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Adopting .NET 5: Understand modern architectures, migration best practices, and the new features in .NET 5

by Hammad Arif Habib Qureshi

A practical guide to building and upgrading new and legacy applications on cloud-native platforms using architectural best practices with .NET 5, C# 9, microservices, and ML.NETKey FeaturesGet up to speed with .NET 5's new improvements and featuresDiscover how to improve existing code design and enhance software maintainabilityExplore explanations and techniques for making programs easier to understand and changeBook Description.NET 5 is the unification of all .NET technologies in a single framework that can run on all platforms and provide a consistent experience to developers, regardless of the device, operating system (OS), or cloud platform they choose. By updating to .NET 5, you can build software that can quickly adapt to the rapidly changing demands of modern consumers and stay up to date on the latest technology trends in .NET. This book provides a comprehensive overview of all the technologies that will form the future landscape of .NET using practical examples based on real-world scenarios, along with best practices to help you migrate from legacy platforms. You'll start by learning about Microsoft's vision and rationale for the unification of the platforms. Then, you'll cover all the new language enhancements in C# 9. As you advance, you'll find out how you can align yourself with modern technology trends, focusing on everything from microservices to orchestrated containerized deployments. Finally, you'll learn how to effectively integrate machine learning in .NET code. By the end of this .NET book, you'll have gained a thorough understanding of the .NET 5 platform, together with a readiness to adapt to future .NET release cycles, and you'll be able to make architectural decisions about porting legacy systems and code bases to a newer platform.What you will learnExplore the key performance improvement areas when migrating to modern architecturesUnderstand app design and development using .NET 5Discover how to shift from legacy to modern application design using microservices and cloud-native architectureExplore common migration pitfalls and make the right decisions in situations where multiple options are availableUnderstand the process of deploying .NET 5 code on serverless and containerized hosts, along with its benefitsFind out what ML.NET has to offer and build .NET apps that use machine learning servicesWho this book is forThis book is for experienced developers as well as software architects who are looking to gain knowledge of the new features and capabilities of .NET 5, along with guidance on modern architectural patterns. If you're a developer who has previously worked on .NET, WPF, ASP.NET, Entity Framework, or other popular .NET libraries, this book will help you understand the migration process for their modern counterparts. Although experience with .NET Core is not required, working knowledge of the C# language and .NET framework is assumed.

Adopting Open Source Software: A Practical Guide

by Brian Fitzgerald Jay P. Kesan Barbara Russo Maha Shaikh Giancarlo Succi

A rich case-study analysis of open source software adoption by public organizations in different countries and settings.Government agencies and public organizations often consider adopting open source software (OSS) for reasons of transparency, cost, citizen access, and greater efficiency in communication and delivering services. Adopting Open Source Software offers five richly detailed real-world case studies of OSS adoption by public organizations. The authors analyze the cases and develop an overarching, conceptual framework to clarify the various enablers and inhibitors of OSS adoption in the public sector. The book provides a useful resource for policymakers, practitioners, and academics.The five cases of OSS adoption include a hospital in Ireland; an IT consortium serving all the municipalities of the province of Bozen-Bolzano, Italy; schools and public offices in the Extremadura region of Spain; the Massachusetts state government's open standards policy in the United States; and the ICT department of the Italian Chamber of Deputies. The book provides a comparative analysis of these cases around the issues of motivation, strategies, technologies, economic and social aspects, and the implications for theory and practice.

Adopting Open Source Software

by Brian Fitzgerald Jay P. Kesan Barbara Russo Maha Shaikh Giancarlo Succi

Government agencies and public organizations often consider adopting open source software (OSS) for reasons of transparency, cost, citizen access, and greater efficiency in communication and delivering services. Adopting Open Source Software offers five richly detailed real-world case studies of OSS adoption by public organizations. The authors analyze the cases and develop an overarching, conceptual framework to clarify the various enablers and inhibitors of OSS adoption in the public sector. The book provides a useful resource for policymakers, practitioners, and academics. The five cases of OSS adoption include a hospital in Ireland; an IT consortium serving all the municipalities of the province of Bozen-Bolzano, Italy; schools and public offices in the Extremadura region of Spain; the Massachusetts state government's open standards policy in the United States; and the ICT department of the Italian Chamber of Deputies. The book provides a comparative analysis of these cases around the issues of motivation, strategies, technologies, economic and social aspects, and the implications for theory and practice.

