Abstract: A missing data compensation method, missing data compensation system and non-transitory computer-readable medium are provided in this disclosure. The method includes the following operations: inputting a sensing signal by a sensor; searching for a historical data sections similar to a first data section from the plurality of historical data sections to generate a plurality of candidate data sections; calculating a plurality of data relation diagrams according to the first data section and the candidate data sections, respectively; utilizing a feature recognition model to calculate a plurality of similarity values according to the data relation diagrams; selecting a candidate data section corresponding to the maximum similarity value as a sample data section; and utilizing the data in the sample data section to compensate the data in the first data section to generate compensated data section.

Abstract: An apparatus and method for generating a motor diagnosis model. Each first dimension-reduced datum of a first motor corresponds to a normal state, an offline state, or an abnormal state, while each second dimension-reduced datum corresponds to the normal state or the offline state. The apparatus rotates the first dimension-reduced data or the second dimension-reduced data and integrates the rotated results with the dimension-reduced data that have not been rotated as a to-be-analyzed dataset. The apparatus trains a classification model for distinguishing data sources by using a subset of the to-be-analyzed dataset, derives an accuracy rate by testing the classification model for distinguishing data sources by using another subset of the to-be-analyzed dataset, and determines whether to use the to-be-analyzed dataset to generate the motor diagnosis model for the second motor.

Abstract: A missing data compensation method, missing data compensation system and non-transitory computer-readable medium are provided in this disclosure. The method includes the following operations: inputting a sensing signal by a sensor; searching for a historical data sections similar to a first data section from the plurality of historical data sections to generate a plurality of candidate data sections; calculating a plurality of data relation diagrams according to the first data section and the candidate data sections, respectively; utilizing a feature recognition model to calculate a plurality of similarity values according to the data relation diagrams; selecting a candidate data section corresponding to the maximum similarity value as a sample data section; and utilizing the data in the sample data section to compensate the data in the first data section to generate compensated data section.

Abstract: A remote working system and a working method thereof are provided. The remote working system includes at least one processor and stores a description file of a workflow. The description file includes a first task description and a second task description. The remote working system receives a service request of executing the workflow. The at least one processor determines a first identification code and a first operation address according to the first task description and calls a first operation program by using the first identification code and the first operation address. A first operation processor executes the first operation program, determines a second identification code and a second operation address according to the second task description, and calls a second operation program by using the second identification code and the second operation address. A second operation processor executes the second operation program.

Abstract: A server and a cloud computing resource optimization method thereof for big data cloud computing architecture are provided. The server runs a dynamic scaling system to perform the following operations: receiving a task message; executing a profiling procedure to generate a profile based on an to-be-executed task recorded in the task message; executing a classifying procedure to determine a task classification of the to-be-executed task; executing a prediction procedure to obtain a plurality of predicted execution times corresponding to a plurality of computing node numbers, a computing node type and a system parameter of the to-be-executed task; executing an optimization procedure to determine a practical computing node number of the to-be-executed task; and transmitting an optimization output message to a management server to make the management server allocate at least one data computing system to execute a program file of the to-be-executed task.

Abstract: A device recommendation system includes an environmental monitoring module, a device monitoring module, an abnormality monitoring module and a decision module. The environmental monitoring module receives environmental data obtained by environmental sensors and generates environmental history data accordingly. The device monitoring module retrieves enablement counts from electronic devices and generates enablement history data accordingly. The abnormality monitoring module determines whether the environmental data exceeds a threshold in a first time section and generates an abnormal signal accordingly. According to the abnormal signal, the decision module calculates the environmental history data based on an initial weight matrix to generate a recommendation data used to change the enablement status of the electronic devices.

Abstract: A server and a cloud computing resource optimization method thereof for cloud big data computing architecture are provided. The server runs a dynamic scaling system to perform the following operations: receiving a task message; executing a profiling procedure to generate a profile based on an to-be-executed task recorded in the task message; executing a classifying procedure to determine a task classification of the to-be-executed task; executing a prediction procedure to obtain a plurality of predicted execution times corresponding to a plurality of computing node numbers, a computing node type and a system parameter of the to-be-executed task; executing an optimization procedure to determine a practical computing node number of the to-be-executed task; and transmitting an optimization output message to a management server to make the management server allocate at least one data computing system to execute a program file of the to-be-executed task.

Abstract: A metadata server, a network device and an automatic resource management method for the metadata server are provided. The metadata server connects to a plurality of storage servers and a plurality of user devices, and stores system topology information which records connection relationships between the storage servers and the user devices. The metadata server detects whether a system change event occurs between the metadata server and a target storage server. When the system change event occurs, the metadata server updates the system topology information, generates a notification message in response to the update on the system topology information, and transmits the notification message to at least one relevant user device of the user devices. The at least one relevant user device may include the network device.

Abstract: A physical machine management device and a physical machine management method are provided. The physical machine management device includes a monitoring unit and a deployment unit which is electrically connected with the monitoring unit. The monitoring unit is configured to monitor information of a hardware pool. The hardware pool includes a first group and a second group which are of different types. The first group includes a physical machine. The deployment unit is configured to move the physical machine from the first group to the second group according to a deployment blueprint and the information. The physical machine management method includes the steps corresponding to the operations of the physical machine management device.

Abstract: A web content extraction system includes a web structure analyzing module, a metadata determining module, a web correlation generating module and a storage path routing module. The web structure analyzing module is configured to divide a web content of a first web into a plurality of metadata and a plurality of ordinary data. The metadata determining module is configured to divide the plurality of metadata into a plurality of target metadata and a plurality of non-target metadata. The plurality of target metadata is corresponding to a second web. The web correlation generating module is configured to generate a correlation level information between the first web and the second web. The storage path routing module is configured to route a web content of the second web to a first storage path or a second storage path and route the ordinary data to the first storage path.

Abstract: A data synchronization system includes a database, a management device, and a synchronization device. The database includes user folders, and the management device includes an authentication module and a data storage module. The authentication module authenticates the identification of the user who uses a client terminal device to log in the authentication module and output an authentication signal based on the result of the identification. The data storage module receives the authentication signal and output an index signal based on the authentication signal. The client terminal device is configured to connect to a corresponding user folder based on the index signal, and the corresponding user folder is used as a major user folder. The synchronization device logs in one of the accounts of a commercial database and synchronizes the data of the account to the major user folder. Furthermore, a method for synchronizing data is also disclosed herein.

Abstract: A data synchronization system includes a database, a management device, and a synchronization device. The database includes user folders, and the management device includes an authentication module and a data storage module. The authentication module authenticates the identification of the user who uses a client terminal device to log in the authentication module and output an authentication signal based on the result of the identification. The data storage module receives the authentication signal and output an index signal based on the authentication signal. The client terminal device is configured to connect to a corresponding user folder based on the index signal, and the corresponding user folder is used as a major user folder. The synchronization device logs in one of the accounts of a commercial database and synchronizes the data of the account to the major user folder. Furthermore, a method for synchronizing data is also disclosed herein.