Abstract: Methods and systems are described for delivering psychophysiological self-regulation training in a virtual, augmented, and/or mixed reality environment that simulates a social situation, such as one involving conflict. A user (e.g., a trainee) may interface with a training computing system directly or via an avatar that may interact with other characters in the simulation who may be programmed at one or more levels of threat to or cooperation with the trainee. The system may provide feedback to the trainee regarding their cognitive and emotional states. The feedback may be designed to encourage them to develop the ability to respond in future real environments with appropriately effective states, where the feedback may take the form of the behavior of the characters, with the trainee's interaction based on their effective states being rewarded by desirable character behavior and the trainee's ineffective states being penalized by undesirable character behavior.

Abstract: A computer-implemented system includes a treatment apparatus configured to implement a treatment plan while the treatment apparatus is being manipulated by a user and a processing device configured to receive a plurality of risk factors, each of the plurality of risk factors being associated with one or more medical events or outcomes for a user; generate a set of the risk factors; determine, based on the set of the risk factors and measurement information associated with the user, one or more individual probabilities that the one or more medical events or outcomes will occur while the treatment apparatus is being manipulated by the user; and perform, based on the one or more individual probabilities, one or more corrective actions associated with the one or more medical events or outcomes.

Abstract: The present disclosure discloses a cloud platform resource cross-project transfer method and system, and a computer storage medium. The method includes: generating a slot position and an authentication key for a resource to be transferred based on a transfer request; generating a transfer Identity (ID) of the resource to be transferred, acquiring a project ID where the resource to be transferred is located based on a resource ID, constructing a transfer structure body, and writing the transfer structure body into a database; generating a transfer record of the transfer structure body in the database, and setting a resource status of the resource to be transferred as waiting for transfer in the transfer record; and returning the transfer ID, the authentication key, a transfer description, and the resource ID to a transfer user based on the transfer request.

Abstract: This disclosure provides systems for generating customized datasets. An example dataset generator mines contacts from multiple members of an enterprise, applies a pattern recognition process to determine attributes of the contacts aligned with objectives of the enterprise, stores the contacts and associated attributes in a relational data structure, and through a machine learning process, generates a customized contact dataset of the contacts with attributes relevant to a user request, an event, or a notification received. The example dataset generator may also generate an action steps dataset for the user. The dataset generator may aggregate contacts from calls, chats, emails, SMS messages, and video feeds of an enterprise, apply a pattern recognition process to determine attributes of the contacts, and through a machine learning process, partition and distribute the contacts and associated action steps on respective dashboards of multiple customer service representatives of the enterprise.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for safe social networking environment. In some implementations, a server receives a request to activate a live sharing feature, the live sharing feature enabling access to a location and a status of a first user. The server obtains data identifying a set of trusted users for the first user. The server determines that an in-person engagement of the first user with a second user has initiated. In response to determining that the engagement has initiated, the server transmits, to each trusted user, data indicating that the first user has initiated the engagement and location data of the first user. The server obtains a status of the first user's engagement with the second user. The server provides, to each trusted user, the status of the first user's engagement and the location data of the first user.

Abstract: A device and method for classifying a category of data are provided. The device includes: a memory storing one or more instructions; and at least one processor configured to execute the one or more instructions stored in the memory to cause the processor to: identify a classification system of a category of data comprising a classification criterion of the category of the data and a plurality of keywords; obtain data comprising at least one sentence; and determine at least one category with respect to the at least one sentence of the data based on the classification system of the category of the data using a neural network that performs classification by unsupervised learning.

Abstract: A computer implemented method for administration of admission offers from educational institutions including receiving student information from students, generating a unique student identifier for each of the students, generating a universal student profile for each of the students on the database, the universal student profile including the unique student identifier, student identification information, and student qualification information for each of the students, identifying matching students from a plurality of universal student profiles stored on the database whose qualification information satisfies the entrance requirement information of any of the plurality of educational institution profiles stored on the database, generating on the database an anonymized version of the universal student profile of each of the matching students, and transmitting over the data network the anonymized version of the universal student profile of each of the matching students to educational institutions whose entrance req

Abstract: Embodiments relate to a dynamic routing system, comprising a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise a first receiving component that receives information of a trip comprising a destination and departure information, and an optimal routing component that determines an optimal routing based on current conditions, user preferences for charging stations, primary user's driving habits, battery's state of health, financial impact, and availability of charging stations at the time of receiving the trip information. At the time of trip set up, the system can make reservations for charging at the charging station requiring a reservation. During the trip, if the system requires a change to the reservation, the system establishes communication with the charging station and adjusts the reservation.

