Modeling of Dynamic Systems Review

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(More customer reviews)I've been reading this and the book is very inspiring. It has so far given me a good insight on modeling of systems and system control. I Highly recommend this book!

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Written by a recognizedauthority in the field of identification andcontrol, this book draws together into a singlevolume the important aspects of systemidentification AND physical modelling. KEYTOPICS: Explores techniques used to constructmathematical models of systems based on knowledgefrom physics, chemistry, biology, etc. (e.g.,techniques with so called bond-graphs, as wellthose which use computer algebra for the modelingwork). Explains system identification techniquesused to infer knowledge about the behavior ofdynamic systems based on observations of thevarious input and output signals that areavailable for measurement. Shows how both types oftechniques need to be applied in any givenpractical modeling situation. Considersapplications, primarily simulation. For practicing engineers who are faced withproblems of modeling.

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Management Decision Making: Spreadsheet Modeling, Analysis, and Application Review

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(More customer reviews)This college-level text is also useful to business and IT professionals because it provides a refresher for decision techniques that are the foundation of a number of disciplines. The book is divided into two parts: (1) deterministic methods, mainly focused on linear programming and optimization, and (2) probability and queuing.
What makes this book valuable to the practicing professional is that it uses one of the most common business tools, Microsoft Excel, and shows how to apply this tool to real world problems. The accompanying CD ROM comes with TreePlan for developing decision trees and CrystalBall for Monte Carlo simulation, as well as workbooks that are used to support the plethora of realistic examples used throughout the book.
Although the book is business-oriented and better suited for operations analysis and MBA students and practitioners, I've used it as a reference for project planning, computer system capacity planning and performance analysis, and IT security risk management - these practical uses of the material show the value of the book in the real world. The supporting web site that the author maintains has materials for lesson plans, errata and additional resources that make this book particularly valuable for the academic and business environments.

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Management Decision Making is a spreadsheet-based introduction to the tools and techniques of modern managerial decision making. The author shows how to formulate models in Microsoft Excel that can be used to analyze complex problems taken from all the functional areas of management, including finance, marketing, operations, and human resources. Throughout, the goal is to understand how business decisions are reached, what tradeoffs are made, and how outcomes depend on the underlying data. A CD-ROM is included that contains the widely-used decision analysis software applications TreePlan and Crystal Ball. The book is aimed at students of business, economics and engineering, including those taking MBA courses.

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Realistic Modeling for Toy Trains: A Hi-rail Guide (Classic Toy Trains Books) Review

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(More customer reviews)When I first saw Dennis Brennan's photographs of his O-scale modeling, I was stunned. Not only was the photography excellent, the model building at the highest level, but there was an understanding of the art of both that elevated the pictures into that rare realm of the truly special.
Is it that the photos manage to create a mood? Is it that the compositions allow the eye to calmly circle the image? Is it that the lighting is natural, not overdone, but still dramatic? Is it that the balance of emptiness to intricate detail is perfect? I really don't know. The odd thing is that I can recognize a Dennis Brennan photo just as I recognize, for instance, a John Allen photo. There's something distinctive and personal that must be very difficult to achieve since I've only rarely seen it.
Brennan's work is about the ordinary. He teaches us that the ordinary can be inspiring and make a blindingly appealing model railroad. It's the intricate fitting of simple, common elements into a compelling whole. When I see the photos, so easy simply to look at, I'm overwhelmed when I consider trying to reproduce this effect.
But now Brennan has written a book that explains his craft and art. He outlines not only the how-to but also the artistic concepts and logic behind what he's accomplished. I'm not sure any of the rest of us can achieve quite what Brennan has, but I know this book can improve anyone's modeling. I believe this book will be a benchmark of its kind, and will influence many model railroads in the future. I only wish I had a copy when I started out over thirty years ago. The time it would have saved me! There must be forty years of knowledge and experience between these covers.
The weathering information alone is simply amazing and worth the price of the book. Brennan has a knack for faded color and worn texture that's not excessive, which tends to be the norm even among the best modelers. And then there's the track work, the structures, the perfect balance of toy train and resonant realism that's so difficult to master. That clean, everyday, balanced look where the viewer doesn't want to change a thing because it's exactly right as it is.

