First-principles study of the Young's modulus of Si <001> nanowires

We report the results of first-principles density functional theory calculations of the Young's modulus and other mechanical properties of hydrogen-passivated Si nanowires. The nanowires are taken to have predominantly {100} surfaces, with small {110} facets. The Young's modulus, the equilibrium length and the residual stress of a series of prismatic wires are found to have a size dependence that scales like the surface area to volume ratio for all but the smallest wires. We analyze the physical origin of the size dependence, and compare the results to two existing models.Comment: 5 pages, 3 figure

First-principles calculation of mechanical properties of Si <001> nanowires and comparison to nanomechanical theory

We report the results of first-principles density functional theory calculations of the Young's modulus and other mechanical properties of hydrogen-passivated Si nanowires. The nanowires are taken to have predominantly {100} surfaces, with small {110} facets according to the Wulff shape. The Young's modulus, the equilibrium length and the constrained residual stress of a series of prismatic beams of differing sizes are found to have size dependences that scale like the surface area to volume ratio for all but the smallest beam. The results are compared with a continuum model and the results of classical atomistic calculations based on an empirical potential. We attribute the size dependence to specific physical structures and interactions. In particular, the hydrogen interactions on the surface and the charge density variations within the beam are quantified and used both to parameterize the continuum model and to account for the discrepancies between the two models and the first-principles results.Comment: 14 pages, 10 figure

Cortical Dynamics of Visual Motion Perception: Short-Range and Long Range Apparent Motion

This article describes further evidence for a new neural network theory of biological motion perception that is called a Motion Boundary Contour System. This theory clarifies why parallel streams Vl-> V2 and Vl-> MT exist for static form and motion form processing among the areas Vl, V2, and MT of visual cortex. The Motion Boundary Contour System consists of several parallel copies, such that each copy is activated by a different range of receptive field sizes. Each copy is further subdivided into two hierarchically organized subsystems: a Motion Oriented Contrast Filter, or MOC Filter, for preprocessing moving images; and a Cooperative-Competitive Feedback Loop, or CC Loop, for generating emergent boundary segmentations of the filtered signals. The present article uses the MOC Filter to explain a variety of classical and recent data about short-range and long-range apparent motion percepts that have not yet been explained by alternative models. These data include split motion; reverse-contrast gamma motion; delta motion; visual inertia; group motion in response to a reverse-contrast Ternus display at short interstimulus intervals; speed-up of motion velocity as interfiash distance increases or flash duration decreases; dependence of the transition from element motion to group motion on stimulus duration and size; various classical dependencies between flash duration, spatial separation, interstimulus interval, and motion threshold known as Korte's Laws; and dependence of motion strength on stimulus orientation and spatial frequency. These results supplement earlier explanations by the model of apparent motion data that other models have not explained; a recent proposed solution of the global aperture problem, including explanations of motion capture and induced motion; an explanation of how parallel cortical systems for static form perception and motion form perception may develop, including a demonstration that these parallel systems are variations on a common cortical design; an explanation of why the geometries of static form and motion form differ, in particular why opposite orientations differ by 90°, whereas opposite directions differ by 180°, and why a cortical stream Vl -> V2 -> MT is needed; and a summary of how the main properties of other motion perception models can be assimilated into different parts of the Motion Boundary Contour System design.Air Force Office of Scientific Research (90-0175); Army Research Office (DAAL-03-88-K0088); Defense Advanced Research Projects Agency (AFOSR-90-0083); Hughes Aircraft Company (S1-903136

Coupling of Length Scales and Atomistic Simulation of MEMS Resonators

We present simulations of the dynamic and temperature dependent behavior of Micro-Electro-Mechanical Systems (MEMS) by utilizing recently developed parallel codes which enable a coupling of length scales. The novel techniques used in this simulation accurately model the behavior of the mechanical components of MEMS down to the atomic scale. We study the vibrational behavior of one class of MEMS devices: micron-scale resonators made of silicon and quartz. The algorithmic and computational avenue applied here represents a significant departure from the usual finite element approach based on continuum elastic theory. The approach is to use an atomistic simulation in regions of significantly anharmonic forces and large surface area to volume ratios or where internal friction due to defects is anticipated. Peripheral regions of MEMS which are well-described by continuum elastic theory are simulated using finite elements for efficiency. Thus, in central regions of the device, the motion of millions of individual atoms is simulated, while the relatively large peripheral regions are modeled with finite elements. The two techniques run concurrently and mesh seamlessly, passing information back and forth. This coupling of length scales gives a natural domain decomposition, so that the code runs on multiprocessor workstations and supercomputers. We present novel simulations of the vibrational behavior of micron-scale silicon and quartz oscillators. Our results are contrasted with the predictions of continuum elastic theory as a function of size, and the failure of the continuum techniques is clear in the limit of small sizes. We also extract the Q value for the resonators and study the corresponding dissipative processes.Comment: 10 pages, 10 figures, to be published in the proceedings of DTM '99; LaTeX with spie.sty, bibtex with spiebib.bst and psfi

CALIPER: Continuous Authentication Layered with Integrated PKI Encoding Recognition

Architectures relying on continuous authentication require a secure way to challenge the user's identity without trusting that the Continuous Authentication Subsystem (CAS) has not been compromised, i.e., that the response to the layer which manages service/application access is not fake. In this paper, we introduce the CALIPER protocol, in which a separate Continuous Access Verification Entity (CAVE) directly challenges the user's identity in a continuous authentication regime. Instead of simply returning authentication probabilities or confidence scores, CALIPER's CAS uses live hard and soft biometric samples from the user to extract a cryptographic private key embedded in a challenge posed by the CAVE. The CAS then uses this key to sign a response to the CAVE. CALIPER supports multiple modalities, key lengths, and security levels and can be applied in two scenarios: One where the CAS must authenticate its user to a CAVE running on a remote server (device-server) for access to remote application data, and another where the CAS must authenticate its user to a locally running trusted computing module (TCM) for access to local application data (device-TCM). We further demonstrate that CALIPER can leverage device hardware resources to enable privacy and security even when the device's kernel is compromised, and we show how this authentication protocol can even be expanded to obfuscate direct kernel object manipulation (DKOM) malwares.Comment: Accepted to CVPR 2016 Biometrics Worksho

Adversarial Diversity and Hard Positive Generation

State-of-the-art deep neural networks suffer from a fundamental problem - they misclassify adversarial examples formed by applying small perturbations to inputs. In this paper, we present a new psychometric perceptual adversarial similarity score (PASS) measure for quantifying adversarial images, introduce the notion of hard positive generation, and use a diverse set of adversarial perturbations - not just the closest ones - for data augmentation. We introduce a novel hot/cold approach for adversarial example generation, which provides multiple possible adversarial perturbations for every single image. The perturbations generated by our novel approach often correspond to semantically meaningful image structures, and allow greater flexibility to scale perturbation-amplitudes, which yields an increased diversity of adversarial images. We present adversarial images on several network topologies and datasets, including LeNet on the MNIST dataset, and GoogLeNet and ResidualNet on the ImageNet dataset. Finally, we demonstrate on LeNet and GoogLeNet that fine-tuning with a diverse set of hard positives improves the robustness of these networks compared to training with prior methods of generating adversarial images.Comment: Accepted to CVPR 2016 DeepVision Worksho