Digital Diversity: Cultures, Languages and Methods' is the motto for this year's Digital Humanities conference; it relates methodical and technical innovation to the traditional research agenda of the Humanities. The conference schedule includes contributions on a wide range of topics, reflecting the increasing breadth in the field on all levels. A recurring theme at Digital Humanities conferen…
Similar to general-purpose languages, domain-specific languages (DSL) can be developed based on grammar formalisms, the model-driven engineering (MDE) is also becoming more and more important for the development of DSLs. On the one hand, metamodels can be used to define the syntax and semantics of DSLs. On the other hand, a DSL can be realized by adapting the Unified Modeling Language (UML) via…
Structure and Interpretation of Computer Programs has had a dramatic impact on computer science curricula over the past decade. This long-awaited revision contains changes throughout the text. There are new implementations of most of the major programming systems in the book, including the interpreters and compilers, and the authors have incorporated many small changes that reflect their experi…
This new edition of The Art of Prolog contains a number of important changes. Most background sections at the end of each chapter have been updated to take account of important recent research results, the references have been greatly expanded, and more advanced exercises have been added which have been used successfully in teaching the course. Part II, The Prolog Language, has been modified to…
Numerical Simulation of the Frank-Kamenetskii PDE: GPU vs. CPU Computing
A MATLAB Interactive Tool for Computer Aided Control Systems Design in Frequency Domain: FRTool
Lütkenhöner’s „Intensity Dependence of Auditory Responses“: An Instructional Example in How Not To Do Computational Neurobiology
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining th…
Anomaly Detection & Behavior Prediction: Higher-Level Fusion Based on Computational Neuroscientific Principles