Hierarchical community structure in complex (social) networks

The investigation of community structure in networks is a task of great importance in many disciplines, namely physics, sociology, biology and computer science where systems are often represented as graphs. One of the challenges is to find local communities from a local viewpoint in a graph without global information in order to reproduce the subjective hierarchical vision for each vertex. In this paper we present the improvement of an information dynamics algorithm in which the label propagation of nodes is based on the Markovian flow of information in the network under cognitive-inspired constraints \cite{Massaro2012}. In this framework we have introduced two more complex heuristics that allow the algorithm to detect the multi-resolution hierarchical community structure of networks from a source vertex or communities adopting fixed values of model's parameters. Experimental results show that the proposed methods are efficient and well-behaved in both real-world and synthetic networks

Geospatial Narratives and their Spatio-Temporal Dynamics: Commonsense Reasoning for High-level Analyses in Geographic Information Systems

The modelling, analysis, and visualisation of dynamic geospatial phenomena has been identified as a key developmental challenge for next-generation Geographic Information Systems (GIS). In this context, the envisaged paradigmatic extensions to contemporary foundational GIS technology raises fundamental questions concerning the ontological, formal representational, and (analytical) computational methods that would underlie their spatial information theoretic underpinnings. We present the conceptual overview and architecture for the development of high-level semantic and qualitative analytical capabilities for dynamic geospatial domains. Building on formal methods in the areas of commonsense reasoning, qualitative reasoning, spatial and temporal representation and reasoning, reasoning about actions and change, and computational models of narrative, we identify concrete theoretical and practical challenges that accrue in the context of formal reasoning about `space, events, actions, and change'. With this as a basis, and within the backdrop of an illustrated scenario involving the spatio-temporal dynamics of urban narratives, we address specific problems and solutions techniques chiefly involving `qualitative abstraction', `data integration and spatial consistency', and `practical geospatial abduction'. From a broad topical viewpoint, we propose that next-generation dynamic GIS technology demands a transdisciplinary scientific perspective that brings together Geography, Artificial Intelligence, and Cognitive Science. Keywords: artificial intelligence; cognitive systems; human-computer interaction; geographic information systems; spatio-temporal dynamics; computational models of narrative; geospatial analysis; geospatial modelling; ontology; qualitative spatial modelling and reasoning; spatial assistance systemsComment: ISPRS International Journal of Geo-Information (ISSN 2220-9964); Special Issue on: Geospatial Monitoring and Modelling of Environmental Change}. IJGI. Editor: Duccio Rocchini. (pre-print of article in press

Toward cumulative cognitive science: a comparison of meta-analysis, mega-analysis, and hybrid approaches

There is increasing interest in cumulative approaches to science, in which instead of analyzing the results of individual papers separately, we integrate information qualitatively or quantitatively. One such approach is meta-analysis, which has over 50 years of literature supporting its usefulness, and is becoming more common in cognitive science. However, changes in technical possibilities by the widespread use of Python and R make it easier to fit more complex models, and even simulate missing data. Here we recommend the use of mega-analyses (based on the aggregation of data sets collected by independent researchers) and hybrid meta- mega-analytic approaches, for cases where raw data is available for some studies. We illustrate the three approaches using a rich test-retest data set of infants’ speech processing as well as synthetic data. We discuss advantages and disadvantages of the three approaches from the viewpoint of a cognitive scientists contemplating their use, and limitations of this article, to be addressed in future work.Introduction - Study Case: Reliability of Infant Speech Perception Measures - Alternatives to Meta-analyses: Mega-analyses, IPD Meta-analyses, and Hybrid Approaches The present study - A Brief Primer on Test-Retest Infant Speech Perception - Modeling Experiment 1: Natural data Experiment 2: Synthetic data General discussion - Potential Limitations Conclusio

Evaluation of Cognitive Architectures for Cyber-Physical Production Systems

Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data, to create additional benefit, such as condition monitoring or optimization. These capabilities can lead to cognition, such that the system is able to adapt independently to changing circumstances by learning from additional sensors information. Developing a reference architecture for the design of CPPS and standardization of machines and software interfaces is crucial to enable compatibility of data usage between different machine models and vendors. This paper analysis existing reference architecture regarding their cognitive abilities, based on requirements that are derived from three different use cases. The results from the evaluation of the reference architectures, which include two instances that stem from the field of cognitive science, reveal a gap in the applicability of the architectures regarding the generalizability and the level of abstraction. While reference architectures from the field of automation are suitable to address use case specific requirements, and do not address the general requirements, especially w.r.t. adaptability, the examples from the field of cognitive science are well usable to reach a high level of adaption and cognition. It is desirable to merge advantages of both classes of architectures to address challenges in the field of CPPS in Industrie 4.0

