Abstract: System and method for seamless switching between operator networks is disclosed. The present invention relates to communication networks and, more particularly, to switching between operators in communication networks. A network element termed as the service aggregator is provided that resides in the operator's network and acts as an intermediate between the mobile user and the operator. In addition, a switching module is provided on the mobile device of the user that interacts with the service aggregator to perform switching. Base station continuously broadcasts signaling information to the mobile device. Based on such signaling information received, the mobile device decides if it wishes to switch to another operator's network. The service aggregator establishes connection with the service gateway of the new network. Further, service aggregator sends handover signal and the mobile device switches seamlessly to the new operator's network.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A method and system are disclosed. The method includes generating uncertain user data corresponding to a user of the user device and transmitting the uncertain user data to a remote computing device. The uncertain user data includes a combination of actual user data and noise data. The method includes receiving an advertisement response message from the remote computing device that includes a plurality of conditional ad objects, each conditional ad object including ad content, one or more access mechanisms, and one or more conditions. The method further includes selecting one or more of the plurality of conditional ad objects based on the actual user data and the one or more conditions defined in the selected conditional ad objects. Furthermore, the method includes displaying, for each selected conditional ad object, an advertisement that is based on the ad content and at least one access mechanism defined in the conditional ad object.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: A system and method for converting an environmental signal surrounding the checkout terminal to a transmission signal is disclosed. The system verifies the accuracy of the transaction at the checkout terminal by analyzing the transmission signal produced by a signal transmission device, which activates upon a detection of a predetermined environmental signal caused around the vicinity of the checkout terminal. The detection of the predetermined environmental signal is performed by a sensor apparatus placed at the checkout terminal which monitors and senses environmental signals during the transaction of an item being purchased at a store.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: A distributed machine learning system and method are disclosed. According to some implementations of this disclosure, the method includes identifying one or more available computing resources and receiving a task object that indicates a training job to perform. The method includes retrieving a container image based on the type of model architecture. The container image includes the model architecture and a filesystem. The method includes retrieving and mounting a base model to the filesystem of the container image. The method further includes retrieving and mounting a volume of training data to the filesystem of the container image to obtain a training container. In some implementations, the method further includes executing the training container on at least one of the one or more available computing resources and receiving a trained model from the container after the container completes the training job. The method further includes storing the trained model.

Abstract: A method and system are disclosed. The method includes generating uncertain user data corresponding to a user of the user device and transmitting the uncertain user data to a remote computing device. The uncertain user data includes a combination of actual user data and noise data. The method includes receiving an advertisement response message from the remote computing device that includes a plurality of conditional ad objects, each conditional ad object including ad content, one or more access mechanisms, and one or more conditions. The method further includes selecting one or more of the plurality of conditional ad objects based on the actual user data and the one or more conditions defined in the selected conditional ad objects. Furthermore, the method includes displaying, for each selected conditional ad object, an advertisement that is based on the ad content and at least one access mechanism defined in the conditional ad object.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: QoS aware multi radio access point for operation in TV whitespaces is disclosed. The present invention relates to operation of access points and, particularly, to operation of access points in TV whitespaces. The AP is configured to intelligently choose the radios, determine available whitespaces in the spectrum and allocate radios to the available whitespaces in the spectrum. The method determines clients that need to be serviced by the AP and assigns each client associated with AP to one of the radios. In addition, the method also takes care of QoS requirements for different services and hence every service is addressed to satisfy its QoS requirements. The method ensures that there is maximum utilization of available whitespace spectrum by accounting for the spectrum specific characteristics. The method considers bands for operation are spread across the spectrum and allocates the clients based on the availability of bands throughout the spectrum.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: Methods and apparatus provide for a Cart Inspector to create a suspicion level for a transaction when a video image of the transaction portrays an item(s) left in a shopping cart. Specifically, the Cart Inspector obtains video data associated with a time(s) of interest. The video data originates from a video camera that monitors a transaction area. The Cart Inspector analyzes the video data with respect to target image(s) associated with a transaction in the transaction area during the time(s) of interest. The Cart Inspector creates an indication of a suspicion level for the transaction based on analysis of the target image(s). Creation of a high suspicion level for the transaction indicates that the transaction's corresponding video images most likely portray occurrences where the purchase price of an item transported through the transaction area was not included in the total amount paid by the customer.

Abstract: The present invention relates to a system and method for proportional-fair resource allocation for multi-rate random access. The method includes receiving, by a device, data packets to be transmitted to an access point on a shared uplink channel, and determining, by the device, whether or not to contend for access to the shared uplink channel based on a probability of access. The probability of access is based on a data transmission rate between the device and the access point.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Abstract: System and method for seamless switching between operator networks is disclosed. The present invention relates to communication networks and, more particularly, to switching between operators in communication networks. A network element termed as the service aggregator is provided that resides in the operator's network and acts as an intermediate between the mobile user and the operator. In addition, a switching module is provided on the mobile device of the user that interacts with the service aggregator to perform switching. Base station continuously broadcasts signaling information to the mobile device. Based on such signaling information received, the mobile device decides if it wishes to switch to another operator's network. The service aggregator establishes connection with the service gateway of the new network. Further, service aggregator sends handover signal and the mobile device switches seamlessly to the new operator's network.

Abstract: A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.