The heroic Dr. Ecco uncovers a fiendish plot in this collection of original puzzles inspired by research methods of computer science and mathematics. No sophisticated mathematical background necessary. Solutions.

"Out of Their Minds" profiles 15 of the planet's foremost computer scientists, including eight winners of the Turing Award, computing's Nobel Prize. Based on recent interviews, the scientists are revealed in fascinating anecdotes about their early inspirations and influences, contributions, and thoughts on the field's explosive future. "A fascinating collection of profiles and interviews with some of the men ... who brought us (to the computing age)"--"The New York Times". 56 illus.

Database tuning is the activity of making a database application run more quickly. Tuning is difficult because it requires global knowledge of an information system, from the hardware to the operating system to the query language to the application. This is the first book to deal with tuning object-oriented database systems in a serious way. Aiming to impart a broad knowledge of applications and of computer systems, the book's practical advice helps to decide whether to change the way to construct applications, the parameters of database systems, the configuration of operating systems, the resources that hardware offers, or perhaps even replace entire components to boost a database performance.

Statistics is the activity of inferring results about a population given a sample. Historically, statistics books assume an underlying distribution to the data (typically, the normal distribution) and derive results under that assumption. Unfortunately, in real life, one cannot normally be sure of the underlying distribution. For that reason, this book presents a distribution-independent approach to statistics based on a simple computational counting idea called resampling. This book explains the basic concepts of resampling, then systematically presents the standard statistical measures along with programs (in the language Python) to calculate them using resampling, and finally illustrates the use of the measures and programs in a case study. The text uses junior high school algebra and many examples to explain the concepts. The ideal reader has mastered at least elementary mathematics, likes to think procedurally, and is comfortable with computers. Table of Contents: The Basic Idea / Bias Corrected Confidence Intervals / Pragmatic Considerations When Using Resampling / Terminology / The Essential Stats / Case Study: New Mexico's 2004 Presidential Ballots / References

Join math detective in solving nearly 40 puzzles inspired by methods in computer science and mathematics. The Tower of Lego, Odd Doors Problem, Spies and Double Agents, many more. Solutions.

In the history of modern computation, large mechanical calculators preceded computers. A person would sit there punching keys according to a procedure and a number would eventually appear. Once calculators became fast enough, it became obvious that the critical path was the punching rather than the calculation itself. That is what made the stored program concept vital to further progress. Once the instructions were stored in the machine, the entire computation could run at the speed of the machine. This book shows how to do the same thing for DNA computing. Rather than asking a robot or a person to pour in specific strands at different times in order to cause a DNA computation to occur (by analogy to a person punching numbers and operations into a mechanical calculator), the DNA instructions are stored within the solution and guide the entire computation. We show how to store straight line programs, conditionals, loops, and a rudimentary form of subroutines. To achieve this goal, the book proposes a complete language for describing the intrinsic topology of DNA complexes and nanomachines, along with the dynamics of such a system. We then describe dynamic behavior using a set of basic transitions, which operate on a small neighborhood within a complex in a well-defined way. These transitions can be formalized as purely syntactical functions of the string representations. Building on that foundation, the book proposes a novel machine motif which constitutes an instruction stack, allowing for the clocked release of an arbitrary sequence of DNA instruction or data strands. The clock mechanism is built of special strands of DNA called "tick" and "tock." Each time a "tick" and "tock" enter a DNA solution, a strand is released from an instruction stack (by analogy to the way in which as a clock cycle in an electronic computer causes a new instruction to enter a processing unit). As long as there remain strands on the stack, the next cycle will release a new instruction strand. Regardless of the actual strand or component to be released at any particular clock step, the "tick" and "tock" fuel strands remain the same, thus shifting the burden of work away from the end user of a machine and easing operation. Pre-loaded stacks enable the concept of a stored program to be realized as a physical DNA mechanism. A conceptual example is given of such a stack operating a walker device. The stack allows for a user to operate such a clocked walker by means of simple repetition of adding two fuel types, in contrast to the previous mechanism of adding a unique fuel -- at least 12 different types of strands -- for each step of the mechanism. We demonstrate by a series of experiments conducted in Ned Seeman's lab that it is possible to "initialize" a clocked stored program DNA machine. We end the book with a discussion of the design features of a programming language for clocked DNA programming. There is a lot left to do. Table of Contents: Introduction / Notation / A Topological Description of DNA Computing / Machines and Motifs / Experiment: Storing Clocked Programs in DNA / A Clocked DNA Programming Language

