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Natural language processing with Python and spaCy: a practical introduction
Vasiliev Y., No Starch Press, San Francisco, CA, 2020. 192 pp. Type: Book (978-1-718500-52-5)
Having had three Amazon Alexa units in my house for years, I’ve always wondered how my utterances are interpreted and understood by a machine, and how a machine talks back to me and carries out my commands without error (almost!). This book ...
Secure and effective implementation of an IOTA light node using STM32
Stucchi D., Susella R., Fragneto P., Rossi B. BlockSys 2019 (Proceedings of the 2nd Workshop on Blockchain-enabled Networked Sensor, New York, NY, Nov 10, 2019) 28-29, 2019. Type: Proceedings
Sensor systems and Internet of Things (IoT) environments raise a new major challenge to security. Some of these issues can be solved with blockchain protocols, for example, distributed ledger technologies (DLTs); however, “it is still not cl...
Carl Adam Petri: ideas, personality, impact
Reisig W., Rozenberg G., Springer International Publishing, New York, NY, 2019. 249 pp. Type: Book (978-3-319961-53-8)
Every computer scientist studies Petri nets in their early academic years. Petri nets are a powerful yet very intuitive modeling tool for concurrent and distributed systems. Such networks were introduced by Carl Adam Petri (1926-2010) in his PhD t...
Deep learning and convolutional neural networks for medical imaging and clinical informatics
Lu L., Wang X., Carneiro G., Yang L., Springer International Publishing, New York, NY, 2019. 461 pp. Type: Book (978-3-030139-68-1)
This book reviews deep learning research and applications “for medical imaging and clinical informatics.” It specifically presents information about the implementation of deep learning and convolutional neural network (CNN) application...
Modern Fortran explained: incorporating Fortran 2018
Metcalf M., Reid J., Cohen M., Oxford University Press, New York, NY, 2018. 522 pp. Type: Book (978-0-198811-88-6)
First introduced in 1957, FORTRAN was designed to be easier than an assembler language for writing algebraic equations on a computer. In this, FORTRAN was spectacularly successful....
Is the stack distance between test case and method correlated with test effectiveness?
Niedermayr R., Wagner S. EASE 2019 (Proceedings of the Evaluation and Assessment on Software Engineering, Copenhagen, Denmark, Apr 15-17, 2019) 189-198, 2019. Type: Proceedings
In general, it is not algorithmically possible to always prove a program’s correctness or incorrectness. So, in practice, a program’s correctness is usually judged by testing the program on test cases from some test suite. How can we g...
Social media data processing infrastructure by using Apache Spark big data platform: Twitter data analysis
Podhoranyi M., Vojacek L. CCIOT 2019 (Proceedings of the 2019 4th International Conference on Cloud Computing and Internet of Things, Tokyo, Japan, Sep 20-22, 2019) 1-6, 2019. Type: Proceedings
What would we do without social media? What would the world look like if there weren’t continuous data streams? If we refer back to our history, the first big breakthrough was around 1440, when Johannes Gutenberg started his printing technol...
Management 4.0: cases and methods for the 4th industrial revolution
Reagan J., Singh M., Springer International Publishing, New York, NY, 2020. 214 pp. Type: Book (978-9-811567-50-6)
Don’t judge this book by its cover. Despite its title, this is not a book about management. It is a book for executives, strategists, managers, technologists, consultants, educators, policymakers, and concerned stakeholders about the need fo...
Linear programming (5th ed.)
Vanderbei R., Springer International Publishing, New York, NY, 2020. 495 pp. Type: Book (978-3-030394-14-1)
Linear programming (LP) finds the optimal solution to a mathematical problem with given resources or constraints. The optimization of resources in achieving an optimal solution employs various methods; simplex, convex analysis, degeneracy, game th...
Assessing neural network scene classification from degraded images
Tadros T., Cullen N., Greene M., Cooper E. ACM Transactions on Applied Perception 16(4): 1-20, 2019. Type: Article, Reviews: (2 of 2)
One of the major problems faced by deep learning techniques--for example, deep convolutional neural networks (CNNs)--is uncontrolled behavior due to glitches in the input. For example, you can modify just a few pixels in a photo’s ...
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