The open access two-volume set LNCS 12224 and 12225 constitutes the refereed proceedings of the 32st International Conference on Computer Aided Verification, CAV 2020, held in Los Angeles, CA, USA, in July 2020.*
The 43 full papers presented together with 18 tool papers and 4 case studies, were carefully reviewed and selected from 240 submissions. The papers were organized in the following topical sections:
Part I: AI verification; blockchain and Security; Concurrency; hardware verification and decision procedures; and hybrid and dynamic systems.
Part II: model checking; software verification; stochastic systems; and synthesis.
*The conference was held virtually due to the COVID-19 pandemic.
This book focuses on the discrete Fourier transform (DFT), discrete convolution, and, particularly, the fast algorithms to calculate them. These topics have been at the center of digital signal processing since its beginning, and new results in hardware, theory and applications continue to keep them important and exciting.
As far as we can tell, Gauss was the first to propose the techniques that we now call the fast Fourier transform (FFT) for calculating the coefficients in a trigonometric expansion of an asteroid's orbit in 1805. However, it was the seminal paper by Cooley and Tukey in 1965 that caught the attention of the science and engineering community and, in a way, founded the discipline of digital signal processing (DSP).
The impact of the Cooley-Tukey FFT was enormous. Problems could be solved quickly that were not even considered a few years earlier. A flurry of research expanded the theory and developed excellent practical programs as well as opening new applications. In 1976, Winograd published a short paper that set a second flurry of research in motion. This was another type of algorithm that expanded the data lengths that could be transformed efficiently and reduced the number of multiplications required. The ground work for this algorithm had be set earlier by Good and by Rader. In 1997 Frigo and Johnson developed a program they called the FFTW (fastest Fourier transform in the west) which is a composite of many of ideas in other algorithms as well as new results to give a robust, very fast system for general data lengths on a variety of computer and DSP architectures. This work won the 1999 Wilkinson Prize for Numerical Software.
It is hard to overemphasis the importance of the DFT, convolution, and fast algorithms. With a history that goes back to Gauss and a compilation of references on these topics that in 1995 resulted in over 2400 entries, the FFT may be the most important numerical algorithm in science, engineering, and applied mathematics. New theoretical results still are appearing, advances in computers and hardware continually restate the basic questions, and new applications open new areas for research. It is hoped that this book will provide the background, references, programs and incentive to encourage further research and results in this area as well as provide tools for practical applications.
Studying the FFT is not only valuable in understanding a powerful tool, it is also a prototype or example of how algorithms can be made efficient and how a theory can be developed to define optimality. The history of this development also gives insight into the process of research where timing and serendipity play interesting roles.
Several chapters or sections are written by authors who have extensive experience and depth working on the particular topics. Ivan Selesnick had written several papers on the design of short FFTs to be used in the prime factor algorithm (PFA) FFT and on automatic design of these short FFTs. Markus Püschel has developed a theoretical framework for “Algebraic Signal Processing" which allows a structured generation of FFT programs and a system called “Spiral" for automatically generating algorithms specifically for an architicture. Steven Johnson along with his colleague Matteo Frigo created, developed, and now maintains the powerful FFTW system: the Fastest Fourier Transform in the West. I sincerely thank these authors for their significant contributions.
The international conference on Intelligent Human Computer Interaction (IHCI) is a forum for the presentation of research results and technological advances at the crossroads of human-computer interaction, artificial intelligence, signal processing, and computer vision. It brings together engineers and scientists from around the world focussing on theoretical, practical, and applicational aspects of the field. The 9th event, IHCI 2017, took place during December 11th–13th, 2017 in Evry, France. The present proceedings consist of papers presented at the conference. The call for papers attracted 25 submissions from around the world, which have been reviewed by at least two and up to four members of the International Program Committee. Fifteen oral communications have been selected, the authors of which come from ten countries and four continents. The summary of one of the invited talks is also included. We thank all the invited speakers, authors, and members of the Program Committee for their contribution in making IHCI 2017 a stimulating and productive conference.
