The Sensitivity of Bank Stocks to Mortgage Portfolio Composition

Previous studies have found that bank stock returns are very sensitive to changes in real estate returns in general. But how the composition and quality of bank real estate portfolios affect the sensitivity of bank stocks to real estate returns has not been rigorously examined. The purpose of this study is to empirically examine this important question. The results indicate that commercial mortgages contribute the most to the sensitivity of bank stock returns. Farmland loans have a negative impact on bank real estate return sensitivity. Thus, farmland loans could play a diversification role in terms of reducing the sensitivity of banks to real estate returns, if used appropriately.

Stationarity and Co-Integration in Systems with Three National Real Estate Indices

This study examines the stochastic properties of the commercial real estate wealth indices for three countries (the U.S., Canada, and the U.K.) and for several property types (aggregate, office, retail, and industrial). Each of the indices is tested for a unit root and all series are found to be nonstationary. Furthermore, all indices also indicate the presence of both drift and trend. The results are strongest when the indices are tested in real estate and exchange rate-adjusted form. Application of Johansen's model indicates that the system for the three countries shows evidence of co-integration for the aggregate, retail, office, and industrial properties. Again, the evidence is the strongest when the indices are tested in real and exchange rate-adjusted form. Hence, it is conceivable that inflationary expectations may be the factor that provides the common linkage between commercial real estate across national boundaries.

The Wealth Effects of Domestic vs International Joint Ventures: The Case of Real Estate

This study examines the wealth effect of international versus domestic real estate joint ventures on the U.S. participating firm's shareholders. This is done using traditional even study methodology for real estate joint venture announcements. The results suggest that domestic real estate joint ventures generally result in a significant increase in the firm's value, while international real estate joint ventures usually have a much less significant to nonsignificant wealth impact. This may be due to the immovability of real properties in foreign countries and the large amount of initial investment in real estate that increase both political and economic risks for international real estate joint ventures. This study also finds that hotel joint ventures generally have a weaker wealth effect than non-hotel real estate joint ventures.

Ultrasonic sonar system for target localization with one emitter and for receivers

This paper presents an ultrasonic active sonar system in air constituting one emitter and four receivers. Target localization is achieved by means of intersection of four ellipsoids defined by the time of flight between emission and reception of the signal reflected by the target. This paper shows a proof of concept of the localization principle through some localization tasks conducted in a laboratory environment. The position of a spherical target is determined with an error between 1cm and 7cm depending on receiver configuration and target position. The purpose of the fully developed sonar system is to assist drones and robots in their autonomous navigation

Bio-inspired sound localization sensor with high directional sensitivity

MEMS microphones inspired by Ormia ochracea are constrained by their reliance on the resonant behavior of the system, forcing designers to compromise the goal of high amplification of directional cues to operate across the audio range. Here we present an alternative approach, namely a system optimized for the maximum amplification of directional cues across a narrow bandwidth operating purely as a sound-localization sensor for wide-band noise. Directional sensitivity is enhanced by increasing the coupling strength beyond the 'dual optimization' point, which represents the collocation of a local maximum in directional sensitivity and a local minimum in non-linearity, compensating for the loss of the desirable linearity of the system by restricting the angular range of operation. Intensity gain achieved is 16.3 dB at 10° sound source azimuth with a linear directional sensitivity of 1.6 dB per degree, while linear directional sensitivity in phase difference gain shows a seven fold increase over the 'dual optimization' point of 8 degrees phase difference per degree change in azimuthal angle

3D printed small-scale acoustic metamaterials based on Helmholtz resonators with tuned overtones

Acoustic metamaterials have been extensively studied in recent decades due to their ability to control acoustic waves. In this paper, we present a prototype of a small-scale acoustic metamaterial based on Helmholtz resonators fabricated with additive manufacturing technology. The results confirm that 3D printed small-scale metamaterials can break the mass law by creating band gaps where the sound is deeply attenuated. We have also introduced a modification of the resonators whereby overtones are exploited and tuned in order to broaden the band gap. The output of this research could be used to provide passive filtering for transducers, to improve noise cancelling headphones, as well as in other smart acoustic sensors and IoT audio applications

