Search

The valuation of Flexible Manufacturing Systems is one of the most frequently undertaken productivity improvement activities. In practice, the introduction of an FMS into industry must be done on the basis of cost justification. Recently developed techniques for the evaluation of the value of flexibility typically include the computation of stochastic dynamic programs. However, the computational effort of stochastic dynamic programs grows combinatorially and limits application to real world problems. In this contribution we derive fast approximations to the stochastic dynamic program and compare their results to the exact solution. The proposed methods show an excellent worst case behavior (1%) for a wide range of volatility of the underlying stochastic profit margins and costs for switching the production mode. The computational effort is reduced by a factor of more than 200.

We provide some new necessary and sufficient conditions which guarantee arbitrary pole placement of a particular linear system over the complex numbers. We exhibit a non-trivial real linear system which is not controllable by real static output feedback and discuss a conjecture from algebraic geometry concerning the existence of real linear systems for which all static feedback laws are real.

In computational linguistics, we are often interested in developing grammar formalisms declaratively. However, tractability often becomes a problem then. Therefore, we want to argue for the use of constraint logic programming (CLP), and it is yet interesting to note that most logic based natural language systems have not attempted to employ CLP. Our framework and the prototype system UBS combines logic programming with constraint domains (e.g. typed feature structures and finite sets) and constraint techniques (e.g. coroutining).

In this note we show that the geometric quotient, under a natural group action, of the generalized state space systems recently considered by Schumacher, Kuijper and Geerts is algebraically isomorphic to the space of a homogeneous autoregressive system. This result essentially follows from work of Stromme published earlier in the algebraic geometry literature. In particular, these generalized state space systems represent a realization of the space of homogeneous autoregressive systems.

We provide a lower bound for the minimal order of a compensator which can se stabilize a generic real m- input , p- output linear system of degree n . In addition we show that the complex systems of degree n are generically stabilizable with a complex compensator of degree at most q if and only if they are generically pole assignable.

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch), The control of compliant robots is, due to their often nonlinear and complex dynamics, inherently difficult. The vision of morphological computation proposes to view these aspects not only as problems, but rather also as parts of the solution. Non-rigid body parts are not seen anymore as imperfect realizations of rigid body parts, but rather as potential computational resources. The applicability of this vision has already been demonstrated for a variety of complex robot control problems. Nevertheless, a theoretical basis for understanding the capabilities and limitations of morphological computation has been missing so far. We present a model for morphological computation with compliant bodies, where a precise mathematical characterization of the potential computational contribution of a complex physical body is feasible. The theory suggests that complexity and nonlinearity, typically unwanted properties of robots, are desired features in order to provide computational power. We demonstrate that simple generic models of physical bodies, based on mass-spring systems, can be used to implement complex nonlinear operators. By adding a simple readout (which is static and linear) to the morphology such devices are able to emulate complex mappings of input to output streams in continuous time. Hence, by outsourcing parts of the computation to the physical body, the difficult problem of learning to control a complex body, could be reduced to a simple and perspicuous learning task, which can not get stuck in local minima of an error function.

The ShanghAI Lectures project contributes to the fundamental goal of making education and knowledge accessible to a broad interdisciplinary and intercultural audience. Deploying state-of-the-art videoconferencing technology and three-dimensional virtual environments, the project enables students and researchers from all around the globe to learn and work together.

Many applications operate on time-"sensitive" data. Some of these data are only valid for certain intervals (e.g., job-assignments, versions of software code), others describe temporal events that happened at certain points in time (e.g., a person's birthday). Until recently, the only way to incorporate time into Semantic Web models was as a data type property. Temporal RDF, however, considers time as an additional dimension in data preserving the semantics of time. In this paper we present a syntax and storage format based on named graphs to express temporal RDF. Given the restriction to preexisting RDF-syntax, our approach can perform any temporal query using standard SPARQL syntax only. For convenience, we introduce a shorthand format called *** -SPARQL for temporal queries and show how *** -SPARQL queries can be translated to standard SPARQL. Additionally, we show that, depending on the underlying data's nature, the temporal RDF approach vastly reduces the number of triples by eliminating redundancies resulting in an increased performance for processing and querying. Last but not least, we introduce a new indexing approach method that can significantly reduce the time needed to execute time point queries (e.g., what happened on January 1st).

In Silico Clinical Trials (ISCT), i.e., clinical experimental campaigns carried out by means of computer simulations, hold the promise to decrease time and cost for the safety and efficacy assessment of pharmacological treatments, reduce the need for animal and human testing, and enable precision medicine.In this paper we present a case study aiming at quantifying, by means of a multi-arm ISCT supervised by intelligent search, the potential impact of precision medicine approaches on a real pharmacological treatment, namely the downregulation phase of a complex clinical protocol for assisted reproduction.

