Snowflake Essentials
Understand the essentials of the Snowflake Database and the overall Snowflake Data Cloud. This book covers how Snowflake's architecture is different from prior on-premises and cloud databases. The authors also discuss, from an insider perspective, how Snowflake grew so fast to become the largest software IPO of all time.Snowflake was the first database made specifically to be optimized with a cloud architecture. This book helps you get started using Snowflake by first understanding its architecture and what separates it from other database platforms you may have used. You will learn about setting up users and accounts, and then creating database objects. You will know how to load data into Snowflake and query and analyze that data, including unstructured data such as data in XML and JSON formats. You will also learn about Snowflake's compute platform and the different data sharing options that are available. What YouWill LearnRun analytics in the Snowflake Data CloudCreate users and roles in SnowflakeSet up security in SnowflakeSet up resource monitors in SnowflakeSet up and optimize Snowflake ComputeLoad, unload, and query structured and unstructured data (JSON, XML) within SnowflakeUse Snowflake Data Sharing to share dataSet up a Snowflake Data ExchangeUse the Snowflake Data Marketplace Who This Book Is ForDatabase professionals or information technology professionals who want to move beyond traditional database technologies by learning Snowflake, a new and massively scalable cloud-based database solution
Oracle Database Administration
Oracle database administration requires a vast amount of information and an ability to perform a myriad of tasks--from installation to tuning to network troubleshooting to overall daily administration. Oracle provides many tools for performing these tasks; the trick is knowing what tool is right for the job, what commands you need to issue (and when), and what parameters and privileges you need to set. And, as every DBA knows, you need to know how do all this under pressure, while you face crisis after crisis. This book provides a concise reference to the enormous store of information an Oracle DBA needs every day (as well as what's needed only when disaster strikes). It's crammed full of quick-reference tables, task lists, and other summary material that both novice and expert DBAs will use time and time again. It covers the commands and operations new to Oracle8, but also provides Oracle7 information for sites still running earlier versions. Oracle Database Administration provides two types of material: DBA tasks--chapters summarizing how to perform critical DBA functions: installation, performance tuning, preventing data loss, networking, security and monitoring, auditing, query optimization, and the use of various Oracle tools and utilities DBA reference--chapters providing a quick reference to the Oracle instance and database, the initialization (INIT.ORA) parameters, the SQL statements commonly used by DBAs, the data dictionary tables, the system privileges and roles, and the SQL*Plus, Export, Import, and SQL*Loader syntax The book also includes a resource summary with references to additional books, Web sites, and other online and offline resources of special use to Oracle DBAs. Oracle Database Administration is the single essential reference you'll turn to again and again. If you must choose only one book to use at the office, keep at home, or carry to a site you're troubleshooting, this will be that book.
Hands-On Data Preprocessing in Python
This book will make the link between data cleaning and preprocessing to help you design effective data analytic solutionsKey Features: Develop the skills to perform data cleaning, data integration, data reduction, and data transformationGet ready to make the most of your data with powerful data transformation and massaging techniquesPerform thorough data cleaning, such as dealing with missing values and outliersBook Description: Data preprocessing is the first step in data visualization, data analytics, and machine learning, where data is prepared for analytics functions to get the best possible insights. Around 90% of the time spent on data analytics, data visualization, and machine learning projects is dedicated to performing data preprocessing.This book will equip you with the optimum data preprocessing techniques from multiple perspectives. You'll learn about different technical and analytical aspects of data preprocessing - data collection, data cleaning, data integration, data reduction, and data transformation - and get to grips with implementing them using the open source Python programming environment. This book will provide a comprehensive articulation of data preprocessing, its whys and hows, and help you identify opportunities where data analytics could lead to more effective decision making. It also demonstrates the role of data management systems and technologies for effective analytics and how to use APIs to pull data.By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques; and handle outliers or missing values to effectively prepare data for analytic tools.What You Will Learn: Use Python to perform analytics functions on your dataUnderstand the role of databases and how to effectively pull data from databasesPerform data preprocessing steps defined by your analytics goalsRecognize and resolve data integration challengesIdentify the need for data reduction and execute itDetect opportunities to improve analytics with data transformationWho this book is for: Junior and senior data analysts, business intelligence professionals, engineering undergraduates, and data enthusiasts looking to perform preprocessing and data cleaning on large amounts of data will find this book useful. Basic programming skills, such as working with variables, conditionals, and loops, along with beginner-level knowledge of Python and simple analytics experience, are assumed.