Adoption of Data Analytics in Higher Education Learning and Teaching (Advances in Analytics for Learning and Teaching)

by David Gibson Dirk Ifenthaler

The book aims to advance global knowledge and practice in applying data science to transform higher education learning and teaching to improve personalization, access and effectiveness of education for all. Currently, higher education institutions and involved stakeholders can derive multiple benefits from educational data mining and learning analytics by using different data analytics strategies to produce summative, real-time, and predictive or prescriptive insights and recommendations. Educational data mining refers to the process of extracting useful information out of a large collection of complex educational datasets while learning analytics emphasizes insights and responses to real-time learning processes based on educational information from digital learning environments, administrative systems, and social platforms. This volume provides insight into the emerging paradigms, frameworks, methods and processes of managing change to better facilitate organizational transformation toward implementation of educational data mining and learning analytics. It features current research exploring the (a) theoretical foundation and empirical evidence of the adoption of learning analytics, (b) technological infrastructure and staff capabilities required, as well as (c) case studies that describe current practices and experiences in the use of data analytics in higher education.

Adoption of Emerging Information and Communication Technology for Sustainability

by Ewa Ziemba Jarosław

This book represents an important voice in the discourse on the adoption of emerging ICT for sustainability. It focuses on how emerging ICT acts as a crucial enabler of sustainability, offering new forward-looking approaches to this field. The book explores how emerging ICT adoption drives sustainability efforts in business and public organizations, promoting ecological, economic, social, cultural, and political sustainability. The book's theoretical discussions, conceptual approaches, empirical studies, diverse perspectives, and views make it a valuable and comprehensive reference work. Appealing to both researchers and practitioners, this book provides significant areas for research and practice related to the contribution of emerging ICT adoption to sustainability. It also suggests vital considerations for programming and building sustainable development-driven emerging ICT adoption. Readers will find answers to important contemporary questions, such as: What are the concepts, frameworks, models, and approaches to enhance sustainable development through the adoption of emerging ICT? How does the adoption of emerging ICT influence sustainability? How can emerging ICT be adopted to enhance sustainability? What are the current practices and successful cases of emerging ICT adoption for sustainability? What factors influence emerging ICT adoption to enhance sustainability?

The Adoption of Fintech: Using Technology for Better Security, Speed, and Customer Experience in Finance

by Syed Hasan Jafar Hani El-Chaarani K. Hemachandran Shakeb Akhtar Parvez Alam Khan

The term Fintech is a combination of the words “financial” and “technology,” which is now a real business need. However, there are limited books covering holistic aspects from adoption to the future of Fintech. This book directs readers on how to adopt Fintech, develop regulation and risk frameworks, implement it in financial services, address ethical dilemmas, and sustain improvements. The anticipated challenges are developing trust, security, privacy, and a regulated environment without compromising profitability and financial stability. The anticipated solution is strengthening the governance, use of unbreachable technologies, risk management, consumer data protection, and sustainable practices.This book is recommended for stakeholders, especially Fintech scholars, practitioners, and policymakers. It provides holistic insight and opportunities to support Fintech developments for the betterment of the economy and society. Fintech is defined as injecting technology into the area of finance for better security, speed, and customer experience. This book provides readers with direct case studies for better understanding. In addition, it explains the regulation and usage of Fintech in daily transactions. Readers are shown how Fintech has an imperative role in financial analysis, Insurtech, and the share market.

Adoption of LMS in Higher Educational Institutions of the Middle East (Advances in Science, Technology & Innovation)

by Rashid A. Khan Hassan Qudrat-Ullah

This book discusses the adoption of learning management systems (LMS) in higher education institutions. It presents influential predictors that may impact instructors’ behavioral intention to adopt learning management systems in the context of Arab culture, as well as a unique model of technology acceptance that draws on and combines previous technology adoption models (i.e., a modified unified theory of acceptance and use of technology model – UTAUT2). Moreover, this study extends the UTAUT2 model by including Hofstede’s (1980) cultural dimensions, and technology awareness as the moderators of the model. It also describes the explanatory technique approach used to collect quantitative data from the instructors at higher education institutions in Saudi Arabia and were analyzed with structural equation modeling using SPSS/Amos software. The findings revealed that facilitating conditions were the strongest predictor of behavioral intention to adopt an LMS, followed by performance expectancy and hedonic motivation, technology awareness, and cultural dimensions exerted a moderating influence on instructors’ behavioral intention to use LMS in their teaching. By including new constructs, this becomes the first study of its kind exploring instructors’ use of LMS in Higher Educational Institutions of Saudi Arabia and other countries of the Middle East. It offers practical insights for a broad range of researchers and professionals at higher education institutions and serves as a reference guide for designers of learning management systems (e.g., blackboard systems), policymakers, and the Ministry of Education staff.

