arXiv subjects

Daniel Schneider

Publications and source records attributed to Daniel Schneider.

44 records · Page 3Linked to original sources

arXiv2019

Trustworthy Experimentation Under Telemetry Loss

Failure to accurately measure the outcomes of an experiment can lead to bias and incorrect conclusions. Online controlled experiments (aka AB tests) are increasingly being used to make decisions to improve websites as well as mobile and desktop applications. We argue that loss of telemetry data (during upload or post-processing) can skew the results of experiments, leading to loss of statistical power and inaccurate or erroneous conclusions. By systematically investigating the causes of telemetry loss, we argue that it is not practical to entirely eliminate it. Consequently, experimentation systems need to be robust to its effects. Furthermore, we note that it is nontrivial to measure the absolute level of telemetry loss in an experimentation system. In this paper, we take a top-down approach towards solving this problem. We motivate the impact of loss qualitatively using experiments in real applications deployed at scale, and formalize the problem by presenting a theoretical breakdown of the bias introduced by loss. Based on this foundation, we present a general framework for quantitatively evaluating the impact of telemetry loss, and present two solutions to measure the absolute levels of loss. This framework is used by well-known applications at Microsoft, with millions of users and billions of sessions. These general principles can be adopted by any application to improve the overall trustworthiness of experimentation and data-driven decision making.

cs.OH↗

arXiv2018

Phase-field analysis of quenching and partitioning in a polycrystalline Fe-C system under constrained-carbon equilibrium condition

Mechanical properties of steels are significantly enhanced by retained austenite. Particularly, it has been shown that a recently developed heat-treatment technique called Quenching and Partitioning (Q\&P) stabilises austenite effectively. In the present work, the phase-field approach is adopted to simulate the phase transformation and carbon diffusion, which respectively accompanies the quenching and partitioning process of the polycrystalline Fe-C system. By incorporating the chemical driving-force from the CALPHAD database, the elastic phase-field model, which recovers the sharp-interface solutions, simulates the martensite (alpha') transformation at three different quenching temperatures. The resulting martensite volume-fractions are in complete agreement with the analytical predictions. For the first time, in this study, the constrained carbon equilibrium (CCE) condition is introduced in the polycrystalline set-up to yield the predicted partitioning endpoints. Under the CCE condition, the carbon partitioning in two alloys of varying composition is analysed through the phase-field model which employs chemical potential as the dynamic variable. The volume fraction and distribution of retained austenite is determined from the carbon distribution and its temporal evolution during the partitioning is investigated. It is identified that in the initial stages of partitioning carbon gets accumulated in the austenite ($γ$) along the $γα'$-interface, owing to the substantial difference in the diffusivities and CCE endpoints. This accumulation stabilises the austenite adjacent to the interface. However, depending on the martensite volume-fraction and the alloy composition, the evolution of the stabilised austenite varies. Furthermore, the influence of the phase distribution on the kinetics of the temporal evolution of retained austenite is elucidated.

cond-mat.mtrl-sci↗

arXiv2017

Towards Fully Environment-Aware UAVs: Real-Time Path Planning with Online 3D Wind Field Prediction in Complex Terrain

Today, low-altitude fixed-wing Unmanned Aerial Vehicles (UAVs) are largely limited to primitively follow user-defined waypoints. To allow fully-autonomous remote missions in complex environments, real-time environment-aware navigation is required both with respect to terrain and strong wind drafts. This paper presents two relevant initial contributions: First, the literature's first-ever 3D wind field prediction method which can run in real time onboard a UAV is presented. The approach retrieves low-resolution global weather data, and uses potential flow theory to adjust the wind field such that terrain boundaries, mass conservation, and the atmospheric stratification are observed. A comparison with 1D LIDAR data shows an overall wind error reduction of 23% with respect to the zero-wind assumption that is mostly used for UAV path planning today. However, given that the vertical winds are not resolved accurately enough further research is required and identified. Second, a sampling-based path planner that considers the aircraft dynamics in non-uniform wind iteratively via Dubins airplane paths is presented. Performance optimizations, e.g. obstacle-aware sampling and fast 2.5D-map collision checks, render the planner 50% faster than the Open Motion Planning Library (OMPL) implementation. Test cases in Alpine terrain show that the wind-aware planning performs up to 50x less iterations than shortest-path planning and is thus slower in low winds, but that it tends to deliver lower-cost paths in stronger winds. More importantly, in contrast to the shortest-path planner, it always delivers collision-free paths. Overall, our initial research demonstrates the feasibility of 3D wind field prediction from a UAV and the advantages of wind-aware planning. This paves the way for follow-up research on fully-autonomous environment-aware navigation of UAVs in real-life missions and complex terrain.