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The author shows step-by-step how various creative elements of a layout fit together using his Sandy Harbor Terminal Railway. Practical building techniqes and realistic modeling concepts, explain how readers can build a hi-rail toy train layout.

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SOA Modeling Patterns for Service Oriented Discovery and Analysis Review

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(More customer reviews)- Sometimes you wonder what you can get for a price that you pay for less than a full tank of gas!
- This book is a clear milestone in software modeling and architecture. I think that this is the next generation. Its value is tremendous to business and IT and especially to analysis, discovery, and modeling of software assets in the space of software development in general, SOA, and Cloud Computing.
- I think that it offers a very important direction and process to establishing services. But the services here are described as holistic software assets such as components, business processes, databases, Web services, applications, and any other software modules you may consider as executables. Interesting!
- In the analysis space, the presented concepts are innovative and can help you to establish a personal strategy as well as an organizational one.
- The patterns are not only design patterns. They are also process patterns, which are important to running projects and analysis patterns that can help you analyze a solution, a design, an architecture, a project direction, or even an enterprise strategy.
- I like the modeling section. Easy to understand and can be used by analysts, architects, managers, developers, and obviously modelers. Note this:
o Contextual analysis and modeling: Generalization, Specification, Expansion, and Contraction
o Structural analysis and modeling: Generalization, Specification, Expansion, and Contraction
- I highly recommend this book. It provides me with tools to see the big picture and helps with hands on low level implementation, such as coding, design, and more.


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Learn the essential tools for developing a sound service-oriented architecture

SOA Modeling Patterns for Service-Oriented Discovery and Analysis introduces a universal, easy-to-use, and nimble SOA modeling language to facilitate the service identification and examination life cycle stage. This business and technological vocabulary will benefit your service development endeavors and foster organizational software asset reuse and consolidation, and reduction of expenditure.
Whether you are a developer, business architect, technical architect, modeler, business analyst, team leader, or manager, this essential guide-introducing an elaborate set of more than 100 patterns and anti-patterns-will help you successfully discover and analyze services, and model a superior solution for your project,.
Explores how to discover services
Explains how to analyze services for construction and production
How to assess service feasibility for deployment
How to employ the SOA modeling language during the service identification and examination process
How to utilize the SOA modeling patterns and anti-patterns for service discovery and analysis

Focusing on the Service-Oriented Discovery and Analysis Life Cycle Stage, this book will help you acquire a broad SOA Modeling knowledge base and leverage that to increase efficiency and productivity in the workplace.

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Model: The Ugly Business of Beautiful Women Review

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(More customer reviews)This book does exactly what the title says, it reveals the ugly side of the modeling business. However, it is an older book so you won't hear any recent names. There is another book out there, "Shut up and Smile" that covers more recent models. But the writing from that book is no comparison to this one. This book is by someone that knows how to write and the stories are very in-depth which can only make the book better. The pictures are also better in this book.

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Hierarchical Modeling and Analysis for Spatial Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) Review

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(More customer reviews)I've bought several spatial statistics books over the years and found they generally fall into one of two categories; oversimplified or cover-to-cover matrix notation, neither of which is very useful for my research. However, this book is "just right," bridging these two extremes. It briefly covers the basics of both point and areal analysis, then gives the reader the tools for more advanced (i.e., realistic) analysis. They devote a chapter to Bayesian basics, which is needed for the last 4 or 5 chapters. The last few chapters weave together a detailed discussion on a variety of hierarchical models and current published results. Most importantly this book offers quite a bit of the necessary R and Winbugs code. Although many of their examples are from the public health world, the techniques and code are easily adapted to natural resource data - my personal focus.

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Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and data analysis for spatial and spatio-temporal data. Starting with overviews of the types of spatial data, the data analysis tools appropriate for each, and a brief review of the Bayesian approach to statistics, the authors discuss hierarchical modeling for univariate spatial response data, including Bayesian kriging and lattice (areal data) modeling. They then consider the problem of spatially misaligned data, methods for handling multivariate spatial responses, spatio-temporal models, and spatial survival models. The final chapter explores a variety of special topics, including spatially varying coefficient models.This book provides clear explanations, plentiful illustrations --some in full color--a variety of homework problems, and tutorials and worked examples using some of the field's most popular software packages.. Written by a team of leaders in the field, it will undoubtedly remain the primary textbook and reference on the subject for years to come.

