The following is a list of titles to appear in Collection I of the new ACM Books series. Upon publication, each of the following books will appear in the ACM Digital Library and be accessible to those with full-text access to Collection I in both PDF and ePub formats. Individual titles will be made available for purchase via Amazon and Barnes & Noble. Please click on the title name below for more information about each title.
Structural bioinformatics is the field related to the development and application of computational models for the prediction and analysis of macromolecular structures. The unique nature of protein and nucleotide structures has presented many computational challenges over the last three decades. The fast accumulation of data, in addition to the rapid increase in computational power, presents a unique set of challenges and opportunities in the analysis, comparison, modeling, and prediction of macromolecular structures and interactions.
The book is intended as a user's guide for key algorithms to solve problems related to macromolecular structure, with emphasis on protein structure, function and dynamics. It can be used as a textbook for a one-semester graduate course in algorithms in bioinformatics.
Cryptography to me is the “black magic,” of cryptographers, enabling tasks that often seem paradoxical or simply just impossible. Like the space explorers, we cryptographers often wonder, “what are the boundaries of this world of “black magic?” This work lays one of the founding stones in furthering our understanding of these edges.
We describe plausible lattice-based constructions with properties that approximate the sought after multilinear maps in hard-discrete-logarithm groups. The security of our constructions relies on seemingly hard problems in ideal lattices, which can be viewed as extensions of the assumed hardness of the NTRU function. These new constructions radically enhance our tool set and open a floodgate of applications. We present a survey of these applications.
This book is based on my PhD thesis which was an extended version of a paper titled
“Candidate Multilinear Maps from Ideal Lattices” co-authored with Craig Gentry and Shai
Halevi. This paper was originally published at EUROCRYPT 2013.
Virtual reality (VR) potentially provides our minds with direct access to digital media in a way that at first seems to have no limits.However, creating compelling VR experiences is an incredibly complex challenge.When VR is done well, the results are brilliant and pleasurable experiences that go beyond what we can do in the real world.When VR is done badly, not only is the system frustrating to use, but sickness can.Reasons for bad VR are numerous; some failures come from the limitations of technology, but many come from a lack of understanding perception, interaction, design principles, and real users. This book discusses such issues, focusing upon the human element of VR rather than technical implementation, for if we do not get the human element correct, then no amount of technology will make VR anything more than an interesting tool confined to research laboratories.Even when VR principals are fully understood, first implementations are rarely novel and never ideal due to the complex nature of VR and the countless possibilities.However, the VR principals discussed within enable us to intelligently experiment with the rules and iteratively design towards innovative experiences.
Chapter 1. Introduction
Chapter 2. Perception
Chapter 3. Cybersickness
Chapter 4. Interaction
Chapter 5. Content Creation
Chapter 6. Iterative Design
Chapter 7. Conclusions and the Future
Software history has a deep impact on current software designers, computer scientists and technologists. Decisions and design constraints made in past are often unknown or poorly understood by current students, yet modern software systems use software based on those earlier decisions and design constraints. This work looks at software history through specific software areas and extracts student-consumable practices, learnings, and trends that are useful in current and future software design. It also exposes key areas that are highly used in modern software, yet no longer taught in most computing programs. Written as a textbook, this book uses past and current specific cases to explore the impact of specific software evolution trends and impacts.
Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. This has led to an increasing demand for powerful software tools to help people analyze and manage vast amounts of text data effectively and efficiently. Unlike data generated by a computer system or sensors, text data are usually generated directly by humans, and are accompanied by semantically rich content.As such, text data are especially valuable for discovering knowledge about human opinions and preferences, in addition to many other kinds of knowledge that we encode in text. In contrast to structured data, which conform to well-defined schemas (thus are relatively easy for computers to handle), text has less explicit structure, requiring computer processing toward understanding of the content encoded in text.The current technology of natural language processing has not yet reached a point to enable a computer to precisely understand natural language text, but a wide range of statistical and heuristic approaches to analysis and management of text data have been developed over the past few decades. They are usually very robust and can be applied to analyze and manage text data in any natural language, and about any topic.
This book provides a systematic introduction to all these approaches, with an emphasis on covering the most useful knowledge and skills required to build a variety of practically useful text information systems. The focus is on text mining applications that can help users analyze patterns in text data to extract and reveal useful knowledge. Information retrieval systems, including search engines and recommender systems, are also covered as supporting technology for text mining applications. The book covers the major concepts, techniques, and ideas in text data mining and information retrieval from a practical viewpoint, and includes many hands-on exercises designed with a companion software toolkit (i.e., MeTA) to help readers learn how to apply techniques of text mining and information retrieval to real-world text data and how to experiment with and improve some of the algorithms for interesting application tasks.The book can be used as a textbook for a computer science undergraduate course or a reference book for practitioners working on relevant problems in analyzing and managing text data
Verified Functional Programming in Agda introduces Computer Science students and interested practitioners to a new way of programming, using the Agda functional programming language. In Agda, one write pure functional programs (no side effects) in an elegant style using recursive equations and user-defined mixfix syntax. But unlike in mainstream programming languages, one can then write proofs of properties of these programs, using the programming language itself as a proof language. This gives programmers the power to establish, using computer-checked mathematical arguments, that their functional programs are correct.
