Probabilistic topographic information visualisation

The focus of this thesis is the extension of topographic visualisation mappings to allow for the incorporation of uncertainty. Few visualisation algorithms in the literature are capable of mapping uncertain data with fewer able to represent observation uncertainties in visualisations. As such, modifications are made to NeuroScale, Locally Linear Embedding, Isomap and Laplacian Eigenmaps to incorporate uncertainty in the observation and visualisation spaces. The proposed mappings are then called Normally-distributed NeuroScale (N-NS), T-distributed NeuroScale (T-NS), Probabilistic LLE (PLLE), Probabilistic Isomap (PIso) and Probabilistic Weighted Neighbourhood Mapping (PWNM). These algorithms generate a probabilistic visualisation space with each latent visualised point transformed to a multivariate Gaussian or T-distribution, using a feed-forward RBF network. Two types of uncertainty are then characterised dependent on the data and mapping procedure. Data dependent uncertainty is the inherent observation uncertainty. Whereas, mapping uncertainty is defined by the Fisher Information of a visualised distribution. This indicates how well the data has been interpolated, offering a level of ‘surprise’ for each observation. These new probabilistic mappings are tested on three datasets of vectorial observations and three datasets of real world time series observations for anomaly detection. In order to visualise the time series data, a method for analysing observed signals and noise distributions, Residual Modelling, is introduced. The performance of the new algorithms on the tested datasets is compared qualitatively with the latent space generated by the Gaussian Process Latent Variable Model (GPLVM). A quantitative comparison using existing evaluation measures from the literature allows performance of each mapping function to be compared. Finally, the mapping uncertainty measure is combined with NeuroScale to build a deep learning classifier, the Cascading RBF. This new structure is tested on the MNist dataset achieving world record performance whilst avoiding the flaws seen in other Deep Learning Machines.

Developing multidimensional metrics for evaluating paediatric neurodevelopmental disorders

Healthy brain functioning depends on efficient communication of information between brain regions, forming complex networks. By quantifying synchronisation between brain regions, a functionally connected brain network can be articulated. In neurodevelopmental disorders, where diagnosis is based on measures of behaviour and tasks, a measure of the underlying biological mechanisms holds promise as a potential clinical tool. Graph theory provides a tool for investigating the neural correlates of neuropsychiatric disorders, where there is disruption of efficient communication within and between brain networks. This research aimed to use recent conceptualisation of graph theory, along with measures of behaviour and cognitive functioning, to increase understanding of the neurobiological risk factors of atypical development. Using magnetoencephalography to investigate frequency-specific temporal dynamics at rest, the research aimed to identify potential biological markers derived from sensor-level whole-brain functional connectivity. Whilst graph theory has proved valuable for insight into network efficiency, its application is hampered by two limitations. First, its measures have hardly been validated in MEG studies, and second, graph measures have been shown to depend on methodological assumptions that restrict direct network comparisons. The first experimental study (Chapter 3) addressed the first limitation by examining the reproducibility of graph-based functional connectivity and network parameters in healthy adult volunteers. Subsequent chapters addressed the second limitation through adapted minimum spanning tree (a network analysis approach that allows for unbiased group comparisons) along with graph network tools that had been shown in Chapter 3 to be highly reproducible. Network topologies were modelled in healthy development (Chapter 4), and atypical neurodevelopment (Chapters 5 and 6). The results provided support to the proposition that measures of network organisation, derived from sensor-space MEG data, offer insights helping to unravel the biological basis of typical brain maturation and neurodevelopmental conditions, with the possibility of future clinical utility.

Common priors for generalized type spaces

The notion of common prior is well-understood and widely-used in the incomplete information games literature. For ordinary type spaces the common prior is de�fined. Pint�er and Udvari (2011) introduce the notion of generalized type space. Generalized type spaces are models for various bonded rationality issues, for �nite belief hierarchies, unawareness among others. In this paper we de�ne the notion of common prior for generalized types spaces. Our results are as follows: the generalization (1) suggests a new form of common prior for ordinary type spaces, (2) shows some quantum game theoretic results (Brandenburger and La Mura, 2011) in new light.

Generalized type spaces

Ordinary type spaces (Heifetz and Samet, 1998) are essential ingredients of incomplete information games. With ordinary type spaces one can grab the notions of beliefs, belief hierarchies and common prior etc. However, ordinary type spaces cannot handle the notions of finite belief hierarchy and unawareness among others. In this paper we consider a generalization of ordinary type spaces, and introduce the so called generalized type spaces which can grab all notions ordinary type spaces can and more, finite belief hierarchies and unawareness among others. We also demonstrate that the universal generalized type space exists.

