Spatial Data and Intelligence
This book constitutes the proceedings of the Second International Conference on Spatial Data and Intelligence, SpatialDI 2021, which was held during April 22-24, 2021 in Hangzhou, China.The 14 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 72 submissions. They are organized in the topical sections named: traffic management, data science, and city analysis.
Business Process Management Forum
This book constitutes the proceedings of the BPM Forum of the 19th International Conference on Business Process Management, BPM 2021, which will take place in Rome, Italy, in September 2021. The BPM Forum offers innovative research papers characterized by their high potential of stimulating interesting discussion and scientific debate, although without yet reaching the same rigor as the papers accepted for the main conference. In this sense, the BPM Forum papers are characterized by novel ideas about emergent BPM topics. The 16 papers presented in this volume were carefully reviewed and selected from a total of 123 submissions to the main conference. They cover all areas of business process management, from process definition to variability, execution, visualization, monitoring, mining, and optimization.
Guide to Intelligent Data Science
Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of thesubject.
Logical Methods
Many believe mathematics is only about calculations, formulas, numbers, and strange letters. But mathematics is much more than just crunching numbers or manipulating symbols. Mathematics is about discovering patterns, uncovering hidden structures, finding counterexamples, and thinking logically. Mathematics is a way of thinking. It is an activity that is both highly creative and challenging. This book offers an introduction to mathematical reasoning for beginning university or college students, providing a solid foundation for further study in mathematics, computer science, and related disciplines. Written in a manner that directly conveys the sense of excitement and discovery at the heart of doing science, its 25 short and visually appealing chapters cover the basics of set theory, logic, proof methods, combinatorics, graph theory, and much more. In the book you will, among other things, find answers to: What is a proof? What is a counterexample?What does it mean to say that something follows logically from a set of premises?What does it mean to abstract over something?How can knowledge and information be represented and used in calculations?What is the connection between Morse code and Fibonacci numbers?Why could it take billions of years to solve Hanoi's Tower? Logical Methods is especially appropriate for students encountering such concepts for the very first time. Designed to ease the transition to a university or college level study of mathematics or computer science, it also provides an accessible and fascinating gateway to logical thinking for students of all disciplines.
The DataOps Revolution
DataOps is a new way of delivering data and analytics that is proven to get results. It enables IT and users to collaborate in the delivery of solutions that help organizations to embrace a data driven culture. This book is a narrative about real world issues involved in using DataOps to make data-driven decisions in modern organizations.
Big Data, IoT, and Machine Learning
This book discusses the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. It describes essential technical knowledge, building blocks, processes, design principles, and implementation of big data tools and machine learning techniques and applications for IoT projects.
Digital Transformation of Collaboration
This proceedings is focused on the emerging concept of Collaborative Innovation Networks (COINs). COINs are at the core of collaborative knowledge networks, distributed communities taking advantage of the wide connectivity and the support of communication technologies, spanning beyond the organizational perimeter of companies on a global scale. The book presents the refereed conference papers from the 7th International Conference on COINs, October 8-9, 2019, in Warsaw, Poland. It includes papers for both application areas of COINs, (1) optimizing organizational creativity and performance, and (2) discovering and predicting new trends by identifying COINs on the Web through online social media analysis. Papers at COINs19 combine a wide range of interdisciplinary fields such as social network analysis, group dynamics, design and visualization, information systems and the psychology and sociality of collaboration, and intercultural analysis through the lens of online social media. They will cover most recent advances in areas from leadership and collaboration, trend prediction and data mining, to social competence and Internet communication.