Abstract: Systems and methods are provided for determining navigation routing of a vehicle based on predicted total cost of possible routes, including: receiving information identifying a destination for a vehicle; determining two or more possible routes from a origination to the destination; determining a plurality of cost factors for a plurality of the determined possible routes, wherein the cost factors comprise direct cost information for the plurality of determined possible routes and indirect cost information for the plurality of determined possible routes; calculating a total cost for each of the plurality of determined possible routes using the cost factors; and presenting to the user a lowest-total-cost route from among the plurality of determined possible routes.

Abstract: Coaching systems and methods, and non-transitory computer readable media, include analyzing an agent's interactions to identify knowledge gaps and specific topics where an agent has difficulties. An algorithm uses bootstrap sampling to verify that an agent's scores are significantly different from other agents' scores. The algorithm further uses a mutual information score to find topics that are associated with interactions having a high knowledge gap score.

Abstract: Systems and methods are disclosed for detecting partial electronic schedule updates and generating targeted electronic notifications. A system may comprise a communication interface configured to establish bidirectional communication with a plurality of electronic devices, and at least one processor.

Abstract: A system for shift design and assignment comprises an interface configured to receive scheduling input data which includes labor demand data, worker data, and scheduling configuration data, and a processor configured to generate a set of shift candidates, determine a set of decision variables, determine a cost function, determine a set of constraints, and determine simultaneously, using a SAT, a MP solver, or a MIP solver, a subset of the shift candidates selected in a final schedule and a set of shift assignments of which worker is assigned to which selected shift candidate of the subset of the shift candidates such that the hard constraints are fully respected, violations to the soft constraints are minimized, and the cost function is minimized.

Abstract: A skill acquisition assistance method includes a first stimulus generating step of acquiring first and second tactile data indicating tactile senses corresponding to a first body part based on an action of the first body part during work time when first and second workers perform the same work and generating a first stimulus based on the first tactile data by a stimulus transmission section mounted on a second body part different from the first body part of the first worker and a second stimulus generating step of switching a stimulus generated by the stimulus transmission section to a second stimulus based on the second tactile data in conjunction with the action of the first body part of the first worker.

Abstract: Centralized communication server systems and methods are provided. In one embodiment, a centralized server includes at least one network interface for bidirectional communication with mobile devices. At least one processor is configured to receive, via the computer network, event information for a discharge event associated with an individual, automatically identify a department associated with the one or more rooms, automatically receive protocol information for the identified department, and identify one or more milestones. The processor(s) are further configured to automatically generate workload data based on the identified milestones, receive assignment information for a plurality of individuals associated with the protocol information, and automatically assign the one or more milestones to the first individual.

Abstract: A system and method for configuring network pairings enabling end-to-end communications between electronic devices is disclosed. The system receives a network pairing request from a requesting device to communicate with a target device. The system identifies historic data associated with the communication object and determines whether an affinity group associated with the requesting device is found. Further, the system determines whether the communication object has a valid permission token associated therewith. If a valid permission token is unavailable, the system checks whether a subscriber filter criteria is met by the requesting device. If the filter criteria is met, system calculates a subscriber access score (SAS) for the requesting device and compares the score to a threshold. When the SAS is greater than the predetermined threshold value, system creates a dynamic network pairing between the requesting device and the target device.

Abstract: One or more systems, devices, computer program products and/or computer-implemented methods of use provided herein relate to outputting an optimal decision policy base on informal knowledge input. A system can comprise a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components can comprise an analysis component that analyzes an input dataset comprising a constraint in a natural language form, and an augmentation component that generates an influence mapping comprising a constraint variable based on the constraint input. In an embodiment, an input dataset employed to support the influence mapping can comprise time-stamped tuple data comprising a state, an action and a reward. In an embodiment, an inference engine can generate an output policy in response to the constraint input and which output policy can be based on the constraint input and constraint variable.

Abstract: A resource data modeling, forecasting, and simulation system analyzes data pertaining to the data processing tasks and the resources assigned to the data processing tasks to generate short-term forecasts and long-term forecasts of task volumes. The forecasted task volumes are further optimized based on different factors to determine the resources required to handle the forecasted task volume. Various simulations of hypothetical what-if scenarios are also generated based on the forecasts and the resource requirements. The resource data modeling, forecasting and simulation system is based on multi-algorithmic ensemble models for forecasting, automated model selection and the unique simulation methodology based on multiple parameters.

