Approaches to Sequence Similarity Representation

We discuss several approaches to similarity preserving coding of symbol sequences and possible connections of their distributed versions to metric embeddings. Interpreting sequence representation methods with embeddings can help develop an approach to their analysis and may lead to discovering useful properties.

Ontological Approach to Domain Knowledge Representation for Information Retrieval in Multiagent Systems

An ontological representation of buyer interests’ knowledge in process of e-commerce is proposed to use. It makes it more efficient to make a search of the most appropriate sellers via multiagent systems. An algorithm of a comparison of buyer ontology with one of e-shops (the taxonomies) and an e-commerce multiagent system are realised using ontology of information retrieval in distributed environment.

Representation of Neural Networks by Dynamical Systems

Representation of neural networks by dynamical systems is considered. The method of training of neural networks with the help of the theory of optimal control is offered.

The Use of Situation Representation when Searching for Solutions in Computer Aided Design Systems

Projects solutions reuse methodology is offered for software development. The main idea consists in connection of the system objective with the situation using the entities which describe the condition of the system in the process of the objective statement. Every situation is associated with one or several design solutions, which can be used at the development. Based on this connection the situation representing language has been created, it lets to express a problem situation using a natural language describe. The similarity measure has been built to compare situations, it is based on the similarity coefficients with adding the absent part weight.

On the F word:a corpus-based analysis of the media representation of feminism in British and German press discourse, 1990-2009

Research in social psychology has shown that public attitudes towards feminism are mostly based on stereotypical views linking feminism with leftist politics and lesbian orientation. It is claimed that such attitudes are due to the negative and sexualised media construction of feminism. Studies concerned with the media representation of feminism seem to confirm this tendency. While most of this research provides significant insights into the representation of feminism, the findings are often based on a small sample of texts. Also, most of the research was conducted in an Anglo-American setting. This study attempts to address some of the shortcomings of previous work by examining the discourse of feminism in a large corpus of German and British newspaper data. It does so by employing the tools of Corpus Linguistics. By investigating the collocation profiles of the search term feminism, we provide evidence of salient discourse patterns surrounding feminism in two different cultural contexts. © The Author(s) 2012.

Peculiar body representation alterations in hemineglect:a case report

We report the case of FP affected by personal and extrapersonal neglect and a body representation deficit characterized by delusional ideas. When FP performed the human figure, he placed body parts to the left, despite his extrapersonal neglect. Differently, when he performed the car figure, he placed all parts to the right, in line with his deficit. Comparing FP with a small patient group with the same clinical features without delusional ideas about body emerged that he was the only one to suffer from a specific body representation deficit characterized by a lack of body ownership sense.

Normal ECG Recognition for Express-Diagnostics Based on Scale-Space Representation and Dynamic Matching

A novel approach of normal ECG recognition based on scale-space signal representation is proposed. The approach utilizes curvature scale-space signal representation used to match visual objects shapes previously and dynamic programming algorithm for matching CSS representations of ECG signals. Extraction and matching processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.

Emotions and a Prior Knowledge Representation in Artificial General Intelligence

In this paper a prior knowledge representation for Artificial General Intelligence is proposed based on fuzzy rules using linguistic variables. These linguistic variables may be produced by neural network. Rules may be used for generation of basic emotions – positive and negative, which influence on planning and execution of behavior. The representation of Three Laws of Robotics as such prior knowledge is suggested as highest level of motivation in AGI.

Ontology-Based Model of Representation of Knowledge about Language Mappings

The paper presents a short review of some systems for program transformations performed on the basis of the internal intermediate representations of these programs. Many systems try to support several languages of representation of the source texts of programs and solve the task of their translation into the internal representation. This task is still a challenge as it is effort-consuming. To reduce the effort, different systems of translator construction, ready compilers with ready grammars of outside designers are used. Though this approach saves the effort, it has its drawbacks and constraints. The paper presents the general idea of using the mapping approach to solve the task within the framework of program transformations and overcome the disadvantages of the existing systems. The paper demonstrates a fragment of the ontology model of high-level languages mappings onto the single representation and gives the example of how the description of (a fragment) a particular mapping is represented in accordance with the ontology model.