AdS3/CFT2 and Holographic Entanglement Entropy (Springer Theses)

by Jie-qiang Wu

This book focuses on AdS3/CFT2, addressing different aspects of this correspondence in field theory and in gravity, including entanglement entropy, higher genus partition function, and conformal block. Holographic entanglement entropy is an important area in holographic and quantum information, which implies a deep relation between geometry and quantum entanglement. In this book, the authors use holographic entanglement entropy as a tool to investigate AdS3/CFT2. They study the entanglement entropy at high temperature in field theory and in holographics, and show that the results match each other in classical and one-loop order. In the AdS3/CFT2 system, they examine in detail the correspondence, exploring the higher genus partition function, entanglement entropy in a general system and conformal block, and they find good correspondence in field theory and gravity. The result strongly supports AdS3/CFT2 correspondence. In addition, they develop several important techniques in 2d CFT and 3d gravity, which also offer inspiration for other fields.

Advance Compression and Watermarking Technique for Speech Signals (SpringerBriefs in Speech Technology)

by Rohit Thanki Komal Borisagar Surekha Borra

This book introduces methods for copyright protection and compression for speech signals. The first method introduces copyright protection of speech signal using watermarking; the second introduces compression of the speech signal using Compressive Sensing (CS). Both methods are tested and analyzed. The speech watermarking method uses technology such as Finite Ridgelet Transform (FRT), Discrete Wavelet Transform (DWT) and Singular Value Decomposition (SVD). The performance of the method is evaluated and compared with existing watermarking methods. In the speech compression method, the standard Compressive Sensing (CS) process is used for compression of the speech signal. The performance of the proposed method is evaluated using various transform bases like Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), Singular Value Decomposition (SVD), and Fast Discrete Curvelet Transform (FDCuT).

Advance Concepts of Image Processing and Pattern Recognition: Effective Solution for Global Challenges (Transactions on Computer Systems and Networks)

by Krishna Kumar Narendra Kumar Celia Shahnaz Mazin Abed Mohammed Ram Shringar Raw

The book explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc. The security features of image processing like image watermarking and image encryption etc. are also discussed in this book. This book will be useful for those who are working in the field of image processing, pattern recognition, and security for digital images. This book targets researchers, academicians, industry, and professionals from R&D organizations, and students, healthcare professionals working in the field of medical imaging, telemedicine, cybersecurity, data scientist, artificial intelligence, image processing, digital hospital, intelligent medicine.

Advance in Structural Bioinformatics (Advances in Experimental Medicine and Biology #827)

by Dongqing Wei Qin Xu Tangzhen Zhao Hao Dai

This text examines in detail mathematical and physical modeling, computational methods and systems for obtaining and analyzing biological structures, using pioneering research cases as examples. As such, it emphasizes programming and problem-solving skills. It provides information on structure bioinformatics at various levels, with individual chapters covering introductory to advanced aspects, from fundamental methods and guidelines on acquiring and analyzing genomics and proteomics sequences, the structures of protein, DNA and RNA, to the basics of physical simulations and methods for conformation searches. This book will be of immense value to researchers and students in the fields of bioinformatics, computational biology and chemistry. Dr. Dongqing Wei is a Professor at the Department of Bioinformatics and Biostatistics, College of Life Science and Biotechnology, Shanghai Jiaotong University, Shanghai, China. His research interest is in the general area of structural bioinformatics.

Advance Metadata Fair: The Retention and Disclosure of 4G, 5G and Social Media Location Information, for Law Enforcement and National Security, and the Impact on Privacy in Australia (Law, Governance and Technology Series #44)