Object categorisation, object naming, and viewpoint-independence in visual remembering: Evidence from young children's drawings of a novel object

A simple object-drawing task confirms a three-way association between object categorisation, viewpoint independence, and longer-term visual remembering. Young children (5- to 7-year-olds) drew a familiar object or a novel object, immediately after it had been hidden from view or on the following day. Both objects were shown from a full range of viewpoints or from just two viewpoints, from neither of which would either object normally be drawn after unrestricted viewing. When drawing from short-term memory after restricted viewing, both objects were most likely to be depicted from a seen viewpoint. When drawing from longer-term memory after restricted viewing, the novel object continued to be drawn from a seen viewpoint, but the mug was now most likely to be drawn from a preferred viewpoint from which it had not been seen. Naming the novel object with a novel count noun ("Look at this. This is a dax"), to signal that it belonged to an object category, resulted in it being drawn in the same way as the familiar object. The results concur with other evidence indicating that short-term and longer-term visual remembering are differentially associated with viewpoint-dependent representations of individual objects and viewpoint independent representations of object categories, respectively

Spectators’ aesthetic experiences of sound and movement in dance performance

In this paper we present a study of spectators’ aesthetic experiences of sound and movement in live dance performance. A multidisciplinary team comprising a choreographer, neuroscientists and qualitative researchers investigated the effects of different sound scores on dance spectators. What would be the impact of auditory stimulation on kinesthetic experience and/or aesthetic appreciation of the dance? What would be the effect of removing music altogether, so that spectators watched dance while hearing only the performers’ breathing and footfalls? We investigated audience experience through qualitative research, using post-performance focus groups, while a separately conducted functional brain imaging (fMRI) study measured the synchrony in brain activity across spectators when they watched dance with sound or breathing only. When audiences watched dance accompanied by music the fMRI data revealed evidence of greater intersubject synchronisation in a brain region consistent with complex auditory processing. The audience research found that some spectators derived pleasure from finding convergences between two complex stimuli (dance and music). The removal of music and the resulting audibility of the performers’ breathing had a significant impact on spectators’ aesthetic experience. The fMRI analysis showed increased synchronisation among observers, suggesting greater influence of the body when interpreting the dance stimuli. The audience research found evidence of similar corporeally focused experience. The paper discusses possible connections between the findings of our different approaches, and considers the implications of this study for interdisciplinary research collaborations between arts and sciences

The challenges of viewpoint-taking when learning a sign language: Data from the 'frog story' in British Sign Language

Little is known about how hearing adults learn sign languages. Our objective in this study was to investigate how learners of British Sign Language (BSL) produce narratives, and we focused in particular on viewpoint-taking. Twenty-three intermediate-level learners of BSL and 10 deaf native/early signers produced a narrative in BSL using the wordless picture book Frog, where are you? (Mayer, 1969). We selected specific episodes from part of the book that provided rich opportunities for shifting between different characters and taking on different viewpoints. We coded for details of story content, the frequency with which different viewpoints were used and how long those viewpoints were used for, and the numbers of articulators that were used simultaneously. We found that even though learners’ and deaf signers’ narratives did not differ in overall duration, learners’ narratives had less content. Learners used character viewpoint less frequently than deaf signers. Although learners spent just as long as deaf signers in character viewpoint, they spent longer than deaf signers in observer viewpoint. Together, these findings suggest that character viewpoint was harder than observer viewpoint for learners. Furthermore, learners were less skilled than deaf signers in using multiple articulators simultaneously. We conclude that challenges for learners of sign include taking character viewpoint when narrating a story and encoding information across multiple articulators simultaneously

Science as systems learning. Some reflections on the cognitive and communicational aspects of science

This paper undertakes a theoretical investigation of the 'learning' aspect of science as opposed to the 'knowledge' aspect. The practical background of the paper is in agricultural systems research – an area of science that can be characterised as 'systemic' because it is involved in the development of its own subject area, agriculture. And the practical purpose of the theoretical investigation is to contribute to a more adequate understanding of science in such areas, which can form a basis for developing and evaluating systemic research methods, and for determining appropriate criteria of scientific quality. Two main perspectives on science as a learning process are explored: research as the learning process of a cognitive system, and science as a social, communicational system. A simple model of a cognitive system is suggested, which integrates both semiotic and cybernetic aspects, as well as a model of selfreflective learning in research, which entails moving from an inside 'actor' stance to an outside 'observer' stance, and back. This leads to a view of scientific knowledge as inherently contextual and to the suggestion of reflexive objectivity and relevance as two related key criteria of good science