Enabling Technologies for the Successful Deployment of Industry 4.0
This book offers the latest research advances in the field of Industry 4.0, focusing on enabling technologies for its deployment in a comprehensive way. This book offers successful implementation of technologies such as artificial intelligence, augmented and virtual reality, autonomous and collaborative robots, cloud computing, and up-to-date guidelines. It investigates how the technologies and principles surrounding Industry 4.0 (e.g., interoperability, decentralized decisions, information transparency, etc.) serve as support for organizational routines and workers (and vice versa). Included are applications of technologies for different sectors and environments as well as for the supply chain management. It also offers a domestic and international mix of case studies that spotlight successes and failures. FeaturesProvides a historical review of Industry 4.0 and its rootsDiscusses the applications of technologies in different sectors and environments (e.g., public vs. private)Presents key enabling technologies for successful implementation in any industrial and service environmentOffers case studies of successes and failures to illustrate how to put theory into practiceInvestigates how technologies serve as support for organizational routines and workers
Data Science
The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on challenging topics in the area surrounding data science. In this book, some of the chapters are written in tutorial style concerning machine learning algorithms, data analysis, information design, infographics, relevant applications, etc. The book is structured as follows: - Part I: Data Science: Theory, Concepts, and AlgorithmsThis part comprises five chapters on data Science theory, concepts, techniques and algorithms. - Part II: Data Design and AnalysisThis part comprises five chapters on data design and analysis.- Part III: Applications and New Trends in Data ScienceThis part comprises four chapters on applications and new trends in data science.
Computational Intelligence in Data Science
This book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science.
Intelligent Workloads at the Edge
Explore IoT, data analytics, and machine learning to solve cyber-physical problems using the latest capabilities of managed services such as AWS IoT Greengrass and Amazon SageMakerKey Features: Accelerate your next edge-focused product development with the power of AWS IoT GreengrassDevelop proficiency in architecting resilient solutions for the edge with proven best practicesHarness the power of analytics and machine learning for solving cyber-physical problemsBook Description: The Internet of Things (IoT) has transformed how people think about and interact with the world. The ubiquitous deployment of sensors around us makes it possible to study the world at any level of accuracy and enable data-driven decision-making anywhere. Data analytics and machine learning (ML) powered by elastic cloud computing have accelerated our ability to understand and analyze the huge amount of data generated by IoT. Now, edge computing has brought information technologies closer to the data source to lower latency and reduce costs.This book will teach you how to combine the technologies of edge computing, data analytics, and ML to deliver next-generation cyber-physical outcomes. You'll begin by discovering how to create software applications that run on edge devices with AWS IoT Greengrass. As you advance, you'll learn how to process and stream IoT data from the edge to the cloud and use it to train ML models using Amazon SageMaker. The book also shows you how to train these models and run them at the edge for optimized performance, cost savings, and data compliance.By the end of this IoT book, you'll be able to scope your own IoT workloads, bring the power of ML to the edge, and operate those workloads in a production setting.What You Will Learn: Build an end-to-end IoT solution from the edge to the cloudDesign and deploy multi-faceted intelligent solutions on the edgeProcess data at the edge through analytics and MLPackage and optimize models for the edge using Amazon SageMakerImplement MLOps and DevOps for operating an edge-based solutionOnboard and manage fleets of edge devices at scaleReview edge-based workloads against industry best practicesWho this book is for: This book is for IoT architects and software engineers responsible for delivering analytical and machine learning-backed software solutions to the edge. AWS customers who want to learn and build IoT solutions will find this book useful. Intermediate-level experience with running Python software on Linux is required to make the most of this book.
Icwe 2021 Workshops
This book constitutes the thoroughly refereed post-workshop proceedings of the 21th International Conference on Web Engineering, ICWE 2021, held in Biarritz, France, in May 2021.*The first international workshop on Big data-driven Edge Cloud Services (BECS 2021) was held to provide a venue in which scholars and practitioners can share their experiences and present on-going work on providing value-added Web services for users by utilizing big data in edge cloud environments. The 5 revised full papers and 1 revised short contribution selected from 11 submissions are presented with 2 invited papers.*The conference was held virtually due to the COVID-19 pandemic.
Computational Data and Social Networks
This book constitutes the refereed proceedings of the 10th International Conference on Computational Data and Social Networks, CSoNet 2021, which was held online during November 15-17, 2021. The conference was initially planned to take place in Montreal, Quebec, Canada, but changed to an online event due to the COVID-19 pandemic. The 24 full and 8 short papers included in this book were carefully reviewed and selected from 57 submissions. They were organized in topical sections as follows: Combinatorial optimization and learning; deep learning and applications to complex and social systems; measurements of insight from data; complex networks analytics; special track on fact-checking, fake news and malware detection in online social networks; and special track on information spread in social and data networks.