by Stanley Shanapinda

This book outlines the legal powers of a major Western nation – Australia – to collect and use location information. Mobile service and social media service providers now have the ability to track, record and store more precise location information. Unlike 4G, 5G mobile communications require that cell towers and antennas be in much closer proximity; as a result, the location data can reveal more personal and sensitive information about individual citizens. Despite this aspect, service providers are required to disclose the data to the authorities, without the need for a judicial warrant. This book was written from the perspective of big location data software analytics, a capability that makes it possible to combine various location data points to create a profile on a given individual’s movements, habits, and political, religious and ideological orientation. In this regard, privacy is poorly protected. The rationale used to justify the powers was enforcing serious crimes – terrorism offences. Location data can now be retained for at least two years and be collected to investigate even minor offences. This can be done without the person being reasonably suspected of a criminal offence – when the individual is simply determined to be a person of interest. This poses legal risks to vulnerable communities. And yet, such investigative techniques are deemed lawful and reasonable. At a time when national security is so broadly defined to include economic issues, which in turn overlap with climate change and environmental protection, these legal powers should be reassessed. The book clarifies the complex rules that every citizen must know in order to have agency. Further, it calls upon authorities to reflect and to self-regulate, by making the conscious decision to surrender some of their powers to review by the independent judiciary. Without the requirement for a judicial warrant or judicial review, the powers are unfairly broad. The book pursues an interdisciplinary approach to assess the functionality of mobile telecommunications in direct relation to law enforcement powers and existing judicial precedents. Further, it offers a unifying techno-legal perspective on a complex issue touching on modern privacy law and communications technologies.

Advance Numerical Techniques to Solve Linear and Nonlinear Differential Equations (River Publishers Series in Mathematical, Statistical and Computational Modelling for Engineering)

by Geeta Arora Mangey Ram

Real-world issues can be translated into the language and concepts of mathematics with the use of mathematical models. Models guided by differential equations with intuitive solutions can be used throughout engineering and the sciences. Almost any changing system may be described by a set of differential equations. They may be found just about anywhere you look in fields including physics, engineering, economics, sociology, biology, business, healthcare, etc. The nature of these equations has been investigated by several mathematicians over the course of hundreds of years and, consequently, numerous effective methods for solving them have been created. It is often impractical to find a purely analytical solution to a system described by a differential equation because either the system itself is too complex or the system being described is too vast. Numerical approaches and computer simulations are especially helpful in such systems. The content provided in this book involves real-world examples, explores research challenges in numerical treatment, and demonstrates how to create new numerical methods for resolving problems. Theories and practical applications in the sciences and engineering are also discussed. Students of engineering and applied mathematics, as well as researchers and engineers who use computers to solve problems numerically or oversee those who do, will find this book focusing on advance numerical techniques to solve linear and nonlinear differential equations useful.

Advanced ActionScript 3: Design Patterns

by Ben Smith

Advanced ActionScript 3 is a fresh look and new approach to utilizing valuable, structural techniques and methods that are commonly used in the field of rich interactive application development. With each method broken down into different strategized explanations, you'll find the approach most suitable for you. Whether it is an example you can utilize as-is, or one you can start with and develop further, you will have a glossary of definitions and organizational concepts at your fingertips. Object-oriented programming (OOP) and design patterns are not new to the field, but can often be overlooked in their value. They are, at times, not only overwhelming to learn, but difficult to put into practice. However, they are useful because they create a structure that can be broken down, rebuilt, and reused. This edition has been fully updated to reflect modern coding standards and practices. Provides the building blocks required for the implementation of OOPAddresses problems and concerns regarding OOPOffers solutions on how to approach and utilize OOP

Advanced Adobe Photoshop CS5 Revealed

by Chris Botello

Discover all that Photoshop CS5 has to offer with ADVANCED ADOBE PHOTOSHOP CS5 REVEALED. This book teaches advanced design techniques using one of the most popular photo-editing programs on the market. Using step-by-step tutorials, readers work with curves, levels, blending modes, painting and drawing tools, and the latest Photoshop special effects to create professional-quality designs and images. They are challenged not only as Photoshop users but as designers, following the steps a designer would take to complete real-world projects. They also see what works in a design and what doesn't. Readers then take their craft to the next level by using the advanced end-of-chapter learning projects. The book's full-color interior and highly visual design make this the ideal book for learning advanced design techniques using the latest version of Adobe Photoshop.

Advanced AI and Internet of Health Things for Combating Pandemics (Internet of Things)

by Mohamed Lahby Virginia Pilloni Jyoti Sekhar Banerjee Mufti Mahmud

This book presents the latest research, theoretical methods, and novel applications in the field of Health 5.0. The authors focus on combating COVID-19 or other pandemics through facilitating various technological services. The authors discuss new models, practical solutions, and technological advances related to detecting and analyzing COVID-19 or other pandemic based on machine intelligence models and communication technologies. The aim of the coverage is to help decision-makers, managers, professionals, and researchers design new paradigms considering the unique opportunities associated with computational intelligence and Internet of Medical Things (IoMT). This book emphasizes the need to analyze all the information through studies and research carried out in the field of computational intelligence, communication networks, and presents the best solutions to combat COVID and other pandemics.

