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Relevant Query Answering over Streaming and Distributed Data: A Study for RDF Streams and Evolving Web Data (SpringerBriefs in Applied Sciences and Technology)
by Emanuele Della Valle Shima ZahmatkeshThis book examines the problem of relevant query answering over the Web and provides a comprehensive overview of relevant query answering over streaming and distributed data. In recent years, Web applications that combine highly dynamic data streams with data distributed over the Web to provide relevant answers have attracted increasing attention. Answering in a timely fashion, i.e., reactively, is one of the most important performance indicators, especially when the distributed data is evolving. The book proposes a solution that retains a local replica of the distributed data and offers various maintenance policies to refresh the replica over time. A limited refresh budget guarantees the reactiveness of the system. Focusing on stream processing and Semantic Web, it appeals to scientists and graduate students in the field.
Relevant Search: With applications for Solr and Elasticsearch
by John Berryman Doug TurnbullSummaryRelevant Search demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyUsers are accustomed to and expect instant, relevant search results. To achieve this, you must master the search engine. Yet for many developers, relevance ranking is mysterious or confusing. About the BookRelevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime. What's InsideTechniques for debugging relevance?Applying search engine features to real problems?Using the user interface to guide searchers?A systematic approach to relevance?A business culture focused on improving searchAbout the ReaderFor developers trying to build smarter search with Elasticsearch or Solr.About the AuthorsDoug Turnbull is lead relevance consultant at OpenSource Connections, where he frequently speaks and blogs. John Berryman is a data engineer at Eventbrite, where he specializes in recommendations and search.Foreword author, Trey Grainger, is a director of engineering at CareerBuilder and author of Solr in Action.Table of ContentsThe search relevance problem Search under the hood Debugging your first relevance problem Taming tokens Basic multifield search Term-centric search Shaping the relevance function Providing relevance feedback Designing a relevance-focused search applicationThe relevance-centered enterprise Semantic and personalized search
Reliability and Availability of Cloud Computing
by Eric Bauer Randee AdamsA holistic approach to service reliability and availability of cloud computing Reliability and Availability of Cloud Computing provides IS/IT system and solution architects, developers, and engineers with the knowledge needed to assess the impact of virtualization and cloud computing on service reliability and availability. It reveals how to select the most appropriate design for reliability diligence to assure that user expectations are met. Organized in three parts (basics, risk analysis, and recommendations), this resource is accessible to readers of diverse backgrounds and experience levels. Numerous examples and more than 100 figures throughout the book help readers visualize problems to better understand the topic—and the authors present risks and options in bulleted lists that can be applied directly to specific applications/problems. Special features of this book include: Rigorous analysis of the reliability and availability risks that are inherent in cloud computing Simple formulas that explain the quantitative aspects of reliability and availability Enlightening discussions of the ways in which virtualized applications and cloud deployments differ from traditional system implementations and deployments Specific recommendations for developing reliable virtualized applications and cloud-based solutions Reliability and Availability of Cloud Computing is the guide for IS/IT staff in business, government, academia, and non-governmental organizations who are moving their applications to the cloud. It is also an important reference for professionals in technical sales, product management, and quality management, as well as software and quality engineers looking to broaden their expertise.
Reliability and Risk Assessment in Engineering: Proceedings of INCRS 2018 (Lecture Notes in Mechanical Engineering)
by Vijay Kumar Gupta Prabhakar V. Varde P. K. Kankar Narendra JoshiThis volume is a collection of articles on reliability and safety engineering presented during INCRS 2018. The articles cover a variety of topics such as big data analytics and their applications in reliability assessment and condition monitoring, health monitoring, management, diagnostics and prognostics of mechanical systems, design for reliability and optimization, and machine learning for industrial applications. A special aspect of this volume is the coverage of performance, failure and reliability issues in electrical distribution systems. This book will be a useful reference for graduate students, researchers and professionals working in the area of reliability assessment, condition monitoring and predictive maintenance.
Reliability and Risk Modeling of Engineering Systems (EAI/Springer Innovations in Communication and Computing)
by Dilbagh Panchal Prasenjit Chatterjee Dragan Pamucar Mohit TyagiThis book addresses reliability, maintenance, risk, and safety issues of industrial systems with applications of the latest decision-making techniques. Thus, this book presents chapters that apply advanced tools, techniques, and computing models for optimizing the performance of industrial and manufacturing systems, along with other complex engineering equipment. Computing techniques like data analytics, failure mode and effects analysis, fuzzy set theory, petri-net, multi-criteria decision-making (MCDM), and soft computing are used for solving problems of reliability, risk, and safety related issues.
