The quantitative performance indicators of Physical Unclonable Functions (PUFs)-Randomness, Steadiness, Correctness, Diffuseness and Uniqueness-are strictly defined and applied to the evaluation of 45 arbiter PUFs on Virtex-5 FPGAs. The indicators effectively reflect the characteristics of PUFs ranging from 0 to 1 with 1 being the highest performance. The indicators enable the easy measurement and intuitive understanding of PUF performances. The experimental results shows that the arbiter PUFs have excellent overall intradevice performances though a slight bit bias is indicated. The inter-device performance is moderate and will suffice for the practical use of PUFs for device authentication and so on. Additionally, the reliability of the obtained PUF performances is statistically discussed in terms of the Confidence Interval and the number of devices. This paper presents in detail the definitions of the performance indicators and the quantitative and statistical evaluation results of the arbiter PUFs.

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This study develops a spatially varying coefficient model by extending the random effects eigenvector spatial filtering model. The developed model has the following properties: its coefficients are interpretable in terms of the Moran coefficient; each of its coefficients can have a different degree of spatial smoothness; and it yields a variant of a Bayesian spatially varying coefficient model. Also, parameter estimation of the model can be executed with a relatively small computationally burden. Results of a Monte Carlo simulation reveal that our model outperforms a conventional eigenvector spatial filtering (ESF) model and geographically weighted regression (GWR) models in terms of the accuracy of the coefficient estimates and computational time. We empirically apply our model to the hedonic land price analysis of flood risk in Japan.

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This study aims to develop and validate prediction models for the number of all heatstroke cases, and heatstrokes of hospital admission and death cases per city per 12 h, using multiple weather information and a population-based database for heatstroke patients in 16 Japanese cities (corresponding to around a 10,000,000 population size). In the testing dataset, mean absolute percentage error of generalized linear models with wet bulb globe temperature as the only predictor and the optimal models, respectively, are 43.0% and 14.8% for spikes in the number of all heatstroke cases, and 37.7% and 10.6% for spikes in the number of heatstrokes of hospital admission and death cases. The optimal models predict the spikes in the number of heatstrokes well by machine learning methods including non-linear multivariable predictors and/or under-sampling and bagging. Here, we develop prediction models whose predictive performances are high enough to be implemented in public health settings.

Cities have become the focus of global climate mitigation efforts because as they are responsible for 60%–70% of energy-related CO2 emissions. As the world is increasingly urbanized, it is crucial to identify cost-effective pathways to decarbonize and enhance the resilience of cities, which ensure the well-being of their dwellers. Here, we propose a ‘SolarEV City’ concept, in which integrated systems of cities’ roof-top photovoltaics and electric vehicles (EVs) supply affordable and dispatchable CO2-free electricity to urban dwellers. Our analyses indicate that implementations of the concept can meet 53%–95% of electricity demands in nine major Japanese urban areas by 2030. CO2 emission from vehicle use and electricity generation in these areas can be reduced by 54%–95% with potential cost savings of 26%–41%. High cost-effectiveness and seasonally stable insolation in low latitudes may imply that the concept may be more effective to decarbonize urban environments in emerging economies in low latitudes. Among several factors, governmental interventions will play a crucial role in realizing such systems, particularly in legislating regulations that enhance penetration of the integrated system of PV and EV and enable formation of decentralized power systems. As bottom-up processes are critical, policy makers, communities, industries, and researchers should work together to build such systems overcoming social and regulatory barriers.