There is a significant need among government agencies and other organizations for tools and techniques that facilitate analysis, dissemination, and sharing of data without compromising privacy and/or confidentiality. Data perturbation techniques are a set of statistical disclosure limitation techniques that try to preserve confidentiality of sensitive numeric data, while retaining the validity ...

The synthetic-perturbation screening (SPS) methodology is based on an empirical approach; SPS introduces artificial perturbations into the MIMD program and captures the effects of such perturbations by using the modern branch of statistics called design of experiments. SPS can provide the basis of a powerful tool for screening MIMD programs for performance bottlenecks. This technique is portabl...

Methodologies to calculate adjoint-based first-order-linear perturbation theory sensitivity coefficients with multigroup Monte Carlo methods are developed, implemented, and tested in this paper. These techniques can quickly produce sensitivity coefficients for all nuclides and reaction types for each region of a system model. Monte Carlo techniques have been developed to calculate the neutron f...

We focus primarily on the use of additive and matrix multiplicative data perturbation techniques in privacy preserving data mining (PPDM). We survey a recent body of research aimed at better understanding the vulnerabilities of these techniques. These researchers assumed the role of an attacker and developed methods for estimating the original data from the perturbed data and any available prio...

Multiconfigurational second-order perturbation theory, both in its single-state multiconfigurational second-order perturbation theory (CASPT2) and multistate (MS-CASPT2) formulations, is used to search for minima on the crossing seams between different potential energy hypersurfaces of electronic states in several molecular systems. The performance of the procedures is tested and discussed, foc...

In this article we study various perturbation techniques in the context of irregular spline-type spaces. We first present the sampling problem in this general setting and prove a general result on the possibility of perturbing sampling sets. This result can be regarded as an spline-type space analogue in the spirit of Kadec’s Theorem for bandlimited functions (see [14] and [15]). We further der...

Collaborative Filtering (CF) techniques are becoming increasingly popular with the evolution of the Internet. E-commerce sites use CF systems to suggest products to customers based on like-minded customers’ preferences. People use CF systems to cope with information overload. To conduct collaborative filtering, data from customers are needed. However, collecting high quality data from customers...

Data perturbation is a data security technique that adds 'noise' to databases to allow individual record confidentiality. This technique allows users to ascertain key summary information about the data while preventing a security breach. Four bias types have been proposed which assess the effectiveness of such a technique. However, these biases deal with simple aggregate concepts (averages, etc...

The visual and oculomotor systems in the brain have been studied extensively in the primate. Together, they can be regarded as a single brain system that underlies active vision--the normal vision that begins with visual processing in the retina and extends through the brain to the generation of eye movement by the brainstem. The system is probably one of the most thoroughly studied brain syste...

Data stream can be conceived as a continuous and changing sequence of data that continuously arrive at a system to store or process. Examples of data streams include computer network traffic, phone conversations, web searches and sensor data etc. These data sets need to be analyzed for identifying trends and patterns, which help us in isolating anomalies and predicting future behavior. However,...