1,156 research outputs found

    ModuLand plug-in for Cytoscape: determination of hierarchical layers of overlapping network modules and community centrality

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    Summary: The ModuLand plug-in provides Cytoscape users an algorithm for determining extensively overlapping network modules. Moreover, it identifies several hierarchical layers of modules, where meta-nodes of the higher hierarchical layer represent modules of the lower layer. The tool assigns module cores, which predict the function of the whole module, and determines key nodes bridging two or multiple modules. The plug-in has a detailed JAVA-based graphical interface with various colouring options. The ModuLand tool can run on Windows, Linux, or Mac OS. We demonstrate its use on protein structure and metabolic networks. Availability: The plug-in and its user guide can be downloaded freely from: http://www.linkgroup.hu/modules.php. Contact: [email protected] Supplementary information: Supplementary information is available at Bioinformatics online.Comment: 39 pages, 1 figure and a Supplement with 9 figures and 10 table

    Improving Safety-Critical Systems by Visual Analysis

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    The importance analysis provides a means of analyzing the contribution of potential low-level system failures to identify and assess vulnerabilities of safety-critical systems. Common approaches attempt to enhance the system safety by addressing vulnerabilities using an iterative analysis process, while considering relevant constraints, e.g., cost, for optimizing the improvements. Typically, data regarding the analysis process is presented across several views with few interactive associations among them. Consequently, this hampers the identification of meaningful information supporting the decision making process. In this paper, we propose a visualization system that visually supports engineers in identifying proper solutions. The visualization integrates a decision tree with a plot representing the cause-effect relationship between the improvement ideas of vulnerabilities and the resulting risk reduction of system. Associating a component fault tree view with the plot allows to maintain helpful context information. The introduced visualization approach enables system and safety engineers to identify and analyze optimal solutions facilitating the improvement of the overall system safety

    Generating Accurate Dependencies for Large Software

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    Dependencies between program elements can reflect the architecture, design, and implementation of a software project. According a industry report, intra- and inter-module dependencies can be a significant source of latent threats to software maintainability in long-term software development, especially when the software has millions of lines of code. This thesis introduces the design and implementation of an accurate and scalable analysis tool that extracts code dependencies from large C/C++ software projects. The tool analyzes both symbol-level and module-level dependencies of a software system and provides an utilization-based dependency model. The accurate dependencies generated by the tool can be provided as the input to other software analysis suits; the results along can help developers identify potential underutilized and inconsistent dependencies in the software. Such information points to potential refactoring opportunities and assists developers with large-scale refactoring tasks.1 yea

    A fuzzy method for propagating functional architecture constraints to physical architecture.

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    International audienceModular product design has received great attention for about 10 years, but few works have proposed tools to either jointly design the functional and physical architectures or propagate the impact of evolutions from one domain to another. In this paper, we present a new method supporting the product architecture design. In new product development situations or in reengineering projects, system architects could use this method in the early design stages to predetermine cohesive modules and integrative elements and to simulate a domain architecture by propagating architecture choices from another domain. To illustrate our approach, we present an industrial case study concerning the design of a new automobile powertrain

    Assessing architectural evolution: A case study

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    This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2011 SpringerThis paper proposes to use a historical perspective on generic laws, principles, and guidelines, like Lehman’s software evolution laws and Martin’s design principles, in order to achieve a multi-faceted process and structural assessment of a system’s architectural evolution. We present a simple structural model with associated historical metrics and visualizations that could form part of an architect’s dashboard. We perform such an assessment for the Eclipse SDK, as a case study of a large, complex, and long-lived system for which sustained effective architectural evolution is paramount. The twofold aim of checking generic principles on a well-know system is, on the one hand, to see whether there are certain lessons that could be learned for best practice of architectural evolution, and on the other hand to get more insights about the applicability of such principles. We find that while the Eclipse SDK does follow several of the laws and principles, there are some deviations, and we discuss areas of architectural improvement and limitations of the assessment approach

    Project-Team RMoD (Analyses and Language Constructs for Object-Oriented Application Evolution) 2009 Activity Report

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    This is the yearly report of the RMOD team. A good way to understand what we are doing

    MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks

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    Predicting multiple real-world tasks in a single model often requires a particularly diverse feature space. Multimodal (MM) models aim to extract the synergistic predictive potential of multiple data types to create a shared feature space with aligned semantic meaning across inputs of drastically varying sizes (i.e. images, text, sound). Most current MM architectures fuse these representations in parallel, which not only limits their interpretability but also creates a dependency on modality availability. We present MultiModN, a multimodal, modular network that fuses latent representations in a sequence of any number, combination, or type of modality while providing granular real-time predictive feedback on any number or combination of predictive tasks. MultiModN's composable pipeline is interpretable-by-design, as well as innately multi-task and robust to the fundamental issue of biased missingness. We perform four experiments on several benchmark MM datasets across 10 real-world tasks (predicting medical diagnoses, academic performance, and weather), and show that MultiModN's sequential MM fusion does not compromise performance compared with a baseline of parallel fusion. By simulating the challenging bias of missing not-at-random (MNAR), this work shows that, contrary to MultiModN, parallel fusion baselines erroneously learn MNAR and suffer catastrophic failure when faced with different patterns of MNAR at inference. To the best of our knowledge, this is the first inherently MNAR-resistant approach to MM modeling. In conclusion, MultiModN provides granular insights, robustness, and flexibility without compromising performance.Comment: Accepted as a full paper at NeurIPS 2023 in New Orleans, US

    A Core Reference Hierarchical Primitive Ontology for Electronic Medical Records Semantics Interoperability

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    Currently, electronic medical records (EMR) cannot be exchanged among hospitals, clinics, laboratories, pharmacies, and insurance providers or made available to patients outside of local networks. Hospital, laboratory, pharmacy, and insurance provider legacy databases can share medical data within a respective network and limited data with patients. The lack of interoperability has its roots in the historical development of electronic medical records. Two issues contribute to interoperability failure. The first is that legacy medical record databases and expert systems were designed with semantics that support only internal information exchange. The second is ontological commitment to the semantics of a particular knowledge representation language formalism. This research seeks to address these interoperability failures through demonstration of the capability of a core reference, hierarchical primitive ontological architecture with concept primitive attributes definitions to integrate and resolve non-interoperable semantics among and extend coverage across existing clinical, drug, and hospital ontologies and terminologies
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