Abstract: The present application relates to a current collector, an electrode plate, a battery cell, a battery, and an electric device. The current collector includes a stainless steel current-collecting portion for collecting a current, where the stainless steel current-collecting portion includes a blank area and a coating area that are arranged adjacent to each other in a preset direction, the coating area is configured to be coated with an active material, and the blank area has a hardness less than that of the coating area.

Abstract: A storage management apparatus, a storage management method, a processor, and a computer system are disclosed. The storage management apparatus includes a translation look-aside buffer, configured to store a plurality of cache entries, wherein the plurality of cache entries comprises a first plurality of level 1 cache entries and a second plurality of level 2 cache entries, wherein the first plurality of level 1 cache entries is less than or equal to the second plurality of level 2 cache entries, and each of the first plurality of level 1 cache entries is different from each of the second plurality of level 2 cache entries; and an address translation unit adapted to translate, based on at least one of the first plurality of level 1 cache entries and the second plurality of level 2 cache entries, a virtual address specified by a translation request into a corresponding translated address.

Abstract: A system and method for multimodal video segmentation in a multi-speaker scenario are provided. A transcript of a video with a plurality of speakers is segmented into a plurality of sentences. Speaker change information is detected between each two adjacent sentences of the plurality of sentences based on at least one of audio content or visual content of the video. The video is segmented into a plurality of video clips based on the transcript of the video and the speaker change information.

Abstract: A field-programmable analog array (FPAA) fabric includes a 6×6 matrix of configurable analog blocks (CABs). The implementation of programmable CABs eliminates the use of fixed analog subcircuits. A unique routing strategy is developed within the CAB units that supports both differential and single-ended mode circuit configurations. The bandwidth limitation due to the routing switches of each individual CAB unit is compensated for through the use of a switch-less routing network between CABs. Algorithms and methodologies facilitate rapid implementation of analog circuits on the FPAA. The proposed FPAA fabric provides high operating speeds as compared to existing FPAA topologies, while providing greater configuration in the CAB units as compared to switch-less FPAA. The FPAA core includes 498 programming switches and 14 global switchless interconnects, while occupying an area of 0.1 mm2 in a 65 nm CMOS process.

Abstract: In this paper, a novel field-programmable analog array (FPAA) is proposed to secure the intellectual property (IP) of analog and mixed-signal circuits. A obfuscation technique is developed to efficiently mask the topology of both differential mode and single-ended mode analog circuits.

Abstract: A method operating a Graphics Processing Unit (GPU) memory can be provided by accessing specified training parameters used to train a Deep Neural Network (DNN) using a GPU with a local GPU memory, the specified training parameters including at least a specified batch size of samples configured to train the DNN. A sub-batch size of the samples can be defined that is less than or equal to the specified batch size of samples in response to determining that an available size of the local GPU memory is insufficient to store all data associated with training the DNN using one batch of the samples. Instructions configured to train the DNN using the sub-batch size can be defined so that an accuracy of the DNN trained using the sub-batch size is about equal to an accuracy of the DNN trained using the specified batch size of the samples.

Abstract: An English pronunciation assessment method includes: receiving an audio file including an English speech and a text transcript corresponding to the English speech; inputting audio signal to one or more acoustic models to obtain phonetic information of each phone in each word, wherein the one or more acoustic models are trained with speeches spoken by native speakers and further with speeches spoken by non-native speakers without labeling out mispronunciations, such that a pronunciation error is detected more accurately based on the obtained phonetic information; extracting time series features of each word; inputting the extracted time series features of each word, the obtained phonetic information of each phone in each word, and the audio signal included in the audio file to a lexical stress model to obtain misplaced lexical stress in each of words in the English speech with different number of syllables without expanding short words to cause input approximation.

Abstract: The invention discloses an OCT probe used for human open lumen system, comprising a probe protector, a probe body, an oily liquid, a metal coil, a probe guard tip and a light-guided optical fiber; the probe body is match mounted will the metal coil, and the metal coil is mounted on the rear end of the probe body; the light-guided optical fiber is fixed inside the probe body; the probe guard tip is sleeved on the probe body, the probe protector is sleeved on the probe guard tip and sleeved on the metal coil; the oily liquid is filled between the probe guard tip and the probe protector, and between the metal coil and the probe protector. The invention effectively remedy for the defect that the image is unclear by filling the oily liquid between the probe protector and the probe body.

