Abstract: According to a present invention embodiment, software is analyzed for security vulnerabilities. Information from a security scan of code is analyzed to identify a security issue pertaining to a code portion. A machine learning model determines an initial risk factor score for the security issue based on a history of information pertaining to one or more prior security scans. The initial risk factor score is refined to produce an overall risk factor score for the security issue based on a confidence of the initial risk factor score. The initial risk factor score is refined based on one or more risk factor scores for operations within the code applied to a variable of the code portion. A classification of the security issue is determined as one of a valid security issue and a false positive based on the overall risk factor score.

Abstract: A magnetic field enhancing component, including: a first dielectric layer comprising a first surface and a second surface opposite to each other; a first electrode layer arranged on the first surface; a second electrode layer and a fourth electrode layer, which are arranged on the second surface at an interval, where orthographic projections of the first electrode layer and the second electrode layer, which are projected onto the first dielectric layer, overlap each other, and orthographic projections of the first electrode layer and the fourth electrode layer, which are projected onto the first dielectric layer, overlap each other; and a first external capacitor, a second external capacitor, and a first switching control circuit. One terminal of the second external capacitor is connected to the second electrode layer, and another terminal of the second external capacitor is connected to one terminal of the first external capacitor and one terminal of the first switching control circuit, respectively.

Abstract: A magnetic field enhancing component and a magnetic field enhancing device. The magnetic field enhancing component includes a first dielectric layer, a first electrode layer, a second electrode layer, a third electrode layer, a fourth electrode layer, and a control circuit. The first electrode layer and the second electrode layer are arranged on a first surface of the first dielectric layer. The third electrode layer and the fourth electrode layer are arranged on a second surface of the first dielectric layer. The first electrode layer and the third electrode layer form a second structural capacitor. The second electrode layer and the fourth electrode layer form a third structural capacitor. The control circuit is connected between the first electrode layer and the second electrode layer, and includes a third capacitor, a first inductor, and a first switch circuit. The first inductor and the first switch circuit are connected in series, then is connected to the third capacitor in parallel.

Abstract: The present disclosure discloses an automated particle implantation system comprising an active system and a passive system. The active system may be configured to obtain a scanning image of a scanned object. The active system may be also configured to plan a radioactive particle implantation treatment according to the scanning image and obtain a radioactive particle implantation treatment planning result. The active system may be further configured to control the passive system to execute a radioactive particle implantation operation based on the radioactive particle implantation treatment planning result. The present disclosure further discloses a particle chain generating mechanism. The present disclosure further discloses a puncture device terminal.

Abstract: Various examples of a system for peanut sorting and grading are disclosed herein. The system for grading peanut maturity, can include: a sample feeder configured to supply individual peanuts to an imaging area; a sorting board comprising a plurality of chutes and a plurality of gates, each chute of the plurality of chutes designated for a grade of peanut; and program instructions to obtain the digital image of the individual peanut; determine the grade of the individual peanut; and sort the individual peanut based on the grade of the individual peanut. A method for grading peanut maturity, can include feeding an individual peanut to an imaging area; obtaining a digital image of the individual peanut; determining a grade of the individual peanut based on an average color; and sorting the individual peanut in a chute of a sorting board based on the grade of the individual peanut.

Abstract: The present disclosure provides peanut maturity grading systems and methods for quickly, efficiently, and objectively determining a peanut maturity grade for a crop of peanuts and determining an optimal harvest time for the crop. Embodiments of systems and methods of the present disclosure can be performed in the field or field-side and do not require assistance of a trained peanut grading specialist.

Abstract: The present disclosure provides peanut maturity grading systems and methods for quickly, efficiently, and objectively determining a peanut maturity grade for a crop of peanuts and determining an optimal harvest time for the crop. Embodiments of systems and methods of the present disclosure can be performed in the field or field-side and do not require assistance of a trained peanut grading specialist.

