Deep neural networks (DNNs) are vulnerable to adversarial examples, which are carefully crafted instances aiming to cause prediction errors for DNNs. Recent research on adversarial examples has examined local neighborhoods in the input space of DNN models. However, previous work has limited what regions to consider, focusing either on low-dimensional subspaces or small balls. In this paper, we ...

This paper extends the traditional representation model for geographic data. The traditional representation model is based on a two-dimensional, static, time-independent world, where only well defined or continuous objects exit. This of course is a very limited representation of the real world. The extended model considers a multi-dimensional, dynamic, time-dependent world where objects can be ...

For 5 millennia, Cannabis sativa has been used throughout the world medically, recreationally, and spiritually. From the mid-19th century to the 1930s, American physicians prescribed it for a plethora of indications, until the federal government started imposing restrictions on its use, culminating in 1970 with the US Congress classifying it as a Schedule I substance, illegal, and without medic...