Abstract: Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Abstract: Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Abstract: Communication circuitry associates a data source with a source Identifier (ID) and a cryptographic key and associates a data target with a target ID, contact token, contact condition, and contact information. The communication circuitry receives and decrypts the encrypted source ID, the encrypted target ID, and the encrypted contact token with the cryptographic key, and in response, authenticates the source ID, authenticates the target ID, and validates the contact token. When the authentication and validation are successful, the communication circuitry selects a portion of the contact information based on the contact condition, encrypts the selected contact information, and transfers the encrypted selected contact information to the data source. The data source uses the selected contact information and the contact token to transfer data to the data target. The data target uses the contact token to validate the data source.

Abstract: Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Abstract: Communication circuitry associates a data source with a source Identifier (ID) and a cryptographic key and associates a data target with a target ID, contact token, contact condition, and contact information. The communication circuitry receives and decrypts the encrypted source ID, the encrypted target ID, and the encrypted contact token with the cryptographic key, and in response, authenticates the source ID, authenticates the target ID, and validates the contact token. When the authentication and validation are successful, the communication circuitry selects a portion of the contact information based on the contact condition, encrypts the selected contact information, and transfers the encrypted selected contact information to the data source. The data source uses the selected contact information and the contact token to transfer data to the data target. The data target uses the contact token to validate the data source.

Abstract: A target transceiver transfers target instructions to a control server that associates a data source with contact information, conditions, and tokens. The target transceiver transfers the contact tokens to a source transceiver for the data source. The source transceiver encrypts and transfers a data target ID and the token to the control server. The control server receives and decrypts the data target ID and the token and identifies the data source, the data target, and the conditions. The control server processes the conditions to select a portion of the contact information and transfers the selected portion of the contact information to the source transceiver. The source transceiver transfers the user data to the target transceiver based on the selected contact information.

Abstract: Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Abstract: Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Abstract: Systems and methods for automated custom training of a scoring model are disclosed herein. The method include: receiving a plurality of responses received from a plurality of students in response to providing of a prompt; identifying an evaluation model relevant to the provided prompt, which evaluation model can be a machine learning model trained to output a score relevant to at least portions of a response; generating a training indicator that provides a graphical depiction of the degree to which the identified evaluation model is trained; determining a training status of the model; receiving at least one evaluation input when the model is identified as insufficiently trained; updating training of the evaluation model based on the at least one received evaluation input; and controlling the training indicator to reflect the degree to which the evaluation model is trained subsequent to the updating of the training of the evaluation model.

Abstract: User Equipment (UE) transfers a session request having a calling party identifier and a digital signature for the calling party identifier. An originating network receives the session request and digitally verifies the calling party digital signature for the calling party identifier. The originating network transfers the session request having the calling party identifier, a user code indicating that the calling party identifier was digitally verified by the originating network, and an originating network digital signature for the originating network. A tandem network receives the session request having the originating network digital signature and digitally verifies the originating network digital signature.

Abstract: In a packet communication system, session border controllers receive and process communication packets to detect DTMF signaling. If DTMF signaling is detected, the session border controllers determine if DTMF transcoding is required. If DTMF transcoding is required, the session border controllers transfer DTMF transcoding instructions to a DTMF transcoding server. In response to the transcoding instructions, the DTMF transcoding server transfers transcoded DTMF signaling.

Abstract: An IP origination point and method to determine transcoding in packet communications are provided. The IP origination point in one example embodiment includes a communication interface configured to exchange packet communications with a media transport path, a storage system configured to store an origination communication, payload data for the origination communication, integrity information for the origination communication that is configured to be modified by one or more transcoding operations, and returned integrity information that may have been modified by the one or more transcoding operations. A processing system generates and transmits the origination communication into the media transport path, compares the returned integrity information to the integrity information, and determines a transcoding level of transcoding that occurred in the media transport path if the returned integrity information is not equal to the sent integrity information.

Abstract: Embodiments disclosed herein provide systems, methods, and computer readable media to provide roaming IP multimedia subsystem (IMS) access. In a particular embodiment, a method provides, in a communication interface, attaching a communication device to provide the communication device with access to a broadband access network associated with a visited domain of the communication device. The method further provides, in a proxy call session control element of a broadband services gateway (BSG), registering the communication device to access IMS services on behalf of an IMS core in the visited domain over the broadband access network, conveying Session Initiation Protocol (SIP) signaling between the communication device and the IMS core as a SIP proxy, and establishing a communication session between the communication device and the IMS core.

