Abstract: An apparatus for wireless communication includes a receiver configured to receive a request for data associated with an Internet-of-things (IoT) service session with an IoT cloud server. The apparatus further includes a transmitter configured to transmit, based on receiving the request and prior to transmitting a response to the request, a message indicating a timing parameter associated with availability of the data. The receiver is further configured to receive an uplink grant at a time that is based on the timing parameter, and the transmitter is further configured to transmit the response to the request based on the uplink grant. The response includes at least a subset of the data.

Abstract: The disclosed technology generally relates to quartz crystal devices and more particularly to quartz crystal devices configured to vibrate in torsional mode. In one aspect, a quartz crystal device configured for temperature sensing comprises a fork-shaped quartz crystal comprising a pair of elongate tines laterally extending from a base region in a horizontal lengthwise direction of the fork-shaped quartz crystal, wherein each of the tines has formed on one or both of opposing sides thereof a pair of vertically recessed groove structures laterally elongated in the horizontal lengthwise direction, wherein the pair of groove structures are separated in a horizontal widthwise direction by a line structure.

Abstract: Certain aspects of the present disclosure provide techniques for committing log data in an application to a log data repository. An example method generally includes receiving, from an application, data to be committed to a remote storage location. A type of the received data is determined. The type of the received data is generally associated with a prioritization level and a compression mechanism to be used in committing the data to the remote storage location. An application execution context associated with the received data is determined. At a dispatch time associated with the prioritization level of the received data and the application execution context associated with the received data, a compressed data payload is generated and transmitted to the remote storage location. Generally, to compress the data payload, at least the received data is generally compressed based on the determined compression mechanism.

Abstract: Method for source localization for cable cut prevention using distributed fiber optic sensing (DFOS)/distributed acoustic sensing (DAS) is described that is robust/immune to underground propagation speed uncertainty. The method estimates the location of a vibration source while considering any uncertainty of vibration propagation speed and formulates the localization as an optimization problem, and both location of the sources and the propagation speed are treated as unknown. This advantageously enables our method to adapt to variances of the velocity and produce a better generalized performance with respect to environmental changes experienced in the field. Our method operates using a DFOS system and AI techniques as an integrated solution for vibration source localization along an entire optical sensor fiber cable route and process real-time DFOS data and extract features that are related to a location of a source of vibrations that may threaten optical fiber facilities.

Abstract: An anti-BCMA antibody or an antigen-binding fragment thereof, and an application thereof in the treatment or prevention of tumor.

Abstract: A system and method for authentication code generation based on adversarial machine learning are provided in this disclosure. The method includes a defensive authentication code generation system, an authentication code formation module, an authentication code scheduling module, an authentication-code adversarial processing center, an attack sample generation module, a verification and error reporting system, a division module, a grouping and distribution system, a category checking module, a data recording unit, a detection module and an integration terminal. In the system and method for authentication code generation based on adversarial machine learning according to the disclosure, attack scenes are simulated for continuous training for the authentication code, error-reporting data are recorded and optimized into the defensive authentication code generation system, so as to improve defense performance of the authentication code.

Abstract: A fuser driving device, a fusing device and an image forming device are provided. The fuser driving device includes: a front frame and a rear frame, where the front frame and the rear frame are fixedly connected to each other; a gear, where two ends of the gear are respectively mounted to the front frame and the rear frame through a bearing; a driving arm mounted in the gear, where the driving arm is movable axially along the gear to enter into or withdraw from the fuser, and when the driving arm enters into the fuser, the driving arm is driven to rotate through the gear, to drive a fusing roller of the fuser to rotate; and a withdrawing device including a pulling member and an operating member, where one end of the pulling member is connected to the driving arm and the other end is connected to the operating member, and the pulling member is moved by operating the operating member to pull the driving arm to withdraw from the fuser into the gear.

Abstract: Disclosed is a charging station capable of realizing mutual capacity aid, which comprises a plurality of charging units, a power bus and a mutual capacity aid bus. Each charging unit is powered by the power bus, and each charging unit provides mutual aid capacity for another charging unit through the mutual capacity aid bus or receives mutual aid capacity from other charging units through the mutual capacity aid bus. The charging station can realize rapid charging of electric vehicles, and can also realize mutual capacity aid.

Abstract: The present disclosure relates to a radiation system. The system may include a treatment assembly, an imaging assembly, a first gantry, and a second gantry. The treatment assembly may include a first radiation source configured to deliver a treatment beam and have a treatment region. The first gantry may be configured to support the first radiation source. The imaging assembly may include a second radiation source and a radiation detector. The second radiation source may be configured to deliver an imaging beam and the radiation detector may be configured to detect at least a portion of the imaging beam. The imaging assembly may have an imaging region. The second gantry may be configured to support the second radiation source and the radiation detector, wherein the second radiation source is located within the second gantry. The treatment region and the imaging region at least partially overlap.

Abstract: A preparation method for a piezoelectric fiber is provided including a piezoelectric functional layer and an insulating layer coated on the piezoelectric functional layer. The piezoelectric functional layer includes a piezoelectric composite layer of a spiral winding structure, and the piezoelectric composite layer includes a first piezoelectric layer, a conductive layer and a second piezoelectric layer that are sequentially stacked. The preparation method includes taking one end of the piezoelectric composite layer as a winding axis, winding the piezoelectric composite layer in a direction perpendicular to the winding axis to form the piezoelectric functional layer, wherein turns of winding the piezoelectric composite layer are greater than 5, coating the piezoelectric functional layer with the insulating layer, and vacuum heating to consolidate, to prepare a preform rod.