Improving distributed representation of word sense via WordNet Gloss composition and context clustering

In recent years, there has been an increas-ing interest in learning a distributed rep-resentation of word sense. Traditional context clustering based models usually require careful tuning of model parame-ters, and typically perform worse on infre-quent word senses. This paper presents a novel approach which addresses these lim-itations by first initializing the word sense embeddings through learning sentence-level embeddings from WordNet glosses using a convolutional neural networks. The initialized word sense embeddings are used by a context clustering based model to generate the distributed representations of word senses. Our learned represen-tations outperform the publicly available embeddings on 2 out of 4 metrics in the word similarity task, and 6 out of 13 sub tasks in the analogical reasoning task.

Automatic ECG Analysis for Preliminary and Detailed Diagnostics Based on Scale-space Representation

A novel approach of automatic ECG analysis based on scale-scale signal representation is proposed. The approach uses curvature scale-space representation to locate main ECG waveform limits and peaks and may be used to correct results of other ECG analysis techniques or independently. Moreover dynamic matching of ECG CSS representations provides robust preliminary recognition of ECG abnormalities which has been proven by experimental results.

Early predictors of phonological and morphological awareness and the link with reading:evidence from children with different patterns of early deficit

This study examines the contribution of early phonological processing (PP) and language skills on later phonological awareness (PA) and morphological awareness (MA), as well as the links among PA, MA, and reading. Children 4-6 years of age with poor PP at the start of school showed weaker PA and MA 3 years later (age 7-9), regardless of their language skills. PA and phonological and morphological strategies predict reading accuracy, whereas MA predicts reading comprehension. Our findings suggest that children with poor early PP are more at risk of developing deficits in MA and PA than children with poor language. They also suggest that there is a direct link between PA and reading accuracy and between MA and reading comprehension that cannot be accounted for by strategy use at the word level.

Method for Analytical Representation of the Maximum Inaccuracies of Indirectly Measurable Variable

Let us have an indirectly measurable variable which is a function of directly measurable variables. In this survey we present the introduced by us method for analytical representation of its maximum absolute and relative inaccuracy as functions, respectively, of the maximum absolute and of the relative inaccuracies of the directly measurable variables. Our new approach consists of assuming for fixed variables the statistical mean values of the absolute values of the coefficients of influence, respectively, of the absolute and relative inaccuracies of the directly measurable variables in order to determine the analytical form of the maximum absolute and relative inaccuracies of an indirectly measurable variable. Moreover, we give a method for determining the numerical values of the maximum absolute and relative inaccuracies. We define a sample plane of the ideal perfectly accurate experiment and using it we give a universal numerical characteristic – a dimensionless scale for determining the quality (accuracy) of the experiment.

Deconstructing phonological tasks:the contribution of stimulus and response type to the prediction of early decoding skills

Abstract Phonological tasks are highly predictive of reading development but their complexity obscures the underlying mechanisms driving this association. There are three key components hypothesised to drive the relationship between phonological tasks and reading; (a) the linguistic nature of the stimuli, (b) the phonological complexity of the stimuli, and (c) the production of a verbal response. We isolated the contribution of the stimulus and response components separately through the creation of latent variables to represent specially designed tasks that were matched for procedure. These tasks were administered to 570 6 to 7-year-old children along with standardised tests of regular word and non-word reading. A structural equation model, where tasks were grouped according to stimulus, revealed that the linguistic nature and the phonological complexity of the stimulus predicted unique variance in decoding, over and above matched comparison tasks without these components. An alternative model, grouped according to response mode, showed that the production of a verbal response was a unique predictor of decoding beyond matched tasks without a verbal response. In summary, we found that multiple factors contributed to reading development, supporting multivariate models over those that prioritize single factors. More broadly, we demonstrate the value of combining matched task designs with latent variable modelling to deconstruct the components of complex tasks.

AstroWeb – A Graphical Representation of an Astronomical WFPDB Database Using a Web-Based Open Source Geographical Information System

ACM Computing Classification System (1998): H.5.2, H.2.8, J.2, H.5.3.