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Power Integrity Modeling and Design for Semiconductors and Systems Review

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(More customer reviews)At first, I was looking for a book covering on-chip power integrity issue and happened to find this book on Amazon. Since I can not search inside this book, I just bought it and later found it is related to the power integrity of package, not chip. However, I DEFINITELY don't regret buying this book because it covers one of the important pieces in the design of power distribution network.
After reading chapter 1, I realize that the power integrity issue should be attacked from a system point of view, including chip, package and board. Only considering on-chip power integrity is not enough because the power supply is located on the board and electrically far away from the chip. The important concept of target impedance is also introduced and really opens my mind on how to design a robust power distribution network.
Chapter 2 covers the modeling of power/ground planes in high performance package and board. Two novel modeling methods, transmission matrix method and cavity-model method are desrcibed in detail here. The major advantages of the two methods over full wave methods, like FDTD and FEM, are ease of integrating into circuit simulators.
Chapter 3 covers the topic of simultaneous switching noises. The signal nets are modeled as uncoupled microstrip and strip transmission lines. The coupling effects between signals and power/ground planes are modeled as controlled sources, which are obtained by mode decomposistion methods. Then, the uncoupled transmission lines and controlled sources are integrated with the power/ground plane models from chapter 2 to conduct simultaneous switching noise analysis.
Chapter 4 introduces time-domain simulations of power distribution networks. The major foucs is how to incorporate s-parameter data into time-domain circuit simulators. The techniques like vetor fitting, passivitiy enforcement by Hamiltonian matrix , signal flow method, and MNA with s-parameter are explained and compared.
Chapter 5 applies the modeling and analysis methods from previous chapters to real applications. Great insight is learned from these real world problems.
I strongly recommend this book to the designers and CAD tool developers of power distribution networks. Since the major focus of this book is package power, I also recommend two other books which cover board and on-chip power integirty issue respectively:
"Frequency-Domain Characterization of Power Distribution Networks" by Istvan Novak and Jason R. Miller
"Power Distribution Networks with On-Chip Decoupling Capacitors" by Mikhail Popovich, Andrey V. Mezhiba, and Eby G. Friedman


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Exercises in Rethinking Innateness: A Handbook for Connectionist Simulations (Neural Network Modeling and Connectionism) Review

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(More customer reviews)Here's a self-contained introduction to connectionist modeling. Easy to read and straight-forward, this text provides software and excercises aimed at stepping a novice through the basics of connectionism. Designed to accompany Rethinking Innateness (1996), these examples provide a glimpse into the world of cognitive modeling. The examples can, at times, be frustrating and the text is in need of more debugging hints; yet, the simulations are rewarding and thought-provoking. While those already familiar with connectionism will find the excercises too basic, those curious about connectionism will find the book a great place to start and one that doesn't bog the reader down with technical jargon. It is accessible, enjoyable, and written by two key players in connectionism: Kim Plunkett and Jeff Elman. Well worth reading, but only if the reader is willing to work through the basic simulations and answer the excercises along the way.

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This book is the companion volume to Rethinking Innateness: AConnectionist Perspective on Development (The MIT Press, 1996), which proposed a newtheoretical framework to answer the question "What does it mean to say that abehavior is innate?" The new work provides concrete illustrations--in the form ofcomputer simulations--of properties of connectionist models that are particularlyrelevant to cognitive development. This enables the reader to pursue in depth someof the practical and empirical issues raised in the first book. The authors' largergoal is to demonstrate the usefulness of neural network modeling as a researchmethodology.The book comes with a complete software package, including demonstrationprojects, for running neural network simulations on both Macintosh and Windows 95.It also contains a series of exercises in the use of the neural network simulatorprovided with the book. The software is also available to run on a variety of UNIXplatforms.

