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In this paper we introduce and study some new cooperation protocols for cooperating distributed (CD) grammar systems. These derivation modes depend on the number of different nonterminals present in the sentential form obtained when a component finished a derivation phase. This measure describes the competence of the grammar on the string (the competence is high if the number of the different nonterminals is small). It is also a measure of the efficiency of the grammar on the given string (a component is more efficient than another one if it is able to decrease the number of nonterminals in the string to a greater extent). We prove that if the underlying derivation mode is the t-mode derivation, then some variants of these systems determine the class of random context ET0L languages. If these CD grammar systems use the k step limited derivations as underlying derivation mode, then they are able to generate any recursively enumerable language.
Background: The biological interpretation of large-scale gene expression data is one of the paramount challenges in current bioinformatics. In particular, placing the results in the context of other available functional genomics data, such as existing bio-ontologies, has already provided substantial improvement for detecting and categorizing genes of interest. One common approach is to look for functional annotations that are significantly enriched within a group or cluster of genes, as compared to a reference group. Results: In this work, we suggest the information-theoretic concept of mutual information to investigate the relationship between groups of genes, as given by data-driven clustering, and their respective functional categories. Drawing upon related approaches (Gibbons and Roth, Genome Research 12: 1574-1581, 2002), we seek to quantify to what extent individual attributes are sufficient to characterize a given group or cluster of genes. Conclusion: We show that the mutual information provides a systematic framework to assess the relationship between groups or clusters of genes and their functional annotations in a quantitative way. Within this framework, the mutual information allows us to address and incorporate several important issues, such as the interdependence of functional annotations and combinatorial combinations of attributes. It thus supplements and extends the conventional search for overrepresented attributes within a group or cluster of genes. In particular taking combinations of attributes into account, the mutual information opens the way to uncover specific functional descriptions of a group of genes or clustering result. All datasets and functional annotations used in this study are publicly available. All scripts used in the analysis are provided as additional files.
Utilizing quad-trees for efficient design space exploration with partial assignment evaluation
(2018)
Recently, it has been shown that constraint-based symbolic solving techniques offer an efficient way for deciding binding and routing options in order to obtain a feasible system level implementation. In combination with various background theories, a feasibility analysis of the resulting system may already be performed on partial solutions. That is, infeasible subsets of mapping and routing options can be pruned early in the decision process, which fastens the solving accordingly. However, allowing a proper design space exploration including multi-objective optimization also requires an efficient structure for storing and managing non-dominated solutions. In this work, we propose and study the usage of the Quad-Tree data structure in the context of partial assignment evaluation during system synthesis. Out experiments show that unnecessary dominance checks can be avoided, which indicates a preference of Quad-Trees over a commonly used list-based implementation for large combinatorial optimization problems.
Scientific writing is an important skill for computer science and computer engineering professionals. In this paper we present a writing concept across the curriculum program directed towards scientific writing. The program is built around a hierarchy of learning outcomes. The hierarchy is constructed through analyzing the learning outcomes in relation to competencies that are needed to fulfill them.
Current curricular trends require teachers in Baden-
Wuerttemberg (Germany) to integrate Computer Science (CS) into
traditional subjects, such as Physical Science. However, concrete guidelines
are missing. To fill this gap, we outline an approach where a
microcontroller is used to perform and evaluate measurements in the
Physical Science classroom.
Using the open-source Arduino platform, we expect students to acquire
and develop both CS and Physical Science competencies by using a
self-programmed microcontroller. In addition to this combined development
of competencies in Physical Science and CS, the subject matter
will be embedded in suitable contexts and learning environments,
such as weather and climate.
User Experience (UX) describes the holistic experience of a user before, during, and after interaction with a platform, product, or service. UX adds value and attraction to their sole functionality and is therefore highly relevant for firms. The increased interest in UX has produced a vast amount of scholarly research since 1983. The research field is, therefore, complex and scattered. Conducting a bibliometric analysis, we aim at structuring the field quantitatively and rather abstractly. We employed citation analyses, co-citation analyses, and content analyses to evaluate productivity and impact of extant research. We suggest that future research should focus more on business and management related topics.
Untitled
(2004)
Untitled
(2011)
In diesem Papier wird das Konzept eines Lernzentrums für die Informatik (LZI) an der Universität Paderborn vorgestellt. Ausgehend von den fachspezifischen Schwierigkeiten der Informatik Studierenden werden die Angebote des LZIs erläutert, die sich über die vier Bereiche Individuelle Beratung und Betreuung, „Offener Lernraum“, Workshops und Lehrveranstaltungen sowie Forschung erstrecken. Eine erste Evaluation mittels Feedbackbögen zeigt, dass das Angebot bei den Studierenden positiv aufgenommen wird. Zukünftig soll das Angebot des LZIs weiter ausgebaut und verbessert werden. Ausgangsbasis dazu sind weitere Studien.
