Collaboration Technologies and Social Computing
This volume constitutes the proceedings of the 27th International Conference on Collaboration Technologies and Social Computing, CollabTech 2021, held August/September 2021. Due to VOVID-19 pandemic is was held virtually. The 5 full and 4 work-in-process papers presented in this volume were carefully reviewed and selected from 19 submissions. The papers focus on innovative technical, human and organizational approaches to expand collaboration support including computer science, management science, design science, cognitive and social science.
Developing Modern Database Applications with PostgreSQL
Get up to speed with core PostgreSQL tasks such as database administration, application development, database performance monitoring, and database testingKey Features: Build real-world enterprise database management systems using Postgres 12 featuresExplore the development, administrative and security aspects of PostgreSQL 12Implement best practices from industry experts to build powerful database applicationsBook Description: PostgreSQL is an open-source object-relational database management system (DBMS) that provides enterprise-level services, including high performance and scalability. This book is a collection of unique projects providing you with a wealth of information relating to administering, monitoring, and testing PostgreSQL. The focus of each project is on both the development and the administrative aspects of PostgreSQL.Starting by exploring development aspects such as database design and its implementation, you'll then cover PostgreSQL administration by understanding PostgreSQL architecture, PostgreSQL performance, and high-availability clusters. Various PostgreSQL projects are explained through current technologies such as DevOps and cloud platforms using programming languages like Python and Node.js. Later, you'll get to grips with the well-known database API tool, PostgREST, before learning how to use popular PostgreSQL database testing frameworks. The book is also packed with essential tips and tricks and common patterns for working seamlessly in a production environment. All the chapters will be explained with the help of a real-world case study on a small banking application for managing ATM locations in a city.By the end of this DBMS book, you'll be proficient in building reliable database solutions as per your organization's needs.What You Will Learn: Set up high availability PostgreSQL database clusters in the same containment, a cross-containment, and on the cloudMonitor the performance of a PostgreSQL databaseCreate automated unit tests and implement test-driven development for a PostgreSQL databaseDevelop PostgreSQL apps on cloud platforms using DevOps with Python and Node.jsWrite robust APIs for PostgreSQL databases using Python programming, Node.js, and PostgRESTCreate a geospatial database using PostGIS and PostgreSQLImplement automatic configuration by Ansible and Terraform for PostgresWho this book is for: This PostgreSQL book is for database developers, database administrators, data architects, or anyone who wants to build end-to-end database projects using Postgres. This book will also appeal to software engineers, IT technicians, computer science researchers, and university students who are interested in database development and administration. Some familiarity with PostgreSQL and Linux is required to grasp the concepts covered in the book effectively.
New Trends in Database and Information Systems
This book constitutes thoroughly reviewed and selected short papers presented at the 25th East-European Conference on Advances in Databases and Information Systems, ADBIS 2021, as well as papers presented at doctoral consortium and ADBIS 2021 workshops. Due to the COVID-19 the conference and satellite events were held in hybrid mode. The 11 full papers and 18 short papers were carefully reviewed and selected from 97 total submissions. This volume presents the papers that have been accepted for the following satellite events: Workshop on Intelligent Data - From Data to Knowledge, DOING 2021; International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2021; Workshop on Modern Approaches in Data Engineering and Information System Design, MADEISD 2021; Workshop on Advances in Data Systems Management, Engineering, and Analytics, MegaData 2021; Workshop on Computational Aspects of Network Science, CAoNS 2021; Doctoral Consortium.
Database Systems for Advanced Applications
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.
