Abstract: A frame sealing adhesive of the liquid-crystal phase shifter is disposed between two transparent substrates, the frame sealing adhesive encloses a first cavity, a first part of the metal-trace layer is located inside the first cavity, and a second part of the metal-trace layer is located outside the first cavity. The second part is disposed on first surfaces or second surfaces of the two transparent substrates. If the second part is disposed on the first surfaces of the two transparent substrates, metal cushion layers are provided between the frame sealing adhesive and the first surfaces of the two transparent substrates. If the second part is disposed on the second surfaces of the two transparent substrates, the first part and the second part are electrically connected by metal via holes provided in the transparent substrates, and the frame sealing adhesive contacts the first surfaces of the two transparent substrates.

Abstract: Managing thermal capabilities of an information handling system, including identifying a maximum supported ambient temperature of the information handling system; identifying a current ambient temperature of the information handling system; calculating a temperature delta based on the maximum supported ambient temperature of the information handling system and the current ambient temperature of the information handling system; adjusting, based on the temperature delta, one or more thermal control trigger points; adjusting, based on the adjusted thermal control trigger points, a fan speed of a fan of the information handling system; and determining, based on the adjusted fan speed of the fan, an updated cooling capacity associated with the information handling system.

Abstract: Disclosed are semiconductor devices that implement relaxed clock forwarding between logic blocks. In one embodiment the system includes a set of logic blocks forming a first processing path. Another set of logic blocks form additional processing paths. A clock is configured to forward the data between the logic blocks asynchronously in the first processing path in which the data is asynchronously forwarded between logic blocks. This forwarding is asynchronous with the additional processing paths data and clock. The ends or last logic block in each path can be synchronized using a synchronizer component. The synchronizer can be a plurality of asynchronous FIFOs. In one embodiment, logic blocks form a matrix and the processing paths are along the rows or columns of the matrix.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. One of the most important applications for artificial intelligence is object recognition and classification from digital images. Convolutional neural networks have proven to be a very effective tool for object recognition and classification from digital images. However, convolutional neural networks are extremely computationally intensive thus requiring high-performance processors, significant computation time, and significant energy consumption. To reduce the computation time and energy consumption a “cone of dependency” and “cone of influence” processing techniques are disclosed. These two techniques arrange the computations required in a manner that minimizes memory accesses such that computations may be performed in local cache memory. These techniques significantly reduce the time to perform the computations and the energy consumed by the hardware implementing a convolutional neural network.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. However, artificial intelligence is extremely computationally intensive field such that it can be expensive, time consuming, and energy consuming. Fortunately, many of the calculations required for artificial intelligence can be performed in parallel such that specialized processors can great increase computational performance. Specifically, artificial intelligence generally requires large numbers of matrix operations to implement neural networks such that specialized matrix processor circuits can improve performance. Thus, this document discloses apparatus and methods for efficiently processing matrix operations.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. However, artificial intelligence is extremely computationally intensive field such that it can be expensive, time consuming, and energy consuming. Fortunately, many of the calculations required for artificial intelligence can be performed in parallel such that specialized processors can great increase computational performance. Specifically, artificial intelligence generally requires large numbers of matrix operations to implement neural networks such that specialized matrix processor circuits can improve performance. To perform all these matrix operations, the neural processing circuits must be quickly and efficiently supplied with data to process or else the matrix processor circuits end up idle or spending large amounts of time loading weight matrix data.

Abstract: Provided is a method comprising obtaining information about a detected memory error in a memory device, the memory device being connected to a first host via a compute express link, CXL, interface. The method comprises further recording the memory error information into a firmware of the memory device.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. However, artificial intelligence is extremely computationally intensive field such that it can be expensive, time consuming, and energy consuming. Fortunately, many of the calculations required for artificial intelligence can be performed in parallel such that specialized processors can greatly increase computational performance. Specifically, artificial intelligence generally requires large numbers of matrix operations to implement neural networks such that specialized Matrix Processor circuits can improve performance. But a neural network is more than a collection of matrix operations; it is a set of specifically coordinated matrix operations with complex data dependencies. Without proper coordination, Matrix Processor circuits may end up idle or spending large amounts of time loading in different weight matrix data.

Abstract: Disclosed herein are methods of molecular magnetic resonance (MR) imaging and positron emission tomography using extracellular probes that target extracellular allysine aldehyde and act as a noninvasive biomarker of fibrogenesis with high sensitivity and specificity in detecting fibrogenesis, for example, in rodent models and human fibrotic tissues.

