42 results about "Tiered approach" patented technology

Systems and methods for allocating bandwidth in a switched digital video (SDV) system based on channel interest. In some embodiments, bandwidth is deallocated from channels and allocated to requested channels having a higher interest. Tiered approaches for allocating bandwidth are disclosed. Embodiments in which QAMs are allocated across services in a multi-service system based on interest are also disclosed. Embodiments for accommodating emergency access system (EAS) functionality in a SDV system are also disclosed.

A method of automating incoming message prioritization. The method including training a global classifier of a computer system using training data. Dynamically training a user-specific classifier of the computer system based on a plurality of feedback instances. Inferring a topic of the incoming message received by the computer system based on a topic-based user model. Computing a plurality of contextual features of the incoming message. Determining a priority classification strategy for assigning a priority level to the incoming message based on the computed contextual features of the incoming message and a weighted combination of the global classifier and the user specific classifier. Classifying the incoming message based on the priority classification strategy.

A method for delivering therapy in a medical device that includes a two-tiered approach of determining the presence of a lead-related condition, and determining, in response to a lead-related condition being present, the presence of oversensing. Deliver of therapy by the medical device is controlled in response to determining that both the lead-related condition and oversensing are present.

A hierarchical system for detecting an object with parallel architecture and a hierarchical method thereof is disclosed. The system includes at least one image-retrieving device retrieving at least an image and searching a plurality of obstacle position images in it. The image-retrieving device is electrically connected with an image-processing device to receive the obstacle position images transmitted by the image-retrieving device, uses parallel architecture classification to obtain at least one object image and a plurality of cropping frames thereof from the obstacle position images, synchronously separates the cropping frames to retrieve characteristic values of each cropping frame, uses convolutional neural network to simultaneously recognize the characteristic values of each cropping frame, and searches and outputs the correct cropping frame from the object image, thereby immediately detecting the object outside a vehicle and obtaining the cropping frame of the object to avoid detection error.

A system and method for detecting network intrusions using one or more statistical models and a generalized likelihood ratio test (GLRT) is provided. The system includes a computer system and a network intrusion detection engine executed by the computer system. To detect network intrusions, the system receives network traffic data, computes a likelihood using one or more statistical models, such as an Markov-modulated Poisson process, and processes the traffic data using a GLRT. The statistical models are used to assess the likelihood of seeing a particular pattern of network traffic. The GLRT is used to classify a particular pattern as either indicative of an attack or not indicative of an attack. The system could apply one or more types of statistical models, such as in a flexible multi-tiered approach.

An apparatus for automating a prioritization of an incoming message, including a batch learning module that generates a global classifier based on training data that is input to the batch learning module. A feedback learning module that generates a user-specific classifier based on a plurality of feedback instances. A feature extraction module that receives the incoming message and a topic-based user model, infers a topic of the incoming message based on the topic-based user model, and computes a plurality of contextual features of the incoming message. A classification module that dynamically determines a priority classification strategy for assigning a priority level to the incoming message based on the plurality of contextual features of the incoming message and a weighted combination of the global classifier and the user-specific classifier, and classifies the incoming message based on the priority classification strategy.

The invention discloses a risk stratification method for myocardial ischemia based on deterministic learning and deep learning. The method includes the steps that conventional 12-lead electrocardiogram signals are collected, based on the deterministic learning theory, neural network modeling and identification are conducted on intrinsic electrocardiodynamic characteristics of the shallow electrocardiogram signals, and the intrinsic dynamic characteristics of ECG signals are obtained; the convolutional neural network under the framework of deep learning is used for achieving the risk stratification of myocardial ischemia. The method combines the deterministic learning dynamic modeling method and the deep learning classification method for the first time, the method is applied to early riskstratification of myocardial ischemia based on the conventional 12-lead electrocardiogram signals, no additional detection equipment is needed, and the method is easy and convenient to use and easy tooperate. Through the deterministic learning method, the dynamic characteristics more sensitive to the ischemic state are extracted, the deep neural network can learn data features independently without further data characterization, and the complexity of the system is reduced.

The present invention discloses a service hierarchical method and a service hierarchical device, relating to the mobile communication field. The method comprises the steps of obtaining a first service type corresponding to a first service request initiated by a terminal user; judging a current terminal whether to exist a second service type; when the judgment result is yes, loading the first service request in a carrier wave corresponding to the first service type or the second service type according to the corresponding relationship of a preset service type and the carrier wave; and when the judgment result is no, loading the first service request in the carrier wave corresponding to the first service type. The device comprises an obtaining module, a judging module and a loading module. In the invention, the service hierarchy is carried out according to different service types, and the corresponding relationship of the service type and the carrier wave is preset, so that similar service characteristics are loaded on the same carrier wave, the service QoS requests are similar, the mutual effects between services are reduced, and the service quality is also improved.

The invention discloses a method and a system for dividing submarine soil layer by pore water pressure static cone penetration, which relates to the field of soil layer dividing. The current stratification method in the CPTU index selection has a greater subjectivity, stratification results are not very accurate. The invention comprises the following steps: acquiring original index data, data processing, dimension reduction processing and clustering; based on the K-means clustering method, the self-encoder is used to reduce the dimension of the submarine pore pressure cone penetration test indexes, remove the redundant features, optimize the weights of the features, and cluster the subsets of the features by K-means. It is found that the outline coefficients and other clustering evaluationindexes of the cluster stratification results are greatly improved. The technical scheme utilizes a self-encoder combined with K-means clustering, the accuracy of the interface of the seabed soil layer is high, and the number of soil types, and the result display can be intuitively displayed.

