Databaser

This book deals with the first discriminant theory of linearly separable data (LSD), Theory3, based on the four ordinary LSD of Theory1 and 169 microarrays (LSD) of Theory2. Furthermore, you can quickly analyze the medical data with the misclassified patients which is the true purpose of diagnoses. Author developed RIP (Optimal-linear discriminant function finding the combinatorial optimal solution) as Theory1 in decades ago, that found the minimum misclassifications. RIP discriminated 63 (=26¿1) models of Swiss banknote (200*6) and found the minimum LSD: basic gene set (BGS). In Theory2, RIP discriminated Shipp microarray (77*7129) which was LSD and had only 32 nonzero coefficients (first Small Matryoshka; SM1). Because RIP discriminated another 7,097 genes and found SM2, the author developed the Matryoshka feature selection Method 2 (Program 3), that splits microarray into many SMs. Program4 can split microarray into many BGSs. Then, the wide columnLSD (Revolution-0), such as microarray (n5) models, including BGS, become LSD among (219¿1) models. Because Program2 confirms BGS has the minimum average error rate, BGS is the most compact and best model satisfying Occam¿s Razor. With this book, physicians obtain complete diagnostic results for disease, and engineers can become a true data scientist, by obtaining integral knowledge ofstatistics and mathematical programming with simple programs.

Dieses Lehrbuch betrachtet Data Management als interdisziplinäres Konzept mit Fokus auf den Zielen datengetriebener Unternehmen. Im Zentrum steht die interaktive Entwicklung eines Unternehmensdatenmodells für ein virtuelles Unternehmen mit Unterstützung eines online Learning Games unter Einbeziehung der Aufgaben, Ziele und Grundsätze des Data Managements, typischer Data-Management-Komponenten und Frameworks wie Datenmodellierung und Design, Metadaten Management, Data Architecture, und Data Governance, und verknüpft diese mit datengetriebenen Anwendungen wie Business Warehousing, Big Data, In-Memory Data Management, und Machine Learning im Data Management Kontext.Das Buch dient als Lehrbuch für Studierende der Informatik, der Wirtschaft und der Wirtschaftsinformatik an Universitäten, Hochschulen und Fachschulen und zur industriellen Aus- und Weiterbildung.

Dieses Buch zeigt die Bedeutung des Kulturwandels bei der Digitalisierung von Arbeitsprozessen, der Gestaltung neuer Arbeitsumgebungen und der Realisierung innovativer Geschäftsmodelle. Dieser Faktor wird zumeist in der Literatur zwar immer wieder betont und als wichtig erachtet, es fehlen jedoch konkrete Vorgehensschritte und die Integration in ein integriertes Kulturkonzept der Unternehmen. Gerade die bewusste Gestaltung der hybrider Unternehmenskultur ermöglicht es, die Potentiale der Leistungssteigerung gemeinsam mit der Zufriedenheit und Produktivität der Mitarbeiter zu vereinbaren. In dieser überarbeiteten und erweiterten 2. Auflage werden konkrete Konzepte vorgestellt, wie die digitale Transformation methodisch mit der veränderten Unternehmenskultur umgesetzt werden kann. Dieses praxeologisch orientierte Buch bietet Unternehmen und Beratern bewährte Modelle, Konzepte und Vorgehensweisen, damit die digitale Transformation nachhaltig gelingen kann.

Dieses Trainingsmanual bietet alles, was Sie für das Führungskräftetraining zur Förderung gesundheitsorientierter Führungskompetenz benötigen. Als Grundlage und Ausgangspunkt dient das Health-oriented Leadership Konzept (HoL) mit dem Fokus auf gesundheitsorientierter Selbst- und Mitarbeiterführung (SelfCare und StaffCare). Das Training selbst ist modular aufgebaut und besteht aus den folgenden 5 Bausteinen:Baustein 1 ¿Warm up¿Baustein 2 ¿Grundlagen¿Baustein 3 ¿SelfCare¿Baustein 4 ¿StaffCare¿ Baustein 5 ¿Cool down¿Somit ist das Manual mit dem klaren Anwendungsbezug bestens geeignet, das Training in der Praxis direkt umzusetzen. Im Manual werden auch die Voraussetzungen und Bedingungen für die erfolgreiche Trainingsdurchführung thematisiert. Der theoretische Hintergrund des Trainings wird anschaulich dargestellt und die Konzeption des Trainings praxisnah erläutert. Zusätzlich gibt es für jedes Modul konkrete und detaillierte Traineranweisungen und das Material für die Durchführung des Trainings.

