SRI International

About: SRI International is a nonprofit organization based out in Menlo Park, California, United States. It is known for research contribution in the topics: Ionosphere & Laser. The organization has 7222 authors who have published 13102 publications receiving 660724 citations. The organization is also known as: Stanford Research Institute & SRI.

Ink jet printing

Abstract: Several basically different nonimpact printing processes have been developed in the last several years using modulated or deflected ink jets. This review paper describes these processes, which are also applicable to the accurate dispensing of fluids, particle sorting, the generation of uniform droplets for research purposes, and other applications.

Inference Controls for Statistical Databases

Abstract: The goal of statistical databases is to provide frequencies, averages, and other statistics about groups of persons (or organizations), while protecting the privacy of the individuals represented in the database. This objective is difficult to achieve, since seemingly innocuous statistics contain small vestiges of the data used to compute them. By correlating enough statistics, sensitive data about an individual can be inferred. As a simple example, suppose there is only one female professor in an electrical engineering department. If statistics are released for the total salary of all professors in the department and the total salary of all male professors, the female professor's salary is easily obtained by subtraction. The problem of protecting against such indirect disclosures of sensitive data is called the inference problem. Over the last several decades, census agencies have developed many techniques for controlling inferences in population surveys. These techniques are applied before data are released so that the distributed data are free from disclosure problems. The data are typically released either in the form of microstatistics, which are files of \"sanitized\" records, or in the form of macrostatistics, which are tables of counts, sums, and higher order statistics. Starting with a study by Hoffman and Miller,' computer scientists began to look at the inference problem in on-line, general-purpose database systems allowing both statistical and nonstatistical access. A hospital database, for example, can give doctors direct access to a patient's medical records, while hospital administrators are permitted access only to statistical summaries of the records. Up until the late 1970's, most studies of the inference problem in these systems led to negative results; every conceivable control seemed to be easy to circumvent, to severely restrict the free flow of information, or to be intractable to implement. Recently, the results have become more positive, since we are now discovering controls that can potentially keep security and information loss at acceptable levels for a reasonable cost. This article surveys some of the controls that have been studied, comparing them with respect to their security, information loss, and cost. The controls are divided into two categories: those that place restrictions on the set of allowable queries and those that add \"noise\" to the data or to the released statistics. The controls are described and further classified within the context of a lattice model.

Method and appartus for increasing resolution of digital color images using correlated decoding

Abstract: Color image compression and decompression is achieved by either spatially and chromatically multiplexing three digitized color planes, such as RGB (Red-Green-Blue) (22), into a digital array representative of a single digitized spatially- and chromatically-multiplexed plane (32, 813f) through use of a data processor or through use of a multi-sensor CCD imaging device with a sensor offset (800), or, by use of a color imaging device, capturing an image directly into a single spatially-multiplexed image plane, for further compression, transmission and/or storage. A decoder (50, 807, 923) extracts, from the stored or transmitted image, data to restore each of the color planes. Specific demultiplexing techniques involve correlating information of other planes with the color plane to be demultiplexed. Various techniques of entropy reduction, smoothing and speckle reduction may be used together with standard digital color compression techniques.

Parent-child interactions when young children have disabilities

Abstract: Publisher Summary This chapter discusses parent–child interactions for young children with disabilities. A major focus of the research on parent–child interactions has been to document what characteristics of parental interactive behavior promote and enhance child developmental outcomes, both short term and long term. The primary focus in this chapter is on the studies with children with disabilities or those at risk for developmental delay. Some of the literature based on the samples of children, who are typically developing, is also included in the discussion to highlight the major themes and issues and to provide comparison groups. The chapter describes selected studies with five populations of children, those with: (a) Down syndrome or mental retardation, (b) developmental delay, (c) orthopedic or motor impairments or cerebral palsy, (d) autism, and (e) low birth weight. Also, the focus is on the studies of behavioral interactions but not on parenting beliefs or attitudes. The chapter concludes with a brief discussion of intervention studies with young children with disabilities or delays aimed at promoting positive parent–child interactions.

MLLR transforms as features in speaker recognition.

Abstract: We explore the use of adaptation transforms employed in speech recognition systems as features for speaker recognition. This approach is attractive because, unlike standard framebased cepstral speaker recognition models, it normalizes for the choice of spoken words in text-independent speaker verification. Affine transforms are computed for the Gaussian means of the acoustic models used in a recognizer, using maximum likelihood linear regression (MLLR). The high-dimensional vectors formed by the transform coefficients are then modeled as speaker features using support vector machines (SVMs). The resulting speaker verification system is competitive, and in some cases significantly more accurate, than state-of-the-art cepstral gaussian mixture and SVM systems. Further improvements are obtained by combining baseline and MLLR-based systems.