Multimodel structural performance monitoring

Journal ArticleMeasurements from load tests may lead to numerical models that better reflect structural behavior. This kind of system identification is not straightforward due to important uncertainties in measurement and models. Moreover, since system identification is an inverse engineering task, many models may fit measured behavior. Traditional model updating methods may not provide the correct behavioral model due to uncertainty and parameter compensation. In this paper, a multimodel approach that explicitly incorporates uncertainties and modeling assumptions is described. The approach samples thousands of models starting from a general parametrized finite-element model. The population of selected candidate models may be used to understand and predict behavior, thereby improving structural management decision making. This approach is applied to measurements from structural performance monitoring of the Langensand Bridge in Lucerne, Switzerland. Predictions from the set of candidate models are homogenous and show an average discrepancy of 4-7% from the displacement measurements. The tests demonstrate the applicability of the multimodel approach for the structural identification and performance monitoring of real structures. The multimodel approach reveals that the Langensand Bridge has a reserve capacity of 30% with respect to serviceability requirements.Swiss National Science Foundatio

Bio-inspired frequency agile acoustic system

Natural passive mechanical systems such as ear tympanic membranes may show active responses by incorporating feedback mechanisms which then affect their mechanical structure. In this paper, the moth’s auditory system is used as a biological model of inspiration. A smart acoustic system which alters its natural resonance frequency was developed. Experimental results, given by a proposed-built real-time embedded system, show time and amplitude dependency towards dynamic frequency adaptation according to the intensity of acoustic input signals

End-of-Life decision tool with emphasis on remanufacturing

Remanufacturing is a product recovery strategy resulting in end-of-life products being returned to as new condition or better and receiving a warranty at least equivalent to the original. To differentiate remanufacturing from other forms of product recovery, a clear definition of a remanufactured product is essential. At present two distinct methods for understanding end-of-life recovery strategies exist; a) the use of tools and b) definitions. These current methods fall short however of categorically stating what is and what is not a remanufactured product. Therefore, the responsibility of classifying a product as remanufactured is left to individuals and organizations and so potential exists for products to be incorrectly labelled. By firstly examining the problems associated with using existing methods to determine the status of end-of-life product, and why product identification is important, this paper then goes on to present a new simple innovative method to quickly and accurately determine the status of a product which has undergone an end-of-life recovery strategy, by virtue of a bespoke tool. The tool presented is the result of two rounds of academic and industrial feedback; an initial tool was presented, and underwent critique, at the International Conference on Remanufacturing 2015 with an updated tool then subject to another independent review from academic and industrial stakeholders. The main benefits associated with this tool are, a) a quick way to identify the status of a product, b) a method for researchers to quickly determine the best terminology for end-of-life products which have received a recovery treatment, c) a quick and reliable method to check whether a remanufactured product is labelled as something else, d) an additional way to ensure compliance with existing legislation and standards, and e) an identification of only the essential characteristics of a remanufactured product

Methodologies for predicting natural frequency variation of a suspension bridge

Journal ArticleThis is the accepted version of an article published in Engineering Structures, 80 (1) pp. 211–221. The Version of Record is available online at http://dx.doi.org/10.1016/j.engstruct.2014.09.001.In vibration-based structural health monitoring, changes in the natural frequency of a structure are used to identify changes in the structural conditions due to damage and deterioration. However, natural frequency values also vary with changes in environmental factors such as temperature and wind. Therefore, it is important to differentiate between the effects due to environmental variations and those resulting from structural damage. In this paper, this task is accomplished by predicting the natural frequency of a structure using measurements of environmental conditions. Five methodologies - multiple linear regression, artificial neural networks, support vector regression, regression tree and random forest - are implemented to predict the natural frequencies of the Tamar Suspension Bridge (UK) using measurements taken from 3 years of continuous monitoring. The effects of environmental factors and traffic loading on natural frequencies are also evaluated by measuring the relative importance of input variables in regression analysis. Results show that support vector regression and random forest are the most suitable methods for predicting variations in natural frequencies. In addition, traffic loading and temperature are found to be two important parameters that need to be measured. Results show potential for application to continuously monitored structures that have complex relationships between natural frequencies and parameters such as loading and environmental factors