In diesem Buch wird der Übergang aus einer Tätigkeit als gewerblich-technische Fachkraft in die hauptamtliche Ausbildungsfunktion in einer betrieblichen Ausbildungswerkstatt untersucht. In einem fallrekonstruktiven Forschungsansatz wird das Erleben und Bewältigen von typischen Herausforderungen während und infolge dieses Übergangs nachgezeichnet. Hierzu wurden hauptamtliche Ausbilder*innen in den industriellen Metall- und Elektroberufen zu ihren Übergangserfahrungen befragt. Ergebnis ist eine empirisch fundierte Beschreibung von fünf typischen Entwicklungsaufgaben, mit denen Ausbilder*innen während und infolge des Übergangs konfrontiert werden und die sie in Abhängigkeit von subjektiven Ressourcen und Orientierungen unterschiedlich deuten und bearbeiten. Die Fallrekonstruktion führt zu vier Typen von Bewältigungsstrategien, die sich hinsichtlich ihres Umgangs mit Erfahrungswissen, ihrer pädagogischen Überzeugungen sowie ihres Reflexionswissens unterscheiden. Darauf aufbauend wird mit Hilfe des Sozialweltkonzeptes die Frage nach der Rolle und Funktion einer übergeordneten kollegialen Bezugsgemeinschaft als potentielle Wissens- und Kompetenzgrundlage der Akteure der beruflich-betrieblichen Bildung vor dem Hintergrund der strukturellen Rahmenbedingungen und Systemspezifika diskutiert.

Strategische Kommunikation zielt mit ihren kontingenten Wirklichkeitsbeschreibungen seit jeher auf gesellschaftliche Wahrheitsmodelle. Wie häufig gesellschaftliche Wahrheitsmodelle auf strategische Kommunikationsbemühungen zurückgehen, auf Unwahrhaftigkeit beruhen und damit zumindest zeitweise zu strategischen Wahrheiten werden, zeigen eindrucksvoll zwischenzeitlich geglaubte Wahrheiten, die sich als Lüge entpuppt haben: von Walter Ulbrichts ¿Niemand hat die Absicht, eine Mauer zu errichten¿ über Hitlers Tagebücher bis hin zu den Massenvernichtungswaffen im Irak. Die erfolgreichen Kampagnen der Brexiteers und von Donald Trump 2016 haben diesem Thema zu neuer und bislang ungeahnter Aufmerksamkeit verholfen. Während die Themen Desinformation und postfaktische Gesellschaft die Journalismus-, politische Kommunikations- und Medienethikforschung aktuell zu dominieren scheinen, ist das Schweigen der deutschsprachigen und internationalen PR- und Organisationskommunikationsforschung auffällig. Dies ist umso bemerkenswerter, weil die PR-Wissenschaft in der Vergangenheit immer wieder versucht hat, ihren Gegenstand zu schärfen, indem sie sich am Begriff der Propaganda abgearbeitet hat. Daraus müsste eigentlich eine Affinität für das Thema Desinformation resultieren. Aber genau das Gegenteil ist offensichtlich der Fall: Hat sich die PR-Wissenschaft gerade deshalb nicht mit Desinformation beschäftigt, weil sie sich so dezidiert von Propaganda und darin eingeschlossenen desinformierenden und manipulativen Techniken abgrenzen will? Was sind die Gründe hierfür? Glauben wir, bereits alles zum Thema gesagt zu haben? Liegt dies daran, dass sich die PR- und Organisationskommunikationsforschung seit jeher vor allem für Unternehmen und weniger für politische und Non-Profit-Organisationen interessiert? Oder fühlen wir uns hier schlicht und ergreifend nicht zuständig? Es scheint offenkundig höchste Zeit zu sein, sich wieder eingehend mit Fragen der Desinformation aus der Perspektive der strategischen Kommunikationsforschung zu befassen. Die Beiträge des Tagungsbandes fokussieren hierzu auf neue theoretische Perspektiven, normative Bewertungen und empirische Befunde.

