825 resultados para Crystallized intelligence


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

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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. ^

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The purpose of this study was to determine if higher academic performance was positively correlated to higher emotional intelligence among traditional age male and female college students enrolled in an Introduction to Business course at a large multi-campus state college in Florida. The Bar-On 2004 (Emotional Quotient Inventory) EQ-i 133-item inventory was used to assess students’ emotional intelligence. Within the scope of this ex-post facto study, a quasi-experimental design was included to further determine if emotional intelligence could be increased through the inclusion of a curricular component on emotional intelligence. Four groups of students (N=111) participated in the three-phase study over two semesters. The first phase (pre-intervention) was limited to students with an established GPA and an attempted-to-completed credit hour ratio within the institution (N=82). Results showed a slight positive correlation between the two factors and the students’ emotional intelligence pretest assessment scores. The second phase of the study involved establishing a control and an experimental group in each of two semesters to compare the attainment of overall emotional intelligence scores as measured by the EQ-i. The third phase of the study examined four measures of academic success (GPA, the attempted-to-completed credit hour ratio, grade in the business course, and persistence in college) to determine if these factors were positively correlated with the students’ posttest EQ-i scores. The study also included a research question to determine if significant differences in overall EQ-i scores existed between male and female students during the three phases. Findings from the study indicated that (a) there was a slight positive correlation in the pre-intervention stage between emotional intelligence and traditional measures of academic success specifically, GPA and the attempted-to-completed credit hour ratio; (b) curricular intervention made a significant difference at the p <.05 level, with an .5 effect size, in one semester but failed to meet that threshold in the following semester with the second pair of groups; (c) at the post-intervention phase, the four measures of traditional academic success yielded a low positive correlation with the students’ emotional intelligence assessment scores, and (d) female students showed significant gains in their overall EQ-i scores.

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This pilot study explored the relationship between emotional intelligence and organizational commitment among provate club board and committee volunteer members. The top three items, ranked by mean scores, of each of three EI dimensions -- IN, OUT, and RELATIONSHIPS wer discussed. A sample of 57 volunteer leaders furhter was split into high EI and low EI groups based on respndents' overall EO median score. Statistical differences between high and low EI groups in three aspects of organizational commitment - affective, continuance, and normative commitment - wer present. 4 t-test results showed that the difference between high and low EI groups in affective commitment among private club volunteer leaders was statistcally significant at p <.05.

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The authors report the pilot study focused on identifying the emotional intelligence (El) of leaders in the automatic merchandising and coffee service industries. The data were collected from 39 executives, members of National Automatic Merchandising Association (NM), who attended 2005 Executive Development Program on the campus of Michigan State University. Three elements of EI- IN, OUT, RELATIONSHIP for these leaders are discussed.