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Modeling a Character in 3DS Max, Second Edition (Wordware Game Developer's Library) Review

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(More customer reviews)I purchased this book after skimming it over in a local store. I wish I had taken a closer look at it. I just came off a 2 week break from work and school. During my break I decided to work on a new model and following along with Mr. Steed's book. This turned out to be frustration hell. The methods in his book are fine if you are into wasting alot of time. Boolean and splines to make a simple character like the one in his book actually doubles your work. You wind up wasting more time cleaning up the errors from following his tutorial. Why he didn't demonstrate the way MOST people in the industry model, which is box modeling, is beyond me. He basicly tries to reinvent the wheel. I found much better tutorials for FREE on the web. Save yourself from learning bad modeling techniques. I happen to also know that Paul Steed DOES NOT model the way presented in the book. This should raise a red flag or two.

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In this update to his best-selling character modeling book, professional modeler and animator Paul Steed shares a number of tips, tricks, and techniques that have made him one of the industry s most recognized 3D artists. Modeling a Character in 3ds max, Second Edition provides readers a professional-level skill set as it chronicles the creation of a single low-poly real-time character from concept to texture mapping, and gives insight into the process of creating a high-resolution character. Learn how to:Model with primitives,Use extrusions and Booleans, Mirror and reuse models, Optimize the mesh, Create and apply textures, Loft shapes

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Structural Equation Modeling With Eqs: Basic Concepts, Applications, And Programming (Multivariate Applications) (Multivariate Applications Series) Review

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(More customer reviews)Byrne offers a more readable alternative to the hard core approach of learning EQS from its official manual. The latter presents a heavily mathematical framework that might be offputting to some readers who lack a strong statistical background.
Instead, her book goes through much of what EQS can do for you. But at a gentler pace. Giving a brief walkthrough of multivariate statistical modelling. The book starts off explaining the format of the EQS input file. It uses a graphical approach similar to what electrical engineers have for laying out circuits. More intuitive for the user. Where you can draw regressions paths from one component in the diagram to other components, for example. This is reminiscent of how SPICE went from a text input file that described a circuit to a graphical approach that was far easier to understand.
Much of the book then goes into how you can test for causality in your model. EQS has formidable abilities to do so, and you need to master how to control these.

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Researchers and students who want a less mathematical alternative to the EQS manual will find exactly what they're looking for in this practical text. Written specifically for those with little to no knowledge of structural equation modeling (SEM) or EQS, the author's goal is to provide a non-mathematical introduction to the basic concepts of SEM by applying these principles to EQS, Version 6.1. The book clearly demonstrates a wide variety of SEM/EQS applications that include confirmatory factor analytic and full latent variable models. Analyses are based on a wide variety of data representing single and multiple-group models; these include data that are normal/non-normal, complete/incomplete, and continuous/categorical. Written in a "user-friendly" style, the author "walks" the reader through the varied steps involved in the process of testing SEM models. These include model specification and estimation, assessment of model fit, description of EQS output, and interpretation of findings. Each of the book's applications is accompanied by: a statement of the hypothesis being tested, a schematic representation of the model, explanations and interpretations of the related EQS input and output files, tips on how to use the associated pull-down menus and icons, and the data file upon which the application is based. Beginning with an overview of the basic concepts of SEM and the EQS program, the book carefully works through applications starting with relatively simple single group analyses, through to more advanced applications, such as a multi-group, latent growth curve, and multilevel modeling.The new edition features: •many new applications that include a latent growth curve model, a multilevel model, a second-order model based on categorical data, a missing data multigroup model based on the EM algorithm, and the testing for latent mean differences related to a higher-order model; •a CD enclosed with the book that includes all application data; •vignettes illustrating procedural and/or data management tasks using a Windows interface; •description of how to build models both interactively using the BUILDULEQ interface and graphically using the EQS Diagrammer.

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Improving Comprehension with Think-Aloud Strategies: Modeling What Good Readers Do Review

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(More customer reviews)If you read aloud to your class, you must read this book! This books brings to our attention the during reading strategies that we do automatically and demonstrates how to teach them to our students. Appropriate for any grade level.