We investigate the operation problem for linear and deterministic context-free languages: Fix an operation on formal languages. Given linear (deterministic, respectively) context-free languages, is the application of this operation to the given languages still a linear (deterministic, respectively) context-free language? Besides the classical operations, for which the linear and deterministic context-free languages are not closed, we also consider the recently introduced root and power operation. We show non-semidecidability, to be more precise, we show completeness for the second level of the arithmetic hierarchy for all of the aforementioned operations, except for the power operation, if the underlying alphabet contains at least two letters. The result for the power opera, tion solves an open problem stated in Theoret. Comput. Sci. 314 (2004) 445-449
Computational thinking is a fundamental skill set that is learned
by studying Informatics and ICT. We argue that its core ideas can
be introduced in an inspiring and integrated way to both teachers and
students using fun and contextually rich cs4fn ‘Computer Science for
Fun’ stories combined with ‘unplugged’ activities including games and
magic tricks. We also argue that understanding people is an important
part of computational thinking. Computational thinking can be fun for
everyone when taught in kinaesthetic ways away from technology.
Unmixing hyperspectral data
(2000)
Parallel communicating finite automata (PCFAs) are systems of several finite state automata which process a common input string in a parallel way and are able to communicate by sending their states upon request. We consider deterministic and nondeterministic variants and distinguish four working modes. It is known that these systems in the most general mode are as powerful as one-way multi-head finite automata. It is additionally known that the number of heads corresponds to the number of automata in PCFAs in a constructive way. Thus, undecidability results as well as results on the hierarchies induced by the number of heads carry over from multi-head finite automata to PCFAs in the most general mode. Here, we complement these undecidability and hierarchy results also for the remaining working modes. In particular, we show that classical decidability questions are not semi-decidable for any type of PCFAs under consideration. Moreover, it is proven that the number of automata in the system induces infinite hierarchies for deterministic and nondeterministic PCFAs in three working modes.
Berufsbegleitende Studiengänge stehen vor besonderen Schwierigkeiten, für die der Einsatz von Blended Learning-Szenarien sinnvoll sein kann. Welche speziellen Herausforderungen sich dabei ergeben und welche Lösungsansätze dagegen steuern, betrachtet der folgende Artikel anhand eines Praxisberichts aus dem Studiengang M. P. A. Wissenschaftsmanagement an der Universität Speyer.
The UDKM1DSIM toolbox is a collection of MATLAB (MathWorks Inc.) classes and routines to simulate the structural dynamics and the according X-ray diffraction response in one-dimensional crystalline sample structures upon an arbitrary time-dependent external stimulus, e.g. an ultrashort laser pulse. The toolbox provides the capabilities to define arbitrary layered structures on the atomic level including a rich database of corresponding element-specific physical properties. The excitation of ultrafast dynamics is represented by an N-temperature model which is commonly applied for ultrafast optical excitations. Structural dynamics due to thermal stress are calculated by a linear-chain model of masses and springs. The resulting X-ray diffraction response is computed by dynamical X-ray theory. The UDKM1DSIM toolbox is highly modular and allows for introducing user-defined results at any step in the simulation procedure.
Program summary
Program title: udkm1Dsim
Catalogue identifier: AERH_v1_0
Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AERH_v1_0.html
Licensing provisions: BSD
No. of lines in distributed program, including test data, etc.: 130221
No. of bytes in distributed program, including test data, etc.: 2746036
Distribution format: tar.gz
Programming language: Matlab (MathWorks Inc.).
Computer: PC/Workstation.
Operating system: Running Matlab installation required (tested on MS Win XP -7, Ubuntu Linux 11.04-13.04).
Has the code been vectorized or parallelized?: Parallelization for dynamical XRD computations. Number of processors used: 1-12 for Matlab Parallel Computing Toolbox; 1 - infinity for Matlab Distributed Computing Toolbox
External routines:
Optional: Matlab Parallel Computing Toolbox, Matlab Distributed Computing Toolbox Required (included in the package): mtimesx Fast Matrix Multiply for Matlab by James Tursa, xml io tools by Jaroslaw Tuszynski, textprogressbar by Paul Proteus
Nature of problem:
Simulate the lattice dynamics of 1D crystalline sample structures due to an ultrafast excitation including thermal transport and compute the corresponding transient X-ray diffraction pattern.
Solution method:
Restrictions:
The program is restricted to 1D sample structures and is further limited to longitudinal acoustic phonon modes and symmetrical X-ray diffraction geometries.
Unusual features: The program is highly modular and allows the inclusion of user-defined inputs at any time of the simulation procedure.