Common priors for generalized type spaces

The notion of common prior is well-understood and widely-used in the incomplete information games literature. For ordinary type spaces the common prior is defined. Pinter and Udvari (2011) introduce the notion of generalized type space. Generalized type spaces are models for various bonded rationality issues, for nite belief hierarchies, unawareness among others. In this paper we dene the notion of common prior for generalized types spaces. Our results are as follows: the generalization (1) suggests a new form of common prior for ordinary type spaces, (2) shows some quantum game theoretic results (Brandenburger and La Mura, 2011) in new light.

Multidimensional classification and diagnosis of leukemia in flow cytometry

This research is to establish new optimization methods for pattern recognition and classification of different white blood cells in actual patient data to enhance the process of diagnosis. Beckman-Coulter Corporation supplied flow cytometry data of numerous patients that are used as training sets to exploit the different physiological characteristics of the different samples provided. The methods of Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used as promising pattern classification techniques to identify different white blood cell samples and provide information to medical doctors in the form of diagnostic references for the specific disease states, leukemia. The obtained results prove that when a neural network classifier is well configured and trained with cross-validation, it can perform better than support vector classifiers alone for this type of data. Furthermore, a new unsupervised learning algorithm---Density based Adaptive Window Clustering algorithm (DAWC) was designed to process large volumes of data for finding location of high data cluster in real-time. It reduces the computational load to ∼O(N) number of computations, and thus making the algorithm more attractive and faster than current hierarchical algorithms.

A generalized multidimensional index structure for multimedia data to support content-based similarity searches in a collaborative search environment

Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment. Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

Avaliação multidimensional da qualidade de vida em idosos: um estudo no Curimataú ocidental paraibano

The fast growth of the elderly population is a reality throughout the world and has become one of the greatest challenges for contemporary public health. When considering the increased life expectancy and the aging as a multidimensional phenomenon, one should highlight the need to investigate if the increase of longevity is associated with satisfactory levels of Quality of Life (QOL). This study has the objective of assessing the QOL of elderly people from the Paraíba’s Western Curimataú microregion, explained by its health and living conditions. This is a cross-sectional and observational study with quantitative design held with 444 elderly people from five cities: Barra de Santa Rosa, Cuité, Nova Floresta, Remígio e Sossego. In order to obtain information, the following instruments were used: I) Questionnaire for collection data related to the elderly population, for sociodemographic, clinical and behavioral characteristics; and II) WHOQOL-Old questionnaire, with a view to measuring and assessing QOL. Data were processed on the IBM-SPSS Statistics 20.0 software by means of the ANOVA (one-way), Student’s t, Mann-Whitney, Kruskal-Wallis and Pearson’s correlation tests, with p-values<0,05 accepted as being statistically significant. The results indicate a good global QOL (ETT=65,69%), with better assessment by elderly men, aged between 60 and 74 years, married, living with partner and children, without caregiver, physical activity practitioners, with up to one health problem before an aspect of multimorbidity and with very good and/or good assessment of basic needs. The self-reported stress showed a negative significant correlation before the global QOL, where the greater the perception of stress, the worse the assessment of QOL. In the faceted assessment of QOL, the Sensory Operation showed the best performance (ETF= 68,86%) and the Social Participation (SP) the worst (ETF=60,37%). In the multiple linear regression model, SP is singly responsible for 51,8% (R2=0,518) of explanation of the global QOL. In the intercorrelation among the WHOQOL-Old facets, only Death and Dying did not reveal significance. The harmony highlighted among the facets raises the need to ensure a comprehensive health care for the elderly population, especially in understanding the social participation as an intrinsic part of the QOL and that it requires the re-discussion and reconstruction of individual and collective, family and community, political and government actions. Hence, guaranteeing an active, healthy and participatory aging, with QOL, is the major challenge.

Avaliação multidimensional da qualidade de vida em idosos: um estudo no Curimataú ocidental paraibano

