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Machine Learning for Healthcare Systems Foundations and Applications

Machine Learning for Healthcare Systems Foundations and Applications

The introduction of digital technology in the healthcare industry is marked by ongoing difficulties with implementation and use. Slow progress has been made in unifying different healthcare systems and much of the world still lacks a fully integrated healthcare system. The intrinsic complexity and development of human biology as well as the differences across patients have repeatedly demonstrated the significance of the human element in the diagnosis and treatment of illnesses. But as digital technology develops healthcare providers will undoubtedly need to use it more and more to give patients the best treatment possible. The extensive use of machine learning in numerous industries including healthcare has been made possible by advancements in data technologies including storage capacity processing capability and data transit speeds. The need for a personalized medicine or precision medicine approach to healthcare has been highlighted by current trends in medicine due to the complexity of providing effective healthcare to each individual. Personalized medicine aims to identify forecast and analyze diagnostic decisions using vast volumes of healthcare data so that doctors may then apply them to each unique patient. These data may include but are not limited to information on a person’s genes or family history medical imaging data drug combinations patient health outcomes at the community level and natural language processing of pre-existing medical documentation. This book provides various insights into machine learning techniques in healthcare system data and its analysis. Recent technological advancements in the healthcare system represent cutting-edge innovations and global research successes in performance modelling analysis and applications. | Machine Learning for Healthcare Systems Foundations and Applications

GBP 99.99
1

An Introduction to Electronic Warfare; from the First Jamming to Machine Learning Techniques

An Introduction to Electronic Warfare; from the First Jamming to Machine Learning Techniques

Since its creation at the beginning of World II radars have forever transformed the practice of modern warfare. The evolution of countermeasure conducted by electronic warfare systems against radars and radars’ corresponding counter countermeasures is an intriguing technical subject. This book provides a very accessible introduction to a broad range of radar and electronic warfare technologies. The subjects covered in this book range from early radar development to later technologies such as stealthy techniques low probability of intercept radar and machine learning. Historical events are used to illustrate the principles of electronic warfare and to help readers to apprehend contexts under which radars and corresponding electronic warfare techniques were developed. | An Introduction to Electronic Warfare; from the First Jamming to Machine Learning Techniques

GBP 99.99
1

Computational and Analytic Methods in Biological Sciences Bioinformatics with Machine Learning and Mathematical Modelling

Computational and Analytic Methods in Biological Sciences Bioinformatics with Machine Learning and Mathematical Modelling

Despite major advances in healthcare over the past century the successful treatment of cancer has remained a significant challenge and cancers are the second leading cause of death worldwide behind cardiovascular disease. Early detection and survival are important issues to control cancer. The development of quantitative methods and computer technology has facilitated the formation of new models in medical and biological sciences. The application of mathematical modelling in solving many real-world problems in medicine and biology has yielded fruitful results. In spite of advancements in instrumentations technology and biomedical equipment it is not always possible to perform experiments in medicine and biology for various reasons. Thus mathematical modelling and simulation are viewed as viable alternatives in such situations and are discussed in this book. The conventional diagnostic techniques of cancer are not always effective as they rely on the physical and morphological appearance of the tumour. Early stage prediction and diagnosis is very difficult with conventional techniques. It is well known that cancers are involved in genome level changes. As of now the prognosis of various types of cancer depends upon findings related to the data generated through different experiments. Several machine learning techniques exist in analysing the data of expressed genes; however the recent results related with deep learning algorithms are more accurate and accommodative as they are effective in selecting and classifying informative genes. This book explores the probabilistic computational deep learning model for cancer classification and prediction. | Computational and Analytic Methods in Biological Sciences Bioinformatics with Machine Learning and Mathematical Modelling