Data Processing with Optimus
Written by the core Optimus team, this comprehensive guide will help you to understand how Optimus improves the whole data processing landscape Key Features: Load, merge, and save small and big data efficiently with OptimusLearn Optimus functions for data analytics, feature engineering, machine learning, cross-validation, and NLPDiscover how Optimus improves other data frame technologies and helps you speed up your data processing tasksBook Description: Optimus is a Python library that works as a unified API for data cleaning, processing, and merging data. It can be used for handling small and big data on your local laptop or on remote clusters using CPUs or GPUs.The book begins by covering the internals of Optimus and how it works in tandem with the existing technologies to serve your data processing needs. You'll then learn how to use Optimus for loading and saving data from text data formats such as CSV and JSON files, exploring binary files such as Excel, and for columnar data processing with Parquet, Avro, and OCR. Next, you'll get to grips with the profiler and its data types - a unique feature of Optimus Dataframe that assists with data quality. You'll see how to use the plots available in Optimus such as histogram, frequency charts, and scatter and box plots, and understand how Optimus lets you connect to libraries such as Plotly and Altair. You'll also delve into advanced applications such as feature engineering, machine learning, cross-validation, and natural language processing functions and explore the advancements in Optimus. Finally, you'll learn how to create data cleaning and transformation functions and add a hypothetical new data processing engine with Optimus.By the end of this book, you'll be able to improve your data science workflow with Optimus easily.What You Will Learn: Use over 100 data processing functions over columns and other string-like valuesReshape and pivot data to get the output in the required formatFind out how to plot histograms, frequency charts, scatter plots, box plots, and moreConnect Optimus with popular Python visualization libraries such as Plotly and AltairApply string clustering techniques to normalize stringsDiscover functions to explore, fix, and remove poor quality dataUse advanced techniques to remove outliers from your dataAdd engines and custom functions to clean, process, and merge dataWho this book is for: This book is for Python developers who want to explore, transform, and prepare big data for machine learning, analytics, and reporting using Optimus, a unified API to work with Pandas, Dask, cuDF, Dask-cuDF, Vaex, and Spark. Although not necessary, beginner-level knowledge of Python will be helpful. Basic knowledge of the CLI is required to install Optimus and its requirements. For using GPU technologies, you'll need an NVIDIA graphics card compatible with NVIDIA's RAPIDS library, which is compatible with Windows 10 and Linux.
Information and Knowledge Systems
This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021.The International Conference on Information and Knowledge Systems (ICIKS 2021) gathered both researchers and practitioners in the fields of Information Systems, Artificial Intelligence, Knowledge Management and Decision Support. ICIKS seeks to promote discussions on various organizational, technological, and socio-cultural aspects of research in the design and use of information and knowledge systems in organizations. The 10 full and 2 short papers presented in this volume were carefully reviewed and selected from 32 submissions. They were organized in topical sections as follows: knowledge systems and decision making; machine learning, recommender systems, and knowledge systems; and security, artificial intelligence, and information systems.
Business Process Management: Blockchain and Robotic Process Automation Forum
This book constitutes the proceedings of the Blockchain and RPA Forum, held as part of the 19th International Conference on Business Process Management, BPM 2021, which took place during September 6-10, 2021, in Rome, Italy.The Blockchain Forum and the RPA Forum have in common that they are centered around an emerging and exciting technology. The blockchain is a sophisticated distributed ledger technology, while RPA software allows for mimicking human, repetitive actions. Each of these have the potential to fundamentally change how business processes are being orchestrated and executed in practice. The 8 papers presented in this volume were carefully reviewed and selected from a total of 14 submissions.
Information Systems: Research, Development, Applications, Education
This book constitutes the refereed proceedings of the 13th PLAIS EuroSymposium 2021 which was held in Sopot, Poland, on September 23, 2021. The objective of the PLAIS EuroSymposium 2021 is to promote and develop high quality research on all issues related to digital transformation. It provides a forum for IS researchers and practitioners in Europe and beyond to interact, collaborate, and develop this field. The 10 papers presented in this volume were carefully reviewed and selected from 34 submissions. They were organized in topical sections named: digital enterprises; smart cities; digital education; and innovative methods in data and process analysis.
