Computer Science Books

In Half-Real, Jesper Juul presents us a not only a new definition for games (computer-based or not), but also an original perspective on videogames and how they operate. Going beyond the 'Ludology x Narratology' discussion, Juul balances the 'Rules' and 'Fiction' elements of video games, emphasizing how they relate to each other.

The book is very insightful, containing information that will be valuable to game designers, academics, gamers and new media enthusiasts. Although you could find some of the its content on Juul's previous articles available on the internet, they are much more complete polished in Haf-Real.

Very good book on the theory of videogames. Accessible, innovative, thoughtful, and centered on concrete (and popular) examples. He also includes lots of screenshots, which is good.

Juul takes what might be called a "grassroots" approach to game studies, not bringing heavy disciplinary baggage to colonize the area, but instead trying to build a formal theory of games from the ground up. He takes his lead primarily from game and culture theorists like Huizinga, Caillois, Crawford and Sutton-Smith rather than from literary theory or media studies. But he really charts his own course and stakes out his own ground in many ways.

He has a strong interest in game rules, which has led some to criticize him for being overly formalistic, but I find this a refreshing and interesting contrast to the more standard "new media" approach to video games.

Computational is a new and rapidly changing field as new research and techniques are being developed on an almost daily basis. It is to the credit of the author and publisher that they have been able to put together such a complete and well organized handbook this early.

Clearly this field is not ready for a standard text to have been developed, indeed it is clearly too much for even one writer. Instead, the editor calls this 'truly a community effort, with the chapters authored by leading researchers widely recognized for their research contributions and expertise.'

In all there are 38 specific chapters organized into eight major parts. The parts are: Sequence Alignments, String Data Strctures, Genome Assembly and EST Clustering, Genome-Scale Computational Methods, Microarrays and Gene Expression Analysis, Computatinal Structural biology, Bioinformatic Databases and Data Mining. The authors represent a who's who of the major American research establishments as well as from Germany, Italy, Russia, Canada, Japan, Isreal, and India.

The book could be used as a text but is probably more useful to the researcher looking for either an introduction to the field in general or go learn about areas outside his particular area of expertise.

Bioinformatics is too big a field to cover in one book, but this thousand-pager comes close. Its 38 chapters give good summaries of just about every major topic in bioinformatics. Since the table of contents isn't visible here (as of this writing), I'll list the major headings into which the chapters are divided:
* Sequence alignments
* String data structures
* Genome assmebly and EST clustering
* Genome-scale computational methods
* Phylogenetics
* Microarrays and expression analysis
* Computational structural biology
* Bioinformatic databases and data mining

A few things are missing, such as RNA structure prediction and mass spec analysis of proteins. Regulatory networks get only brief mention, perhaps because the topic is still too researchy for any body of accepted practice. These are quibbles, though. The book does a very good job of providing brief surveys of many topics, with an extensive bibliography at the end of each chapter.

This doesn't replace other books that examine specific topics in greater depth. Instead, it provides quick surveys of many topics, and lots of pointers for further information. For the subjects it covers, it's a great starting point.

//wiredweird

I bought this book as a supplement to my course of discrete mathematics.

With the combination of a study book and this book, you can smoothly learn discrete mathematics.

At the university I am attending Johnsonbaugh's book was a required text for a subject introducing discrete mathematics. Unfortunately, like many others it seems, I was less than impressed with the books ability 'teach', or even reinforce what we had just studied in lectures. I went looking for another book, not so much as a replacement for Johnsonbaugh's book, but as an additional reference/study aid.

Since owning this book I've found myself turning to it for explanations and examples over the required text. Almost every section lists definitions of terms, a bunch of useful facts and fully worked examples. Explanations and examples are clear and concise, while the facts often help to understand the process involved before getting into the examples.

I'd like to stress that this is certainly no replacement for a text book in discrete/combinatorial mathematics, however it is marvelous to have by your side to provide additional help through problem areas.

This book will occupy a prime spot on my bookshelf. I've had to use a bunch of different books to find this kind of information before. It's nice to see such a wide range of topics from discrete math covered so thoroughly.

