Abstract: A pneumatic tire includes: bead cores formed by winding bead wires in a ring shape and having a polygonal cross-section shape in a meridian cross-section; a carcass extended between bead portions on both sides in a width direction, the carcass being folded back to an outer side in the width direction of the bead portion, the carcass being formed by coating a carcass cord with a coating rubber; an inner organic fiber reinforced layer wound around the bead core and formed by coating an organic fiber cord with a coating rubber; and a rubber reinforcing layer between the inner organic fiber reinforced layer and the carcass to cover at least an apex on an innermost side of the bead core in the width direction. A shortest distance between the bead wire and the carcass cord is 3 mm or more.

Abstract: Provided are a method and device for sending information, and a method and device for receiving information. The method includes: a base station sends first information to a terminal over a downlink channel, wherein the first information include one of the following: information for triggering a random access procedure, and Msg4 in a random access process.

Abstract: A wireless communication system includes a plurality of communication nodes. A first communication node may determine transmit a master information block (MIB), where the MIB comprises a plurality of sub-MIBs. The first communication node transmits the plurality of sub-MIBs to one or more second communication nodes. A second communication node receives the plurality of sub-MIBs and detects the plurality of sub-MIBs. In various embodiments, the plurality of sub-MIBs includes a common sub-MIB common to different types of communication nodes, and a specific sub-MIB specific to a particular type of communication node.

Abstract: A preparation method of submicron powder of high-entropy nitride via nitride thermal reduction with mechano-chemical assistance, comprising material preparation—grinding—activation—preforming—reaction. In the present invention, high-entropy metal nitride and silicon nitride is used as raw materials, soft mechanochemical activation technologies are used to reduce reaction activation energy of the system, thereafter, by thermal reduction of the nitride, high-purity high-entropy nitride powder is prepared with solid phase methods, and the shortage of high-purity high-entropy nitride powder is addressed. There is no impure phase in the (Hf0.2Zr0.2Ti0.2Nb0.2Ta0.2)N high entropy powder prepared according to the present invention, and a single phase solid solution of good crystallinity is formed, and distribution of elements and ingredients in the powder is even, no foreign element is present, and oxygen content is controlled to be less than 0.3%.

Abstract: A motion control method, a robot controller, and a computer readable storage medium are provided. The method includes: calculating an inverse Jacobian matrix of a whole-body generalized coordinate vector at a current time relative to an actual task space vector of a humanoid robot; calculating a target generalized coordinate vector corresponding to a to-be-executed task space vector at a current moment by combining an actual task space vector and the to-be-executed task space vector into a null space of the inverse Jacobian matrix according to preset position constraint(s) corresponding to the whole-body generalized coordinate vector; and controlling a motion state of the humanoid robot according to the target generalized coordinate vector. In this manner, the motion of the humanoid robot is optimized as a whole to achieve the purpose of controlling the humanoid robot to avoid the limits of the motion of joints.

Abstract: The disclosure relates to a system and method for medical imaging. The method may include: move, by a motion controller, a phantom along an axis of a scanner to a plurality of phantom positions; acquire, by a scanner of the imaging device, a first set of PET data relating to the phantom at the plurality of phantom positions; and store the first set of PET data as an electrical file. The length of an axis of the phantom may be shorter than the length of an axis of the scanner, and at least one of the plurality of phantom positions may be inside a bore of the scanner.

Abstract: A gait planning method and a robot using the same as well as a computer readable storage medium are provided. The method includes: determining a reference leg length l0 and a leg length variation range A of a robot; performing a trajectory planning on a length of at least one of the legs of the robot using; an equation including the reference leg length, the leg length variation range, and a preset recurrent excitation function of a time variable t. In this manner, the trajectory planning for the leg length of the robot during motion is performed according to the characteristics of motion scene such as robot jumping or running so that the change of the leg length of the robot is adapted to the motion process, which greatly improves the stability of the robot in the motion scene such as jumping or running.

Abstract: A robot control method includes: acquiring distances between a center of mass (COM) of the biped robot and each of preset key points of feet of the biped robot, and acquiring an initial position of the COM of the biped robot; calculating a position offset of the COM based on the distances; adjusting the initial position of the COM based on the position offset of the COM to obtain a desired position of the COM of the biped robot; and determining desired walking parameters of the biped robot based on the desired position of the COM by using a preset inverse kinematics algorithm, wherein the desired walking parameters are configured to control the biped robot to walk.

Abstract: The present disclosure relates to processing operations that execute image classification training for domain-specific traffic, where training operations are entirely compliant with data privacy regulations and policies. Image classification model training, as described herein, is configured to classify meaningful image categories in domain-specific scenarios where there is unknown data traffic and strict data compliance requirements that result in privacy-limited image data sets. Iterative image classification training satisfies data compliance requirements through a combination of online image classification training and offline image classification training. This results in tuned image recognition classifiers that have improved accuracy and efficiency over general image recognition classifiers when working with domain-specific data traffic. One or more image recognition classifiers are independently trained and tuned to detect an image class for image classification.

