Steffens, Adrian

Technologies are disclosed herein that are directed to the improvement of vulnerability assessment process by avoiding false positive vulnerabilities caused by vendor specific backports of vulnerability fixes that are not considered by conventional vulnerability assessment systems. To secure their software products, vendors identify components that are affected by vulnerabilities used by their products and apply vulnerability fixes introduced by later component versions to those component versions used in their products. This created "gaps" in vulnerable component version ranges provided by public vulnerability intelligence data streams. Vulnerability assessment processes that solely rely on public vulnerability intelligence data incorrectly report vulnerabilities for component versions containing such backported vulnerability fixes. An integrated vulnerability intelligence database that combines public vulnerability intelligence data with vendor specific vulnerability backport data provides a more complete basis for vulnerability assessments that are not prone to fix backport caused false positives.

The disclosure relates to a computer-implemented method for extracting data from textual records. The technical problems solved by the disclosure are i) to generate an extraction pattern for extracting a selected data field from a reference record, ii) to improve the robustness of the extraction pattern by reducing its length, and iii) to extract the selected field from a set of records. The solution comprises determining whether the extraction pattern is disjoint to any segment of the preceding pattern; forming a new extraction pattern by inserting the data type for last data field in the preceding pattern at the beginning of the extraction pattern; and repeating the previous steps with the new extraction pattern until the new extraction pattern is disjoint to all segment comprising the preceding pattern. (Fig. 6)

A method for adjusting a dispersive device (14) for spectroscopic microscopy is disclosed. The method comprises: providing light from a monochromatic light source (10) to a detector (15) via a dispersive device (14) with an optical resonator (20); varying at least one optical length parameter of the dispersive device (14), the at least one optical length parameter comprising a thickness of the optical resonator (20) and/or a refractive index of the optical resonator (20), and determining, by the detector (15), detected data indicative of a diffraction maximum; determining at least one of a width and an intensity of the diffraction maximum for varied values of the at least one optical length parameter; determining an adjustment setting for the at least one optical length parameter for which: the intensity is above a first threshold value and/or the width is below a second threshold value, and a coupling angle of the diffraction maximum is minimized up to a safety margin; performing spectroscopic microscopy using scattered light which is scattered from a sample (12) and passes the dispersive device (14), wherein the dispersive device (14) is adjusted with the adjustment setting. Further, a corresponding system for adjusting a dispersive device (14) for spectroscopic microscopy is disclosed. (Fig. 3)

A method for Brillouin microscopy is disclosed. The method comprises: scanning a sample (12) in a medium (19) with focused laser light along a plurality of scanning areas (21); during the scanning of the sample (12), for a current scanning area (22) of the scanning areas (21) currently being irradiated with the focused laser light: determining a measurement time for the current scanning area; and determining, using a detector (15), of a plurality of spectral measurement values from scattered light scattered from the current scanning area (22) for the duration of the measurement time; wherein the measurement time is determined using a quality metric with respect to a target quality metric which is indicative of at least one of a signal quality, a goodness of fit, a peak shape, and a peak height of a Brillouin peak (34).

A method and a system for removing particles during laser-based scanning microscopy are disclosed. The method comprises: scanning a sample (12) in a medium (19) with focused laser light along a plurality of scanning areas (21) and thereby determining a plurality of measurement values, each indicating scattered light from a corresponding one of the scanning areas (21); determining an occurrence of a particle (30) in an active scanning area (22) based on comparing values of a measurement values subset which corresponds to a scanning areas subset (32) of spatially connected scanning areas containing the active scanning area (22); in reaction to having determined the occurrence of the particle (30) in the active scanning area (22), removing the particle (30) from the active scanning area (22), comprising one of: providing a relative movement of the focused laser light from the active scanning area (22) to outside the scanning areas subset (32) and subsequently lowering a laser power of the focused laser light below an optical trapping threshold, and lowering the laser power of the focused laser light below the optical trapping threshold and providing a flow of the medium (19) in the active scanning area (22).

Disclosed are a headphone control method and a headphone. The method is applied to the headphone including a feed-forward microphone and a feed-back microphone and includes: acquiring (202) a first audio signal through the feed-forward microphone and acquiring a second audio signal through the feed-back microphone; determining (204) a current scene type of an external scene where the headphone is located based on the first audio signal, and obtaining a target effect audio signal corresponding to the current scene type; determining (206) current spectrum relationship information between the first audio signal and the second audio signal, and target spectrum relationship information between the first audio signal and the target effect audio signal; adjusting (208) filter parameters of the headphone according to the current spectrum relationship information and the target spectrum relationship information; reacquiring the second audio signal; and an error between the re-acquired second audio signal and the target effect audio signal is less than a preset error. Using the method can improve an auditory effect after wearing the headphone.

A work vehicle includes a driving force transmission shaft that is disposed with an axis oriented in a front-rear direction and to which driving force of an engine is transmitted, a transmission shaft that is disposed with an axis oriented in a left-right direction and that transmits driving force from the driving force transmission shaft to left and right front wheels, a front axle case that houses the transmission shaft, and a steering cylinder that is capable of changing a turning angle of the front wheels and is provided on the front axle case so as to be positioned above the transmission shaft. (Fig. 1)

A working machine (1) includes a machine body (2), a traveling device (3) to support the machine body (2) such that the machine body (2) is allowed to travel, an operator's seat (4), a protector (8) provided on the machine body (2) to protect the operator's seat (4), and a position detector (40) to acquire position information from one or more positioning satellites. The protector (8) includes a roof (17) provided above the operator's seat (4). The position detector (40) is housed in the roof (17). (Fig. 2)

The present disclosure pertains to a computer-implemented method for generating synthetic data. The method comprises: providing a tensor network including a plurality of tensors and a training dataset including at least one training data string; training the tensor network with respect to the training dataset by gradient descent, comprising the following steps: determining a tensor network gradient from the tensor network, the tensor network gradient being evaluated using the training dataset; applying noise to the tensor network gradient; and adjusting the tensor network based on the tensor network gradient. The method further comprises generating, from the tensor network, synthetic data including a synthetic data string. Each component to be sampled of the synthetic data string is generated according to a sample probability which is a marginal probability for the component or a conditional probability conditioned on at least one value of a further component of the synthetic data string; and at least one of determining the marginal probability and determining the conditional probability comprises separating, for the component, a corresponding partial tensor network from the tensor network and determining a squared norm of the corresponding partial tensor network. Further, a data processing system, a computer program product, and a computer-readable medium are disclosed. (Fig. 2)

A computer-implemented method is presented for extracting data from textual records. The objective of the disclosure is to identify the most appropriate pattern in a set of patterns for extracting data from data records and by applying the most appropriate pattern to a plurality of data records, to robustly extract data from textual records.