1000 resultados para Norms extraction


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We present a methodology to extract legal norms from regulatory documents for their formalisation and later compliance checking. The need for the methodology is motivated from the shortcomings of existing approaches where the rule type and process aspects relevant to the rules are largely overlook. The methodology incorporates the well–known IF. . . THEN structure extended with the process aspect and rule type, and guides how to properly extract the conditions and logical structure of the legal rules for reasoning and modelling of obligations for compliance checking.

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The Automated Estimator and LCADesign are two early examples of nD modelling software which both rely on the extraction of quantities from CAD models to support their further processing. The issues of building information modelling (BIM), quantity takeoff for different purposes and automating quantity takeoff are discussed by comparing the aims and use of the two programs. The technical features of the two programs are also described. The technical issues around the use of 3D models is described together with implementation issues and comments about the implementation of the IFC specifications. Some user issues that emerged through the development process are described, with a summary of the generic research tasks which are necessary to fully support the use of BIM and nD modelling.

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Purpose: An extended Theory of Planned Behavior (TPB) model tests how customer loyalty intentions may relate to subjective and descriptive norms. The study further determines whether consumption characteristics – product enjoyment and importance – moderate norms-loyalty relationships.----- Methodology: Using a two-study approach focusing on youth, an Australian study (n = 244) first augmented TPB with descriptive norm. A Singapore study (n = 415) followed up with how consumption characteristics might moderate norms-loyalty relationships. With both studies, linear regressions tested the relationships among the variables.----- Findings: Extending TPB with descriptive norm improved TPB’s predictive ability across studies. Further, product enjoyment and importance moderated the norms-loyalty relationships differently. Subjective norm related to loyalty intentions significantly with high enjoyment, whereas descriptive norm was significant with low enjoyment. Only subjective norm was significant with low importance.----- Research limitations: Single-item variables, self-reported questionnaires on intended rather than actual behavior, and not controlling for cultural differences between the two samples limit generalizablity.----- Practical implications: The significance of both norms suggests that mobile firms should reach youth through their peers. With youth, social pressure may be influential particularly with hedonic products. However, the different moderations of product enjoyment and importance imply that a blanket marketing strategy targeting youth may not work.----- Originality/Value: This study extends academic knowledge on the relationships between norms and customer loyalty, particularly with consumption characteristics as moderators. The findings highlight the importance of considering different norms with consumer behavior. The study should help mobile firms understand how social influences impact customer loyalty.

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Australian non-users of vitamin supplements (N = 162) and functional foods (N = 226) responded to a questionnaire examining their attitudes, subjective norms, and perceived behavioural control from the Theory of Planned Behaviour (TPB), risk dread and risk familiarity, and willingness to engage in free product trials. The impact of participants’ gender and age was also examined. Attitude and subjective norms were significant determinants of non-users willingness to trial each of the health products. Participants’ dread of the risk associated with the product was also a determinant of willingness to use functional foods. The overall models predicted between 25% and 30% of the variance in people’s willingness to trial the products. The findings provided some support for the TPB in predicting people’s willingness to trial functional foods and vitamin supplements and suggested, for willingness to trial functional foods, that non-users are also influenced by their dread of the risk associated with product use.

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With the widespread applications of electronic learning (e-Learning) technologies to education at all levels, increasing number of online educational resources and messages are generated from the corresponding e-Learning environments. Nevertheless, it is quite difficult, if not totally impossible, for instructors to read through and analyze the online messages to predict the progress of their students on the fly. The main contribution of this paper is the illustration of a novel concept map generation mechanism which is underpinned by a fuzzy domain ontology extraction algorithm. The proposed mechanism can automatically construct concept maps based on the messages posted to online discussion forums. By browsing the concept maps, instructors can quickly identify the progress of their students and adjust the pedagogical sequence on the fly. Our initial experimental results reveal that the accuracy and the quality of the automatically generated concept maps are promising. Our research work opens the door to the development and application of intelligent software tools to enhance e-Learning.

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The relationship between multiple cameras viewing the same scene may be discovered automatically by finding corresponding points in the two views and then solving for the camera geometry. In camera networks with sparsely placed cameras, low resolution cameras or in scenes with few distinguishable features it may be difficult to find a sufficient number of reliable correspondences from which to compute geometry. This paper presents a method for extracting a larger number of correspondences from an initial set of putative correspondences without any knowledge of the scene or camera geometry. The method may be used to increase the number of correspondences and make geometry computations possible in cases where existing methods have produced insufficient correspondences.

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The automatic extraction of road features from remote sensed images has been a topic of great interest within the photogrammetric and remote sensing communities for over 3 decades. Although various techniques have been reported in the literature, it is still challenging to efficiently extract the road details with the increasing of image resolution as well as the requirement for accurate and up-to-date road data. In this paper, we will focus on the automatic detection of road lane markings, which are crucial for many applications, including lane level navigation and lane departure warning. The approach consists of four steps: i) data preprocessing, ii) image segmentation and road surface detection, iii) road lane marking extraction based on the generated road surface, and iv) testing and system evaluation. The proposed approach utilized the unsupervised ISODATA image segmentation algorithm, which segments the image into vegetation regions, and road surface based only on the Cb component of YCbCr color space. A shadow detection method based on YCbCr color space is also employed to detect and recover the shadows from the road surface casted by the vehicles and trees. Finally, the lane marking features are detected from the road surface using the histogram clustering. The experiments of applying the proposed method to the aerial imagery dataset of Gympie, Queensland demonstrate the efficiency of the approach.