A Radial-In-Plane Sensitivity Interferometer with Divergent Illumination for Displacement Measurement

An in-plane radial sensitivity interferometer that uses the divergent illumination for displacement measurement in the radial direction is presented. A description and mathematical model for calculating the sensitivity vector are also presented. The interferometer has two polarizing filters: a circular one and a linear one to implement the phase stepping technique. A measurement of the radial deformation by thermal expansion is performed over an aluminium plate in order to test the interferometer. The results indicate that the maximum contribution of the out-of-plane with respect to the radial-in-plane sensitivity vector is less than 3% and decreases by less than 1% when measurements are performed near the optical axis. The measurement is compared with the results obtained by a finite element analysis on a virtual specimen model.

Not All Attributes are Created Equal: dX -Private Mechanisms for Linear Queries

Differential privacy provides strong privacy guarantees simultaneously enabling useful insights from sensitive datasets. However, it provides the same level of protection for all elements (individuals and attributes) in the data. There are practical scenarios where some data attributes need more/less protection than others. In this paper, we consider dX -privacy, an instantiation of the privacy notion introduced in [6], which allows this flexibility by specifying a separate privacy budget for each pair of elements in the data domain. We describe a systematic procedure to tailor any existing differentially private mechanism that assumes a query set and a sensitivity vector as input into its dX -private variant, specifically focusing on linear queries. Our proposed meta procedure has broad applications as linear queries form the basis of a range of data analysis and machine learning algorithms, and the ability to define a more flexible privacy budget across the data domain results in improved privacy/utility tradeoff in these applications. We propose several dX -private mechanisms, and provide theoretical guarantees on the trade-off between utility and privacy. We also experimentally demonstrate the effectiveness of our procedure, by evaluating our proposed dX -private Laplace mechanism on both synthetic and real datasets using a set of randomly generated linear queries.

Maximizing Sensitivity Vector Fields: A Parametric Study

Sensitivity vector fields (SVFs) have proven to be an effective method for identifying parametric variations in dynamical systems. These fields are constructed using information about how a dynamical system's attractor deforms under prescribed parametric variations. Once constructed, they can be used to quantify any additional variations from the nominal parameter set as they occur. Since SVFs are based on attractor deformations, the geometry and other qualities of the baseline system attractor impact how well a set of SVFs will perform. This paper examines the role attractor characteristics and the choices made in SVF construction play in determining the sensitivity of SVFs. The use of nonlinear feedback to change a dynamical system with the intent of improving SVF sensitivity is explored. These ideas are presented in the context of constructing SVFs for several dynamical systems.

Experimental Research on the Acceleration Sensitivity of Quartz Crystal Oscillators

Quartz crystal oscillators are often used as the reference frequency sources, but they are very sensitive to accelerations. This paper discussed how accelerations affect oscillators’ frequency stability. The frequency shifts caused by gravity was shown through 2g-tipover experiment. Then a vibration experiment system was built up, which consist of the vibrating platform, the controlling part, the measuring part and the oscillator. We studied the relationship between accelerations and oscillator’s frequency shifts by imposing sinusoidal and random vibrations onto the oscillator and observing the phase noise degradation via signal source analyzer. The paper also brought up the measuring method of the acceleration sensitivity vector.