Data Science at the Command Line
This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools--useful whether you work with Windows, macOS, or Linux. You'll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you're comfortable processing data with Python or R, you'll learn how to greatly improve your data science workflow by leveraging the command line's power. This book is ideal for data scientists, analysts, engineers, system administrators, and researchers. Obtain data from websites, APIs, databases, and spreadsheets Perform scrub operations on text, CSV, HTML, XML, and JSON files Explore data, compute descriptive statistics, and create visualizations Manage your data science workflow Create your own tools from one-liners and existing Python or R code Parallelize and distribute data-intensive pipelines Model data with dimensionality reduction, regression, and classification algorithms Leverage the command line from Python, Jupyter, R, RStudio, and Apache Spark
Data Modeling with SAP Bw/4hana 2.0
Gain practical guidance for implementing data models on the SAP BW/4HANA platform using modern modeling concepts. You will walk through the various modeling scenarios such as exposing HANA tables and views through BW/4HANA, creating virtual and hybrid data models, and integrating SAP and non-SAP data into a single data model. Data Modeling with SAP BW/4HANA 2.0 gives you the skills you need to use the new SAP BW/HANA features and objects, covers modern modelling concepts, and equips you with the practical knowledge of how to use the best of the HANA and BW/4HANA worlds. What You Will Learn Discover the new modeling features in SAP BW/4HANA Combine SAP HANA and SAP BW/4HANA artifacts Leverage virtualization when designing and building data models Build hybrid data models combining InfoObject, OpenODS, and a field-based approach Integrate SAP and non-SAP data into single modelWho This Book Is For BI consultants, architects, developers, and analysts working in the SAP BW/4HANA environment.
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 organisations to embrace a data-driven culture. The DataOps Revolution: Delivering the Data-Driven Enterprise is a narrative about real world issues involved in using DataOps to make data-driven decisions in modern organisations. The book is built around real delivery examples based on the author's own experience and lays out principles and a methodology for business success using DataOps. Presenting practical design patterns and DataOps approaches, the book shows how DataOps projects are run and presents the benefits of using DataOps to implement data solutions. Best practices are introduced in this book through the telling of a story, which relates how a lead manager must find a way through complexity to turn an organisation around. This narrative vividly illustrates DataOps in action, enabling readers to incorporate best practices into everyday projects. The book tells the story of an embattled CIO who turns to a new and untested project manager charged with a wide remit to roll out DataOps techniques to an entire organisation. It illustrates a different approach to addressing the challenges in bridging the gap between IT and the business. The approach presented in this story lines up to the six IMPACT pillars of the DataOps model that Kinaesis (www.kinaesis.com) has been using through its consultants to deliver successful projects and turn around failing deliveries. The pillars help to organise thinking and structure an approach to project delivery. The pillars are broken down and translated into steps that can be applied to real-world projects that can deliver satisfaction and fulfillment to customers and project team members.
Big Data, IoT, and Machine Learning
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases
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.
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.
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.
Closing the Analytics Talent Gap
How can we recruit out of your program? We have a project - how do we reach out to your students? If we do research together who owns it? We have employees who need to "upskill" in analytics - can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a "real" analytical project in the classroom? How can I get "real" data to help my students develop the skills necessary to be a "data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data - structured and unstructured, static and in-motion, voice, text, and image - into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding "data natives" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. .　　
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.
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.
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.
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.
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.
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.
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.
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.
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
For increasingly data-savvy clients, lawyers can no longer give "it depends" answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions. Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as: Mining legal data Computational law Uncovering bias through the use of Big Data Quantifying the quality of legal services Data mining and decision-making Contract analytics and contract standards In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable.Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information about the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.
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.
Teaching Data Analytics
The need for analytics skills is a source of the burgeoning growth in the number of analytics and decision science programs in higher education developed to feed the need for capable employees in this area. The very size and continuing growth of this need means that there is still space for new program development. Schools wishing to pursue business analytics programs intentionally assess the maturity level of their programs and take steps to close the gap. Teaching Data Analytics: Pedagogy and Program Design is a reference for faculty and administrators seeking direction about adding or enhancing analytics offerings at their institutions. It provides guidance by examining best practices from the perspectives of faculty and practitioners. By emphasizing the connection of data analytics to organizational success, it reviews the position of analytics and decision science programs in higher education, and to review the critical connection between this area of study and career opportunities. The book features: A variety of perspectives ranging from the scholarly theoretical to the practitioner appliedAn in-depth look into a wide breadth of skills from closely technology-focused to robustly soft human connection skillsResources for existing faculty to acquire and maintain additional analytics-relevant skills that can enrich their current course offerings. Acknowledging the dichotomy between data analytics and data science, this book emphasizes data analytics rather than data science, although the book does touch upon the data science realm. Starting with industry perspectives, the book covers the applied world of data analytics, covering necessary skills and applications, as well as developing compelling visualizations. It then dives into pedagogical and program design approaches in data analytics education and concludes with ideas for program design tactics. This reference is a launching point for discussions about how to connect industry's need for skilled data analysts to higher education's need to design a rigorous curriculum that promotes student critical thinking, communication, and ethical skills. It also provides insight into adding new elements to existing data analytics courses and for taking the next step in adding data analytics offerings, whether it be incorporating additional analytics assignments into existing courses, offering one course designed for undergraduates, or an integrated program designed for graduate students.
