An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term

An extensible benchmark and tooling for comparing reverse engineering approaches

Various tools exist to reverse engineer software source code and generate design information, such as UML projections. Each has specific strengths and weaknesses, however no standardised benchmark exists that can be used to evaluate and compare their performance and effectiveness in a systematic manner. To facilitate such comparison in this paper we introduce the Reverse Engineering to Design Benchmark (RED-BM), which consists of a comprehensive set of Java-based targets for reverse engineering and a formal set of performance measures with which tools and approaches can be analysed and ranked. When used to evaluate 12 industry standard tools performance figures range from 8.82\% to 100\% demonstrating the ability of the benchmark to differentiate between tools. To aid the comparison, analysis and further use of reverse engineering XMI output we have developed a parser which can interpret the XMI output format of the most commonly used reverse engineering applications, and is used in a number of tools

A free and open source programming library for landscape metrics calculations

Landscape metrics are used in a wide range of environmental studies such as land use change and land degradation studies, soil erosion and run-off predictions, management of hunting communities, and strategic planning for environmental management, to name just a few. Due to their utility for a variety of applications, there are many indices and software packages that have been designed to provide calculations and analysis of landscape structure patterns in categorical maps. With the purpose of making a comparison between the most used tools (Fragstats, V-Late, PA4...), this paper examines their advantages and disadvantages in order to create a list of common features that need to be incorporated into this type of software. An Application Programming Interface (API) is produced without limitations on data input, that is capable of calculating vector or raster metrics and is extensible. This API should make it possible not only to build third party applications easily, but also make it possible to add new metrics and research into new paradigms related to traditional landscape metrics. Land-metrics DIY (DoIt Yourself) is the library presented in this paper. It can calculate almost 40 landscape metrics from geometry provided by an ESRI Shapefile. © 2011 Elsevier Ltd.We especially appreciate the comments and suggestions by A. Jakeman and three anonymous reviewers which led to substantial improvements of the manuscript. This paper is partially supported by the FPU - Doctoral Research Scholarship program of the "Ministerio de Educacion de Espana" (2007-2011). Moreover, we would like to thank all the FOSS community, and in particular to Diego Guidi (NTS main developer) for their interesting and important work. Of course, we also thank the OGC and all FOSS projects related to spatial information because they suppose a strategic support to the further development of our idea and other possible GIS projects.Zaragozi Zaragozi, BM.; Belda Antoli, A.; Linares Pellicer, JJ.; Martínez-Pérez, JE.; Navarro, JT.; Esparza Peidro, J. (2012). A free and open source programming library for landscape metrics calculations. Environmental Modelling and Software. 31:131-140. doi:10.1016/j.envsoft.2011.10.009S1311403

Algorithms for automated assignment of solution-state and solid-state protein NMR spectra.

Protein nuclear magnetic resonance spectroscopy (Protein NMR) is an invaluable analytical technique for studying protein structure, function, and dynamics. There are two major types of NMR spectroscopy that are used for investigation of protein structure – solution-state and solid-state NMR. Solution-based NMR spectroscopy is typically applied to proteins of small and medium size that are soluble in water. Solid-state NMR spectroscopy is amenable for proteins that are insoluble in water. In the vast majority NMR-based protein studies, the first step after experiment optimization is the assignment of protein resonances via the association of chemical shift values to specific atoms in a protein macromolecule. Depending on the quality of the spectra, a manual protein resonance assignment process often requires a considerable amount of time, from weeks to months-worth of effort even, by an experienced NMR spectroscopist . The resonance assignment processes for solution-state and solid-state protein NMR studies are conceptually similar, but have distinct differences due to the utilization of different NMR experiments and to the use of different resonances for grouping peaks into spin systems. Currently, there is a shortage of robust, effective software tools that can perform solid-state protein resonance assignment and there is no general software that can perform both solution-state and solid-state protein resonance assignment in a reliable, automated fashion. Hence, the motivation of this research is to design and implement algorithms and software tools that will automate the resonance assignment problem. As a result of this research, several algorithms and software packages that aid several important steps in the protein resonance assignment process were developed. For example, the nmrstarlib software package can access and utilize data deposited in the NMR-STAR format; the core of this library is the lexical analyzer for NMR-STAR syntax that acts as a generator-based state-machine for token processing. The jpredapi software package provides an easy-to-use API to submit and retrieve results from secondary structure prediction server. The single peak list and pairwise peak list registration algorithms address the problem of multiple sources of variance within single peak list and between different peak lists and is capable of calculating the match tolerance values necessary for spin system grouping. The single peak list and pairwise peak list grouping algorithms are based on the well-known DBSCAN clustering algorithm and are designed to group peaks into spin systems within single peak list as well as between different peak lists

Blueprint model and language for engineering cloud applications

Abstract: The research presented in this thesis is positioned within the domain of engineering CSBAs. Its contribution is twofold: (1) a uniform specification language, called the Blueprint Specification Language (BSL), for specifying cloud services across several cloud vendors and (2) a set of associated techniques, called the Blueprint Manipulation Techniques (BMTs), for publishing, querying, and composing cloud service specifications with aim to support the flexible design and configuration of an CSBA.

Exchange of knowledge in customized product development processes

If Customized Product Development is perceived as developing products that fulfill the customers individual requirements and in parallel reflect production constraints, such as manufacturing capabilities, a direct demand can be derived for solutions to adapt a given design easy and fast to new requirements based upon the companies production knowledge - at best in an automated way. The latter is usually covered by Knowledge Based Engineering systems. KBE systems are capable to automate repetitive engineering tasks, such as the automated calculation of ship structural design. However, while the efficiency of implemented KBE projects is non controversial, the development or modification of an existing KBE solution usually requires substantial investments due to knowledge acquisition, codification and software implementation. In addition most solutions are still case based and not grounded in structural frameworks. Knowledge is often written in a proprietary language; rules and algorithms are not compatible with other KBE-frameworks and are usually not on a level that is comprehensible for the engineers or domain experts. While this may not be crucial for long development cycles, it may become a hurdle in terms of Customized Product Development with its short cycles. In other words, future KBE must support an incorporation of knowledge from different domains and business units. Thus the objective of the paper is to explain the need for a change in collaborative knowledge sharing and re-use in context of KBE. Based upon, the constraints for a KBE related interchange format are drafted. A three layered approach is proposed in order to adequately represent and exchange KBE knowledge. Each layer addresses different levels of abstraction: an upper layer describing just the core knowledge at a glance, a middle layer in order to codify the knowledge on abstract level, but with purpose of software development and a base layer covering the software code itself. Utilizing an independent format for management of KBE knowledge, the users of CAx systems are able to exchange codified knowledge and gain the rationale behind. Hence the full paper attempts to deliver a substantial contribution for the development of systems, which are capable to easily adapt a given design to upcoming user-requirements, while facing the production challenges

Host-Based Virtual Networks Management in Cloud Datacenters

Infrastructure management is of key importance in a wide array of computer and network environments. The use of virtualization in cloud datacenters has driven the communications and computing convergence to a common operational entity. Failure to effectively manage the involved infrastructure results as impediments in provisioning a successful service. Information models facilitate the infrastructure management and current solutions can be effectively applied in most datacenter scenarios, apart from cases where the networking architecture relies heavily on systems virtualization. In this paper we propose an information model for managing virtual network architectures, where hypervisors and computing server resources are deployed as the basis of the networking layer. We provide a successful proof of concept by managing a virtual machine-based network infrastructure acting as an IP routing platform using statistical methods. Our proposal enables a dynamic reconfiguration of allocated infrastructure resources adapting, in real-time, to variations in the imposed workload