Abstract: The present invention discloses a method of detecting sleep disorder based on an EEG signal and device of the same. The method and device only need an EEG signal for analysis to determine sleep disorder and abnormal score. Therefore, the method and device may reduce cost of collecting physical information and avoid from uncomfortable feeling of user who wears several sensors.

Abstract: According to one embodiment of the invention, a method for detecting driving anomalies comprises steps of: with at least one algorithm, processing raw data from On-Board Diagnostics of a car to generate time-series data, with the time series data as input, using an automatic driving behavior separating technology to identify a plurality of driving behaviors; with the driving behaviors as input, using an artificial intelligence technology to build up a driving anomaly detection model without labeling the driving behaviors; and issuing an alarm for driving anomaly identified according to an analyzing result of alarm signature of the driving behaviors.

Abstract: An anomaly flow detection device and an anomaly flow detection method thereof are provided.

Abstract: The present invention discloses a prediction method for system errors, applied in prediction system predicting system errors of a monitored system. The method comprises steps of: pre-processing training data formed with data points at time slots to generate corresponding features to the data points of each time slot, and extract a frequency-based feature for each time slot according to distribution of clustering, grouping or classification of the corresponding features in the previous time slot of the current time slot. Using machine learning algorithm and taking model building data coming from the corresponding features and frequency-based feature as input to build up a prediction model for predicting and alerting a future error of the monitored system.

Abstract: The present invention discloses a prediction method based on unstructured data, applied in a prediction system comprising an analyzing module and a model-building module to predict future behaviors of a user. The prediction method comprises steps of: with the analyzing module, analyzing a recording file with a natural language processing algorithm to generate at least one feature vector, wherein the recording file is related to a subject behavior in a predetermined observation period, at least one record in a form of unstructured data is stored therein, and the record comprises a time stamp and a recording text; and with the model-building module, using a surprised machine learning algorithm building a model with information corresponding to the feature vector as input for predicting future behaviors of a user, wherein the record is one of query record of domain name system, transaction record of automated teller machine, transaction record of structured query language and literal record.

Abstract: A detective method, applied in a detective system comprising an activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprises steps of using an unsupervised machine learning technique, a Natural Language Processing technique (NLP) and a supervised machine learning technique. As such, an activity-or-behavior model is built for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system. The activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the sensor data values and a selected temporal information about at least one sensor data stream and between different sensor data streams.

Abstract: According to one embodiment of the invention, a method for detecting driving anomalies comprises steps of: with at least one algorithm, processing raw data from On-Board Diagnostics of a car to generate time-series data, with the time series data as input, using an automatic driving behavior separating technology to identify a plurality of driving behaviors; with the driving behaviors as input, using an artificial intelligence technology to build up a driving anomaly detection model without labeling the driving behaviors; and issuing an alarm for driving anomaly identified according to an analyzing result of alarm signature of the driving behaviors.

Abstract: An anomaly flow detection device and an anomaly flow detection method thereof are provided.

Abstract: A communication terminal device, a communication system and a communication method are provided. The communication terminal device includes a first communication chip, a second communication chip and a switching unit. When detecting an Internet telephone packet or a network traffic greater than a threshold, the switching unit turns off a first communication chip and turns on a second communication chip to enable the Internet telephone packet or the network traffic to be transmitted from the Internet to the second communication chip. When receiving an Internet telephone packet or a paging, the first communication chip is detached from a core network and issues a notification. The switching unit enables the second communication chip to be attached to the core network in response to the notification to enable the Internet telephone packet or the network traffic to be transmitted from the core network to the second communication chip.

Abstract: According to one embodiment of the invention, a detective method, applied in a detective system comprising a activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprising steps of: using an unsupervised machine learning technique to preprocess and analyze raw sensor data obtained from the monitored subject system to generate post data; with the post data as input, using a Natural Language Processing technique (NLP) to discover the activities or behaviors performed by the subject system; and with output data from the NLP technique as input, using a surprised machine learning technique to build an activity-or-behavior model for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system; wherein the activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the senso

Abstract: A millimeter-wave antenna device and a millimeter-wave antenna array device thereof are characterized in that bump portions on coaxial cable connector bases protrude into through holes of a millimeter-wave substrate to effectuate fixation thereof and ensure that the millimeter-wave substrate is tightly coupled to the coaxial cable connector bases to not only ensure the precision of the position of a feed impedance unit of a microstrip antenna structure but also ensure that, when fixed to an antenna back panel frame, a triangular configuration is effectuated such that larger antenna spacing (i.e., 8.5˜12 mm) is achieved while meeting the functional requirement of an antenna beam scan, that is, an allowance of ±30 degrees approximately, thereby circumventing a problem, i.e., the spacing between antenna units is too small to enable an external emitting/receiving module to function.