Concurrent Data Processing in Elixir
Learn different ways of writing concurrent code in Elixir and increase your application's performance, without sacrificing scalability or fault-tolerance. Most projects benefit from running background tasks and processing data concurrently, but the world of OTP and various libraries can be challenging. Which Supervisor and what strategy to use? What about GenServer? Maybe you need back-pressure, but is GenStage, Flow, or Broadway a better choice? You will learn everything you need to know to answer these questions, start building highly concurrent applications in no time, and write code that's not only fast, but also resilient to errors and easy to scale. Whether you are building a high-frequency stock trading application or a consumer web app, you need to know how to leverage concurrency to build applications that are fast and efficient. Elixir and the OTP offer a range of powerful tools, and this guide will show you how to choose the best tool for each job, and use it effectively to quickly start building highly concurrent applications. Learn about Tasks, supervision trees, and the different types of Supervisors available to you. Understand why processes and process linking are the building blocks of concurrency in Elixir. Get comfortable with the OTP and use the GenServer behaviour to maintain process state for long-running jobs. Easily scale the number of running processes using the Registry. Handle large volumes of data and traffic spikes with GenStage, using back-pressure to your advantage. Create your first multi-stage data processing pipeline using producer, consumer, and producer-consumer stages. Process large collections with Flow, using MapReduce and more in parallel. Thanks to Broadway, you will see how easy it is to integrate with popular message broker systems, or even existing GenStage producers. Start building the high-performance and fault-tolerant applications Elixir is famous for today. What You Need: You'll need Elixir 1.9] and Erlang/OTP 22+ installed on a Mac OS X, Linux, or Windows machine.
Multimedia Technology and Enhanced Learning
This two-volume book constitutes the refereed proceedings of the 3rd International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021, held in April 2021. Due to the COVID-19 pandemic the conference was held virtually. The 97 revised full papers have been selected from 208 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Data Management Technologies and Applications
This book constitutes the thoroughly refereed proceedings of the 9th International Conference on Data Management Technologies and Applications, DATA 2020, which was supposed to take place in Paris, France, in July 2020. Due to the Covid-19 pandemic the event was held virtually. The 14 revised full papers were carefully reviewed and selected from 70 submissions. The papers deal with the following topics: datamining; decision support systems; data analytics; data and information quality; digital rights management; big data; knowledge management; ontology engineering; digital libraries; mobile databases; object-oriented database systems; data integrity.
Multimedia Technology and Enhanced Learning
This two-volume book constitutes the refereed proceedings of the 3rd International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021, held in April 2021. Due to the COVID-19 pandemic the conference was held virtually. The 97 revised full papers have been selected from 208 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Closing the Analytics Talent Gap
Organizations recognize that universities are rich resource for closing their analytical talent gaps. The book addresses the benefits and challenges of working with university analytics and data science programs at the undergraduate, masters, and doctoral levels.
Big Data, Political Campaigning and the Law
In this multidisciplinary book, experts from around the globe examine how data-driven political campaigning works, what challenges it poses for personal privacy and democracy, and how emerging practices should be regulated.
Maple in Mathematics Education and Research
This book constitutes refereed proceedings of the 4th Maple Conference, MC 2020, held in Waterloo, Ontario, Canada, in November 2020. The 25 revised full papers and 3 short papers were carefully reviewed and selected out of 75 submissions, one invited paper is also presented in the volume. The papers included in this book cover topics in education, algorithms, and applciations of the mathematical software Maple.
Applied Cryptography in Computer and Communications
This book constitutes the refereed post-conference proceedings of the First International Conference on Applied Cryptography in Computer and Communications, AC3 2021, and the First International Workshop on Security for Internet of Things (IoT). The conference was held in May 2021 and due to COVID-19 pandemic virtually.The 15 revised full papers were carefully reviewed and selected from 42 submissions. The papers present are grouped in 4 tracks on blockchain; authentication; secure computation; practical crypto application. They detail technical aspects of applied cryptography, including symmetric cryptography, public-key cryptography, cryptographic protocols, cryptographic implementations, cryptographic standards and practices.
Advances of Science and Technology
This two-volume set constitutes the refereed post-conference proceedings of the 8th International Conference on Advancement of Science and Technology, ICAST 2020, which took place in Bahir Dar, Ethiopia, in October 2020.The 74 revised full papers were carefully reviewed and selected from more than 200 submissions of which 157 were sent out for peer review. The papers present economic and technologic developments in modern societies in 6 tracks: Chemical, food and bio-process engineering; Electrical and computer engineering; IT, computer science and software engineering; Civil, water resources, and environmental engineering; Mechanical and industrial engineering; Material science and engineering.
