Convergence of a spreading activation neural network with application of simulating aphasic naming errors in Finnish language

Aphasia is a language disorder caused by brain damage. Difficulties in word processing called anomia constitute the most common type of errors in aphasia. Naming errors are characteristic of aphasia and can be used to investigate the disorder. In this context, naming refers to a psycholinguistic test where the subject is asked to utter the names of target objects presented to him or her in the form of simple pictures. In the case of aphasia the subject may name objects presented or concepts incorrectly by word blends (e.g. semantic error to say “right” for “left”) or even forming nonwords (words without sensible meaning). Previously [[Reference to 5], [Reference to 6], [Reference to 8], [Reference to 10] and [Reference to 11]], we have constructed a simulation technique with a spreading activation algorithm to model the mental word processing of an aphasic by employing a succession of four neural networks with semantic, phonological, syllabic and phonemic processing functions, respectively. Treating words and their component parts as textual units, naming errors are generated in the system by spreading activation in the networks. In this paper we study the convergence properties of the algorithms which are used for spreading activation in these networks. Convergence shows which component parts dominate other parts in the networks employed. It can be reasonable also in the psycholinguistic sense, at least concerning the so-called perseveration in which some word or sound is repeated being unable to form a correct word. To enable to predict and control the behaviour of the model the convergence property is useful to understand.     

Finite element analysis of the Girkmann problem using the modern hp-version and the classical h-version

We perform finite element analysis of the so called Girkmann problem in structural mechanics. The problem involves an axially symmetric spherical shell stiffened with a foot ring and is approached (1) by using the axisymmetric formulation of linear elasticity theory and (2) by using a dimensionally reduced shell-ring model. In the first approach the problem is solved with a fully automatic hp-adaptive finite element solver whereas the classical h-version of the finite element method is used in the second approach. We study the convergence behaviour of the different numerical models and show that accurate stress resultants can be obtained with both models by using effective post-processing formulas.     

A review and comparison of strategies for multi-step ahead time series forecasting based on the NN5 forecasting competition

Multi-step ahead forecasting is still an open challenge in time series forecasting. Several approaches that deal with this complex problem have been proposed in the literature but an extensive comparison on a large number of tasks is still missing. This paper aims to fill this gap by reviewing existing strategies for multi-step ahead forecasting and comparing them in theoretical and practical terms. To attain such an objective, we performed a large scale comparison of these different strategies using a large experimental benchmark (namely the 111 series from the NN5 forecasting competition). In addition, we considered the effects of deseasonalization, input variable selection, and forecast combination on these strategies and on multi-step ahead forecasting at large. The following three findings appear to be consistently supported by the experimental results: Multiple-Output strategies are the best performing approaches, deseasonalization leads to uniformly improved forecast accuracy, and input selection is more effective when performed in conjunction with deseasonalization.     

Comparison of load-balancing approaches for multipath connectivity

During past years, the so-called resource pooling principle in data networks has been studied more carefully. For example, the recent work on routing on the Internet over multiple paths and Multipath TCP both seek to make the best possible use of multiple connecting paths between two end points. In deployments where multiple users could share multiple paths, one of the very first questions that comes to mind is, should we schedule packets from the users on a per-flow or per-packet basis? In this paper we study networking scenarios in which several networks are connected to each other via multiple paths. We seek to understand how a multi-homed router should schedule packets and packet flows out towards other networks. Our primary interests are to study path utilization and analyze the bandwidth fairness of various approaches using different traffic loads.     

Thermochromic Furofurans. IV. Approach to the synthesis of bridgehead substituted furo[3,2-b]furans and side products of McMurry reactions

Substituted dihydroxystilbenes 2 are suitable starting materials for the synthesis of photochromic systems derived from 3 / 4 . Attempts to couple the naphthones 8a - 8e by the McMurry reaction with TiCl₃/LiAlH₄ yielded mainly reduction products such as 8f , g or 9 . However, the furofuran 3b was isolated when using the zinc–copper couple for reduction. The helicene 11 was formed as an unexpected by-product in the McMurry reaction of the pivaloylnaphthalene 8d .     

Oxidation of Potato Starch by Hydrogen Peroxide

Potato starch was oxidized by hydrogen peroxide in alkaline and acidic reaction conditions with copper, iron and tungstate catalysts in order to introduce carboxyl and carbonyl groups to the starch molecule. Carbonyl contents up to 6.6 per 100 glucose units could be obtained, whereas carboxyl content remained low (up to 1.4). Starch yields in the alkaline and acidic reactions were 90 and 99%, respectively. The molecular weight decreased markedly with the degree of oxidation, and was dependent on the catalyst used. Rheological measurements revealed that when the molecular weight of the moderately oxidized starch was high, a very firm gel (G' = 40kPa) was obtained with 25% starch concentration. When the degree of oxidation increased, the storage modulus G' decreased. The more the oxidized starch contained carbonyl groups, the higher was the gelatinization temperature.     

EXTRACTING CONTEXTUALIZED COMPLEX BIOLOGICAL EVENTS WITH RICH GRAPH‐BASED FEATURE SETS

We describe a system for extracting complex events among genes and proteins from biomedical literature, developed in context of the BioNLP’09 Shared Task on Event Extraction. For each event, the system extracts its text trigger, class, and arguments. In contrast to the approaches prevailing prior to the shared task, events can be arguments of other events, resulting in a nested structure that better captures the underlying biological statements. We divide the task into independent steps which we approach as machine learning problems. We define a wide array of features and in particular make extensive use of dependency parse graphs. A rule‐based postprocessing step is used to refine the output in accordance with the restrictions of the extraction task. In the shared task evaluation, the system achieved an F‐score of 51.95% on the primary task, the best performance among the participants. Currently, with modifications and improvements described in this article, the system achieves 52.86% F‐score on Task 1, the primary task, improving on its original performance. In addition, we extend the system also to Tasks 2 and 3, gaining F‐scores of 51.28% and 50.18%, respectively. The system thus addresses the BioNLP’09 Shared Task in its entirety and achieves the best performance on all three subtasks.     

A randomized approximation algorithm for computing bucket orders

We show that a simple randomized algorithm has an expected constant factor approximation guarantee for fitting bucket orders to a set of pairwise preferences.     

Software model checking is a rich research field

This introductory paper has been written for readers who know nothing about model checking but do know about software. Its aim is to present, almost without mathematical terms, the fundamental general approaches on which the papers in this Special Section build, and give an idea of what kind of contribution each paper makes. The main issues discussed are motivation for model checking, state spaces, and bounded model checking with sat solvers. Individual papers lead to discuss the following ideas: exploiting a distributed computing environment for model checking, constructing those states first that look most promising for eventually finding errors, only constructing a representative subset of states, the representation of contents of variables in an abstract way with approximation from below, and the use of more general solvers than sat solvers in bounded model checking.