932 resultados para inductive reasoning


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In the context of the digital business ecosystems, small organizations cooperate between them in order to achieve common goals or offer new services for expanding their markets. There are different approaches for these cooperation models such as virtual enterprises, virtual organizations or dynamic electronic institutions which in their lifecycle have in common a dissolution phase. However this phase has not been studied deeply in the current literature and it lacks formalization. In this paper a first approach for achieving and managing the dissolution phase is proposed, as well as a CBR process in order to support it in a multi-agent system

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The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious task of knowledge acquisition and representation needed by other reasoning techniques as expert systems. An outlook of CBR terminology and basic concepts are presented. The adaptation of CBR in performing expert supervisory tasks, taking into account the particularities and difficulties derived from dynamic systems, is discussed. A special interest is focused in proposing a general case definition suitable for supervisory tasks. Finally, this structure and the whole methodology is tested in a application example for monitoring a real drier chamber

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This paper shows the impact of the atomic capabilities concept to include control-oriented knowledge of linear control systems in the decisions making structure of physical agents. These agents operate in a real environment managing physical objects (e.g. their physical bodies) in coordinated tasks. This approach is presented using an introspective reasoning approach and control theory based on the specific tasks of passing a ball and executing the offside manoeuvre between physical agents in the robotic soccer testbed. Experimental results and conclusions are presented, emphasising the advantages of our approach that improve the multi-agent performance in cooperative systems

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In this study, 100 clinical isolates of Streptococcus agalactiae recovered from genitourinary tract specimens of non-pregnant individuals living in Rio de Janeiro were submitted for antimicrobial susceptibility testing, detection of macrolide resistance genes and evaluation of the genetic diversity of erythromycin-resistant isolates. By agar diffusion method, all isolates were susceptible to ceftazidime, penicillin and vancomycin. Isolates were resistant to levofloxacin (1%), clindamycin (5%), erythromycin (11%) and tetracycline (83%) and were intermediated to erythromycin (4%) and tetracycline (6%). Erythromycin-resistant and intermediated isolates presented the following phenotypes: M (n = 3), constitutive macrolide-lincosamide-streptogramin B (MLS B, n = 5) and inductive MLS B (n = 7). Determinants of macrolide resistance genes, erm and mef, were detected in isolates presenting MLS B and M phenotypes, respectively. Randomly amplified polymorphic DNA profiles of erythromycin-resistant isolates were clustered into two major groups of similarity.

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OBJECTIVES: Theory of mind (ToM) performance in aging and dementia of the Alzheimer type (DAT) has been a growing interest of researchers and recently, theoretical trends in ToM development have led to a focus on determining the cognitive skills involved in ToM performance. The aim of the present review is to answer three main questions: How is ToM assessed in aging and DAT? How does ToM performance evolve in aging and DAT? Do cognitive processes influence ToM performance in aging and DAT? METHOD: A systematic review was conducted to provide a targeted overview of recent studies relating ToM performance with cognitive processes in aging and DAT. RESULTS: RESULTS suggest a decrease in ToM performance, more pronounced in complex ToM tasks. Moreover, the review points up the strong involvement of executive functions, especially inhibition, and reasoning skills in ToM task achievement. CONCLUSION: Current data suggest that the structure of ToM tasks itself could lead to poor performance, especially in populations with reduced cognitive abilities.

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Monitor a distribution network implies working with a huge amount of data coining from the different elements that interact in the network. This paper presents a visualization tool that simplifies the task of searching the database for useful information applicable to fault management or preventive maintenance of the network

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A long-standing tradition in personality research in psychology, and nowadays increasingly in psychiatry, is that psychotic and psychotic-like thoughts are considered common experiences in the general population. Given their widespread occurrence, such experiences cannot merely reflect pathological functioning. Moreover, reflecting the multi-dimensionality of schizotypy, some dimensions might be informative for healthy functioning while others less so. Here, we explored these possibilities by reviewing research that links schizotypy to favourable functioning such as subjective wellbeing, cognitive functioning (major focus on creativity) and personality correlates. This research highlights the existence of healthy people with psychotic-like traits who mainly experience positive schizotypy (but also affective features mapping onto bipolar disorder). These individuals seem to benefit from a healthy way to organise their thoughts and experiences, i.e. they employ an adaptive cognitive framework to explain and integrate their unusual experiences. We conclude that, instead of focussing only on the pathological, future studies should explore the behavioural, genetic, imaging and psychopharmacological correlates that define the healthy expression of psychotic-like traits. Such studies would inform on protective or compensatory mechanisms of psychosis-risk and could usefully inform us on the evolutionary advantages of the psychosis dimension.

