Abstract: A method, system, and article provide image processing with power reduction while using universal serial bus cameras.

Abstract: An electronic device includes a metal back cover, a metal frame, a first antenna module and a second antenna module. The metal frame includes a first and a second disconnection portion, a first and a second connection portion. The first and the second connection portion are connected to the metal back cover. The first disconnection portion is separated from the first connection portion, the metal back cover and the second disconnection portion to form a first slot. The second disconnection portion is connected to the second connection portion and is separated from the metal back cover to form a second slot. The first antenna module is connected to the first disconnection portion, and forms a first antenna path. The second antenna module is connected to the second disconnection portion, and forms a second and a third antenna path with the second disconnection portion and the metal back cover.

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.

Abstract: A process operating system includes a process control platform, a process operating 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 operating 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 payment type recommendation method includes the following steps: obtaining payment data; generating a store group and a company group according to payment type and consumption location in the payment data; calculating the store payment average ratio according to the payment type corresponding to the store group; calculating the company average payment ratio according to the payment type corresponding to the company group; generating the user payment preference according to the company average payment ratio; defining the preference order according to the amount of the user payment preference; calculating the overall return rate according to the preference order using the wholesale price, the expected revenue weight, the user payment preference, a payment combination, and a total cost; and displaying the payment combination and the overall return rate corresponding to the payment combination on a display screen.

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 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 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 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 monitoring system is provided to perform a monitoring operation including: initiating a first process to serve as a first task agent for determining whether there is a monitoring item among the application servers, and if so, generating a monitoring task; initiating a second process to serve as a second task agent for obtaining monitoring data by monitoring the monitoring item according to the monitoring task; initiating a third process to serve as a third task agent for determining whether the monitoring data meets an abnormality definition associated with the monitoring task, and if so, generating an alert message; and initiating a fourth process to serve as a fourth task agent for determining, according to an alert rule, whether or not to send the alert message to a manager of the application server with which the monitoring item is associated.

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 management method for management of resources of servers is provided, the method including the step of: collecting, by a resource status monitor, performance monitoring data of each resource within each of the servers and operation status data of a plurality of virtual machines within the servers; analyzing, by an abnormality analysis and determination device, the performance monitoring data and the operation status data collected to automatically send a trigger signal in response to determining that a virtual machine in performance abnormal status is exist among the virtual machines; and automatically performing, by a resource allocator, a processing on the virtual machine in performance abnormal status in response to the trigger signal, wherein the processing is at least one action of a limiting processing, a transfer processing and a resource allocation.

Abstract: The invention provides a resource monitoring system. The monitoring unit inputs the collected monitoring data to a data-monitoring queue. The monitoring data stored in data-monitoring queue is inputted into a database. A trigger event is created when the monitor data satisfies the corresponding triggering conditions. In addition, an disposal mechanism is processed according to the triggering event. As such, the system can reply the trigger event at time.

Abstract: A resource adjustment system and method for virtual machines (VMs) are provided. The method includes: obtaining, by a monitoring module, performance and status information of a first server and at least one VM of the first server; estimating, by an estimating module, the first server and each VM according to the performance and status information and an evaluation index and obtaining a server estimation score of the first server and a virtual machine estimation score of every VM; and finding, by a moving module, a second server according to the performance and status information and the evaluation index when a virtual machine estimation score of at least one first VM of the first server or the server estimation score exceeds a threshold, finding at least one VM suitable to be moved according to a moving order, and moving the at least one VM to the second server.

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 resource adjustment system and method for virtual machines (VMs) are provided. The method includes: obtaining, by a monitoring module, performance and status information of a first server and at least one VM of the first server; estimating, by an estimating module, the first server and each VM according to the performance and status information and an evaluation index and obtaining a server estimation score of the first server and a virtual machine estimation score of every VM; and finding, by a moving module, a second server according to the performance and status information and the evaluation index when a virtual machine estimation score of at least one first VM of the first server or the server estimation score exceeds a threshold, finding at least one VM suitable to be moved according to a moving order, and moving the at least one VM to the second server.

Abstract: A foldable container, of which each of the two side walls has two sections to be foldable inwards so as to have the side walls folded on the floor of the container; the roof of the container is then fallen upon the side walls. Between the roof and the folded side walls, there is a space to accommodate the two end walls; consequently, the container can closely be folded up to facilitate an empty container to be handled in freight. The present invention discloses the fastenable hinges of the side walls and the connecting device of the end walls.