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IoT, Machine Learning and Blockchain Technologies for Renewable Energy and Modern Hybrid Power Systems - - Bog - River Publishers - Plusbog.dk

Pattern Recognition and Machine Vision - - Bog - River Publishers - Plusbog.dk

Pattern Recognition and Machine Vision - - Bog - River Publishers - Plusbog.dk

In recent years, there has been a growing interest in the fields of pattern recognition and machine vision in academia and industries. New theories have been developed, with new design of technology and systems in both hardware and software. They are widely applied to our daily life to solve real problems in such diverse areas as science, engineering, agriculture, e-commerce, education, robotics, government, medicine, games and animation, medical imaging analysis and diagnosis, military, and national security.The foundation of all this field can be traced back to the late Prof. King-Sun Fu, one of the founding fathers of pattern recognition, who, with visionary insight founded the International Association for Pattern Recognition around 1980. In the almost 30 years since then, the world has witnessed the rapid growth and development of this field. It is probably true to say that most people are affected by, or use applications of pattern recognition in daily life.Today, on the eve of 25th anniversary of the unfortunate and untimely passing of Prof. Fu, we are proud to produce this volume of collected works from world renowned professionals and experts in pattern recognition and machine vision, in honor and memory of the late Prof. King-Sun Fu. We hope this book will help promote further the course, not only of fundamental principles, systems and technologies, but also its vast range of applications to help in solving problems in daily life.ContentsBasic Foundations of Pattern Recognition and Artificial Intelligence, Methodologies of Machine Vision and Image Processing, Intelligent Pattern Recognition Systems, 3-D Object Pattern Analysis, Modelling and Simulation, Analysis of DNA Microarray Gene Expression Data based on Pattern Recognition Methods, PRMV Applications.

DKK 1022.00
1

Applications of Machine Learning in Big-Data Analytics and Cloud Computing - - Bog - River Publishers - Plusbog.dk

Applications of Machine Learning in Big-Data Analytics and Cloud Computing - - Bog - River Publishers - Plusbog.dk

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

DKK 457.00
1

Machine Learning for Healthcare Systems - - Bog - River Publishers - Plusbog.dk

Machine Learning for Healthcare Systems - - Bog - River Publishers - Plusbog.dk

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.

DKK 1042.00
1

Applications of Machine Learning in Big-Data Analytics and Cloud Computing - Dr. Sumit Kundu - Bog - River Publishers - Plusbog.dk

Applications of Machine Learning in Big-Data Analytics and Cloud Computing - Dr. Sumit Kundu - Bog - River Publishers - Plusbog.dk

Cloud Computing and Big Data technologies have become the new descriptors of the digital age. The global amount of digital data has increased more than nine times in volume in just five years and by 2030 its volume may reach a staggering 65 trillion gigabytes. This explosion of data has led to opportunities and transformation in various areas such as healthcare, enterprises, industrial manufacturing and transportation. New Cloud Computing and Big Data tools endow researchers and analysts with novel techniques and opportunities to collect, manage and analyze the vast quantities of data. In Cloud and Big Data Analytics, the two areas of Swarm Intelligence and Deep Learning are a developing type of Machine Learning techniques that show enormous potential for solving complex business problems. Deep Learning enables computers to analyze large quantities of unstructured and binary data and to deduce relationships without requiring specific models or programming instructions. This book introduces the state-of-the-art trends and advances in the use of Machine Learning in Cloud and Big Data Analytics. The book will serve as a reference for Data Scientists, systems architects, developers, new researchers and graduate level students in Computer and Data science. The book will describe the concepts necessary to understand current Machine Learning issues, challenges and possible solutions as well as upcoming trends in Big Data Analytics.

DKK 967.00
1

Practical Guide to Machine Learning, NLP, and Generative AI: Libraries, Algorithms, and Applications - Kumar Reddy Cheepati - Bog - River Publishers -

Practical Guide to Machine Learning, NLP, and Generative AI: Libraries, Algorithms, and Applications - Kumar Reddy Cheepati - Bog - River Publishers -

