Local ISS of large-scale interconnections and estimates for stability regions

We consider interconnections of locally input-to-state stable (LISS) systems. The class of LISS systems is quite large, in particular it contains input-to-state stable (ISS) and integral input-to-state stable (iISS) systems.Local small-gain conditions both for LISS trajectory and Lyapunov formulations guaranteeing LISS of the composite system are provided in this paper. Notably, estimates for the resulting stability region of the composite system are also given. This in particular provides an advantage over the linearization approach, as will be discussed.     

On notions of regularity for data languages

With motivation from considerations in XML database theory and model checking, data strings have been introduced as an extension of finite alphabet strings which carry, at each position, a symbol and a data value from an infinite domain. Previous work has shown that it is difficult to come up with an expressive yet decidable automaton model for data languages. Recently, such a model, data automata, was introduced. This paper introduces a simpler but equivalent model and investigates its expressive power, algorithmic and closure properties, and some extensions.     

DYFRAM: dynamic fragmentation and replica management in distributed database systems

In distributed database systems, tables are frequently fragmented and replicated over a number of sites in order to reduce network communication costs. How to fragment, when to replicate and how to allocate the fragments to the sites are challenging problems that has previously been solved either by static fragmentation, replication and allocation, or based on a priori query analysis. Many emerging applications of distributed database systems generate very dynamic workloads with frequent changes in access patterns from different sites. In such contexts, continuous refragmentation and reallocation can significantly improve performance. In this paper we present DYFRAM, a decentralized approach for dynamic table fragmentation and allocation in distributed database systems based on observation of the access patterns of sites to tables. The approach performs fragmentation, replication, and reallocation based on recent access history, aiming at maximizing the number of local accesses compared to accesses from remote sites. We show through simulations and experiments on the DASCOSA distributed database system that the approach significantly reduces communication costs for typical access patterns, thus demonstrating the feasibility of our approach.     

Domain science and engineering from computer science to the sciences of informatics. Part I: Engineering

In this paper, we wish to advocate that departments of computer science put emphasis on teaching programming and software engineering based on formal methods; and more emphasis on research into formal methods for the trustworthy development of software. We also wish to advocate that the concepts of domain science and domain engineering become an indispensable part of the science of informatics and of software engineering.     

Optimal Sparse Matrix Dense Vector Multiplication in the I/O-Model

We study the problem of sparse-matrix dense-vector multiplication (SpMV) in external memory. The task of SpMV is to compute y:=Ax, where A is a sparse N×N matrix and x is a vector. We express sparsity by a parameter k, and for each choice of k consider the class of matrices where the number of nonzero entries is kN, i.e., where the average number of nonzero entries per column is k.     

Incremental Linear Discriminant Analysis Using Sufficient Spanning Sets and Its Applications

This paper presents an incremental learning solution for Linear Discriminant Analysis (LDA) and its applications to object recognition problems. We apply the sufficient spanning set approximation in three steps i.e. update for the total scatter matrix, between-class scatter matrix and the projected data matrix, which leads an online solution which closely agrees with the batch solution in accuracy while significantly reducing the computational complexity. The algorithm yields an efficient solution to incremental LDA even when the number of classes as well as the set size is large. The incremental LDA method has been also shown useful for semi-supervised online learning. Label propagation is done by integrating the incremental LDA into an EM framework. The method has been demonstrated in the task of merging large datasets which were collected during MPEG standardization for face image retrieval, face authentication using the BANCA dataset, and object categorisation using the Caltech101 dataset.     

Defining syntax-directed translations by tree bimorphisms

We introduce a class of tree bimorphisms that define exactly the translations performed by syntax-directed translation schemata. We also show that these “quasi-alphabetic” tree bimorphisms preserve recognizability, and that their class is closed under composition and inverses.     

Efficient search based on content similarity over self-organizing P2P networks

The advent of the World Wide Web has made an enormous amount of information available to everyone and the widespread use of digital equipment enables end-users (peers) to produce their own digital content. This vast amount of information requires scalable data management systems. Peer-to-peer (P2P) systems have so far been well established in several application areas, with file-sharing being the most prominent. The next challenge that needs to be addressed is (more complex) data sharing, management and query processing, thus facilitating the delivery of a wide spectrum of novel data-centric applications to the end-user, while providing high Quality-of-Service. In this paper, we propose a self-organizing P2P system that is capable to identify peers with similar content and intentionally assign them to the same super-peer. During content retrieval, fewer super-peers need to be contacted and therefore efficient similarity search is supported, in terms of reduced network traffic and contacted peers. Our approach increases the responsiveness and reliability of a P2P system and we demonstrate the advantages of our approach using large-scale simulations.     

Musculoskeletal complaints among nurses related to patient handling tasks and psychosocial factors--based on logbook registrations

The aims were to evaluate the inter-method reliability of a registration sheet for patient handling tasks, to study the day-to-day variation of musculoskeletal complaints (MSC) and to examine whether patient handling tasks and psychosocial factors were associated with MSC.Nurses (n = 148) fulfilled logbooks for three consecutive working days followed by a day off. Low back pain (LBP), neck/shoulder pain (NSP), knee pain (KP), psychosocial factors (time pressure, stress, conscience of the quality of work) and patient transfers and care tasks were reported.The logbook was reliable for both transfer and care tasks. The numbers of nurses reporting MSC and the level of pain increased significantly during the three working days (15%-30% and 17%-37%, respectively) and decreased on the day off. Stress and transfer task were associated with LPB and transfer tasks were associated with KP.Our results confirm a relationship between work factors and MSC and indicate that logs could be one way to obtain a better understanding of the complex interaction of various nursing working conditions in relation to MSC.