Data Analytics and Management in Data Intensive Domains
This book constitutes the post-conference proceedings of the 22nd International Conference on Data Analytics and Management in Data Intensive Domains, DAMDID/RCDL 2020, held in Voronezh, Russia, in October 2020*.The 16 revised full papers and two keynotes were carefully reviewed and selected from 60 submissions. The papers are organized in the following topical sections: data Integration, conceptual models and ontologies; data management in semantic web; data analysis in medicine; data analysis in astronomy; information extraction from text.* The conference was held virtually due to the COVID-19 pandemic.
Advances of Science and Technology
This two-volume set constitutes the refereed post-conference proceedings of the 8th International Conference on Advancement of Science and Technology, ICAST 2020, which took place in Bahir Dar, Ethiopia, in October 2020.The 74 revised full papers were carefully reviewed and selected from more than 200 submissions of which 157 were sent out for peer review. The papers present economic and technologic developments in modern societies in 6 tracks: Chemical, food and bio-process engineering; Electrical and computer engineering; IT, computer science and software engineering; Civil, water resources, and environmental engineering; Mechanical and industrial engineering; Material science and engineering.
Geometric Science of Information
This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021.The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.
Getting Started with Streamlit for Data Science
Create, deploy, and test your Python applications, analyses, and models with ease using StreamlitKey Features: Learn how to showcase machine learning models in a Streamlit application effectively and efficientlyBecome an expert Streamlit creator by getting hands-on with complex application creationDiscover how Streamlit enables you to create and deploy apps effortlesslyBook Description: Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time.You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you'll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps.By the end of this book, you'll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.What You Will Learn: Set up your first development environment and create a basic Streamlit app from scratchExplore methods for uploading, downloading, and manipulating data in Streamlit appsCreate dynamic visualizations in Streamlit using built-in and imported Python librariesDiscover strategies for creating and deploying machine learning models in StreamlitUse Streamlit sharing for one-click deploymentBeautify Streamlit apps using themes, Streamlit Components, and Streamlit sidebarImplement best practices for prototyping your data science work with StreamlitWho this book is for: This book is for data scientists and machine learning enthusiasts who want to create web apps using Streamlit. Whether you're a junior data scientist looking to deploy your first machine learning project in Python to improve your resume or a senior data scientist who wants to use Streamlit to make convincing and dynamic data analyses, this book will help you get there! Prior knowledge of Python programming will assist with understanding the concepts covered.
Advances in the Theory of Probabilistic and Fuzzy Data Scientific Methods with Applications
This book focuses on the advanced soft computational and probabilistic methods that the authors have published over the past few years. It describes theoretical results and applications, and discusses how various uncertainty measures - probability, plausibility and belief measures - can be treated in a unified way. It also examines approximations of four notable probability distributions (Weibull, exponential, logistic and normal) using a unified probability distribution function, and presents a fuzzy arithmetic-based time series model that provides an easy-to-use forecasting technique. Lastly, it proposes flexible fuzzy numbers for Likert scale-based evaluations. Featuring methods that can be successfully applied in a variety of areas, including engineering, economics, biology and the medical sciences, the book offers useful guidelines for practitioners and researchers.
Experimental IR Meets Multilinguality, Multimodality, and Interaction
This book constitutes the refereed proceedings of the 12th International Conference of the CLEF Association, CLEF 2021, held virtually in September 2021.The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 11 full papers presented in this volume were carefully reviewed and selected from 21 submissions. This year, the contributions addressed the following challenges: application of neural methods for entity recognition as well as misinformation detection in the health area, skills extraction in job-match databases, stock market prediction using financial news, and extraction of audio features for podcast retrieval. In addition to this, the volume presents 5 "best of the labs" papers which were reviewed as full paper submissions with the same review criteria. 12 lab overview papers were accepted and represent scientific challenges based on new data sets and real world problems in multimodal and multilingual information access.
Human Aspects of Information Security and Assurance
This book constitutes the proceedings of the 15th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2021, held virtually in July 2021.The 18 papers presented in this volume were carefully reviewed and selected from 30 submissions. They are organized in the following topical sections: attitudes and perspectives; cyber security education; and people and technology.