This is an essential resource for beginners and experienced practitioners in machine learning. This comprehensive guide covers a broad spectrum of machine learning topics, starting with an in-depth exploration of popular machine learning libraries. Readers will gain a thorough understanding of Scikit-learn, TensorFlow, PyTorch, Keras, and other pivotal libraries like XGBoost, LightGBM, and CatBoost, which are integral for efficient model development and deployment. The book delves into various neural network architectures, providing readers with a solid foundation in understanding and applying these models. Beginning with the basics of the Perceptron and its application in digit classification, it progresses to more complex structures such as multilayer perceptrons for financial forecasting, radial basis function networks for air quality prediction, and convolutional neural networks (CNNs) for image classification. Additionally, the book covers recurrent neural networks (RNNs) and their variants like long short-term memory (LSTM) and gated recurrent units (GRUs), which are crucial for time-series analysis and sequential data applications. Supervised machine learning algorithms are meticulously explained, with practical examples to illustrate their application. The book covers logistic regression and its use in predicting sports outcomes, decision trees for plant classification, random forests for traffic prediction, and support vector machines for house price prediction. Gradient boosting machines and their applications in genomics, AdaBoost for bioinformatics data classification, and extreme gradient boosting (XGBoost) for churn prediction are also discussed, providing readers with a robust toolkit for various predictive tasks. Unsupervised learning algorithms are another significant focus of the book, introducing readers to techniques for uncovering hidden patterns in data. Hierarchical clustering for gene expression data analysis, principal component analysis (PCA) for climate predictions, and singular value decomposition (SVD) for signal denoising are thoroughly explained. The book also explores applications like robot navigation and network security, demonstrating the versatility of these techniques. Natural language processing (NLP) is comprehensively covered, highlighting its fundamental concepts and various applications. The book discusses the overview of NLP, its fundamental concepts, and its diverse applications such as chatbots, virtual assistants, clinical NLP applications, and social media analytics. Detailed sections on text pre-processing, syntactic analysis, machine translation, text classification, named entity recognition, and sentiment analysis equip readers with the knowledge to build sophisticated NLP models. The final chapters of the book explore generative AI, including generative adversarial networks (GANs) for image generation, variational autoencoders for vibrational encoder training, and autoregressive models for time series forecasting. It also delves into Markov chain models for text generation, Boltzmann machines for pattern recognition, and deep belief networks for financial forecasting. Special attention is given to the application of recurrent neural networks (RNNs) for generation tasks, such as wind power plant predictions and battery range prediction, showcasing the practical implementations of generative AI in various fields.

DKK 590.00
1

Pattern Recognition and Machine Vision- In Honor and Memory of Late Prof. King-Sun Fu - - Bog - River Publishers - Plusbog.dk

Pattern Recognition and Machine Vision- In Honor and Memory of Late Prof. King-Sun Fu - - Bog - River Publishers - Plusbog.dk

In recent years, there has been a growing interest in the fields of pattern recognition and machine vision in academia and industries. New theories have been developed, with new design of technology and systems in both hardware and software. They are widely applied to our daily life to solve real problems in such diverse areas as science, engineering, agriculture, e-commerce, education, robotics, government, medicine, games and animation, medical imaging analysis and diagnosis, military, and national security.The foundation of all this field can be traced back to the late Prof. King-Sun Fu, one of the founding fathers of pattern recognition, who, with visionary insight founded the International Association for Pattern Recognition around 1980. In the almost 30 years since then, the world has witnessed the rapid growth and development of this field. It is probably true to say that most people are affected by, or use applications of pattern recognition in daily life.Today, on the eve of 25th anniversary of the unfortunate and untimely passing of Prof. Fu, we are proud to produce this volume of collected works from world renowned professionals and experts in pattern recognition and machine vision, in honor and memory of the late Prof. King-Sun Fu. We hope this book will help promote further the course, not only of fundamental principles, systems and technologies, but also its vast range of applications to help in solving problems in daily life.ContentsBasic Foundations of Pattern Recognition and Artificial Intelligence, Methodologies of Machine Vision and Image Processing, Intelligent Pattern Recognition Systems, 3-D Object Pattern Analysis, Modelling and Simulation, Analysis of DNA Microarray Gene Expression Data based on Pattern Recognition Methods, PRMV Applications.