I have a small library on printing and printing technologies. This book is the best single book I own. It's the best single source on printing I've seen, as well. The subject is laid out logically; the theory is provided to allow understanding; the graphics are clear and informative, and frequently provided; the writing style is clear, although a bit "Germanic" in thought-processes, resulting from the translation I assume.
I recommend this book to any printing professional seeking to learn about their field, or to any student of the industry. Just don't drop it on your toes.

Just ordered my english version of this, already having the german language version. The book is top-notch, very clearly explaining and illustrating, both with drawings and photos, the various components and materials used for all types of printing. Its breadth and depth make it a vital reference for anyone involved in the graphic arts industries.

When it comes to working with statistics, R is a great tool to have at your disposal. Sadly, there is a shortage of information that closes the gap between the simplistic examples used to learn data analysis with R and the more complicated techniques necessary to use R when working with more complex data sets.

_A Handbook of Statistical Analyses Using R_ sits nicely between the traditional introductory tomes for R (Introductory Statistics with R by Peter Dalgaard, or Statistics: An Introduction using R by Michael J. Crawley being two of the best) and the more advanced single topic texts which have a tendency to focus on one particular modeling technique.

As a workbook, the examples are short enough to be worked through in anywhere from 30 minutes to two hours. And while they often assume that the reader is familiar with certain aspects of statistical analysis, a quick refresher is provided for most topics before the exercises.

As a quick reference used to give examples of how to analyze different types of data, the book stands out for having a diverse set of worked examples that give a great jump start into working with R if you need a sample to get going.

If you work with R long enough, you'll find that you need a variety of reference sources to draw upon. _A Handbook of Statistical Analyses Using R_ is a solid addition to that reference library.

Brian Everett has previously written similar handbooks for SAS and SPlus. As R is becoming the language of choice in statistical computing in research particularly academoc research this book is a welcome addition. This book is actually a great booj on statistical methods and covers most of the important modern advances including ANOVA, linear regression, generalized linear models with emphasis on logistic regression, probability density estimation (nonparametric), recursive partitioning (i.e. classification and regression trees), survival analysis, bootstrap methods, longitudinal data analysis including mixed effect linear models and generalized estimating equations, meta analyses, principal component analysis, multidimensional scaling and cluster analysis, In each case the methods are clearly explained, are illustrated using real data for examples using R code that is listed for the student to replicate. results are presented through computer output and graphs. This is a very diverse set of methods covering many topics and expecially those commonly needed in clinical trials. the book also contains a very useful bibliography. unfortunately Bayesian techniques are sorely missing with the only reference to Bayes being Schwarz's Bayesian Information Criterion (BIC) that is used for model comparisons.

This book helps open up sensible techniques thst can be applied to a wide variety of problems that the applied researcher might need. The only major technique that is missing here are the Bayesian hierarchical models that have been used extensively in the medical device arm of the FDA (CDRH) are not covered in this fine text.

My orginal DR guide was lost in a basement flood, I was looking for a replacement for my desk libary at work. There was some math (statistics)on availablity / reliablity that was a little hard to follow - my college math is quite rusty, but it was nicly summerized in a graph format, so I could follow it. The network and data center sections are very well done.

This is my first book about this matter. Although I have some experience implementing solution with HA/DR requirements, this book was very clarifier. Topics are conceptually clear and also this proposes a good methodology to face HA/DR requirements.

You will get some technical details about components that allow implement HA/DR, however it is not in deep. Don't think you will get a comercial product review. This is not the target.

It is a very good book.

I was just beginning to read about Irish history, and was looking for a good book to start with, when I saw someone buying this handy little introduction. I promptly bought & read it myself, and wasn't in the least disappointed. I finished the book in a day, and yet, when I was done, I knew 10 times more about the subject than I had previously, enough to completely revise what I thought were my opinions.

This is a concise, well-written, and readable summary of the general course of Irish history. It's not quite "in-depth," but it's too thorough to be dismissed as a rough outline or anything similar. It's a sound elementary primer on a complex subject, and the perfect starting point for further, more detailed learning.