Abstract: The present disclosure relates to processing operations that execute image classification training for domain-specific traffic, where training operations are entirely compliant with data privacy regulations and policies. Image classification model training, as described herein, is configured to classify meaningful image categories in domain-specific scenarios where there is unknown data traffic and strict data compliance requirements that result in privacy-limited image data sets. Iterative image classification training satisfies data compliance requirements through a combination of online image classification training and offline image classification training. This results in tuned image recognition classifiers that have improved accuracy and efficiency over general image recognition classifiers when working with domain-specific data traffic. One or more image recognition classifiers are independently trained and tuned to detect an image class for image classification.

Abstract: A textual user input is received and a plurality of different text-to-content models are run on the textual user input. A selection system attempts to identify a suggested content item, based upon the outputs of the text-to-content models. The selection system first attempts to generate a completed suggestion based on outputs from a single text-to-content model. It then attempts to mix the outputs of the text-to-content models to obtain a completed content suggestion.

Abstract: A textual user input is received and a plurality of different text-to-content models are run on the textual user input. A selection system attempts to identify a suggested content item, based upon the outputs of the text-to-content models. The selection system first attempts to generate a completed suggestion based on outputs from a single text-to-content model. It then attempts to mix the outputs of the text-to-content models to obtain a completed content suggestion.

Abstract: The present disclosure relates to processing operations configured for an image recognition pipeline that is used to tailor real-time management of image recognition processing for technical scenarios across a plurality of different applications/services. Image recognition processing is optimized at run-time to ensure that latency requirements are met so that image recognition processing results are returned in a timely manner that aids task execution in an application-specific instances. An image recognition pipeline may manage a plurality of image recognition models that comprise a combination of image analysis service (IAS) models and deep learning models.

Abstract: The present disclosure relates to processing operations that execute image classification training for domain-specific traffic, where training operations are entirely compliant with data privacy regulations and policies. Image classification model training, as described herein, is configured to classify meaningful image categories in domain-specific scenarios where there is unknown data traffic and strict data compliance requirements that result in privacy-limited image data sets. Iterative image classification training satisfies data compliance requirements through a combination of online image classification training and offline image classification training. This results in tuned image recognition classifiers that have improved accuracy and efficiency over general image recognition classifiers when working with domain-specific data traffic. One or more image recognition classifiers are independently trained and tuned to detect an image class for image classification.

Abstract: The present disclosure relates to processing operations configured for an image recognition pipeline that is used to tailor real-time management of image recognition processing for technical scenarios across a plurality of different applications/services. Image recognition processing is optimized at run-time to ensure that latency requirements are met so that image recognition processing results are returned in a timely manner that aids task execution in an application-specific instances. An image recognition pipeline may manage a plurality of image recognition models that comprise a combination of image analysis service (IAS) models and deep learning models.

Abstract: A network address mapping system is described. The network address mapping system can identify a set of Web pages, collects information from the Web pages indicating geographical locations (“geolocations”), and correlate the geolocations with the network addresses from which the identified Web pages are served. The collected information can be weighted based on various factors, such as its relative position in a Web page. The collected information can then be used to identify a geolocation. The network mapping system can deduce geolocations for portions of ranges of network addresses based on the score, and can infer geolocations for other portions based on the deduced geolocations. This mapping can then be stored in a database and provided as a geomapping service. The network address mapping system is able to map network addresses to geographical locations.

Abstract: Methods and apparatuses that synchronize a paper document to an associated digital document by establishing a mapping. An embedded interactive code (EIC) Document is created as a digital file that serves as an intermediate tier between the paper document and the digital document. Both the paper document and the EIC document are generated while printing the paper document. The EIC document records the corresponding EIC array allocations and a unique document identification number. An image capturing pen may generate a stroke on any page of paper document. With the EIC document, the methods and apparatuses inform an application the page and location on the page of the stroke.

Abstract: A method and apparatus for capturing information encoded within a surface, such as location information or document metadata, and associating the information with a document is described. The captured information may be obtained by a camera associated with a pointing or writing device having a camera, such as an image-capturing pen.

Abstract: Computer-readable media having computer-executable instructions provide support for the printing of documents containing embedded interactive code information in conjunction with different applications that include Microsoft Word, Microsoft PowerPoint®, and Microsoft InfoPath™. With a Microsoft Word document, the contents and the associated portion of the EIC pattern are printed page by page. A virtual printer intercepts a spooled printed job and saves the associated enhanced metafile. Subsequently, the EMF and the associated EIC pattern for each page are printed. With a Microsoft PowerPoint® document, each page is printed with a selected number of slides and with an associated portion of the EIC pattern. A note-taking section and play control buttons may be printed. For a Microsoft InfoPath™ document, an HTML document is obtained from the InfoPath XML document before printing. Microsoft InfoPath prints the image of one page with the associated EIC pattern.