Running time: The running time is highly dependent on the number of unit cells in the sample structure and other simulation parameters such as time span or angular grid for X-ray diffraction computations. However, the example files are computed in approx. 1-5 min each on a 8 Core Processor with 16 GB RAM available.
Answer Set Programming (ASP) is a paradigm for modeling and solving problems for knowledge representation and reasoning. There are plenty of results dedicated to studying the hardness of (fragments of) ASP. So far, these studies resulted in characterizations in terms of computational complexity as well as in fine-grained insights presented in form of dichotomy-style results, lower bounds when translating to other formalisms like propositional satisfiability (SAT), and even detailed parameterized complexity landscapes. A generic parameter in parameterized complexity originating from graph theory is the socalled treewidth, which in a sense captures structural density of a program. Recently, there was an increase in the number of treewidth-based solvers related to SAT. While there are translations from (normal) ASP to SAT, no reduction that preserves treewidth or at least keeps track of the treewidth increase is known. In this paper we propose a novel reduction from normal ASP to SAT that is aware of the treewidth, and guarantees that a slight increase of treewidth is indeed sufficient. Further, we show a new result establishing that, when considering treewidth, already the fragment of normal ASP is slightly harder than SAT (under reasonable assumptions in computational complexity). This also confirms that our reduction probably cannot be significantly improved and that the slight increase of treewidth is unavoidable. Finally, we present an empirical study of our novel reduction from normal ASP to SAT, where we compare treewidth upper bounds that are obtained via known decomposition heuristics. Overall, our reduction works better with these heuristics than existing translations. (c) 2021 Elsevier B.V. All rights reserved.
TrainTrap
(2020)
A well-known result by Stein (1956) shows that in particular situations, biased estimators can yield better parameter estimates than their generally preferred unbiased counterparts. This letter follows the same spirit, as we will stabilize the unbiased generalization error estimates by regularization and finally obtain more robust model selection criteria for learning. We trade a small bias against a larger variance reduction, which has the beneficial effect of being more precise on a single training set. We focus on the subspace information criterion (SIC), which is an unbiased estimator of the expected generalization error measured by the reproducing kernel Hilbert space norm. SIC can be applied to the kernel regression, and it was shown in earlier experiments that a small regularization of SIC has a stabilization effect. However, it remained open how to appropriately determine the degree of regularization in SIC. In this article, we derive an unbiased estimator of the expected squared error, between SIC and the expected generalization error and propose determining the degree of regularization of SIC such that the estimator of the expected squared error is minimized. Computer simulations with artificial and real data sets illustrate that the proposed method works effectively for improving the precision of SIC, especially in the high-noise-level cases. We furthermore compare the proposed method to the original SIC, the cross-validation, and an empirical Bayesian method in ridge parameter selection, with good results
We introduce a type and effect system, for an imperative object calculus, which infers sharing possibly introduced by the evaluation of an expression, represented as an equivalence relation among its free variables. This direct representation of sharing effects at the syntactic level allows us to express in a natural way, and to generalize, widely-used notions in literature, notably uniqueness and borrowing. Moreover, the calculus is pure in the sense that reduction is defined on language terms only, since they directly encode store. The advantage of this non-standard execution model with respect to a behaviorally equivalent standard model using a global auxiliary structure is that reachability relations among references are partly encoded by scoping. (C) 2018 Elsevier B.V. All rights reserved.
Nowadays, model-driven engineering (MDE) promises to ease software development by decreasing the inherent complexity of classical software development. In order to deliver on this promise, MDE increases the level of abstraction and automation, through a consideration of domain-specific models (DSMs) and model operations (e.g. model transformations or code generations). DSMs conform to domain-specific modeling languages (DSMLs), which increase the level of abstraction, and model operations are first-class entities of software development because they increase the level of automation. Nevertheless, MDE has to deal with at least two new dimensions of complexity, which are basically caused by the increased linguistic and technological heterogeneity. The first dimension of complexity is setting up an MDE environment, an activity comprised of the implementation or selection of DSMLs and model operations. Setting up an MDE environment is both time-consuming and error-prone because of the implementation or adaptation of model operations. The second dimension of complexity is concerned with applying MDE for actual software development. Applying MDE is challenging because a collection of DSMs, which conform to potentially heterogeneous DSMLs, are required to completely specify a complex software system. A single DSML can only be used to describe a specific aspect of a software system at a certain level of abstraction and from a certain perspective. Additionally, DSMs are usually not independent but instead have inherent interdependencies, reflecting (partial) similar aspects of a software system at different levels of abstraction or from different perspectives. A subset of these dependencies are applications of various model operations, which are necessary to keep the degree of automation high. This becomes even worse when addressing the first dimension of complexity. Due to continuous changes, all kinds of dependencies, including the applications of model operations, must also be managed continuously. This comprises maintaining the existence of these dependencies and the appropriate (re-)application of model operations. The contribution of this thesis is an approach that combines traceability and model management to address the aforementioned challenges of configuring and applying MDE for software development. The approach is considered as a traceability approach because it supports capturing and automatically maintaining dependencies between DSMs. The approach is considered as a model management approach because it supports managing the automated (re-)application of heterogeneous model operations. In addition, the approach is considered as a comprehensive model management. Since the decomposition of model operations is encouraged to alleviate the first dimension of complexity, the subsequent composition of model operations is required to counteract their fragmentation. A significant portion of this thesis concerns itself with providing a method for the specification of decoupled yet still highly cohesive complex compositions of heterogeneous model operations. The approach supports two different kinds of compositions - data-flow compositions and context compositions. Data-flow composition is used to define a network of heterogeneous model operations coupled by sharing input and output DSMs alone. Context composition is related to a concept used in declarative model transformation approaches to compose individual model transformation rules (units) at any level of detail. In this thesis, context composition provides the ability to use a collection of dependencies as context for the composition of other dependencies, including model operations. In addition, the actual implementation of model operations, which are going to be composed, do not need to implement any composition concerns. The approach is realized by means of a formalism called an executable and dynamic hierarchical megamodel, based on the original idea of megamodels. This formalism supports specifying compositions of dependencies (traceability and model operations). On top of this formalism, traceability is realized by means of a localization concept, and model management by means of an execution concept.
