Ontology supported comparison in vague domains

It is problematic to use standard ontology tools when describing vague domains. Standard ontologies are designed to formally define one view of a domain, and although it is possible to define disagreeing statements, it is not advisable, as the resulting inferences could be incorrect. Two different solutions to the above problem in two different vague domains have been developed and are presented. The first domain is the knowledge base of conversational agents (chatbots). An ontological scripting language has been designed to access ontology data from within chatbot code. The solution developed is based on reifications of user statements. It enables a new layer of logics based on the different views of the users, enabling the body of knowledge to grow automatically. The second domain is competencies and competency frameworks. An ontological framework has been developed to model different competencies using the emergent standards. It enables comparison of competencies using a mix of linguistic logics and descriptive logics. The comparison results are non-binary, therefore not simple yes and no answers, highlighting the vague nature of the comparisons. The solution has been developed with small ontologies which can be added to and modified in order for the competency user to build a total picture that fits the user’s purpose. Finally these two approaches are viewed in the light of how they could aid future work in vague domains, further work in both domains is described and also in other domains such as the semantic web. This demonstrates two different approaches to achieve inferences using standard ontology tools in vague domains.

Video activity extraction and reporting with incremental unsupervised learning

The present work presents a new method for activity extraction and reporting from video based on the aggregation of fuzzy relations. Trajectory clustering is first employed mainly to discover the points of entry and exit of mobiles appearing in the scene. In a second step, proximity relations between resulting clusters of detected mobiles and contextual elements from the scene are modeled employing fuzzy relations. These can then be aggregated employing typical soft-computing algebra. A clustering algorithm based on the transitive closure calculation of the fuzzy relations allows building the structure of the scene and characterises the ongoing different activities of the scene. Discovered activity zones can be reported as activity maps with different granularities thanks to the analysis of the transitive closure matrix. Taking advantage of the soft relation properties, activity zones and related activities can be labeled in a more human-like language. We present results obtained on real videos corresponding to apron monitoring in the Toulouse airport in France.

Operatives’ experiences of cultural diversity on Australian construction sites

Construction sites are among Australia's most culturally diverse workplaces. A survey of 1155 construction operatives on Australian construction sites investigated, for the first time, the extent of this diversity and how it is experienced by workers. Results show that while cultural diversity presents organizational challenges by segregating the workforce, operatives' cultural groups also perform positive functions such as maintaining positive bonds among group members and providing group support and safe havens. While there broadly appears to be equality of opportunity for all cultural groups, there is significant evidence of differential treatment for some groups, particularly in relation to accessing higher paying jobs, offensive graffiti and racist joke telling. Language barriers are one of the major challenges affecting work and social relations between different cultural groups and there is evidence that this has a detrimental impact upon safety.

Sentence repetition in adolescents with specific language impairments and autism: an investigation of complex syntax

Background: Recent studies have indicated that many children with autism spectrum disorders present with language difficulties that are similar to those of children with specific language impairments, leading some to argue for similar structural deficits in these two disorders. Aims: Repetition of sentences involving long-distance dependencies was used to investigate complex syntax in these groups. Methods & Procedures: Adolescents with specific language impairments (mean age = 15;3, n = 14) and autism spectrum disorders plus language impairment (autism plus language impairment; mean age = 14;8, n = 16) were recruited alongside typically developing adolescents (mean age = 14;4, n = 17). They were required to repeat sentences containing relative clauses that varied in syntactic complexity. Outcomes & Results: The adolescents with specific language impairments presented with greater syntactic difficulties than the adolescents with autism plus language impairment, as manifested by higher error rates on the more complex object relative clauses, and a greater tendency to make syntactic changes during repetition. Conclusions & Implications: Adolescents with specific language impairments may have more severe syntactic difficulties than adolescents with autism plus language impairment, possibly due to their short-term memory limitations.