Systems, methods, and devices are described for supporting macrocell-to-femtocell hand-ins of active macro communications for mobile devices. An out-of-band (OOB) link is used to detect that a mobile device is in proximity of a femtocell. Having detected the mobile device in proximity to the femtocell, an OOB proximity detection is communicated to a femtocell gateway disposed in a core network in communication with the macro network to effectively pre-register the mobile device with the femto-convergence system. When the femtocell gateway receives a handover request from the macro network implicating the pre-registered mobile device, it is able to reliably determine the appropriate target femtocell to use for the hand-in according to the pre-registration, even where identification of the appropriate target femtocell would otherwise be unreliable. Some embodiments may also handling registering the mobile device after a handover request has occurred, including tiered approaches.

An automated tiering system and an automated tiering method are provided. The system includes a controller and multiple storage apparatuses that are layered into at least two tiers according to performance. In the method, an algorithm analyzer corresponding to each of multiple system configurations is executed to analyze data blocks in each storage apparatus to determine a target block of each data block after relocation and generate an estimated data allocation map. Then, a simulation engine is executed to classify the target blocks in the data allocation map according to a usage frequency of each target block so as to generate an exploitation map, and evaluate all of the exploitation maps to find the system configuration that raises the most performance as a best configuration. Finally, a data migrator is executed to migrate the data blocks in the storage apparatus according to the best configuration.

A multi-objective optimization Pareto set non-inferiority stratification method based on subspace statistics comprises the following steps: (1) constructing multidimensional space, (2) performing subspace division and equipotential distribution sector determination, (3) performing population-individual subspace mapping, (4) performing dominant individual statistics on subspaces, (5) calculating individual ranks, and (6) performing Pareto set non-inferiority stratification. The multi-objective optimization Pareto set non-inferiority stratification method has the advantages that it is not necessary that global traversal is performed on each individual in a population in a set to count the number of the dominant individuals; after high-dimensional solution space is discretized into the subspaces, the whole space can be divided into a dominant subspace set, an equivalently dominant subspace set and an inferior subspace set according to each subspace; all the individuals only need to be counted at a time according to the dominant subspaces or the inferior subspaces of equipotential distribution sectors, so that fast Pareto set non-inferiority stratification is achieved. In this way, the method provides a basis for real-time and quasi real-time engineering application of the evolutionary multi-objective optimization algorithm.

The invention relates to the technical field of software development, and specifically relates to a project hierarchical method for an Android application. The method comprises the following steps: analyzing functions of various module pages of a project, separating a view logic, a business logic and a data request logic in Activity; and processing event and data transfer between a business logic layer and a data layer through an event bus mechanism of an event distribution layer, so as to realize project hierarchy. The project hierarchical method for the Android application provided by the invention effectively improves the division of project developers, reduces the maintenance cost of the project, promotes decoupling between function modules and facilitates unit testing; and the project hierarchical method can be used for project hierarchy of the Android application.

A multi-tiered approach to identifying digital content and acting upon the identification includes transmitting data from a device on which the content is stored or played to a first tier entity where the content and the device are identified. The first tier entity may use any one of many techniques for identifying the data and device. Once the identification data is determined, the information is transmitted to any one of multiple second tier entities that work in cooperation with the first tier entity. The second tier entities may then perform any desired functions based on the identification, such as providing offers, content, products and/or services to the device, or to other devices associated with the device or the device user. Other tiers may be employed for carrying out particular functions or activities, such as under the direction of the second tier entities.

Aspects extend to methods, systems, and computer program products for automated task processing with escalation. An overall task to be achieved (e.g., scheduling a meeting) can be broken down into a grouping of (e.g., loosely-coupled) asynchronous sub-tasks. Completing the grouping of sub-tasks completes the overall task. Performance of some sub-tasks can be automated. Other sub-tasks can be escalated for performance by micro workers. When a micro worker is unable to perform a sub-task, the overall task can be escalated to a macro worker. Accordingly, a three tiered approach of automation, micro workers, and macro workers is scalable, cost efficient, and also provides flexibility to accurately handle more complex tasks and sub-tasks.

An embodiment of the invention provides a data layering method, medium and device and computing equipment. The data layering method comprises the following steps: sequencing to-be-layered data according to numbers to obtain sequenced data; and layering the sequenced data according to the number of preset layers and the principle that the sum of obtained variances of data intervals after layering is minimum. According to the technical scheme, the to-be-layered data are reasonably distributed into the different data intervals in a balanced manner, the different data intervals have obvious distinction degrees, and therefore, data features of the different data intervals can be shown effectively.

The invention relates to a precise customer stratification method based on customer order analysis, has relatively flexible analysis capability and can realize multiple types of stratification scheme combinations. The method comprises steps that customer order data is acquired, and the customer order data comprises historical customer order data; analysis dimensions are defined based on the customer order data; the customer order data is classified according to the dimensions; the customer order data after classification and customer data are stored; the dimensions are selected by users to screen out user costumers consistent with dimension conditions from the customer data; the user customer data screened out by the users through the dimensions is stored; the user customer data is stratified according to user selection. The method is advantaged in that the dimensions can be autonomously defined according to demands of enterprises, corresponding customer dimension data can be acquired through analysis according to the historical order data, and grouping of corresponding customer groups can be carried out by users through flexible dimension combinations according to self demands.