Graph-based ontology reasoning for formal verification of BREEAM rules

Globally, the need to check regulation compliance for sustainability has become central in the delivery of construction projects. This is partly due to policies by various governments requiring existing and new buildings to comply with certain standards or regulations. However, the verification of whether a building complies with any particular standard or regulation has proven challenging in practice. The purpose of formal verification is to prove that under a certain set of assumptions, a building will adhere to a certain set of requirements, for example the minimum performance standards of key environmental issues. Compliance checking requires different criteria often difficult to straightforwardly define and combine in an integrated fashion for providing holistic interpretation to facilitate easy decision-making. Such criteria, their various flows and combinations can easily be dealt with using conceptual graph theories and Semantic Web concepts which allow rules to be imbued to facilitate reasoning. The aim of this study is to tap on conceptual graphs and Semantic Web concepts to develop a system for checking Building Research Establishment Environmental Assessment Methodology (BREEAM) sustainability standard compliance in the French construction industry. A conceptual graph-based framework that formally describes BREEAM requirements and visually analyse compliance checking processes has been proposed. When implemented in a software that integrates conceptual graphs and Semantic Web knowledge, automatic reasoning allows both the logical specification and the visual interpretation to be displayed and further provides a semantic support for compliance checking information.     

English validation of the short form of the Physical Self-Inventory (PSI-S)

The study examined the psychometric properties of scores on the English version of the short Physical Self-Inventory (PSI-S) among 1368 English-Speaking and 224 French-Speaking adolescents. Participants completed the original PSI-S and a revised version including positively-worded reformulations of the original negatively-worded items. The results supported the a priori factor structure, composite reliability, and test-retest reliability (7–8 months) of scores on the revised PSI-S, and its equivalence with the French version. Compared to confirmatory factor analyses, exploratory structural equation modeling resulted in a superior solution, and more cleanly differentiated factors. PSI-S responses were longitudinally invariant across 7–8 months, and presented no evidence of differential item functioning as a function of age, gender, body mass index (BMI) and physical activity. The results showed latent mean differences as a function of gender, BMI (linear and curvilinear effects), and physical activity, supporting the criterion-related validity of the PSI-S factors.     

The logic in language: How all quantifiers are alike,but each quantifier is different

Quantifier words like each, every, all and three are among the most abstract words in language. Unlike nouns, verbs and adjectives, the meanings of quantifiers are not related to a referent out in the world. Rather, quantifiers specify what relationships hold between the sets of entities, events and properties denoted by other words. When two quantifiers are in the same clause, they create a systematic ambiguity. “Every kid climbed a tree” could mean that there was only one tree, climbed by all, or many different trees, one per climbing kid. In the present study, participants chose a picture to indicate their preferred reading of different ambiguous sentences – those containing every, as well as the other three quantifiers. In Experiment 1, we found large systematic differences in preference, depending on the quantifier word. In Experiment 2, we then manipulated the choice of a particular reading of one sentence, and tested how this affected participants’ reading preference on a subsequent target sentence. We found a priming effect for all quantifiers, but only when the prime and target sentences contained the same quantifier. For example, all-a sentences prime other all-a sentences, while each-a primes each-a, but sentences with each do not prime sentences with all or vice versa. In Experiment 3, we ask whether the lack of priming across quantifiers could be due to the two sentences sharing one fewer word. We find that changing the verb between the prime and target sentence does not reduce the priming effect. In Experiment 4, we discover one case where there is priming across quantifiers – when one number (e.g. three) is in the prime, and a different one (e.g. four) is in the target. We discuss how these findings relate to linguistic theories of quantifier meaning and what they tell us about the division of labor between conceptual content and combinatorial semantics, as well as the mental representations of quantification and of the abstract logical structure of language.     

Using movement and intentions to understand simple events

In order to understand ongoing activity, observers segment it into meaningful temporal parts. Segmentation can be based on bottom-up processing of distinctive sensory characteristics, such as movement features. Segmentation may also be affected by top-down effects of knowledge structures, including information about actors’ intentions. Three experiments investigated the role of movement features and intentions in perceptual event segmentation, using simple animations. In all conditions, movement features significantly predicted where participants segmented. This relationship was stronger when participants identified larger units than when they identified smaller units, and stronger when the animations were generated randomly than when they were generated by goal-directed human activity. This pattern suggests that bottom-up processing played an important role in segmentation of these stimuli, but that this was modulated by top-down influence of knowledge structures. To describe accurately how observers perceive ongoing activity, one must account for the effects of distinctive sensory characteristics, the effects of knowledge structures, and their interactions.     

Extractive document summarization using an adaptive,knowledge based cognitive model

Document summarization involves identifying the salient text in a document and creating a representative summary. The event-index cognitive model describes the human cognitive processes involved in generating situational models from a given text to comprehend that text. This paper proposes an adaptive, knowledge based event-index cognitive model that creates an extractive summary for a given document. The proposed cognitive model uses the hierarchical human memory model and emotion to create the extractive summary. The performance of the proposed cognitive model was compared with the existing state-of-art methods using the DUC (Document Understanding Conference) 2001 dataset and the ROUGE (Recall-Oriented Understudy for Gisting Evaluation) summary evaluation tool. Under ROUGE-N, ROUGE-L, ROUGE-S and ROUGE-SU evaluations, the proposed cognitive model for document summarization achieved an improvement of 25%, 12%, 24% and 18% in mean F-measure values. The results are statistically verified as significantly better than existing state-of-art methods using one way ANOVA with post-hoc Tukey-HSD test. In addition, this paper discusses the possible future research directions in document summarization based on the proposed cognitive model.     

Psychometric properties of the Portuguese version of the Alabama Parenting Questionnaire parent form

ABSTRACT

The Alabama Parenting Questionnaire parent form (APQ-P) is one of the most commonly used measures to assess parenting practices. The current study evaluated the psychometric properties of the APQ-P using a community sample of 499 Portuguese mothers of children and adolescents aged 10 to 17 years. Confirmatory factor analysis revealed adequate psychometric properties of a three-factor model (positive parenting, ineffective parenting, and poor monitoring) in a solution of 20-items. After comparing the three-factor model across children’s age groups (≤13 vs. ≥14), partial metric and partial scalar invariance were found. Items loadings were similar between groups for ineffective parenting and poor monitoring, and factor scores were similar between groups for positive parenting. The 20-item version can be an appropriate measure of parenting, relevant for research and intervention purposes. Future studies should validate the current findings in independent samples, and devote particular attention to different parenting practices across different children’s age groups.