Download Free A T R U E Book in PDF and EPUB Free Download. You can read online A T R U E and write the review.

This book constitutes the refereed proceedings of the 11th International Conference on Computer Aided Verification, CAV'99, held in Trento, Italy in July 1999 as part of FLoC'99. The 34 revised full papers presented were carefully reviewed and selected from a total of 107 submissions. Also included are six invited contributions and five tool presentations. The book is organized in topical sections on processor verification, protocol verification and testing, infinite state spaces, theory of verification, linear temporal logic, modeling of systems, symbolic model checking, theorem proving, automata-theoretic methods, and abstraction.
Cosmic rays consist of elementary particles with enormous energy which originate from outside our solar system and constantly hit the Earth’s atmosphere. Where do these cosmic rays originate? How does nature accelerate the cosmic-ray particles to energies with orders of magnitude beyond the limits of manmade particle accelerators? What can we learn by measuring the interactions of the cosmic rays with the atmosphere? Digital radio-antenna arrays offer a promising, complementary measurement method for high-energy cosmic rays. This thesis reports on substantial advances in the development of the radio technique, which will be used to address these questions in future experiments.
A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
This book is a work of fiction centered about the capture of a high ranking U.S Air Force officer by the FARC. I hope the story line helps bring to the forefront of the American conscience the plight of Marc, Keith and Tom.
This book constitutes the proceedings of the 14th International Conference on Web Information Systems Engineering, WISE 2013, held in Nanjing, China, in October 2013. The 48 full papers, 29 short papers, and 10 demo and 5 challenge papers, presented in the two-volume proceedings LNCS 8180 and 8181, were carefully reviewed and selected from 198 submissions. They are organized in topical sections named: Web mining; Web recommendation; Web services; data engineering and database; semi-structured data and modeling; Web data integration and hidden Web; challenge; social Web; information extraction and multilingual management; networks, graphs and Web-based business processes; event processing, Web monitoring and management; and innovative techniques and creations.
A comprehensive introduction to strain-based structural health monitoring of civil structures, with focus on measurement and data analysis Introduction to Strain-Based Structural Health Monitoring of Civil Structures focuses on the SHM of civil structures and infrastructure, and develops the relevant topics of measurement and data analysis from a fundamental to advanced level. The book contains an overview of the available and emerging strain monitoring technologies like traditional strain-gauges and vibrating wire sensors, discrete and distributed fiber optic sensors, and large area electronics. The fundamentals of error analysis, as well as typical sources of errors in measurements, are discussed. Sources of strain in typical construction materials such concrete, steel, timber, and composite materials are also discussed, while both basic and advanced data interpretation and analysis for monitoring of concrete and steel structures are presented in detail. Methods applicable to a large spectrum of beam-like structural elements and civil structures, such as bridges, buildings, and pipelines, are summarized. These methods are developed at three scales: local scale (material or structural), global (structural) scale, and integrity scale, and are illustrated with practical examples. Key features: Defines and describes SHM and identifies its main components and stakeholders. Explores the potential and benefits as well as the limitations of SHM. Introduces strain-based structural health monitoring of civil structures, with focus on measurement and data analysis. Covers the physical principles, advantages, and limitations of various types of sensors. Covers fundamental error analysis and presents typical sources of errors. Covers the sources of short- and long-term strain, and how to interpret the strain measurement. Includes basic and advanced model-based methods for data analysis. Contains the basic strain-based SHM methods for monitoring various types of structures at local, global, and integrity scale. Suitable as a guide for practicing engineers, a reference for infrastructure owners, and a textbook for researchers and SHM university courses. A valuable companion to Glisic & Inaudi’s Fibre Optic Methods for Structural Health Monitoring. Introduction to Strain-Based Structural Health Monitoring of Civil Structures is essential, state-of-the-art reading for civil and structural engineers and professionals in SHM, as well as teachers, researchers, and students in civil engineering.
The book reports on the latest advances and challenges of soft computing. It gathers original scientific contributions written by top scientists in the field and covering theories, methods and applications in a number of research areas related to soft-computing, such as decision-making, probabilistic reasoning, image processing, control, neural networks and data analysis.
This two-volume set, LNAI 9077 + 9078, constitutes the refereed proceedings of the 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2015, held in Ho Chi Minh City, Vietnam, in May 2015. The proceedings contain 117 paper carefully reviewed and selected from 405 submissions. They have been organized in topical sections named: social networks and social media; classification; machine learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; outlier and anomaly detection; mining uncertain and imprecise data; mining temporal and spatial data; feature extraction and selection; mining heterogeneous, high-dimensional, and sequential data; entity resolution and topic-modeling; itemset and high-performance data mining; and recommendations.
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer. Features: Describes the connection between causal analysis and statistical inference Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichment, incorporating historical data, and confirmatory treatment comparison, illustrated by real-world applications Presents adaptive methods for clustering similar patient subgroups to improve efficiency Describes Bayesian nonparametric regression analyses of real-world datasets from oncology Provides pointers to software for implementation Bayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who desire to apply modern Bayesian methods to their own clinical trials and data analyses. It also might be used to teach a special topics course on precision medicine using a Bayesian approach to postgraduate biostatistics students. The main goal of the book is to show how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.