Abstract: A medical error reduction system may include a medical error reduction software for use in creating and revising at least one drug library. The software configured to provide one of a plurality of sets of privileges to each of a plurality of sets of users. Each of the plurality of sets of privileges arranged to allocate a degree of software functionality to one of the plurality of sets of users. The degree of software functionality configured to define the ability of a user to alter the at least one drug library. The medical error reduction system may include at least one server. The medical error reduction system may include at least one editor computer each of the at least one editor computer comprising a processor in communication with a display. The at least one editor computer and at least one server may be configured to communicate via a network in a client-server based model. Each of the at least one drug library may be for use in at least one medical device.

Abstract: Methods and systems are disclosed herein for preventing hallucinations in machine learning models by enabling query responses based on a predefined ground truth defined by a corpus of information. The system may use multiple machine learning models. In particular, the system may receive a user query and use a machine learning model to split the user query into multiple sub-queries that would ask component questions for the query. The component questions may then be used to get accurate information for responding to the query. Once the information is identified, the hallucination prevention system may input that information into another machine learning model (for example, a large language model) with instructions to deliver the response to the query based on the identified information, but put it into a specific, desired form. In some embodiments, another machine learning model may be used to identify undesired responses based on policy and/or other requirements.

Abstract: In implementations of systems for generating digital content, a computing device implements a generation system to receive a user input specifying a characteristic for digital content. The generation system generates input text based on the characteristic for processing by a first machine learning model. Output text generated by the first machine learning model based on processing the input text is received. The output text describes a digital content component. The generation system generates the digital content component by processing the output text using a second machine learning model. The generation system generates the digital content including the digital content component for display in a user interface based on the characteristic.

Abstract: An electric circuit and a method for filtering glitches are described. The electric circuit includes a filter, an inverter circuit, and a reset circuit. The inverter circuit is electrically coupled to an output of the filter. The reset circuit is electrically coupled to the output of the filter. The reset circuit pulls the output of the filter high when an input signal to the electric circuit and the output of the inverter circuit are both low, pulls the output of the filter low when the input signal to the electric circuit and the output of the inverter circuit are both high, and passes the output of the filter when (i) the input signal to the electric circuit is high and the output of the inverter circuit is low or (ii) the input signal to the electric circuit is low and the output of the inverter circuit is high.

Abstract: Devices and techniques are generally described for cohort determination in natural language processing. In various examples, a first natural language input to a natural language processing system may be determined. The first natural language input may be associated with a first account identifier. A first machine learning model may determine first data representing one or more words of the first natural language input. A second machine learning model may determine second data representing one or more acoustic characteristics of the first natural language input. Third data may be determined, the third data including a predicted performance for processing the first natural language input by the natural language processing system. The third data may be determined based on the first data representation and the second data representation.

Abstract: Customizable audit templates are provided for auditing a network. A list of custom audit templates are displayed on an audit template user interface (UI) presented on a display device. From the audit template UI, an action is selected from: using a pre-existing audit template selected from the list of custom audit templates, editing the pre-existing audit template selected from the list of custom audit templates, or creating a new audit template to present in the list of custom audit templates. Based on the selection, one audit template is identified from the list of custom audit templates to use to perform an audit. An audit is executed based on the one audit template identified from the list of custom audit templates. A report is generated using results obtained from executing the audit based on the one audit template identified from the list of custom audit templates.

Abstract: Techniques for updating a machine learning (ML) model are described. A device or system may receive input data corresponding to a natural or non-natural language (e.g., gesture) input. Using a first ML model, the device or system may determine the input data corresponds to a data category of a plurality of data categories. Based on the data category, the device or system may select a ML training type from among a plurality of ML training types. Using the input data, the device or system may perform the selected ML training type with respect to a runtime ML model to generate an updated ML model.

Abstract: Systems and methods of managing virtual application performance in a virtual computing environment are provided. A system determines an application interaction score based on corresponding application interaction factors associated with sessions. The system determines the application interaction score for each virtual application accessed during each of the sessions. The system generates an aggregated application interaction score for each of the sessions based at least on combining the application interaction score for each of the virtual applications accessed during a corresponding session. The system performs an action based at least in part on the aggregated application interaction score to improve performance of a virtual application accessed via the virtual computing environment.

Abstract: Techniques for instantiating a reference type to create a first descendant loader and a second descendant loader. The first descendant loader and the second descendant loader may be isolated loaders. The first descendant loader may load a first plugin and a first set of libraries. The first set of libraries may be needed to complete a first operation. The second descendant loader may load a second plugin and a second set of libraries. The second set of libraries may be needed to complete a second operation. The first set of libraries may conflict with the second set of libraries. A first method of the first plugin may be invoked through a plugin interface in order to complete the first operation. A second method of the second plugin may be invoked through the plugin interface to complete the second operation.

Abstract: A method including obtaining an index message at both (a) an index updater for an index and (b) a subindex updater for a subindex. The method also can include updating, by the index updater, the index based on the index message. The method additionally can include determining, at the subindex updater, whether the index message is eligible for the subindex. The method further can include updating, by the subindex updater, the subindex based on the index message when the index message is eligible for the subindex. Other embodiments are described.