The Textual Warehouse
Build a Textual Warehouse to help your organization understand and analyze documents through text analytics (both sentiment and non-sentiment analysis), to make better business decisions. Learn the important role of documents and text within your organization, the difference between identifying and qualifying text, and when you need document preprocessing. Appreciate the power of taxonomies and the necessity of textual ETL. Know how the textual warehouse architecture differs from the conventional data warehouse architecture and when to apply contextualization and textual disambiguation.About BillBill Inmon, the "father of the data warehouse," has written 60 books published in nine languages. ComputerWorld named Bill one of the ten most influential people in the history of the computer profession. Bill's latest adventure is the building of technology known as textual disambiguation. About RanjeetRanjeet Srivastava is a data management professional and an enterprise architect with more than 20 years in enterprise product research, development, and design of data-intensive mission-critical applications.
Smart and Intelligent Systems
In today's digital world, the words "smart" and intelligent" are now used to label devices, machinery, systems, and even environments. What is a "smart" system? Is "smart" synonymous to "intelligent"? If not, what does an "intelligent system" mean? Are all the smart systems intelligent?
National Cyber Summit (Ncs) Research Track 2021
Part I - Cyber Security EducationAn Integrated System for Connecting Cybersecurity Competency, Student Activities and Career Building Li-Chiou Chen, Andreea Cotoranu, Praviin Mandhare and Darren Hayes Simulating Industrial Control Systems using Node-RED and Unreal Engine 4 Steven Day, William Smallwood and Joshua Kuhn Student Educational Learning Experience Through Cooperative Research Melissa Hannis, Idongesit Mkpong-Ruffin and Drew Hamilton Digital Forensics Education: Challenges and Future Opportunities Megan Stigall and Kim-Kwang Raymond Choo Designing a Cybersecurity Curriculum Library: Best Practices from Digital Library Research Blair Taylor, Sidd Kaza and Melissa Dark Design of a Virtual Cybersecurity Escape Room Tania Williams and Omar El-Gayar Part II - Cyber Security Technology A Novel Method for the Automated Generation for JOP Chain Exploits Bramwell Brizendine, Austin Babcock and Josh Stroschien Increasing Log Availability in Unmanned Vehicle Systems Nicholas Carter, Peter Pommer, Duane Davis and Cynthia Irvine Testing Detection of K-Ary Code Obfuscated by Metamorphic and Polymorphic Techniques George Harter and Neil Rowe Enhancing Secure Coding Assistant System with Design by Contract and Programming Logic Wenhui Liang, Cui Zhang and Jun Dai Social Engineering Attacks in Healthcare Systems: A Survey Christopher Nguyen, Walt Williams, Brandon Didlake, Donte Mitchell, James McGinnis and Dipankar Dasgupta Identifying Anomalous Industrial-Control-System Network Flow Activity Using Cloud Honeypots Neil Rowe, Thuy Nguyen, Jeffrey Dougherty, Matthew Bieker and Darry Pilkington Risks of Electric Vehicle Supply Equipment Integration within Building Energy Management System Environments: A Look at Remote Attack Surface and Implications Roland Varriale, Michael Jaynes and Ryan Crawford
Intelligent Computing Theories and Application
This two-volume set of LNCS 12836 and LNCS 12837 constitutes - in conjunction with the volume LNAI 12838 - the refereed proceedings of the 17th International Conference on Intelligent Computing, ICIC 2021, held in Shenzhen, China in August 2021. The 192 full papers of the three proceedings volumes were carefully reviewed and selected from 458 submissions. The ICIC theme unifies the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. The theme for this conference is "Advanced Intelligent Computing Methodologies and Applications."The papers are organized in the following subsections: Artificial Intelligence in Real World Applications, Biomedical Informatics Theory and Methods, Complex Diseases Informatics, Gene Regulation Modeling and Analysis, Intelligent Computing in Computational Biology, and Protein Structure and Function Prediction.
Chinese Computational Linguistics
This book constitutes the proceedings of the 20th China National Conference on Computational Linguistics, CCL 2021, held in Hohhot, China, in August 2021.The 31 full presented in this volume were carefully reviewed and selected from 90 submissions. The conference papers covers the following topics such as Machine Translation and Multilingual Information Processing, Minority Language Information Processing, Social Computing and Sentiment Analysis, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications.