Advanced AI Techniques and Applications in Bioinformatics (Smart and Intelligent Computing in Engineering)

by Loveleen Gaur, Arun Solanki, Samuel Fosso Wamba and Noor Zaman Jhanjhi

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this book are an indispensable resource for computer scientists, engineers, biologists, mathematicians, physicians, and medical informaticists. Features: Focusses on the cross-disciplinary relation between computer science and biology and the role of machine learning methods in resolving complex problems in bioinformatics Provides a comprehensive and balanced blend of topics and applications using various advanced algorithms Presents cutting-edge research methodologies in the area of AI methods when applied to bioinformatics and innovative solutions Discusses the AI/ML techniques, their use, and their potential for use in common and future bioinformatics applications Includes recent achievements in AI and bioinformatics contributed by a global team of researchers

Advanced Algorithms and Data Structures

by Marcello La Rocca

Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing.Summary As a software engineer, you&’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don&’t despair! Many of these &“new&” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Can you improve the speed and efficiency of your applications without investing in new hardware? Well, yes, you can: Innovations in algorithms and data structures have led to huge advances in application performance. Pick up this book to discover a collection of advanced algorithms that will make you a more effective developer. About the book Advanced Algorithms and Data Structures introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You&’ll discover cutting-edge approaches to a variety of tricky scenarios. You&’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms About the reader For intermediate programmers. About the author Marcello La Rocca is a research scientist and a full-stack engineer. His focus is on optimization algorithms, genetic algorithms, machine learning, and quantum computing. Table of Contents 1 Introducing data structures PART 1 IMPROVING OVER BASIC DATA STRUCTURES 2 Improving priority queues: d-way heaps 3 Treaps: Using randomization to balance binary search trees 4 Bloom filters: Reducing the memory for tracking content 5 Disjoint sets: Sub-linear time processing 6 Trie, radix trie: Efficient string search 7 Use case: LRU cache PART 2 MULTIDEMENSIONAL QUERIES 8 Nearest neighbors search 9 K-d trees: Multidimensional data indexing 10 Similarity Search Trees: Approximate nearest neighbors search for image retrieval 11 Applications of nearest neighbor search 12 Clustering 13 Parallel clustering: MapReduce and canopy clustering PART 3 PLANAR GRAPHS AND MINIMUM CROSSING NUMBER 14 An introduction to graphs: Finding paths of minimum distance 15 Graph embeddings and planarity: Drawing graphs with minimal edge intersections 16 Gradient descent: Optimization problems (not just) on graphs 17 Simulated annealing: Optimization beyond local minima 18 Genetic algorithms: Biologically inspired, fast-converging optimization

Advanced Analytics and AI: Impact, Implementation, and the Future of Work (Wiley Finance)

by Tony Boobier

Be prepared for the arrival of automated decision making Once thought of as science fiction, major corporations are already beginning to use cognitive systems to assist in providing wealth advice and also in medication treatment. The use of Cognitive Analytics/Artificial Intelligence (AI) Systems is set to accelerate, with the expectation that it’ll be considered ‘mainstream’ in the next 5 – 10 years. It’ll change the way we as individuals interact with data and systems—and the way we run our businesses. Cognitive Analysis and AI prepares business users for the era of cognitive analytics / artificial intelligence. Building on established texts and commentary, it specifically prepares you in terms of expectation, impact on personal roles, and responsibilities. It focuses on the specific impact on key industries (retail, financial services, utilities and media) and also on key professions (such as accounting, operational management, supply chain and risk management). Shows you how users interact with the system in natural language Explains how cognitive analysis/AI can source ‘big data’ Provides a roadmap for implementation Gets you up to speed now before you get left behind If you’re a decision maker or budget holder within the corporate context, this invaluable book helps you gain an advantage from the deployment of cognitive analytics tools.

