Dual Logic Concepts based on Mathematical Morphology in Stratified Institutions: Applications to Spatial Reasoning

Several logical operators are defined as dual pairs, in different types of logics. Such dual pairs of operators also occur in other algebraic theories, such as mathematical morphology. Based on this observation, this paper proposes to define, at the abstract level of institutions, a pair of abstract dual and logical operators as morphological erosion and dilation. Standard quantifiers and modalities are then derived from these two abstract logical operators. These operators are studied both on sets of states and sets of models. To cope with the lack of explicit set of states in institutions, the proposed abstract logical dual operators are defined in an extension of institutions, the stratified institutions, which take into account the notion of open sentences, the satisfaction of which is parametrized by sets of states. A hint on the potential interest of the proposed framework for spatial reasoning is also provided.Comment: 36 page

Inductive Pattern Formation

With the extended computational limits of algorithmic recursion, scientific investigation is transitioning away from computationally decidable problems and beginning to address computationally undecidable complexity. The analysis of deductive inference in structure-property models are yielding to the synthesis of inductive inference in process-structure simulations. Process-structure modeling has examined external order parameters of inductive pattern formation, but investigation of the internal order parameters of self-organization have been hampered by the lack of a mathematical formalism with the ability to quantitatively define a specific configuration of points. This investigation addressed this issue of quantitative synthesis. Local space was developed by the Poincare inflation of a set of points to construct neighborhood intersections, defining topological distance and introducing situated Boolean topology as a local replacement for point-set topology. Parallel development of the local semi-metric topological space, the local semi-metric probability space, and the local metric space of a set of points provides a triangulation of connectivity measures to define the quantitative architectural identity of a configuration and structure independent axes of a structural configuration space. The recursive sequence of intersections constructs a probabilistic discrete spacetime model of interacting fields to define the internal order parameters of self-organization, with order parameters external to the configuration modeled by adjusting the morphological parameters of individual neighborhoods and the interplay of excitatory and inhibitory point sets. The evolutionary trajectory of a configuration maps the development of specific hierarchical structure that is emergent from a specific set of initial conditions, with nested boundaries signaling the nonlinear properties of local causative configurations. This exploration of architectural configuration space concluded with initial process-structure-property models of deductive and inductive inference spaces. In the computationally undecidable problem of human niche construction, an adaptive-inductive pattern formation model with predictive control organized the bipartite recursion between an information structure and its physical expression as hierarchical ensembles of artificial neural network-like structures. The union of architectural identity and bipartite recursion generates a predictive structural model of an evolutionary design process, offering an alternative to the limitations of cognitive descriptive modeling. The low computational complexity of these models enable them to be embedded in physical constructions to create the artificial life forms of a real-time autonomously adaptive human habitat

Supporting multimedia user interface design using mental models and representational expressiveness

This thesis addresses the problem of output media allocation in the design of multimedia user interfaces. The literature survey identifies a formal definition of the representational capabilities of different media.as important in this task. Equally important, though less prominent in the literature, is that the correct mental model of a domain is paramount for the successful completion of tasks. The thesis proposes an original linguistic and cognitive based descriptive framework, in two parts. The first part defines expressiveness, the amount of representational abstraction a medium provides over any domain. The second part describes how this expressiveness is linked to the mental models that media induce, and how this in turn affects task performance. It is postulated that the mental models induced by different media, will reflect the abstractive representation those media offer over the task domain. This must then be matched to the abstraction required by tasks to allow them to be effectively accomplished. A 34 subject experiment compares five media, of two levels of expressiveness, over a range of tasks, in a complex and dynamic domain. The results indicate that expressiveness may allow media to be matched more closely to tasks, if the mental models they are known to induce are considered. Finally, the thesis proposes a tentative framework for media allocation, and two example interfaces are designed using this framework. This framework is based on the matching of expressiveness to the abstraction of a domain required by tasks. The need for the methodology to take account of the user's cognitive capabilities is stressed, and the experimental results are seen as the beginning of this procedure

Dwelling on ontology - semantic reasoning over topographic maps

The thesis builds upon the hypothesis that the spatial arrangement of topographic features, such as buildings, roads and other land cover parcels, indicates how land is used. The aim is to make this kind of high-level semantic information explicit within topographic data. There is an increasing need to share and use data for a wider range of purposes, and to make data more definitive, intelligent and accessible. Unfortunately, we still encounter a gap between low-level data representations and high-level concepts that typify human qualitative spatial reasoning. The thesis adopts an ontological approach to bridge this gap and to derive functional information by using standard reasoning mechanisms offered by logic-based knowledge representation formalisms. It formulates a framework for the processes involved in interpreting land use information from topographic maps. Land use is a high-level abstract concept, but it is also an observable fact intimately tied to geography. By decomposing this relationship, the thesis correlates a one-to-one mapping between high-level conceptualisations established from human knowledge and real world entities represented in the data. Based on a middle-out approach, it develops a conceptual model that incrementally links different levels of detail, and thereby derives coarser, more meaningful descriptions from more detailed ones. The thesis verifies its proposed ideas by implementing an ontology describing the land use ‘residential area’ in the ontology editor Protégé. By asserting knowledge about high-level concepts such as types of dwellings, urban blocks and residential districts as well as individuals that link directly to topographic features stored in the database, the reasoner successfully infers instances of the defined classes. Despite current technological limitations, ontologies are a promising way forward in the manner we handle and integrate geographic data, especially with respect to how humans conceptualise geographic space

