Abstract: A resource management method, a resource management system, and a workload scheduling apparatus for network slicing are provided. In the method resource management, a service request related to an application type of a terminal device is received. A monitoring report of the terminal device is obtained according to the service request. The monitoring result relates to a condition of the radio resource used by the terminal device. A usage situation of a slicing resource is analyzed based on the slicing resource requested by the service request and the monitoring report to predict a predicted arrangement result of the slicing resource. The slicing resource requested by the service result is arranged according to the predicted arrangement result to transmit a corresponding setting configuration to the radio access network. The setting configuration serves to adjust the slicing resource. Accordingly, the request of the service and the current condition are fulfilled.

Abstract: A resource management method, a resource management system, and a workload scheduling apparatus for network slicing are provided. In the method resource management, a service request related to an application type of a terminal device is received. A monitoring report of the terminal device is obtained according to the service request. The monitoring result relates to a condition of the radio resource used by the terminal device. A usage situation of a slicing resource is analyzed based on the slicing resource requested by the service request and the monitoring report to predict a predicted arrangement result of the slicing resource. The slicing resource requested by the service result is arranged according to the predicted arrangement result to transmit a corresponding setting configuration to the radio access network. The setting configuration serves to adjust the slicing resource. Accordingly, the request of the service and the current condition are fulfilled.

Abstract: A system and method relate to providing machine learning predictions with defenses against patch attacks. The system and method include obtaining a digital image and generating a set of location data via a random process. The set of location data include randomly selected locations on the digital image that provide feasible bases for creating regions for cropping. A set of random crops is generated based on the set of location data. Each crop includes a different region of the digital image as defined in relation to its corresponding location data. The machine learning system is configured to provide a prediction for each crop of the set of random crops and output a set of predictions. The set of predictions is evaluated collectively to determine a majority prediction from among the set of predictions. An output label is generated for the digital image based on the majority prediction. The output label includes the majority prediction as an identifier for the digital image.

Abstract: A computer-implemented method for training a machine-learning network. The machine-learning network method includes receiving an input data from a sensor, wherein the input data includes paired cleaned-perturbed data, wherein the input data is indicative of image, radar, sonar, or sound information, generate a perturbed version of the input data, utilizing a generator, in response to the input data, create a paired training data set utilizing an data from the input data and a perturbed image utilizing the perturbed version of the input data, jointly training the generator and a classifier in response to the paired training data set, determining a latent vector utilized to generate perturbation configured to maximize classification loss of a classifier and minimize generation loss of the generator, and outputting a trained generator and a trained classifier upon convergence to a first threshold.

Abstract: A computer-implemented method for training a machine learning network. The method may include receiving an input data, selecting one or more batch samples from the input data, applying a perturbation object onto the one or more batch samples to create a perturbed sample, running the perturbed sample through the machine learning network, updating the perturbation object in response to the function in response to running the perturbed sample, and outputting the perturbation object in response to exceeding a convergence threshold.

Abstract: A method of road sign classification utilizing a knowledge graph, including detecting and selecting a representation of a sign across a plurality of frames, outputting a prompt initiating a request for a classification associated with the representation of the sign, classifying one or more images including the sign, querying the knowledge graph to obtain a plurality of road sign classes with at least one same attribute as the sign, and classifying the sign across the plurality of frames in response to a confidence level exceeding a threshold.

Abstract: A computer-implemented method for training a neural network, comprising receiving an input data, defining a perturbed version of the input data in response to a dimensional latent vector and the input data, training a variational auto encoder (VAE) utilizing the perturbed version of the input data, wherein the VAE outputs, utilizing an encoder, a latent vector in response to the input data and the perturbed version of the input data, decoding the latent vector, utilizing a decoder of the VAE, back to an input latent space to output a perturbed example, and outputting a learned perturbed set utilizing one or more perturbed examples and upon convergence to a first threshold.

Abstract: A method for dynamically adjusting a broadcast area is provided. The method includes the following steps. Information of at least one target base station which subscribes a broadcast service is obtained. A broadcast service base station list corresponding to a broadcast area identification code is set to contain the at least one target base station. The broadcast area identification code corresponds to the broadcast service. A command for adding a new broadcast area identification code is selectively transmitted to the at least one target base station in the broadcast service base station list so that the at least one target base station records the broadcast area identification code to receive the broadcast service corresponding to the broadcast area identification code.

Abstract: The present disclosure provides a method of maintaining the continuity of a transmission service and a service center. The method includes: receiving a consumption report from a user equipment, wherein the user equipment receives a first transmission service through a first bearer; in response to receiving a specific request, obtaining user identification information of the user equipment from the specific request; accessing the consumption report corresponding to the user equipment based on the user identification information, and obtaining first service information of the first transmission service from the consumption report; and controlling the user equipment to switch to use a second bearer to receive a second transmission service according to the first service information, wherein the first bearer is one of a unicast bearer and a broadcast bearer, and the second bearer is another of the unicast bearer and the broadcast bearer.