Roman’s Data Science How to monetize your data
An introduction to the field of data analysis written in jargon-free language that is not bogged down by programming code and mathematical formulas. It covers the most essential topics in the fields of data science, machine learning and business intelligence that you are likely to come across on a regular basis. The main goal is to help readers get the most out of their data, make business decisions and create information products - all without paying over the odds.In a career spanning over 20 years, the author has worked as a junior data analyst, headed up the analytics division of an $10-billion company and co-founded a recommendation systems startup. The text was edited by a professional journalist. It contains QR codes and links with links you can follow if you want a deeper understanding of the topics covered.
Web Information Systems Engineering - WISE 2021
This two-volume set constitutes the proceedings of the 22nd International Conference on Web Information Systems Engineering, WISE 2021, held in Melbourne, VIC, Australia, in October 2021.The 55 full, 29 short and 5 demo papers, plus 2 tutorials were carefully reviewed and selected from 229 submissions. The papers are organized in the following topical sections: Part I: BlockChain and Crowdsourcing; Database System and Workflow; Data Mining and Applications; Knowledge Graph and Entity Linking; Graph Neural Network; Graph Query; Social Network; Spatial and Temporal Data Analysis.Part II: Deep Learning (1), Deep Learning (2), Recommender Systems (1), Recommender Systems (2), Text Mining (1), Text Mining (2), Service Computing and Cloud Computing (1), Service Computing and Cloud Computing (2), Tutorial and Demo.
Towards Open and Trustworthy Digital Societies
This book constitutes the refereed proceedings of the 23rd International Conference on Asia-Pacific Digital Libraries, ICADL 2021, which was held in December 2021. Due to COVID-19 pandemic the conference was held virtually.The 17 full, 14 short, and 5 practice papers presented in this volume were carefully reviewed and selected from 87 submissions. The papers were organized in topical sections named: Knowledge Discovery from Digital Collections; Search for Better User Experience; Information Extraction; Multimedia; Text Classification and Matching; Data Infrastructure for Digital Libraries; Data Modeling; Neural-based Learning.
Tableau for Business Users
Learn Tableau by working through concrete examples and issues that you are likely to face in your day-to-day work. Author Shankar Arul starts by teaching you the fundamentals of data analytics before moving on to the core concepts of Tableau. You will learn how to create calculated fields, and about the currently available calculation functionalities in Tableau, including Basic Expressions, Level of Detail (LOD) Expressions, and Table Calculations. As the book progresses, you'll be walked through comparisons and trend calculations using tables. A concluding chapter on dashboarding will show you how to build actionable dashboards to communicate analysis and visualizations. You'll also see how Tableau can complement and communicate with Excel. After completing this book, you will be ready to tackle the challenges of data analytics using Tableau without getting bogged down by the technicalities of the tool. What Will You Learn Master the core concepts of Tableau Automate and simplify dashboards to help business users Understand the basics of data visualization techniques Leverage powerful features such as parameters, table calculations, level of detail expressions, and more Who is This book For Business analysts, data analysts, as well as financial analysts.
Web Information Systems Engineering - WISE 2021
This two-volume set constitutes the proceedings of the 22nd International Conference on Web Information Systems Engineering, WISE 2021, held in Melbourne, VIC, Australia, in October 2021.The 55 full, 29 short and 5 demo papers, plus 2 tutorials were carefully reviewed and selected from 229 submissions. The papers are organized in the following topical sections: Part I: BlockChain and Crowdsourcing; Database System and Workflow; Data Mining and Applications; Knowledge Graph and Entity Linking; Graph Neural Network; Graph Query; Social Network; Spatial and Temporal Data Analysis.Part II: Deep Learning (1), Deep Learning (2), Recommender Systems (1), Recommender Systems (2), Text Mining (1), Text Mining (2), Service Computing and Cloud Computing (1), Service Computing and Cloud Computing (2), Tutorial and Demo.
Data Science
The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.
