Abstract: An image labeling apparatus, method, and computer program product are provided. The image labeling apparatus generates several image features of several to-be-processed images and classifies them into several groups. For each group, the image labeling apparatus: (a) selects the image feature closest to the center as a representative feature and a compared feature, (b) selects the image feature farthest to the compared feature as a candidate feature, and (c) compares the similarity between the candidate feature and each representative feature with a threshold. When all the similarities are smaller than the threshold, adopts the candidate feature as another representative feature and the compared feature and repeats (b) and (c). The group(s) whose number of representative features is more than another threshold will be re-classified.

Abstract: A yield-rate assessment apparatus for a manufacture system including a plurality of machines, each machine participating in one or more manufacture steps of a batch of products in the manufacture system, performs for each machine: calculating a bad-piece expectation value and a quantity of potential bad pieces at each corresponding manufacture step based on a quantity of bad pieces detected after the last one of the manufacture steps is finished and an initial yield rate of the current machine; calculating a good-piece expectation value based on a quantity of good pieces detected after the last one of the manufacture steps is finished and a summation of all quantities of potential bad pieces calculated for the current machine; and assessing a yield rate according to the good-piece expectation value calculated for the current machine and a summation of the bad-piece expectation value calculated for the current machine at each corresponding step.

Abstract: An image labeling apparatus, method, and computer program product are provided. The image labeling apparatus generates several image features of several to-be-processed images and classifies them into several groups. For each group, the image labeling apparatus: (a) selects the image feature closest to the center as a representative feature and a compared feature, (b) selects the image feature farthest to the compared feature as a candidate feature, and (c) compares the similarity between the candidate feature and each representative feature with a threshold. When all the similarities are smaller than the threshold, adopts the candidate feature as another representative feature and the compared feature and repeats (b) and (c). The group(s) whose number of representative features is more than another threshold will be re-classified.

Abstract: A yield-rate assessment apparatus for a manufacture system including a plurality of machines, each machine participating in one or more manufacture steps of a batch of products in the manufacture system, performs for each machine: calculating a bad-piece expectation value and a quantity of potential bad pieces at each corresponding manufacture step based on a quantity of bad pieces detected after the last one of the manufacture steps is finished and an initial yield rate of the current machine; calculating a good-piece expectation value based on a quantity of good pieces detected after the last one of the manufacture steps is finished and a summation of all quantities of potential bad pieces calculated for the current machine; and assessing a yield rate according to the good-piece expectation value calculated for the current machine and a summation of the bad-piece expectation value calculated for the current machine at each corresponding step.

Abstract: When the inspection unit corresponding to at least one disabled layer of a multilayer system is unavailable, a fault-eliminating device defines the at least one disabled layer and a target layer as a combined layer. The fault dependency of the target layer is the lowest among the fault dependency of the at least one available layer. The inspection unit of the at least one available layer is active and the fault dependency thereof is higher than the disabled layer. Then, the device makes the inspection unit and the fault symptom corresponding to the target layer correspond to the combined layer, so as to update a list of layers and a fault model. After that, the device determines a source of a fault from the layers according to the list of layers and the fault model, and performs a strategy of fault elimination corresponding to the source, to eliminate the fault.

Abstract: The present disclosure relates to packet-aware fault tolerance methods of virtual machines applied to cloud services. One such method includes using a primary input processing unit to receive an uploaded packet and replicating the uploaded packet to a backup input processing unit. The method can further include utilizing a primary execution unit to operate the uploaded packet to generate an output packet, which is then transmitted to a processing unit. A backup execution unit can be used to operate the uploaded packet to generate a backup output packet. The backup output packet can be transmitted to a backup processing unit. A fault-tolerance control component can receive the primary output packet from the primary output processing unit. The primary fault-tolerance control component can be used to compare a primary packet checksum of the primary output packet is consistent with a backup packet checksum.