A pattern language to cover from a small debugging trace to a distributed log with billions of messages from hundreds of computers, thousands of components, threads, and processes.

In today's data-driven world, understanding statistical models is crucial for effective analysis and decision making. Whether you're a beginner or an experienced user, this book equips you with the foundational knowledge to grasp and implement statistical models within Tableau. Gain the confidence to speak fluently about the models you employ, driving adoption of your insights and analysis across your organization. As AI continues to revolutionize industries, possessing the skills to leverage statistical models is no longer optional--it's a necessity. Stay ahead of the curve and harness the full potential of your data by mastering the ability to interpret and utilize the insights generated by these models. Whether you're a data enthusiast, analyst, or business professional, this book empowers you to navigate the ever-evolving landscape of data analytics with confidence and proficiency. Start your journey toward data mastery today. In this book, you will learn: The basics of foundational statistical modeling with Tableau How to prove your analysis is statistically significant How to calculate and interpret confidence intervals Best practices for incorporating statistics into data visualizations How to connect external analytics resources from Tableau using R and Python

Unlock the Power of Cloud Infrastructure with "IaaS Mastery" Book Bundle!Are you ready to conquer the dynamic world of cloud infrastructure? Look no further than the "IaaS Mastery: Infrastructure as a Service" book bundle, your comprehensive guide to mastering cloud technology with a focus on the industry's leading providers.Discover What's Inside:Book 1 - IaaS Fundamentals: A Beginner's Guide to Cloud Infrastructure Begin your journey with a solid foundation. Learn the essentials of cloud computing and understand the core principles of Infrastructure as a Service. Perfect for newcomers and those seeking a refresher on cloud basics.Book 2 - Mastering IaaS: Building Scalable Cloud Solutions with AWS and GCE Dive into practical applications with Amazon Web Services (AWS) and Google Cloud Engine (GCE). Gain hands-on experience in creating scalable and resilient cloud solutions using these renowned platforms.Book 3 - Advanced IaaS Architectures: Optimizing Microsoft Azure for Enterprises Elevate your expertise with a deep dive into Microsoft Azure. Explore advanced topics such as high-performance networks, scalable compute solutions, security measures, and automation tailored for enterprise workloads.Book 4 - IaaS Expertise: Harnessing the Power of IBM Cloud for Enterprise Solutions Unleash the potential of IBM Cloud as a tool for enterprise transformation. Discover infrastructure offerings, networking strategies, security features, and advanced automation capabilities. Real-world enterprise success stories provide valuable insights.Why Choose "IaaS Mastery"?· Comprehensive Coverage: From beginner to expert, this bundle covers everything you need to know about IaaS.· Hands-On Experience: Practical examples and real-world scenarios ensure you're ready to apply your knowledge.· Top Cloud Providers: Learn from the best-AWS, GCE, Microsoft Azure, and IBM Cloud.· Enterprise Focus: Equip yourself with skills tailored for the demands of large organizations.· Future-Proof Your Career: Cloud technology is the future; stay ahead of the curve with this invaluable resource.Don't miss this opportunity to become an IaaS expert. Whether you're an IT professional, aspiring cloud enthusiast, or business leader, "IaaS Mastery" empowers you with the knowledge and skills to succeed in the digital age. Purchase the bundle today and embark on your journey to mastering cloud infrastructure!