Advanced Analytics and Deep Learning Models (Next Generation Computing and Communication Engineering)

by Archana Mire Shaveta Malik Amit Kumar Tyagi

Advanced Analytics and Deep Learning Models The book provides readers with an in-depth understanding of concepts and technologies related to the importance of analytics and deep learning in many useful real-world applications such as e-healthcare, transportation, agriculture, stock market, etc. Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis. It is an approach to data analysis. Beyond the traditional business intelligence, it is a semi and autonomous analysis of data by using different techniques and tools. However, deep learning and data analysis both are high centers of data science. Almost all the private and public organizations collect heavy amounts of data, i.e., domain-specific data. Many small/large companies are exploring large amounts of data for existing and future technology. Deep learning is also exploring large amounts of unsupervised data making it beneficial and effective for big data. Deep learning can be used to deal with all kinds of problems and challenges that include collecting unlabeled and uncategorized raw data, extracting complex patterns from a large amount of data, retrieving fast information, tagging data, etc. This book contains 16 chapters on artificial intelligence, machine learning, deep learning, and their uses in many useful sectors like stock market prediction, a recommendation system for better service selection, e-healthcare, telemedicine, transportation. There are also chapters on innovations and future opportunities with fog computing/cloud computing and artificial intelligence. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in healthcare, telemedicine, transportation, and the financial sector. The book will also be a great source for software engineers and advanced students who are beginners in the field of advanced analytics in deep learning.

Advanced Analytics and Learning on Temporal Data: 7th ECML PKDD Workshop, AALTD 2022, Grenoble, France, September 19–23, 2022, Revised Selected Papers (Lecture Notes in Computer Science #13812)

by Thomas Guyet Georgiana Ifrim Simon Malinowski Anthony Bagnall Patrick Shafer Vincent Lemaire

This book constitutes the refereed proceedings of the 7th ECML PKDD Workshop, AALTD 2022, held in Grenoble, France, during September 19–23, 2022.The 12 full papers included in this book were carefully reviewed and selected from 21 submissions. They were organized in topical sections as follows: Oral presentation and poster presentation.

Advanced Analytics and Learning on Temporal Data: 8th ECML PKDD Workshop, AALTD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14343)

by Georgiana Ifrim Romain Tavenard Anthony Bagnall Patrick Schaefer Simon Malinowski Thomas Guyet Vincent Lemaire

This volume LNCS 14343 constitutes the refereed proceedings of the 8th ECML PKDD Workshop, AALTD 2023, in Turin, Italy, in September 2023. The 20 full papers were carefully reviewed and selected from 28 submissions. They are organized in the following topical section as follows: Machine Learning; Data Mining; Pattern Analysis; Statistics to Share their Challenges and Advances in Temporal Data Analysis.

Advanced Analytics and Learning on Temporal Data: 4th ECML PKDD Workshop, AALTD 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers (Lecture Notes in Computer Science #11986)

by Vincent Lemaire Simon Malinowski Anthony Bagnall Alexis Bondu Thomas Guyet Romain Tavenard

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Würzburg, Germany, in September 2019. The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

Advanced Analytics and Learning on Temporal Data: 5th ECML PKDD Workshop, AALTD 2020, Ghent, Belgium, September 18, 2020, Revised Selected Papers (Lecture Notes in Computer Science #12588)

by Vincent Lemaire Simon Malinowski Anthony Bagnall Thomas Guyet Romain Tavenard Georgiana Ifrim

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in Ghent, Belgium, in September 2020. The 15 full papers presented in this book were carefully reviewed and selected from 29 submissions. The selected papers are devoted to topics such as Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Early Classification of Temporal Data; Deep Learning and Learning Representations for Temporal Data; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Space-Temporal Statistical Analysis; Functional Data Analysis Methods; Temporal Data Streams; Interpretable Time-Series Analysis Methods; Dimensionality Reduction, Sparsity, Algorithmic Complexity and Big Data Challenge; and Bio-Informatics, Medical, Energy Consumption, Temporal Data.

Advanced Analytics and Learning on Temporal Data: 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers (Lecture Notes in Computer Science #13114)

by Vincent Lemaire Simon Malinowski Anthony Bagnall Thomas Guyet Romain Tavenard Georgiana Ifrim

This book constitutes the refereed proceedings of the 6th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2021, held during September 13-17, 2021. The workshop was planned to take place in Bilbao, Spain, but was held virtually due to the COVID-19 pandemic. The 12 full papers presented in this book were carefully reviewed and selected from 21 submissions. They focus on the following topics: Temporal Data Clustering; Classification of Univariate and Multivariate Time Series; Multivariate Time Series Co-clustering; Efficient Event Detection; Modeling Temporal Dependencies; Advanced Forecasting and Prediction Models; Cluster-based Forecasting; Explanation Methods for Time Series Classification; Multimodal Meta-Learning for Time Series Regression; and Multivariate Time Series Anomaly Detection.

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