GBP 99.99
1

Basics of CNC Programming

Basics of CNC Programming

Before the introduction of automatic machines and automation industrial manufacturing of machines and their parts for the key industries were made though manually operated machines. Due to this manufacturers could not make complex profiles or shapes with high accuracy. As a result the production rate tended to be slow production costs were very high rejection rates were high and manufacturers often could not complete tasks on time. Industry was boosted by the introduction of the semi-automatic manufacturing machine known as the NC machine which was introduced in the 1950��s at the Massachusetts Institute of Technology in the USA. After these NC machine started to be used typical profiles and complex shapes could get produced more readily which in turn lead to an improved production rate with higher accuracy. Thereafter in the 1970��s an even larger revolutionary change was introduced to manufacturing namely the use of the CNC machine (Computer Numerical Control). Since then CNC has become the dominant production method in most manufacturing industries including automotive aviation defence oil and gas medical electronics industry and the optical industry. Basics of CNC Programming describes how to design CNC programs and what cutting parameters are required to make a good manufacturing program. The authors explain about cutting parameters in CNC machines such as cutting feed depth of cut rpm cutting speed etc. and they also explain the G codes and M codes which are common to CNC. The skill-set of CNC program writing is covered as well as how to cut material during different operations like straight turning step turning taper turning drilling chamfering radius profile profile turning etc. In so doing the authors cover the level of CNC programming from basic to industrial format. Drawings and CNC programs to practice on are also included for the reader.

GBP 38.99
1

FM-UWB Transceivers for Autonomous Wireless Systems

FM-UWB Transceivers for Autonomous Wireless Systems

Significant research effort has been devoted to the study and realization of autonomous wireless systems for wireless sensor and personal-area networking the internet of things and machine-to-machine communications. Low-power RF integrated circuits an energy harvester and a power management circuit are fundamental elements of these systems. An FM-UWB Transceiver for Autonomous Wireless Systems presents state-of-the-art developments in low-power FM-UWB transceiver realizations. The design performance and implementation of prototype transceivers in CMOS technology are presented. A working hardware realization of an autonomous node that includes a prototype power management circuit is also proposed and detailed in this book. Technical topics include: Low-complexity FM-UWB modulation schemesLow-power FM-UWB transceiver prototypes in CMOS technologyCMOS on-chip digital calibration techniquesSolar power harvester and power management in CMOS for low-power RF circuitsAn FM-UWB Transceiver for Autonomous Wireless Systems is an ideal text and reference for engineers working in wireless communication industries as well as academic staff and graduate students engaged in electrical engineering and communication systems research. | FM-UWB Transceivers for Autonomous Wireless Systems

GBP 74.99
1

Smart Antennas Electromagnetic Interference and Microwave Antennas for Wireless Communications

Smart Antennas Electromagnetic Interference and Microwave Antennas for Wireless Communications

This book covers all areas of smart antennas electromagnetic interference and microwave antennas for wireless communications. Smart antennas or adaptive antennas are multi-antenna components on one or both sides of a radio communication connection combined with advanced signal processing algorithms. They've evolved into a critical technology for third-generation and beyond mobile communication systems to meet their lofty capacity and performance targets. It seems that a significant capacity gain is achievable particularly if they are employed on both sides of the connection. There are several essential characteristics of these systems that need scientific and technical investigation. Included in the book are beamforming massive MIMO network MIMO mmwave transmission compressive sensing MIMO radar sensor networks vehicle-to-vehicle communication location and machine learning.

GBP 99.99
1

A First Course in Control System Design

A First Course in Control System Design

Control systems are pervasive in our lives. Our homes have environmental controls. The appliances we use such as the washing machine microwave etc. carry embedded controllers in them. We fly in airplanes and drive automobiles that extensively use control systems. The industrial plants that produce consumer goods run on process control systems. The recent drive toward automation has increased our reliance on control systems technology. This book discusses control systems design from a model-based perspective for dynamic system models of single-input single-output type. The emphasis in this book is on understanding and applying the techniques that enable the design of effective control systems in multiple engineering disciplines. The book covers both time-domain and the frequency-domain design methods as well as controller design for both continuous-time and discrete-time systems. MATLAB© and its Control Systems Toolbox are extensively used for design. | A First Course in Control System Design