The international conference on Intelligent Human Computer Interaction (IHCI) is a forum for the presentation of research results and technological advances at the crossroads of human-computer interaction, artificial intelligence, signal processing, and computer vision. It brings together engineers and scientists from around the world focussing on theoretical, practical, and applicational aspects of the field. The 9th event, IHCI 2017, took place during December 11th–13th, 2017 in Evry, France. The present proceedings consist of papers presented at the conference. The call for papers attracted 25 submissions from around the world, which have been reviewed by at least two and up to four members of the International Program Committee. Fifteen oral communications have been selected, the authors of which come from ten countries and four continents. The summary of one of the invited talks is also included. We thank all the invited speakers, authors, and members of the Program Committee for their contribution in making IHCI 2017 a stimulating and productive conference.
In diesem Open-Access-Tagungsband sind die besten Beiträge des 9. Jahreskolloquiums "Kommunikation in der Automation" (KommA 2018) und des 6. Jahreskolloquiums "Bildverarbeitung in der Automation" (BVAu 2018) enthalten. Die Kolloquien fanden am 20. und 21. November 2018 in der SmartFactoryOWL, einer gemeinsamen Einrichtung des Fraunhofer IOSB-INA und der Technischen Hochschule Ostwestfalen-Lippe statt.Die vorgestellten neuesten Forschungsergebnisse auf den Gebieten der industriellen Kommunikationstechnik und Bildverarbeitung erweitern den aktuellen Stand der Forschung und Technik. Die in den Beiträgen enthaltenen anschaulichen Beispiele aus dem Bereich der Automation setzen die Ergebnisse in den direkten Anwendungsbezug.
Die Herausgeber
Prof. Dr. Jürgen Jasperneite leitet das Fraunhofer IOSB-INA und ist Vorstand im Institut für industrielle Informationstechnik (inIT) der Technischen Hochschule Ostwestfalen-Lippe (TH-OWL). An der TH-OWL vertritt er das Fachgebiet Computernetzwerke mit einem Fokus auf die industrielle Kommunikation. Sein Forschungsinteresse liegt im Bereich der intelligenten Automation und Vernetzung für cyber-physische Systeme (CPS).Prof. Dr. Volker Lohweg leitet das Institut für industrielle Informationstechnik und vertritt das Fachgebiet Diskrete Systeme mit der AG Bildverarbeitung und Mustererkennung und Sensor- und Informationsfusion in Forschung und Lehre. Seine Forschungsschwerpunkte liegen in den Bereichen Technische Kognitive Systeme mit dem Fokus auf industrieller Echtzeit-Bildverarbeitung und Mustererkennung sowie Sensor- und Informationsfusion für die Anwendungsbereiche Dokumentensicherheit und Automation.
This book, written with support from the National Institute for Biomedical Imaging and Bioengineering through grant R01 EB017205-01A1, is meant to serve as an illustrative guide for scientists, engineers, and clinicians that are interested in performing retrospective research using data from EHRs. It is divided into three major parts. The first part of the book paints the current landscape and describes the body of knowledge that dictates clinical practice guidelines, including the limitations and the challenges. This sets the stage for presenting the motivation behind the secondary analysis of EHR data. The part also describes the data landscape, who the key players are, and which types of databases are useful for which kinds of questions. Finally, the part outlines the political, regulatory and technical challenges faced by clinical informaticians, and provides suggestions on how to navigate through these challenges. In the second part, the process of parsing a clinical question into a study design and methodology is broken down into five steps. The first step explains how to formulate the right research question, and bring together the appropriate team. The second step outlines strategies for identifying, extracting, Oxford, and preprocessing EHR data to comprehend and address the research question of interest. The third step presents techniques in exploratory analysis and data visualization. In the fourth step, a detailed guide on how to choose the type of analysis that best answers the research question is provided. Finally, the fifth and final step illustrates how to validate results, using cross validation, sensitivity analyses, testing of falsification hypotheses, and other common techniques in the field. The third, and final part of the book, provides a comprehensive collection of case studies. These case studies highlight various aspects of the research pipeline presented in the second part of the book, and help ground the reader in real world data analyses. We have written the book so that a reader at different levels may easily start at different parts. For the novice researcher, the book should be read from start to finish. For individuals who are already acquainted with the challenges of clinical informatics, but would like guidance on how to most effectively perform the analysis, the book should be read from the second part onward. Finally, the part on case studies provides project-specific practical considerations on study design and methodology and is recommended for all readers.
