Abstract:
A process operating system includes a process control platform, a process operation platform and an endpoint task robot. The process control platform is configured to receive operation information, extract a task from the operation information using a semantic analysis method, and publish the task. The process operation platform is configured to receive the task and store the task in a task queue. After receiving the task, the process operating platform defines a processing flow based on the task, and sorts the order of the task in the task queue. The endpoint task robot is configured to automatically obtain the task from the process operation platform, executes the task according to the processing flow. It then writes the execution result into the log queue and transmits the execution result to the process control platform.
Abstract:
A consumption prediction method includes the following steps: calculating a personal preference correlation coefficient; inputting historical environment data, a historical consumption record and the personal preference correlation coefficient into a first neural network model; a training model is generated by the first neural network model; and determining whether the accuracy rate of the training model is higher than the training threshold. When the accuracy rate of the training model is higher than the training threshold, the training model is regarded as a prediction model.
Abstract:
The data forwarding system includes a data storage device and a server. The data storage device is configured to store shared data uploaded by a first developer via a first terminal device. The server includes a processor which can load program codes to execute: a forwarding procedure for forwarding the shared data to a receiving device; a forwarding setting procedure for enabling the developer to apply forwarding settings to the shared data; a data processing procedure for executing the necessary data processing before forwarding the shared data; and a forwarding condition verification procedure for examining whether the shared data conforms to the forwarding settings.
Abstract:
A management method of cloud resources is provided for use in a hybrid cloud system with first and second cloud systems, wherein the first cloud system includes first servers operating first virtual machines (VMs) and the second cloud system includes second servers operating second VMs, the method including the step of: collecting, by a resource monitor, performance monitoring data of the first VMs within the first servers; analyzing, by an analysis and determination device, the performance monitoring data collected to automatically send a trigger signal in response to determining that a predetermined trigger condition is met, wherein the trigger signal indicates a deployment target and a deployment type; and automatically performing, by a resource deployment device, an operation corresponding to the deployment type on the deployment target in the second cloud system in response to the trigger signal.
Abstract:
A system for creating virtual machines, adapted to a virtual management platform, includes a configuration module, a selection module, a determination module and a distribution module. The configuration module creates a plurality of virtual sections according to the resource specifications. The selection module selects one of the virtual sections according to the customized specifications. The determination module creates a virtual section-setting profile according to the customized specifications. The determination module further calculates the quantity of the remaining resources of the virtual section, and determines whether the quantity of the customized specifications will exceed the remaining resources or not. When the quantity of the customized specifications does not exceed the quantity of the remaining resources, the distribution module creates a virtual machine in the virtual section according to the virtual section-setting profile.
Abstract:
A work scheduling method implemented via a cloud platform is provided. The work scheduling method is used in a cloud platform work schedule system. The method includes: arranging, by a developing interface of a developing module, a work schedule; generating, by the developing module, a dynamic linking library (DLL) which corresponds to the work schedule and uploading the dynamic linking library to the cloud platform through the internet; transferring, by a disposing module, the dynamic linking library to a Application service; computing, by a scheduling module, a scheduling time according to the work schedule; and executing, by an executing module, the application service according to the scheduling time.
Abstract:
A data processing method includes the following steps: generating a machine-learning parameter and obtaining a storage parameter code, wherein the storage parameter code corresponds to a storage space; receiving the machine-learning parameter and the storage parameter code, and storing the machine-learning parameter in the storage space according to the storage parameter code, and generating an event notification when the machine-learning parameter is modified; and generating a loading request according to the event notification, and the loading request is used to request the modified machine-learning parameter, wherein after the loading request is generated, the modified machine-learning parameter is downloaded from the storage space corresponding to the storage parameter code.
Abstract:
A cloud service system includes a hardware resource, a storage device, and a controller. The hardware resource is installed with a system, and a software container is instantiated for cloud service execution on the hardware resource. The storage device stores a plurality of libraries, each of which is associated with a respective version of the system. The controller determines a first version of the system according to a deployment request, determines whether one of the libraries is associated with the first version, and selects one of the libraries for instantiating the software container according to a selection history of the libraries in response to none of the libraries being associated with the first version.
Abstract:
A monitoring management system is provided to perform a monitoring operation including: detecting a system configuration of an application server; determining whether the system configuration is compliant with a monitoring rule corresponding to the application server; generating a monitoring configuration when the system configuration is compliant with the monitoring rule; and allocating at least one monitoring server to monitor the application server according to the monitoring configuration.
Abstract:
A character recognition method includes the stages as detailed in the following paragraph. An image is received, wherein the image is one in a plurality of consecutive images. A target object in the image is detected. Object information of the target object is defined according to the area ratio of the target object occupied in the image. Whether the target object in the image is the same as the target object in the previous image is determined according to the object information. Character recognition on the target object is performed to obtain a recognition result. The weighting score of the recognition result is calculated according to the object information and the recognition result. The weighting score of the recognition result of the target object in the consecutive images is accumulated until the weighting score is higher than a preset value, and the recognition result is output.