An investigation of resource-allocation decisions by means of project networks.

This paper investigates the relationship between resource allocation and ES-policies, which are a type of scheduling policies introduced for stochastic scheduling and which can be represented by a directed acyclic graph. We present a formal treatment of resource flows as are presentation of resource-allocation decisions, extending the existing literature. A number of complexity results are established, showing that a number of recently proposed objective functions for evaluating the quality of ES-policies lead to difficult problems. Finally, some reflections are provided on possible effciency enhancements to enumeration algorithms for ES-policies.Complexity; Project scheduling; Resource allocation; Resource constraints;

On-Line Reevaluation of Functions

Given a finite set S and a function f : S^n -> S^m, we consider the problem of making a data structure which maintains a value of x in S^n and allows us to efficiently change an arbitrary coordinate of x and efficiently evaluate f_i(x) for arbitrary i. We both examine the problem for specific choices of f and relate the possibility of an efficient solution to general properties of f: expressibility as a formula, space complexity and time complexity

Modular Materialisation of Datalog Programs

The semina\"ive algorithm can materialise all consequences of arbitrary datalog rules, and it also forms the basis for incremental algorithms that update a materialisation as the input facts change. Certain (combinations of) rules, however, can be handled much more efficiently using custom algorithms. To integrate such algorithms into a general reasoning approach that can handle arbitrary rules, we propose a modular framework for materialisation computation and its maintenance. We split a datalog program into modules that can be handled using specialised algorithms, and handle the remaining rules using the semina\"ive algorithm. We also present two algorithms for computing the transitive and the symmetric-transitive closure of a relation that can be used within our framework. Finally, we show empirically that our framework can handle arbitrary datalog programs while outperforming existing approaches, often by orders of magnitude.Comment: Accepted at AAAI 201

Searching Constant Width Mazes Captures the AC0 Hierarchy

We show that searching a width k maze is complete for Pi_k, i.e.,for the k'th level of the AC0 hierarchy. Equivalently, st-connectivityfor width k grid graphs is complete for Pi_k. As an application, weshow that there is a data structure solving dynamic st-connectivity for constant width grid graphs with time bound O(log log n) per operation on a random access machine. The dynamic algorithm is derived from the parallel one in an indirect way using algebraic tools

Dynamic Complexity of Reachability: How Many Changes Can We Handle?

In 2015, it was shown that reachability for arbitrary directed graphs can be updated by first-order formulas after inserting or deleting single edges. Later, in 2018, this was extended for changes of size (log n)/(log log n), where n is the size of the graph. Changes of polylogarithmic size can be handled when also majority quantifiers may be used. In this paper we extend these results by showing that, for changes of polylogarithmic size, first-order update formulas suffice for maintaining (1) undirected reachability, and (2) directed reachability under insertions. For classes of directed graphs for which efficient parallel algorithms can compute non-zero circulation weights, reachability can be maintained with update formulas that may use "modulo 2" quantifiers under changes of polylogarithmic size. Examples for these classes include the class of planar graphs and graphs with bounded treewidth. The latter is shown here. As the logics we consider cannot maintain reachability under changes of larger sizes, our results are optimal with respect to the size of the changes

Large scale statistical inference of signaling pathways from RNAi and microarray data

<p>Abstract</p> <p>Background</p> <p>The advent of RNA interference techniques enables the selective silencing of biologically interesting genes in an efficient way. In combination with DNA microarray technology this enables researchers to gain insights into signaling pathways by observing downstream effects of individual knock-downs on gene expression. These secondary effects can be used to computationally reverse engineer features of the upstream signaling pathway.</p> <p>Results</p> <p>In this paper we address this challenging problem by extending previous work by Markowetz <it>et al</it>., who proposed a statistical framework to score networks hypotheses in a Bayesian manner. Our extensions go in three directions: First, we introduce a way to omit the data discretization step needed in the original framework via a calculation based on <it>p</it>-values instead. Second, we show how prior assumptions on the network structure can be incorporated into the scoring scheme using regularization techniques. Third and most important, we propose methods to scale up the original approach, which is limited to around 5 genes, to large scale networks.</p> <p>Conclusion</p> <p>Comparisons of these methods on artificial data are conducted. Our proposed module network is employed to infer the signaling network between 13 genes in the ER-<it>α </it>pathway in human MCF-7 breast cancer cells. Using a bootstrapping approach this reconstruction can be found with good statistical stability.</p> <p>The code for the module network inference method is available in the latest version of the <it>R</it>-package <it>nem</it>, which can be obtained from the Bioconductor homepage.</p

The theory of interface slicing

Interface slicing is a new tool which was developed to facilitate reuse-based software engineering, by addressing the following problems, needs, and issues: (1) size of systems incorporating reused modules; (2) knowledge requirements for program modification; (3) program understanding for reverse engineering; (4) module granularity and domain management; and (5) time and space complexity of conventional slicing. The definition of a form of static program analysis called interface slicing is addressed