Application of Artificial Intelligence Methods to Computer Design of Inorganic Compounds

In this paper the main problems for computer design of materials, which would have predefined properties, with the use of artificial intelligence methods are presented. The DB on inorganic compound properties and the system of DBs on materials for electronics with completely assessed information: phase diagram DB of material systems with semiconducting phases and DB on acousto-optical, electro-optical, and nonlinear optical properties are considered. These DBs are a source of information for data analysis. Using the DBs and artificial intelligence methods we have predicted thousands of new compounds in ternary, quaternary and more complicated chemical systems and estimated some of their properties (crystal structure type, melting point, homogeneity region etc.). The comparison of our predictions with experimental data, obtained later, showed that the average reliability of predicted inorganic compounds exceeds 80%. The perspectives of computational material design with the use of artificial intelligence methods are considered.

Formal Definition of Artificial Intelligence

* This publication is partially supported by the KT-DigiCult-Bg project.

Teaching Strategies and Ontologies for E-Learning

* The work is partially suported by Russian Foundation for Basic Studies (grant 02-01-00466).

Manuscript Digitization and Electronic Processing of Manuscripts in the Czech National Library

The paper informs about the history of manuscript digitization in the National Library of the Czech Republic as well as about other issues concerning processing of manuscripts. The main consequence of the massive digitization and record and/or full text processing is a paradigm shift leading to the digital history.

About the Journal of RAAI ”News of Artificial Intelligence”

Beginning from 1991, Russian (initially Soviet) Association for Artificial Intelligence (RAAI) publishes the own journal ‘News of Artificial Intelligence’. The journal is founded on the initiative of the famous specialist in the field of Artificial Intelligence (AI), the first president of Soviet Association for Artificial Intelligence, the academician of Russian Academy of Natural Science (RANS), doctor of technical sciences (d.t.s.), professor D.A. Pospelov, which from 1991 up to 2001 was its main editor.

Application of the Artificial Intelligence Algorithms with a Cognitive Graphic as a Tool for a System Analysis of Electrophysiological Processes

Summarizing the accumulated experience for a long time in the polyparametric cognitive modeling of different physiological processes (electrocardiogram, electroencephalogram, electroreovasogram and others) and the development on this basis some diagnostics methods give ground for formulating a new methodology of the system analysis in biology. The gist of the methodology consists of parametrization of fractals of electrophysiological processes, matrix description of functional state of an object with a unified set of parameters, construction of the polyparametric cognitive geometric model with artificial intelligence algorithms. The geometry model enables to display the parameter relationships are adequate to requirements of the system approach. The objective character of the elements of the models and high degree of formalization which facilitate the use of the mathematical methods are advantages of these models. At the same time the geometric images are easily interpreted in physiological and clinical terms. The polyparametric modeling is an object oriented tool possessed advances functional facilities and some principal features.

e-Learning, e-Practising and e-Tutoring: an Integrated Approach

In this paper is described a didactic methodology combining current e-learning methods and the support of Intelligent Agents technologies. The aim is to favor the synthesis among theoretical approach and based practical approach using the so-called Intelligent Agent, software that exploits the Artificial Intelligence and that operates as tutor, facilitating the consumers in the training operations. The paper illustrates how such new Intelligent Agent algorithm (IA) is used in the training of employees working in the transportation sector, thanks to the experience gained with the PARMENIDE project - Promoting Advanced Resources and Methodologies for New Teaching and Learning Solutions in Digital Education.

Premonitory urges and sensorimotor processing in Tourette syndrome

Most patients with Tourette syndrome report characteristic sensory experiences (premonitory urges) associated with the expression of tic symptoms. Despite the central role of these experiences to the clinical phenomenology of Tourette syndrome, little is known about their underlying brain processes. In the present article we present the results of a systematic literature review of the published studies addressing the pathophysiological mechanisms of premonitory urges. We identified some preliminary evidence for specific alterations in sensorimotor processing at both cortical and subcortical levels. A better insight into the brain correlates of premonitory urges could lead to the identification of new targets to treat the sensory initiators of tics in patients with Tourette syndrome. © 2013 - IOS Press and the authors. All rights reserved.

