On the Power of Las Vegas for One-Way Communication Complexity, OBDDs, and Finite Automata

The study of the computational power of randomized computations is one of the central tasks of complexity theory. The main goal of this paper is the comparison of the power of Las Vegas computation and deterministic respectively nondeterministic computation. We investigate the power of Las Vegas computation for the complexity measures of one-way communication, ordered binary decision diagrams, and finite automata.(i) For the one-way communication complexity of two-party protocols we show that Las Vegas communication can save at most one half of the deterministic one-way communication complexity. We also present a language for which this gap is tight.(ii) The result (i) is applied to show an at most polynomial gap between determinism and Las Vegas for ordered binary decision diagrams.(iii) For the size (i.e., the number of states) of finite automata we show that the size of Las Vegas finite automata recognizing a language L is at least the square root of the size of the minimal deterministic finite automaton recognizing L. Using a specific language we verify the optimality of this lower bound.     

Modeling and animation of facial expressions based on B-Splines

This paper describes a technique for the automatic adaptation of a canonical facial model to data obtained by a 3D laser scanner. The facial model is a B-spline surface with 13×16 control points. We introduce a technique by which this canonical model is fit to the scanned data and that takes into consideration the requirements for the animation of facial expressions. The animation of facial expressions is based on the facial action coding system (FACS). Using B-splines in combination with FACS, we automatically create the impression of a moving skin. To increase the realism of the animation we map textural information onto the B-spline surface.     

Iterative multi-party agreement negotiation for establishing collaborations

Inter-domain collaborations suffer not only from technological obstacles that hinder interoperability, but also from diverting business objectives of the involved domains. Today, hand-crafted contracts define the terms and conditions for service interactions. Electronic negotiation can serve as the enabler of dynamic interdomain collaborations by providing a large degree of freedom for the automation of agreement formation and electronic contracting. Negotiation by electronic means has been an area of intensive research for many years now. However, most effort was put on the determination of prices and neglected that real-world agreements also consist of complex dependencies of interdependent obligations. In this paper we present agreement negotiation as a tool to establish ad hoc services collaborations. Our novel protocol allows for the discovery of complex agreement options and for the formation of multi-party agreements. The protocol works through an iterative exchange of requirements and offers. A major benefit over existing bilateral negotiation protocols is that our protocol is capable of discovering potential collaborations between different parties. It will leave each negotiating party with a complete agreement document after a successful negotiation. This comprehensive agreement document defines the interdependent obligations between all parties and is well suited for E-Contracting.     

Propagation Models for Trust and Distrust in Social Networks

Semantic Web endeavors have mainly focused on issues pertaining to knowledge representation and ontology design. However, besides understanding information metadata stated by subjects, knowing about their credibility becomes equally crucial. Hence, trust and trust metrics, conceived as computational means to evaluate trust relationships between individuals, come into play. Our major contribution to Semantic Web trust management through this work is twofold. First, we introduce a classification scheme for trust metrics along various axes and discuss advantages and drawbacks of existing approaches for Semantic Web scenarios. Hereby, we devise an advocacy for local group trust metrics, guiding us to the second part which presents Appleseed, our novel proposal for local group trust computation. Compelling in its simplicity, Appleseed borrows many ideas from spreading activation models in psychology and relates their concepts to trust evaluation in an intuitive fashion. Moreover, we provide extensions for the Appleseed nucleus that make our trust metric handle distrust statements. Cai-Nicolas Ziegler is a post-doctoral researcher at DBIS, the Databases and Information Systems group of the University of Freiburg, Germany. He studied Computer Science at the University of Passau, Germany, and Université Laval, Québec, receiving his Diploma (equivalent to MSc) in 2003. Cai-Nicolas obtained his PhD in Computer Science from the University of Freiburg in 2005. His primary research interests cover collaborative filtering applications and recommender systems, as well as computational trust models on the verge of human-computer interaction. Georg Lausen is head of the research group on Databases and Information Systems (DBIS) at the University of Freiburg, Germany. He received his Diploma in Industrial Engineering in 1978, PhD in 1982, and his postdoctoral lecture qualification (Habilitation) in 1985 from the University of Karlsruhe (TH). He was associate professor for Information Technology and Integration Problems at the Technical University of Darmstadt from 1986 to 1987. From 1987 to 1994 he was full professor for databases and informations systems at the University of Mannheim, and since 1994 at the University of Freiburg. His current research interests comprise information integration, internet technologies, and Web services.     

