Parametric Sequence Alignment with Constraints

Approximate matching techniques based on string alignment are important tools for investigating similarities between strings, such as those representing DNA and protein sequences. We propose a constraint based approach for parametric sequence alignment which allows for more general string alignment queries where the alignment cost can itself be parameterized as a query with some initial constraints. Thus, the costs need not be fixed in a parametric alignment query unlike the case in normal alignment. The basic dynamic programming string edit distance algorithm is generalized to a naive algorithm which uses inequalities to represent the alignment score. The naive algorithm is rather costly and the remainder of the paper develops an improvement which prunes alternatives where it can and approximates the alternatives otherwise. This reduces the number of inequalities significantly and strengthens the constraint representation with equalities. We present some preliminary results using parametric alignment on some general alignment queries.     

Organizational climate in air traffic control Innovative preparedness for implementation of new technology and organizational development in a rule governed organization

A positive and innovative organizational climate is of great importance in order to manage and adapt to change. Such a climate seldom evolves in organizations closely governed by rules and regulations. Because of ongoing organizational and technical changes within the Swedish Air Navigation Services Provider, a study concerning the organizational climate for changes and innovations was conducted to investigate the organization's capacity to cope with changes. Study locations were the two Swedish main air traffic control centers and parts of the civil aviation administration headquarters. In the study 390 subjects took part and the CCQ questionnaire was used to measure the organizational climate. The results show that the organizational climate is quite positive despite the rule-governed work. The results also show that administrative personnel assess the organizational climate as more positive than operative personnel. Comparisons between management positions did not result in any differences.     

Distributed Symbolic Bounded Property Checking

In this paper we describe an algorithm for distributed, BDD-based bounded property checking and its implementation in the verification tool SymC. The distributed algorithm verifies larger models and returns results faster than the sequential version.The core algorithm distributes partitions of the state set to computation nodes after reaching a threshold size. The nodes proceed with image computation on the nodes asynchronously. The main scalability problem of this scheme is the overlap of state set partitions. We present static and dynamic overlap reduction techniques.     

Interferometer for cold neutrons

Design and setup of an interferometer for cold and ultracold neutrons are described. As neutron optical components three holographically produced gratings are arranged in triple Laue geometry. The gratings are adjusted during their recording process in photosensitized polymer slabs once for ever. Employing this device we measured the coherence function of a cold neutron beam by means of interferometry.     

Quantenprogrammiersprachen

Algorithmen für Quantenrechner wie der Faktorisierungsalgorithmus von Shor lassen sich mittels neuer Programmiersprachen formulieren, die neben konventionellen auch über für Quantenrechner spezifische Sprachkonstrukte verfügen. In Verbindung mit Simulatoren kann man so auch bereits heute Programme für Quantenrechner entwickeln und testen.     

Computing the update of the repeated median regression line in linear time

The repeated median line estimator is a highly robust method for fitting a regression line to a set of n data points in the plane. In this paper, we consider the problem of updating the estimate after a point is removed from or added to the data set. This problem occurs, e.g., in statistical online monitoring, where the computational effort is often critical. We present a deterministic algorithm for the update working in O(n) time and O(n²) space.     

A Tractable Class of Maximal Hedging Policies in Multi-Part Manufacturing Systems

The flow control problem in multi-part failure prone manufacturing systems is considered. While computationnaly attractive, the near optimal controllers of Caramanis and Sharifnia, suffer from the drawback that the production capacity set must be approximated via a very restricted set of inscribed hypercubes, namely those for which a componentwise feasibility requirement is satisfied. Also, due to the completely decoupled nature of production along each component, utilization of the restricted capacity set is suboptimal. A class of capacity set incribed hypercube policies called simple maximal hedging (SMH) policies is introduced. In SMH policies production levels along the various components of the capacity set are coupled, the componentwise feasibility requirement is lifted, and there is no underutilization of production capacity if needed. In a p part types manufacturing system, for partwise additive cost functionals, it is shown that performance evaluation of a given SMH policy reduces to the analysis of p decoupled (fictitious) semi-Markovian machines. The machines are Markovianized via first passage-time analysis and a Padé approximants technique. Numerical optimization over the class of SMH policies in a sample manufacturing system indicates that their performance can come close to that of the optimal control.