Reliability and Statistical Computing: Modeling, Methods and Applications (Springer Series in Reliability Engineering)
by Hoang PhamThis book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Reliability and Statistics in Transportation and Communication: Selected Papers from the 19th International Conference on Reliability and Statistics in Transportation and Communication, RelStat’19, 16-19 October 2019, Riga, Latvia (Lecture Notes in Networks and Systems #117)
by Igor Kabashkin Irina Yatskiv Olegas PrentkovskisThis book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice. The book presents the most noteworthy methods and results discussed at the International Conference on Reliability and Statistics in Transportation and Communication (RelStat), which took place in Riga, Latvia on October 16 – 19, 2019. It spans a broad spectrum of topics, from mathematical models and design methodologies, to software engineering, data security and financial issues, as well as practical problems in technical systems, such as transportation and telecommunications, and in engineering education.
Reliability and Statistics in Transportation and Communication: Selected Papers from the 20th International Conference on Reliability and Statistics in Transportation and Communication, RelStat2020, 14-17 October 2020, Riga, Latvia (Lecture Notes in Networks and Systems #195)
by Igor Kabashkin Irina Yatskiv Olegas PrentkovskisThis book reports on cutting-edge theories and methods for analyzing complex systems, such as transportation and communication networks and discusses multi-disciplinary approaches to dependability problems encountered when dealing with complex systems in practice. The book presents the most noteworthy methods and results discussed at the International Conference on Reliability and Statistics in Transportation and Communication (RelStat), which took place remotely from Riga, Latvia, on October 14 – 17, 2020. It spans a broad spectrum of topics, from mathematical models and design methodologies, to software engineering, data security and financial issues, as well as practical problems in technical systems, such as transportation and telecommunications, and in engineering education.
Reliability Aspect of Cloud Computing Environment
by Vikas Kumar R. VidhyalakshmiThis book presents both qualitative and quantitative approaches to cloud reliability measurements, together with specific case studies to reflect the real-time reliability applications. Traditional software reliability models cannot be used for cloud reliability evaluation due to the changes in the development architecture and delivery designs. The customer–vendor relationship mostly comes to a close with traditional software installations, whereas a SaaS subscription is just a start of the customer–vendor relationship. Reliability of cloud services is normally presented in terms of percentage, such as 99.9% or 99.99%. However, this type of reliability measurement provides confidence only in the service availability feature and may cover all the quality attributes of the product.The book offers a comprehensive review of the reliability models suitable for different services and deployments to help readers identify the appropriate cloud products for individual business needs. It also helps developers understand customer expectations and, most importantly, helps vendors to improve their service and support. As such it is a valuable resource for cloud customers, developers, vendors and the researchers.
Reliability Assessment of Safety and Production Systems: Analysis, Modelling, Calculations and Case Studies (Springer Series in Reliability Engineering)
by Jean-Pierre Signoret Alain LeroyThis book provides, as simply as possible, sound foundations for an in-depth understanding of reliability engineering with regard to qualitative analysis, modelling, and probabilistic calculations of safety and production systems. Drawing on the authors’ extensive experience within the field of reliability engineering, it addresses and discusses a variety of topics, including: • Background and overview of safety and dependability studies; • Explanation and critical analysis of definitions related to core concepts; • Risk identification through qualitative approaches (preliminary hazard analysis, HAZOP, FMECA, etc.); • Modelling of industrial systems through static (fault tree, reliability block diagram), sequential (cause-consequence diagrams, event trees, LOPA, bowtie), and dynamic (Markov graphs, Petri nets) approaches; • Probabilistic calculations through state-of-the-art analytical or Monte Carlo simulation techniques; • Analysis, modelling, and calculations of common cause failure and uncertainties; • Linkages and combinations between the various modelling and calculation approaches; • Reliability data collection and standardization. The book features illustrations, explanations, examples, and exercises to help readers gain a detailed understanding of the topic and implement it into their own work. Further, it analyses the production availability of production systems and the functional safety of safety systems (SIL calculations), showcasing specific applications of the general theory discussed. Given its scope, this book is a valuable resource for engineers, software designers, standard developers, professors, and students.