Classification of Paintings by Artist, Movement, and Indoor Setting Using MPEG-7 Descriptor Features

ACM Computing Classification System (1998): I.4.9, I.4.10.

Emotional intelligence and translation:a new bridge

This paper presents a case for the study of non-cognitive psychological processes in Translation Studies (TS). More specifically, it aims to highlight the value of studying the emotional intelligence (EI) of translators and interpreters. Firstly, the concept of EI is defined and a review of trait EI profiling is undertaken, with a focus on two recent studies that have relevance for TS. Secondly, recent research within TS and related disciplines that provides evidence of the value of studying the affective and emotional traits of translators and interpreters is discussed. The final section of this paper provides some recommendations for the study of EI in TS research to benefit the translation and interpreting community. It will be argued that investigating emotional intelligence is both necessary and desirable to gain a deeper understanding of translation and interpreting processes.

Reconciling OWL and non-monotonic rules for the semantic web

We propose a description logic extending SROIQ (the description logic underlying OWL 2 DL) and at the same time encompassing some of the most prominent monotonic and nonmonotonic rule languages, in particular Datalog extended with the answer set semantics. Our proposal could be considered a substantial contribution towards fulfilling the quest for a unifying logic for the Semantic Web. As a case in point, two non-monotonic extensions of description logics considered to be of distinct expressiveness until now are covered in our proposal. In contrast to earlier such proposals, our language has the "look and feel" of a description logic and avoids hybrid or first-order syntaxes. © 2012 The Author(s).

Trait emotional intelligence and translation:a study of professional translators

A study of 155 professional translators was carried out to examine the relationship between trait emotional intelligence (trait EI) and literary translation, job satisfaction and career success. Participants were surveyed and their answers were correlated with scores from an emotional intelligence measure, the TEIQue. The analysis revealed that literary and non-literary translators have different trait EI profiles. Some significant correlations were found between trait EI and the variables of job satisfaction, career success, and literary translation experience. This is the first study to examine the effect of EI on translator working practices. Findings illustrate that trait EI may be predictive of some aspects of translator behaviour and highlight the relevance of exploring the emotional intelligence of professional translators.

The relationship between spoken language and speech and nonspeech processing in children with autism:a magnetic event-related field study

It has been proposed that language impairments in children with Autism Spectrum Disorders (ASD) stem from atypical neural processing of speech and/or nonspeech sounds. However, the strength of this proposal is compromised by the unreliable outcomes of previous studies of speech and nonspeech processing in ASD. The aim of this study was to determine whether there was an association between poor spoken language and atypical event-related field (ERF) responses to speech and nonspeech sounds in children with ASD (n = 14) and controls (n = 18). Data from this developmental population (ages 6-14) were analysed using a novel combination of methods to maximize the reliability of our findings while taking into consideration the heterogeneity of the ASD population. The results showed that poor spoken language scores were associated with atypical left hemisphere brain responses (200 to 400 ms) to both speech and nonspeech in the ASD group. These data support the idea that some children with ASD may have an immature auditory cortex that affects their ability to process both speech and nonspeech sounds. Their poor speech processing may impair their ability to process the speech of other people, and hence reduce their ability to learn the phonology, syntax, and semantics of their native language.

Emotional intelligence and leadership in organizations: A meta-analytic test of process mechanisms

The present study—employing psychometric meta-analysis of 92 independent studies with sample sizes ranging from 26 to 322 leaders—examined the relationship between EI and leadership effectiveness. Overall, the results supported a linkage between leader EI and effectiveness that was moderate in nature (ρ = .25). In addition, the positive manifold of the effect sizes presented in this study, ranging from .10 to .44, indicate that emotional intelligence has meaningful relations with myriad leadership outcomes including effectiveness, transformational leadership, LMX, follower job satisfaction, and others. Furthermore, this paper examined potential process mechanisms that may account for the EI-leadership effectiveness relationship and showed that both transformational leadership and LMX partially mediate this relationship. However, while the predictive validities of EI were moderate in nature, path analysis and hierarchical regression suggests that EI contributes less than or equal to 1% of explained variance in leadership effectiveness once personality and intelligence are accounted for. ^