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BACKGROUND: This study assesses the benefits of an individualized therapy (RECOS program) compared with the more general cognitive remediation therapy (CRT). METHODS: 138 participants took part with 65 randomized to CRT and 73 to RECOS. In the RECOS group, participants were directed towards one of five training modules (verbal memory, visuo-spatial memory and attention, working memory, selective attention or reasoning) corresponding to their key cognitive concern whereas the CRT group received a standard program. The main outcome was the total score on BADS (Behavioural Assessment of Dysexecutive Syndrome) and the secondary outcomes were: cognition (executive functions; selective attention; visuospatial memory and attention; verbal memory; working memory) and clinical measures (symptoms; insight; neurocognitive complaints; self-esteem). All outcomes were assessed at baseline (T1), week 12 (posttherapy, T2), and follow-up (week 36, i.e., 6months posttherapy, T3). RESULTS: No difference was shown for the main outcome. A significant improvement was found for BADS' profile score for RECOS at T2 and T3, and for CRT at T3. Change in BADS in the RECOS and CRT arms were not significantly different between T1 and T2 (+0.86, p=0.108), or between T1 and T3 (+0.36, p=0.540). Significant improvements were found in several secondary outcomes including cognition (executive functions, selective attention, verbal memory, and visuospatial abilities) and clinician measures (symptoms and awareness to be hampered by cognitive deficits in everyday) in both treatment arms following treatment. Self-esteem improved only in RECOS arm at T3, and working memory improved only in CRT arm at T2 and T3, but there were no differences in changes between arms. CONCLUSIONS: RECOS (specific remediation) and CRT (general remediation) globally showed similar efficacy in the present trial.

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This paper introduces how artificial intelligence technologies can be integrated into a known computer aided control system design (CACSD) framework, Matlab/Simulink, using an object oriented approach. The aim is to build a framework to aid supervisory systems analysis, design and implementation. The idea is to take advantage of an existing CACSD framework, Matlab/Simulink, so that engineers can proceed: first to design a control system, and then to design a straightforward supervisory system of the control system in the same framework. Thus, expert systems and qualitative reasoning tools are incorporated into this popular CACSD framework to develop a computer aided supervisory system design (CASSD) framework. Object-variables an introduced into Matlab/Simulink for sharing information between tools

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Deduction allows us to draw consequences from previous knowledge. Deductive reasoning can be applied to several types of problem, for example, conditional, syllogistic, and relational. It has been assumed that the same cognitive operations underlie solutions to them all; however, this hypothesis remains to be tested empirically. We used event-related fMRI, in the same group of subjects, to compare reasoning-related activity associated with conditional and syllogistic deductive problems. Furthermore, we assessed reasoning-related activity for the two main stages of deduction, namely encoding of premises and their integration. Encoding syllogistic premises for reasoning was associated with activation of BA 44/45 more than encoding them for literal recall. During integration, left fronto-lateral cortex (BA 44/45, 6) and basal ganglia activated with both conditional and syllogistic reasoning. Besides that, integration of syllogistic problems additionally was associated with activation of left parietal (BA 7) and left ventro-lateral frontal cortex (BA 47). This difference suggests a dissociation between conditional and syllogistic reasoning at the integration stage. Our finding indicates that the integration of conditional and syllogistic reasoning is carried out by means of different, but partly overlapping, sets of anatomical regions and by inference, cognitive processes. The involvement of BA 44/45 during both encoding (syllogisms) and premise integration (syllogisms and conditionals) suggests a central role in deductive reasoning for syntactic manipulations and formal/linguistic representations.

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To detect directional couplings from time series various measures based on distances in reconstructed state spaces were introduced. These measures can, however, be biased by asymmetries in the dynamics' structure, noise color, or noise level, which are ubiquitous in experimental signals. Using theoretical reasoning and results from model systems we identify the various sources of bias and show that most of them can be eliminated by an appropriate normalization. We furthermore diminish the remaining biases by introducing a measure based on ranks of distances. This rank-based measure outperforms existing distance-based measures concerning both sensitivity and specificity for directional couplings. Therefore, our findings are relevant for a reliable detection of directional couplings from experimental signals.

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We propose an edge detector based on the selection of wellcontrasted pieces of level lines, following the proposal ofDesolneux-Moisan-Morel (DMM) [1]. The DMM edge detectorhas the problem of over-representation, that is, everyedge is detected several times in slightly different positions.In this paper we propose two modifications of the originalDMM edge detector in order to solve this problem. The firstmodification is a post-processing of the output using a generalmethod to select the best representative of a bundle of curves.The second modification is the use of Canny’s edge detectorinstead of the norm of the gradient to build the statistics. Thetwo modifications are independent and can be applied separately.Elementary reasoning and some experiments showthat the best results are obtained when both modifications areapplied together.

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The paper presents a competence-based instructional design system and a way to provide a personalization of navigation in the course content. The navigation aid tool builds on the competence graph and the student model, which includes the elements of uncertainty in the assessment of students. An individualized navigation graph is constructed for each student, suggesting the competences the student is more prepared to study. We use fuzzy set theory for dealing with uncertainty. The marks of the assessment tests are transformed into linguistic terms and used for assigning values to linguistic variables. For each competence, the level of difficulty and the level of knowing its prerequisites are calculated based on the assessment marks. Using these linguistic variables and approximate reasoning (fuzzy IF-THEN rules), a crisp category is assigned to each competence regarding its level of recommendation.

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The treatment of the recently ruptured Achilles tendon can be conservative or surgical. The conservative treatment may be carried out using either a static cast immobilisation or using a dynamic brace and an early functional rehabilitation. The surgical technique can be either open or mini-invasive. Neglected and ancient ruptures may need to be treated surgically by a tendinoplasty. There is an ongoing discussion about how to manage the recently ruptured Achilles tendon, especially since recent descriptions of conservative-functional treatment procedures and mini-invasive surgical techniques. We present the choice of the different treatment options and the clinical reasoning to identify the best adapted treatment for the individual patient. The ideal treatment option depends on the functional demand and the medical condition of the patient.

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The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.