Damping of MHD turbulence in partially ionized plasma: implications for cosmic ray propagation

We study the damping from neutral-ion collisions of both incompressible and compressible magnetohydrodynamic (MHD) turbulence in partially ionized medium. We start from the linear analysis of MHD waves applying both single-fluid and two-fluid treatments. The damping rates derived from the linear analysis are then used in determining the damping scales of MHD turbulence. The physical connection between the damping scale of MHD turbulence and cutoff boundary of linear MHD waves is investigated. Our analytical results are shown to be applicable in a variety of partially ionized interstellar medium (ISM) phases and solar chromosphere. As a significant astrophysical utility, we introduce damping effects to propagation of cosmic rays in partially ionized ISM. The important role of turbulence damping in both transit-time damping and gyroresonance is identified.Comment: 29 pages, 16 figure

Design reuse research : a computational perspective

This paper gives an overview of some computer based systems that focus on supporting engineering design reuse. Design reuse is considered here to reflect the utilisation of any knowledge gained from a design activity and not just past designs of artefacts. A design reuse process model, containing three main processes and six knowledge components, is used as a basis to identify the main areas of contribution from the systems. From this it can be concluded that while reuse libraries and design by reuse has received most attention, design for reuse, domain exploration and five of the other knowledge components lack research effort

A History of Cluster Analysis Using the Classification Society's Bibliography Over Four Decades

The Classification Literature Automated Search Service, an annual bibliography based on citation of one or more of a set of around 80 book or journal publications, ran from 1972 to 2012. We analyze here the years 1994 to 2011. The Classification Society's Service, as it was termed, has been produced by the Classification Society. In earlier decades it was distributed as a diskette or CD with the Journal of Classification. Among our findings are the following: an enormous increase in scholarly production post approximately 2000; a very major increase in quantity, coupled with work in different disciplines, from approximately 2004; and a major shift also from cluster analysis in earlier times having mathematics and psychology as disciplines of the journals published in, and affiliations of authors, contrasted with, in more recent times, a "centre of gravity" in management and engineering.Comment: 23 pages, 9 figure

Quasi-local energy-momentum and two-surface characterization of the pp-wave spacetimes

In the present paper the determination of the {\it pp}-wave metric form the geometry of certain spacelike two-surfaces is considered. It has been shown that the vanishing of the Dougan--Mason quasi-local mass $m_{\$}$, associated with the smooth boundary $\$:=\partial\Sigma\approx S^2$ of a spacelike hypersurface $\Sigma$, is equivalent to the statement that the Cauchy development $D(\Sigma)$ is of a {\it pp}-wave type geometry with pure radiation, provided the ingoing null normals are not diverging on $\$$ and the dominant energy condition holds on $D(\Sigma)$. The metric on $D(\Sigma)$ itself, however, has not been determined. Here, assuming that the matter is a zero-rest-mass-field, it is shown that both the matter field and the {\it pp}-wave metric of $D(\Sigma)$ are completely determined by the value of the zero-rest-mass-field on $\$$ and the two dimensional Sen--geometry of $\$$ provided a convexity condition, slightly stronger than above, holds. Thus the {\it pp}-waves can be characterized not only by the usual Cauchy data on a {\it three} dimensional $\Sigma$ but by data on its {\it two} dimensional boundary $\$$ too. In addition, it is shown that the Ludvigsen--Vickers quasi-local angular momentum of axially symmetric {\it pp}-wave geometries has the familiar properties known for pure (matter) radiation.Comment: 15 pages, Plain Tex, no figure

Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

Patent Data for Engineering Design: A Critical Review and Future Directions

Patent data have long been used for engineering design research because of its large and expanding size, and widely varying massive amount of design information contained in patents. Recent advances in artificial intelligence and data science present unprecedented opportunities to develop data-driven design methods and tools, as well as advance design science, using the patent database. Herein, we survey and categorize the patent-for-design literature based on its contributions to design theories, methods, tools, and strategies, as well as the types of patent data and data-driven methods used in respective studies. Our review highlights promising future research directions in patent data-driven design research and practice.Comment: Accepted by JCIS

Ontology Extraction and Usage in the Scholarly Knowledge Domain

Ontologies of research areas have been proven to be useful resources for analysing and making sense of scholarly data. In this chapter, we present the Computer Science Ontology (CSO), which is the largest ontology of research areas in the field, and discuss a number of applications that build on CSO to support high-level tasks, such as topic classification, metadata extraction, and recommendation of books

Design of a heat transfer subsystem using a real time expert system

The aim of this work is to design and develop an interactive and real time expert system for the automation of the design of a heat transfer subsystems; Each set (representing the design configuration) is evaluated in terms of performance criteria (e.g., pressure drop across each component, capital costs, and operating costs of the system) to obtain a plausible design of the power plant. The design and operational parameters for various components of the power plant are optimized for a given level of power output, using a numerical algorithm; An expert tool, G2 developed by the Gensym Corporation is used in creating the application knowledge base. The application development mainly concentrates on the piping network, the heat exchanger system, and the pumping system. The optimal information obtained from the numerical algorithm for different power outputs is in turn provided to the knowledge base. Thus, when the demand for the power output changes, the application will automatically access this information and make the necessary changes to the power plant components for optimized operation. The model application is designed such that, if the monitored values deviate from the allowed range, appropriate warning messages are generated, and if possible, actions are taken to avoid damaging consequences. (Abstract shortened by UMI.)

Data science for engineering design: State of the art and future directions

Abstract Engineering design (ED) is the process of solving technical problems within requirements and constraints to create new artifacts. Data science (DS) is the inter-disciplinary field that uses computational systems to extract knowledge from structured and unstructured data. The synergies between these two fields have a long story and throughout the past decades, ED has increasingly benefited from an integration with DS. We present a literature review at the intersection between ED and DS, identifying the tools, algorithms and data sources that show the most potential in contributing to ED, and identifying a set of challenges that future data scientists and designers should tackle, to maximize the potential of DS in supporting effective and efficient designs. A rigorous scoping review approach has been supported by Natural Language Processing techniques, in order to offer a review of research across two fuzzy-confining disciplines. The paper identifies challenges related to the two fields of research and to their interfaces. The main gaps in the literature revolve around the adaptation of computational techniques to be applied in the peculiar context of design, the identification of data sources to boost design research and a proper featurization of this data. The challenges have been classified considering their impacts on ED phases and applicability of DS methods, giving a map for future research across the fields. The scoping review shows that to fully take advantage of DS tools there must be an increase in the collaboration between design practitioners and researchers in order to open new data driven opportunities