cs.RO↗

arXiv2017

Feasibility of Corneal Imaging for Handheld Augmented Reality

Smartphones are a popular device class for mobile Augmented Reality but suffer from a limited input space. Around-device interaction techniques aim at extending this input space using various sensing modalities. In this paper we present our work towards extending the input area of mobile devices using front-facing device-centered cameras that capture reflections in the cornea. As current generation mobile devices lack high resolution front-facing cameras, we study the feasibility of around-device interaction using corneal reflective imaging based on a high resolution camera. We present a workflow, a technical prototype and a feasibility evaluation.

cs.HC↗

arXiv2017

Towards Around-Device Interaction using Corneal Imaging

Around-device interaction techniques aim at extending the input space using various sensing modalities on mobile and wearable devices. In this paper, we present our work towards extending the input area of mobile devices using front-facing device-centered cameras that capture reflections in the human eye. As current generation mobile devices lack high resolution front-facing cameras we study the feasibility of around-device interaction using corneal reflective imaging based on a high resolution camera. We present a workflow, a technical prototype and an evaluation, including a migration path from high resolution to low resolution imagers. Our study indicates, that under optimal conditions a spatial sensing resolution of 5 cm in the vicinity of a mobile phone is possible.

cs.HC↗

arXiv2016

Short-time diffusion behavior of Brownian particles in confining potentials

Diffusion behavior of Brownian particles in confined spaces was studied for the displacements notably shorter than the confinement size. The confinements, resembling structure of porous solids, were modeled using a spatially-varying potential field with an infinitely large potential representing the solid part and zero potential in the void space. Between them, a smooth transient mimicking the interaction potential of the tracer molecules with the pore walls was applied. The respective Smoluchowski equation describing diffusion of tracer particles in the thus created force field was solved under certain approximations allowing for a general analytical solution. The time-depended diffusion coefficient obtained was found to agree with that obtained earlier using the Fick's diffusion equation, but with a different numerical constant. Numerical solution of the Smoluchowski equation with selected interaction potentials was used to clarify the origin of this discrepancy. The conditions under which the solutions obtained within these two approaches converge were established.

cond-mat.dis-nn↗

arXiv2015

Spectral Sensitivity of Graphene/Silicon Heterojunction Photodetectors

We have studied the optical properties of two-dimensional (2D) Schottky photodiode heterojunctions made of chemical vapor deposited (CVD) graphene on n- and p-type Silicon (Si) substrates. Much better rectification behavior is observed from the diodes fabricated on n- Si substrates in comparison with the devices on p-Si substrates in dark condition. Also, graphene/n-Si photodiodes show a considerable responsivity of 270 mA/W within the silicon spectral range in DC reverse bias condition. The present results are furthermore compared with that of a molybdenum disulfide (MoS2)/p-type silicon photodiodes.

cond-mat.mes-hall↗

arXiv2015

Using Models at Runtime to Address Assurance for Self-Adaptive Systems

A self-adaptive software system modifies its behavior at runtime in response to changes within the system or in its execution environment. The fulfillment of the system requirements needs to be guaranteed even in the presence of adverse conditions and adaptations. Thus, a key challenge for self-adaptive software systems is assurance. Traditionally, confidence in the correctness of a system is gained through a variety of activities and processes performed at development time, such as design analysis and testing. In the presence of selfadaptation, however, some of the assurance tasks may need to be performed at runtime. This need calls for the development of techniques that enable continuous assurance throughout the software life cycle. Fundamental to the development of runtime assurance techniques is research into the use of models at runtime (M@RT). This chapter explores the state of the art for usingM@RT to address the assurance of self-adaptive software systems. It defines what information can be captured by M@RT, specifically for the purpose of assurance, and puts this definition into the context of existing work. We then outline key research challenges for assurance at runtime and characterize assurance methods. The chapter concludes with an exploration of selected application areas where M@RT could provide significant benefits beyond existing assurance techniques for adaptive systems.

cs.SE↗