Innovation for Systems Information and Decision
This book constitutes the refereed proceedings of the Third International Meeting on Innovation for Systems Information and Decision, INSID 2021, which was held during December 1-3, 2021. The conference was initially planned to take place in Recife, Brazil, but changed to a virtual meeting due to the COVID-19 pandemic. The 9 full papers presented in this volume were carefully reviewed and selected from a total of 76 submissions. They reflect methodological improvements and advances in multi-criteria decision-making/multi-criteria decision-aid (MCDM/MCDA) oriented toward real-world applications, which contribute to the understanding of relevant developments of current research on and future trends of innovation for systems information and decision.
Transactions on Large-Scale Data- and Knowledge-Centered Systems L
The LNCS journal Transactions on Large-Scale Data and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability.This, the 50th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains five fully revised selected regular papers. Topics covered include data anonymization, quasi-identifier discovery methods, symbolic time series representation, detection of anomalies in time series, data quality management in biobanks, and the use of multi-agent technology in the design of intelligent systems for maritime transport.
Intelligent Systems
The two-volume set LNAI 13073 and 13074 constitutes the proceedings of the 10th Brazilian Conference on Intelligent Systems, BRACIS 2021, held in S瓊o Paolo, Brazil, in November-December 2021. The total of 77 papers presented in these two volumes was carefully reviewed and selected from 192 submissions.The contributions are organized in the following topical sections: Part I: Agent and Multi-Agent Systems, Planning and Reinforcement Learning; Evolutionary Computation, Metaheuristics, Constrains and Search, Combinatorial and Numerical Optimization, Knowledge Representation, Logic and Fuzzy Systems; Machine Learning and Data Mining. Part II: Multidisciplinary Artificial and Computational Intelligence and Applications; Neural Networks, Deep Learning and Computer Vision; Text Mining and Natural Language Processing. Due to the COVID-2019 pandemic, BRACIS 2021 was held as a virtual event.
Creating Actionable Insights Using Tableau CRM
Leverage Tableau CRM to generate valuable business insights and solve business problems efficientlyKey Features: Extract, combine, transform, and visualize your data to derive business insights using Tableau CRMGain hands-on experience as you walk through practical dashboard use cases in Tableau CRMLearn how to build best-in-class dashboards from a Tableau CRM thought leaderBook Description: Tableau CRM, formerly Einstein Analytics, is a powerful and versatile data analytics platform that enables organizations to extract, combine, transform, and visualize their data to create valuable business insights. Despite being a highly capable tool and in high demand in the industry, proficiency in Tableau CRM skills is hard to find.Creating Actionable Insights Using Tableau CRM provides a hands-on approach to Tableau CRM implementation and associated methodologies that will have you up and running and productive in no time. The book provides you with detailed explanations of essential concepts to help you to gain confidence and become competent in using the Tableau CRM platform for data extraction, combination, transformation, visualization, and action. As you make progress, you'll understand what Tableau CRM is and where it provides business value. You'll also learn how to bring your data together in Tableau CRM, build datasets and lenses for data analysis, create effective analytics dashboards for visualization and consumption by end users, and build dashboard actions that take the user from data to insight to action with ease.By the end of this Tableau book, you'll be able to solve business problems using Tableau CRM and design, build, test, and deploy Tableau CRM analytics dashboards efficiently.What You Will Learn: Implement and configure Tableau CRM from scratchBuild your first Tableau CRM analytics app and embed your Tableau CRM dashboards in Salesforce to enhance user adoptionConnect Salesforce and external data with Tableau CRM and create datasetsCreate a data recipe and get familiar with the recipe UIBuild a custom dashboard in Tableau CRM using the dashboard editorUse lenses to create a Tableau CRM analytics dashboardConfigure and implement data security and governanceBuild configured record actions to automate data directly in SalesforceWho this book is for: This book is for data analysts, business analysts, BI professionals, and Salesforce users who want to explore Tableau CRM's capabilities and features. Basic knowledge of Salesforce and data analytics is assumed to get the most out of this book.
Enterprise Applications, Markets and Services in the Finance Industry
Financial Innovation.- The MiFIR Trading Obligation: Impact on Trading Volume and Liquidity in Electronic Trading.- Open Innovation Effectiveness in the Financial Services Sector.- Identification of financial statement fraud in Greece by using computational intelligence techniques.- What Sort of Asset? Bitcoin Analysed.- Blockchained Sukuk-financing.- Market data Analytics.- The Role of Customer Retention in Business Outcomes of Online Service Providers.- Using NSIA framework to evaluate impact of sentiment datasets on intraday financial market measures: a case study.- Financial Data Visualization in 3D on Immersive Virtual Reality Displays.- Document Representation for Text Mining: Opportunities for Analytics in Finance.- Semantic Modelling.- A Semantic Model Based Framework for Regulatory Reporting Process Management.- Applying Ontology-informed Lattice Reduction Using the Discrimination Power Index to Financial Domain.- A Statistical Learning Ontology for Managing Analytics Knowledge.
