A system and method are disclosed for solving a supply chain planning problem modeled as a linear programming (LP) problem. Embodiments include receiving a matrix formulation of at least a portion of the LP problem representing a supply chain planning problem for a supply chain network, generating an image based on the matrix formulation to identify connected components, partitioning the matrix formulation based, at least in part, on the connected components constraint into at least two partitions, formulating an LP subproblem from each of the at least two partitions, and solving the LP subproblems to generate a global solution to the supply chain planning problem.

Described herein is a computer implemented method. The method includes receiving, via an input device, first user input drawing an input shape and generating, based on the first user input, original drawing data that includes an ordered set of points that define the input shape. The original drawing is processed to generate an input vector which also includes an ordered set of points. The input shape is then classified as a first template shape by processing the input vector using a machine learning model. A new shape is then generated based on the first template shape and the original drawing data.

Provided is a driving assistance system including a storage device having a program stored therein and a hardware processor, wherein the hardware processor executes the program stored in the storage device, to thereby recognize an object which is present outside of a vehicle on the basis of a detection result of at least one of a radar device and an imaging device which are mounted in the vehicle, perform driving assistance for the vehicle on the basis of a recognition result, and determine a degree of matching between a portion of a contour line of the object and a road partition line and suppress an operation of the driving assistance in a case where the degree of matching is equal to or greater than a threshold.

A headphone for spatial audio rendering includes a first database having an impulse response pair corresponding to a reference speaker location. A head sensor provides head orientation information to a second database having rotation filters, the filters corresponding to different azimuth and elevation positions relative to the reference speaker location. A digital signal processor combines the rotation filters with the impulse response pair to generate an output binaural audio signal to transducers of the headphone. Efficiencies in creating impulse response or HRTF databases are achieved by sampling the impulse response less frequently than in conventional methods. This sampling at coarser intervals reduces the number of data measurements required to generate a spherical grid and reduces the time involved in capturing the impulse responses. Impulse responses for data points falling between the sampled data points are generated by interpolating in the frequency domain.

A non-intrusive detection method for detecting at least one pop-up window button of the pop-up window includes the following steps: retrieving a screen image on a display device; comparing the screen image with a preset screen image and generating a differential image area according the screen image and the preset screen image; determining the differential image area as the pop-up window when the differential image area is greater than an image area threshold value; selecting a plurality of contour lengths of the pop-up window matching up with a contour length threshold value by Canny edge detector; and analyzing the contour lengths according to Douglas-Peucker algorithm and an amount of endpoints to generate a contour edge corresponding to the pop-up window button.

Free space machine interface and control can be facilitated by predictive entities useful in interpreting a control object's position and/or motion (including objects having one or more articulating members, i.e., humans and/or animals and/or machines). Predictive entities can be driven using motion information captured using image information or the equivalents. Predictive information can be improved applying techniques for correlating with information from observations.

A method of detecting concealed objects using a thermal imager includes obtaining an output comprising a plurality of pixels representing a person, analyzing each pixel matching a contour of the person and excluding any pixel within a blob bounding box of the person, and determining whether a pixel address is represented in a pixel map. In addition, the method includes comparing a value of each remaining pixel to an allowable minimum threshold value representing a lower pre-defined body temperature, and comparing the value of each remaining pixel greater than or equal to the allowable minimum threshold value to an upper allowable threshold value representing an upper pre-defined body temperature. The method also includes excluding any of the remaining pixels within a range between the lower and upper pre-defined body temperatures to define final set of pixels and calculating a pixel difference to indicate a severity of the difference.

A method of detecting concealed objects using a thermal imager includes obtaining an output comprising a plurality of pixels representing a person, analyzing each pixel matching a contour of the person and excluding any pixel within a blob bounding box of the person, and determining whether a pixel address is represented in a pixel map. In addition, the method includes comparing a value of each remaining pixel to an allowable minimum threshold value representing a lower pre-defined body temperature, and comparing the value of each remaining pixel greater than or equal to the allowable minimum threshold value to an upper allowable threshold value representing an upper pre-defined body temperature. The method also includes excluding any of the remaining pixels within a range between the lower and upper pre-defined body temperatures to define final set of pixels, and calculating a pixel difference to indicate a severity of the difference.

A system and method that transforms data formats into contour metrics and further transforms each contour of that mapping into contours pattern metric sets so that each metric created has a representation of one level of contour presentation, at each iteration of the learning contour identification system defined herein. This transformation of data instance to contour metrics permits a user to take relevant data of a data set, as determined by a learning contour identification system, to machines of other types and function, for the purpose of further analysis of the patterns found and labeled by said system. The invention performs with data format representations, not limited to, signals, images, or waveform embodiments so as to identify, track, or detect patterns of, amplitudes, frequencies, phases, and density functions, within the data case and then by way of using combinations of statistical, feedback adaptive, classification, training algorithm metrics stored in hardware, identifies patterns in past data cases that repeat in future, or present data cases, so that high-percentage labeling and identification is a achieved.

A method, system, apparatus, article of manufacture, and computer-readable storage medium provide the ability to merge multiple point cloud scans. A first raw scan file and a second raw scan file (each including multiple points) are imported. The scan files are segmented by extracting segments based on geometry in the scene. The segments are filtered to reduce a number of segments and identify features. A set of candidate matching feature pairs are acquired by coarsely registering features from one scan to features from another scan. The candidate pairs are refined by improving alignment based on corresponding points in the features. The candidate pairs are scored and then merged based on the scores.