Abstract: A surface electromyography signal-torque matching method based on multi-segmentation parallel CNN model (MSP-CNN model), step 1: collecting torque signals and surface electromyography (sEMG) signals when tightening a bolt; step 2: dividing a range of a transducer by at least two granularities, generating a plurality of torque sub-ranges corresponding to the at least two granularities and labeling the plurality of torque sub-ranges with torque labels; step 3: generating sEMG graphs of the sEMG signals in each time window; step 4: determining the torque labels of each time window under each of the at least two granularities according to the torque sub-ranges that average values of torques fall in; step 5: establishing a sample set; step 6: building a MSP-CNN model, and training parallel independent CNN models with sample datasets; and step 7: inputting the sEMG signals of the operator during assembly into trained MSP-CNN model and identifying assembly torques.

Abstract: The present application discloses an OLED display panel and a manufacturing method thereof. The OLED display panel includes: a base layer, an active layer, a gate insulating layer, a first metal layer, and a second metal layer, wherein the active layer includes a channel portion, a source contact portion, a first electrode, and an anode; the second metal layer is arranged above the first metal layer and connected to the source contact portion; the insulating layer, the first metal layer, and the second metal layer are stacked, and an opening is defined in the insulating layer at the position corresponding to the anode.

Abstract: Discussed are a flexible thin film transistor (TFT) substrate, a flexible display panel and a flexible display device. The flexible TFT substrate of the present application can improve bending resistance of the flexible TFT substrate by arranging a concave structure in the bonding region and placing an organic material in the concave structure. When the bonding region is bent, a width of the bonding region can be reduced. Accordingly, a bezel width of the flexible display panel including the flexible TFT substrate is reduced, and a narrow bezel design is realized.

Abstract: An electronic device is provided, which includes a receive coil, a wireless electric energy receiver, a three-level buck circuit, a battery, and a receive end controller. A charging control method is also provided that includes: obtaining a battery voltage, and sending a first control signal and a second control signal based on the battery voltage. The wireless electric energy receiver converts, based on the first control signal, an alternating current generated by the receive coil through induction into a direct current, and outputs a first voltage, V1, to charge the battery in a first voltage mode. The three-level buck circuit bucks an output voltage of the wireless electric energy receiver based on the second control signal, and then outputs a voltage to the battery.

Abstract: The present invention relates to a preparation and purification method for cationic quaternary ammonium salt of sodium hyaluronate in homogeneous medium. By adding a homogeneous solvent and a sodium hyaluronate solid to a vessel, heating the vessel until the contents are dissolved to form a homogeneous system, adding an aqueous solution of 2,3-epoxypropyltrimethylammonium chloride (GTA) to the homogeneous system, then adding a base catalyst, and stirring at a preset temperature to carry out a graft reaction, a graft product is obtained wherein 2,3-epoxypropyltrimethylammonium chloride is grafted to the oxygen atom of the hydroxymethyl group of sodium hyaluronate. By using the method, a graft product wherein 2,3-epoxypropyltrimethylammonium chloride is grafted to the oxygen atom of the hydroxymethyl group of sodium hyaluronate is obtained. Addition of salts is avoided during the reaction, a grafting yield up to 0.69 is obtained, and coagulation occurred to the product is effectively solved.

Abstract: Various embodiments described herein utilize multiple levels of generative adversarial networks (GANs) to facilitate generation of digital images based on user-provided images. Some embodiments comprise a first generative adversarial network (GAN) and a second GAN coupled to the first GAN, where the first GAN includes an image generator and at least two discriminators, and the second GAN includes an image generator and at least one discriminator. According to some embodiments, the (first) image generator of the first GAN is trained by processing a user-provided image using the first GAN. For some embodiments, the user-provided image and the first generated image, generated by processing the user-provided image using the first GAN, are combined to produce a combined image. For some embodiments, the (second) image generator of the second GAN is trained by processing the combined image using the second GAN.

Abstract: Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.

Abstract: Techniques and systems are described that leverage computer vision as part of search to expand functionality of a computing device available to a user and increase operational computational efficiency as well as efficiency in user interaction. In a first example, user interaction with items of digital content is monitored. Computer vision techniques are used to identify digital images in the digital content, objects within the digital images, and characteristics of those objects. This information is used to assign a user to a user segment of a user population which is then used to control output of subsequent digital content to the user, e.g., recommendations, digital marketing content, and so forth.

Abstract: Example implementations described herein are directed to a system for manufacturing dispatching using reinforcement learning and transfer learning. The systems and methods described herein can be deployed in factories for manufacturing dispatching for reducing job-due related costs. In particular, example implementations described herein can be used to reduce massive data collection and reduce model training time, which can eventually improve dispatching efficiency and reduce factory cost.