This book aims to gather high-quality research papers on developing theories, frameworks, architectures, and algorithms for solving complex challenges in smart healthcare applications for real industry use. It explores the recent theoretical and practical applications of metaheuristics and optimization in various smart healthcare contexts. The book also discusses the capability of optimization techniques to obtain optimal parameters in ML and DL technologies. It provides an open platform for academics and engineers to share their unique ideas and investigate the potential convergence of existing systems and advanced metaheuristic algorithms. The book's outcome will enable decision-makers and practitioners to select suitable optimization approaches for scheduling patients in crowded environments with minimized human errors.The healthcare system aims to improve the lives of disabled, elderly, sick individuals, and children. IoT-based systems simplify decision-making and task automation, offering an automated foundation. Nature-inspired metaheuristics and mining algorithms are crucial for healthcare applications, reducing costs, increasing efficiency, enabling accurate data analysis, and enhancing patient care. Metaheuristics improve algorithm performance and address challenges in data mining and ML, making them essential in healthcare research. Real-time IoT-based healthcare systems can be modeled using an IoT-based metaheuristic approach to generate optimal solutions.Metaheuristics are powerful technologies for optimization problems in healthcare systems. They balance exact methods, which guarantee optimal solutions but require significant computational resources, with fast but low-quality greedy methods. Metaheuristic algorithms find better solutions while minimizing computational time. The scientific community is increasingly interested in metaheuristics, incorporating techniques from AI, operations research, and soft computing. New metaheuristicsoffer efficient ways to address optimization problems and tackle unsolved challenges. They can be parameterized to control performance and adjust the trade-off between solution quality and resource utilization. Metaheuristics manage the trade-off between performance and solution quality, making them highly applicable to real-time applications with pragmatic objectives.

The book delivers an excellent professional development resource for educators and practitioners on the cutting-edge computational intelligence techniques and applications. It covers many areas and topics of computational intelligence techniques and applications proposed by computational intelligence experts and researchers and furthers the enhancement of the community outreach and engagement component of computational intelligence techniques and applications. Furthermore, it presents a rich collection of manuscripts in highly regarded computational intelligence techniques and applications topics that have been creatively compiled. Computers are capable of learning from data and observations and providing solutions to real-life complex problems, following the same reasoning approach of human experts in various fields. This book endows a rich collection of applications in widespread areas. Among the areas addressed in this book are Computational Intelligence Principles andTechniques; CI in Manufacturing, Engineering, and Industry; CI in Recognition and Processing; CI in Robotics and Automation; CI in Communications and Networking; CI in Traditional Vehicles, Electric Vehicles, and Autonomous Vehicles; CI in Smart Cities and Smart Energy Systems; and CI in Finance, Business, Economics, and Education. These areas span many topics including repetitive manufacturing, discrete manufacturing, process manufacturing, electronic systems, speech recognition, pattern recognition, signal processing, image processing, industrial monitoring, vision systems for automation and robotics, cooperative and network robotics, perception, planning, control, urban traffic networks control, vehicle-to-roadside communications, smart buildings, smart urbanism, smart infrastructure, smart connected communities, smart energy, security, arts, and music.

This book provides an industry-oriented data analytics approach for process engineers, including data acquisition methods and sources, exploratory data analysis and sensitivity analysis, data-based modelling for prediction, data-based modelling for monitoring and control, and data-based optimization of processes. While many of the current data analytics books target business-related problems, the rationale for this book is a specific need to understand and select applicable data analytics approaches pragmatically to analyze process engineering¿related problems; this tailored solution for engineers gets amalgamated with governing equations, and in several cases, with the physical understanding of the phenomenon being analyzed. We also consider this book strategically conceived to help map Education 4.0 with Industry 4.0 since it can support undergraduate and graduate students to gain valuable and applicable data analytics stills that can be further used in their workplace. Moreover, itcan be used as a reference book for professionals, a quick reference to data analytics tools that can facilitate and/or optimize their process engineering tasks.

This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems.The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented.This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.