Abstract: Methods and computer program products for organization and improvement of systems, processes, and operations for performing work. A system includes a database for storing metric data, a quantum computer in communication with the database, and a server in communication with the database and the quantum computer. Instructions implemented by the server include providing the metric data associated with the plurality of projects to the quantum computer for the quantum computer to quantify metrics for each of the plurality of projects and receiving quality improvement analysis from the quantum computer for the plurality of projects. The instructions include identifying five or fewer projects of the plurality of projects based on which of the plurality of projects fails a quality threshold for the metric data by a greatest margin.

Abstract: This disclosure lies in the field of a computer implemented method of routing a video call from a call center computer system comprising a controller, a transceiver, and a machine learning system, to a product service agent computer system assigned to a certain medical device product type and associated services. This disclosure involves using artificial intelligence in order to identify a medical device product based on recorded product image data. Further aspects of this disclosure provide a corresponding call center computer system for routing a video call initiated by a mobile device from the call center computer system to a medical device product service agent computer system as well as a computer-implemented method for generating a model of a medical device product type.

Abstract: An iOS application program construction method and an apparatus, and electronic devices, and a storage medium are provided. The iOS application program construction method includes: configuring project information; based on the project information and at least one target component, utilizing a compilation management service and employing a script to configure a preset project, so as to obtain a target project; and packaging the target project by utilizing a packaging system to obtain an iOS application program corresponding to the target project.

Abstract: A method of estimating a time to complete a task for a user of a computer comprises: identifying a target task for which a time is to be estimated for completing the task, determining as a start point the completion of the last task completed by the user on the computer, obtaining, from data relating to a corpus of users, data for at least a subset of those users who completed the last task completed by the user before also completing the target task wherein the obtained data comprises timing data, calculating a representative time from the start point to the completion of the target task, based upon the obtained data, and implementing a predetermined action responsive to the calculated representative time.

Abstract: Computer-implemented systems and methods are provided for automated task scheduling and management. In some embodiments, a system for automated task scheduling may comprise at least one processor configured to receive a request with information for a task to be performed by a respondent. The one or more processors may retrieve employee information and, based on one or more attributes in the employee information and one or more attributes in the task information, identify one or more employees to complete the task. The one or more processors may assign the task to the identified employee(s), and monitor a status of the task based on periodic inputs from the employee.

Abstract: Certain exemplary embodiments can provide a method that comprises rendering a first user interface. The first user interface accepts a request from a partner to provide a service to an initiative. Services are provided within a boundary of a governmental entity. The first user interface is structurally changed responsive to information received from a database concerning the service and the initiative.

Abstract: A micromobility transit vehicle service task management system and related methods are disclosed. In one embodiment, a system determines service tasks to be executed based on a level of availability of one or more micromobility transit vehicles. A value for each of the tasks is determined based on a cost to perform the task and value generated by an increase in availability of the one or more micromobility transit vehicles, for dynamic transportation matching, from execution of the task. The tasks may be prioritized into an order of execution that maximizes a total of the values of the tasks. The determined values of the tasks may be adjusted in the prioritization of the tasks based on the order of execution of the tasks. A navigational task route may be generated based on the prioritized tasks and assigned to a technician device to guide a technician to each of the tasks.

Abstract: A system and method for analyzing risk and providing risk mitigation instructions. The system receives analyzes sensor data and other data corresponding to a user to determine a test group. The system uses the test group to determine a risk score, and, subsequently, a risk mitigation strategy. Machine learning techniques are implemented to refine how the test group, risk score, and mitigation are each selected.

Abstract: In an example embodiment, a solution is provided that allows a user to submit a document. Information can be obtained from the document using optical character recognition (OCR) or other techniques. This information can then be used to identify one or more workflows that pertain to the document. The one or more workflows may be ranked using machine learning techniques and presented to the user. Once the user selects a desired workflow, the information obtained from the document can then be used to automatically complete at least a portion of the workflow, for example by prefilling one or more fields in a form.

Abstract: A computer-implemented method for dynamically reallocating resources to users of a coaching service. The method can include initially allocating resources to users of the coaching service, receiving indications of activities of the users relative to their allocated resources, and comparing the activities relative to a reference value to produce an outcome including a likelihood that a target user will benefit from a target resource. Upon identifying the target user, a dynamic reallocation process deallocates the target resource from another user and reallocates the target resource to the target user.