Automated Segmentation of Cerebral Aneurysm Using a Novel Statistical Multiresolution Approach

Cerebral Aneurysm (CA) is a vascular disease that threatens the lives of many adults. It a ects almost 1:5 - 5% of the general population. Sub- Arachnoid Hemorrhage (SAH), resulted by a ruptured CA, has high rates of morbidity and mortality. Therefore, radiologists aim to detect it and diagnose it at an early stage, by analyzing the medical images, to prevent or reduce its damages. The analysis process is traditionally done manually. However, with the emerging of the technology, Computer-Aided Diagnosis (CAD) algorithms are adopted in the clinics to overcome the traditional process disadvantages, as the dependency of the radiologist's experience, the inter and intra observation variability, the increase in the probability of error which increases consequently with the growing number of medical images to be analyzed, and the artifacts added by the medical images' acquisition methods (i.e., MRA, CTA, PET, RA, etc.) which impedes the radiologist' s work. Due to the aforementioned reasons, many research works propose di erent segmentation approaches to automate the analysis process of detecting a CA using complementary segmentation techniques; but due to the challenging task of developing a robust reproducible reliable algorithm to detect CA regardless of its shape, size, and location from a variety of the acquisition methods, a diversity of proposed and developed approaches exist which still su er from some limitations. This thesis aims to contribute in this research area by adopting two promising techniques based on the multiresolution and statistical approaches in the Two-Dimensional (2D) domain. The rst technique is the Contourlet Transform (CT), which empowers the segmentation by extracting features not apparent in the normal image scale. While the second technique is the Hidden Markov Random Field model with Expectation Maximization (HMRF-EM), which segments the image based on the relationship of the neighboring pixels in the contourlet domain. The developed algorithm reveals promising results on the four tested Three- Dimensional Rotational Angiography (3D RA) datasets, where an objective and a subjective evaluation are carried out. For the objective evaluation, six performance metrics are adopted which are: accuracy, Dice Similarity Index (DSI), False Positive Ratio (FPR), False Negative Ratio (FNR), speci city, and sensitivity. As for the subjective evaluation, one expert and four observers with some medical background are involved to assess the segmentation visually. Both evaluations compare the segmented volumes against the ground truth data

Mathematical Methods for the Quantification of Actin-Filaments in Microscopic Images

In cell biology confocal laser scanning microscopic images of the actin filament of human osteoblasts are produced to assess the cell development. This thesis aims at an advanced approach for accurate quantitative measurements about the morphology of the bright-ridge set of these microscopic images and thus about the actin filament. Therefore automatic preprocessing, tagging and quantification interplay to approximate the capabilities of the human observer to intuitively recognize the filaments correctly. Numerical experiments with random models confirm the accuracy of this approach

Las publicaciones de Ramón Margalef en Investigación Pesquera y Scientia Marina: Los comienzos de la ecología marina en el CSIC

Ramon Margalef López (1919-2004) was one of the most prominent scientists of the 20th century in the fields of limnology, oceanography and ecology. His contributions to theoretical ecology, which won him international recognition, were based on a great deal of laboratory and field work and on extensive observations of the natural world, a passion that he acquired at a young age. Some of the early papers of Ramon Margalef appeared in the Publicaciones del Instituto de Biología Aplicada, but as of 1955 many of his marine studies were published in Investigación Pesquera, the journal of the Instituto de Investigaciones Pesqueras of the CSIC in Barcelona. He also wrote several articles for Scientia Marina, the journal that replaced Investigación Pesquera in 1989 after the Instituto de Investigaciones Pesqueras became the Institut de Ciències del Mar. The present article aims to give an overview of Margalef’s contributions to these journals to mark the celebration in 2019 of the 100th anniversary of his birth.Ramon Margalef López (1919-2004) fue uno de los científicos más destacados del siglo XX en los campos de la limnología, la oceanografía y la ecología. Sus contribuciones a la ecología teórica, que le valieron el reconocimiento internacional, se basaron en una gran cantidad de trabajo en el campo y en el laboratorio, y en extensivas observaciones del mundo natural, una pasión que adquirió a una edad temprana. Algunos de los primeros artículos de Ramon Margalef aparecieron en las Publicaciones del Instituto de Biología Aplicada pero, después de 1955, muchos de sus trabajos marinos se publicaron en Investigación Pesquera, la revista del Instituto de Investigaciones Pesqueras del CSIC en Barcelona. También escribió varios artículos para Scientia Marina, la revista que sucedió a Investigación Pesquera en 1989, después de que el Instituto de Investigaciones Pesqueras se convirtiera en el Institut de Ciències del Mar. El presente escrito tiene como objetivo dar una visión general de las contribuciones de Margalef a estas revistas, en el contexto de la reciente celebración (2019) del centenario de su nacimiento