University Research, Industrial R&D, and the Anchor Tenant Hypothesis

We examine geographic concentration, agglomeration, and co-location of university research and industrial R&D in three technological areas: medical imaging, neural networks, and signal processing. Using data on scientific publications and patents as indicators of university research and industrial R&D, we find strong evidence of geographic concentration in both activities at the level of MSAs. While evidence for agglomeration (in the sense of excess' concentration relative to the size of MSAs and the size distribution of research labs) of research in these fields is mixed, we do find strong evidence of co-location of upstream and downstream activity. We view such co-located vertically connected activities as constituents of a local innovation system,' and these appear to vary markedly in their ability to convert local academic research into local commercial innovation. We develop and test the hypothesis that the presence of a large, local, R&D-intensive firm an anchor tenant' enhances the productivity of local innovation systems by making local university research more likely to be absorbed by and to stimulate local industrial R&D. Presence of anchor tenant firms may be an important factor in stimulating both the demand and supply sides of local markets for innovation and may be an important channel for transmission of spillovers. While our empirical results are preliminary, they indicate that anchor tenant technology firms may be an economically important aspect of the institutional structure of local economies.

Why are Some Regions More Innovative than Others? The Role of Firm Size Diversity

Large labs may spawn spin-outs caused by innovations deemed unrelated to the firm's overall business. Small labs generate demand for specialized services that lower entry costs for others. We develop a theoretical framework to study the interplay of these two localized externalities and their impact on regional innovation. We examine MSA-level patent data during the period 1975-2000 and find that innovation output is higher where large and small labs coexist. The finding is robust to across-region as well as within-region analysis, IV analysis, and the effect is stronger in certain subsamples consistent with our explanation but not the plausible alternatives.

Methods and Systems for Characterization of an Anomaly Using Infrared Flash Thermography

A method for characterizing an anomaly in a material comprises (a) extracting contrast data; (b) measuring a contrast evolution; (c) filtering the contrast evolution; (d) measuring a peak amplitude of the contrast evolution; (d) determining a diameter and a depth of the anomaly, and (e) repeating the step of determining the diameter and the depth of the anomaly until a change in the estimate of the depth is less than a set value. The step of determining the diameter and the depth of the anomaly comprises estimating the depth using a diameter constant C.sub.D equal to one for the first iteration of determining the diameter and the depth; estimating the diameter; and comparing the estimate of the depth of the anomaly after each iteration of estimating to the prior estimate of the depth to calculate the change in the estimate of the depth of the anomaly

Ultrasonic Measurement of Loads in Bolts Used in Structural Joints

The paper is an overview of work by the author in measuring and monitoring loads in bolts using an ultrasonic extensometer

Applicability of a Conservative Margin Approach for Assessing NDE Flaw Detectability

Nondestructive Evaluation (NDE) procedures are required to detect flaws in structures with a high percentage detectability and high confidence. Conventional Probability of Detection (POD) methods are statistical in nature and require detection data from a relatively large number of flaw specimens. In many circumstances, due to the high cost and long lead time, it is impractical to build the large set of flaw specimens that is required by the conventional POD methodology. Therefore, in such situations it is desirable to have a flaw detectability estimation approach that allows for a reduced number of flaw specimens but provides a high degree of confidence in establishing the flaw detectability size. This paper presents an alternative approach called the conservative margin approach (CMA). To investigate the applicability of the CMA approach, flaw detectability sizes determined by the CMA and POD approaches have been compared on actual datasets. The results of these comparisons are presented and the applicability of the CMA approach is discussed

Assessing Reliability of NDE Flaw Detection Using Smaller Number of Demonstration Data Points

The paper provides an engineering analysis approach for assessing reliability of NDE flaw detection using smaller number of demonstration data points. It explores dependence of probability of detection (POD), probability of false positive (POF), on contrast-to-noise ratio, and net decision threshold-to-noise ratio in a simulated data; and draws some generically applicable inferences to devise the approach. ASTM nondestructive evaluation standards provide requirements on signal-to-noise ratio and/or contrast-to-noise ratio in order to provide reliable flaw detection and limit false positive calls. POD analysis of inspection test data results in an estimated flaw size, denoted by 90/95. This flaw size has 90% POD and minimum 95% confidence. POF is also estimated in the analysis. POD demonstration requires specimens with flaws of known size. In many situations, it is very expensive to produce the large number of flaws required for the POD analysis. In some situations, only real flaws can truly represent the flaws for demonstration. Real flaws of correct size and location in part configuration specimen may be difficult to produce, if not impossible. Here, an engineering analysis approach is devised using simulation to assess reliability of NDE technique when a limited number of flaws are available for demonstration. In this simulation, a technique is considered reliable, if it provides flaw detectability size equal to or better than the theoretical 90 used in simulation and also provides a POF less than or equal to a chosen value. The paper uses simulated signal response versus flaw size data to devise the approach. Linear correlation is used between the signal response data and flaw size. POD software mh1823 uses generalized linear model (GLM) in POD analysis after transforming the flaw size and signal response, if needed, using logarithm. Therefore, this approach is in agreement with the linear signal correlation used in mh1823. Using the POD analysis of data, generic conditions on contrast-to-noise ratio and net decision threshold-to-noise ratio are derived for reliable flaw detection. In order to assess technique reliability using the engineering approach, signal response-to-flaw size correlation about the flaw size of concern is needed. In addition, measurement of noise is also needed. If the technique meets the above requirements, assumption of linear signal-to-flaw size correlation and conditions on noise, then the technique can be assessed using this analysis as it fits the underlying POD model used here. The approach is conservative and is designed to provide a larger flaw size compared to the POD approach. Such NDE technique assessment approach, although, not as rigorous as POD, can be cost effective if the larger flaw size can be tolerated. Typically, this is a situation for all quality control NDE inspections. Here, an NDE technique needs to be reliable and 90/95 is not estimated, but the assessed flaw size is assumed to be larger than the unknown a90 due to conservative factors or margins. Applicability of the approach for assessing reliability of flaw detection in x-ray radiography and 2D imaging in general is also explored