This book explores the employment of market mechanisms for data-interactive innovations. Based on the concept of innovators' marketplaces the book introduces a new concept of 'data jackets' to enable analysis of what kind of data exist, where they are located, and what kind of information they hold, even if the contents of data cannot be made publicly available.The book presents the concept of a marketplace for data in the case of data-interactive innovations. It introduces the marketplace as a platform for value-based exchange of data and - based on the idea of the innovators' marketplace - explains how data jackets can be utilized independently from the actual contents of the data. Specific chapters deepen the understanding of variables, constraints and intentions as constituent parts of data jackets, and the extension to variable quest, a process towards the design of data. A number of case studies showcases how the methods and processes presented can be employed in real-life contexts. Finally the authors present some extensions of the concept for web-based IMDJ and connections to business information system and an outlook.

Get up and running with building data pipelines and creating interactive dashboards to visualize, monitor, and present a wide variety of time-series data with this comprehensive introductory guideKey FeaturesInstall, set up, and configure Grafana for real-time data analysis, visualization, and alertingVisualize and monitor data using data sources such as InfluxDB, Telegraf, Prometheus, and ElasticsearchExplore Grafana's cloud support with Microsoft Azure, Amazon CloudWatch, and Google Cloud MonitoringPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionGet ready to unlock the full potential of the open-source Grafana observability platform, ideal for analyzing and monitoring time-series data with this updated second edition. This beginners guide will help you get up to speed with Grafana's latest features for querying, visualizing, and exploring logs and metrics, no matter where they are stored.Starting with the basics, this book demonstrates how to quickly install and set up a Grafana server using Docker. You'll then be introduced to the main components of the Grafana interface before learning how to analyze and visualize data from sources such as InfluxDB, Telegraf, Prometheus, Logstash, and Elasticsearch. The book extensively covers key panel visualizations in Grafana, including Time Series, Stat, Table, Bar Gauge, and Text, and guides you in using Python to pipeline data, transformations to facilitate analytics, and templating to build dynamic dashboards. Exploring real-time data streaming with Telegraf, Promtail, and Loki, you'll work with observability features like alerting rules and integration with PagerDuty and Slack. As you progress, the book addresses the administrative aspects of Grafana, from configuring users and organizations to implementing user authentication with Okta and LDAP, as well as organizing dashboards into folders, and more. By the end of this book, you'll have gained all the knowledge you need to start building interactive dashboards.What you will learnLearn the techniques of data visualization using GrafanaGet familiar with the major components of Time series visualizationExplore data transformation operations, query inspector, and time interval settingsWork with advanced dashboard features, such as annotations, variable-based templating, and dashboard linking and sharingConnect user authentication through Okta, Google, GitHub, and other external providersDiscover Grafana's monitoring support for cloud service infrastructuresWho this book is forThis book is for business intelligence developers, business analysts, data analysts, and anyone interested in performing time-series data analysis and monitoring using Grafana. You'll also find this book useful if you're looking to create and share interactive dashboards or get up to speed with the latest features of Grafana. Although no prior knowledge of Grafana is required, basic knowledge of data visualization and some Python programming experience will help you understand the concepts covered in the book.Table of ContentsIntroducing Data Visualization with GrafanaTouring the Grafana InterfaceDiving into Grafana's Time Series VisualizationConnecting Grafana to a Prometheus Data SourceExtracting and Visualizing Data with InfluxDB and GrafanaShaping Data with Grafana TransformationsSurveying Key Grafana VisualizationsSurveying Additional Grafana VisualizationsCreating Insightful DashboardsWorking with Advanced Dashboard Features and Elasticsearch(N.B. Please use the Look Inside option to see further chapters)