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 (MAS) are one of the most exciting and the fastest growing domains in the intelligent resource management and agent-oriented technology, which deals with modeling of autonomous decisions making entities. Recent developments have produced very encouraging results in the novel approach of handling multiplayer interactive systems. In particular, the multiagent system approach is adapted to model, control, manage or test the operations and management of several system applications including multi-vehicles, microgrids, multi-robots, where agents represent individual entities in the network. Each participant is modeled as an autonomous participant with independent strategies and responses to outcomes. They are able to operate autonomously and interact pro-actively with their environment. In recent works, the problem of information consensus is addressed, where a team of vehicles communicate with each other to agree on key pieces of information that enable them to work together in a coordinated fashion. The problem is challenging because communication channels have limited range and there are possibilities of fading and dropout. The book comprises chapters on synchronization and consensus in multiagent systems. It shows that the joint presentation of synchronization and consensus enables readers to learn about similarities and differences of both concepts. It reviews the cooperative control of multi-agent dynamical systems interconnected by a communication network topology. Using the terminology of cooperative control, each system is endowed with its own state variable and dynamics. A fundamental problem in multi-agent dynamical systems on networks is the design of distributed protocols that guarantee consensus or synchronization in the sense that the states of all the systems reach the same value.It is evident from the results that research in multiagent systems offer opportunities for further developments in theoretical, simulation and implementations. This book attempts to fill this gap and aims at presenting a comprehensive volume that documents theoretical aspects and practical applications.
Text Mining with Machine Learning
This book provides a perspective on the application of machine learning-based methods in knowledge discovery from natural languages texts. By analysing various data sets, conclusions which are not normally evident, emerge and can be used for various purposes and applications. 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. The book is not only aimed at IT specialists, but is meant for a wider audience that needs to process big sets of text documents and has basic knowledge of the subject, e.g. e-mail service providers, online shoppers, librarians, etc.The book starts with an introduction to text-based natural language data processing and its goals and problems. It focuses on machine learning, presenting various algorithms with their use and possibilities, and reviews the positives and negatives. Beginning with the initial data pre-processing, a reader can follow the steps provided in the R-language including the subsuming of various available plug-ins into the resulting software tool. A big advantage is that R also contains many libraries implementing machine learning algorithms, so a reader can concentrate on the principal target without the need to implement the details of the algorithms her- or himself. To make sense of the results, the book also provides explanations of the algorithms, which supports the final evaluation and interpretation of the results. The examples are demonstrated using realworld data from commonly accessible Internet sources.
Valuing Data
The past decade has seen a dramatic increase in the amount and variety of information that is generated and stored electronically by business enterprises. Storing this increased volume of information has not been a problem to date, but as these information stores grow larger and larger, multiple challenges arise for senior management: namely, questions such as "How much is our data worth?" "Are we storing our data in the most cost-effective way?" "Are we managing our data effectively and efficiently?" "Do we know which data is most important?" "Are we extracting business insight from the right data?" "Are our data adding to the value of our business?" "Are our data a liability?" "What is the potential for monetizing our data?" and "Do we have an appropriate risk management plan in place to protect our data?"To answer these value-based questions, data must be treated with the same rigor and discipline as other tangible and intangible assets. In other words, corporate data should be treated as a potential asset and should have its own asset valuation methodology that is accepted by the business community, the accounting and valuation community, and other important stakeholder groups. Valuing Data: An Open Framework is a first step in that direction. Its purpose is to: Provide the reader with some background on the nature of dataPresent the common categories of business dataExplain the importance of data managementReport the current thinking on data valuationOffer some business reasons to value dataPresent an "open framework"-along with some proposed methods-for valuing dataThe book does not aim to prescribe exactly how data should be valued monetarily, but rather it is a "starting point" for a discussion of data valuation with the objective of developing a stakeholder consensus, which, in turn, will become accepted standards and practices.