Digital Future of Healthcare
This book focuses on the applications of different digital platforms in the field of healthcare. It describes different devices used in digital healthcare, their benefits, diagnosis, use in treatment, and use cases related to mobile healthcare. Further, it covers machine and deep learning, blockchain technology, big data analytics as relevant to digital healthcare, telehealth technology, and digital applications in the field of push-and-pull pharma marketing. Overall, it enables readers to understand the basics of decision-making processes using digital techniques for the healthcare field. Features: Discusses various aspects of digitization of healthcare systems Examines deployment of machine learning including IoT and medical analytics Provides studies on the design, implementation, development, and management of intelligent healthcare systems Includes sensor-based digitization of healthcare data Reviews real-time advancement and challenges of digital communication in the field of healthcare This book is aimed at researchers and graduate students in healthcare, internet of things, machine learning, computer science, robotics, wearables, electrical engineering, and biomedical engineering.
Applied Edge AI
The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products, solutions and services. Businesses, individuals, and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools, the world is destined to have a dazzling array of edge-native, people-centric, event-driven, real-time, service-oriented, process-aware, and insights-filled services. Further on, business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules, AI algorithms and models, enabling frameworks, integrated platforms, accelerators, high-performance processors, etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations.Applied Edge AI: Concepts, Platforms, and Industry Use Cases focuses on the technologies, processes, systems, and applications that are driving this evolution. It examines the implementation technologies; the products, processes, platforms, patterns, and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips, algorithms, and tools to implement Edge AI, as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI, edge computing, and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication
Future Data and Security Engineering
This book constitutes the proceedings of the 8th International Conference on Future Data and Security Engineering, FDSE 2021, which was supposed to be held in Ho Chi Minh City, Vietnam, in November 2021, but the conference was held virtually due to the COVID-19 pandemic. The 24 full papers presented together with 2 invited keynotes were carefully reviewed and selected from 168 submissions. The selected papers are organized into the following topical headings: Big Data Analytics and Distributed Systems; Advances in Machine Learning for Big Data Analytics; Industry 4.0 and Smart City: Data Analytics and Security; Blockchain and IoT Applications; Machine Learning and Artificial Intelligence for Security and Privacy; Emerging Data Management Systems and Applications.
Smart Objects and Technologies for Social Good
This book constitutes the refereed post-conference proceedings of the 7th EAI International Conference on Smart Objects and Technologies for social Good, GOODTECHS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were selected from 53 submissions and issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights. The papers are arranged in tracks on machine learning; IoT; social considerations of technology; technology and ageing; healthcare.
Intelligent Data Engineering and Automated Learning - IDEAL 2021
This book constitutes the refereed proceedings of the 22nd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2021, which took place during November 25-27, 2021. The conference was originally planned to take place in Manchester, UK, but was held virtually due to the COVID-19 pandemic.The 61 full papers included in this book were carefully reviewed and selected from 85 submissions. They deal with emerging and challenging topics in intelligent data analytics and associated machine learning paradigms and systems. Special sessions were held on clustering for interpretable machine learning; machine learning towards smarter multimodal systems; and computational intelligence for computer vision and image processing.
Engineering Artificially Intelligent Systems
Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time.To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.
Service-Oriented Computing
This book constitutes the proceedings of the 19th International Conference on Service-Oriented Computing, ICSOC 2020, which is held virtually in November 2021.The 29 full, 28 short, and 3 vision papers included in this volume were carefully reviewed and selected from 189 submissions. They were organized in topical sections named: Blockchains and smart contracts, Architectures, microservices and APIs, Applications, Internet-of-Things, crowdsourced, social, and conversational services, Service composition and recommendation, Cloud computing, and Edge computing.