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Help students learn how to read better with the powerful technique that makes the reading process come alive for kids. Model predicting, inferring, visualizing, summarizing, making connections to real life and more.

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Geostatistics: Modeling Spatial Uncertainty (Wiley Series in Probability and Statistics) Review

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(More customer reviews)Highly recommended! This is easily the most comprehensive, scholarly, and up-to-date work in the area.
The authors cover the entire range of geostatistics - structural analysis (variogram fitting), kriging, multivariate and nonlinear methods, conditional simulation, scale effects, and inverse problems. The chapter on geostatistical simulation is particularly impressive, and much unpublished work of Georges Matheron and the Center for Geostatistics at Fontainebleau, France, is made available here for the first time. Practical and theoretical aspects of geostatistics balance each other very nicely.
This is not an introductory text - there are other books in the area which are custom-tailored to beginners - but it is an invaluable, and very carefully written, reference. For anyone applying geostatistical techniques in environmental sciences, earth sciences, engineering, or related fields, this book is a must-have!

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A novel, practical approach to modeling spatial uncertainty.This book deals with statistical models used to describe natural variables distributed in space or in time and space. It takes a practical, unified approach to geostatistics-integrating statistical data with physical equations and geological concepts while stressing the importance of an objective description based on empirical evidence. This unique approach facilitates realistic modeling that accounts for the complexity of natural phenomena and helps solve economic and development problems-in mining, oil exploration, environmental engineering, and other real-world situations involving spatial uncertainty.Up-to-date, comprehensive, and well-written, Geostatistics: Modeling Spatial Uncertainty explains both theory and applications, covers many useful topics, and offers a wealth of new insights for nonstatisticians and seasoned professionals alike. This volume:* Reviews the most up-to-date geostatistical methods and the types of problems they address.* Emphasizes the statistical methodologies employed in spatial estimation.* Presents simulation techniques and digital models of uncertainty.* Features more than 150 figures and many concrete examples throughout the text.* Includes extensive footnoting as well as a thorough bibliography.Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects.

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Cognitive Modeling (Bradford Books) Review

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(More customer reviews)This book could be considered to be a collection of articles on the `computational theory of mind.' Although the articles are somewhat out of date, due to the advances in neuroscience and cognitive science that have occurred since the time of publication of the book, it does serve as a good motivation for the understanding of more recent developments. I did not read all of the articles in the book, and so my review will be confined to the ones that I did.
The article on ACT in chapter 2 is basically a theory of cognition that is based on recursion. Referring to ACT as a "simple theory of complex cognition", John Anderson, the author of the article, wants to simulate the manner in which humans develop recursive programs. The machine that is to simulate this makes use of `production rules,' in its knowledge base, which the author claims is exhaustive enough to produce complex cognition. To produce true machine intelligence, all one has to do is to tune these production rules and make use of them as needed. As the author describes it, the original ACT theory was based on human associative memory, but the one described in this article is called ACT-R, and can simulate adaptive behavior in the presence of a noisy environment. The author describes various simulations using ACT-R, and concludes that it is sensitive to prior information and to information about what is appropriate response to the situation it finds itself in. The author stresses more than once the simplicity of the ACT-R system: it is able to encode data from the environment as declarative knowledge, encode the changes in the environment as procedural knowledge, and encode the statistics of this knowledge use in the environment.
Another highly interesting article is the one by Alan Prince and Paul Smolensky on the application of optimization theory to linguistics. Called `optimality theory' by the authors in their extensive research on the topic, in the article they discuss the relations between optimality in grammar and optimization in neural networks. The authors discuss with great clarity the role that constraints play in the construction of linguistic structures, and the fact that these constraints typically conflict with each other. This conflict between grammatical constraints must thus be managed by a successful grammatical architecture. Optimality theory asserts that these constraints are universal in the sense that they are present in every language. The connection of optimality theory with neural networks arises when one is interested in finding out if the properties of optimality theory can be explained in terms of fundamental principles of cognition. The computational theory of neural networks the authors believe holds some clues on these properties. In order to make the connection with grammatical issues, as abstract as they are, and because neural networks are highly nonlinear dynamical systems, one must find a way of encapsulating the complicated behavior of neural networks. The authors accomplish this by the use of Lyapunov functions, which for reasons of consistency of terminology they call `harmony functions.' For those neural networks admitting a harmony function, the initial activation pattern flows through the network to construct a pattern of activity that maximizes "harmony." Most interestingly, the harmony function for a neural network performs the same function as does the mechanisms needed for well-formed grammar. The patterns of activation are thus a mathematical analog of the structure of linguistic representations. However, the authors are careful to note that not every weighting scheme for the neural network will give a possible human language. It is here where the constraints play an essential role in limiting the possible linguistic patterns and relations.
The article by Keith Holyoak and Paul Thagard discusses the construction of a correspondence between a source analog and of a target. This is the so-called analogical mapping, which is constructed using a collection of structural, semantic, and pragmatic constraints. In the view of the authors, the concept of analogy can be broken down into four components, namely the selection of a source analog, the actual mapping, an analogical inference (transfer), and the actual learning that takes place. The authors omit discussion of the last component in this article. The finding of the correspondences between the two analogs can result in a combinatorial explosion, and so use is made of appropriate constraints. These constraints consist of those that exemplify structural consistency, those of semantic similarity, and lastly of pragmatic centrality. The theory of analogical mapping that the authors propose is governed by these constraints. They discuss the ACME (Analogical Constraint Mapping Engine) algorithm as one that constructs a network of units representing mapping hypotheses and eventually converges to a state that represents the best mapping. They list several applications of ACME, such as radiation problems, attribute mappings, chemical analogies, and the classical `farmer's dilemma' problem. ACME was also able to simulate a number of empirical results related to human analogical reasoning. The analogical mapping they discuss is most powerful in a specific domain however. This domain-specificity is a typical restriction for most of the efforts in learning theory and artificial intelligence.

