Definitions of Biodiversity and Measures of Its Value

The destruction of natural habitats has prompted concerns about the loss of biological diversity. Regrettably, however, there is no consensus among either biologists or economists on the most meaningful measures of biodiversity. Fundamentally different definitions are useful in asking fundamentally different questions. Considerable attention has been given to the value of diversity in search models. A measure of “aggregate variability” is appropriate to such models. Values derived from search models tend to be well behaved; they exhibit diminishing returns in diversity. In contrast, a definition of diversity as “relative abundance” is more appropriate to more complex objective functions. Values derived in these models are not necessarily well behaved. The differences between diversity values arising in search models and those arising from more general objectives are demonstrated. An example shows that “consistency tests” applied to measures of valuation may not be useful when diversity per se is being valued.Biological diversity; biodiversity; diversity index, abundance; search; variability, consistency; contingent valuation; diminishing returns; increasing returns

H2B: Heartbeat-based Secret Key Generation Using Piezo Vibration Sensors

We present Heartbeats-2-Bits (H2B), which is a system for securely pairing wearable devices by generating a shared secret key from the skin vibrations caused by heartbeat. This work is motivated by potential power saving opportunity arising from the fact that heartbeat intervals can be detected energy-efficiently using inexpensive and power-efficient piezo sensors, which obviates the need to employ complex heartbeat monitors such as Electrocardiogram or Photoplethysmogram. Indeed, our experiments show that piezo sensors can measure heartbeat intervals on many different body locations including chest, wrist, waist, neck and ankle. Unfortunately, we also discover that the heartbeat interval signal captured by piezo vibration sensors has low Signal-to-Noise Ratio (SNR) because they are not designed as precision heartbeat monitors, which becomes the key challenge for H2B. To overcome this problem, we first apply a quantile function-based quantization method to fully extract the useful entropy from the noisy piezo measurements. We then propose a novel Compressive Sensing-based reconciliation method to correct the high bit mismatch rates between the two independently generated keys caused by low SNR. We prototype H2B using off-the-shelf piezo sensors and evaluate its performance on a dataset collected from different body positions of 23 participants. Our results show that H2B has an overwhelming pairing success rate of 95.6%. We also analyze and demonstrate H2B's robustness against three types of attacks. Finally, our power measurements show that H2B is very power-efficient