Abstract: A storage maintains raw image data including video having a sequence of frames, and annotations of the frames that indicate aspects of objects identified in the respective frames. A processor determines, for annotation of key frames of the raw image data, a task type for key frames and an agent type for key frames, receives annotations of objects identified in the key frames of the raw image data according to the key frame task type and key frame agent type, selects to review the key frames based on a confidence level of the annotations of the key frames, determines, for annotation of intermediate frames of the raw image data, a task type for intermediate frames and an agent type for intermediate frames, and receives annotations of objects identified in the intermediate frames of the raw image data according to the intermediate frame task type and intermediate frame agent type.

Abstract: A data annotation system for a machine-learning system includes a computing system configured to execute a machine-learning algorithm for generating data annotations of input data. The computing system is further configured to execute an interface for communicating results and predictions of the machine-learning algorithm to non-expert workers for review. The interface communicates with the non-expert worker using visualization and natural language to elicit feedback to improve performance of the machine-learning algorithm.

Abstract: A decision-support system for a public transportation system includes a computing system programmed to generate public transit route options for the commuter based on at least one decision factor that estimates an expected impact on other commuters resulting from the commuter choosing each of the public transit route options, and output, for display, values associated with the at least one decision factor to influence the commuter in making a route selection.

Abstract: A method for dynamically adjusting a broadcast area is provided. The method includes the following steps. Information of at least one target base station which subscribes a broadcast service is obtained. A broadcast service base station list corresponding to a broadcast area identification code is set to contain the at least one target base station. The broadcast area identification code corresponds to the broadcast service. A command for adding a new broadcast area identification code is selectively transmitted to the at least one target base station in the broadcast service base station list so that the at least one target base station records the broadcast area identification code to receive the broadcast service corresponding to the broadcast area identification code.

Abstract: The present disclosure provides a method of maintaining the continuity of a transmission service and a service center. The method includes: receiving a consumption report from a user equipment, wherein the user equipment receives a first transmission service through a first bearer; in response to receiving a specific request, obtaining user identification information of the user equipment from the specific request; accessing the consumption report corresponding to the user equipment based on the user identification information, and obtaining first service information of the first transmission service from the consumption report; and controlling the user equipment to switch to use a second bearer to receive a second transmission service according to the first service information, wherein the first bearer is one of a unicast bearer and a broadcast bearer, and the second bearer is another of the unicast bearer and the broadcast bearer.

Abstract: A system for training a machine learning model using a batch based active learning approach. The system includes an information source and an electronic processor. The electronic processor is configured to receive a machine learning model to train, an unlabeled training data set, a labeled training data set, and an identifier of the information source. The electronic processor is also configured to select a batch of training examples from the unlabeled training data set and send, to the information source, a request for, for each training example included in the batch, a label for the training example. The electronic processor is further configured to, for each training example included in the batch, receive a label, associate the training example with the label, and add the training example to the labeled training data set. The electronic processor is also configured to train the machine learning model using the labeled training data.

Abstract: A storage maintains raw image data including video having a sequence of frames, and annotations of the frames that indicate aspects of objects identified in the respective frames. A processor determines, for annotation of key frames of the raw image data, a task type for key frames and an agent type for key frames, receives annotations of objects identified in the key frames of the raw image data according to the key frame task type and key frame agent type, selects to review the key frames based on a confidence level of the annotations of the key frames, determines, for annotation of intermediate frames of the raw image data, a task type for intermediate frames and an agent type for intermediate frames, and receives annotations of objects identified in the intermediate frames of the raw image data according to the intermediate frame task type and intermediate frame agent type.

Abstract: A data annotation system for a machine-learning system includes a computing system configured to execute a machine-learning algorithm for generating data annotations of input data. The computing system is further configured to execute an interface for communicating results and predictions of the machine-learning algorithm to non-expert workers for review. The interface communicates with the non-expert worker using visualization and natural language to elicit feedback to improve performance of the machine-learning algorithm.

Abstract: An information synthesis system for generating a knowledge base injects domain knowledge into semi-crowdsourced summarization pipelines for extracting information from unstructured data sources. The summarization pipeline includes chains of tasks completed by crowd workers and/or machined. The information synthesis system distributes the tasks to crowd workers and/or machines. Task responses are processed and aggregated to determine new information that is used to update the knowledge base.

Abstract: A decision-support system for a public transportation system includes a computing system programmed to generate public transit route options for the commuter based on at least one decision factor that estimates an expected impact on other commuters resulting from the commuter choosing each of the public transit route options, and output, for display, values associated with the at least one decision factor to influence the commuter in making a route selection.

Abstract: A method includes analyzing a preview image made by an image sensor when operating in a preview image mode to determine if the preview image contains some portion that corresponds to information that is considered not subject to being imaged. The method further includes, if it is determined that the preview image does comprise some image portion that corresponds to information that is considered not subject to being imaged, disabling the image sensor from capturing an image that would correspond to the preview image. Analyzing can include accessing a data storage that contains representations of information that is considered not subject to being imaged for comparison with image features extracted from the preview image, where the data storage is at least one of contained in a device that also contains the image sensor, or is located remotely from the device and can be accessed via a wireless connection.