2,611 research outputs found
One-dimensional layout optimization, with applications to graph drawing by axis separation
AbstractIn this paper we discuss a useful family of graph drawing algorithms, characterized by their ability to draw graphs in one dimension. We define the special requirements from such algorithms and show how several graph drawing techniques can be extended to handle this task. In particular, we suggest a novel optimization algorithm that facilitates using the Kamada and Kawai model [Inform. Process. Lett. 31 (1989) 7–15] for producing one-dimensional layouts. The most important application of the algorithms seems to be in achieving graph drawing by axis separation, where each axis of the drawing addresses different aspects of aesthetics
Separation of Test-Free Propositional Dynamic Logics over Context-Free Languages
For a class L of languages let PDL[L] be an extension of Propositional
Dynamic Logic which allows programs to be in a language of L rather than just
to be regular. If L contains a non-regular language, PDL[L] can express
non-regular properties, in contrast to pure PDL.
For regular, visibly pushdown and deterministic context-free languages, the
separation of the respective PDLs can be proven by automata-theoretic
techniques. However, these techniques introduce non-determinism on the automata
side. As non-determinism is also the difference between DCFL and CFL, these
techniques seem to be inappropriate to separate PDL[DCFL] from PDL[CFL].
Nevertheless, this separation is shown but for programs without test operators.Comment: In Proceedings GandALF 2011, arXiv:1106.081
Human or Machine: Reflections on Turing-Inspired Testing for the Everyday
In his seminal paper "Computing Machinery and Intelligence", Alan Turing
introduced the "imitation game" as part of exploring the concept of machine
intelligence. The Turing Test has since been the subject of much analysis,
debate, refinement and extension. Here we sidestep the question of whether a
particular machine can be labeled intelligent, or can be said to match human
capabilities in a given context. Instead, but inspired by Turing, we draw
attention to the seemingly simpler challenge of determining whether one is
interacting with a human or with a machine, in the context of everyday life. We
are interested in reflecting upon the importance of this Human-or-Machine
question and the use one may make of a reliable answer thereto. Whereas
Turing's original test is widely considered to be more of a thought experiment,
the Human-or-Machine question as discussed here has obvious practical
significance. And while the jury is still not in regarding the possibility of
machines that can mimic human behavior with high fidelity in everyday contexts,
we argue that near-term exploration of the issues raised here can contribute to
development methods for computerized systems, and may also improve our
understanding of human behavior in general
Computable queries for relational data bases
AbstractThe concept of “reasonable” queries on relational data bases is investigated. We provide an abstract characterization of the class of queries which are computable, and define the completeness of a query language as the property of being precisely powerful enough to express the queries in this class. This definition is then compared with other proposals for measuring the power of query languages. Our main result is the completeness of a simple programming language which can be thought of as consisting of the relational algebra augmented with the power of iteration
Music Technology Education and a Plugin-Based Platform as a Tool to Enhance Creativity, Multidisciplinarity, Creative Design, and Collaboration Skills
Music technology is known to have the ability to enhance creativity and creative development among students. A high level of engagement has been shown among students who studied and developed musical projects, and among students who were intellectually involved in the process of meaningful exploration. When students develop a music technology project, they use their software design skills to build and combine different artistic and computational components. Here we present a creative education method for computer science and software engineering students, it uses Muzilator, a plugin-based web platform that enables developers to develop a project as a set of independent web applications (plugins). Students can share their plugins with others or use plugins developed by others. We examined 75 projects of teams of computer science students who participated in a Computer Music course. We studied the characteristics of these projects and Muzilator’s effectiveness as a creative education and collaboration tool. Some of our results show that Muzilator-based projects received higher creativity and multidisciplinarity ratings than did other projects, and that high-risk projects were more creative and artistic than low-risk ones. We also found a gender-dependency: women tended more than men to develop interactive applications, while men tended to choose more theoretic (algorithmic), non-interactive projects. Keywords: educational method, creativity, music education, software design, multidisciplinarity. DOI: 10.7176/JEP/12-11-01 Publication date: April 30th 202
Autonomics: In Search of a Foundation for Next Generation Autonomous Systems
The potential benefits of autonomous systems have been driving intensive
development of such systems, and of supporting tools and methodologies.
However, there are still major issues to be dealt with before such development
becomes commonplace engineering practice, with accepted and trustworthy
deliverables. We argue that a solid, evolving, publicly available,
community-controlled foundation for developing next generation autonomous
systems is a must. We discuss what is needed for such a foundation, identify a
central aspect thereof, namely, decision-making, and focus on three main
challenges: (i) how to specify autonomous system behavior and the associated
decisions in the face of unpredictability of future events and conditions and
the inadequacy of current languages for describing these; (ii) how to carry out
faithful simulation and analysis of system behavior with respect to rich
environments that include humans, physical artifacts, and other systems,; and
(iii) how to engineer systems that combine executable model-driven techniques
and data-driven machine learning techniques. We argue that autonomics, i.e.,
the study of unique challenges presented by next generation autonomous systems,
and research towards resolving them, can introduce substantial contributions
and innovations in system engineering and computer science
Biocharts: a visual formalism for complex biological systems
We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis
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