Optimizing Databricks Workloads
Accelerate computations and make the most of your data effectively and efficiently on DatabricksKey Features: Understand Spark optimizations for big data workloads and maximizing performanceBuild efficient big data engineering pipelines with Databricks and Delta LakeEfficiently manage Spark clusters for big data processing Book Description: Databricks is an industry-leading, cloud-based platform for data analytics, data science, and data engineering supporting thousands of organizations across the world in their data journey. It is a fast, easy, and collaborative Apache Spark-based big data analytics platform for data science and data engineering in the cloud.In Optimizing Databricks Workloads, you will get started with a brief introduction to Azure Databricks and quickly begin to understand the important optimization techniques. The book covers how to select the optimal Spark cluster configuration for running big data processing and workloads in Databricks, some very useful optimization techniques for Spark DataFrames, best practices for optimizing Delta Lake, and techniques to optimize Spark jobs through Spark core. It contains an opportunity to learn about some of the real-world scenarios where optimizing workloads in Databricks has helped organizations increase performance and save costs across various domains.By the end of this book, you will be prepared with the necessary toolkit to speed up your Spark jobs and process your data more efficiently.What You Will Learn: Get to grips with Spark fundamentals and the Databricks platformProcess big data using the Spark DataFrame API with Delta LakeAnalyze data using graph processing in DatabricksUse MLflow to manage machine learning life cycles in DatabricksFind out how to choose the right cluster configuration for your workloadsExplore file compaction and clustering methods to tune Delta tablesDiscover advanced optimization techniques to speed up Spark jobsWho this book is for: This book is for data engineers, data scientists, and cloud architects who have working knowledge of Spark/Databricks and some basic understanding of data engineering principles. Readers will need to have a working knowledge of Python, and some experience of SQL in PySpark and Spark SQL is beneficial.
Computational Intelligence in Data Science
This book constitutes the refereed post-conference proceedings of the Third IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2020, held in Chennai, India, in February 2020.The 19 revised full papers and 8 revised short papers presented were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: computational intelligence for text analysis; computational intelligence for image and video analysis; and data science.
Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications
This book constitutes the proceedings of the 8th International Conference on Future Data and Security Engineering, FDSE 2021, held in Ho Chi Minh City, Vietnam, in November 2021.*The 28 full papers and 8 short were carefully reviewed and selected from 168 submissions. The selected papers are organized into the following topical headings: big data analytics and distributed systems; security and privacy engineering; industry 4.0 and smart city: data analytics and security; blockchain and access control; data analytics and healthcare systems; and short papers: security and data engineering.* The conference was held virtually due to the COVID-19 pandemic.
The Practice of Enterprise Modeling
This book constitutes the proceedings papers of the 14th IFIP Working Conference on the Practice of Enterprise Modeling, held in Riga, Latvia, during November 24-26, 2021. PoEM offers a forum for sharing experiences and knowledge between the academic community and practitioners from industry and the public sector. This year the theme of the conference is the use of enterprise modeling and enterprise architecture towards ensuring sustainability and resilience of enterprises and societies. The 14 full and 6 short papers presented in this volume were carefully reviewed and selected from a total of 47 submissions. They were organized in topical sections named: enterprise modeling and enterprise architecture; enterprise modeling methods and method engineering; business process modeling and management; requirements engineering for privacy, security and governance; and case studies and experiences.
Kafka: The Definitive Guide
Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes. Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer. You'll examine: Best practices for deploying and configuring Kafka Kafka producers and consumers for writing and reading messages Patterns and use-case requirements to ensure reliable data delivery Best practices for building data pipelines and applications with Kafka How to perform monitoring, tuning, and maintenance tasks with Kafka in production The most critical metrics among Kafka's operational measurements Kafka's delivery capabilities for stream processing systems
Mobile Multimedia Communications
This book constitutes the thoroughly refereed post-conference proceedings of the 14th International Conference on Mobile Multimedia Communications, Mobimedia 2021, held in July 2021. Due to COVID-19 pandemic the conference was held virtually. The 66 revised full papers presented were carefully selected from 166 submissions. The papers are organized in topical sections as follows: Internet of Things and Wireless Communications Communication; Strategy Optimization and Task Scheduling Oral Presentations; Privacy Computing Technology; Cyberspace Security and Access control; Neural Networks and Feature Learning Task Classification and Prediction; Object Recognition and Detection.
Logistics and Supply Chain Management
This book constitutes selected and revised papers from the 7th International Conference Logistics and Supply Chain Management, held in December 2020 in Tehran, Iran. Due to the COVID-19 pandemic the conference was held online. The 17 full papers and 2 short papers pressented were thoroughly reviewed and selected out of 70 submissions. The papers are organized in the topical sections on ​information technology in supply chain management; production/scheduling and transportation in supply chain management; sustainable and resilient supply chain management; humanitarian supply chain management.
