AIERO: An algorithm for identifying engineering relationships in ontologies

Semantic technologies are playing an increasingly popular role as a means for advancing the capabilities of knowledge management systems. Among these advancements, researchers have successfully leveraged semantic technologies, and their accompanying techniques, to improve the representation and search capabilities of knowledge management systems. This paper introduces a further application of semantic techniques. We explore semantic relatedness as a means of facilitating the development of more “intelligent” engineering knowledge management systems. Using semantic relatedness quantifications to analyze and rank concept pairs, this novel approach exploits semantic relationships to help identify key engineering relationships, similar to those leveraged in change management systems, in product development processes. As part of this work, we review several different semantic relatedness techniques, including a meronomic technique recently introduced by the authors. We introduce an aggregate measure, termed “An Algorithm for Identifying Engineering Relationships in Ontologies,” or AIERO, as a means to purposely quantify semantic relationships within product development frameworks. To assess its consistency and accuracy, AIERO is tested using three separate, independently developed ontologies. The results indicate AIERO is capable of returning consistent rankings of concept pairs across varying knowledge frameworks. A PCB (printed circuit board) case study then highlights AIERO’s unique ability to leverage semantic relationships to systematically narrow where engineering interdependencies are likely to be found between various elements of product development processes

Towards Industrial Implementation of Emerging Semantic Technologies

Every new design, project, or procedure within a company generates a considerable amount of new information and important knowledge. Furthermore, a tremendous amount of legacy knowledge already exists in companies in electronic and non-electronic formats, and techniques are needed for representing, structuring and reusing this knowledge. Many researchers have spent considerable time and effort developing semantic knowledge management systems, which in theory are presumed to address these problems. Despite significant research investments, little has been done to implement these systems within an industrial setting. In this paper we identify five main requirements to the development of an industry-ready application of semantic knowledge management systems and discuss how each of these can be addressed. These requirements include the ease of new knowledge management software adoption, the incorporation of legacy information, the ease of use of the user interface, the security of the stored information, and the robustness of the software to support multiple file types and allow for the sharing of information across platforms. Collaboration with Raytheon, a defense and aerospace systems company, allowed our team to develop and demonstrate a successful adoption of semantic abilities by a commercial company. Salient features of this work include a new tool, the e-Design MemoExtractor Software Tool, designed to mine and capture company information, a Raytheon-specific extension to the e-Design Framework, and a novel semantic environment in the form of a customized semantic wikiSMW+. The advantages of this approach are discussed in the context of the industrial case study with Raytheon

DFT-based Conformational Analysis of a Phospholipid Molecule (DMPC)

The conformational space of the dimyristoyl phosphatidylcholine (DMPC) molecule has been studied using Density Functional Theory (DFT), augmented with a damped empirical dispersion energy term (DFT-D). Fourteen ground-state isomers have been found with total energies within less than 1 kcal/mol. Despite differences in combinations of their torsion angles, all these conformers share a common geometric profile, which includes a balance of attractive, repulsive and constraint forces between and within specific groups of atoms. The definition of this profile fits with most of the structural characteristics deduced from measured NMR properties of DMPC solutions. The calculated vibrational spectrum of the molecule is in good agreement with experimental data obtained for DMPC bilayers. These results support the idea that DMPC molecules preserve their individual molecular structures in the various assemblies.Comment: 31 pages, 6 Tables, 4 Figure

A localised chlorophyll deficiency associated with male sterility in Nicotiana tabacum L.

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Size--sensitive melting characteristics of gallium clusters: Comparison of Experiment and Theory for Ga17+_{17}{}^{+} and Ga20+_{20}{}^{+}

Experiments and simulations have been performed to examine the finite-temperature behavior of Ga$_{17}{}^{+}$ and Ga$_{20}{}^{+}$ clusters. Specific heats and average collision cross sections have been measured as a function of temperature, and the results compared to simulations performed using first principles Density--Functional Molecular--Dynamics. The experimental results show that while Ga$_{17}{}^{+}$ apparently undergoes a solid--liquid transition without a significant peak in the specific--heat, Ga$_{20}{}^{+}$ melts with a relatively sharp peak. Our analysis of the computational results indicate a strong correlation between the ground--state geometry and the finite--temperature behavior of the cluster. If the ground--state geometry is symmetric and "ordered" the cluster is found to have a distinct peak in the specific--heat. However, if the ground--state geometry is amorphous or "disordered" the cluster melts without a peak in the specific--heat.Comment: 6 figure