Abstract: Examples disclosed herein provide systems, methods, and software for implementing default data quotas for wireless devices. In one example, a packet data network gateway is configured to identify a communication for a wireless device and transfer a quota query for the wireless device to an online charging server. The packet data network gateway is further configured to receive actual and default quota information from the online charging server and implement the default quota information when the communication link between the gateway and the online charging server is interrupted.

Abstract: A call setup system and method configured to setup a wireless media session extending from a first network to a second network are provided. The system in one example embodiment includes media gateways (MG-Bs) of a first network interface of an interconnect network and a soft switch B (SSW-B) within the first network. The SSW-B receives a media session initiation from a wireless communication device B (WCD-B) of the first network, wherein the WCD-B is attempting to initiate a media session to a wireless communication device A (WCD-A) of the second network, obtains a MG-Bx network address of a selected MG-Bx of the one or more MG-Bs, forwards a call initiation information to a SSW-A of the second network, and receives a media gateway MG-Ax network address from the SSW-A, wherein the WCD-B of first network is placed in communication with the WCD-A of the second network via the selected MG-Bx and the selected MG-Ax.

Abstract: A Dual Tone Multi Frequency (DTMF) circuit for relaying DTMF digits includes a communication interface, a storage system configured to store a sampling window size, a DTMF test sequence, a returned DTMF sequence, and one or more DTMF digits, with the one or more DTMF digits to be transferred to a second DTMF circuit by the DTMF circuit, and a processing system. The processing system receives the one or more DTMF digits via the communication interface and an input sampling window, generates the DTMF test sequence and transmits the DTMF test sequence to the second DTMF circuit, compares the DTMF test sequence to a returned DTMF sequence received back from the second DTMF circuit, and if the returned DTMF sequence is not the same as the DTMF test sequence, adjusts the sampling window size of the input sampling window.

Abstract: There is disclosed a connector system (500) comprising a contact pin (400) and a socket (200) for receiving the contact pin. The contact pin comprises a first groove (402) extending around the axis (410) of the contact pin; a coiled spring (404) within the first groove; and a set of teeth (406) extending around the axis of the contact pin. The socket (200) comprises a cup portion (202). The cup portion comprises a set of teeth (206) extending around the axis (210) of the cup portion (202) and for engaging with the teeth (406) of the contact pin; and a first contact surface (518) inside the cup portion and extending around the axis (210) of the cup portion for contacting the coiled spring (404) of the contact pin.

Abstract: Systems, methods, and software are described herein for operating a RTP server including receiving a session request from a user communication device indicating the user communication device has packet format switching capability, transferring an acknowledgement to the user communication device wherein the acknowledgement comprises at least a header-free packet string length, transferring a RTP stream using bundled packet format, transferring a packet format switch triggering event, and transferring the RTP stream using header-free packet format for at least as long as the header-free packet string length.

Abstract: There is disclosed a connector system (500) comprising a contact pin (400) and a socket (200) for receiving the contact pin. The contact pin comprises a first groove (402) extending around the axis (410) of the contact pin; a coiled spring (404) within the first groove; and a set of teeth (406) extending around the axis of the contact pin. The socket (200) comprises a cup portion (202). The cup portion comprises a set of teeth (206) extending around the axis (210) of the cup portion (202) and for engaging with the teeth (406) of the contact pin; and a first contact surface (518) inside the cup portion and extending around the axis (210) of the cup portion for contacting the coiled spring (404) of the contact pin.

Abstract: An originating device coupled to an originating network requests a media call to a terminating device coupled to a terminating network. In between the originating and terminating networks, a tandem network receives a signaling message for the media call transferred by the originating network. The tandem network retrieves and processes numbers for the originating device and the terminating device from the signaling message to determine a loss adjustment for the media call and to select the originating device or the terminating device to make the loss adjustment. The tandem network transfers a loss instruction indicating the loss adjustment to the originating network or the terminating network for delivery to the selected device. The selected device receives the loss instruction and responsively makes the loss adjustment.