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Computational modeling plays a central role in cognitive science. Thisbook provides a comprehensive introduction to computational models of humancognition. It covers major approaches and architectures, both neural network andsymbolic; major theoretical issues; and specific computational models of a varietyof cognitive processes, ranging from low-level (e.g., attention and memory) tohigher-level (e.g., language and reasoning). The articles included in the bookprovide original descriptions of developments in the field. The emphasis is onimplemented computational models rather than on mathematical or nonformalapproaches, and on modeling empirical data from human subjects.

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Ship Modeling from Scratch: Tips and Techniques for Building Without Kits Review

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(More customer reviews)I purchased this book several years past. This Amazon.com reviewer is an avid ship modeler. I use this book nearly constantly. I give this book five stars.
Now, this book was written in 1993. So, there are no web sites for reference nor is there a more recent write up. If a person is interested in making a scratch built ship they should surf onto the steelnavy.com web site. Steel Navy is known as one of the best web references for ship building. Museum quality ships from the world have pictures on that page. If you want American warship plans then surf to "Maryland Silver". They have nearly all of the ship plans of the modern Navy. Furthermore, they have plans for most of the pre-1880 (modern Navy) ships. Last, a fair source of ship plans is Ebay. One vendor on Ebay sells quite warships and Great Lakes vessels. If you are making a modern ship and need fittings the web sites to check out are H&R Products, Blue Jacket Ship Models, and The Scale Shipyard. All three web locations have lots of fittings for ships.
Now, back to this book.
This book covers all necessary steps for a ship modeler. The first chapter is on getting correct plans. If your plans are off then what is the point? The second chapter covers making the keel, ribs (frames), and then planking the ship. The rest of the chapters follow in logical progression. The chapters vary from rigging your model if you have a sailing ship to building a superstructure for a modern ship. Note, there are two complete sets of plans in the back of the book. One for a sailing ship and another for a simple cargo steamer. I didn't build either because this modeler makes battleships.
Speaking of battleships, the book gives quite a bit of information on constructing a South Carolina class battleship. The South Carolina class is semi-famous in model circles. The first ship of the class, BB-27, the USS Michigan, has extensive model construction articles written about it in this book. Now, the chapter on Cage Mast Construction is about the only major book that has been published that covers this topic. Cage Masts were found on every battleship made in the USA from about 1910 to 1920. Cage Masts are seen on many of the battleships, like the USS Tennessee, at Pearl Harbor. So, it's very good that a major book tells how to make a cage mast. Note, the chapter on Cage Mast construction will advise a builder to make a jig for the mast. Furthermore, it's advisable that no cage mast be made that is smaller than 1/144th scale.
The book also gives advise on the cutting of wood, plastics, and metal. Furthermore, there is suggestions by the author on what type of wood cutting machines to buy, such as a table saw, and what sort of finishing tool to purchase. The hobby of ship modelling is a lot easier if you have a Demel tool.
The book had lots of little helpful items. It give basic instructions for making a deadeye. Port holes, very necessary for a making a convincing ship, are covered in this book. If you don't want to follow the advise you can get fair portholes from either H & R Products or Blue Jacket.
The only thing that isn't really covered in this book is making a boat radio controlled. You'll have to get another book if you wish to RC your beloved museum quality ship.
I hope you enjoy this book as much as I have. This book should be studies by any body who wishes to make their first scratch built model. Note, there are no large scale commercial models of Great Lakes steamers or Pre-WWII battleships. So, if you want to build a nice model battleship of the USS Florida you'll have to get the plans from Maryland Silver, the fitting from H & R Products, and read this book to learn the knowledge necessary for making that model.
Best wishes, fellow ship builder, on reading this book. You'll enjoy your purchase. I look forward to hearing about your question on steelnavy.com .
This book is worth all five stars.

