Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models

The prediction accuracy has been the long-lasting and sole standard for comparing the performance of different image classification models, including the ImageNet competition. However, recent studies have highlighted the lack of robustness in well-trained deep neural networks to adversarial examples. Visually imperceptible perturbations to natural images can easily be crafted and mislead the image classifiers towards misclassification. To demystify the trade-offs between robustness and accuracy, in this paper we thoroughly benchmark 18 ImageNet models using multiple robustness metrics, including the distortion, success rate and transferability of adversarial examples between 306 pairs of models. Our extensive experimental results reveal several new insights: (1) linear scaling law - the empirical $\ell_2$ and $\ell_\infty$ distortion metrics scale linearly with the logarithm of classification error; (2) model architecture is a more critical factor to robustness than model size, and the disclosed accuracy-robustness Pareto frontier can be used as an evaluation criterion for ImageNet model designers; (3) for a similar network architecture, increasing network depth slightly improves robustness in $\ell_\infty$ distortion; (4) there exist models (in VGG family) that exhibit high adversarial transferability, while most adversarial examples crafted from one model can only be transferred within the same family. Experiment code is publicly available at \url{https://github.com/huanzhang12/Adversarial_Survey}.Comment: Accepted by the European Conference on Computer Vision (ECCV) 201

Reliability and Validity of Widely Used International Surveys on the Environment

Do existing public opinion surveys provide valid and reliable measures of attitudes towards environmental sustainability? This question is critical given the importance of public support for achieving sustainability. Starting with 28 survey items about the environment drawn from the World Values Survey Waves 5 and 6 and the 2010 International Social Survey Program, we assessed reliability by checking for significant correlations between similar or identical items on different surveys. Next, to assess validity, we evaluated correlations between survey items and 22 objective environmental indicators drawn from the Environmental Performance Index (EPI). As the level of economic development is a likely confound, we also performed partial correlation analyses controlling for GDP per capita. From the initial 28 items, we identified 23 sufficiently reliable items, but many of these were found to have low predictive power in the validity analysis. Items about air and water pollution were valid predictors of objective environmental conditions in these areas. Items asking about the relative importance of environmental problems compared to other social issues were also good positive predictors of progress on perceptible environmental issues. Items asking about general sentiment with no clear referent performed poorly. When controlling for GDP, country-level attitudes were more aligned with country-specific environmental conditions. Finally, nearly half of all EPI indicators were associated with few or no survey items, indicating the existence of 'blind spots' in public awareness. Our findings should offer guidance to both survey developers and users, as well as to policy makers responsible for conveying information about environmental sustainability to the wider public

Temperature effects of Mach-Zehnder interferometer using a liquid crystal-filled fiber

We demonstrated a simple and cost-effective method to fabricate all fiber Mach-Zehnder interferometer (MZI) based on cascading a short section of liquid crystal (LC)-filled hollow-optic fiber (HOF) between two single mode fibers by using automatically splicing technique. The transmission spectra of the proposed MZI with different LC-infiltrated length were measured and the temperature-induced wavelength shifts of the interference fringes were recorded. Both blue shift and red shift were observed, depending the temperature range. Based on our experimental results, interference fringe was observed with a maximum interferometric contrast over 35dB. The temperature-induced resonant wavelength blue-shifts 70.4 nm for the MZI with an LC length of 9.79 mm and the wavelength temperature sensitivity of -1.55 nm/°C is easily achieved as the temperature increases from 25°C to 77°C

Certified Robustness of Quantum Classifiers against Adversarial Examples through Quantum Noise

Recently, quantum classifiers have been known to be vulnerable to adversarial attacks, where quantum classifiers are fooled by imperceptible noises to have misclassification. In this paper, we propose one first theoretical study that utilizing the added quantum random rotation noise can improve the robustness of quantum classifiers against adversarial attacks. We connect the definition of differential privacy and demonstrate the quantum classifier trained with the natural presence of additive noise is differentially private. Lastly, we derive a certified robustness bound to enable quantum classifiers to defend against adversarial examples supported by experimental results.Comment: Submitted to IEEE ICASSP 202

Spatiotemporal Trends in Oral Cancer Mortality and Potential Risks Associated with Heavy Metal Content in Taiwan Soil

Central and Eastern Taiwan have alarmingly high oral cancer (OC) mortality rates, however, the effect of lifestyle factors such as betel chewing cannot fully explain the observed high-risk. Elevated concentrations of heavy metals in the soil reflect somewhat the levels of exposure to the human body, which may promote cancer development in local residents. This study assesses the space-time distribution of OC mortality in Taiwan, and its association with prime factors leading to soil heavy metal content. The current research obtained OC mortality data from the Atlas of Cancer Mortality in Taiwan, 1972–2001, and derived soil heavy metals content data from a nationwide survey carried out by ROCEPA in 1985. The exploratory data analyses showed that OC mortality rates in both genders had high spatial autocorrelation (Moran’s I = 0.6716 and 0.6318 for males and females). Factor analyses revealed three common factors (CFs) representing the major pattern of soil pollution in Taiwan. The results for Spatial Lag Models (SLM) showed that CF1 (Cr, Cu, Ni, and Zn) was most spatially related to male OC mortality which implicates that some metals in CF1 might play as promoters in OC etiology