Abstract: An offload determination system for multiple wireless network, a server and a method thereof are provided. The system includes a server, a first and a second wireless base station and a user equipment (UE). The first and the second wireless base station provides a first and a second wireless network respectively. The server has traffic tariff information corresponding to the UE. The server monitors and obtains quality of service (QoS) information of the first and the second wireless base station respectively, evaluates a data transfer efficiency information of the first and the second wireless base stations according to the traffic tariff information and the QoS information, and transmits the data transfer efficiency information to the UE. The UE selectively uses the first or second wireless network based on the data transmission efficiency information.

Abstract: A method of handover is provided. It includes: performing a mobile base station tracking area update procedure; performing a mobile device tracking area update procedure; transmitting a mobile base station identity of the mobile base station to a mobile device mobility management entity corresponding to the mobile device by a fixed base station; transmitting a request for setting the mobile base station ID to the mobile device by the MD mobility management entity; writing the mobile device ID into a mobile network ID list of the mobile device by the mobile device; when the mobile device receives from the fixed base station a handover message indicating the mobile device to hand over to the mobile base station and the mobile device determines the mobile network ID list includes the mobile base station ID of the mobile base station, then, the mobile device hands over to the mobile base station.

Abstract: A millimeter-wave antenna device and a millimeter-wave antenna array device thereof are characterized in that bump portions on coaxial cable connector bases protrude into through holes of a millimeter-wave substrate to effectuate fixation thereof and ensure that the millimeter-wave substrate is tightly coupled to the coaxial cable connector bases to not only ensure the precision of the position of a feed impedance unit of a microstrip antenna structure but also ensure that, when fixed to an antenna back panel frame, a triangular configuration is effectuated such that larger antenna spacing (i.e., 8.5˜12 mm) is achieved while meeting the functional requirement of an antenna beam scan, that is, an allowance of ±30 degrees approximately, thereby circumventing a problem, i.e., the spacing between antenna units is too small to enable an external emitting/receiving module to function.

Abstract: The present application is provided a system and a method of a trigger service, which is applied between an end equipment group and an application service terminal. The end equipment group includes a plurality of end equipment, and the end equipment of the mobile equipment group is configured to sequentially connect to mobile network. Each of the end equipment is configured to keep connection with mobile network in a waiting period and suspended to access mobile network after the waiting time period. The application service terminal is configured to transmit a trigger message to the end equipment group, and the trigger message is repeatedly transmitted in a transmission period of the message arrangement. During the transmission period, each of the end equipment of each end equipment group in mobile network is configured to execute the requested order of the trigger message when it receives the trigger message from the application service terminal.

Abstract: An offload determination system for multiple wireless network, a server and a method thereof are provided. The system includes a server, a first and a second wireless base station and a user equipment (UE). The first and the second wireless base station provides a first and a second wireless network respectively. The server has traffic tariff information corresponding to the UE. The server monitors and obtains quality of service (QoS) information of the first and the second wireless base station respectively, evaluates a data transfer efficiency information of the first and the second wireless base stations according to the traffic tariff information and the QoS information, and transmits the data transfer efficiency information to the UE. The UE selectively uses the first or second wireless network based on the data transmission efficiency information.

Abstract: The present application provides a peer-to-peer networking method and system for integrating heterogeneous social networks. The method applied in a server device includes the following steps: First, the server device connects with a plurality of peer nodes; each of the peer node defines a user end and accessing at least one social network. Then, the server device according to a social relationship of the social networks links to the corresponding peer nodes for integrating a peer-to-peer social network (P2P-iSN) which configures a plurality of social paths among the peer nodes from the different social networks.

Abstract: The present application provides a peer-to-peer networking method and system for integrating heterogeneous social networks. The method applied in a server device includes the following steps: First, the server device connects with a plurality of peer nodes; each of the peer node defines a user end and accessing at least one social network. Then, the server device according to a social relationship of the social networks links to the corresponding peer nodes for integrating a peer-to-peer social network (P2P-iSN) which configures a plurality of social paths among the peer nodes from the different social networks.

Abstract: The present application is provided a system and a method of a trigger service, which is applied between an end equipment group and an application service terminal. The end equipment group includes a plurality of end equipment, and the end equipment of the mobile equipment group is configured to sequentially connect to mobile network. Each of the end equipment is configured to keep connection with mobile network in a waiting period and suspended to access mobile network after the waiting time period. The application service terminal is configured to transmit a trigger message to the end equipment group, and the trigger message is repeatedly transmitted in a transmission period of the message arrangement. During the transmission period, each of the end equipment of each end equipment group in mobile network is configured to execute the requested order of the trigger message when it receives the trigger message from the application service terminal.

Abstract: A method for reducing the handover frequency by a communication device in femtocell networks includes the steps: measuring the radio signal strength by a communication device and storing the information of the serving base station into a cache memory; checking whether the stored information in the cache memory is classified as “femtocell” or not; if so, deleting the macrocell's information from the measurement report by the communication device and transmitting this to the serving base station; when the radio link failure occurred, checking whether the stored information in the cache memory is classified as “femtocell” or not; if so, initiating a timer; detecting an available femtocell before the timer expires; transmitting a call reestablishment request message to the available femtocell for rebuilding the link.