Abstract: Devices and servers in a commercial insurance growth data system may be configured to receive and respond to requests for commercial insurance growth data from insurance agents. For example, an insurance provider server may be configured to receive commercial insurance information requests from insurance agent devices, determine sets of insurance agent characteristics for the corresponding agents, generate commercial insurance growth data packages based on sets of agent characteristics and other factors, and transmit the commercial insurance growth data packages to the insurance agent devices. The sets of agent characteristics may be provided by an insurance agent user via a software user interface and/or may be retrieved from an insurance agent database. Business segments for commercial insurance growth may be selected by the insurance agent, or may be selected for the insurance agent via an analysis by an insurance provider.

Abstract: Techniques are provided herein for providing information during a life cycle of a user's engagement with a product or service. A wireless device is configured to, in response to processing a computer readable artifact after the user has acquired the product or service, transmit a request for first information pertaining to the product or service. A computer is configured to retrieve the first information without regard for the life cycle of the product or service. The computer is further configured to retrieve supplemental information pertaining to the product or service, and provide the first information together with the supplemental information to the wireless device. The supplemental information retrieved varies depending on a current state of the life cycle.

Abstract: Methods, apparatuses, and systems for scheduling tasks to field professionals include a memory configured to store historical data associated with past demand for field professionals, a network interface, and at least one processor connectable to the network interface. The at least one processor is configured to access the memory and to: receive a set of requests reflecting a current demand for on-site services; predict imminent demand for on-site services based on the historical data; generate a schedule for a set of field professionals based on the current demand for on-site services; and reserve in the schedule availability based on the predicted imminent demand for on-site services.

Abstract: Methods and systems disclosed herein utilize an automated analytics framework to implement a perioperative complication risk algorithm that uses existing clinical data in electronic health records to forecast patient-level probabilistic risk scores for eight major postoperative complications. An example method includes accessing health record data for a patient, normalizing the accessed health record data to generate a health record data set for the patient, transforming one or more features from the health record data set, selecting one or more transformed features from the health record data set, calculating risk probabilities for one or more complication risk categories based on the health record data set and the selected one or more features, calculating mortality risk probabilities for one or more mortality risk categories based on the calculated risk probabilities, and generating a personalized risk panel based on the calculated risk probabilities and the calculated mortality risk probabilities.

Abstract: The present embodiment provide a monitoring system for monitoring at least one of fixed equipment installed in a floor and a moving object moving in the floor, the fixed equipment and moving object being monitoring targets, the monitoring system includes a recognition device that recognizes the monitoring target and outputs recognition information, and a management device that collects position information of the monitoring target from the recognition information.

Abstract: A system may receive, identify, and/or extract one or more pieces of information (e.g., categories of knowledge) from an input (e.g., a knowledge source, as described herein). The categories of knowledge may include one or more phrase and/or multi-word phrase, which may be referred to as individual pieces of knowledge (e.g., knowledge entities). The system may identify one or more relationships between the categories of knowledge and/or the individual pieces of knowledge. For example, the relationships may be inter and/or intra-categorical relationships. The relationships may be organized to form a hierarchical relationship driven knowledge engine. The knowledge engine may organize the knowledge entities by entity (e.g., operator, company, job posting) and/or contextualize the knowledge entities by domain (e.g., profession, employer, etc.) by, for example, creating one or more knowledge profiles. The knowledge engine may then use these knowledge profile to dynamically respond to informational requests.

Abstract: Systems and methods for quantifying a user capability in accordance with an organizational role are disclosed herein. In an aspect, a role capability assessment is deployed to a user comprising at least one question whereby the user selects at least one answer that corresponds to the at least one question and the at least one answer conveys information to determine the capability of the user to perform an organizational role. In another aspect, a set of answer data associated with the at least one answer is received whereby the set of answer data correlates to the capability of the user to perform a role within an organization.

Abstract: Disclosed is a platform that manages worker users in a temporary staffing environment via an artificial machine learning model. The temporary staffing platform matches available workers to available shifts/gigs. Additional features include generating provisional or near-miss matches and informing workers how to turn those near-misses into full matches, plotting a gig-career path to develop additional skills, gamify development, and automatically generate resumes. The platform generates a set of skill tags associated with each shift/gig performed by the user. Designing of resume text files by the artificial machine learning model includes procedurally generated descriptions of experience the a user has based on the recording of each shift/gig performed by the user and the skill tags associated with each recorded shift/gig, wherein a format of the resume text file is formulated by the artificial machine learning model evaluating a mix of skill tags and employers amassed by the user.