In vivo imaging of the cardiac 3D fibre architecture is still a challenge, but it would have many clinical applications, for instance to better understand pathologies and to follow up remodelling after therapy. Recently, cardiac MRI enabled the acquisition of Diffusion Tensor images (DTI) of 2D slices. We propose a method for the complete 3D reconstruction of cardiac fibre architecture in the left ventricular myocardium from sparse in vivo DTI slices. This is achieved in two steps. First we map non-linearly the left ventricular geometry to a truncated ellipsoid. Second, we express coordinates and tensor components in Prolate Spheroidal System, where an anisotropic Gaussian kernel regression interpolation is performed. The framework is initially applied to a statistical cardiac DTI atlas in order to estimate the optimal anisotropic bandwidths. Then, it is applied to in vivo beating heart DTI data sparsely acquired on a healthy subject. Resulting in vivo tensor field shows good correlation with literature, especially the elevation (helix) angle transmural variation. To our knowledge, this is the first reconstruction of in vivo human 3D cardiac fibre structure. Such approach opens up possibilities in terms of analysis of the fibre architecture in patients.

In event pattern matching, various selection strategies have been proposed to impose additional constraints on the events that participate in a match. The skip-till-next-match selection strategy is used in scenarios where some incoming events are noise and therefore should be ignored. Skip-till-next-match is prone to blocking noise, i.e., noise that prevents the detection of matches. In this paper, we propose the robust skip-till-next-match selection strategy, which is robust against noise and finds matches that are missed by skip-till-next-match when blocking noise occurs in the input stream. To implement the new strategy in automaton-based pattern matching algorithms, we propose a backtracking mechanism. Extensive experiments using real-world data and different event pattern matching algorithms show that with skip-till-next-match the number of matches not detected due to blocking noise can be substantial, and that our backtracking mechanism outperforms alternative solutions that first produce a superset of the result followed by a post processing step to filter out non-compliant matches.

Business Intelligence solutions, encompassing technologies such as multi-dimensional data modeling and aggregate query processing, are being applied increasingly to non-traditional data. This paper extends multi-dimensional aggregation to apply to data with associated interval values that capture when the data hold. In temporal databases, intervals typically capture the states of reality that the data apply to, or capture when the data are, or were, part of the current database state. This paper proposes a new aggregation operator that addresses several challenges posed by interval data. First, the intervals to be associated with the result tuples may not be known in advance, but depend on the actual data. Such unknown intervals are accommodated by allowing result groups that are specified only partially. Second, the operator contends with the case where an interval associated with data expresses that the data holds for each point in the interval, as well as the case where the data holds only for the entire interval, but must be adjusted to apply to sub-intervals. The paper reports on an implementation of the new operator and on an empirical study that indicates that the operator scales to large data sets and is competitive with respect to other temporal aggregation algorithms.

We present a new access control mechanism for P2P networks with distributed enforcement, called P2P Access Control System (PACS). PACS enforces powerful access control models like RBAC with administrative delegation inside a P2P network in a pure P2P manner, which is not possible in any of the currently used P2P access control mechanisms. PACS uses client-side enforcement to support the replication of confidential data. To avoid a single point of failure at the time of privilege enforcement, we use threshold cryptography to distribute the enforcement among the participants. Our analysis of the expected number of messages and the computational effort needed in PACS shows that its increased flexibility comes with an acceptable additional overhead.

Since its introduction some twenty years ago, named entity (NE) processing has become an essential component of virtually any text mining application and has undergone major changes. Recently, two main trends characterise its developments: the adoption of deep learning architectures and the consideration of textual material originating from historical and cultural heritage collections. While the former opens up new opportunities, the latter introduces new challenges with heterogeneous, historical and noisy inputs. If NE processing tools are increasingly being used in the context of historical documents, performance values are below the ones on contemporary data and are hardly comparable. In this context, this paper introduces the CLEF 2020 Evaluation Lab HIPE (Identifying Historical People, Places and other Entities) on named entity recognition and linking on diachronic historical newspaper material in French, German and English. Our objective is threefold: strengthening the robustness of existing approaches on non-standard inputs, enabling performance comparison of NE processing on historical texts, and, in the long run, fostering efficient semantic indexing of historical documents in order to support scholarship on digital cultural heritage collections.

This paper introduces a method to predict and analyse students' mathematical performance by detecting distinguishable subgroups of children who share similar learning patterns. We employ pairwise clustering to analyse a comprehensive dataset of user interactions obtained from a computer-based training system. The available data consist of multiple learning trajectories measured from children with developmental dyscalculia, as well as from control children. Our online classification algorithm allows accurate assignment of children to clusters early in the training, enabling prediction of learning characteristics. The included results demonstrate the high predictive power of assignments of children to subgroups, and the significant improvement in prediction accuracy for short- and long-term performance, knowledge gaps, overall training achievements, and scores of further external assessments.

AceWiki is a prototype that shows how a semantic wiki using controlled natural language - Attempto Controlled English (ACE) in our case - can make ontology management easy for everybody. Sentences in ACE can automatically be translated into first-order logic, OWL, or SWRL. AceWiki integrates the OWL reasoner Pellet and ensures that the ontology is always consistent. Previous results have shown that people with no background in logic are able to add formal knowledge to AceWiki without being instructed or trained in advance.