Reliability Assessment of Tethered High-altitude Unmanned Telecommunication Platforms: k-out-of-n Reliability Models and Applications (Infosys Science Foundation Series)
by Vladimir M. Vishnevsky Dharmaraja Selvamuthu Vladimir Rykov Dmitry V. Kozyrev Nika Ivanova Achyutha KrishnamoorthyThis book provides a systematic presentation of the major results in the field of the theory of k-out-of-n systems obtained in recent years and their applications for the reliability assessment of high-altitude unmanned platforms. Mathematical models, methods, and algorithms, presented in the book, will make a significant contribution to the development of reliability theory and the theoretical foundations of unmanned UAV-based aerial communications networks in the framework of the concept of creating the 5G and beyond networks. The book gives a description of new mathematical methods and approaches (based on decomposable semi-regenerative processes, simulation and machine learning methods, and inventory models) to the study of the complex k-out-of-n systems, which makes it possible to carry out numerical calculations of reliability indicators. Organized into five chapters, each chapter begins with a summary of the main definitions andresults contained in the chapter. The content of this book is based on the original results developed by the authors, many of which appear for the first time in book form.
Reliability, Availability and Serviceability of Networks-on-Chip
by Alexandre de Morais Amory Érika Cota Marcelo Soares LubaszewskiThis book presents an overview of the issues related to the test, diagnosis and fault-tolerance of Network on Chip-based systems. It is the first book dedicated to the quality aspects of NoC-based systems and will serve as an invaluable reference to the problems, challenges, solutions, and trade-offs related to designing and implementing state-of-the-art, on-chip communication architectures.
Reliability Engineering and Computational Intelligence (Studies in Computational Intelligence #976)
by Coen Van Gulijk Elena ZaitsevaComputational intelligence is rapidly becoming an essential part of reliability engineering. This book offers a wide spectrum of viewpoints on the merger of technologies. Leading scientists share their insights and progress on reliability engineering techniques, suitable mathematical methods, and practical applications. Thought-provoking ideas are embedded in a solid scientific basis that contribute to the development the emerging field. This book is for anyone working on the most fundamental paradigm-shift in resilience engineering in decades. Scientists benefit from this book by gaining insight in the latest in the merger of reliability engineering and computational intelligence. Businesses and (IT) suppliers can find inspiration for the future, and reliability engineers can use the book to move closer to the cutting edge of technology.
Reliability Engineering and Computational Intelligence for Complex Systems: Design, Analysis and Evaluation (Studies in Systems, Decision and Control #496)
by Coen Van Gulijk Elena Zaitseva Miroslav KvassayThis book offers insight into the current issues of the merger between reliability engineering and computational intelligence. The intense development of information technology allows for designing more complex systems as well as creating more detailed models of real-world systems which forces traditional reliability engineering approaches based on Boolean algebra, probability theory, and statistics to embrace the world of data science. The works deal with methodological developments as well as applications in the development of safe and reliable systems in various kinds of distribution networks, in the development of highly reliable healthcare systems, in finding weaknesses in systems with the human factor, or in reliability analysis of large information systems and other software solutions. In this book, experts from various fields of reliability engineering and computational intelligence present their view on the risks, the opportunities and the synergy between reliability engineering and computational intelligence that have been developed separately but in recent years have found a way to each other. The topics addressed include the latest advances in computing technology to improve the real lives of millions of people by increasing safety and reliability of various types of real-life systems by increasing the availability of software services, reducing the accident rate of means of transport, developing high reliable patient-specific health care, or generally, save cost and increase efficiency in the work and living environment. Though this book, the reader has access to professionals and researchers in the fields of reliability engineering and computational intelligence that share their experience in merging the two as well as an insight into the latest methods, concerns and application domains.
Reliability Engineering for Industrial Processes: An Analytics Perspective (Springer Series in Reliability Engineering)
by P. K. Kapur Hoang Pham Gurinder Singh Vivek KumarThis book explores how transformative changes driven by the new-age economy can bring about improvements in a company's engineering and manufacturing capabilities. The new-age economy is driven by advanced engineering and manufacturing practices, processes, and technologies, including the Internet of Things (IoT), Cloud Computing, Blockchain, Artificial Intelligence, Robotics, Cyber-Physical Systems (CPS), and Internet-enabled systems to automate industrial processes. Today's business dynamics are governed by uncertainties, disruptions, complexities, and ambiguities that demand quicker and more intelligent decisions. These changes could relate a renaissance in the company's engineering and manufacturing capabilities. To sustain these volatile and ever-changing business dynamics, Industry 4.0 and 5.0 have revolutionized how organizations operate and make intelligent business decisions. Moreover, the extensive role of business analytics has overcome the limitations ofclassical computing through new technologies and intelligent computing methodologies. Over the past few years, much emphasis has been given to investing in developing hardware and programming frameworks for achieving computational intelligence using fuzzy logic, evolutionary computation, neural networks, probabilistic methods, and learning theory. Within this frame of reference, the reliability, quality, and maintenance of complex industrial and manufacturing systems are essential for organizations to utilize them successfully for informed decisions. This book focuses on studies that provide new solutions for system reliability, quality, security, and maintainability using quantitative and qualitative research. It emphasizes developments and problems in systems engineering management, systems integration, software and hardware engineering, and the development process.
