ; 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2–4, 2020, Proceedings
This book constitutes the refereed proceedings of the 9th IAPR TC3 International Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2020, held in Winterthur, Switzerland, in September 2020. The conference was held virtually due to the COVID-19 pandemic. The 22 revised full papers presented were carefully reviewed and selected from 34 submissions. The papers present and discuss the latest research in all areas of neural network-and machine learning-based pattern recognition. They are organized in two sections: learning algorithms and architectures, and applications.
Artificial neural networks in Pattern Recognition ; 3d IAPR Workshop, ANNPR 2008 Paris, France, July 2-4, 2008 Proceedings
Constitutes the refereed proceedings of the Third TC3 IAPR Workshop on Artificial Neural Networks in Pattern Recognition, ANNPR 2008, held in Paris, France, in July 2008.