NQR on Gallium Single Crystals for Absolute Thermometry at Very Low Temperatures

It is shown that NMR/NQR-thermometry on Ga single crystals can serve the need of absolute thermometry in a temperature range from below 20 K to above 1 mK. Thus, the sensitive range includes all phase transition temperatures around 1 mK of solid and fluid ³ He, a necessity for an extension of the ³ He-melting-pressure temperature scale towards lower temperatures. The experiments were performed in magnetic fields of 50 to 200 mT and at temperatures down to 200 K using single rf-pulses. Special care was taken for the orientation of the magnetic field with respect to crystal orientation which was obtained by in-situ pulsed NMR-experiments. It has been shown that in the investigated parameter range nonlinear effects in NMR due to high spin alignment had no significant influence. In pulsed NMR as well as in specific heat experiments it could be shown that spin-spin interactions are only weak in Ga and do not influence nuclear paramagnetism, at least at temperatures above 100 K. The advantages of using Ga instead other elements for population difference thermometry are discussed.     

Generalized sparse MRF appearance models

Image segmentation or registration approaches that rely on a local search paradigm (e.g, Active Appearance Models, Active Contours) require an initialization that provides for considerable overlap or a coarse localization of the object to be segmented or localized. In this paper we propose an approach that does not need such an initialization, but localizes anatomical structures in a global manner by formulating the localization task as the solution of a Markov Random Field (MRF).     

Efficient moving horizon state and parameter estimation for SMB processes

In this paper, a moving horizon state and parameter estimation scheme for chromatographic simulated moving bed SMB processes is proposed. The simultaneous state and parameter estimation is based on a high-order nonlinear SMB model which incorporates rigorous models of the chromatographic columns and the discrete shiftings of the inlet and outlet ports. The estimation is performed using sparse measurement information: the concentrations of the components are only measured at the two outlet ports (which are periodically switched from one column to the next) and at one fixed location between two columns. The goal is to reconstruct the full state of the system, i.e. the concentration profiles along all columns, and to identify critical model parameters reliably such that the estimated model can be used in the context of online optimizing control. The state estimation scheme is based upon a deterministic model within the prediction horizon, state noise is only present in the state and the parameters prior to and at the beginning of the horizon. By solving the optimization problem with a multiple-shooting method and applying a real-time iteration scheme, the computation times are such that the scheme can be applied online. Numerical simulations of a validated model for a separation problem with nonlinear isotherms of the Langmuir type demonstrate the efficiency of the algorithm.     

Query answering under probabilistic uncertainty in Datalog+ / − ontologies

The recently introduced Datalog+?/?? family of ontology languages is especially useful for representing and reasoning over lightweight ontologies, and is set to play a central role in the context of query answering and information extraction for the Semantic Web. Recently, it has become apparent that it is necessary to develop a principled way to handle uncertainty in this domain. In addition to uncertainty as an inherent aspect of the Web, one must also deal with forms of uncertainty due to inconsistency and incompleteness, uncertainty resulting from automatically processing Web data, as well as uncertainty stemming from the integration of multiple heterogeneous data sources. In this paper, we take an important step in this direction by developing a probabilistic extension of Datalog+?/??. This extension uses Markov logic networks as the underlying probabilistic semantics. Here, we focus especially on scalable algorithms for answering threshold queries, which correspond to the question “what is the set of all ground atoms that are inferred from a given probabilistic ontology with a probability of at least p?”. These queries are especially relevant to Web information extraction, since uncertain rules lead to uncertain facts, and only information with a certain minimum confidence is desired. We present several algorithms, namely a basic approach, an anytime one, and one based on heuristics, which is guaranteed to return sound results. Furthermore, we also study inconsistency in probabilistic Datalog+?/?? ontologies. We propose two approaches for computing preferred repairs based on two different notions of distance between repairs, namely symmetric and score-based distance. We also study the complexity of the decision problems corresponding to computing such repairs, which turn out to be polynomial and NP-complete in the data complexity, respectively.     

Integrating a flexible anthropomorphic, robot hand into the control, system of a humanoid robot

This article presents the approaches taken to integrate a novel anthropomorphic robot hand into a humanoid robot. The requisites enabling such a robot hand to use everyday objects in an environment built for humans are presented. Starting from a design that resembles the human hand regarding size and movability of the mechatronical system, a low-level control system is shown providing reliable and stable controllers for single joint angles and torques, entire fingers and several coordinated fingers. Further on, the high-level control system connecting the low-level control system with the rest of the humanoid robot is presented. It provides grasp skills to the superior robot control system, coordinates movements of hand and arm and determines grasp patterns, depending on the object to grasp and the task to execute. Finally some preliminary results of the system, which is currently tested in simulations, will be presented.