Abstract: Various examples of a system for peanut sorting and grading are disclosed herein. The system for grading peanut maturity, can include: a sample feeder configured to supply individual peanuts to an imaging area; a sorting board comprising a plurality of chutes and a plurality of gates, each chute of the plurality of chutes designated for a grade of peanut; and program instructions to obtain the digital image of the individual peanut; determine the grade of the individual peanut; and sort the individual peanut based on the grade of the individual peanut. A method for grading peanut maturity, can include feeding an individual peanut to an imaging area; obtaining a digital image of the individual peanut; determining a grade of the individual peanut based on an average color; and sorting the individual peanut in a chute of a sorting board based on the grade of the individual peanut.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Abstract: The present disclosure provides peanut maturity grading systems and methods for quickly, efficiently, and objectively determining a peanut maturity grade for a crop of peanuts and determining an optimal harvest time for the crop. Embodiments of systems and methods of the present disclosure can be performed in the field or field-side and do not require assistance of a trained peanut grading specialist.

Abstract: This disclosure provides a method, a computing system and a computer program product for optimizing computer-readable commands. The method includes detecting an intention of a set of commands based on a semantic model. The semantic model represents the set of commands and contexts of execution of the set of commands. The method further includes obtaining a predetermined semantic sub-model associated with the intention and updating the semantic model with the predetermined semantic sub-model. The method further includes generating a script of commands based on the updated semantic model.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Abstract: This disclosure provides a method, a computing system and a computer program product for optimizing computer-readable commands. The method includes detecting an intention of a set of commands based on a semantic model. The semantic model represents the set of commands and contexts of execution of the set of commands. The method further includes obtaining a predetermined semantic sub-model associated with the intention and updating the semantic model with the predetermined semantic sub-model. The method further includes generating a script of commands based on the updated semantic model.

Abstract: The present disclosure provides peanut maturity grading systems and methods for quickly, efficiently, and objectively determining a peanut maturity grade for a crop of peanuts and determining an optimal harvest time for the crop. Embodiments of systems and methods of the present disclosure can be performed in the field or field-side and do not require assistance of a trained peanut grading specialist.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Abstract: A method, a computer program product, and a computer system for determining a location using street view images. A mobile device obtains an image captured by the mobile device, obtains a set of street view images, and obtains a first graph of the image captured by the mobile device and a plurality of second graphs of the set of the street view images. The first graph includes nodes representing interest points in the image captured by the mobile device, and the plurality of the second graphs includes nodes representing interest points in the set of the street view images. The mobile device determines a location of the mobile device, based on relevance between the first graph and the plurality of the second graphs.

Abstract: A method, system and computer-usable medium are disclosed for managing resource capacity for the provision of cloud-based services. Application deployment and undeployment data is received, and then processed, to perform an update of a capacity-weighted graph to reflect a set of applications deployed in a cloud computing environment. The application deployment and undeployment data is then further processed to determine a set of resource dependencies associated with the set of deployed applications. Thereafter, monitoring operations are performed to monitor consumption of a set of services associated with the set of deployed applications. Further monitoring operations are then performed to monitor requests from the set of deployed applications to predict the need for the provision of a set of additional services for consumption at runtime.

Abstract: A method and system of implementing continuous deployment of scripts in languages that only support single deployment. The method and system may develop incremental scripts based on differences between a pending script and an implemented script.

Abstract: In an approach to tracking at least one target subject in a camera network, a search is started to find a target subject on a camera within a camera network. Features are extracted from the target subject and search queries are initiated in other nearby cameras within the camera network. Search queries attempt to detect target subjects and present the finds in a ranked order. Application of aggregate searches in multiple cameras and prior search results are used to improve matching results in the camera network; propagate a search of the target subject to discover the full pathway in the camera network; and project future occurrences of the target subject in subsequent cameras in the camera network.

Abstract: A method for translating a webpage includes receiving an HTML package comprising one or more HTML files and one or more corresponding program integrated information (PII) files, identifying elements corresponding to the one or more HTML files to be translated into a target language, creating a mapping file corresponding to the identified elements, wherein the mapping file indicates a PII file to which each identified element corresponds as well as context information corresponding to each PII file, translating the PII files indicated by the mapping file into a target language to provide translated PII files, and replacing untranslated PII files in the HTML package with corresponding translated PII files to provide a translated package.