The submission and management of computational jobs is a traditional part of utility computing environments. End users and developers of domain-specific software abstractions often have to deal with the heterogeneity of such batch processing systems. This lead to a number of application programming interface and job description standards in the past, which are implemented and established for cluster and Grid systems. With the recent rise of cloud computing as new utility computing paradigm, the standardized access to batch processing facilities operated on cloud resources becomes an important issue. Furthermore, the design of such a standard has to consider a tradeoff between feature completeness and the achievable level of interoperability. The article discusses this general challenge, and presents some existing standards with traditional cluster and Grid computing background that may be applicable to cloud environments. We present OCCI-DRMAA as one approach for standardized access to batch processing facilities hosted in a cloud.
We elaborate upon the theoretical foundations of a metric temporal extension of Answer Set Programming. In analogy to previous extensions of ASP with constructs from Linear Temporal and Dynamic Logic, we accomplish this in the setting of the logic of Here-and-There and its non-monotonic extension, called Equilibrium Logic. More precisely, we develop our logic on the same semantic underpinnings as its predecessors and thus use a simple time domain of bounded time steps. This allows us to compare all variants in a uniform framework and ultimately combine them in a common implementation.
Towards computer science
(1998)
Answer Set Programming (ASP) is a successful rule-based formalism for modeling and solving knowledge-intense combinatorial (optimization) problems. Despite its success in both academic and industry, open challenges like automatic source code optimization, and software engineering remains. This is because a problem encoded into an ASP might not have the desired solving performance compared to an equivalent representation. Motivated by these two challenges, this paper has three main contributions. First, we propose a developing process towards a methodology to implement ASP programs, being faithful to existing methods. Second, we present ASP encodings that serve as the basis from the developing process. Third, we demonstrate the use of ASP to reverse the standard solving process. That is, knowing answer sets in advance, and desired strong equivalent properties, “we” exhaustively reconstruct ASP programs if they exist. This paper was originally motivated by the search of propositional formulas (if they exist) that represent the semantics of a new aggregate operator. Particularly, a parity aggregate. This aggregate comes as an improvement from the already existing parity (xor) constraints from xorro, where lacks expressiveness, even though these constraints fit perfectly for reasoning modes like sampling or model counting. To this end, this extended version covers the fundaments from parity constraints as well as the xorro system. Hence, we delve a little more in the examples and the proposed methodology over parity constraints. Finally, we discuss our results by showing the only representation available, that satisfies different properties from the classical logic xor operator, which is also consistent with the semantics of parity constraints from xorro.
Non-stationarities are ubiquitous in EEG signals. They are especially apparent in the use of EEG-based brain- computer interfaces (BCIs): (a) in the differences between the initial calibration measurement and the online operation of a BCI, or (b) caused by changes in the subject's brain processes during an experiment (e.g. due to fatigue, change of task involvement, etc). In this paper, we quantify for the first time such systematic evidence of statistical differences in data recorded during offline and online sessions. Furthermore, we propose novel techniques of investigating and visualizing data distributions, which are particularly useful for the analysis of (non-) stationarities. Our study shows that the brain signals used for control can change substantially from the offline calibration sessions to online control, and also within a single session. In addition to this general characterization of the signals, we propose several adaptive classification schemes and study their performance on data recorded during online experiments. An encouraging result of our study is that surprisingly simple adaptive methods in combination with an offline feature selection scheme can significantly increase BCI performance