Written by a team of well-known PostgreSQL experts, this new edition will cover all the latest updates of PostgreSQL 16 including 12+ new and improved recipes on logging, monitoring, security and high-performancePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesSkill-up as a database administrator by achieving improved query performance, backup, and recovery management, setting up replication and so onGet to grips with the essentials of database management with a recipe-based approach using the latest features of PostgreSQL 16New and updated recipes on crucial PostgreSQL topics like Monitoring, Logging, Scalability and so onBook DescriptionPostgreSQL has seen a huge increase in its customer base in the past few years and is becoming one of the go-to solutions for anyone who has a database-specific challenge. This PostgreSQL book touches on all the fundamentals of Database Administration in a problem-solution format. It is intended to be the perfect desk reference guide.This new edition focuses on recipes based on the new PostgreSQL 16 release. The additions include handling complex batch loading scenarios with the SQL MERGE statement, security improvements, running Postgres on Kubernetes or with TPA and Ansible, and more. This edition also focuses on certain performance gains, such as query optimization, and the acceleration of specific operations, such as sort. It will help you understand roles, ensuring high availability, concurrency, and replication. It also draws your attention to aspects like validating backups, recovery, monitoring, and scaling aspects. This book will act as a one-stop solution to all your real-world database administration challenges.By the end of this book, you will be able to manage, monitor, and replicate your PostgreSQL 16 database for efficient administration and maintenance with the best practices from experts.What you will learnDiscover how to improve batch data loading with the SQL MERGE statementUse logical replication to apply large transactions in parallelImprove your back up and recovery performance with server-side compressionTackle basic to high-end and real-world PostgreSQL challenges with practical recipesMonitor and fine-tune your database with easeLearn to navigate the newly introduced features of PostgreSQL 16Efficiently secure your PostgreSQL database with new and updated featuresWho this book is forThis Postgres book is for database administrators, data architects, database developers, and anyone with an interest in planning and running live production databases using PostgreSQL 14. Those looking for hands-on solutions to any problem associated with PostgreSQL 14 administration will also find this book useful. Some experience with handling PostgreSQL databases will help you to make the most out of this book, however, it is a useful resource even if you are just beginning your Postgres journeyTable of ContentsFirst StepsExploring the DatabaseServer ConfigurationServer ControlTables and DataSecurityDatabase AdministrationMonitoring and DiagnosisRegular MaintenancePerformance and ConcurrencyBackup and RecoveryReplication and Upgrades

Kryptowerte wie der Bitcoin stellen ein neuartiges Phänomen dar, welches vor allem in rechtlicher Hinsicht zahlreiche Fragen aufwirft. Die vorliegende Arbeit erforscht nach Erläuterung der technischen Grundlagen der Blockchaintechnologie die währungs- und aufsichtsrechtliche Einordnung von Kryptowerten am Beispiel des Bitcoin. Im Mittelpunkt der Arbeit steht dabei die Untersuchung der Frage, ob sich der börsliche Handel mit Kryptowerten unter bestehende rechtliche Strukturen fassen lässt. Zudem wird die Erfüllung von solchen Börsengeschäften mit Kryptowerten untersucht.

This book constitutes invited papers from the Second International Workshop on Frontiers in Software Engineering Education, FISEE 2023, which took place at the Château de Villebrumier, France, during January 23-25, 2023.The Editorial and the 8 papers included in this volume were considerably enhanced after the conference and during two different peer-review phases. The contributions cover the main topics of the workshop: education in technology and technology for education; new (and fearless) ideas on education; adjustments in teaching during pandemic: experience reports; models for class development; how to design learning objectives and outcomes; labs and practical sessions: how to conduct them; curriculum development; course design; quality course assessment; long-life studies in education; empirical research in SE education; experiences in starting-up new educational systems; blended education.FISEE 2023 is part of a series of scientific events held at the new LASER center in Villebrumier near Montauban and Toulouse, France.

