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Ralston R: The Forecast

The Forecast

An Inside Look at How Successful Leaders Drive Revenue Growth

Event-driven microservices offer an optimal approach to harnessing event streams, reacting and responding to changes as they occur across your company. With this fully revised and updated guide, you'll learn how to apply the principles of event-driven architecture to create event streams and build powerful microservice applications. Author Adam Bellemare takes you through the process of creating event-driven microservice architectures, from first principles all the way to advanced applications. Covering events, event streams, and microservices, this book will give you powerful and reusable patterns for sharing and using important data all across your organization. <ul><li>The theory and principles of event-driven architectures</li> <li>How to design and build event-driven microservice architectures to deliver exceptional business value</li> <li>Event and event-stream design patterns, including schemas and evolution through time</li> <li>Microservice application patterns, both as singular services and as a collection of multiple services</li> <li>Tooling and techniques to get your event-driven microservice ecosystem off the ground and set yourself up for success</li> <li>Integrating event-driven applications into your existing architecture</li>
</ul>

Leveraging Organizational Data at Scale

Building Event-Driven Microservices

Advanced Computational and Mathematical Approaches in Applied Differential Equations explores cutting-edge techniques and methodologies in solving complex differential equations, a cornerstone of mathematical modeling across science and engineering. The book bridges theory and application, offering advanced computational strategies and innovative mathematical insights to address real-world problems. Beginning with an overview that presents a unified framework that defines the types of differential equations covered (e.g. ordinary, partial, fractional, fuzzy), the book then progresses to foundations and methods such as Lie symmetries, homotropy, Adomian, FEM, FDM, spectral, machine learning, fuzzy, and fractional derivatives, addressing both computational and mathematical dimensions. Differential equations are fundamental to modeling complex systems, yet solving them often involves significant challenges due to their complexity and nonlinearity. The book equips readers with advanced tools and methodologies to overcome these challenges, providing innovative solutions that improve accuracy, efficiency, and applicability in real-world scenarios. Ideal for researchers, practitioners, and advanced students, it provides a comprehensive resource for tackling challenging applied differential equations with better precision and efficiency.

Advanced Computational and Mathematical Approaches in Applied Differential Equations

Stop Overthinking and Launch Your Dream Business

Fear Is a Liar

An expert playbook for UX professionals researching, designing, and testing AI-powered products In UX for AI: A Framework for Designing AI-Driven Products, Greg Nudelman - a seasoned UX designer and AI strategist - delivers a proven framework for creating exciting, effective, and practical UX designs that integrate with new artificial intelligence technologies. You'll find tools you can put to work immediately as you research, plan, design, and test user experiences that incorporate human-AI interactions. The book offers hands-on design techniques that rely on tested user research methods. It also includes exercises, like Digital Twin and Value Matrix, that build your design skills and confidence, as well as AI patterns and best practices that have proven effective in real-world deployments of LLMs (Large Language Models), AI agents, copilots, AI search tools, and more. UX for AI is an original and up-to-date design guide that belongs on the desk of every UX designer and product professional working with AI-enabled or AI-driven products. It's also a must-read for students of UX design, new and trainee UX professionals, and anyone else involved in the creation of software that incorporates artificial intelligence.

A Framework for Designing AI-Driven Products

UX for AI

She built the thing everyone said they wanted. Not one person signed up. Not "a few." Not "slower than expected." Zero. After nine years as a compliance manager for a real estate association, L. V. Ivy had heard the same complaints on repeat - agents blindsided by lapsed licenses, brokers with no clean way to track their teams, dues and deadlines scattered across half a dozen disconnected systems. Nine years of if only something like this existed. So when she lost that job, she built it. AI tools made it possible to ship a full platform alone, fast, and every video she watched told her the same thing: build the whole ecosystem and it will sell itself. She spent four months and her unemployment money finding out what that advice leaves out. This is that story, told in order, without the course-seller's polish. It is not an argument against using AI - the tools are real, and she still uses them daily. It is about the part nobody selling a course wants to mention: the tools were never the piece that was missing. Ten short chapters, each closing with two questions pointed straight back at whatever you're building right now: <ul><li>The dream you're being sold - and who profits from it</li><li>The psychology of easy money</li><li>Why a real problem still isn't a business</li><li>Building in a vacuum, and why nobody tells you no</li><li>What "marketing" actually costs</li><li>The warning signs of an ecosystem nobody asked for</li><li>The order she'd follow if she started over</li><li>Keeping your day job while you test the idea</li><li>When it is actually time to quit</li></ul> Written by someone still in it, while the details were fresh - not from the far side of a success story. If you have an idea, an AI subscription, and a plan to go all in, read this first. It's a couple of hours. It may save you four months.

What I Learned Building a Platform Nobody Used

DON'T QUIT YOUR DAY JOB FOR AI

While the hotel and short term rental sectors are growing, there is a technology divide between operators using technology strategically to run better operations and those that are not. Hospitality professionals need to understand their businesses' pain points to better invest in technology solutions and transform their businesses to be more profitable, and in some cases, more personal.
 