Abstract: A method includes processing a data file including one or more parameters for configuring a network function provided by a network device. The data file is processed to recognize and extract the one or more parameters included in the data file. The method also includes causing one or more of a plurality of parameter fields included in a graphical user interface to be populated with the one or more parameters extracted from the data file according to a mapping between the one or more parameters extracted from the data file and corresponding parameter fields included in the graphical user interface. The method further includes processing parameters included in the parameter fields to generate a JavaScript Object Notation (JSON) configuration file. The method additionally includes causing the JSON configuration file to be sent to the network device to implement the network function according to the JSON configuration file.

Abstract: An apparatus, computing device, computer program product, and a computer-implemented method for delivering financial services and, more particularly, for facilitating enhanced network communication between a user and a financial institution. The computing device is operable to dynamically conduct a geographic location analysis of data relating to a current geographic location of a client device executing a mobile application or a desktop application associated with a financial institution over a communication network. The computing device is operable to cause, based on the geographic location analysis, display of a dashboard on the client device and a widget on the dashboard that includes a profile of a branch employee of the financial institution.

Abstract: A configuration manager (CM) User Interface (UI) enables a user to initiate a configuration push by a configuration manager. A CM UI is displayed and accessed by a user. A network function device to configure is identified. A configuration file for configuring the network function device is provided to the CM using the CM UI. The user, form the CM UI, initiates a configuration push of the configuration file by the CM to the network function device to begin configuring the network function device.

Abstract: A method includes causing an electronic self-organizing network (eSON) general-purpose remote procedure call (gRPC) client to register a first cell in a communication network. The first cell is registered on an eSON gRPC server. The method also includes causing first information associated with the first cell to be processed by the eSON gRPC server to determine whether a mismatch exists between the first cell and a second cell in the communication network. The method further includes, in response to receiving a first message indicating the mismatch exists from the eSON gRPC server, sending a second message indicating the mismatch exists to an operational support system (OSS) to cause the OSS to generate a change request to be communicated to a network configuration controller for changing a network function implemented by a network device corresponding to one of the first cell or the second cell to resolve the mismatch that exists.

Abstract: Techniques for partially processing an input on a device and completing processing at a remote system are provided. The device may process an input using an on-device machine learning (ML) model, and determine to cease processing at an intermediary node of the (ML) model based on the output of the intermediary node. Based on the output of the intermediary node satisfying a condition, the device may use the output of the intermediary node to generate an output responsive to the input. Conversely, if the output of the intermediary node does not satisfy a condition, the device may send the output of the intermediary node to the remote system, so the remote system can use another machine learning model to complete processing with respect to the input.

Abstract: Accordingly, embodiments herein disclose a method for configuring at least one Network Configuration Protocol (NETCONF) server by a NETCONF controller (102). The method includes establishing direct communication between a Network Element(s) (NEs) (500) (e.g., NETCONF server) and an Operational Support System (OSS) device (1000) using a NETCONF protocol to configure the NEs (500) without communicating with an Element Management System (EMS) server. As a result, a process associated with the NEs (500), such as configure/reconfigure/retrieve information, becomes faster and does not require a response from a third entity (e.g., the EMS server, vendor dependent entity, etc.).

Abstract: A system and method are provided to configure a network for onboarding of devices. A hierarchical parameter data file describing configuration parameters of the plurality of devices, such as a Yet Another Next Generation (YANG) model, is received. A parameter database file including a plurality of configuration parameters is populated, with at least one of the configuration parameters being derived from content of the hierarchical parameter data file, and a parameter library is generated based on the parameter database file. A class definition file is generated based on at least one of the database file and the hierarchical parameter data file. Then, for a network function, a corresponding configuration file is generated based on the parameter library and the class definition file, and is provided to the network function for implementation.

Abstract: An electric circuit and a method for filtering glitches are described. The electric circuit includes a filter, an inverter circuit, and a reset circuit. The inverter circuit is electrically coupled to an output of the filter. The reset circuit is electrically coupled to the output of the filter. The reset circuit pulls the output of the filter high when an input signal to the electric circuit and the output of the inverter circuit are both low, pulls the output of the filter low when the input signal to the electric circuit and the output of the inverter circuit are both high, and passes the output of the filter when (i) the input signal to the electric circuit is high and the output of the inverter circuit is low or (ii) the input signal to the electric circuit is low and the output of the inverter circuit is high.

Abstract: Architecture that enables a user to designate acceptance to receiving social cards from other user in a social network using a personal digital assistant. A mapping component maintains the mappings of all users who have accepted to participate in card sharing and the acceptance level. A whitelist of users can be created that lists the users to whom a social card can be sent from an endpoint. The user can create local groups dynamically at runtime on the local endpoint, where the local groups enable the sharing of the personalized content with multiple users concurrently. The shared card is selected by the sending user and becomes available to the PDA on the proactive canvas of the recipient's PDA along with other cards. Based on the user engagement history, these cards can be ranked among other cards social or non-social PDA cards. Conflation, push notifications, and filtering are also provided.

Abstract: Techniques are described for the discovery of source range partitioning information. An example method includes a device determining a partition boundary value for the data based at least in part on the following steps. The device can determine a first plurality of bounded value sets and a second plurality of bounded value sets. The device can calculate a first average value of a first value and a second average value. The device can determine a first deviation value of the first average value from the first value and a second deviation value of the second average value from a third value. The device can determine the first partition boundary value based at least in part on the first deviation value and the second deviation value, the first partition boundary value being the first candidate partition boundary value or the second candidate partition boundary value.