Abstract: Cognitive determination of whether a message is suitable for sending over a data communications network can include extracting tokens from the message prior to transmitting the message. One or more intended recipients of the message can be determined from the tokens. A machine learning classification model corresponding to the one or more recipients of the message can be selected. The machine learning classification model can be constructed based on tokens extracted from prior messages, which are combined to create a plurality of documents for training the machine learning classification model. The one or more tokens extracted from the message can be classified using the machine learning classification model. An alert message can be generated in response to determining based on the classifying that the message is unsuited for sending.

Abstract: A method for time synchronization using distributed fiber optic sensing (DFOS) that employs several trusted time beacons that are attached to the DFOS sensing fiber which in turn is connected to the DFOS interrogator. The beacons transmit their signal via two different mediums, (1) wirelessly to sensor nodes in the coverage area, and (2) through vibrations on fiber to the DFOS/DAS system located at a trusted area such as the central office. Wireless broadcast to nearby sensors includes a timestamp and beacon ID. All the sensors in the field use one of the beacons in their vicinity (the one with the strongest signal) as their time reference and send the data back with the corresponding beacon index.

Abstract: A machine learning (ML)/artificial intelligence (AI) based distributed fiber optic sensing (DFOS) system and method providing detection and localization of gunshot events. In addition to the ML/AI DFOS, a signal processing pipeline that compresses an audible distributed acoustic sensing (DAS) waveform data into a small set of features that protects privacy of individuals while preserving the utility of acoustic events to detect the gunshot events and discriminate same from other events. A data-driven deep learning approach automatically predicts acoustic event types with higher accuracy that realized by prior art methods.

Abstract: Cognitive determination of whether a message is suitable for sending over a data communications network can include extracting tokens from the message prior to transmitting the message. One or more intended recipients of the message can be determined from the tokens. A machine learning classification model corresponding to the one or more recipients of the message can be selected. The machine learning classification model can be constructed based on tokens extracted from prior messages, which are combined to create a plurality of documents for training the machine learning classification model. The one or more tokens extracted from the message can be classified using the machine learning classification model. An alert message can be generated in response to determining based on the classifying that the message is unsuited for sending.

Abstract: Edge device task management by receiving an indicator corresponding to a first container running a task on a first edge device of a cluster of edge devices, wherein the indicator indicates an error status of the first container, and wherein task data of the task is stored in a first local storage of the first edge device, selecting a second edge device from the cluster of edge devices, wherein a second container on the second edge device is to run the task, instructing the first and second edge devices to transfer the task data from the first local storage of the first edge device to a second local storage of the second edge device, and in response to receiving a notification that indicates the task data has been transferred from the first local storage to the second local storage, sending the task to the second container.

Abstract: Methods and systems for training a neural network include generate an image of a mask. A copy of an image is generated from an original set of training data. The copy is altered to add the image of a mask to a face detected within the copy. An augmented set of training data is generated that includes the original set of training data and the altered copy. A neural network model is trained to recognize masked faces using the augmented set of training data.

Abstract: A preparation method tor a piezoelectric fiber is provided including a piezoelectric functional layer and an insulating layer coated on the piezoelectric functional layer. The piezoelectric functional layer includes a piezoelectric composite layer of a spiral winding structure, and the piezoelectric composite layer includes a first piezoelectric layer, a conductive layer and a second piezoelectric layer that are sequentially stacked. The preparation method piezoelectric composite layer in a direction perpendicular to the winding axis to form the piezoelectric functional layer, wherein turns of winding the piezoelectric composite layer are greater than 5, coating the piezoelectric functional layer with the insulating layer, and vacuum heating to consolidate, to prepare a preform rod.

Abstract: Systems, methods, and structures for colorless distributed fiber optic sensing/distributed vibration sensing (DOFS/DVS) over dense wavelength division multiplexing (DWDM) telecommunications facilities that operate over a C-band wavelength range spanning from 1525 nm to 1565 nm wherein the DOFS/DVS systems exhibit suitable reconfigurability of its wavelength to match a wavelength of a desired testing channel and may advantageously provide DOFS/DVS capabilities to existing DWDM communications infrastructure as a retrofit.

Abstract: Aspects of the present disclosure describe Rayleigh-based DTSS that utilizes few-mode fiber (FMF), which supports multiple spatial modes. For each spatial mode, a wavelength-scanning configuration gives the relative wavelength (or frequency) shift between two consecutive measurements. The temperature and strain changes can therefore be separated through different temperature/strain sensitivities of various mode-pairs. Advantageously, Rayleigh-based DTSS according to aspects of the present disclosure removes temperature-strain ambiguity, enhances measurement accuracy, reduces errors. and enables new features for multi-parameter sensing.

Abstract: Certain aspects of the present disclosure provide techniques for committing log data in an application to a log data repository. An example method generally includes receiving, from an application, data to be committed to a remote storage location. A type of the received data is determined. The type of the received data is generally associated with a prioritization level and a compression mechanism to be used in committing the data to the remote storage location. An application execution context associated with the received data is determined. At a dispatch time associated with the prioritization level of the received data and the application execution context associated with the received data, a compressed data payload is generated and transmitted to the remote storage location. Generally, to compress the data payload, at least the received data is generally compressed based on the determined compression mechanism.