Enhancing mirror adaptive random testing through dynamic partitioning

Context: Adaptive random testing (ART), originally proposed as an enhancement of random testing, is often criticized for the high computation overhead of many ART algorithms. Mirror ART (MART) is a novel approach that can be generally applied to improve the efficiency of various ART algorithms based on the combination of ''divide-and-conquer'' and ''heuristic'' strategies. Objective: The computation overhead of the existing MART methods is actually on the same order of magnitude as that of the original ART algorithms. In this paper, we aim to further decrease the order of computation overhead for MART. Method: We conjecture that the mirroring scheme in MART should be dynamic instead of static to deliver a higher efficiency. We thus propose a new approach, namely dynamic mirror ART (DMART), which incrementally partitions the input domain and adopts new mirror functions. Results: Our simulations demonstrate that the new DMART approach delivers comparable failure-detection effectiveness as the original MART and ART algorithms while having much lower computation overhead. The experimental studies further show that the new approach also delivers a better and more reliable performance on programs with failure-unrelated parameters. Conclusion: In general, DMART is much more cost-effective than MART. Since its mirroring scheme is independent of concrete ART algorithms, DMART can be generally applied to improve the cost-effectiveness of various ART algorithms

Towards Social Autonomous Vehicles: Efficient Collision Avoidance Scheme Using Richardson's Arms Race Model

Background Road collisions and casualties pose a serious threat to commuters around the globe. Autonomous Vehicles (AVs) aim to make the use of technology to reduce the road accidents. However, the most of research work in the context of collision avoidance has been performed to address, separately, the rear end, front end and lateral collisions in less congested and with high inter-vehicular distances. Purpose The goal of this paper is to introduce the concept of a social agent, which interact with other AVs in social manners like humans are social having the capability of predicting intentions, i.e. mentalizing and copying the actions of each other, i.e. mirroring. The proposed social agent is based on a human-brain inspired mentalizing and mirroring capabilities and has been modelled for collision detection and avoidance under congested urban road traffic. Method We designed our social agent having the capabilities of mentalizing and mirroring and for this purpose we utilized Exploratory Agent Based Modeling (EABM) level of Cognitive Agent Based Computing (CABC) framework proposed by Niazi and Hussain. Results Our simulation and practical experiments reveal that by embedding Richardson's arms race model within AVs, collisions can be avoided while travelling on congested urban roads in a flock like topologies. The performance of the proposed social agent has been compared at two different levels.Comment: 48 pages, 21 figure

Variance Reduction for Faster Non-Convex Optimization

We consider the fundamental problem in non-convex optimization of efficiently reaching a stationary point. In contrast to the convex case, in the long history of this basic problem, the only known theoretical results on first-order non-convex optimization remain to be full gradient descent that converges in $O(1/\varepsilon)$ iterations for smooth objectives, and stochastic gradient descent that converges in $O(1/\varepsilon^2)$ iterations for objectives that are sum of smooth functions. We provide the first improvement in this line of research. Our result is based on the variance reduction trick recently introduced to convex optimization, as well as a brand new analysis of variance reduction that is suitable for non-convex optimization. For objectives that are sum of smooth functions, our first-order minibatch stochastic method converges with an $O(1/\varepsilon)$ rate, and is faster than full gradient descent by $\Omega(n^{1/3})$. We demonstrate the effectiveness of our methods on empirical risk minimizations with non-convex loss functions and training neural nets.Comment: polished writin

ShaneAO: wide science spectrum adaptive optics system for the Lick Observatory

A new high-order adaptive optics system is now being commissioned at the Lick Observatory Shane 3-meter telescope in California. This system uses a high return efficiency sodium beacon and a combination of low and high-order deformable mirrors to achieve diffraction-limited imaging over a wide spectrum of infrared science wavelengths covering 0.8 to 2.2 microns. We present the design performance goals and the first on-sky test results. We discuss several innovations that make this system a pathfinder for next generation AO systems. These include a unique woofer-tweeter control that provides full dynamic range correction from tip/tilt to 16 cycles, variable pupil sampling wavefront sensor, new enhanced silver coatings developed at UC Observatories that improve science and LGS throughput, and tight mechanical rigidity that enables a multi-hour diffraction- limited exposure in LGS mode for faint object spectroscopy science.Comment: 11 pages, 10 figures. Presented at SPIE Astronomical Telescopes + Instrumentation conference, paper 9148-7

Implementation of a digital optical phase conjugation system and its application to study the robustness of turbidity suppression by phase conjugation

In this work, we report a novel high capacity (number of degrees of freedom) open loop adaptive optics method, termed digital optical phase conjugation (DOPC), which provides a robust optoelectronic optical phase conjugation (OPC) solution. We showed that our prototype can phase conjugate light fields with ~3.9 x 10^(−3) degree accuracy over a range of ~3 degrees and can phase conjugate an input field through a relatively thick turbid medium (μ_sl ~13). Furthermore, we employed this system to show that the reversing of random scattering in turbid media by phase conjugation is surprisingly robust and accommodating of phase errors. An OPC wavefront with significant spatial phase errors (error uniformly distributed from – π/2 to π/2) can nevertheless allow OPC reconstruction through a scattering medium with ~40% of the efficiency achieved with phase error free OPC

Individuality in Fish Behavior: Ecology and Comparative Psychology

This work is a brief review of a series of studies of the phenotypic organization and ecological significance of individual differences in fish behavior. The following species were studied: guppy Poecilia retuculata, lion-headed cichlid Steatocranus cassuarius, and the convict cichlid Archocentrus nigrofasciatum. We developed methods for the analysis of individual differences in fish behavior and studied their structure, development, and ecological and evolutionary significance

Limb radiance inversion radiometer

Engineering and scientific objectives of the LRIR experiment are described along with system requirements, subassemblies, and experiment operation. The mechanical, electrical, and thermal interfaces between the LRIR experiment and the Nimbus F spacecraft are defined. The protoflight model qualification and acceptance test program is summarized. Test data is presented in tables to give an overall view of each test parameter and possible trends of the performance of the LRIR experiment. Conclusions and recommendations are included