Professor Honglei Xu' research interests include theory and applications of nonlinear control and systems engineering.
Prof. Song Wang is a professor of Department of Mathematics and Statistics, The University of Western Australia. He has published over 100 research papers in various international journals including Automatica, Biomaterials, IEEE Trans. on Neural Networks, J. Comp. Phys., Math. Comp, IMA J Numer. Anal, Int. J. Bifurcation & Chaos, Numer. Math., Reports on Progress in Physics, SIAM J Numer, Anal, SIAM J. on Optimization.
Prof. SOON-YI WU's research interests include functional analysis, linear programming, optimization.
The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and construction management.
The Goal: A Process of Ongoing Improvement by Eliyahu Goldratt and Jeff Cox describes a process by which an unprofitable manufacturing operation can be made profitable. It conveys proven factory turnaround principles through a fictional story…
PLEASE NOTE: This is key takeaways and analysis of the book and NOT the original book.
Inside this Instaread of The Goal:Overview of the bookImportant PeopleKey TakeawaysAnalysis of Key Takeaways
Topics covered in the first part include control theory on infinite dimensional Banach spaces, history-dependent inclusion and linear programming complexity theory. Chapters also explore the use of approximations of Hamilton-Jacobi-Bellman inequality for solving periodic optimization problems and look at multi-objective semi-infinite optimization problems and production planning problems.
In the second part, the authors address techniques and applications of optimization and control in a variety of disciplines, such as chaos synchronization, facial expression recognition and dynamic input-output economic models. Other applications considered here include image retrieval, natural earth satellites orbital transfers, snap-back repellers and modern logistic systems.
Readers will learn of advances in optimization, control and operations research, as well as potential new avenues of research and development. The book will appeal to scientific researchers, mathematicians and all specialists interested in the latest advances in optimization and control.
But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.
Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet.
Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype.
But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.
Each chapter will cover a different technique in a spreadsheet so you can follow along:Mathematical optimization, including non-linear programming and genetic algorithms Clustering via k-means, spherical k-means, and graph modularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, and bag-of-words models Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation Moving from spreadsheets into the R programming language
You get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.
"Ariely not only gives us a great read; he also makes us much wiser."
—George Akerlof, 2001 Nobel Laureate in Economics
—New York Times Book Review
Why do our headaches persist after we take a one-cent aspirin but disappear when we take a fifty-cent aspirin? Why do we splurge on a lavish meal but cut coupons to save twenty-five cents on a can of soup?
When it comes to making decisions in our lives, we think we're making smart, rational choices. But are we?
In this newly revised and expanded edition of the groundbreaking New York Times bestseller, Dan Ariely refutes the common assumption that we behave in fundamentally rational ways. From drinking coffee to losing weight, from buying a car to choosing a romantic partner, we consistently overpay, underestimate, and procrastinate. Yet these misguided behaviors are neither random nor senseless. They're systematic and predictable—making us predictably irrational.