Randomized nonlinear component analysis

Copyright © (2014) by the International Machine Learning Society (IMLS) All rights reserved. Classical methods such as Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA) are ubiquitous in statistics. However, these techniques are only able to reveal linear re-lationships in data. Although nonlinear variants of PCA and CCA have been proposed, these are computationally prohibitive in the large scale. In a separate strand of recent research, randomized methods have been proposed to construct features that help reveal nonlinear patterns in data. For basic tasks such as regression or classification, random features exhibit little or no loss in performance, while achieving drastic savings in computational requirements. In this paper we leverage randomness to design scalable new variants of nonlinear PCA and CCA; our ideas extend to key multivariate analysis tools such as spectral clustering or LDA. We demonstrate our algorithms through experiments on real- world data, on which we compare against the state-of-the-art. A simple R implementation of the presented algorithms is provided.

Visual pattern recognition models for remote sensing of civil infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Tailored seeding geometries for the multi-fidelity design of compression systems

Design optimisation of compressor systems is a computationally expensive problem due to the large number of variables, complicated design space and expense of the analysis tools. One approach to reduce the expense of the process and make it achievable in industrial timescales is to employ multi-fidelity techniques, which utilise more rapid tools in conjunction with the highest fidelity analyses. The complexity of the compressor design landscape is such that the starting point for these optimisations can influence the achievable results; these starting points are often existing (optimised) compressor designs, which form a limited set in terms of both quantity and diversity of the design. To facilitate the multi-fidelity optimisation procedure, a compressor synthesis code was developed which allowed the performance attributes (e.g. stage loadings, inlet conditions) to be stipulated, enabling the generation of a variety of compressors covering a range of both design topology and quality to act as seeding geometries for the optimisation procedures. Analysis of the performance of the multi-fidelity optimisation system when restricting its exploration space to topologically different areas of the design space indicated little advantage over allowing the system to search the design space itself. However, comparing results from optimisations started from seed designs with different aerodynamic qualites indicated an improved performance could be achieved by starting an optimisation from a higher quality point, and thus that the choice of starting point did affect the final outcome of the optimisations. Both investigations indicated that the performance gains through the optimisation were largely defined by the early exploration of the design space where the multi-fidelity speedup could be exploited, thus extending this region is likely to have the greatest effect on performance of the optimisation system. © 2013 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Parallel coordinates in computational engineering design

Modern Engineering Design involves the deployment of many computational tools. Re- search on challenging real-world design problems is focused on developing improvements for the engineering design process through the integration and application of advanced com- putational search/optimization and analysis tools. Successful application of these methods generates vast quantities of data on potential optimum designs. To gain maximum value from the optimization process, designers need to visualise and interpret this information leading to better understanding of the complex and multimodal relations between param- eters, objectives and decision-making of multiple and strongly conflicting criteria. Initial work by the authors has identified that the Parallel Coordinates interactive visualisation method has considerable potential in this regard. This methodology involves significant levels of user-interaction, making the engineering designer central to the process, rather than the passive recipient of a deluge of pre-formatted information. In the present work we have applied and demonstrated this methodology in two differ- ent aerodynamic turbomachinery design cases; a detailed 3D shape design for compressor blades, and a preliminary mean-line design for the whole compressor core. The first case comprises 26 design parameters for the parameterisation of the blade geometry, and we analysed the data produced from a three-objective optimization study, thus describing a design space with 29 dimensions. The latter case comprises 45 design parameters and two objective functions, hence developing a design space with 47 dimensions. In both cases the dimensionality can be managed quite easily in Parallel Coordinates space, and most importantly, we are able to identify interesting and crucial aspects of the relationships between the design parameters and optimum level of the objective functions under con- sideration. These findings guide the human designer to find answers to questions that could not even be addressed before. In this way, understanding the design leads to more intelligent decision-making and design space exploration. © 2012 AIAA.

On the application of differential geometry to MDO

Multidisciplinary Design Optimization (MDO) is a methodology for optimizing large coupled systems. Over the years, a number of different MDO decomposition strategies, known as architectures, have been developed, and various pieces of analytical work have been done on MDO and its architectures. However, MDO lacks an overarching paradigm which would unify the field and promote cumulative research. In this paper, we propose a differential geometry framework as such a paradigm: Differential geometry comes with its own set of analysis tools and a long history of use in theoretical physics. We begin by outlining some of the mathematics behind differential geometry and then translate MDO into that framework. This initial work gives new tools and techniques for studying MDO and its architectures while producing a naturally arising measure of design coupling. The framework also suggests several new areas for exploration into and analysis of MDO systems. At this point, analogies with particle dynamics and systems of differential equations look particularly promising for both the wealth of extant background theory that they have and the potential predictive and evaluative power that they hold. © 2012 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

Tailored seeding geometries for the multi-fidelity design of compression systems

Design optimisation of compressor systems is a computationally expensive problem due to the large number of variables, complicated design space and expense of the analysis tools. One approach to reduce the expense of the process and make it achievable in industrial timescales is to employ multi-fidelity techniques, which utilise more rapid tools in conjunction with the highest fidelity analyses. The complexity of the compressor design landscape is such that the starting point for these optimisations can influence the achievable results; these starting points are often existing (optimised) compressor designs, which form a limited set in terms of both quantity and diversity of the design. To facilitate the multi-fidelity optimisation procedure, a compressor synthesis code was developed which allowed the performance attributes (e.g. stage loadings, inlet conditions) to be stipulated, enabling the generation of a variety of compressors covering a range of both design topology and quality to act as seeding geometries for the optimisation procedures. Analysis of the performance of the multi-fidelity optimisation system when restricting its exploration space to topologically different areas of the design space indicated little advantage over allowing the system to search the design space itself. However, comparing results from optimisations started from seed designs with different aerodynamic qualites indicated an improved performance could be achieved by starting an optimisation from a higher quality point, and thus that the choice of starting point did affect the final outcome of the optimisations. Both investigations indicated that the performance gains through the optimisation were largely defined by the early exploration of the design space where the multi-fidelity speedup could be exploited, thus extending this region is likely to have the greatest effect on performance of the optimisation system. © 2012 AIAA.

