Abstract: A method of automatically setting optical parameters, using Automatic Optical Inspection (AOI) System, the method includes the following steps. Firstly, a recommended object image is obtained when the AOI system is set under a first recommended optical parameter set. Then, a computation is performed on an object standard picture and a recommended object image to obtain a recommended error value between the object standard picture and the recommended object image according to an optimized error function. Then, whether the recommended error value converges is determined. Then, when the recommended error value does not converge, a computation is performed to obtain a second recommended optical parameter set according to the recommended error value and the first recommended optical parameter set. Then when the recommended error value converges, the first recommended optical parameter set is decided as an optimal optical parameter set of the AOI system.

Abstract: A method of automatically setting optical parameters, using Automatic Optical Inspection (AOI) System, the method includes: obtaining a recommended object image when the AOI system under a first recommended optical parameter set; performing computation on a standard image of a and a recommended image of the to-be-measured object according to an optimized error function to obtain a recommended error value between the standard image and the recommended image; determining whether the recommended error value converges, when determining that the recommended error value does not converge, performing computation according to the recommended error value and first recommended optical parameter set to obtain a second recommended optical parameter set; when the recommended error value converges, deciding the first recommended optical parameter set as the best optical parameter set of the AOI system.

Abstract: An embodiment of an equipment health state monitoring method adapted to monitor an equipment having a monitored part, including: obtaining a plurality of first values of the monitored part from a sensor in a first time period; extracting a plurality of first parameters from the first values; generating an equipment health state index model according to the first parameters; obtaining a plurality of second value from the sensor in a second time period after the first time period; extracting a plurality of second parameters from the second values; generating a plurality of equipment health state indices according to the second parameters and the equipment health state index model; generating a health state control chart according to the equipment health state indices; and determining whether each of the equipment health state indices locates in an alert area of the health state control chart and outputting a determination result accordingly.

Abstract: A method and a system for analyzing a plurality of process factors affecting the trend of a continuous process are provided. The method includes the following steps: A plurality of similar time periods are selected from a time series. The trend of the continuous process in each of the similar time periods is similar to the trend of the continuous process in a current time period. A contribution of each of the process factors corresponding a monitoring target is analyzed according to the process factor values in the similar time periods and a plurality of monitor target values of the monitoring target. Part of the process factors are picked out according to the contributions.

Abstract: An embodiment of an equipment health state monitoring method adapted to monitor an equipment having a monitored part, including: obtaining a plurality of first values of the monitored part from a sensor in a first time period; extracting a plurality of first parameters from the first values; generating an equipment health state index model according to the first parameters; obtaining a plurality of second value from the sensor in a second time period after the first time period; extracting a plurality of second parameters from the second values; generating a plurality of equipment health state indices according to the second parameters and the equipment health state index model; generating a health state control chart according to the equipment health state indices; and determining whether each of the equipment health state indices locates in an alert area of the health state control chart and outputting a determination result accordingly.

Abstract: A method and a system for analyzing a plurality of process factors affecting the trend of a continuous process are provided. The method includes the following steps: A plurality of similar time periods are selected from a time series. The trend of the continuous process in each of the similar time periods is similar to the trend of the continuous process in a current time period. A contribution of each of the process factors corresponding a monitoring target is analyzed according to the process factor values in the similar time periods and a plurality of monitor target values of the monitoring target. Part of the process factors are picked out according to the contributions.

Abstract: A method for analyzing variation causes of manufacturing process is applied. The method includes acquiring manufacturing process data of a plurality of products, and using at least one of a non-probability based classifier and a probability based classifier to compute manufacturing process data to acquire a contribution rate of each of the manufacturing process parameters. The method further includes determining whether a classifier accuracy rate is greater than a threshold. The method further includes, if yes, performing a deleting operation to delete a manufacturing process parameter having a lowest contribution rate and using the at least one of the non-probability based classifier and the probability based classifier to compute the manufacturing process data again; and if no, setting the manufacturing process parameters not deleted by the deleting operation plus the manufacturing process parameter deleted in the last deleting operation as the at least one crucial manufacturing process parameter.

Abstract: A method and a system of cause analysis and correction for manufacturing data comprises: based on an plurality of historic manufacturing data, establishing abnormal classification rules and normal classification rules; comparing a current manufacturing data to the abnormal classification rules to identify a matching abnormal rule with the manufacturing data and an abnormal class thereof; comparing the current manufacturing data to the normal classification rules to determine a correcting rule and determine one or more correcting values of at least one of a plurality of manufacturing parameters; extracting abnormal features from the historic manufacturing data having the same condition as that of the manufacturing data, and extracting normal features from the historic manufacturing data matching the correcting rule; and based on the abnormal and the normal features, evaluating the cause contribution of the plurality of manufacturing parameters corresponding to the manufacturing data.

Abstract: A method for contour fitting and posture identification initially receives sensor data formed of a plurality of sensor signals. Thereafter at least one candidate posture or contour is determined from a set of at least one posture model based on the sensor data. Finally, user posture is determined from the at least one candidate posture through a decision making process. The sensor data can also be used to modify the at least one posture model for increasing identification accuracy. The sampling frequency of each sensor signal is dynamically adjusted to receive the sensor data in a nearly real-time manner.