Time-series data—data arriving in time order, or a data stream—can be found in fields such as physics, finance, music, networking, and medical instrumentation. Designing fast, scalable algorithms for analyzing single or multiple time series can lead to scientific discoveries, medical diagnoses, and perhaps profits. High Performance Discovery in Time Series presents rapid-discovery techniques for finding portions of time series with many events (i.e., gamma-ray scatterings) and finding closely related time series (i.e., highly correlated price and return histories, or musical melodies). A typical time-series technique may compute a "consensus" time series—from a collection of time series—to use regression analysis for predicting future time points. By contrast, this book aims at efficient discovery in time series, rather than prediction, and its novelty lies in its algorithmic contributions and its simple, practical algorithms and case studies. It presumes familiarity with only basic calculus and some linear algebra. Topics and Features: *Presents efficient algorithms for discovering unusual bursts of activity in large time-series databases * Describes the mathematics and algorithms for finding correlation relationships between thousands or millions of time series across fixed or moving windows *Demonstrates strong, relevant applications built on a solid scientific basis *Outlines how readers can adapt the techniques for their own needs and goals *Describes algorithms for query by humming, gamma-ray burst detection, pairs trading, and density detection *Offers self-contained descriptions of wavelets, fast Fourier transforms, and sketches as they apply to time-series analysis This new monograph provides a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams. It offers essential coverage of the topic for computer scientists, physicists, medical researchers, financial mathematicians, musicologists, and researchers and professionals who must analyze massive time series. In addition, it can serve as an ideal text/reference for graduate students in many data-rich disciplines.

"The voices we hear come from a diverse group of personalities who tell their stories with no holds barred. The reader is given views of the United States and Russia from a very unusual perspective: the candid words of strong people who have survived in both cultures."--BOOK JACKET.

The Fourth International Workshop on Database Programming Languages - Object Models and Languages (DBPL-4) took place in Manhattan, New York City, 30 August-1 September 1993. The areas of interest and the format of DBPL-4 focused on the integration of programming languages, object models, type systems and database systems. As in the previous DBPL workshops, the setting was informal, allowing the participants to actively discuss and argue about the ideas presented in the talks. The comments and remarks made by the participants during and after the presentations were taken into account in the preparation of the final versions of the papers. The result, we believe, is a set of excellent papers. The DBPL sequence is closely related to the sequence of International Workshops on Persistent Object Systems (POS), first started in 1985. While the DBPL workshops focus on language and model issues, the POS workshops have focused on implementation issues; thus the two sequences complement each other. Many researchers participate in both workshop series. The eight sessions of the technical program of DBPL-4 were as follows: 1. Bulk types and their query languages (two sessions). 2. Object models and languages. 3. Data types with order. 4. Mechanisms to support persistence, reflection, and extensibility. 5. Query optimization and integrity constraints. 6. Logic-based models. 7. Implementation and performance issues.

Imagine being able to ask Newton about falling apples or Euclid about his personal vision of geometry. In Out of their Minds, readers will hear the Newtons and Euclids of the computer age as they talk about their discoveries in information technology that have changed forever the way we live, work, and think about the world. Out of their Minds introduces readers to fifteen of the planet's foremost computer scientists, including eight winners of the Turing Award, computing's Nobel Prize. The scientists reveal themselves in fascinating anecdotes about their early inspirations and influences, their contributions to computer science, and their thoughts on its explosive future.