Abstract: A label-free optical device for near real time quantification of the multifractal micro-optical properties of a sample includes a source of broadband light; a tunable filter that receives at least a portion of the broadband light and then transmits narrowband light, whereby a specific band of light is selected to avoid unwanted absorption of light by the sample; where the narrowband light is configured to illuminate a selected area of the sample, and in response elastically-scattered light is dispersed from the sample; a light collection device configured to collect at least some of the elastically-scattered light; where at least some of the collected elastically-scattered light is configured to be transmitted to a detector by the light collection device, and the detector is configured to record a light scattering signal; and where the detector is configured to perform light scattering signal measurements at multiple angles or wavelengths to determine a refractive index multifractality of the sample.

Abstract: An electronic biasing circuit for memory operating in a high temperature environment, comprising a first memory cell and a second memory cell, a first MOSFET transistor electrically coupled in series with the first memory cell, wherein the first MOSFET transistor is configured as a switch, a second MOSFET transistor electrically coupled in series with the second memory cell, wherein the second MOSFET transistor is configured as a switch, a DC bias current source configured to generate a negative DC bias voltage signal, a first read/word line electrically coupled to a gate of the first MOSFET transistor, and a second read/word line electrically coupled to a gate of the second MOSFET transistor, wherein in response to a read operation of the first memory cell, the second read/word line is configured to deliver the negative DC bias voltage signal to the gate of the second MOSFET transistor.

Abstract: A label-free optical device for near real time quantification of the multifractal micro-optical properties of a sample includes a source of broadband light; a tunable filter that receives at least a portion of the broadband light and then transmits narrowband light, whereby a specific band of light is selected to avoid unwanted absorption of light by the sample; where the narrowband light is configured to illuminate a selected area of the sample, and in response elastically-scattered light is dispersed from the sample; a light collection device configured to collect at least some of the elastically-scattered light; where at least some of the collected elastically-scattered light is configured to be transmitted to a detector by the light collection device, and the detector is configured to record a light scattering signal; and where the detector is configured to perform light scattering signal measurements at multiple angles or wavelengths to determine a refractive index multifractality of the sample.

Abstract: A system and computer-implemented method for ensuring code quality compliance for one or more Database Management Systems (DBMSs) is provided. The system comprises a user interface configured to prompt one or more users to select one or more options and provide information for configuring rules corresponding to coding standards and best practices. The system further comprises a rules registration module to register the configured rules in a repository for validation. Furthermore, the system comprises a source selector to provide options to the one or more users to select one or more DBMSs and a source manager to fetch database code from the one or more selected DBMSs. In addition, the system comprises one or more parsers to parse the fetched database code, a validator to validate the parsed code using the registered rules and a report manager to provide results of the validation to the one or more users.

Abstract: A system and computer-implemented method for ensuring code quality compliance for one or more Database Management Systems (DBMSs) is provided. The system comprises a user interface configured to prompt one or more users to select one or more options and provide information for configuring rules corresponding to coding standards and best practices. The system further comprises a rules registration module to register the configured rules in a repository for validation. Furthermore, the system comprises a source selector to provide options to the one or more users to select one or more DBMSs and a source manager to fetch database code from the one or more selected DBMSs. In addition, the system comprises one or more parsers to parse the fetched database code, a validator to validate the parsed code using the registered rules and a report manager to provide results of the validation to the one or more users.

Abstract: A method of analyzing a medical image, where the medical image comprises one or more than one region of interest, and where the method comprises a) providing the medical image comprising a set of actual image values; b) rescaling the actual image values to produce corresponding rescaled image values and to produce a rescaled image from the rescaled image values; c) deriving a histogram of the rescaled image values; d) using the histogram to derive an adaptive segmentation threshold; e) using the adaptive segmentation threshold to recursively split the rescaled image; f) terminating the recursive splitting of the sub(sub) images using one or more than one predetermined criteria; and g) identifying one sub(sub) image in the terminated Hierarchical Region Splitting Tree which comprises the region of interest.

Abstract: A method of analyzing a medical image, where the medical image comprises one or more than one region of interest, and where the method comprises a) providing the medical image comprising a set of actual image values; b) rescaling the actual image values to produce corresponding rescaled image values and to produce a rescaled image from the rescaled image values; c) deriving a histogram of the rescaled image values; d) using the histogram to derive an adaptive segmentation threshold; e) using the adaptive segmentation threshold to recursively split the rescaled image; f) terminating the recursive splitting of the sub(sub) images using one or more than one predetermined criteria; and g) identifying one sub(sub) image in the terminated Hierarchical Region Splitting Tree which comprises the region of interest.

Abstract: A method of analyzing a medical image, where the medical image comprises one or more than one region of interest, and where the method comprises a) providing the medical image comprising a set of actual image values; b) rescaling the actual image values to produce corresponding rescaled image values and to produce a rescaled image from the rescaled image values; c) deriving a histogram of the rescaled image values; d) using the histogram to derive an adaptive segmentation threshold; e) using the adaptive segmentation threshold to recursively split the rescaled image; f) terminating the recursive splitting of the sub(sub) images using one or more than one predetermined criteria; and g) identifying one sub(sub) image in the terminated Hierarchical Region Splitting Tree which comprises the region of interest.

Abstract: A method of analyzing a medical image, where the medical image comprises one or more than one region of interest, and where the method comprises a) providing the medical image comprising a set of actual image values; b) rescaling the actual image values to produce corresponding rescaled image values and to produce a rescaled image from the rescaled image values; c) deriving a histogram of the rescaled image values; d) using the histogram to derive an adaptive segmentation threshold; e) using the adaptive segmentation threshold to recursively split the rescaled image; f) terminating the recursive splitting of the sub(sub) images using one or more than one predetermined criteria; and g) identifying one sub(sub) image in the terminated Hierarchical Region Splitting Tree which comprises the region of interest.

Abstract: A method of analyzing a medical image, where the medical image comprises one or more than one region of interest, and where the method comprises a) providing the medical image comprising a set of actual image values; b) rescaling the actual image values to produce corresponding rescaled image values and to produce a rescaled image from the rescaled image values; c) deriving a histogram of the rescaled image values; d) using the histogram to derive an adaptive segmentation threshold; e) using the adaptive segmentation threshold to recursively split the rescaled image; f) terminating the recursive splitting of the sub(sub) images using one or more than one predetermined criteria; and g) identifying one sub(sub) image in the terminated Hierarchical Region Splitting Tree which comprises the region of interest.