Abstract: A system and method for analyzing text stream message for a micro-blog are provided. The system includes a sliding window module, storing a plurality of text stream messages from the micro-blog and updating the plurality of text stream messages once every preset duration; a dynamic text weight module, receiving the plurality of text stream messages and calculating the plurality of text stream messages for generating a burst weight according to a dynamic text stream weight algorithm; a clustering module, clustering the plurality of text stream messages for generating a plurality of clusters by a clustering algorithm according to the plurality of text stream messages and the burst weight; and a memory device, storing the clusters.

Abstract: A method and mobile device for awareness of language ability are provided. “Repeated pattern index”-related properties, such as, a vocabulary usage amount, a vocabulary type, or a ratio, a time point, a time length or repeated contents of a repeated voice segment, and “community interaction index”-related properties, such as, a number of persons who speak with a user, a conversation time length, or whether the user talks alone during each time interval, are extracted according to voice data collected by a voice collection element worn on the user. Then, a language ability of the user is further calculated, so as to provide evaluation of the language ability of a dementia patient for reference.

Abstract: The present invention relates to a method and system for monitoring sport related fitness by estimating muscle power and joint force of limbs, in which the system comprises a sensing module and a force/track detection module, wherein sensor values from the sensing module are fed to the force/track detection module to be used as base for estimating feature parameters and classifying a motion series relating to muscle power and joint force of limbs so as to obtain skill-related fitness parameters corresponding to the sensing of the sensor module.

Abstract: The present invention relates to a method and system for monitoring sport related fitness by estimating muscle power and joint force of limbs, in which the system comprises a sensing module and a force/track detection module, wherein sensor values from the sensing module are fed to the force/track detection module to be used as base for estimating feature parameters and classifying a motion series relating to muscle power and joint force of limbs so as to obtain skill-related fitness parameters corresponding to the sensing of the sensor module.

Abstract: The present invention relates to a method and system for monitoring sport related fitness by estimating muscle power and joint force of limbs, in which the system comprises a sensing module and a force/track detection module, wherein sensor values from the sensing module are fed to the force/track detection module to be used as base for estimating feature parameters and classifying a motion series relating to muscle power and joint force of limbs so as to obtain skill-related fitness parameters corresponding to the sensing of the sensor module.

Abstract: A method and mobile device for awareness of language ability are provided. “Repeated pattern index”-related properties, such as, a vocabulary usage amount, a vocabulary type, or a ratio, a time point, a time length or repeated contents of a repeated voice segment, and “community interaction index”-related properties, such as, a number of persons who speak with a user, a conversation time length, or whether the user talks alone during each time interval, are extracted according to voice data collected by a voice collection element worn on the user. Then, a language ability of the user is further calculated, so as to provide evaluation of the language ability of a dementia patient for reference.

Abstract: The present invention relates to a method and system for monitoring sport related fitness by estimating muscle power and joint force of limbs, in which the system comprises a sensing module and a force/track detection module, wherein sensor values from the sensing module are fed to the force/track detection module to be used as base for estimating feature parameters and classifying a motion series relating to muscle power and joint force of limbs so as to obtain skill-related fitness parameters corresponding to the sensing of the sensor module.

Abstract: A method for contour fitting and posture identification initially receives a sensor data formed of a plurality of sensor signals. Thereafter at least one candidate posture or contour is determined from a set of at least one posture model based on the sensor data. Finally, user posture is determined from the at least one candidate posture through a decision making process. The sensor data can also be used to modify the at least one posture model for increasing identification accuracy. The sampling frequency of each sensor signal is dynamically adjusted to receive the sensor data in a nearly real-time manner.

Abstract: A unit selection module for Chinese Text-to-Speech (TTS) synthesis includes a probabilistic context free grammar (PCFG) parser, a latent semantic indexing (LSI) module, and a modified variable-length unit selection scheme; any Chinese sentence is firstly input and then parsed into a context-free grammar (CFG) by the PCFG parser; wherein there are several possible CFGs for every Chinese sentence, and the CFG (or the syntactic structure) with the highest probability is then taken as the best CFG (or the syntactic structure) of the Chinese sentence; the LSI module is then used to calculate the structural distance between all the candidate synthesis units and the target unit in a corpus; through the modified variable-length unit selection scheme, tagged with the dynamic programming algorithm, the units are searched to find the best synthesis unit concatenation sequence.

Abstract: This invention relates to a unit selection module for Chinese Text-to-Speech (TTS) synthesis, mainly comprising a probabilistic context free grammar (PCFG) parser, a latent semantic indexing (LSI) module, and a modified variable-length unit selection scheme; any Chinese sentence is firstly input and then parsed into a context-free grammar (CFG) by the PCFG parser; wherein there are several possible CFGs for every Chinese sentence, and the CFG (or the syntactic structure) with the highest probability is then taken as the best CFG (or the syntactic structure) of the Chinese sentence; the LSI module is then used to calculate the structural distance between all the candidate synthesis units and the target unit in a corpus; through the modified variable-length unit selection scheme, tagged with the dynamic programming algorithm, the units are searched to find the best synthesis unit concatenation sequence.