Abstract: A system evaluates currency in an area using image processing. In some examples, the system receives an image of an area from an image sensor, processes the image to identify at least one item of currency in the area, determine a value of the currency irrespective of validity, and counts the currency. In various examples, the system receives an image of an area from an image sensor; processes the image to identify at least one item of currency in the area; determines whether the currency has an error condition; and when the currency is determined to have the error condition, provides output on the error condition. In a number of examples, the system receives an image of an area from an image sensor; processes the image to identify at least one item of currency in the area; determines whether the currency is valid; and when the currency is determined to be suspect, provides output on the currency.

Abstract: A non-transitory computer readable storage medium may have stored thereon instructions that, when executed by an endpoint device, cause the endpoint device to perform operations including: (i) establishing, by the endpoint device, a first communication channel with an intermediary proxy server; (ii) receiving, from a computational instance and via the intermediary proxy server, a registration payload comprising a list of available proxy servers; (iii) ranking, at the endpoint device, the list of available proxy servers; (iv) selecting, by the endpoint device, a particular proxy server from the list of available proxy servers as ranked; (v) establishing, by the endpoint device, a second communication channel with the particular proxy server; and (vi) communicating, by the endpoint device, with the computational instance via the particular proxy server by utilizing the second communication channel.

Abstract: A non-transitory computer readable storage medium may have stored thereon instructions that, when executed by an endpoint device, cause the endpoint device to perform operations including: (i) establishing, by the endpoint device, a first communication channel with an intermediary proxy server; (ii) receiving, from a computational instance and via the intermediary proxy server, a registration payload comprising a list of available proxy servers; (iii) ranking, at the endpoint device, the list of available proxy servers; (iv) selecting, by the endpoint device, a particular proxy server from the list of available proxy servers as ranked; (v) establishing, by the endpoint device, a second communication channel with the particular proxy server; and (vi) communicating, by the endpoint device, with the computational instance via the particular proxy server by utilizing the second communication channel.

Abstract: Automating discovery server configuration as part of a discovery process includes determining one or more subnets selected from multiple subnets. Each of the one or more subnets selected is associated with a respective scheduled task. In response to determining the one or more subnets selected, one or more available discovery servers are identified from multiple discovery servers. The one or more discovery servers are configured based at least in part on the one or more subnets selected. In response to the automatic configuration, network discovery is initiated to perform the respective scheduled task.

Abstract: Systems and methods for mapping configuration items to business functions within a corporate infrastructure are disclosed. Discovery processes to automatically create and update service maps may introduce an artificial dependency between configuration items that is not necessary to the business function represented in the service map. These unnecessary dependencies may be considered “noise” and unnecessarily complicate the service map. Using machine learning techniques and procedures to identify short lived connections embodiments in accordance with this disclosure, dependency connections that may be considered noise may be detected and flagged. Once detected, these connections may be automatically removed from the service map to improve its accuracy and usefulness. Additionally, a user interface is provided that explains the “reason codes” for identification of noise connections.

Abstract: An example embodiment may involve providing for display a discovery schedule creation page for creating a discovery schedule. The embodiment may also involve, in response to receiving user input indicative of creation of a discovery schedule via the discovery schedule creation page, providing for display a discovery process page. Providing the discovery process page for display may involve, while the discovery process is being carried out according to the discovery schedule, dynamically updating the discovery process page to include total numbers of discovery results. The discovery process page may include selectable links for navigating to and displaying three pages: a discovered configuration items page, an error flow page, and a scheduling summary page.

Abstract: Automating discovery server configuration as part of a discovery process includes determining one or more subnets selected from multiple subnets. Each of the one or more subnets selected is associated with a respective scheduled task. In response to determining the one or more subnets selected, one or more available discovery servers are identified from multiple discovery servers. The one or more discovery servers are configured based at least in part on the one or more subnets selected. In response to the automatic configuration, network discovery is initiated to perform the respective scheduled task.

Abstract: Automating discovery server configuration as part of a discovery process includes determining one or more subnets selected from multiple subnets. Each of the one or more subnets selected is associated with a respective scheduled task. In response to determining the one or more subnets selected, one or more available discovery servers are identified from multiple discovery servers. The one or more discovery servers are configured based at least in part on the one or more subnets selected. In response to the automatic configuration, network discovery is initiated to perform the respective scheduled task.

Abstract: An example embodiment may involve providing for display a discovery schedule creation page for creating a discovery schedule. The embodiment may also involve, in response to receiving user input indicative of creation of a discovery schedule via the discovery schedule creation page, providing for display a discovery process page. Providing the discovery process page for display may involve, while the discovery process is being carried out according to the discovery schedule, dynamically updating the discovery process page to include total numbers of discovery results. The discovery process page may include selectable links for navigating to and displaying three pages: a discovered configuration items page, an error flow page, and a scheduling summary page.