DKK 467.00
1

An Introduction to Electronic Warfare; from the First Jamming to Machine Learning Techniques - Chi Hao Cheng - Bog - River Publishers - Plusbog.dk

An Introduction to Electronic Warfare; from the First Jamming to Machine Learning Techniques - Chi Hao Cheng - Bog - River Publishers - Plusbog.dk

Machine Learning Methods for Signal, Image and Speech Processing - Sheng Lung Peng - Bog - River Publishers - Plusbog.dk

Machine Learning Methods for Signal, Image and Speech Processing - Mvv Prasad Kantipudi - Bog - River Publishers - Plusbog.dk

A First Course in Control System Design - Kamran Iqbal - Bog - River Publishers - Plusbog.dk

A First Course in Control System Design - Kamran Iqbal - Bog - River Publishers - Plusbog.dk

A First Course in Control System Design - Kamran Iqbal - Bog - River Publishers - Plusbog.dk

Convergence of Communications, Navigation, Sensing and Services - - Bog - River Publishers - Plusbog.dk

Convergence of Communications, Navigation, Sensing and Services - - Bog - River Publishers - Plusbog.dk

Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence - - Bog - River Publishers - Plusbog.dk

Big Data Analytics and Intelligent Systems for Cyber Threat Intelligence - - Bog - River Publishers - Plusbog.dk

In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include: • Big data analytics for cyber threat intelligence and detection • Artificial intelligence analytics techniques • Real-time situational awareness • Machine learning techniques for CTI • Deep learning techniques for CTI • Malware detection and prevention techniques • Intrusion and cybersecurity threat detection and analysis • Blockchain and machine learning techniques for CTI

DKK 1042.00
1

Basics of CNC Programming - Pawan Negi - Bog - River Publishers - Plusbog.dk

Basics of CNC Programming - Pawan Negi - Bog - River Publishers - Plusbog.dk

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.

DKK 920.00
1

Basics of CNC Programming - Pawan Negi - Bog - River Publishers - Plusbog.dk

Basics of CNC Programming - Pawan Negi - Bog - River Publishers - Plusbog.dk

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.

DKK 429.00
1

Practical Lubrication for Industrial Facilities, Third Edition - Heinz P. Bloch - Bog - River Publishers - Plusbog.dk

Data Driven Energy Centered Maintenance - Fadi Alshakhshir - Bog - River Publishers - Plusbog.dk

Data Driven Energy Centered Maintenance - Fadi Alshakhshir - Bog - River Publishers - Plusbog.dk

Over recent years, many new technologies have been introduced to drive the digital transformation in the building maintenance industry. The current trend in digital evolution involves data-driven decision making which opens new opportunities for an energy centered maintenance model. Artificial Intelligence and Machine Learning are helping the maintenance team to get to the next level of maintenance intelligence to provide real-time early warning of abnormal equipment performance. This edition follows the same methodology as the First. It provides detailed descriptions of the latest technologies associated with Artificial Intelligence and Machine Learning which enable data-driven decision-making processes about the equipment’s operation and maintenance. Technical topics discussed in the book include: - Different Maintenance Types and The Need for Energy Centered Maintenance - The Centered Maintenance Model - Energy Centered Maintenance Process - Measures of Equipment and Maintenance Efficiency and Effectiveness - Data-Driven Energy Centered Maintenance Model: - - Digitally Enabled Energy Centered Maintenance Tasks - Artificial Intelligence and Machine Learning in Energy Centered Maintenance - Model Capabilities and Analytics Rules - Building Management System Schematics The book contains a detailed description of the digital transformation process of most of the maintenance inspection tasks as they move away from being manually triggered. The book is aimed at building operators as well as those building automation companies who are working continuously to digitalize building operation and maintenance procedures. The benefits are reductions in the equipment failure rate, improvements in equipment reliability, increases in equipment efficiency and extended equipment lifespan.

DKK 588.00
1

Next Generation Internet of Things ? Distributed Intelligence at the Edge and Human-Machine Interactions - - Bog - River Publishers - Plusbog.dk

Next Generation Internet of Things ? Distributed Intelligence at the Edge and Human-Machine Interactions - - Bog - River Publishers - Plusbog.dk

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.

DKK 429.00
1

Next Generation Internet of Things ? Distributed Intelligence at the Edge and Human-Machine Interactions - - Bog - River Publishers - Plusbog.dk

Next Generation Internet of Things ? Distributed Intelligence at the Edge and Human-Machine Interactions - - Bog - River Publishers - Plusbog.dk

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas.

DKK 920.00
1

Artificial Intelligence, Blockchain and IoT for Smart Healthcare - Hitesh Kumar Sharma - Bog - River Publishers - Plusbog.dk