Data Mining and Big Data
​This two-volume set, CCIS 1453 and CCIS 1454, constitutes refereed proceedings of the 6th International Conference on Data Mining and Big Data, DMBD 2021, held in Guangzhou, China, in October 2021. The 57 full papers and 28 short papers presented in this two-volume set were carefully reviewed and selected from 258 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.
Machine Translation
This book constitutes the refereed proceedings of the 17th China Conference on Machine Translation, CCMT 2020, held in Xining, China, in October 2021. The 10 papers presented in this volume were carefully reviewed and selected from 25 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
Data Mining and Big Data
This two-volume set, CCIS 1453 and CCIS 1454, constitutes refereed proceedings of the 6th International Conference on Data Mining and Big Data, DMBD 2021, held in Guangzhou, China, in October 2021. The 57 full papers and 28 short papers presented in this two-volume set were carefully reviewed and selected from 258 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.
The Little Book of Artificial Intelligence
This book is a brief introduction to artificial intelligence. It is intended for readers, in business, education, government, and self-edification. The author would like to thank his wife Margaret for helping with the manuscript. As in most disciplines, some of the subject matter is new and some of the subject matter is not so new, especially to persons trained in the subject of computers. A person with a degree in computer science should know it already. Artificial intelligence is an important subject to the modern world, and some disciplines have already benefitted greatly from it. The reader can survey the subject matter in any order he or she pleases. The busy executive can benefit greatly from it their parent organization. Executives in finance and banking can use to understand what is going on in their endeavors. Artificial intelligence is not only software but uses specially prepared software to take intellectual benefit in understanding what his or her data systems are doing. Artificial intelligence is something for the future from self-driving vehicles to self-managed business.
The Little Book of Artificial Intelligence
This book is a brief introduction to artificial intelligence. It is intended for readers, in business, education, government, and self-edification. The author would like to thank his wife Margaret for helping with the manuscript. As in most disciplines, some of the subject matter is new and some of the subject matter is not so new, especially to persons trained in the subject of computers. A person with a degree in computer science should know it already. Artificial intelligence is an important subject to the modern world, and some disciplines have already benefitted greatly from it. The reader can survey the subject matter in any order he or she pleases. The busy executive can benefit greatly from it their parent organization. Executives in finance and banking can use to understand what is going on in their endeavors. Artificial intelligence is not only software but uses specially prepared software to take intellectual benefit in understanding what his or her data systems are doing. Artificial intelligence is something for the future from self-driving vehicles to self-managed business.
Blockchain for International Security
This book intersects the distributed ledger technology (DLT) community with the international security community. Given the increasing application of blockchain technology in the fields of business and international development, there is a growing body of study on other use cases. For instance, can blockchain have a significant role in preserving and improving international security? This book explores this question in the context of preventing the proliferation of some of the most dangerous materials in the world-items that if not secured can lend to the development of weapons of mass destruction. It considers how blockchain can increase efficiencies in the global trade of nuclear and chemical materials and technology, thereby increasing assurances related to compliance with international nonproliferation and disarmament treaties.
Text Mining with MATLAB(R)
Text Mining with MATLAB(R) provides a comprehensive introduction to text mining using MATLAB. It is designed to help text mining practitioners, as well as those with little-to-no experience with text mining in general, familiarize themselves with MATLAB and its complex applications. The book is structured in three main parts: The first part, Fundamentals, introduces basic procedures and methods for manipulating and operating with text within the MATLAB programming environment. The second part of the book, Mathematical Models, is devoted to motivating, introducing, and explaining the two main paradigms of mathematical models most commonly used for representing text data: the statistical and the geometrical approach. Eventually, the third part of the book, Techniques and Applications, addresses general problems in text mining and natural language processing applications such as document categorization, document search, content analysis, summarization, question answering, and conversational systems. This second edition includes updates in line with the recently released "Text Analytics Toolbox" within the MATLAB product and introduces three new chapters and six new sections in existing ones. All descriptions presented are supported with practical examples that are fully reproducible. Further reading, as well as additional exercises and projects, are proposed at the end of each chapter for those readers interested in conducting further experimentation.
