The relationship between student-centred lectures, emotional intelligence, and study teams:a social telemetry study with mobile telephony

A student-centred approach to teaching has been conceptualized as a key driver in higher education to facilitate understanding of concepts and improve attainment. The occurrence of student study team behaviours is diagnostic of this approach to teaching. However, the extent to which team behaviours are performed outside the parameters of formal teacher-learner environments remains under-researched. This is problematic as it is unclear whether study teams are maintained outside the confines of lectures, and the extent to which they impact on individual student grades. A naturalistic observational study was carried out that utilized short message text service communication as a means to record the frequency of team behaviours within informal environments. The findings suggest the frequency of team behaviours: 1) were positively associated with student grades; 2) increased after lectures independently rated as low in employing a student-centred focus; and 3) were facilitated by students' trait emotional intelligence.

Application of the Artificial Intelligence Algorithms for System Analysis of Multi Dimension Physiological Data for Developing Polyparametric Information System of Public Health Diagnostics

The polyparametric intelligence information system for diagnostics human functional state in medicine and public health is developed. The essence of the system consists in polyparametric describing of human functional state with the unified set of physiological parameters and using the polyparametric cognitive model developed as the tool for a system analysis of multitude data and diagnostics of a human functional state. The model is developed on the basis of general principles geometry and symmetry by algorithms of artificial intelligence systems. The architecture of the system is represented. The model allows analyzing traditional signs - absolute values of electrophysiological parameters and new signs generated by the model – relationships of ones. The classification of physiological multidimensional data is made with a transformer of the model. The results are presented to a physician in a form of visual graph – a pattern individual functional state. This graph allows performing clinical syndrome analysis. A level of human functional state is defined in the case of the developed standard (“ideal”) functional state. The complete formalization of results makes it possible to accumulate physiological data and to analyze them by mathematics methods.

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.

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.

Intelligence Algorithms for Increasing Navigation Systems Accuracy

Application of neural network algorithm for increasing the accuracy of navigation systems are showing. Various navigation systems, where a couple of sensors are used in the same device in different positions and the disturbances act equally on both sensors, the trained neural network can be advantageous for increasing the accuracy of system. The neural algorithm had used for determination the interconnection between the sensors errors in two channels to avoid the unobservation of navigation system. Representation of thermal error of two- component navigation sensors by time model, which coefficients depend only on parameters of the device, its orientations relative to disturbance vector allows to predict thermal errors change, measuring the current temperature and having identified preliminary parameters of the model for the set position. These properties of thermal model are used for training the neural network and compensation the errors of navigation system in non- stationary thermal fields.

Systemological Bases of Business Intelligence

Sustainable development support, balanced scorecard development and business process modeling are viewed from the position of systemology. Extensional, intentional and potential properties of a system are considered as necessary to satisfy functional requirements of a meta-system. The correspondence between extensional, intentional and potential properties of a system and sustainable, unsustainable, crisis and catastrophic states of a system is determined. The inaccessibility cause of the system mission is uncovered. The correspondence between extensional, intentional and potential properties of a system and balanced scorecard perspectives is showed. The IDEF0 function modeling method is checked against balanced scorecard perspectives. The correspondence between balanced scorecard perspectives and IDEF0 notations is considered.

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.

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.

The New Science Intensive Standard of Master Preparation in Sphere of Competitive Intelligence on the Basis of Systemological Knowledge-Oriented Technologies

Methodological, theoretical and technological bases of the new branch standard of Ukraine higher education which regulates preparation process of masters - professionals in the information area and information analysts are considered. The new systemological knowledge-oriented technologies developed in KNURE which considerably surpass foreign analogues are put as the basis of training.

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.

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.

Az információterjedés szerepe az innováció-elfogadásban. Az okostelefonok és az on-line kollektív intelligencia (Role of informationspread in the innovation acceptance: the smart phones and the online collective intelligence)

A tanulmány célja az innováció-terjedés marketingvonzatú irodalmának bemutatása, valamint betekintés az exploratív tartalomelemzés módszerével az informális, kollektív intelligenciát generáló on-line felületek, nevesül a blogok és fórumok kutathatóságába. Az okostelefonok innováció-elfogadásának példáján keresztül a szerzők megpróbálják felderíteni az információterjedés elméletének megvalósulását az elemzett felületeken. Bemutatnak három, a mintára jellemző információterjedési és felvett szerep mintát, melyek alapul szolgálhatnak a további célirányú kutatások számára. / === / Adaptive smart phones that give space for user-added functions create active online discussions. Committed users are ready to share information, advise others, while less expert users seek this information. In their paper the authors show that related user-generated content i.e. blogs and bulletin boards provide a rich data source for analysis, which gives them the opportunity to further elaborate on the diffusion of information in the case of smart phone usage among online Hungarian users. Online collective intelligence may well contribute to the diffusion of innovations through diffusing information. Following a thorough review on the literature on the diffusion of innovations, in their exploratory content analysis, they found two categories of users on the analyzed boards: a first group we dubbed "experts" (corresponding to innovators in Bass's typology) that made a special effort trying to solve particular problems thus contributing to collective intelligence, thus reducing (among others) the perceived complexity of these phones and adding to their trialability, both factors influencing users' innovation acceptance, and a second group, "simple users" (or imitators in Bass's typology), uninterested in product innovation, still asking questions and searching for solutions concerning extant technology. Manufacturers do not seem yet to regard these boards as a source of valuable data, even though these clearly serve as an important pool of information and a growing factor of decision for their potential customers.

Actionable pattern analysis in computing and business intelligence systems

With advances in science and technology, computing and business intelligence (BI) systems are steadily becoming more complex with an increasing variety of heterogeneous software and hardware components. They are thus becoming progressively more difficult to monitor, manage and maintain. Traditional approaches to system management have largely relied on domain experts through a knowledge acquisition process that translates domain knowledge into operating rules and policies. It is widely acknowledged as a cumbersome, labor intensive, and error prone process, besides being difficult to keep up with the rapidly changing environments. In addition, many traditional business systems deliver primarily pre-defined historic metrics for a long-term strategic or mid-term tactical analysis, and lack the necessary flexibility to support evolving metrics or data collection for real-time operational analysis. There is thus a pressing need for automatic and efficient approaches to monitor and manage complex computing and BI systems. To realize the goal of autonomic management and enable self-management capabilities, we propose to mine system historical log data generated by computing and BI systems, and automatically extract actionable patterns from this data. This dissertation focuses on the development of different data mining techniques to extract actionable patterns from various types of log data in computing and BI systems. Four key problems—Log data categorization and event summarization, Leading indicator identification , Pattern prioritization by exploring the link structures , and Tensor model for three-way log data are studied. Case studies and comprehensive experiments on real application scenarios and datasets are conducted to show the effectiveness of our proposed approaches.

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. ^