Abstract: The disclosure generally pertains to systems and methods for assigning alternative energy vehicles to travel routes based on vehicle wear-and-tear ratings. Wear-and-tear ratings may be influenced by factors such as, for example, road grade, travel speed, electric motor use, and battery use, on various travel routes. An example method for determining a wear-and-tear rating of an alternative energy vehicle may involve determining an amount of stress imposed upon an electric motor of an alternative energy vehicle due to a grade of a road on a travel route, and an amount of energy consumed from a battery of the alternative energy vehicle due to a speed of travel on the travel route. The wear-and-tear rating of the alternative energy vehicle may then be determined based on the amount of stress imposed upon the electric motor and/or the amount of energy consumed from the battery on the travel route.

Abstract: Example implementations described herein involve systems and methods that can involve extracting features from each of a plurality of time-series sensor data, the plurality of time-series sensor data associated with execution of one or more operations; clustering the extracted features into a plurality of tasks that occur from execution of the one or more operations, each of the plurality of tasks associated with a clustering identifier (ID) from the clustering; and calculating a cycle time of the cycle based on the initiation and end of the cycle recognized by referencing a cycle pattern model, wherein the cycle pattern model comprises configuration information of a cycle including a set from a plurality of the clustering IDs.

Abstract: A vegetation management system includes a computing system including a processor having an associated memory that is configured for implementing a vegetative modeler including an image analyzer and at least one 3-dimensional (3D) vegetation growth model. The vegetative modeler is for analyzing images of vegetation that is growing around electrical power lines of an electric utility including identifying locations of the vegetation relative to locations of the electrical power lines and to identify specific types of the vegetation. The 3D vegetation growth model utilizes at least the locations of the vegetation relative to the locations of the electrical power lines and the specific types of the vegetation to generate a predicted timing of encroachment of the electrical power lines by the vegetation to identify future encroachment areas. A scheduler is for scheduling vegetative maintenance of the vegetation for the future encroachment areas.

Abstract: A method of exchanging messages across a network, the method comprising receiving a resource request message from an asset controller, the resource request message comprising asset data and a resource request, analyzing the resource request message in order to select at least one resource candidate from a plurality of available resource candidates, the resource candidates having a resource for exchange with the asset, sending the resource request message to the selected at least one resource candidate, receiving a resource approval message from the at least one resource candidate, the resource approval message being indicative of an approval to supply the resource in accordance with the resource request message, and in the event that the resource approval message indicates approval to supply the resource, generating a transaction authorization message, the transaction authorization message being used to authorize a transaction to supply the resource on the basis of the resource request message.

Abstract: In some examples, user journey carbon footprint reduction may include generating, for a vehicle associated with a user, a carbon emission quota for user journey carbon footprint reduction. A predicted journey carbon emissions may be generated for the vehicle for a specified journey. Based on collaborative filtering, at least one goal-based and conditions-based recommendation may be generated for the user of the vehicle for the specified journey for the user journey carbon footprint reduction. Based on a user behavior model, a user-interface display may be generated for the specified journey for the user journey carbon footprint reduction. Further, based on the user behavior model, and real-time monitoring of the user and the vehicle, a real-time update of the user-interface display may be generated for the specified journey for the user journey carbon footprint reduction.

Abstract: Method and system for evaluating, rewarding and facilitating philanthropic works are described. Ethical accounts and points are introduced and computer-implemented fair evaluations of, and hence interchangeable rewards for, various philanthropic works that reflect different time values are provided. Automatic calculation and distribution of rewarding points from a beneficiary to not only its benefactor but also the benefactor' precious benefactors are implemented to encourage sustainable philanthropy over time. Rewarding amounts and paths are tracked explicitly for impact measurement of philanthropic works, which may be used to facilitate more effective allocation of philanthropic resources. Volunteer requesting, applying and rewarding at the level of minimum durations are enabled, and automated coordination and documentation are offered to further facilitate philanthropic endeavors.

Abstract: Embodiments include a computer implemented method for automatically identifying an issue from a help message received via a chat interface and generating a response for responding to the help message. The method can include receiving one or more response templates that each include a reference to a resource associated with a help topic. The method can also include receiving, from a second user, a help request via the chat interface of a help channel. In response to receiving the help request the method can include parsing the help request to identify a help topic, generating a help desk ticket associated with the help request and generating a response message that includes an information resource associated with the help topic, and sending the response message to the user. In response to the user viewing the information resource and selecting a user interface element, the method can include automatically closing the help desk ticket.

