Automatic Segmentation of Subfigure Image Panels for Multimodal Biomedical Document Retrieval

Biomedical images are often referenced for clinical decision support (CDS), educational purposes, and research. The task of automatically finding the images in a scientific article that are most useful for the purpose of determining relevance to a clinical situation is traditionally done using text and is quite challenging. We propose to improve this by associating image features from the entire image and from relevant regions of interest with biomedical concepts described in the figure caption or discussion in the article. However, images used in scientific article figures are often composed of multiple panels where each sub-figure (panel) is referenced in the caption using alphanumeric labels, e.g. Figure 1(a), 2(c), etc. It is necessary to separate individual panels from a multi-panel figure as a first step toward automatic annotation of images. In this work we present methods that add make robust our previous efforts reported here. Specifically, we address the limitation in segmenting figures that do not exhibit explicit inter-panel boundaries, e.g. illustrations, graphs, and charts. We present a novel hybrid clustering algorithm based on particle swarm optimization (PSO) with fuzzy logic controller (FLC) to locate related figure components in such images. Results from our evaluation are very promising with 93.64% panel detection accuracy for regular (non-illustration) figure images and 92.1% accuracy for illustration images. A computational complexity analysis also shows that PSO is an optimal approach with relatively low computation time. The accuracy of separating these two type images is 98.11% and is achieved using decision tree

Design and implementation of the land surface model NaturalEnvironment within the generic framework OpenDanubia for integrative, distributed environmental modelling

The project GLOWA-Danube (http://www.glowa-danube.de) aimed at investigating the manifold consequences of Global Change on regional water resources in the Upper Danube Basin. In order to achieve this task, an interdisciplinary, university-based network of experts developed the integrative Decision Support System OpenDanubia (OD). The common base for implementing and coupling the various scientific model components is a generic framework, which provides the coordination of the coupled models that run in parallel exchanging iteratively data via their interfaces. The OD framework takes care of technical aspects, such as ordered data exchange between sub-models, data aggregation, data output, model parallelization and data distribution over the network, which means that model developers do not have to be concerned about complexities evolving from coupling their models. Within this framework the sub-model NaturalEnvironment, representing a land surface model, was developed and implemented. The object-oriented design of this sub-model facilitates a plain, logical representation of the actual physical processes simulated by the sub-model. Physical processes to be modelled are organized in naturally ordered, exchangeable lists that are executed on each spatial computation unit for each modelling time step, depending on their land cover. The type of land cover to be simulated on each freely defined spatial unit is distinguished by one of the three types aquatic, terrestrial and glacier. Additionally, the type terrestrial is influenced by dynamic land use changes which can be triggered e.g. by the socio-economic OD sub-model Farming. This paper presents the basic design of the open source (GPL'ed) OD framework and highlights the implementation of the sub-model NaturalEnvironment within this framework, as well as its interactions with other components included in OD

Utilising Provenance to Enhance Social Computation

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Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Transdisciplinarity seen through Information, Communication, Computation, (Inter-)Action and Cognition

Similar to oil that acted as a basic raw material and key driving force of industrial society, information acts as a raw material and principal mover of knowledge society in the knowledge production, propagation and application. New developments in information processing and information communication technologies allow increasingly complex and accurate descriptions, representations and models, which are often multi-parameter, multi-perspective, multi-level and multidimensional. This leads to the necessity of collaborative work between different domains with corresponding specialist competences, sciences and research traditions. We present several major transdisciplinary unification projects for information and knowledge, which proceed on the descriptive, logical and the level of generative mechanisms. Parallel process of boundary crossing and transdisciplinary activity is going on in the applied domains. Technological artifacts are becoming increasingly complex and their design is strongly user-centered, which brings in not only the function and various technological qualities but also other aspects including esthetic, user experience, ethics and sustainability with social and environmental dimensions. When integrating knowledge from a variety of fields, with contributions from different groups of stakeholders, numerous challenges are met in establishing common view and common course of action. In this context, information is our environment, and informational ecology determines both epistemology and spaces for action. We present some insights into the current state of the art of transdisciplinary theory and practice of information studies and informatics. We depict different facets of transdisciplinarity as we see it from our different research fields that include information studies, computability, human-computer interaction, multi-operating-systems environments and philosophy.Comment: Chapter in a forthcoming book: Information Studies and the Quest for Transdisciplinarity - Forthcoming book in World Scientific. Mark Burgin and Wolfgang Hofkirchner, Editor

Efficient Iterative Processing in the SciDB Parallel Array Engine

Many scientific data-intensive applications perform iterative computations on array data. There exist multiple engines specialized for array processing. These engines efficiently support various types of operations, but none includes native support for iterative processing. In this paper, we develop a model for iterative array computations and a series of optimizations. We evaluate the benefits of an optimized, native support for iterative array processing on the SciDB engine and real workloads from the astronomy domain