Computer Information Systems and Industrial Management
This book constitutes the proceedings of the 20th International Conference on Computer Information Systems and Industrial Management Applications, CISIM 2021, held in Elk, Poland, September 24-26, 2021. The 38 papers presented together with 1 invited speech and 3 abstracts of keynotes were carefully reviewed and selected from 69 submissions. The main topics covered by the chapters in this book are mobile and pervasive computing, machine learning, high performance computing, image processing, industrial management. Additionally, the reader will find interesting papers on computer information systems, biometrics, security systems, and sensor network service. The contributions are organized in the following topical sections: biometrics and pattern recognition applications; computer information systems and security; industrial management and other applications; machine learning and artificial neural networks; modelling and optimization, and others.Chapter 24 "A first step towards automated species recognition from camera trap images of mammals using AI in a European temperate forest" is published open access under a CC BY license (Creative Commons Attribution 4.0 International License).
Data Science for Economics and Finance
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Computational Advances in Bio and Medical Sciences
This book constitutes the proceedings of the 10th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2020, held in December 2020. Due to COVID-19 pandemic the conference was held virtually.The 6 regular and 5 invited papers presented in this book were carefully reviewed and selected from 16 submissions. The use of high throughput technologies is fundamentally changing the life sciences and leading to the collection of large amounts of biological and medical data. The papers show how the use of this data can help expand our knowledge of fundamental biological processes and improve human health - using novel computational models and advanced analysis algorithms.
Data-Driven Law
Data has reshaped industries around the world, from finance and medicine to sports. Law has trailed behind other industries, but is quickly following suit. For many years, law firms made important decisions - including very large decisions - based on limited experience (at best), or hunches (at worst). Data science is growing quickly in law firm
Teaching Data Analytics
Geared towards educators interested in developing curriculum related to data analytics. Contains best practices for individual courses and program development.
Advanced Information Systems Engineering
This book constitutes the proceedings of the 33rd International Conference on Advanced Information Systems Engineering, CAiSE 2021, which was held online during June 28-July 2, 2021. The conference was planned to take place in Melbourne, Australia, and changed to an online format due to the COVID-19 pandemic. The papers included in these proceedings focus on intelligent information systems and deal with novel approaches to IS engineering; models, methods and techniques in IS engineering; architectures and platforms for IS engineering; and domain specific and multi-aspect in IS engineering.
The Analytics Process
This book is about the process of using analytics and the capabilities of analytics in today's organizations. Cutting through the buzz surrounding the term analytics and the overloaded expectations about using analytics, the book demystifies analytics with an in-depth examination of concepts grounded in operations research and management science. Analytics as a set of tools and processes is only as effective as: The data with which it is working The human judgment applying the processes and understanding the output of these processes. For this reason, the book focuses on the analytics process. What is intrinsic to analytics' real organizational impact are the careful application of tools and the thoughtful application of their outcomes. This work emphasizes analytics as part of a process that supports decision-making within organizations. It wants to debunk overblown expectations that somehow analytics outputs or analytics as applied to other concepts, such as Big Data, are the be-all and end-all of the analytics process. They are, instead, only a step within a holistic and critical approach to management thinking that can create real value for an organization.To develop this holistic approach, the book is divided into two sections that examine concepts and applications. The first section makes the case for executive management taking a holistic approach to analytics. It draws on rich research in operations and management science that form the context in which analytics tools are to be applied. There is a strong emphasis on knowledge management concepts and techniques, as well as risk management concepts and techniques. The second section focuses on both the use of the analytics process and organizational issues that are required to make the analytics process relevant and impactful.
Multiagent Systems
Multiagent systems offer tremendous opportunities for development in computing and its applications. The objective of this book is to identify preliminary requirements and fundamental issues related to multiagent systems. The book is a comprehensive volume on the subject.
Valuing Data
Data has value, but our accounting methods do not give data a monetary value. This book presents a straight-forward, well-researched, practical solution to this problem by defining exactly what "data" is, explaining the role of data management in data asset valuations, and presenting an "open framework" - along with methods - for valuing data.
Text Mining with Machine Learning
The book provides explanations of principles of time-proven machine learning algorithms applied in text mining together with step-by-step demonstrations of how to reveal the semantic contents in real-world datasets using the popular R-language with its implemented machine learning algorithms.
