Abstract: A computer-implemented method includes receiving, by a processing system, a user story for developing software. The processing system characterizes the user story to determine a plurality of attributes. The processing system classifies a complexity of the user story associated with the attributes. The processing system determines a history score of the user story based on a similarity of one or more previously analyzed user stories having a similar complexity. The processing system recommends one or more modifications to the user story to increase alignment of one or more attributes of the user story with the one or more previously analyzed user stories.

Abstract: A determination is made whether an incident that affects one configuration item in a plurality of configuration items within an information technology environment impacts at least one event for at least one other configuration item in the plurality of configuration items. In response to determining that the incident does impact at least one event on at least one other configuration item, one or more pre-defined actions to execute on the at least one other configuration item are identified. The identified one or more pre-defined actions are executed on the at least one other configuration item.

Abstract: A method for determining a state of a tailgate (9) of a pickup vehicle (1) by a camera system (2), includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (8) captured by a camera (3), determining a first region of interest (ROI1) in the captured image (8) by an electronic computing device (4) of the camera system (2), wherein the first region of interest (ROI1) includes the potential tailgate (9) at least partially, determining a parameter optically characterizing the tailgate (9) depending on the captured image (8), analyzing the first region of interest (ROI1) with regard to the characterizing parameter, and determining a closed state of the tailgate (9) as state or determining an opened state of the tailgate (9) as state depending on the analysis of the first region of interest (ROI1). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: A method for determining a camera parameter for a camera (3) of a camera system (2) of a pickup vehicle (1) includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (18) captured by using the camera (3), determining at least one first cargo bed edge line of the cargo bed (5) by optical analysis of the captured image (18) by using an electronic computing device (4) of the camera system (3), providing a function parameter for a cost function (15) by analysis of at least one first cargo bed edge line by using a regression-analysis algorithm of a solver module (14) of the electronic computing device (4), and determining the camera parameter on the basis of the cost function (15) depending on the provided function parameter by using the electronic computing device (4). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: A determination is made whether an incident that affects one configuration item in a plurality of configuration items within an information technology environment impacts at least one event for at least one other configuration item in the plurality of configuration items. In response to determining that the incident does impact at least one event on at least one other configuration item, one or more pre-defined actions to execute on the at least one other configuration item are identified. The identified one or more pre-defined actions are executed on the at least one other configuration item.

Abstract: A method for determining a camera parameter for a camera (3) of a camera system (2) of a pickup vehicle (1) includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (18) captured by using the camera (3), determining at least one first cargo bed edge line of the cargo bed (5) by optical analysis of the captured image (18) by using an electronic computing device (4) of the camera system (3), providing a function parameter for a cost function (15) by analysis of at least one first cargo bed edge line by using a regression-analysis algorithm of a solver module (14) of the electronic computing device (4), and determining the camera parameter on the basis of the cost function (15) depending on the provided function parameter by using the electronic computing device (4). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: A method for determining a state of a tailgate (9) of a pickup vehicle (1) by a camera system (2), includes capturing a cargo bed (5) of the pickup vehicle (1) in an image (8) captured by a camera (3), determining a first region of interest (ROI1) in the captured image (8) by an electronic computing device (4) of the camera system (2), wherein the first region of interest (ROI1) includes the potential tailgate (9) at least partially, determining a parameter optically characterizing the tailgate (9) depending on the captured image (8), analyzing the first region of interest (ROI1) with regard to the characterizing parameter, and determining a closed state of the tailgate (9) as state or determining an opened state of the tailgate (9) as state depending on the analysis of the first region of interest (ROI1). A computer program product, an electronic computing device (4) as well as a camera system (2) are also disclosed.

Abstract: A computer-implemented method for decoding brain imaging data of individual subjects by using additional imaging data from other subjects includes receiving a plurality of functional Magnetic Resonance Imaging (fMRI) datasets corresponding to a plurality of subjects. Each fMRI dataset corresponds to a distinct subject and comprises brain activation patterns resulting from presentation of a plurality of stimuli to the distinct subject. A group dimensionality reduction (GDR) technique is applied to the example fMRI datasets to yield a low-dimensional space of response variables shared by the plurality of subjects. A model is trained to predict a set of target variables based on the low-dimensional space of response variables shared by all subjects, wherein the set of target variables comprise one or more characteristics of the plurality of stimuli.

Abstract: By way of introduction, the present embodiments described below include apparatuses and methods for generating natural language representations of mental content from functional brain images. Given functional imaging data acquired while a subject reads a text passage, a reconstruction of the text passage is produced. Linguistic semantic vector representations are assigned (1301) to words, phrases or sentences to be used as training stimuli. Basis learning is performed (1305), using brain imaging data acquired (1303) when a subject is exposed to the training stimuli and the corresponding semantic vectors for training stimuli, to learn an image basis directly. Semantic vector decoding (1309) is performed with functional brain imaging data for test stimuli and using the image basis to generate a semantic vector representing the test imaging stimuli. Text generation (1311) is then performed using the decoded semantic vector representing the test imaging stimuli.

Abstract: Systems, methods and apparatuses are provided for the reduction of hydrodynamic frictional drag. These systems, methods and apparatuses can include a vessel surface having an external layer and a plurality of dimples, wherein the external layer comprises a hydrophilic material, and wherein each of the dimples includes an inner surface having a superhydrophobic coating. The dimples can be configured to maintain an air-water interface as one or more fluids flow over the vessel surface. In some embodiments, a pressure reservoir can be coupled with the dimples, and can include an acoustic speaker to vibrate the air-water interface.

