Simulation Books

Dr. Goel is a very talented engineer and professor and knows a lot about VLSI interconnections. He is the best teacher that I've ever had in college or earlier and has taught me a lot about VLSI design and the physics of semiconductors.

This book excellent for anyone interested in the complex and unique world of hybrid systems. Wolf Kohn is simply brilliant! Highly recommended. Many of the authors of this book are still pursuing careers in hybrid systems, most prominently with the Seattle-based company, Hynomics, which plans to go public soon.

This is probably one of the most realistic flight simulator games out there. This isn't one of those autmagic start games, and all you get to do is dog fight. you have to turn on your engines, set your radar screens, power up, take off, retract your gear, etc. Very involved game for the avid flight sim lover like myself, but not for the light hearted. Pilots love this game, I know a lot of hornet pilots that used this game to practice when they were in flight school, including my brother. Enjoy!!

This is absolute a bible book for any person who want to learn Gibbs sampler and simulated annealing seriously. The format of this book, though full of mathematical equations, is very self-evident and concise. Nothing is missing and nothing is redundent. It is an enjoyable journey to follow the logic and principle in this book, with all your attention in. There are full of in-depth discussion in all aspect of the Gibbs sampler, simulated annealing, from the visiting scheme to cooling schedule, and parallel algorithms. The references are excellent too. The author seems to have read all publications till 1995 about this topic and give an excellent detailed and in-depth survey in his book. At the end of your reading, you would have love the mathematical form the author used. Without these tools, many discussions in this book will be just impossible and groundless. I personally have read this book for several times.

The huge majority of bioinformatics (BI) books seem to treat the topic as an end in itself. I have to admit, there is a lot to enjoy in the algorithms people have developed and in clever implementations. Often, though, the calculations appear to be fine art, to enjoy in abstract, or for creating point solutions to isolated problems.

This book breaks the mold. It addresses every aspect of immunology, using BI as the tool and as the unifying language for discussing immunology's many aspects. The content gets off to a slow start, starting with two chapters describing the topic and its importance. The next three chapters summarize a few of the basic algorithms: alignment and multiple alignment, motif-finding, Gibbs sampling, clustering, and neural networks. The discussion is competent, and the authors' handling of neural nets stands out from the crowd of BI books. Still, the pace is too brisk and the range of topics is too narrow to recommend this book as a general BI text.

It's not one, and never meant to be. That section just reminds the knowledgable reader of the mathematical tools and BI terms to be used in the remaining nine chapters. Here's where an immunology background will help a lot. I know, because I lack one. Still, the discussion holds to a level that a determined reader with a general bio and BI background can follow. Even at my barely-following level, it's exciting stuff.

At this writing, the 2005 H5N1 bird flu is all over the front pages, so medical response to emerging viruses is on people's minds. This book explores the whole range of issues in immunological response to the threat: identifying specific viral features that stand out as vaccine targets, understanding the immunological mechanisms that need to be engaged, evolution of the pathogens to emerging human resistance, and the ways that human variation affects the decisions in medicine and public policy.

That last surprised me, but makes perfect sense. Different human populations have slightly different sets of alleles for immunological response. It's one of the reasons that humanity does so well in a world of ever-changing antigenic threats. As a species, we have so many possible responses to any challenge that someone somewhere is bound to be able to survive almost any pathogen around. The range of immune-response alleles, their different sensitivities and combinations, and their distributions in different gene pools helps decide how a vaccine must be crafted. If the vaccine antigen generally triggers a good response in African Americans but not East Asians, it answers only part of the question.

This is the first text I know that really shows BI at work in clinically important ways. It's a guided tour of the world of immunological attacks and responses, measured using BI tools - not just pathogens, but allergens, autoimmune triggers, and even possible cancer treatment. Beginners will have a rough time following the discussion, but this is a book for people deep in their specialty. It gave me a good idea of what questions are asked, and why, and how BI answers them. I look forward to seeing an immunological researcher's review of this text - from the pure BI stand point, it's narrow, but shows the versatility of the tools it chooses.

//wiredweird

In 1988, at Los Alamos, I was in a research group that did simulations of hair cells in the inner ear. These were then state of the art, and involved modelling the transport of various elements like potassium across the cell boundaries.

But computer hardware has improved enormously since then. Along with the understanding at the cellular level of many processes. So now, "in silico" simulations have become feasible for a wide range of biological systems. This book explores that range. From single cells to clusters/networks of cells, all the way up to entire organs.

At all these levels, different assumptions have to be made to render practical computational results. You can judge for yourself whether the assumptions are justified, and perhaps how future advances in hardware will let us relax these.

Rough sets analysis for imag

This book is written by the author who made RSPICE. In this book, he explains the inner workings of SPICE and what those strange spice parameters(such as ITL1, ITL2...)mean. I can say I understand and use SPICE much better because of this book. Highly recommendable!

This text, explore and discuss the geographic modeling and how it is used to improve planning by providing spatial information, and uses examples taken from real situations. The books offers a bief introduction about local decision and planning in organizations, it dicuss applications in retail planning, including a chapter that focuses on the automobile industry, health-care planning and analysis, urban and water-resource planning, and financial services. The book's uses range form regression techniques and choice models to spatial interaction models and market indicators, it may be useful to suplement a second or third level geography course to emphatize some real-word applications of geography theory. The bok is an extraordinary resourse and it is readable.

This book is recommended to people that already have some background in GIS and logic (Graduate students, faculty).Due to it is written using math terms (many greek simbols!) sometimes became dry. But,the book cover from the begining almost every aspect to create an Intelligent spatial decision support system from scratch. The author also give an example applied to raster GIS. NO softawe or CD is provided.