Abstract: Client data corresponding to a single client can be stored. A decision to proceed with a defragmentation of two or more particular core groups can be determined. A destination core group to receive client data can be identified. At least one additional core group can be initiated to manage interim data write requests from the single client. Each of the two or more particular core groups can be closed to data write requests. A defragmentation of the two or more particular core groups can be performed by merging into the destination core group. The destination core group can be availed to data read and delete requests. The two or more fragmented core groups can be reallocated for other uses. The additional core groups continue to receive read and write requests. The destination core groups further can be merged and defragmented further.

Abstract: Presented are systems and methods for uplink frequency selective precoding. A wireless communication device may receive a first signaling from the wireless communication node. The first signaling may include a plurality of precoding information associated with a plurality of port groups. The wireless communication device may determine signals precoded according to the plurality of precoding information. The wireless communication device may transmit the signals to the wireless communication node.

Abstract: A wireless communication method includes receiving, by a wireless communication device from a network, at least one port parameter, determining, by the wireless communication device, at least one uplink codebook parameter, and determining, by the wireless communication device, a precoder for an uplink transmission based on the at least one uplink codebook parameter and the at least one port parameter.

Abstract: The invention discloses a high impermeability and low thermal conductivity inorganic lightweight foam concrete and its preparation method, including the following mass fraction of raw materials: 1260˜1540 parts of ordinary silicate cement, 20˜60 parts of nano-silica, 460˜740 parts of fly ash, 360˜440 parts of aggregate, 9˜11 parts of redispersible latex powder, 7.2˜8.8 parts of polypropylene fiber, 27˜33 parts of quick-setting agent, 500 parts of fluorine-free foam, 900˜1100 parts of water. 33 parts, 500 parts of fluorine-free foam, 900˜1100 parts of water. The high impermeability and low thermal conductivity inorganic lightweight foam concrete prepared by the present invention has a simple formulation, good workability, light weight and low thermal conductivity, and is suitable for the construction of thermal insulation system for building exterior walls.

Abstract: A method for contrastive learning by selecting dropout ratios and locations based on reinforcement learning includes receiving training data having a positive sample corresponding to a target and negative samples not corresponding to the target. A dropout policy for a neural network is produced based on the training data, where the dropout policy identifies at least one connection between neurons in the neural network to dropout. The training data is encoded, based on the dropout policy, to form embeddings, where the embeddings include multiple positive sample embeddings corresponding to the positive sample and multiple negative sample embedding corresponding to the negative samples.

Abstract: Disclosed are methods, systems, apparatuses, and computer readable media for generating a wireless device report for assisting a network node with frequency domain and time domain synchronization. In one aspect, a method of wireless communication is disclosed. The method includes receiving, at a wireless device, a report configuration associated with a reference signal (RS). The method further includes determining, at the wireless device, channel state information (CSI), wherein the CSI comprises at least one of an RS indicator, a rank indicator (RI), a precoding matrix indicator (PMI), Doppler information, or a channel quality index (CQI), according to the report configuration. The method includes reporting, at a wireless device, the channel state information (CSI).

Abstract: A computer-implemented method, system and computer program product for detecting Unicode injection in text. A language model is trained to determine if text data (e.g., text fragment) conforms with human writing habits using negative and positive samples. Negative samples include samples of text that are not classified as being suspect for containing Unicode characters. Such negative samples include text written by humans. Positive samples include samples of text that are to be classified as being suspect for containing Unicode characters. Such positive samples may be formed by randomly inserting Unicode characters into the corpus of negative samples. After training the language model, the language model is able to determine whether the received text data (e.g., text fragment) is suspect for containing Unicode characters based on whether the text data conforms with human writing habits.

Abstract: A system, method, and computer program product for implementing cognitive natural language processing software framework optimization is provided. The method includes receiving instructions associated with an audible user input of a user. An AI input intention of the user is determined and key information is extracted from the audible user input. The key information is inputted into a generated database table and additional key information is retrieved from a dialog table. A supplementary database table comprising the additional key information is generated and the key information is spliced with the additional key information. A resulting spliced data structure is merged into a final database table and natural language is converted into a request code structure within an SQL structure and an interactive AI interface presenting results of the converting is generated. Operational functionality of an AI device is enabled for audibly presenting results of the conversion.

Abstract: Client data corresponding to a single client can be stored. A decision to proceed with a defragmentation of two or more particular core groups can be determined. A destination core group to receive client data can be identified. At least one additional core group can be initiated to manage interim data write requests from the single client. Each of the two or more particular core groups can be closed to data write requests. A defragmentation of the two or more particular core groups can be performed by merging into the destination core group. The destination core group can be availed to data read and delete requests. The two or more fragmented core groups can be reallocated for other uses. The additional core groups continue to receive read and write requests. The destination core groups further can be merged and defragmented further.

Abstract: A computer-implemented process for modifying a training dataset includes the following operations. The training dataset is benchmarked using a State Of The Art (SOTA) neural network to determine a benchmark for the training dataset. The training set is divided into a plurality of slices. A sequence of a plurality of atomic operations are selected using a selection strategy generator operating on one of the plurality of slices. The sequence of the plurality of atomic operations is applied to modify the one of the plurality of slices to generate a revised one of the plurality of slices. Reverse reinforcement learning is performed on the revised one of the plurality of slices using the benchmark and the SOTA neural network. The training dataset is modified by replacing the one of the plurality of slices with the revised one of the plurality of slices to generate a modified training dataset.