Abstract: By way of introduction, the present embodiments described below include apparatuses and methods for generating natural language representations of mental content from functional brain images. Given functional imaging data acquired while a subject reads a text passage, a reconstruction of the text passage is produced. Linguistic semantic vector representations are assigned (1301) to words, phrases or sentences to be used as training stimuli. Basis learning is performed (1305), using brain imaging data acquired (1303) when a subject is exposed to the training stimuli and the corresponding semantic vectors for training stimuli, to learn an image basis directly. Semantic vector decoding (1309) is performed with functional brain imaging data for test stimuli and using the image basis to generate a semantic vector representing the test imaging stimuli. Text generation (1311) is then performed using the decoded semantic vector representing the test imaging stimuli.

Abstract: A computer-implemented method of monitoring dynamics of patient brain state during neurosurgical procedures includes receiving a plurality of brain response images acquired using a functional MRI scan of a patient over a plurality of time points and selecting a plurality of image features from the brain response images. One or more recurrent neural network (RNN) model are used to directly estimate one or more brain state measurements at each time point based on the image features. Once estimated, the brain state measurements are presented on a display.

Abstract: A method for subject-specific assessment of neurological disorders, the method includes receiving 3D image data representative of a subject's brain and identifying subject-specific anatomical structures in the 3D image data. A subject-specific model for electrical dynamics is created based on the 3D image data and the subject-specific anatomical structures and one or more functional indicators of neurological disorder are computed using the subject-specific model for electrical dynamics.

Abstract: A computer-implemented method for decoding brain imaging data of individual subjects by using additional imaging data from other subjects includes receiving a plurality of functional Magnetic Resonance Imaging (fMRI) datasets corresponding to a plurality of subjects. Each fMRI dataset corresponds to a distinct subject and comprises brain activation patterns resulting from presentation of a plurality of stimuli to the distinct subject. A group dimensionality reduction (GDR) technique is applied to the example fMRI datasets to yield a low-dimensional space of response variables shared by the plurality of subjects. A model is trained to predict a set of target variables based on the low-dimensional space of response variables shared by all subjects, wherein the set of target variables comprise one or more characteristics of the plurality of stimuli.

Abstract: A computer-implemented method for decoding patient characteristics and brain state from multi-modality brain imaging data includes receiving a plurality of brain imaging datasets comprising brain imaging data corresponding to plurality of subjects. The brain imaging datasets are aligned to a common reference space and quantitative measures are extracted from each brain imaging dataset. Non-imaging characteristics corresponding to each subject are received and a forward model is trained to map the plurality of characteristics to the quantitative measures.

Abstract: Systems, methods and apparatuses are provided for the reduction of hydrodynamic frictional drag. These systems, methods and apparatuses can include a vessel surface having an external layer and a plurality of dimples, wherein the external layer comprises a hydrophilic material, and wherein each of the dimples includes an inner surface having a superhydrophobic coating. The dimples can be configured to maintain an air-water interface as one or more fluids flow over the vessel surface. In some embodiments, a pressure reservoir can be coupled with the dimples, and can include an acoustic speaker to vibrate the air-water interface.

Abstract: A computer-implemented method for predicting answers to questions concerning medical image analytics reports includes splitting a medical image analytics report into a plurality of sentences and generating a plurality of sentence embedding vectors by applying a natural language processing framework to the plurality of sentences. A question related to subject matter included in the medical image analytics report is received and a question embedding vector is generated by applying the natural language processing framework to the question. A subset of the sentence embedding vectors most similar to the question embedding vector is identified by applying a similarity matching process to the sentence embedding vectors and the question embedding vector. A trained recurrent neural network (RNN) is used to determine a predicted answer to the question based on the subset of the sentence embedding vectors.

Abstract: A computer-implemented method for predicting answers to questions concerning medical image analytics reports includes splitting a medical image analytics report into a plurality of sentences and generating a plurality of sentence embedding vectors by applying a natural language processing framework to the plurality of sentences. A question related to subject matter included in the medical image analytics report is received and a question embedding vector is generated by applying the natural language processing framework to the question. A subset of the sentence embedding vectors most similar to the question embedding vector is identified by applying a similarity matching process to the sentence embedding vectors and the question embedding vector. A trained recurrent neural network (RNN) is used to determine a predicted answer to the question based on the subset of the sentence embedding vectors.

Abstract: A device and method for three-dimensional (3-D) imaging using a defocusing technique is disclosed. The device comprises a lens, a central aperture located along an optical axis for projecting an entire image of a target object, at least one defocusing aperture located off of the optical axis, a sensor operable for capturing electromagnetic radiation transmitted from an object through the lens and the central aperture and the at least one defocusing aperture, and a processor communicatively connected with the sensor for processing the sensor information and producing a 3-D image of the object. Different optical filters can be used for the central aperture and the defocusing apertures respectively, whereby a background image produced by the central aperture can be easily distinguished from defocused images produced by the defocusing apertures.

Abstract: A toroidal plasma is generated without voltage input. It can be produced using a pressurized water jet directed at a non-conductive, dielectric plate. Systems and methods employing the setup are described in which energy is generated and optionally harvested in addition to corona light.