Abstract: Systems and methods for visually displaying instances of increased susceptibility for commission of medical errors are provided. Execution of programming instructions on a computer-readable medium causes a processor to retrieve historical workload data corresponding to environmental conditions experienced by and near misses associated with an individual or team of individuals during a first period of time from one or more data repositories. Retrieved workload data is processed to establish threshold limits for distinct working conditions represented within the workload data for the individual or team of individuals. Workload data corresponding to a second period of time is retrieved for the individual or team of individuals and compared to established threshold limits by the processor. Based on the comparison, the processor generates one or more displayable indicia indicative of the individual's or team of individuals' risk of committing a medical error due to an experienced workload.

Abstract: A system associated with determining physician attribution related to in-patient care based at least on prediction of attribution values associated with patient-physician attribution is disclosed. The system extracts clinical data associated with a patient from a first database, with the extracted clinical data comprising clinical information related to the patient and the clinical information including vector values indicative of clinical progress of the patient at various stages of treatment. The system stores the extracted clinical data in a second database and determines attribution values using the attribution manager with the attribution values being based on a predictive analysis using predetermined weights associated with the vector values. A training data set is generated based on learned weight values associated with the clinical progress of the patient. The system iteratively updates the vector values of the patient at least using a predictive analysis associated with the training data set.

Abstract: First and second target controllers implemented in a storage system are associated with respective first and second storage pools having respective first and second service level objectives. Input-output (IO) operations are received from one or more host devices and processed in the storage system, with different ones of the IO operations being directed from one or more initiators of the one or more host devices to different ones of the first and second target controllers. Separate feedback information is provided from the storage system to the one or more host devices for respective ones of the first and second target controllers, so as to permit different amounts of throttling of additional IO operations in the one or more host devices based at least in part on whether those additional IO operations are to be directed to the first target controller or the second target controller.

Abstract: Described are approaches for assigning tasks between machine resources (e.g., AI task performers, AI task validators), human resources (e.g., task performers, task validators), and/or other smart systems to facilitate collaborative text detection, text recognition, and text retrieval in order to optimize system performance along a variety of different selection criteria specifying various performant dimensions, including, but not limited to improving system efficiency, reducing task performer and/or task validator idle time, improving triage outcomes, reducing data processing loads, maintaining client confidentiality, etc., that may be associated with one or more customers.

Abstract: Technologies and techniques for operating a resource management system for medical software applications. Profile parameters of a first health care facility are received and processed to select one of a plurality stored profile data that contain profile parameters having a threshold similarity to the profile parameters for the first health care facility. A system resource manager loads resource management data associated with the selected profile data, wherein the resource management data comprises data relating to capabilities and capacities of the health care facility associated with the selected profile data. A systems intelligence manager performs predictive processing on the resource management data of the selected profile data to determine via simulation if the resource management data meets a threshold. The resource management data of the selected profile data is transmitted to the first health care facility for execution in the resource management software and updated using feedback data.

Abstract: A method and system for assessing a career profile of a candidate is disclosed. The system comprises a database configured to include a plurality of parameters and a plurality of scores respective to each parameter, a parser configured to parse the career profile to identify at least one parameter from the plurality of parameters within the career profile and an analytics engine configured to retrieve a score from the plurality of scores for the at least one parameter identified within the career profile, compute a score of at least one category based on the retrieved score, wherein the at least one category comprises the at least one parameter identified within the career profile, and provide feedback to the candidate on the career profile in accordance with the computed score of the at least one category.

Abstract: A controller is configured to set a stopping order of a plurality of vehicles, which indicates the vehicle order at a stop location in a stopping area. The controller is further configured to estimate an arrival order, which indicates the order in which the plurality of vehicles arrive at a prescribed location, based on position information of the plurality of vehicles. The controller is further configured to determine whether the arrival order differs from the stopping order The controller is further configured to control the travel of at least one vehicle from among the plurality of vehicles upon determining that the arrival order differs from the stopping order, such that the arrival order is the same as the stopping order by a time the plurality of vehicles arrive at the prescribed location.

Abstract: In some embodiments, status scores representing the status of an entity at various times are determined. Classifiers may be used to translate the status scores into status levels, and visual representations of the progression of the entity's status levels over time may be generated. In some embodiments, predictive models are used to detect outlying events and entities based on the status scores. Some predictive models may be used to predict whether an entity is an outlying candidate for a transition from one state to another state. Other predictive models may be used to predict whether an entity is an outlier relative to a group of other entities.