GBP 94.99
1

Applications of Big Data and Artificial Intelligence in Smart Energy Systems Volume 2 Energy Planning Operations Control and Market Perspectives

Applications of Big Data and Artificial Intelligence in Smart Energy Systems Volume 2 Energy Planning Operations Control and Market Perspectives

In the era of propelling traditional energy systems to evolve towards smart energy systems including power generation energy storage systems and electricity consumption have become more dynamic. The quality and reliability of power supply are impacted by the sporadic and rising use of electric vehicles and domestic & industrial loads. Similarly with the integration of solid state devices renewable sources and distributed generation power generation processes are evolving in a variety of ways. Several cutting-edge technologies are necessary for the safe and secure operation of power systems in such a dynamic setting including load distribution automation energy regulation and control and energy trading. This book covers the applications of various big data analytics artificial intelligence and machine learning technologies in smart grids for demand prediction decision-making processes policy and energy management. The book delves into the new technologies such as the Internet of Things blockchain etc. for smart home solutions and smart city solutions in depth in the context of the modern power systems. Technical topics discussed in the book include: • Hybrid smart energy system technologies • Energy demand forecasting • Use of different protocols and communication in smart energy systems • Power quality and allied issues and mitigation using AI • Intelligent transportation • Virtual power plants • AI business models. | Applications of Big Data and Artificial Intelligence in Smart Energy Systems Volume 2 Energy Planning Operations Control and Market Perspectives

GBP 99.99
1

Big Data in Oncology: Impact Challenges and Risk Assessment

Big Data in Oncology: Impact Challenges and Risk Assessment

We are in the era of large-scale science. In oncology there is a huge number of data sets grouping information on cancer genomes transcriptomes clinical data and more. The challenge of big data in cancer is to integrate all this diversity of data collected into a unique platform that can be analyzed leading to the generation of readable files. The possibility of harnessing information from all the accumulated data leads to an improvement in cancer patient treatment and outcome. Solving the big data problem in oncology has multiple facets. Big data in Oncology: Impact Challenges and Risk Assessment brings together insights from emerging sophisticated information and communication technologies such as artificial intelligence data science and big data analytics for cancer management. This book focuses on targeted disease treatment using big data analytics. It provides information about targeted treatment in oncology challenges and application of big data in cancer therapy. Recent developments in the fields of artificial intelligence machine learning medical imaging personalized medicine computing and data analytics for improved patient care. Description of the application of big data with AI to discover new targeting points for cancer treatment. Summary of several risk assessments in the field of oncology using big data. Focus on prediction of doses in oncology using big data The most targeted or relevant audience is academics research scholars health care professionals hospital management pharmaceutical chemists the biomedical industry software engineers and IT professionals.

GBP 110.00
1

Embedded Artificial Intelligence Devices Embedded Systems and Industrial Applications

Embedded Artificial Intelligence Devices Embedded Systems and Industrial Applications

Recent technological developments in sensors edge computing connectivity and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN) or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs communication and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications based on close cooperation between three large-scale ECSEL JU projects AI4DI ANDANTE and TEMPO. The book’s content targets researchers designers developers academics post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI addressing methodologies tools and techniques to offer insight into technological trends and their use across different industries. | Embedded Artificial Intelligence Devices Embedded Systems and Industrial Applications