Reliability of Power Systems (Power Systems)
by G.F. Kovalev L.M. LebedevaThis book presents essential methods and tools for research into the reliability of energy systems. It describes in detail the content setting, formalisation, and use of algorithms for assessing the reliability of modern, large, and complex electric power systems. The book uses a wealth of tables and illustrations to represent results and source information in a clear manner. It discusses the main operating conditions which affect the reliability of electric power systems, and describes corresponding computing tools which can help solve issues as they arise. Further, all methodologies presented here are demonstrated in numerical examples. Though primarily intended for researchers and practitioners in the field of electric power systems, the book will also benefit general readers interested in this area.
Reliability, Safety and Hazard Assessment for Risk-Based Technologies: Proceedings of ICRESH 2019 (Lecture Notes in Mechanical Engineering)
by Prabhakar V. Varde Raghu V. Prakash Gopika VinodThis volume presents selected papers from the International Conference on Reliability, Safety, and Hazard. It presents the latest developments in reliability engineering and probabilistic safety assessment, and brings together contributions from a diverse international community and covers all aspects of safety, reliability, and hazard assessment across a host of interdisciplinary applications. This book will be of interest to researchers in both academia and the industry.
Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification: 4th International Conference, RSSRail 2022, Paris, France, June 1–2, 2022, Proceedings (Lecture Notes in Computer Science #13294)
by Simon Collart-Dutilleul Anne E. Haxthausen Thierry LecomteThis book constitutes the refereed proceedings of the 4th International Conference on Reliability, Safety, and Security of Railway Systems, RSSRail 2022, held in Paris, France, in June 2022. The 16 full papers presented in this book were carefully reviewed and selected from numerous submissions. They cover a range of topics including railways system and infrastructure advance modelling; scheduling and track planning; safety process and validation; modelling; formal verification; and security.
Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification: Third International Conference, RSSRail 2019, Lille, France, June 4–6, 2019, Proceedings (Lecture Notes in Computer Science #11495)
by Simon Collart-Dutilleul Thierry Lecomte Alexander RomanovskyThis book constitutes the refereed proceedings of the Third International Conference on Reliability, Safety, and Security of Railway Systems, RSSRail 2019, held in Lille, France in June 2019. The 18 full papers presented in this book were carefully reviewed and selected from 38 submissions. They cover a range of topics including railways system and infrastructure advance modelling; scheduling and track planning; safety process and validation; modelling; formal verification; and security.
Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification: 5th International Conference, RSSRail 2023, Berlin, Germany, October 10–12, 2023, Proceedings (Lecture Notes in Computer Science #14198)
by Birgit Milius Simon Collart-Dutilleul Thierry LecomteThis book constitutes the proceedings of the 5th International Conference on Reliability, Safety, and Security of Railway Systems. Modelling, Analysis, Verification, and Certification, RSSRail 2023, held in Berlin, Germany, during October 10–12, 2023.The 13 full papers presented in this book together with 3 keynotes were carefully reviewed and selected from 25 submissions. The papers are divided into the following topical sections: modeling for security; tooled approaches and dependability of highly automated transport systems; formal methods for safety assessment; and formal model and visual tooling.
Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures
by Punit Gupta Dinesh Kumar Saini Kashif Zia H. S. Madhusudhan Kumar T. SatishOne of the major developments in the computing field has been cloud computing, which enables users to do complicated computations that local devices are unable to handle. The computing power and flexibility that have made the cloud so popular do not come without challenges. It is particularly challenging to decide which resources to use, even when they have the same configuration but different levels of performance because of the variable structure of the available resources. Cloud data centers can host millions of virtual machines, and where to locate these machines in the cloud is a difficult problem. Additionally, fulfilling optimization needs is a complex problem.Reliable and Intelligent Optimization in Multi-Layered Cloud Computing Architectures examines ways to meet these challenges. It discusses virtual machine placement techniques and task scheduling techniques that optimize resource utilization and minimize energy consumption of cloud data centers. Placement techniques presented can provide an optimal solution to the optimization problem using multiple objectives. The book focuses on basic design principles and analysis of virtual machine placement techniques and task allocation techniques. It also looks at virtual machine placement techniques that can improve quality-of-service (QoS) in service-oriented architecture (SOA) computing. The aims of virtual machine placement include minimizing energy usage, network traffic, economical cost, maximizing performance, and maximizing resource utilization. Other highlights of the book include: Improving QoS and resource efficiency Fault-tolerant and reliable resource optimization models A reactive fault tolerance method using checkpointing restart Cost and network-aware metaheuristics. Virtual machine scheduling and placement Electricity consumption in cloud data centers Written by leading experts and researchers, this book provides insights and techniques to those dedicated to improving cloud computing and its services.