A REALLY GOOD BOOK TO GET THE GENERAL HISTORY OF IRELAND FROM A MORE OR LESS IMPARTIAL SOURCE. PROVIDES A VERY GOOD UNDERSTANDING OF THE SHAPING OF IRELAND'S PAST AND HOW IT INFLUENCES THE PRESENT.

This book is an excellent resource on understanding the key concepts of wireless LAN and wireless ATM. About 80% of the book focuses on wireless LAN. I am from a non-wireless field but this book brings out the salient features of wireless networks in a very succinct and insightful manner. Understanding these concepts allow one to grapple with emerging wireless LAN technologies, which is currently evolving very quickly. It was no surprise that an abridged version of the book was distributed with Cisco wireless LAN products. To me, the book is written with the right depth. If you enjoy reading magazines such as IEEE Spectrum and Technology Review, this is the book for you.

An up-to-date book on wireless LANs and wireless ATM. Information is presented in a clear and precise way.

Hilbert's 10th problem was solved, as well explicated in this book, but many of the ramifications of this solution were very unexpected and almost surprising beyond belief!

This book is not easy, but it is also not hard in the way if many advanced mathematical texts. The authors have done a great service by presenting proofs well within the range of non-experts with a general college level of mathematical sophistication. They are truly to be congratulated for this unique and priceless contribution to mathematical literature. No one had any idea of the rich results that would ensue on the solution to this seemingly simple to state problem, and the not so surprising result that the answer was in the negative. If you like mathematics, you will find many delightful and surprising results presented here in a way very comprehensible to those willing to work through these proofs designed for the most general audience possible.

Yuri V. Matiyasevich's "Hilbert's Tenth Problem" has two parts. "The first part, consisting of Chapters 1-5, presents the solution of Hilbert's Tenth Problem." The second part (Chapters 6-10) is "devoted to application."

Hilbert's Tenth Problem is about the "determination of the solvability of a Diophantine equation." To be specific, the problem asked for "devise a process ... which ... can ... [determine in] a finite number of operations whether the equation is solvable in ... integers." David Hilbert posted the problem in 1900. "Today ... the words `devise a process' ... mean `find an algorithm.' When Hilbert's Problem was posed, there was no ... rigorous ... notion of algorithm ... [Until 1930s] Kurt Godel, Alonzo Church, Alan Turing, and other logicians provided a rigorous formulation ... of computability; [then] ... it [is] possible to establish algorithmic insolvability ... "

The problem was considered solved by Yuri Matiyasevich in 1970. In short, Matiyasevich proved the Martin Davis's conjecture. The readers will find Matiyasevich's "Hilbert's Tenth Problem: What can we do with Diophantine equations?" helpful. Martin Davis's conjecture states that a set is Diophantine if and only if it is list-able. There is a classical result in the computability theory: there exists an un-decidable list-able set. The un-decidability of the set implies that there is no algorithm to determine [the] values of the parameters [of] the Diophantine representation [so that the representation] has a solution.

On the other hand, the material on the book is more technical. "... we can reformulate Hilbert's Tenth Problem in the following ... way: is the set of codes of all solvable Diophantine equations ... Turing decidable? ... the complement of [the set of codes] is not Diophantine. This implies that [the set] is not Turing decidable. In other words, it is impossible to construct a Turing machine that ... will halt after a finite number of steps in state q2 [yes] or q3 [no], depending on whether the equation ... is or is not solvable."

In terms of application, "we can construct a Diophantine equation whose un-solvability is equivalent to the Riemann Hypothesis." Similar utilization can be applied to number theory, calculus, and game theory problems. But we have no obvious way to restate the twin prime conjecture ... as the problem of the solvability or un-solvability of a particular Diophantine equation."

Well written and clear material.
As a researcher in dynamical systems, I found this book a very interesting introduction to neural nets.
Would like to see the section on genetic programming fleshed out even further.

DESEAMOS OBTENER MAS INFORMACION SOBRE EL TEMA, SOMOS UNA INSTITUCION EDUCATIVA ESPECIALIZADA EN EL CAMPO DE LA CRIMINALISTICA.

AGRADECEMOS LA COLABORACION PRESTADA, SI ES POSIBLE NOS GUSTARIA UN DEMO.