Abstract: The present disclosure relates to a mulch film laying robot and a mulch film laying method. The mulch film laying robot comprises a walking mechanism for walking, a mulch film laying mechanism for mulch film laying, a mulch film compaction mechanism for compacting a laid mulch film, and a reconfiguration mechanism for a robot to cross obstacles. The walking mechanism comprises a plurality of pairs of vertical supports, rollers are arranged at the lower ends of the vertical supports, walking rotating motors for driving the rollers are arranged at the bottoms of two pairs of vertical supports at both ends of the walking mechanism, and the vertical supports on the same side are sequentially connected and fixed by transverse connecting rods. The reconfiguration mechanism is arranged between each pair of vertical supports, and the reconfiguration mechanism comprises two reconfiguration arms.

Abstract: Embodiments of the present invention facilitate product defect detection. A computer-implemented method comprises: receiving, by a device operatively coupled to one or more processors, a template image of a normal product; generating, by the device, one or more geometric training parameters for transforming the template image; and transforming, by the device, the template image using the one or more geometric training parameters to generate a transformed image for training a data model, wherein the trained data model being used for aligning the template image and an image under inspection of a product.

Abstract: Applications under test (AUT) may be tested by automated testing systems utilizing machine vision to recognize visual elements presented by the AUT and apply inputs to graphical elements, just as a human would. By utilizing the smallest image patch available, processing demands of the testing system are minimized. However, the image patch used to identify a portion of an AUT must be identifiable to the automated system. By selecting image patches that comprise the smallest size, but can be identified in an AUT by an automated system using machine vision, even as the AUT display is resized, reproportioned, noisy, or otherwise altered from the testing platform that was utilized for training.

Abstract: A technique includes receiving, by a computer, user input representing creation of a first programmatic description of a first test object of source code to be tested. The technique includes, in response to receiving the user input, determining, by the computer, based on other programmatic descriptions of other test objects, a recommendation of a parameter to be used in the first programmatic description to identify the first test object. The technique includes causing, by the computer, a display of the recommendation.

Abstract: The present invention relates to a cut-stem separating and baffling apparatus and a primary air separation apparatus. The cut-stem separating and baffling apparatus includes a cut-stem separating baffle and struts; and the strut includes a base, a hanging panel, and an inner hexagon adjustment bolt, where the base includes a connecting segment and a support segment that are connected to each other, where the connecting segment is located above the cut-stem separating baffle, and the support segment is located behind the cut-stem separating baffle; the hanging panel includes a transverse hanging panel, and a longitudinal hanging panel, and a connecting hanging panel is disposed in a direction of the longitudinal hanging panel toward the cut-stem separating baffle, where the connecting hanging panel is connected to the cut-stem separating baffle; and the connecting segment of the base is connected to the transverse hanging panel using the inner hexagon adjustment bolt.

Abstract: In an approach to AI empowered factory automation using an industrial IoT, responsive to receiving a new production task, production requirements are input into an AI engine. Equipment and software containers are selected based on the AI model. An orchestration service is created, where the orchestration service collaborates the equipment and the software containers.

Abstract: The present disclosure relates to the technical field of tea brewing devices, and more particularly, to a beverage brewing device. The beverage brewing device comprises a kettle body, a heating disc, and a tea-leaf basket. The heating disc and the tea-leaf basket are located in the kettle body and an air cylinder mechanism is fixed in the kettle body. A moving piston is arranged in an inner cavity of the air cylinder mechanism, and the piston is connected to the tea-leaf basket. The air cylinder mechanism is connected to an air pump, which is used for conveying a driving gas to the air cylinder mechanism. The piston is driven by the driving gas, thereby driving the tea-leaf basket to move in the kettle body. The air cylinder mechanism may automatically drive the tea-leaf basket to move up and down, achieving a simple structure and a low cost.

Abstract: A system, method, and computer program product provides a way to separate connected or adhered adjacent characters of a digital image for license plate recognition. As a threshold processing, the method performs a recognition of character adhesion by obtaining character parameters using an image processor. The parameters include a horizontal max crossing and a ratio of width and height. A first rule-based module is used responsive to the character parameters to distinguish the adhered characters (character adhesions) that are easy to judge, leaving the uncertain part to a character adhesion classifier model for discrimination. Character adhesion data is obtained by data augmentation including the adding of a random distance between two single characters to create class like adhered characters. Then the character adhesion classifier model of single character and character adhesion data is trained. Any uncertain part can be distinguished by the trained character adhesion classifier model.

Abstract: An image of a graphical user interface is captured. A process is started to record identification of a graphical object (e.g., a text field) in the image of the graphical user interface. Recording identification of the graphical object in the image of the graphical user interface is based on machine learning. An end to the process to record identification of the graphical object in the image of the graphical user interface is identified. A machine learned software object is updated. For example, the machine learned software object is updated with a location of the graphical object. The updated machine learned software object then is used to test the graphical object. For example, to automatically fill in the text field using a test script.