Analysis of document-mining techniques and tools for technology intelligence: Discovering knowledge from technical documents

This research proposes a method for extracting technology intelligence (TI) systematically from a large set of document data. To do this, the internal and external sources in the form of documents, which might be valuable for TI, are first identified. Then the existing techniques and software systems applicable to document analysis are examined. Finally, based on the reviews, a document-mining framework designed for TI is suggested and guidelines for software selection are proposed. The research output is expected to support intelligence operatives in finding suitable techniques and software systems for getting value from document-mining and thus facilitate effective knowledge management. Copyright © 2012 Inderscience Enterprises Ltd.

CLADP - THE CAMBRIDGE LINEAR ANALYSIS AND DESIGN PROGRAMS USER REFERENCE MANUAL (4TH ISSUE: APRIL 1983).

CLADP is an engineering software program developed at Cambridge University for the interactive computer aided design of feedback control systems. CLADP contains a wide range of tools for the analysis of complex systems, and the assessment of their performance when feedback control is applied, thus enabling control systems to be designed to meet difficult performance objectives. The range of tools within CLADP include the latest techniques in the field whose central theme is the extension of classical frequency domain concepts (well known and well proven for single loop systems) to multivariable or multiloop systems, and by making extensive use of graphical presentation information is provided in a readily understood form.

Design of carbon nanotubes based microwave applications employing mechanical resonance analysis

Carbon nanotubes (CNTs) have good mechanical properties and unique structural, electronic, thermal, and optical characteristics. In this work, we present the results of our investigations of a resonator device based on embedded vertical CNT arrays. The device's design is based on the mechanical resonance of the tubes. CoventorWare FEA tools have been used to simulate the mechanical resonance frequencies of the vertical nanotubes arrays integrated on a silicon substrate. ©2008 IEEE.

Proceedings of an international workshop on the value of computer-based engineering tools, held in Cambridge in April 1997

There is increasing adoption of computer-based tools to support the product development process. Tolls include computer-aided design, computer-aided manufacture, systems engineering and product data management systems. The fact that companies choose to invest in tools might be regarded as evidence that tools, in aggregate, are perceived to possess business value through their application to engineering activities. Yet the ways in which value accrues from tool technology are poorly understood.

This report records the proceedings of an international workshop during which some novel approaches to improving our understanding of this problem of tool valuation were presented and debated. The value of methods and processes were also discussed. The workshop brought together British, Dutch, German and Italian researchers. The presenters included speakers from industry and academia (the University of Cambridge, the University of Magdeburg and the Politechnico de Torino)

The work presented showed great variety. Research methods include case studies, questionnaires, statistical analysis, semi-structured interviews, deduction, inductive reasoning, the recording of anecdotes and analogies. The presentations drew on financial investment theory, the industrial experience of workshop participants, discussions with students developing tools, modern economic theories and speculation on the effects of company capabilities.

An analysis of factors improving technology roadmap credibility: A communications theory assessment of roadmapping processes

In recent years, many industrial firms have been able to use roadmapping as an effective process methodology for projecting future technology and for coordinating technology planning and strategy. Firms potentially realize a number of benefits in deploying technology roadmapping (TRM) processes. Roadmaps provide information identifying which new technologies will meet firms' future product demands, allowing companies to leverage R&D investments through choosing appropriately out of a range of alternative technologies. Moreover, the roadmapping process serves an important communication tool helping to bring about consensus among roadmap developers, as well as between participants brought in during the development process, who may communicate their understanding of shared corporate goals through the roadmap. However, there are few conceptual accounts or case studies have made the argument that roadmapping processes may be used effectively as communication tools. This paper, therefore, seeks to elaborate a theoretical foundation for identifying the factors that must be considered in setting up a roadmap and for analyzing the effect of these factors on technology roadmap credibility as perceived by its users. Based on the survey results of 120 different R&D units, this empirical study found that firms need to explore further how they can enable frequent interactions between the TRM development team and TRM participants. A high level of interaction will improve the credibility of a TRM, with communication channels selected by the organization also positively affecting TRM credibility. © 2011 Elsevier Inc.

A matrix-calculation-based algorithm for numerical change propagation analysis

Engineering changes (ECs) are raised throughout the lifecycle of engineering products. A single change to one component produces knock-on effects on others necessitating additional changes. This change propagation significantly affects the development time and cost and determines the product's success. Predicting and managing such ECs is, thus, essential to companies. Some prediction tools model change propagation by algorithms, whereof a subgroup is numerical. Current numerical change propagation algorithms either do not account for the exclusion of cyclic propagation paths or are based on exhaustive searching methods. This paper presents a new matrix-calculation-based algorithm which can be applied directly to a numerical product model to analyze change propagation and support change prediction. The algorithm applies matrix multiplications on mutations of a given design structure matrix accounting for the exclusion of self-dependences and cyclic propagation paths and delivers the same results as the exhaustive search-based Trail Counting algorithm. Despite its factorial time complexity, the algorithm proves advantageous because of its straightforward matrix-based calculations which avoid exhaustive searching. Thereby, the algorithm can be implemented in established numerical programs such as Microsoft Excel which promise a wider application of the tools within and across companies along with better familiarity, usability, practicality, security, and robustness. © 1988-2012 IEEE.