Abstract: An augmented reality implementing method applied to a server, which includes a plurality of augmented reality objects and a plurality of setting records corresponding to the augmented reality objects respectively is provided. Firstly, the server receives an augmented reality request from a mobile device, where the augmented reality request is related to a target device. Then, the server is communicated with the target device to access current information. Then, the server determines the current information corresponds to which one of the setting records, and selects one of the augmented reality objects based on the determined setting record as a virtual object provided to the mobile device.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. However, artificial intelligence is very computationally intensive field. Fortunately, many of the required calculations can be performed in parallel such that specialized processors can greatly increase computation performance. In particular, Graphics Processor Units (GPUs) are often used in artificial intelligence. Although GPUs have helped, they are not ideal for artificial intelligence. Specifically, GPUs are used to compute matrix operations in one direction with a pipelined architecture. However, artificial intelligence is a field that uses both forward propagation computations and back propagation calculations. To efficiently perform artificial intelligence calculations, a symmetric matrix processing element is introduced. The symmetric matrix processing element can perform forward propagation and backward propagation calculations just as easily.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. One of the most important applications for artificial intelligence is object recognition and classification from digital images. Convolutional neural networks have proven to be a very effective tool for object recognition and classification from digital images. However, convolutional neural networks are extremely computationally intensive thus requiring high-performance processors, significant computation time, and significant energy consumption. To reduce the computation time and energy consumption a “cone of dependency” and “cone of influence” processing techniques are disclosed. These two techniques arrange the computations required in a manner that minimizes memory accesses such that computations may be performed in local cache memory. These techniques significantly reduce the time to perform the computations and the energy consumed by the hardware implementing a convolutional neural network.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. However, artificial intelligence is very computationally intensive field. Fortunately, many of the required calculations can be performed in parallel such that specialized processors can greatly increase computation performance. In particular, Graphics Processor Units (GPUs) are often used in artificial intelligence. Although GPUs have helped, they are not ideal for artificial intelligence. Specifically, GPUs are used to compute matrix operations in one direction with a pipelined architecture. However, artificial intelligence is a field that uses both forward propagation computations and back propagation calculations. To efficiently perform artificial intelligence calculations, a symmetric matrix processing element is introduced. The symmetric matrix processing element can perform forward propagation and backward propagation calculations just as easily.

Abstract: Artificial intelligence is an increasingly important sector of the computer industry. However, artificial intelligence is extremely computationally intensive field such that it can be expensive, time consuming, and energy consuming field. Fortunately, many of the calculations required for artificial intelligence can be performed in parallel such that specialized processors can great increase computational performance for AI applications. Specifically, artificial intelligence generally requires large numbers of matrix operations such that specialized matrix processor circuits can greatly improve performance. To efficiently execute all these matrix operations, the matrix processor circuits must be quickly and efficiently supplied with a stream of data and instructions to process or else the matrix processor circuits end up idle. Thus, this document discloses packet architecture for efficiently creating and supplying neural network processors with work packets to process.

Abstract: A face model building method is provided. The face model building method includes: obtaining a plurality of facial feature animation objects and a plurality of object parameters respectively corresponding to the facial feature animation objects, where the facial feature animation objects include a plurality of two-dimensional facial feature animation objects and at least one three-dimensional facial feature animation object; and integrating the facial feature animation objects according to the object parameters to generate a three-dimensional face model. A face model building system is further provided.

Abstract: A face model editing method adapted to a face model editing system having a modeling platform and an editing platform is provided. The modeling platform has a plurality of face feature animation objects and a plurality of object parameters thereof. The face model editing method includes: receiving an object selection instruction by using the editing platform, and accessing the object parameter of the face feature animation object from the modeling platform according to the object selection instruction; receiving an adjusting instruction by using the editing platform, and adjusting the accessed object parameter; transmitting, by the editing platform, the adjusted object parameter to the modeling platform to update the object parameters; and generating, by the modeling platform, a three-dimensional face model by using the updated object parameters in combination with the face feature animation objects, and transmitting the three-dimensional face model to the editing platform for demonstration.

Abstract: Ethylcellulose dispersions in water are film forming compositions that have found use in personal care applications. Conventional methods can require that aqueous dispersions of water-insoluble polymers such as ethylcellulose be obtained using surfactants such as sodium lauryl sulfate (SLS). There is a desire to reduce the degree of consumer exposure to SLS in personal care products. The present invention describes ethylcellulose dispersions comprising surfactants to substantially replace sodium lauryl sulfate. The present invention also describes methods of reducing or substantially eliminating SLS in personal care products that comprise ethylcellulose dispersions.

Abstract: An augmented reality implementing method applied to a server, which includes a plurality of augmented reality objects and a plurality of setting records corresponding to the augmented reality objects respectively is provided. Firstly, the server receives an augmented reality request from a mobile device, where the augmented reality request is related to a target device. Then, the server is communicated with the target device to access current information. Then, the server determines the current information corresponds to which one of the setting records, and selects one of the augmented reality objects based on the determined setting record as a virtual object provided to the mobile device.

Abstract: Methods and systems are provided for dynamically visualizing an object of interest that includes part of the vasculature of a patient, which employ a 3D model of the object to generate at least one roadmap that includes information that characterizes properties of the object (such as centerlines, contours, and an image mask. Reference location(s) corresponding to the roadmap(s) are determined for an interventional device used to treat the object. In an online phase, non-contrast-enhanced x-ray image data of the object are obtained and processed to determine location of the interventional device in the image data, and a particular roadmap is selected or accessed. The reference location corresponding to the particular roadmap and the determined location of interventional device are used to transform the particular roadmap. A visual representation of the transformed roadmap is overlaid on the image data for display.

Abstract: Some embodiments of the present disclosure relate to methods, devices and computer-readable media for measuring traffic hit time during path switch. The method performed at a first device includes: sending, to a second device, operation administration and maintenance (OAM) frames with continuous sequence numbers; receiving from the second device response OAM frames; determining traffic hit start time and traffic hit stop time based on the received OAM frames; detecting an occurrence of the path switch, and determining that the path switch is completed before the traffic hit stop time; and in response to determining that the path switch is completed before the traffic hit stop time, calculating traffic hit time based at least on the traffic hit start time and the traffic hit stop time.