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Building a model from a kit is an excellent way to develop your modeling skills. But once you've mastered the basics, where do you go? If you're looking for a challenge, you move on to scratchbuilding. And that can be imposing: With a kit, you worked with someone else's plans, materials, and building instructions. Scratchbuilding makes you master of your own fate. You do the research, choose the subject, the scale, the material. The choices are limited only by your enthusiasm.
Edwin B. Leaf scratchbuilt his first model--a Baltimore clipper--nearly fifty years ago, and he's been refining and building on his skills ever since. In Ship Modeling from Scratch he lays out the principles--from concept to construction to display--on which scratchbuilding is based. In clear, concise language complemented by detailed illustrations he tells how to interpret existing drawings or create your own, what materials to choose, what tools to buy, and what techniques to use to build everything from plank-on-frame, plank-on-bulkhead, or modern steel hulls to creating sharp and properly scaled details--paint to portholes.
Building a model from scratch is a singular pursuit that requires patience, confidence, and ingenuity. With Ship Modeling from Scratch open on your workbench, you have your own private tutor guiding you through the troublespots.

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Dynamic Modeling (Modeling Dynamic Systems) Review

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(More customer reviews)This is an excellent book for beginning and intermediate modelers. I found it to be engaging, practical, and easy to understand. Dynamic modeling has become an essential tool to facilitate understanding developments in our increasingly complex and interdependent world, to communicate ideas across disciplinary boundaries, and to help solve problems. This book is a great place to begin. It offers a hands-on introduction to dynamic modeling.
The authors start with an easy to understand, step-by-step description of the modeling process, key principles of modeling, and general methods of modeling. This is followed-up with and numerous examples from chemistry, genetics, ecology, economics, and engineering. But this is not just a book to read. The book comes with run-time versions of the easy to learn STELLA and Madonna software as well as copies of the various models developed in each of the 37 chapters.
The authors encourage readers to build the models themselves as they work through the chapters, and then explore the dynamics by experimenting with the models. This is an active, fun way to learn. It definitely helped me to expand my systems thinking capability. Although my substantive interest is organizations, I learned a great deal by analogy from working through models of problems from other disciplines. Basic systems principles apply across disciplines, and useful insights can be gleaned from recognizing similar dynamic structures underlying different systems.
I particularly liked the instruction by example that is used throughout this book. I learned so much from this book because the reading and modeling, modeling and reading formed a positive feedback loop. The reading provided direction and engaged me in the modeling, and the modeling clarified and reinforced the concepts in the reading. Drawing from my experience with this book, I think it is ideal for those who are just getting started in dynamic modeling or have been learning for several years but want to sharpen and expand their systems thinking and modeling skills.