Abstract: A mechanism is provided for controlling the internal air-quality of a vehicle, including configuring a control policy that controls an internal air-quality of a vehicle and performing an action dictated by the control policy according to a window status of the vehicle.

Abstract: The present invention relates to a method, system and computer program product for defect enhancement. According to the method, a plurality of proposed regions from a plurality of images taken for a display panel is obtained. Each of proposed region of the plurality of proposed regions include a suspected defect on the display panel. At least two proposed regions from the plurality of proposed regions that deserve to be superimposed based on a set of conditions is determined. The at least two proposed regions for acquiring an enhanced defect are superimposed.

Abstract: A cigarette device management system includes an information management module, and a maintenance prediction module, a device state acquisition module and a purchase statistics module which are in communication connection with it. The maintenance prediction module is built by an artificial neural network model and is configured to predict a failure interval. The device state acquisition module acquires a device operating parameter and an operating duration of the device in real time, and compares the device operating parameter with a safety parameter range. In accordance with the system, the maintenance timing of the device can be predicted, the purchase quantity of the spare part and the purchase timing of the spare part also can be predicted.

Abstract: A system, method, and computer program product provides a way to separate connected or adhered adjacent characters of a digital image for license plate recognition. As a threshold processing, the method performs a recognition of character adhesion by obtaining character parameters using an image processor. The parameters include a horizontal max crossing and a ratio of width and height. A first rule-based module is used responsive to the character parameters to distinguish the adhered characters (character adhesions) that are easy to judge, leaving the uncertain part to a character adhesion classifier model for discrimination. Character adhesion data is obtained by data augmentation including the adding of a random distance between two single characters to create class like adhered characters. Then the character adhesion classifier model of single character and character adhesion data is trained. Any uncertain part can be distinguished by the trained character adhesion classifier model.

Abstract: Applications under test (AUT) may be tested by automated testing systems utilizing machine vision to recognize visual elements presented by the AUT and apply inputs to graphical elements, just as a human would. By utilizing the smallest image patch available, processing demands of the testing system are minimized. However, the image patch used to identify a portion of an AUT must be identifiable to the automated system. By selecting image patches that comprise the smallest size, but can be identified in an AUT by an automated system using machine vision, even as the AUT display is resized, reproportioned, noisy, or otherwise altered from the testing platform that was utilized for training.

Abstract: Blockchain based IoT data management can include receiving IoT data are with one or more processing units. At least one aggregation pattern of the IoT data can be determined by one or more processing units. The IoT data can be hashed, based upon the at least one aggregation pattern to obtain hash values of the IoT data by one or more processing units. The hash values can be sent to a blockchain system for storing by one or more processing units.

Abstract: A platform for processing a workpiece includes a transmission mechanism, a plurality of workstations and a plurality of movable vehicles. The transmission mechanism transports the workpiece to be processed to one of the plurality of workstations. Each movable vehicle includes a processing module and a docking interface adapted to connect with a docking station of each workstation. The movable vehicles are each adapted to move in and out of each workstation, and each processing module is adapted to process the workpiece transmitted to the workstation after the movable vehicle is moved in and positioned in the workstation.

Abstract: In an approach to AI empowered factory automation using an industrial IoT, responsive to receiving a new production task, production requirements are input into an AI engine. Equipment and software containers are selected based on the AI model. An orchestration service is created, where the orchestration service collaborates the equipment and the software containers.

Abstract: The present disclosure relates to training a machine learning model to classify images. An example method generally includes receiving a training data set including images in a first category and images in a second category. A convolutional neural network (CNN) is trained using the training data set, and a feature map is generated from layers of the CNN based on features of images in the training data set. A first area in the feature map including images in the first category and a second area in the feature map where images in the first category overlap with images in the second category are identified. The first category is split into a first subcategory corresponding to the first area and a second subcategory corresponding to the second area. The CNN is retrained based on the images in the first subcategory, images in the second subcategory, and images in the second category.

Abstract: A device for wholly treating urban and rural mixed household refuse at low temperature on site is provided. The device includes a vibration sieving and crushing system, a magnetic separator, conveyor belts, a magnetic pulse mineralization reactor and a tail gas purifying device. By using the device, urban and rural mixed household refuse is continuously fed; the mixed household refuse is sieved by the vibrating sieve according to viscosity, weight and size; nonferrous metal is sieved through a magnetic field; and organic substances are conveyed to the magnetic pulse mineralization mixed household refuse treatment device for terminal treatment. So, efficient reduction and harmlessness of the organic substances in the mixed household refuse are realized, and the pollution of organic wastes on the environment is effectively eliminated.

Abstract: A computing device includes a processor and a medium storing instructions. The instructions are executable by the processor to: identify, based on a blob detection analysis, a plurality of potential input elements in a graphical user interface (GUI); determine a set of rows including potential input elements that are in a horizontal alignment and in a same size range; determine a set of columns including potential input elements that are in a vertical alignment and in a same size range; determine a set of input elements comprising multiple potential input elements that are located at intersections of the identified set of rows and the identified set of columns; and perform automated testing of the GUI using the determined set of input elements.