Improving productivity - Opening the black box

Hourly productivity levels in the UK still remain behind those in some competitor countries. The government devotes much policy attention to enhancing productivity and continues to emphasise its five drivers - investment, innovation, skills, enterprise, and competition. This article argues that it is investment broadly defined that is the key to sustained productivity improvement. The emphasis should be on improving productivity simultaneously with improving the quality of production. Only thus will the gains be widely shared. In achieving these aims there are two prerequisites for policy-makers. The first is to ensure better coordination of policy than appears to be currently achieved by the present departmental structures in Whitehall. The second is to recognize fully the long and complex chain of causation that can be triggered by pulling on one policy lever. Such complexity can only be fully understood by more research on what actually goes on inside the black box of the organization. © 2006 Oxford University Press.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.

A policy dimension required for technology roadmapping: Learning from the development of emerging wind energy industry in China

Innovation policies play an important role throughout the development process of emerging industries. However, existing policy studies view the process as a black-box, and fail to understand the policy-industry interactions through the process. This paper aims to develop an integrated technology roadmapping tool, in order to facilitate the better understanding of policy heterogeneity at the different stages of new energy industries in China. Through the case study of Chinese wind energy equipment manufacturing industry, this paper elaborates the dynamics between policy and the growth process of the industry. Further, this paper generalizes some Chinese specifics for the policy-industry interactions. As a practical output, this study proposes a policy-technology roadmapping framework that maps policy-market-product- technology interactions in response to the requirement for analyzing and planning the development of new industries in emerging economies (e.g. China). This paper will be of interest to policy makers, strategists, investors, and industrial experts. © 2011 IEEE.

A policy dimension required for technology roadmapping: Learning from the emergence of Chinese wind turbine industry

Innovation policies play an important role throughout the development process of emerging industries in China. Existing policy and industry studies view the emergence process as a black-box, and fail to understand the impacts of policy to the process along which it varies. This paper aims to develop a multi-dimensional roadmapping tool to better analyse the dynamics between policy and industrial growth for new industries in China. Through reviewing the emergence process of Chinese wind turbine industry, this paper elaborates how policy and other factors influence the emergence of this industry along this path. Further, this paper generalises some Chinese specifics for the policy-industry dynamics. As a practical output, this study proposes a roadmapping framework that generalises some patterns of policy-industry interactions for the emergence process of new industries in China. This paper will be of interest to policy makers, strategists, investors and industrial experts. Copyright © 2013 Inderscience Enterprises Ltd.

Probabilistic graphical models for semi-supervised traffic classification

Traffic classification using machine learning continues to be an active research area. The majority of work in this area uses off-the-shelf machine learning tools and treats them as black-box classifiers. This approach turns all the modelling complexity into a feature selection problem. In this paper, we build a problem-specific solution to the traffic classification problem by designing a custom probabilistic graphical model. Graphical models are a modular framework to design classifiers which incorporate domain-specific knowledge. More specifically, our solution introduces semi-supervised learning which means we learn from both labelled and unlabelled traffic flows. We show that our solution performs competitively compared to previous approaches while using less data and simpler features. Copyright © 2010 ACM.

Handbook of nanoindentation with biological applications

Nanoindentation is ideal for the characterization of inhomogeneous biological materials. However, the use of nanoindentation techniques in biological systems is associated with some distinctively different techniques and challenges. For example, engineering materials used in the microelectronics industry (e.g. ceramics and metals) for which the technique was developed, are relatively stiff and exhibit time-independent mechanical responses. Biological materials, on the other hand, exhibit time-dependent behavior, and can span a range of stiffness regimes from moduli of Pa to GPa - eight to nine orders of magnitude. As such, there are differences in the selection of instrumentation, tip geometry, and data analysis in comparison with the "black box" nanoindentation techniques as sold by commercial manufacturers. The use of scanning probe equipment (atomic force miscroscopy) is also common for small-scale indentation of soft materials in biology. The book is broadly divided into two parts. The first part presents the "basic science" of nanoindentation including the background of contact mechanics underlying indentation technique, and the instrumentation used to gather mechanical data. Both the mechanics background and the instrumentation overview provide perspectives that are optimized for biological applications, including discussions on hydrated materials and adaptations for low-stiffness materials. The second part of the book covers the applications of nanoindentation technique in biological materials. Included in the coverage are mineralized and nonmineralized tissues, wood and plant tissues, tissue-engineering substitute materials, cells and membranes, and cutting-edge applications at molecular level including the use of functionalized tips to probe specific molecular interactions (e.g. the ligand-receptor binding). The book concludes with a concise summary and an insightful forecast of the future highlighting the current challenges. © 2011 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

Industrial practice in technology planning - Implications for a useful tool catalogue for technology management

A survey on technology planning and its implications for a useful tool catalogue for technology management was conducted. The survey provided a picture of technology planning, across a broad range of company size, manufacturing type and sector. It was concluded from the findings that technology planning is an important business activity across industry sectors and company types, driven increasing competition, market requirements and regulation technology change. The process technology roadmapping was used to support technology strategy and planning and could be useful way of structuring both the use of tools in a company and a tool catalogue.

Updated correlation between aircraft smoke number and black carbon concentration

Aircraft emissions of black carbon (BC) contribute to anthropogenic climate forcing and degrade air quality. The smoke number (SN) is the current regulatory measure of aircraft particulate matter emissions and quantifies exhaust plume visibility. Several correlations between SN and the exhaust mass concentration of BC (CBC) have been developed, based on measurements relevant to older aircraft engines. These form the basis of the current standard method used to estimate aircraft BC emissions (First Order Approximation version 3 [FOA3]) for the purposes of environmental impact analyses. In this study, BC with a geometric mean diameter (GMD) of 20, 30, and 60 nm and filter diameters of 19 and 35 mm are used to investigate the effect of particle size and sampling variability on SN measurements. For BC with 20 and 30 nm GMD, corresponding to BC emitted by modern aircraft engines, a smaller SN results from a given CBC than is the case for BC with 60 nm GMD, which is more typical of older engines. An updated correlation between CBC and SNthat accounts for typical size of BC emitted by modern aircraft is proposed. An uncertainty of ±25% accounts for variation in GMD in the range 20-30 nm and for the range of filter diameters. The SN-CBC correlation currently used in FOA3 underestimates by a factor of 2.5-3 for SN <15, implying that current estimates of aircraft BC emissions derived from SN are underestimated by the same factor. Copyright © American Association for Aerosol Research.