Abstract: An example embodiment may involve providing for display a discovery schedule creation page for creating a discovery schedule. The embodiment may also involve, in response to receiving user input indicative of creation of a discovery schedule via the discovery schedule creation page, providing for display a discovery process page. Providing the discovery process page for display may involve, while the discovery process is being carried out according to the discovery schedule, dynamically updating the discovery process page to include total numbers of discovery results. The discovery process page may include selectable links for navigating to and displaying three pages: a discovered configuration items page, an error flow page, and a scheduling summary page.

Abstract: An example embodiment may involve providing for display a discovery schedule creation page for creating a discovery schedule. The embodiment may also involve, in response to receiving user input indicative of creation of a discovery schedule via the discovery schedule creation page, providing for display a discovery process page. Providing the discovery process page for display may involve, while the discovery process is being carried out according to the discovery schedule, dynamically updating the discovery process page to include total numbers of discovery results. The discovery process page may include selectable links for navigating to and displaying three pages: a discovered configuration items page, an error flow page, and a scheduling summary page.

Abstract: Systems and methods for mapping configuration items to business functions within a corporate infrastructure are disclosed. Discovery processes to automatically create and update service maps may introduce an artificial dependency between configuration items that is not necessary to the business function represented in the service map. These unnecessary dependencies may be considered “noise” and unnecessarily complicate the service map. Using machine learning techniques and procedures to identify short lived connections embodiments in accordance with this disclosure, dependency connections that may be considered noise may be detected and flagged. Once detected, these connections may be automatically removed from the service map to improve its accuracy and usefulness. Additionally, a user interface is provided that explains the “reason codes” for identification of noise connections.

Abstract: Automating discovery server configuration as part of a discovery process includes determining one or more subnets selected from multiple subnets. Each of the one or more subnets selected is associated with a respective scheduled task. In response to determining the one or more subnets selected, one or more available discovery servers are identified from multiple discovery servers. The one or more discovery servers are configured based at least in part on the one or more subnets selected. In response to the automatic configuration, network discovery is initiated to perform the respective scheduled task.

Abstract: The learning system disclosed herein enables a performance assessment to be incorporated or integrated into instructional materials being administered to a student as part of the student's current learning prescription. As the student progresses through the instructional materials, the system collects and maintains data regarding the student's performance. When data indicate that the student is not meeting certain educational goals, the system adjusts or alters the student's learning prescription to accommodate the student's current needs.

Abstract: A learning system includes at least one student workstation in a first learning environment which holds a learning session for a student. The system generates and displays primary instructional material to the student in accordance with student profile data for the student. The system causes supplemental material or content to be generated and displayed to the student at the student workstation when a downtime interval is triggered. The system generates the instructional material in accordance with the student profile data for the student. The system allows the student to seamlessly continue the learning session in a second, different learning environment. The system further allows the student to seamlessly complete the learning session in a third, different learning environment. The disclosed system thus enables students to work in various different learning environments and reduce the impact of interruptions in the learning experience.

Abstract: Methods and apparatus for displaying data on a multi-user display device are disclosed. A first subset of the data is displayed in a first orientation, such that the displayed data is in a proper orientation with respect to a first user located at a first side of the display device. Upon receiving a user input requesting to share the data, a second subset of the data is displayed in a second different orientation, such that the displayed data is in the proper orientation with respect to a second user located at a second different side of the display device. Which subset of the data is displayed to which user is based at least in part on identifying information associated with each user.

Abstract: The learning system disclosed herein enables a performance assessment to be incorporated or integrated into instructional materials being administered to a student as part of the student's current learning prescription. As the student progresses through the instructional materials, the system collects and maintains data regarding the student's performance. When data indicate that the student is not meeting certain educational goals, the system adjusts or alters the student's learning prescription to accommodate the student's current needs.

Abstract: A learning system includes at least one student workstation which holds a learning session for a student. The system generates and displays primary instructional material to the student in accordance with student profile data for the student. The system causes supplemental material or content to be generated and displayed to the student at the student workstation when a downtime interval is triggered. The system generates the supplemental material in accordance with the student profile data for the student. The disclosed system thus enables downtime to be more appropriately utilized by the student, in a manner that accommodates the learning preferences and skill gaps of the student and/or that rewards the student for showing proficiency at a skill.

Abstract: Methods and apparatus for rewarding students with redeemable tokens during a lesson are disclosed. As the student works through the lesson, the system determines whether any designated performance events occur based on the student's performance. Based on any occurrences of performance events, the system may accumulate one or more tokens for the student. The system may provide a visual indication of any tracked occurences of performance events. For example, for each occurrence of a performance event, the system increments a progress meter by a designated amount. When progress meter reaches a designated level, the system accumulates a designated quantity of tokens for the student. The amount by which the progress meter increments for each occurrence of a performance event may be based on the type of performance event which occurs. Different types of performance events may have different values or contribute differently toward the accumulation of tokens.