GBP 94.99
1

SMART Integrated Circuit Design and Methodology

SMART Integrated Circuit Design and Methodology

This book describes advanced flows and methodologies for the design and implementation of system-on-chip (SoC). It is written by a mixture of industrial experts and key academic professors and researchers. The intended audience is not only students but also engineers with system-on-chip and semiconductor background currently working in the semiconductor industry. Integrated Circuits are available in every electronic product especially in emerging market segments such as 5G mobile communications autonomous driving fully electrified vehicles and artificial intelligence. These product types require real-time processing at billions of operations per second. The development design cycle time is driving costs and time to market more than ever before. The traditional design methodologies have reached their limits and innovative solutions are essential to serve the emerging SoC design challenges. In the framework of the Circuit and System Society (CASS) Outreach Initiative 2022 call the SMART Integrated Circuits design methodology – named SMARTIC – Seasonal School was performed in November 2022 in Thessaloniki (Greece). Features Core analog circuits of any system of chip such as high-performance rectifiers and filters are addressed in detail together with their respective design methodology. New advanced methodologies towards design cycle speed up based on machine learning and artificial intelligence applications. Advanced analog design methodology based on gm/Id and lock up tables. A powerful flow for enabling fast time to market analog circuit design focusing on baseband circuits More exotic methodologies and applications with focus on digital-based analog processing in nanoscale CMOS ICs and the design and development of depleted monolithic active pixel sensors for high-radiation applications together with all the respective challenges of this application. | SMART Integrated Circuit Design and Methodology

GBP 94.99
1

Disruptive Artificial Intelligence and Sustainable Human Resource Management Impacts and Innovations -The Future of HR

Disruptive Artificial Intelligence and Sustainable Human Resource Management Impacts and Innovations -The Future of HR

It is well-established that every organization is founded with a specific purpose and goals. Virtually all business organizations obtain measurements and metrics dealing with outcomes and results. However what is reflected on the balance sheet does not necessarily show the actual worth of the organizations and ensure their survival and sustainability. Thus the question arises what exactly makes the organizations sustainable and thriving in an ever-changing environment? There are several examples of companies like Faber-Castell Bank of Ireland Chivas DuPont and many more which have been able to sustain and survive over more than 200 years and still have a successful existence in the present era. Thus it is important for the organization to pay equal attention to its three bottom lines i. e. people profit and planet for its sustainability which not only meet the needs of the present generation but should have a futuristic approach as well. In the present era organizations are adopting a new normal working dynamic and coping with the post-pandemic situations to sustain themselves in the business environment. Technology plays a significant role in this new working dynamic and cutting-edge technologies like machine learning artificial intelligence blockchain ChatGPT Internet of Things and much more effectively facilitate human functioning at work. The book aims to contribute to understanding and developing sustainable human resource management processes and practices aligned with recent technologies. It highlights the interconnection among the three bottom-line sustainable approaches for the growth and development of the organization. Topics discussed in this book include: • Disruptive Technologies and HR Sustainability • Convergence of Innovative Technologies HR and Organizational Growth • Triple bottom-line Sustainability for HRM • Business-oriented Talent analytics and HR Sustainability • Role of Leadership in sustainable HRM practices. | Disruptive Artificial Intelligence and Sustainable Human Resource Management Impacts and Innovations -The Future of HR

GBP 99.99
1

Applied Data Analytics - Principles and Applications

Applied Data Analytics - Principles and Applications

The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very lage data sizes. Analysis of x-ray images in medical applications cyber security data crime data telecommunications and stock market data health records and business analytics data are but a few areas of interest. Applications and platforms including R RapidMiner and Weka provide the basis for analysis often used by practitioners who pay little to no attention to the underlying mathematics and processes impacting the data. This often leads to an inability to explain results or correct mistakes or to spot errors. Applied Data Analytics - Principles and Applications seeks to bridge this missing gap by providing some of the most sought after techniques in big data analytics. Establishing strong foundations in these topics provides practical ease when big data analyses are undertaken using the widely available open source and commercially orientated computation platforms languages and visualisation systems. The book when combined with such platforms provides a complete set of tools required to handle big data and can lead to fast implementations and applications. The book contains a mixture of machine learning foundations deep learning artificial intelligence statistics and evolutionary learning mathematics written from the usage point of view with rich explanations on what the concepts mean. The author has thus avoided the complexities often associated with these concepts when found in research papers. The tutorial nature of the book and the applications provided are some of the reasons why the book is suitable for undergraduate postgraduate and big data analytics enthusiasts. This text should ease the fear of mathematics often associated with practical data analytics and support rapid applications in artificial intelligence environmental sensor data modelling and analysis health informatics business data analytics data from Internet of Things and deep learning applications.

GBP 94.99
1