Abstract: Optimizations are provided for segmenting tissue objects included in an ultrasound image. Initially, raw pixel data is received. Here, each pixel corresponds to ultrasound information. This raw pixel data is processed through a first fully convolutional network to generate a first segmentation label map. This first map includes a first set of objects that have been segmented into a coarse segmentation class. Then, this first map is processed through a second fully convolutional network to generate a second segmentation label map. This second map is processed using the raw pixel data as a base reference. Further, this second map includes a second set of objects that have been segmented into a fine segmentation class. Then, a contour optimization algorithm is applied to at least one of the second set of objects in order to refine that object's contour boundary. Subsequently, that object is identified as corresponding to a lymph node.

Abstract: A method operating a Graphics Processing Unit (GPU) memory can be provided by accessing specified training parameters used to train a Deep Neural Network (DNN) using a GPU with a local GPU memory, the specified training parameters including at least a specified batch size of samples configured to train the DNN. A sub-batch size of the samples can be defined that is less than or equal to the specified batch size of samples in response to determining that an available size of the local GPU memory is insufficient to store all data associated with training the DNN using one batch of the samples. Instructions configured to train the DNN using the sub-batch size can be defined so that an accuracy of the DNN trained using the sub-batch size is about equal to an accuracy of the DNN trained using the specified batch size of the samples.

Abstract: Optimizations are provided for segmenting tissue objects included in an ultrasound image. Initially, raw pixel data is received. Here, each pixel corresponds to ultrasound information. This raw pixel data is processed through a first fully convolutional network to generate a first segmentation label map. This first map includes a first set of objects that have been segmented into a coarse segmentation class. Then, this first map is processed through a second fully convolutional network to generate a second segmentation label map. This second map is processed using the raw pixel data as a base reference. Further, this second map includes a second set of objects that have been segmented into a fine segmentation class. Then, a contour optimization algorithm is applied to at least one of the second set of objects in order to refine that object's contour boundary. Subsequently, that object is identified as corresponding to a lymph node.

Abstract: The invention discloses an OCT probe used for human open lumen system, comprising a probe protector, a probe body, an oily liquid, a metal coil, a probe guard tip and a light-guided optical fiber; the probe body is match mounted will the metal coil, and the metal coil is mounted on the rear end of the probe body; the light-guided optical fiber is fixed inside the probe body; the probe guard tip is sleeved on the probe body, the probe protector is sleeved on the probe guard tip and sleeved on the metal coil; the oily liquid is filled between the probe guard tip and the probe protector, and between the metal coil and the probe protector. The invention effectively remedy for the defect that the image is unclear by filling the oily liquid between the probe protector and the probe body.

Abstract: Systems and methods are provided for identifying markers for inflammation in a tissue image. The tissue image is captured as an image of a histology slide. Subcellular structures in the tissue image are segmented via a first automated process to identify at least one variety of immune cells within the image. Glands and vilii are identified within the tissue image via a second automated process. Neutrophils are identified within the tissue image via a third automated process. An output representing the identified glands, villi, neutrophils, and other immune cells is provided to a human operator.

Abstract: Systems and methods are provided for identifying markers for inflammation in a tissue image. The tissue image is captured as an image of a histology slide. Subcellular structures in the tissue image are segmented via a first automated process to identify at least one variety of immune cells within the image. Glands and vilii are identified within the tissue image via a second automated process. Neutrophils are identified within the tissue image via a third automated process. An output representing the identified glands, villi, neutrophils, and other immune cells is provided to a human operator.

Abstract: Disclosed is an example method to calculate radiation dose. The method includes receiving a tissue matrix in which the tissue matrix includes a plurality of voxels. The example method also includes producing a first plurality of transport lines with a direction controller in which each transport line is indicative of a cone of irradiated energy, and calculating at least one radiation dose with at least one deposit engine substantially in parallel with producing a second plurality of transport lines with the direction controller.

Abstract: Disclosed is an example method to calculate radiation dose. The method includes receiving a tissue matrix in which the tissue matrix includes a plurality of voxels. The example method also includes producing a first plurality of transport lines with a direction controller in which each transport line is indicative of a cone of irradiated energy, and calculating at least one radiation dose with at least one deposit engine substantially in parallel with producing a second plurality of transport lines with the direction controller.