21 resultados para Interdisciplinary approach to knowledge


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In this paper, we propose an adaptive approach to merging possibilistic knowledge bases that deploys multiple operators instead of a single operator in the merging process. The merging approach consists of two steps: one is called the splitting step and the other is called the combination step. The splitting step splits each knowledge base into two subbases and then in the second step, different classes of subbases are combined using different operators. Our approach is applied to knowledge bases which are self-consistent and the result of merging is also a consistent knowledge base. Two operators are proposed based on two different splitting methods. Both operators result in a possibilistic knowledge base which contains more information than that obtained by the t-conorm (such as the maximum) based merging methods. In the flat case, one of the operators provides a good alternative to syntax-based merging operators in classical logic.

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Knowledge is an important component in many intelligent systems.
Since items of knowledge in a knowledge base can be conflicting, especially if
there are multiple sources contributing to the knowledge in this base, significant
research efforts have been made on developing inconsistency measures for
knowledge bases and on developing merging approaches. Most of these efforts
start with flat knowledge bases. However, in many real-world applications, items
of knowledge are not perceived with equal importance, rather, weights (which
can be used to indicate the importance or priority) are associated with items of
knowledge. Therefore, measuring the inconsistency of a knowledge base with
weighted formulae as well as their merging is an important but difficult task. In
this paper, we derive a numerical characteristic function from each knowledge
base with weighted formulae, based on the Dempster-Shafer theory of evidence.
Using these functions, we are able to measure the inconsistency of the knowledge
base in a convenient and rational way, and are able to merge multiple knowledge
bases with weighted formulae, even if knowledge in these bases may be
inconsistent. Furthermore, by examining whether multiple knowledge bases are
dependent or independent, they can be combined in different ways using their
characteristic functions, which cannot be handled (or at least have never been
considered) in classic knowledge based merging approaches in the literature.

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AIMS: To estimate 1) the associations between parent-adolescent relationship, parental knowledge and subsequent adolescent drinking frequency and 2) the influence of alcohol use on parental knowledge.

DESIGN: Path analysis of school based cohort study with annual surveys SETTING: Post primary schools from urban and intermediate/rural areas in Northern Ireland PARTICIPANTS: 4,937 post primary school students aged around 11 years in 2000 followed until around age 16 in 2005.

MEASUREMENTS: Pupil reported measures of: frequency of alcohol use; parental-child relationship quality; sub-dimensions of parental monitoring: parental control, parental solicitation, child disclosure and child secrecy.

FINDINGS: Higher levels of parental control (Ordinal logistic OR 0.86 95% CI 0.78, 0.95) and lower levels of child secrecy (OR 0.83 95% CI 0.75 0.92) were associated with less frequent alcohol use subsequently. Parental solicitation and parent-child relationship quality were not associated with drinking frequency. Weekly alcohol drinking was associated with higher subsequent secrecy (Beta -0.42 95% CI -0.53, -0.32) and lower parental control (Beta -0.15 95% CI -0.26, -0.04). Secrecy was more strongly predictive of alcohol use at younger compared with older ages (P=0.02), and alcohol use was less strongly associated with parental control among families with poorer relationships (P=0.04).

CONCLUSIONS: Adolescent alcohol use appears to increase as parental control decreases and child secrecy increases. Greater parental control is associated with less frequent adolescent drinking subsequently, while parent-child attachment and parental solicitation have little influence on alcohol use. 

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In this paper, we propose a theoretical framework for the design of tangible interfaces for musical expression. The main insight for the proposed approach is the importance and utility of familiar sensorimotor experiences for the creation of engaging and playable new musical instruments. In particular, we suggest exploiting the commonalities between different natural interactions by varying the auditory response or tactile details of the instrument within certain limits. Using this principle, devices for classes of sounds such as coarse grain collision interactions or friction interactions can be designed. The designs we propose retain the familiar tactile aspect of the interaction so that the performer can take advantage of tacit knowledge gained through experiences with such phenomena in the real world.

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Polymer extrusion is a complex process and the availability of good dynamic models is key for improved system operation. Previous modelling attempts have failed adequately to capture the non-linearities of the process or prove too complex for control applications. This work presents a novel approach to the problem by the modelling of extrusion viscosity and pressure, adopting a grey box modelling technique that combines mechanistic knowledge with empirical data using a genetic algorithm approach. The models are shown to outperform those of a much higher order generated by a conventional black box technique while providing insight into the underlying processes at work within the extruder.

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The efficient generation of parallel code for multi-processor environments, is a large and complicated issue. Attempts to address this problem have always resulted in significant input from users. Because of constraints on user knowledge and time, the automation of the process is a promising and practically important research area. In recent years heuristic approaches have been used to capture available knowledge and make it available for the parallelisation process. Here, the introduction of a novel approach of neural network techniques is combined with an expert system technique to enhance the availability of knowledge to aid in the automatic generation of parallel code.

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BACKGROUND: Safe drug prescribing and administration are essential elements within undergraduate healthcare curricula, but medication errors, especially in paediatric practice, continue to compromise patient safety. In this area of clinical care, collective responsibility, team working and communication between health professionals have been identified as key elements in safe clinical practice. To date, there is limited research evidence as to how best to deliver teaching and learning of these competencies to practitioners of the future.

METHODS: An interprofessional workshop to facilitate learning of knowledge, core competencies, communication and team working skills in paediatric drug prescribing and administration at undergraduate level was developed and evaluated. The practical, ward-based workshop was delivered to 4th year medical and 3rd year nursing students and evaluated using a pre and post workshop questionnaire with open-ended response questions.

RESULTS: Following the workshop, students reported an increase in their knowledge and awareness of paediatric medication safety and the causes of medication errors (p < 0.001), with the greatest increase noted among medical students. Highly significant changes in students' attitudes to shared learning were observed, indicating that safe medication practice is learnt more effectively with students from other healthcare disciplines. Qualitative data revealed that students' participation in the workshop improved communication and teamworking skills, and led to greater awareness of the role of other healthcare professionals.

CONCLUSION: This study has helped bridge the knowledge-skills gap, demonstrating how an interprofessional approach to drug prescribing and administration has the potential to improve quality and safety within healthcare.

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In this paper we discuss the dualism of gene networks and their role in systems biology. We argue that gene networks ( 1) can serve as a conceptual framework, forming a fundamental level of a phenomenological description, and ( 2) are a means to represent and analyze data. The latter point does not only allow a systems analysis but is even amenable for a direct approach to study biological function. Here we focus on the clarity of our main arguments and conceptual meaning of gene networks, rather than the causal inference of gene networks from data. (C) 2010 John Wiley & Sons, Inc. WIREs Syst Biol Med 2011 3 379-391 DOI: 10.1002/wsbm.134