Advances in Bias and Fairness in Information Retrieval
This book constitutes refereed proceedings of the Second International Workshop on Algorithmic Bias in Search and Recommendation, BIAS 2021, held in April, 2021. Due to the COVID-19 pandemic BIAS 2021 was held virtually. The 11 full papers and 3 short papers were carefully reviewed and selected from 37 submissions. The papers cover topics that go from search and recommendation in online dating, education, and social media, over the impact of gender bias in word embeddings, to tools that allow to explore bias and fairnesson the Web.
Data Science for Economics and Finance
This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.
Data Modeling for Azure Data Services
Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guideKey Features: Design a cost-effective, performant, and scalable database in AzureChoose and implement the most suitable design for a databaseDiscover how your database can scale with growing data volumes, concurrent users, and query complexityBook Description: Data is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation.Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory.By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution.What You Will Learn: Model relational database using normalization, dimensional, or Data Vault modelingProvision and implement Azure SQL DB and Azure Synapse SQL PoolsDiscover how to model a Data Lake and implement it using Azure StorageModel a NoSQL database and provision and implement an Azure Cosmos DBUse Azure Data Factory to implement ETL/ELT processesCreate a star schema model using dimensional modelingWho this book is for: This book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.
Exam Ref AZ-304 Microsoft Azure Architect Design Certification and Beyond
Master the Microsoft Azure platform and prepare for the AZ-304 certification exam by learning the key concepts needed to identify key stakeholder requirements and translate these into robust solutionsKey Features: Build secure and scalable solutions on the Microsoft Azure platformLearn how to design solutions that are compliant with customer requirementsWork with real-world scenarios to become a successful Azure architect, and prepare for the AZ-304 examBook Description: The AZ-304 exam tests an architect's ability to design scalable, reliable, and secure solutions in Azure based on customer requirements. Exam Ref AZ-304 Microsoft Azure Architect Design Certification and Beyond offers complete, up-to-date coverage of the AZ-304 exam content to help you prepare for it confidently, pass the exam first time, and get ready for real-world challenges.This book will help you to investigate the need for good architectural practices and discover how they address common concerns for cloud-based solutions. You will work through the CloudStack, from identity and access through to infrastructure (IaaS), data, applications, and serverless (PaaS). As you make progress, you will delve into operations including monitoring, resilience, scalability, and disaster recovery. Finally, you'll gain a clear understanding of how these operations fit into the real world with the help of full scenario-based examples throughout the book.By the end of this Azure book, you'll have covered everything you need to pass the AZ-304 certification exam and have a handy desktop reference guide.What You Will Learn: Understand the role of architecture in the cloudEnsure security through identity, authorization, and governanceFind out how to use infrastructure components such as compute, containerization, networking, and storage accountsDesign scalable applications and databases using web apps, functions, messaging, SQL, and Cosmos DBMaintain operational health through monitoring, alerting, and backupsDiscover how to create repeatable and reliable automated deploymentsUnderstand customer requirements and respond to their changing needsWho this book is for: This book is for Azure Solution Architects who advise stakeholders and help translate business requirements into secure, scalable, and reliable solutions. Junior architects looking to advance their skills in the Cloud will also benefit from this book. Experience with the Azure platform is expected, and a general understanding of development patterns will be advantageous.
Computational Sciences - Modelling, Computing and Soft Computing
This book constitutes revised and selected papers of the First International Conference on Computational Sciences - Modelling, Computing and Soft Computing, held in Kozhikode, Kerala, India, in September 2020. The 15 full papers and 6 short papers presented were thoroughly reviewed and selected from the 150 submissions. They are organized in the topical secions on computing; soft computing; general computing; modelling.
Advances in Databases and Information Systems
This book constitutes the proceedings of the 25th European Conference on Advances in Databases and Information Systems, ADBIS 2021, held in Tartu, Estonia, in August 2021. The 18 full papers presented together with 3 keynotes were carefully reviewed and selected from 70 submissions. The selected papers span a wide spectrum of topics in databases and related technologies, tackling challenging problems and presenting inventive and efficient solutions. They are organized in 5 sessions: patterns and events, social media and text mining, indexes, queries and constraints, high-dimensional data and data streams, and data integration.