This book explores provenance, the study and documentation of how things come to be.  Traditionally defined as the origins, source, or ownership of an artifact, provenance today is not limited to historical domains.  It can be used to describe what did happen (retrospective provenance), what could happen (subjunctive provenance), or what will happen (prospective provenance). Provenance information is ubiquitous and abundant; for example, a wine label that details the winery, type of grape, and country of origin tells a provenance story that determines the value of the bottle.  This book presents select standards used in organizing provenance information and provides concrete examples on how to implement them.  Provenance transcends disciplines, and this book is intended for anyone who is interested in documenting workflows and recipes.  The goal is to empower readers to frame and answer provenance questions for their own work.  Provenance is increasingly important in computational workflows and e-sciences and addresses the need for a practical introduction to provenance documentation with simple-to-use multi-disciplinary examples and activities.  Case studies and examples address the creation of basic records using a variety of provenance metadata models, and the differences between PROV, ProvONE, and PREMIS are discussed.  Readers will gain an understanding of the uses of provenance metadata in different domains and sectors in order to make informed decisions on their use.  Documenting provenance can be a daunting challenge, and with clear examples and explanations, the task will be less intimidating to explore provenance needs.

This book discusses the role of mobile network data in urban informatics, particularly how mobile network data is utilized in the mobility context, where approaches, models, and systems are developed for understanding travel behavior. The objectives of this book are thus to evaluate the extent to which mobile network data reflects travel behavior and to develop guidelines on how to best use such data to understand and model travel behavior. To achieve these objectives, the book attempts to evaluate the strengths and weaknesses of this data source for urban informatics and its applicability to the development and implementation of travel behavior models through a series of the authors' research studies.Traditionally, survey-based information is used as an input for travel demand models that predict future travel behavior and transportation needs. A survey-based approach is however costly and time-consuming, and hence its information can be dated and limited to a particular region. Mobile network data thus emerges as a promising alternative data source that is massive in both cross-sectional and longitudinal perspectives, and one that provides both broader geographic coverage of travelers and longer-term travel behavior observation. The two most common types of travel demand model that have played an essential role in managing and planning for transportation systems are four-step models and activity-based models. The book's chapters are structured on the basis of these travel demand models in order to provide researchers and practitioners with an understanding of urban informatics and the important role that mobile network data plays in advancing the state of the art from the perspectives of travel behavior research.

Information Modeling and Relational Databases provides an introduction to ORM (Object Role Modeling)-and much more. In fact, it's the only book to go beyond introductory coverage and provide all of the in-depth instruction you need to transform knowledge from domain experts into a sound database design. Inside, ORM authority Terry Halpin blends conceptual information with practical instruction that will let you begin using ORM effectively as soon as possible. Supported by examples, exercises, and useful background information, his step-by-step approach teaches you to develop a natural-language-based ORM model and then, where needed, abstract ER and UML models from it. This book will quickly make you proficient in the modeling technique that is proving vital to the development of accurate and efficient databases that best meet real business objectives.The most in-depth coverage of Object Role Modeling available anywhere-written by a pioneer in the development of ORM.Provides additional coverage of Entity Relationship (ER) modeling and the Unified Modeling Language-all from an ORM perspective.Intended for anyone with a stake in the accuracy and efficacy of databases: systems analysts, information modelers, database designers and administrators, instructors, managers, and programmers.Explains and illustrates required concepts from mathematics and set theory.

This book constitutes the proceedings of the First International Conference, AI4S 2023, held in Pune, India, during September 4-5, 2023.The 14 full papers and the 2 short papers included in this volume were carefully reviewed and selected from 72 submissions. This volume aims to open discussion on trustworthy AI and related topics, trying to bring the most up to date developments around the world from researchers and practitioners.

This book focuses on online transaction processing indexes designed for scalable, byte-addressable non-volatile memory (NVM) and provides a systematic review and summary of the fundamental principles and techniques as well as an outlook on the future of this research area.In this book, the authors divide the development of NVM indexes into three ¿eras¿¿ pre-Optane, Optane and post-Optane¿based on when the first major scalable NVM device (Optane) became commercially available and when it was announced to be discontinued. The book will analyze the reasons for the slow adoption of NVM and give an outlook for indexing techniques in the post-Optane era.The book assumes only basic undergraduate-level understanding on indexing (e.g., B+-trees, hash tables) and database systems in general. It is otherwise self-contained with the necessary background information, including an introduction to NVM hardware and software/programming issues, a detailed description of different indexes in highly concurrent systems for non-experts and new researchers to get started in this area.