The fast growth of the elderly population is a reality throughout the world and has become one of the greatest challenges for contemporary public health. When considering the increased life expectancy and the aging as a multidimensional phenomenon, one should highlight the need to investigate if the increase of longevity is associated with satisfactory levels of Quality of Life (QOL). This study has the objective of assessing the QOL of elderly people from the Paraíba’s Western Curimataú microregion, explained by its health and living conditions. This is a cross-sectional and observational study with quantitative design held with 444 elderly people from five cities: Barra de Santa Rosa, Cuité, Nova Floresta, Remígio e Sossego. In order to obtain information, the following instruments were used: I) Questionnaire for collection data related to the elderly population, for sociodemographic, clinical and behavioral characteristics; and II) WHOQOL-Old questionnaire, with a view to measuring and assessing QOL. Data were processed on the IBM-SPSS Statistics 20.0 software by means of the ANOVA (one-way), Student’s t, Mann-Whitney, Kruskal-Wallis and Pearson’s correlation tests, with p-values<0,05 accepted as being statistically significant. The results indicate a good global QOL (ETT=65,69%), with better assessment by elderly men, aged between 60 and 74 years, married, living with partner and children, without caregiver, physical activity practitioners, with up to one health problem before an aspect of multimorbidity and with very good and/or good assessment of basic needs. The self-reported stress showed a negative significant correlation before the global QOL, where the greater the perception of stress, the worse the assessment of QOL. In the faceted assessment of QOL, the Sensory Operation showed the best performance (ETF= 68,86%) and the Social Participation (SP) the worst (ETF=60,37%). In the multiple linear regression model, SP is singly responsible for 51,8% (R2=0,518) of explanation of the global QOL. In the intercorrelation among the WHOQOL-Old facets, only Death and Dying did not reveal significance. The harmony highlighted among the facets raises the need to ensure a comprehensive health care for the elderly population, especially in understanding the social participation as an intrinsic part of the QOL and that it requires the re-discussion and reconstruction of individual and collective, family and community, political and government actions. Hence, guaranteeing an active, healthy and participatory aging, with QOL, is the major challenge.

What happens at the gap between knowledge and practice? Spaces of encounter and misencounter between environmental scientists and local people

Researchers studying processes of global environmental change are increasingly interested in their work having impacts that go beyond academia to influence policy and management. Recent scholarship in the conservation sciences has pointed to the existence of a research-action gap and has proposed various solutions for overcoming it. However, most of these studies have been limited to the spaces of dissemination, where the science has already been done and is then to be passed over to users of the information. Much less attention has been paid to encounters that occur between scientists and nonscientists during the practice of doing scientific research, especially in situations that include everyday roles of labor and styles of communication (i.e., fieldwork). This paper builds on theories of contact that have examined encounters and relations between different groups and cultures in diverse settings. I use quantitative and qualitative evidence from Madidi National Park, Bolivia, including an analysis of past research in the protected area, as well as interviews (N = 137) and workshops and focus groups (N = 12) with local inhabitants, scientists, and park guards. The study demonstrates the significance of currently unacknowledged or undervalued components of the research-action gap, such as power, respect, and recognition, to develop a relational and reciprocal notion of impact. I explain why, within such spaces of encounter or misencounter between scientists and local people, knowledge can be exchanged or hidden away, worldviews can be expanded or further entrenched, and scientific research can be welcomed or rejected.

Visualising Spaces: The Illustrated Map as a Mode of Communicating Fact, Fiction and Feeling

Communicating thoughts, facts and narratives through visual devices such as allegory or symbolism was fundamental to early map making and this remains the case with contemporary illustration. Drawing was employed then as a way of describing historic narratives (fact and folklore) through the convenience of a drawn symbol or character. The map creators were visionaries, depicting known discoveries and anticipating what existed beyond the agreed boundaries. As we now have photographic and virtual reality maps at our disposal, how can illustration develop the language of what a map is and can be? How can we break the rules of map design and yet still communicate the idea of a sense of place with the aim to inform, excite and/or educate the ‘traveller’? As Illustrators we need to question the purpose of creating a ‘map’: what do we want to communicate and is representational image making the only way to present information of a location? Is creating a more personal interpretation a form of cartouche, reminiscent of elements within the Hereford Mappa Mundi and maps of Blaeu, and can this improve/hinder the communicative aspect of the map? Looking at a variety of historical and contemporary illustrated maps and artists (such as Grayson Perry), who track their journeys through drawing, both conventional journeys and emotional, I will aim to prove that the illustrated map is not mere decoration but is a visual language providing an allegorical response to tangible places and personal feelings.

Sharing through Collaborative Spaces: Enhancing Collaborative Networks Interoperability

Part 14: Interoperability and Integration

STORM - a novel information fusion and cluster interpretation technique

Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, useful for better understanding of a problem at hand, than by looking only at the data itself. Although abundant expert knowledge exists in many areas where unlabelled data is examined, such knowledge is rarely incorporated into automatic analysis. Incorporation of expert knowledge is frequently a matter of combining multiple data sources from disparate hypothetical spaces. In cases where such spaces belong to different data types, this task becomes even more challenging. In this paper we present a novel immune-inspired method that enables the fusion of such disparate types of data for a specific set of problems. We show that our method provides a better visual understanding of one hypothetical space with the help of data from another hypothetical space. We believe that our model has implications for the field of exploratory data analysis and knowledge discovery.