This book, written with support from the National Institute for Biomedical Imaging and Bioengineering through grant R01 EB017205-01A1, is meant to serve as an illustrative guide for scientists, engineers, and clinicians that are interested in performing retrospective research using data from EHRs. It is divided into three major parts. The first part of the book paints the current landscape and describes the body of knowledge that dictates clinical practice guidelines, including the limitations and the challenges. This sets the stage for presenting the motivation behind the secondary analysis of EHR data. The part also describes the data landscape, who the key players are, and which types of databases are useful for which kinds of questions. Finally, the part outlines the political, regulatory and technical challenges faced by clinical informaticians, and provides suggestions on how to navigate through these challenges. In the second part, the process of parsing a clinical question into a study design and methodology is broken down into five steps. The first step explains how to formulate the right research question, and bring together the appropriate team. The second step outlines strategies for identifying, extracting, Oxford, and preprocessing EHR data to comprehend and address the research question of interest. The third step presents techniques in exploratory analysis and data visualization. In the fourth step, a detailed guide on how to choose the type of analysis that best answers the research question is provided. Finally, the fifth and final step illustrates how to validate results, using cross validation, sensitivity analyses, testing of falsification hypotheses, and other common techniques in the field. The third, and final part of the book, provides a comprehensive collection of case studies. These case studies highlight various aspects of the research pipeline presented in the second part of the book, and help ground the reader in real world data analyses. We have written the book so that a reader at different levels may easily start at different parts. For the novice researcher, the book should be read from start to finish. For individuals who are already acquainted with the challenges of clinical informatics, but would like guidance on how to most effectively perform the analysis, the book should be read from the second part onward. Finally, the part on case studies provides project-specific practical considerations on study design and methodology and is recommended for all readers.
This book, written with support from the National Institute for Biomedical Imaging and Bioengineering through grant R01 EB017205-01A1, is meant to serve as an illustrative guide for scientists, engineers, and clinicians that are interested in performing retrospective research using data from EHRs. It is divided into three major parts. The first part of the book paints the current landscape and describes the body of knowledge that dictates clinical practice guidelines, including the limitations and the challenges. This sets the stage for presenting the motivation behind the secondary analysis of EHR data. The part also describes the data landscape, who the key players are, and which types of databases are useful for which kinds of questions. Finally, the part outlines the political, regulatory and technical challenges faced by clinical informaticians, and provides suggestions on how to navigate through these challenges. In the second part, the process of parsing a clinical question into a study design and methodology is broken down into five steps. The first step explains how to formulate the right research question, and bring together the appropriate team. The second step outlines strategies for identifying, extracting, Oxford, and preprocessing EHR data to comprehend and address the research question of interest. The third step presents techniques in exploratory analysis and data visualization. In the fourth step, a detailed guide on how to choose the type of analysis that best answers the research question is provided. Finally, the fifth and final step illustrates how to validate results, using cross validation, sensitivity analyses, testing of falsification hypotheses, and other common techniques in the field. The third, and final part of the book, provides a comprehensive collection of case studies. These case studies highlight various aspects of the research pipeline presented in the second part of the book, and help ground the reader in real world data analyses. We have written the book so that a reader at different levels may easily start at different parts. For the novice researcher, the book should be read from start to finish. For individuals who are already acquainted with the challenges of clinical informatics, but would like guidance on how to most effectively perform the analysis, the book should be read from the second part onward. Finally, the part on case studies provides project-specific practical considerations on study design and methodology and is recommended for all readers.
This open access book constitutes the refereed proceedings of the 6th Asian Supercomputing Conference, SCFA 2020, which was planned to be held in February 2020, but unfortunately, the physical conference was cancelled due to the COVID-19 pandemic.
The 8 full papers presented in this book were carefully reviewed and selected from 22 submissions. They cover a range of topics including file systems, memory hierarchy, HPC cloud platform, container image configuration workflow, large-scale applications, and scheduling.