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The book uses STELLA software to develop simulation models, thus allowing readers to convert their understanding of a phenomenon to a computer model, and then run it to yield the inevitable dynamic consequences built into the structure. Part I provides an introduction to modeling dynamic systems, while Part II offers general modeling methods. Parts III through VIII then apply these methods to model real-world phenomena from chemistry, genetics, ecology, economics, and engineering. Dynamic Modeling includes STELLA run-time software for both Windows and Mac systems, as well as computer files of sample models used in the book. A clear, approachable introduction to the modeling process, of interest in any field where real problems can be illuminated by computer simulation.

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Introduction to Regression Modeling (with CD-ROM) (Duxbury Applied) Review

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(More customer reviews)This is an accessible and very well-written introductory book on linear regression that goes much deeper than most books written at its level. Compared with other similar books, it is much more thoughtful and critical. This is one of the few introductory books on regression that gets people to actually think about the material and does not set up bad habits or encourage people to proceed blindly.
The prerequisites for this book are modest. It does require some math skills, particularly, ability to manipulate summation notation effectively. Some parts of the book require linear algebra. The book has a short review of linear algebra, which is not enough to teach the subject on its own, but might be useful review for someone with prior exposure. A few sections are genuinely hard (such as the implementation of nonlinear regression) and require more math skills, but these are not central to the flow of the book and can be omitted. In terms of other background, some general life experience and familiarity with the social sciences or natural sciences would be helpful in order to appreciate the motivation behind and applications of the material.
This book offers a remarkably exhaustive a coverage of the conventional topics in regression. The choice and order of topics is natural. I particularly like the way the book includes chapters on model selection and model checking, and explores these issues in depth. These are issues that are often glossed over.
Perhaps the best aspect of this book is the interplay between mathematical theory and applications. The mathematical details are expanded in rich discussion which helps the reader to develop mathematical intuition, and these details are presented in ways that enrich the discussion of applications. This is one of the few books that presents both the mathematical and practical sides of the subject well and integrates them fully. It takes skill and thought to create a book as well-executed as this one, and I think the authors deserve credit for this!
This book would make an excellent textbook for a first course in regression. It would remain a useful reference for more advanced students. People looking for a more advanced book on the same subject might want to check out the book "Statistical Models" by Freedman, or the "Regression Analysis: A Constructive Critique" by Berk.
Lastly, I must mention, the price of this book is absurd! This book should be less than half the cost. It's not that long and it has the usual cheap glued binding of a textbook. At $122, the glued binding for this book should constitute a criminal offense.

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Using a data-driven approach, this book is an exciting blend of theory and interesting regression applications. Students learn the theory behind regression while actively applying it. Working with many case studies, projects, and exercises from areas such as engineering, business, social sciences, and the physical sciences, students discover the purpose of regression and learn how, when, and where regression models work. The book covers the analysis of observational data as well as of data that arise from designed experiments. Special emphasis is given to the difficulties when working with observational data, such as problems arising from multicollinearity and "messy" data situations that violate some of the usual regression assumptions. Throughout the text, students learn regression modeling by solving exercises that emphasize theoretical concepts, by analyzing real data sets, and by working on projects that require them to identify a problem of interest and collect data that are relevant to the problem's solution. The book goes beyond linear regression by covering nonlinear models, regression models with time series errors, and logistic and Poisson regression models.

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Detailing Scale Model Aircraft (Scale Modeling Handbook) Review

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(More customer reviews)Mr. Ashey seems to know what he's talking about. This book covers a wide range of topics centered around altering and adding detail to your models. Lots of techniques for begginers to advanced modelers with simple tips to create the effects you want. He sometimes uses tools that most of us don't have, and doesn't always explain their uses, (i.e. working w/ resin and superglue) but on the whole a Very informative book. I would suggest it for anyone who wants to get more out of their model than what comes in the box.

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Teaches how to create accurate and realistic scale aircraft from scratchbuilding to painting. Includes simple techniques for adding interior and exterior details, removing seams, applying decals, and weathering.

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