 Tech-enabled Hospitality looks at how the intersection of technology and personalized service can redefine the future of hospitality, including for large chains and small and medium-sized enterprises (SMEs) in the lodging sector. With its focus on practical applications of technology for enhancing both operational efficiency and guest experiences, this book is a valuable resource for those looking to modernize their hospitality business without losing the essence of personal touch. Through real-world examples and in-depth expert interviews from brands such as Stripe, SiteMinder and Rocco Forte, this book explores hospitality functions such as hotel management, operations, revenue management, sustainability, IoT, access control, guest communications, payment processing, guest experience, virtual concierge and AI tools. This book will help hospitality professionals better understand the hows and whys of implementing technology to run everyday aspects of a hospitality business while still leaving room, if desired, to provide a uniquely human experience that underpins true 'hospitality'.

Strategies to Elevate Guest Experience and Operational Efficiency

Tech-Enabled Hospitality

Reshaping Geotechnical Engineering with Machine Learning: Theory, Applications, and Innovations explores the transformative impact of machine learning (ML) on the field of geotechnical engineering. The book begins by examining the broad applications of ML in key areas such as foundation engineering and slope stability, demonstrating how advanced algorithms can enhance predictive accuracy and decision-making. It emphasizes the importance of robust data acquisition and preprocessing techniques, which are critical for the successful implementation of ML models in geotechnical contexts. The text examines the use of machine learning for predicting soil behavior, a complex challenge in geotechnical engineering, and highlights its role in risk assessment and management. In addition, it also addresses the integration of ML with finite element modeling to improve the analysis of tunnel and underground stability. The applications of machine learning in understanding geotechnical materials further showcase the versatility of these techniques. It also covers experimental investigations, including laboratory and field studies, which provide essential data for model training and validation. Through detailed case studies, the book illustrates practical implementations of machine learning, bridging theory and real-world problem-solving.

Theory, Applications, and Innovations

Reshaping Geotechnical Engineering with Machine Learning

Concepts and Methods

Digital Twins in Manufacturing

Introduction to Process Systems Engineering: Basic Principles and Calculations with MATLAB and Python comprehensively approaches how to master core chemical engineering concepts through computational methods. The book bridges the gap between theory and practice by integrating numerical computations from the outset, enabling students and professionals to develop practical skills alongside foundational knowledge. Covering essential topics such as mass and energy balances, property calculations, vapor-liquid equilibria, and process optimization, the book emphasizes realistic problem-solving using accessible MATLAB and Python programs. Each chapter features real-world examples, progressively increasing in complexity to build confidence and competence. The material is tailored to current chemical engineering practice, making it an invaluable resource for students, researchers, and industry practitioners seeking to enhance their computational and analytical capabilities in process systems engineering. This book empowers readers to learn by doing, fostering a deeper understanding of both theoretical principles and their practical applications.

Basic Principles and Calculations with MATLAB and Python

Introduction to Process Systems Engineering

Statistical Methods in the Atmospheric Sciences, Fifth Edition provides a structured exploration of the statistical techniques essential for analyzing atmospheric data. The book begins with foundational concepts in probability, setting the stage for more advanced topics. It then covers univariate statistics, including empirical distributions, parametric probability models, and both frequentist and Bayesian inference methods, offering tools for rigorous data analysis and interpretation. The text also addresses statistical forecasting and ensemble forecasting, along with methods for verifying forecast accuracy. In addition, time series analysis is explored in detail, enabling readers to understand temporal dependencies in atmospheric data. The book advances into multivariate statistics, presenting matrix algebra and random matrices as mathematical foundations. It discusses the multivariate normal distribution, principal component analysis (EOF), and multivariate analysis of vector pairs to handle complex, multidimensional atmospheric datasets. Techniques for discrimination, classification, and cluster analysis are also examined, providing methods for categorizing and interpreting atmospheric patterns. Supplementary materials include example data sets, probability tables, and a glossary of symbols and acronyms, along with answers to exercises that reinforce learning.

Statistical Methods in the Atmospheric Sciences

Scaling a supply chain and logistics SaaS company past founder-led sales is not a sales problem. It is a system problem.
Most founders try to fix it with better reps, sharper pitches, or more outbound. None of that works until the underlying system works. Ideal customer profile. Messaging that holds in someone else's mouth. A sales process with real exit criteria. Pricing that qualifies buyers. Revenue operations that give you numbers you can trust.
GO TO MARKET LIKE YOU MEAN IT: The Tactical Field Guide for Scaling Supply Chain &amp; Logistics SaaS Revenue is the operating playbook for CEOs, founders, and sales leaders at logistics and supply chain SaaS companies between $3M and $50M ARR who need a motion their team can run without them.
This Industry Edition adapts the core framework for the realities of selling into logistics: skeptical operator buyers, long integration horizons, careful procurement cycles, and champions who must defend you internally against CIOs, CFOs, and the operators who use your product at two in the morning when something breaks.
Inside you will find:

A 30-day plan to install a RevOps backbone
A behavioral ICP framework tuned to logistics buyer archetypes
The Industry Relay method for outbound that actually gets replies in this industry
The Unit of Value Test for pricing logistics SaaS beyond per-seat models
A framework for earning operator trust in AI-accelerated GTM
Nineteen chapters covering ICP, messaging, outbound, pricing, RevOps, hiring, forecasting, and reporting
More than thirty-six companion worksheets and templates

With a foreword by Nick Costides, retired Global President of Information Technology at UPS, this is a working reference for founders who want to stop selling with personality and start selling with a system.
If your sales motion depends on you being on every call, this book is for you.

The Tactical Field Guide for Scaling Supply Chain & Logistics SaaS Revenue

Go to Market Like You Mean It

Funktionsreferenzmodell für ERP-Software

The Forecast

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