Reliable Computer Systems: Design and Evaluation, Third Edition
by null Daniel P. Siewiorek null Robert S. SwarzThis classic reference work is a comprehensive guide to the design, evaluation, and use of reliable computer systems. It includes case studies of reliable systems from manufacturers, such as Tandem, Stratus, IBM, and Digital. It covers special systems such as the Galileo Orbiter fault protection system and AT&T telephone switching system processors
Reliable Control and Filtering of Linear Systems with Adaptive Mechanisms (Automation and Control Engineering)
by null Guang-Hong Yang null Dan YeMore and more, the advanced technological systems of today rely on sophisticated control systems designed to assure greater levels of safe operation while optimizing performance. Rather than assuming always perfect conditions, these systems require adaptive approaches capable of coping with inevitable system component faults. Conventional feedback control designs do not offer that capability and can result in unsatisfactory performance or even instability, which is totally unacceptable in complex systems such as aircraft, spacecraft, and nuclear power plants where safety is a paramount concern. Reliable Control and Filtering of Linear Systems with Adaptive Mechanisms presents recent research results that are advancing the field. It shows how adaptive mechanisms can be successfully introduced into the traditional reliable control/filtering, so that, based on the online estimation of eventual faults, the proposed adaptive reliable controller/filter parameters are updated automatically to compensate for any fault effects. Presenting a new method for fault-tolerant control (FTC) in the context of existing research, this uniquely cohesive volume, coauthored by two leading researchers — Focuses on the issues of reliable control/filtering in the framework of indirect adaptive method and LMI techniques Starts from the development and main research methods in FTC to offer a systematic presentation of new methods for adaptive reliable control/filtering of linear systems Explains the principles behind adaptive designs for closed-loop systems in normal operation as well as those that account for both actuator and sensor failures Presents rigorous mathematical analysis of control methods as well as easy-to-implement algorithms Includes practical case studies derived from the aerospace industry including simulation results for the F-16 The authors also extend the design idea from linear systems to linear time-delay systems via both memory and memory-less controllers. Moreover, some more recent results for the corresponding adaptive reliable control against actuator saturation are included. Ultimately, this remarkably practical resource, offers design approaches and guidelines that researchers can readily employ in the design of advanced FTC techniques offering improved reliability, maintainability, and survivability.
Reliable JavaScript: How to Code Safely in the World's Most Dangerous Language
by Seth Richards Lawrence SpencerCreate more robust applications with a test-first approach to JavaScript <P><P> Reliable JavaScript, How to Code Safely in the World's Most Dangerous Language demonstrates how to create test-driven development for large-scale JavaScript applications that will stand the test of time and stay accurate through long-term use and maintenance. Taking a test-first approach to software architecture, this book walks you through several patterns and practices and explains what they are supposed to do by having you write unit tests. Write the code to pass the unit tests, so you not only develop your technique for structuring large-scale applications, but you also learn how to test your work. You'll come away with hands-on practice that results in code that is correct from the start, and has the test coverage to ensure that it stays correct during subsequent maintenance. All code is provided both in the text and on the web, so you can immediately get started designing more complete, robust applications.<P> JavaScript has graduated from field-validation scripts to full-scale applications, but many developers still approach their work as if they were writing simple scripts. If you're one of those developers, this book is the solution you need to whip your code into shape and create JavaScript applications that work.<P> * Write more concise and elegant code by thinking in JavaScript<P> * Test the implementation and use of common design patterns<P> * Master the use of advanced JavaScript features<P> * Ensure your code's conformance to your organization's standards<P> If you're ready to step up your code and develop more complete software solutions, Reliable JavaScript is your essential resource.
Reliable Machine Learning: Applying SRE Principles to ML in Production
by Cathy Chen Niall Richard Murphy Kranti Parisa D. Sculley Todd UnderwoodWhether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization. By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind. You'll examine:What ML is: how it functions and what it relies onConceptual frameworks for understanding how ML "loops" workHow effective productionization can make your ML systems easily monitorable, deployable, and operableWhy ML systems make production troubleshooting more difficult, and how to compensate accordinglyHow ML, product, and production teams can communicate effectively