This book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.

This book is about data analytics, including problem definition, data preparation, and data analysis. A variety of techniques (e.g., regression, logistic regression, cluster analysis, neural nets, decision trees, and others) are covered with conceptual background as well as demonstrations of KNIME using each tool.The book uses KNIME, which is a comprehensive, open-source software tool for analytics that does not require coding but instead uses an intuitive drag-and-drop workflow to create a network of connected nodes on an interactive canvas. KNIME workflows provide graphic representations of each step taken in analyses, making the analyses self-documenting. The graphical documentation makes it easy to reproduce analyses, as well as to communicate methods and results to others. Integration with R is also available in KNIME, and several examples using R nodes in a KNIME workflow are demonstrated for special functions and tools not explicitly included in KNIME.

This book aims to highlight the latest achievements in the use of AI and multimodal artificial intelligence in biomedicine and healthcare. Multimodal AI is a relatively new concept in AI, in which different types of data (e.g. text, image, video, audio, and numerical data) are collected, integrated, and processed through a series of intelligence processing algorithms to improve performance. The edited volume contains selected papers presented at the 2022 Health Intelligence workshop and the associated Data Hackathon/Challenge, co-located with the Thirty-Sixth Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI and Multimodal AI in public health and medicine.

This volume presents a collection of twenty-five peer-reviewed articles carefully selected from the contributions presented at the XXV Congress of the Portuguese Statistical Society (2021). Containing state-of-the-art developments in theoretical and applied statistics, the book will be accessible to readers with a background in mathematics and statistics, but will also be of interest to researchers from other scientific disciplines (e.g., biology, economics, medicine), who will find a broad range of relevant applications.

Save time analyzing volumes of data using a structured method to extract, model, and create insights from your dataKey FeaturesAcquire expertise in using Excel's Data Model and Power Pivot to connect and analyze multiple sources of dataCreate key performance indicators for decision making using DAX and Cube functionsApply your knowledge of Data Model to build an interactive dashboard that delivers key insights to your usersPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMicrosoft Excel's BI solutions have evolved, offering users more flexibility and control over analyzing data directly in Excel. Features like PivotTables, Data Model, Power Query, and Power Pivot empower Excel users to efficiently get, transform, model, aggregate, and visualize data.Data Modeling with Microsoft Excel offers a practical way to demystify the use and application of these tools using real-world examples and simple illustrations.This book will introduce you to the world of data modeling in Excel, as well as definitions and best practices in data structuring for both normalized and denormalized data. The next set of chapters will take you through the useful features of Data Model and Power Pivot, helping you get to grips with the types of schemas (snowflake and star) and create relationships within multiple tables. You'll also understand how to create powerful and flexible measures using DAX and Cube functions.By the end of this book, you'll be able to apply the acquired knowledge in real-world scenarios and build an interactive dashboard that will help you make important decisions.What you will learnImplement the concept of data modeling within and beyond ExcelGet, transform, model, aggregate, and visualize data with Power QueryUnderstand best practices for data structuring in MS ExcelBuild powerful measures using DAX from the Data ModelGenerate flexible calculations using Cube functionsDesign engaging dashboards for your usersWho this book is forThis book is for Excel users looking for hands-on and effective methods to manage and analyze large volumes of data within Microsoft Excel using Power Pivot. Whether you're new or already familiar with Excel's data analytics tools, this book will give you further insights on how you can apply Power Pivot, Data Model, DAX measures, and Cube functions to save time on routine data management tasks. An understanding of Excel's features like tables, PivotTable, and some basic aggregating functions will be helpful but not necessary to make the most of this book.Table of ContentsGetting Started with Data Modeling - Overview and ImportanceData Structuring for Data ModelsPreparing your Data for the Data ModelData Modeling with Power Pivot Creating DAX Calculations from your Data ModelCreating Cube Functions from your Data ModelCommunicating insights from your Data Model using DashboardsVisualization Elements for your DashboardChoosing the right Design ThemesPublication and Deployment