Abstract: A packet-aware fault-tolerance method of a virtual machine applied to cloud services, the method including the following steps: receiving, by a primary input processing unit, an uploaded packet; replicating, by the primary input processing unit, the uploaded packet to a backup input processing unit; operating, by a primary execution unit, the uploaded packet to generate a primary output packet, and transmitting the primary output packet to a primary output processing unit, and operating, by a backup execution unit, the uploaded packet to generate a backup output packet, and transmitting the backup output packet to a backup output processing unit; receiving, by a primary fault-tolerance control component, the primary output packet transmitted by the primary output processing unit, and receiving a backup packet checksum of the backup output packet transmitted by the backup output processing unit; and comparing, by the primary fault-tolerance control component, whether a primary packet checksum of the primary ou

Abstract: A fault tolerant method for multiple servers includes the following steps: sensing, by each server, a voltage of hardware of the server; receiving, by a cabinet manager, data of an operating state of a blade server and data of a voltage of hardware of each server; reading, by a monitoring server, the data of the operating state of the blade server and the data of the voltage of the hardware of a monitored server, where the data is transmitted by the monitored server in a cabinet manager; determining, by the monitoring server, whether the operating state of the blade server of the monitored server is faulty or whether the voltage of the hardware has no power supply; if the operating state of the blade server of the monitored server is faulty or the voltage of the hardware has no power supply, starting, by the monitoring server, a backup virtual machine; and restarting, by the cabinet manager, a faulty server.

Abstract: A module for authenticating a user of a mobile device. The mobile device has an orientation sensor and a touch screen sensor. The module includes: a behavioral biometrics conversion element, used to perform calculation by matching timestamps with a plurality of behavioral data of operations, sensed by the orientation sensor and the touch screen sensor, on the mobile device to acquire a plurality of behavioral biometrics quantities, and convert, by using a statistical method, multiple sets of the behavioral biometrics quantities into a behavioral biometrics pattern in a histogram constructing manner; and an authentication mechanism core element, used to determine whether the behavioral biometrics pattern conforms to a behavioral biometrics model pattern in a histogram manner. The present invention further includes a method and a computer program product for authenticating a user of a smart phone.

Abstract: A module for authenticating a user of a mobile device. The mobile device has an orientation sensor and a touch screen sensor. The module includes: a behavioral biometrics conversion element, used to perform calculation by matching timestamps with a plurality of behavioral data of operations, sensed by the orientation sensor and the touch screen sensor, on the mobile device to acquire a plurality of behavioral biometrics quantities, and convert, by using a statistical method, multiple sets of the behavioral biometrics quantities into a behavioral biometrics pattern in a histogram constructing manner; and an authentication mechanism core element, used to determine whether the behavioral biometrics pattern conforms to a behavioral biometrics model pattern in a histogram manner. The present invention further includes a method and a computer program product for authenticating a user of a smart phone.

Abstract: An application module (A) running on a host computer in a computer network is failure-protected with one or more backup copies that are operative on other host computers in the network. In order to effect fault protection, the application module registers itself with a ReplicaManager daemon process (112) by sending a registration message, which message, in addition to identifying the registering application module and the host computer on which it is running, includes the particular replication strategy (cold backup, warm backup, or hot backup) and the degree of replication associated with that application module. The backup copies are then maintained in a fail-over state according to the registered replication strategy. A WatchDog daemon (113), running on the same host computer as the registered application periodically monitors the registered application to detect failures.

Abstract: An application module (A) running on a host computer in a computer network is failure-protected with one or more backup copies that are operative on other host computers in the network. In order to effect fault protection, the application module registers itself with a ReplicaManager daemon process (112) by sending a registration message, which message, in addition to identifying the registering application module and the host computer on which it is running, includes the particular replication strategy (cold backup, warm backup, or hot backup) and the degree of replication associated with that application module. The backup copies are then maintained in a fail-over state according to the registered replication strategy. A WatchDog daemon (113), running on the same host computer as the registered application periodically monitors the registered application to detect failures.