Extending Power BI with Python and R
Perform more advanced analysis and manipulation of your data beyond what Power BI can do to unlock valuable insights using Python and RKey Features: Get the most out of Python and R with Power BI by implementing non-trivial codeLeverage the toolset of Python and R chunks to inject scripts into your Power BI dashboardsImplement new techniques for ingesting, enriching, and visualizing data with Python and R in Power BIBook Description: Python and R allow you to extend Power BI capabilities to simplify ingestion and transformation activities, enhance dashboards, and highlight insights. With this book, you'll be able to make your artifacts far more interesting and rich in insights using analytical languages.You'll start by learning how to configure your Power BI environment to use your Python and R scripts. The book then explores data ingestion and data transformation extensions, and advances to focus on data augmentation and data visualization. You'll understand how to import data from external sources and transform them using complex algorithms. The book helps you implement personal data de-identification methods such as pseudonymization, anonymization, and masking in Power BI. You'll be able to call external APIs to enrich your data much more quickly using Python programming and R programming. Later, you'll learn advanced Python and R techniques to perform in-depth analysis and extract valuable information using statistics and machine learning. You'll also understand the main statistical features of datasets by plotting multiple visual graphs in the process of creating a machine learning model.By the end of this book, you'll be able to enrich your Power BI data models and visualizations using complex algorithms in Python and R.What You Will Learn: Discover best practices for using Python and R in Power BI productsUse Python and R to perform complex data manipulations in Power BIApply data anonymization and data pseudonymization in Power BILog data and load large datasets in Power BI using Python and REnrich your Power BI dashboards using external APIs and machine learning modelsExtract insights from your data using linear optimization and other algorithmsHandle outliers and missing values for multivariate and time-series dataCreate any visualization, as complex as you want, using R scriptsWho this book is for: This book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.
The Semantic Web - ISWC 2021
This book constitutes the proceedings of the 20th International Semantic Web Conference, ISWC 2021, which took place in October 2021. Due to COVID-19 pandemic the conference was held virtually. The papers included in this volume deal with the latest advances in fundamental research, innovative technology, and applications of the Semantic Web, linked data, knowledge graphs, and knowledge processing on the Web. Papers are organized in a research track, resources and in-use track. The research track details theoretical, analytical and empirical aspects of the Semantic Web and its intersection with other disciplines. The resources track promotes the sharing of resources which support, enable or utilize semantic web research, including datasets, ontologies, software, and benchmarks. And finally, the in-use-track is dedicated to novel and significant research contributions addressing theoretical, analytical and empirical aspects of the Semantic Web and its intersection with other disciplines.
Advanced Speech Recognition: Concepts and Case Studies
This book majorly emphasizes on speech recognition and the associated tasks like speech optimization and modeling. Renowned veteran researchers from across the globe have contributed significant information in this profound book. The aim of this book is to serve as a comprehensive source of information and assist a broad spectrum of readers.
Database Systems: Design, Implementation and Management
Databases are structured accumulations of data, built for easy access and retrieval of data as per requirement. Such data frameworks are constructed according to industrial or organizational needs. Large databases require elaborate and efficient database management systems. They are of two types- general and special purpose. It has applications across a number of fields such as library systems, website management, inventory management, etc. This book sheds light on the modern techniques and methods of database system design, their applications and management. It elucidates concepts and innovative models around prospective developments with respect to database systems. This book will serve as a valuable source of reference for professionals, researchers and students in the fields of computer science and engineering, information science, knowledge management and software engineering.
Computational Mechanics
Computational mechanics is the study of mechanics through computational methods. This book on computational mechanics deals with numerical and computational modeling and their applications that can solve problems in mechanical engineering. This field has three main sub-fields which are mathematics, computer science and mechanics. Different approaches, evaluations, methodologies and advanced studies on this field have been included in this book. It elucidates concepts and innovative models around prospective developments with respect to computational mechanics. The book is appropriate for students seeking detailed information in this area as well as for experts. It will help the readers in keeping pace with the rapid changes in this field.
Monte Carlo Search
This book constitutes the refereed proceedings of the First Workshop on Monte Carlo Search, MCS 2020, organized in conjunction with IJCAI 2020. The event was supposed to take place in Yokohama, Japan, in July 2020, but due to the Covid-19 pandemic was held virtually on January 7, 2021. The 9 full papers of the specialized project were carefully reviewed and selected from 15 submissions. The following topics are covered in the contributions: discrete mathematics in computer science, games, optimization, search algorithms, Monte Carlo methods, neural networks, reinforcement learning, machine learning.
Handbook of Distributed Sensor Networks: Volume I
Some of the applications that have been derived from sensor networks can be found in the field of transport, environmental studies, engineering, production technologies, security, etc. A huge number of problems related to the input of data directly from sensors to an automated system can be solved by using distributed sensor systems. This book discusses distributed sensor networks by essentially focusing on applications and recent researches. It provides key ideas and approaches, which can help in the development of high performance computing solutions for complex sensor networks problems.