Abstract: Example implementations described herein can involve systems and methods involving, for receipt of input data from one or more assets, identifying and separating different event contexts from the input data; training a plurality of machine learning models for each of the different event contexts; selecting a best performing model from the plurality of machine learning models to form a compound model; selecting a best performing subset of the input data for the compound model based on maximizing a metric; and deploying the compound model for the selected subset.

Abstract: Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.

Abstract: Camera platform techniques are described. In an implementation, a plurality of digital images and data describing times, at which, the plurality of digital images are captured is received by a computing device. Objects of clothing are recognized from the digital images by the computing device using object recognition as part of machine learning. A user schedule is also received by the computing device that describes user appointments and times, at which, the appointments are scheduled. A user profile is generated by the computing device by training a model using machine learning based on the recognized objects of clothing, times at which corresponding digital images are captured, and the user schedule. From the user profile, a recommendation is generated by processing a subsequent user schedule using the model as part of machine learning by the computing device.

Abstract: Techniques and systems are described that leverage computer vision as part of search to expand functionality of a computing device available to a user and increase operational computational efficiency as well as efficiency in user interaction. In a first example, user interaction with items of digital content is monitored. Computer vision techniques are used to identify digital images in the digital content, objects within the digital images, and characteristics of those objects. This information is used to assign a user to a user segment of a user population which is then used to control output of subsequent digital content to the user, e.g., recommendations, digital marketing content, and so forth.

Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.

Abstract: The present disclosure provides an agrochemical composition comprising a pesticidal active ingredient, an enhancer comprising a salt of dialkylsulfosuccinate, a salt of lauryl sulfate, a salt of lauryl benzene sulfonate, fatty alcohol derivative, a salt of alkyl naphthyl sulphonate, or a salt of alkylnaphthyl sulphate, or a mixture thereof, and a dispersing agent comprising polycarboxylate, phenol sulfonic acid condensation, polyoxypropylene-polyoxyethylene block copolymer, or naphthalene sulfonic acid condensation, or a mixture thereof. The invention also provides a method for controlling pests in a crop, comprising applying an agriculturally effective amount of said composition to the crop in need thereof or its environment.

Abstract: A method for simultaneous determination of nitrogen and oxygen isotope compositions of natural nitrate and nitrite, which quantitatively converts natural nitrate and nitrite into an organic ester and a nitro-compounds respectively, and then nitrate and nitrite ?18O and ?15N are simultaneously determined by adopting a gas chromatography/pyrolysis/gas chromatography/isotope ratio mass spectrometry coupling technology (GC/Py/GC/IRMS). According to the method for simultaneously determining the nitrogen and oxygen isotope compositions of the natural nitrate salt and nitrite salt, the small amount of sample does not result in the loss, acquisition, exchange and fractionation of nitrogen and oxygen.

Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.

Abstract: Example implementations involve a system for Predictive Maintenance using Generative Adversarial Networks for Failure Prediction. Through utilizing three processes concurrently and training them iteratively with data-label pairs, example implementations described herein can thereby generate a more accurate predictive maintenance model than that of the related art. Example implementations further involve shared networks so that the three processes can be trained concurrently while sharing parameters with each other.

Abstract: The disclosure describes a method for simultaneous determination of nitrogen and oxygen isotope compositions of natural nitrate and nitrite, which quantitatively converts natural nitrate and nitrite into an organic ester and a nitro-compounds respectively, and then nitrate and nitrite ?18O and ?15N are simultaneously determined by adopting a gas chromatography/pyrolysis/gas chromatography/isotope ratio mass spectrometry coupling technology (GC/Py/GC/IRMS). According to the method for simultaneously determining the nitrogen and oxygen isotope compositions of the natural nitrate salt and nitrite salt, the small amount of sample does not result in the loss, acquisition, exchange and fractionation of nitrogen and oxygen.

Abstract: A chip package device includes a chip, and a first substrate and a second substrate that are disposed opposite to each other, where the chip is disposed on a surface that is of the first substrate and that faces the second substrate. The chip is electrically connected to the first substrate through a first conductive part, the first substrate is electrically connected to the second substrate through a second conductive part, and a heat dissipation passage is formed between the chip and the second substrate through a thermally conductive layer. The chip package device may further include a molding compound that is configured to wrap the chip. The thermally conductive layer disposed between the chip and the second substrate can quickly dissipate a large amount of heat generated by the chip to the second substrate so that the chip maintains a normal temperature.