Speech perception and phonological short-term memory capacity in language impairment: preliminary evidence from adolescents with specific language impairment (SLI) and autism spectrum disorders (ASD)

Background: The cognitive bases of language impairment in specific language impairment (SLI) and autism spectrum disorders (ASD) were investigated in a novel non-word comparison task which manipulated phonological short-term memory (PSTM) and speech perception, both implicated in poor non-word repetition. Aims: This study aimed to investigate the contributions of PSTM and speech perception in non-word processing and whether individuals with SLI and ASD plus language impairment (ALI) show similar or different patterns of deficit in these cognitive processes. Method & Procedures: Three groups of adolescents (aged 14–17 years), 14 with SLI, 16 with ALI, and 17 age and non-verbal IQ matched typically developing (TD) controls, made speeded discriminations between non-word pairs. Stimuli varied in PSTM load (two- or four-syllables) and speech perception load (mismatches on a word-initial or word-medial segment). Outcomes & Results: Reaction times showed effects of both non-word length and mismatch position and these factors interacted: four-syllable and word-initial mismatch stimuli resulted in the slowest decisions. Individuals with language impairment showed the same pattern of performance as those with typical development in the reaction time data. A marginal interaction between group and item length was driven by the SLI and ALI groups being less accurate with long items than short ones, a difference not found in the TD group. Conclusions & Implications: Non-word discrimination suggests that there are similarities and differences between adolescents with SLI and ALI and their TD peers. Reaction times appear to be affected by increasing PSTM and speech perception loads in a similar way. However, there was some, albeit weaker, evidence that adolescents with SLI and ALI are less accurate than TD individuals, with both showing an effect of PSTM load. This may indicate, at some level, the processing substrate supporting both PSTM and speech perception is intact in adolescents with SLI and ALI, but also in both there may be impaired access to PSTM resources.

Non-word repetition in adolescents with Specific Language Impairment and Autism plus Language Impairments: a qualitative analysis

Non-word repetition (NWR) was investigated in adolescents with typical development, Specific Language Impairment (SLI) and Autism Plus language Impairment (ALI) (n = 17, 13, 16, and mean age 14;4, 15;4, 14;8 respectively). The study evaluated the hypothesis that poor NWR performance in both groups indicates an overlapping language phenotype (Kjelgaard & Tager-Flusberg, 2001). Performance was investigated both quantitatively, e.g. overall error rates, and qualitatively, e.g. effect of length on repetition, proportion of errors affecting phonological structure, and proportion of consonant substitutions involving manner changes. Findings were consistent with previous research (Whitehouse, Barry, & Bishop, 2008) demonstrating a greater effect of length in the SLI group than the ALI group, which may be due to greater short-term memory limitations. In addition, an automated count of phoneme errors identified poorer performance in the SLI group than the ALI group. These findings indicate differences in the language profiles of individuals with SLI and ALI, but do not rule out a partial overlap. Errors affecting phonological structure were relatively frequent, accounting for around 40% of phonemic errors, but less frequent than straight Consonant-for-Consonant or vowel-for-vowel substitutions. It is proposed that these two different types of errors may reflect separate contributory mechanisms. Around 50% of consonant substitutions in the clinical groups involved manner changes, suggesting poor auditory-perceptual encoding. From a clinical perspective algorithms which automatically count phoneme errors may enhance sensitivity of NWR as a diagnostic marker of language impairment. Learning outcomes: Readers will be able to (1) describe and evaluate the hypothesis that there is a phenotypic overlap between SLI and Autism Spectrum Disorders (2) describe differences in the NWR performance of adolescents with SLI and ALI, and discuss whether these differences support or refute the phenotypic overlap hypothesis, and (3) understand how computational algorithms such as the Levenshtein Distance may be used to analyse NWR data.

The programming language standards scene, ten years on paper 19: Pop

This paper, one of a simultaneously published set, describes the establishment in 1990 of the UK standards project for the Pop programming language, and the progress of the project to the end of 1993.

POP-11 comes of age: the advancement of an AI programming language

In 1989, the computer programming language POP-11 is 21 years old. This book looks at the reasons behind its invention, and traces its rise from an experimental language to a major AI language, playing a major part in many innovating projects. There is a chapter on the inventor of the language, Robin Popplestone, and a discussion of the applications of POP-11 in a variety of areas. The efficiency of AI programming is covered, along with a comparison between POP-11 and other programming languages. The book concludes by reviewing the standardization of POP-11 into POP91.