Abstract: Disclosed are techniques for modifying deep learning models (such as neural networks) to run more efficiently in computing environments with limited floating point computation resources. A deep learning model is trained using a set of training data. Input and output values are then recorded from the layers of the trained model when supplied with the training data, which are then used to generate deep forest decision tree models corresponding to individual layers of the trained model. Experimental versions of the trained model are then generated with different layers of the trained model replaced with their corresponding deep forest decision tree models. These experimental versions are then ranked according to the accuracy of their results compared to the results of the trained model. An updated trained model is then generated with one or more layers replaced with their corresponding deep forest decision tree models.

Abstract: Provided is an application method of a Micro Electro Mechanical Systems (MEMS) inertial sensor and an electronic device. An application method of an accelerometer includes: based on an influence of a strain, generated under the action of an external force, of the accelerometer on a detection signal of the accelerometer, adopting the detection signal to reflect the external force. An application method of a gyroscope includes: based on an influence of a strain, generated under the action of an external force, of the gyroscope on a detection signal of the gyroscope, adopting the detection signal to reflect the external force. Further provided is an electronic device adopting the foregoing methods.

Abstract: An example operation may include one or more of executing a machine learning model on training data, where the training data comprises a plurality of word strings, identifying words within the training data that are extracted by the machine learning model during the executing, determining a color for the machine learning model based on the identified words and a predefined mapping of words to colors, and rendering, via a user interface, a label associated with the machine learning model in the determined color for the machine learning model.

Abstract: A hydraulic composite bushing includes: a core shaft, with a continuously spiral fluid channel groove; a rubber member, arranged around the core shaft, and having two recesses formed radially outside of the fluid channel groove and radially opposite to each other; a support ring arranged around the rubber member; an outer cover pressing on the support ring from a radially outer side thereof; and a sealing device provided at each end of a fluid channel tube arranged within the fluid channel groove. Two ends of the fluid channel tube pass through the rubber member radially to extend into two hydraulic chambers respectively, with the hydraulic chambers in communication with each other through the fluid channel tube. One end of the sealing device is arranged inside the flow channel groove and the other end thereof passes through the rubber member to extend into the hydraulic chambers.

Abstract: A hydraulic composite bushing, a flow channel for same, and a method for forming the flow channel, wherein the hydraulic composite bushing includes: a core shaft; a rubber member, arranged on an outer peripheral surface of the core shaft and provided with two recesses diametrically opposite to each other; two support rings arranged around the rubber member; and an outer casing press-fitted on the support rings from a radially outer side thereof through interference fit. The outer casing covers the recesses to form two hydraulic chambers for accommodating hydraulic fluid between the rubber member and the outer casing, and the support ring is provided with a flow channel for the hydraulic fluid, so that two hydraulic chambers are in communication with each other via the flow channel. A sealing device is provided at a connection between the outer casing and each of the recesses to seal each hydraulic chamber.

Abstract: In an approach for road section recognition using multi-modal cognitive mechanism, a processor receives an audio signal from a road test. A processor processes the audio signal to generate an acoustic spectrum density distribution map to identify a respective at least one road section switching point in a first mode. A processor processes a spectrogram of the audio signal to identify the respective at least one road section switching point in a second mode. A processor uses a machine learning model to predict an expected sound at each frame of the audio signal, to calculate a similarity between the expected sound and an actual sound, and to identify the respective at least one road switching point when the similarity is lower than a pre-set similarity threshold in a third mode. A processor combines results of the three modes to obtain a final set of road section switching points.

Abstract: A three-axis microelectromechanical system (MEMS) gyroscope includes four proof masses, where the proof masses are connected by spring beams and/or rigid beams; a first proof mass is configured to move in an X-axis direction; a second proof mass is configured to rotate around an X-direction axis, a Y-direction axis, and a Z-direction axis, and when the first proof mass moves in the X-axis direction, the second proof mass is driven to rotate around the Z-direction axis; a third proof mass is configured to move in the X-axis direction and a Y-axis direction, and when the first proof mass moves in the X-axis direction, the third proof mass is driven to move in the Y-axis direction; a fourth proof mass is configured to move in the X-axis direction, and when the third proof mass moves in the X-axis direction, the fourth proof mass is driven to move in the X-axis direction.

Abstract: Embodiments of the present disclosure relate to question answering. A computer-implemented method includes determining a plurality of intention candidates of a user from the user's question; determining a set of entities and attributes associated with the set of entities from the plurality of intention candidates; constructing a decision tree from the set of entities and the attributes associated with the set of entities, wherein each node of the decision tree is associated with a respective one of the attributes and represents a respective subset of the plurality of intention candidates, and wherein the respective subset of the plurality of intention candidates are split based on the entities associated with the respective one of the attributes; and generating a question corresponding to a node of the decision tree to determine the user's intention.

Abstract: A headphone and an electronic device are provided. The headphone includes a gyroscope, which senses a bone conduction vibration and provides a quadrature error signal for reflecting the bone conduction vibration. Specifically, the headphone includes a transmission assembly that acts directly or indirectly on the gyroscope or an inertial measurement unit (IMU) including the gyroscope. The transmission assembly transmits the bone conduction vibration to the gyroscope to make the gyroscope strain, thereby causing the quadrature error signal of the gyroscope to change to detect the bone conduction vibration with sensitivity.

Abstract: A headphone and an electronic device are provided. The headphone includes a gyroscope, which senses a bone conduction vibration and provides a quadrature error signal for reflecting the bone conduction vibration. Specifically, the headphone includes a transmission assembly that acts directly or indirectly on the gyroscope or an inertial measurement unit (IMU) including the gyroscope. The transmission assembly transmits the bone conduction vibration to the gyroscope to make the gyroscope strain, thereby causing the quadrature error signal of the gyroscope to change to detect the bone conduction vibration with sensitivity.