“IT’S ALL RIGHT”. Multimodal rightward spatial bias modified by age and praxis

The general goal of the present work was to study whether spatial perceptual asymmetry initially observed in linguistic dichotic listening studies is related to the linguistic nature of the stimuli and/or is modality-specific, as well as to investigate whether the spatial perceptual/attentional asymmetry changes as a function of age and sensory deficit via praxis. Several dichotic listening studies with linguistic stimuli have shown that the inherent perceptual right ear advantage (REA), which presumably results from the left lateralized linguistic functions (bottom-up processes), can be modified with executive functions (top-down control). Executive functions mature slowly during childhood, are well developed in adulthood, and decline as a function of ageing. In Study I, the purpose was to investigate with a cross-sectional experiment from a lifespan perspective the age-related changes in top-down control of REA for linguistic stimuli in dichotic listening with a forced-attention paradigm (DL). In Study II, the aim was to determine whether the REA is linguistic-stimulus-specific or not, and whether the lifespan changes in perceptual asymmetry observed in dichotic listening would exist also in auditory spatial attention tasks that put load on attentional control. In Study III, using visual spatial attention tasks, mimicking the auditory tasks applied in Study II, it was investigated whether or not the stimulus-non-specific rightward spatial bias found in auditory modality is a multimodal phenomenon. Finally, as it has been suggested that the absence of visual input in blind participants leads to improved auditory spatial perceptual and cognitive skills, the aim in Study IV was to determine, whether blindness modifies the ear advantage in DL. Altogether 180-190 right-handed participants between 5 and 79 years of age were studied in Studies I to III, and in Study IV the performance of 14 blind individuals was compared with that of 129 normally sighted individuals. The results showed that only rightward spatial bias was observed in tasks with intensive attentional load, independent of the type of stimuli (linguistic vs. non-linguistic) or the modality (auditory vs. visual). This multimodal rightward spatial bias probably results from a complex interaction of asymmetrical perceptual, attentional, and/or motor mechanisms. Most importantly, the strength of the rightward spatial bias changed as a function of age and augmented praxis due to sensory deficit. The efficiency of the performance in spatial attention tasks and the ability to overcome the rightward spatial bias increased during childhood, was at its best in young adulthood, and decreased as a function of ageing. Between the ages of 5 and 11 years probably at first develops movement and impulse control, followed by the gradual development of abilities to inhibit distractions and disengage attention. The errors especially in bilateral stimulus conditions suggest that a mild phenomenon resembling extinction can be observed throughout the lifespan, but especially the ability to distribute attention to multiple targets simultaneously decreases in the course of ageing. Blindness enhances the processing of auditory bilateral linguistic stimuli, the ability to overcome a stimulus-driven laterality effect related to speech sound perception, and the ability to direct attention to an appropriate spatial location. It was concluded that the ability to voluntarily suppress and inhibit the multimodal rightward spatial bias changes as a function of age and praxis due to sensory deficit and probably reflects the developmental level of executive functions.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Making home rules for mother tongues : the legal implications of linguistic diversity in the design of autonomy regimes

Principen om nationalismen där det politiska och det nationella är samspelt kan vara av markant betydelse för uppbyggande av autonomiska regimer. Likaså tillåter decentralicering och delegering av befogenheter för språk och utbildning (officiellt erkännande av språk, standardisering av språk, undervisningsspråk och relaterade läroplaner) formning av identiteter inom dessa autonomiska regimer. Resultatet är en ofullkomlig cirkulär relation där språk, samfund och politiska institutioner ömsesidigt och kontinuerligt formar varandra: lingvistiskt mångfald prägar och formger autonomiska ordningar och vice-versa. De juridiska implikationerna av territoriella och icke-territoriella former av autonomi är dock av en annan art. Emedan territoriell autonomi bygger på idéen om ett eventuellt inkluderande hemland för lingvistiska grupper, vars vistelseort är avgörande, förstärker den icke-territoriella autonomin idéen om ett exclusivt samfund bestående av själv-identifierade medlemmar som är kapabla till självstyre oavsett territoriella gränser. Denna avhandling utgör an analys av sådana juridiska implikationer genom komparativa och institutionella analyser. Avhandlingen föreslår som resultat en serie av normativa och pragmatiska rekommendationer inriktade på att främja demokratiseringsprocesser i linje med principer om multikulturalism.