Despite many efforts, balance control of humanoid robots in the presence of unforeseen external or internal forces has remained an unsolved problem. The difficulty of this problem is a consequence of the high dimensionality of the action space of a humanoid robot, due to its large number of degrees of freedom (joints), and of non-linearities in its kinematic chains. Biped biological organisms face similar difficulties, but have nevertheless solved this problem. Experimental data reveal that many biological organisms reduce the high dimensionality of their action space by generating movements through linear superposition of a rather small number of stereotypical combinations of simultaneous movements of many joints, to which we refer as kinematic synergies in this paper. We show that by constructing two suitable non-linear kinematic synergies for the lower part of the body of a humanoid robot, balance control can in fact be reduced to a linear control problem, at least in the case of relatively slow movements. We demonstrate for a variety of tasks that the humanoid robot HOAP-2 acquires through this approach the capability to balance dynamically against unforeseen disturbances that may arise from external forces or from manipulating unknown loads.

Sustainability, the capacity to endure, is fundamental for the societies on our planet. Despite its increasing recognition in software engineering, it remains difficult to assess the delayed systemic effects of decisions taken in requirements engineering and systems design. To support this difficult task, this paper introduces the concept of sustainability debt. The metaphor helps in the discovery, documentation, and communication of sustainability issues in requirements engineering. We build on the existing metaphor of technical debt and extend it to four other dimensions of sustainability to help think about sustainability-aware software systems engineering. We highlight the meaning of debt in each dimension and the relationships between those dimensions. Finally, we discuss the use of the metaphor and explore how it can help us to design sustainability-aware software intensive systems.

In this paper we compare two approaches to model the vague German spatial relation in der Nähe von (English: ”close to”) to enable its usage in (semantic) web searches. A user wants for example to find all relevant documents regarding parks or forestal landscapes close to a city. The problem is that there are no clear metric distance limits for possibly matching places because they are only restricted via the vague natural language expression. And since human perception does not work only in distances we can’t handle the queries simply with metric distances. Our first approach models the meaning of these expressions in description logics using relations of the Region Connection Calculus. A formalism has been developed to find all instances that are potentially perceived as close to. The second approach deals with the idea that everything that can be reached in a reasonable amount of time with a given means of transport (e.g. car) is potentially perceived as close. This approach uses route calculations with a route planner. The first approach has already been evaluated. The second is still under development. But we can already show a correlation between what people consider as close to and time needed to get there.

Erworben im Rahmen der Schweizer Nationallizenzen (www.nationallizenzen.ch), The generation of robust periodic movements of complex nonlinear robotic systems is inherently difficult, especially, if parts of the robots are compliant. It has previously been proposed that complex nonlinear features of a robot, similarly as in biological organisms, might possibly facilitate its control. This bold hypothesis, commonly referred to as morphological computation, has recently received some theoretical support by Hauser et al. We show in this article that this theoretical support can be extended to cover not only the case of fading memory responses to external signals, but also the essential case of autonomous generation of adaptive periodic patterns, as, e.g., needed for locomotion. The theory predicts that feedback into the morphological computing system is necessary and sufficient for such tasks, for which a fading memory is insufficient. We demonstrate the viability of this theoretical analysis through computer simulations of complex nonlinear mass-spring systems that are trained to generate a large diversity of periodic movements by adapting the weights of a simple linear feedback device. Hence, the results of this article substantially enlarge the theoretically tractable application domain of morphological computation in robotics, and also provide new paradigms for understanding control principles of biological organisms.

This work is supported by the Royal Society grant IE120643. The authors thank Floris Heim from University of Zurich for data collection. JV and UD are supported by the EU FP7 Marie Curie ITN GEOCROWD (FP7-PEOPLE-2010-ITN-264994) Eye movement analysis can provide insights into the cognitive processes in human mind and have been successfully utilized to study visual tasks such as reading and exploration of digital displays. However recording eye movements requires costly equipment and the face-to-face individual data collection forces us to work with only a limited number of participants. Interactive displays are alternatively evaluated through mouse movements which can be collected considerably easier than eye movements. It is however an open question if and how these two types of movement are linked. In this project, we study the link between eye and mouse movements to understand the eye-hand coordination specifically with visual search tasks in geographic displays. Publisher PDF

Large amounts of technical documentation are available in machine readable form, however there is a lack of effective ways to access them. In this paper we propose an approach based on linguistic techniques, geared towards the creation of a domain-specific Knowledge Base, starting from the available technical documentation.

Background The biomedical domain is witnessing a rapid growth of the amount of published scientific results, which makes it increasingly difficult to filter the core information. There is a real need for support tools that 'digest' the published results and extract the most important information. Results We describe and evaluate an environment supporting the extraction of domain-specific relations, such as protein-protein interactions, from a richly-annotated corpus. We use full, deep-linguistic parsing and manually created, versatile patterns, expressing a large set of syntactic alternations, plus semantic ontology information. Conclusion The experiments show that our approach described is capable of delivering high-precision results, while maintaining sufficient levels of recall. The high level of abstraction of the rules used by the system, which are considerably more powerful and versatile than finite-state approaches, allows speedy interactive development and validation.