Abstract: Systems, apparatuses, methods, and computer program products are disclosed for managing open issues. An example method includes obtaining a dashboard access request for a portion of open issues managed by the issue management system, the issue management system storing variables associated with each open issue of the open issues; obtaining a dashboard data package based on scores for the portion of open issues, the scores indicating a severity level of the open issues of the portion of open issues and being based on the variables that are stored in the issue management system; and performing an action set using the dashboard data package to manage the portion of open issues.

Abstract: Computer-implemented methods selecting a cloud computing system for deployment of a workload are provided. Aspects include obtaining an input function that characterizes the workload and obtaining a plurality of performance models, wherein each of the plurality of performance models corresponds to one of a plurality of cloud computing systems including the cloud computing system. Aspects also include applying the input function into each of the plurality of performance models, calculating one or more of a gain, a phase shift, and a stability margin for each of the plurality of performance models, and selecting the cloud computing system from the plurality of cloud computing systems based at least in part on the one or more of the gain, the phase shift, and the stability margin.

Abstract: A computer-implemented method comprising receiving user preference information, based on the received user preference information, determining one or more user settings, processing data to determine a data condition, wherein, to determine the data condition, a plurality of alternate data inputs of different types are processed and normalized, and applied to a series of operations to generate a forecast having a degree of confidence, and the data condition is compared with third party information; providing an electronic notification indicative of the data condition to the user device, wherein the electronic notification includes the data condition compared with the third party information, a confidence indicator associated with the data condition, and a user prompt; in response to a single user input, the user device generating an instruction to execute the user request; and based on the instruction, executing the user request based on the determined one or more user settings.

Abstract: A system includes a computing platform including a hardware processor and a system memory storing a software code. The hardware processor is configured to execute the software code to track interactions with a user application during use of the user application, generate, based on tracking the interactions, interaction data identifying multiple interaction events during the use, and perform a validity assessment of the interaction data. The hardware processor is further configured to execute the software code to identify, based on the validity assessment, one or more anomalies in the interaction data, and output, based on identifying the one or more anomalies in the interaction data, one or more of the interaction events corresponding respectively to the one or more anomalies.

Abstract: In various examples, object detections of a machine learning model are leveraged to automatically generate new ground truth data for images captured at different perspectives. The machine learning model may generate a prediction of a detected object at the different perspective, and an object tracking algorithm may be used to track the object through other images in a sequence of images where the machine learning model may not have detected the object. New ground truth data may be generated as a result of the object tracking algorithms outputs, and the new ground truth data may be used to retrain or update the machine learning model, train a different machine learning model, or increase the robustness of a ground truth data set that may be used for training machine learning models from various perspectives.

Abstract: According to examples, an apparatus may include a processor and a memory on which is stored machine-readable instructions that when executed by the processor, may cause the processor to identify a first set of entities corresponding to a security incident, identify anomalies associated with the first set of entities that occurred around a predefined time period with respect to the incident, identify a second set of entities associated with the identified anomalies, identify a set of incidents that share a common entity from the second set of entities, determine a probability of likelihood that the set of incidents normally share the common entity, determine whether the determined probability of likelihood falls below a predefined threshold, and based on the determined probability of likelihood falling below the predefined threshold, output an indication that the security incident and the set of incidents are likely related.

Abstract: A display assembly with electric vehicle charging equipment includes one or more side assemblies, each connected to a structural frame and including an electronic display subassembly. An external portion of the electric vehicle charging equipment is connected to the structural frame and located rearward of the cover of each of the one or more side assemblies, where the cover is located forward of a display layer. An internal portion of the electric vehicle charging equipment is located at a cavity provided below or rearward of the cover of each of the one or more side assemblies.

Abstract: An analytics server for scalable predictive analysis for analytics as a software service in multi-tenant environment is provided. The analytics server automatically validates portability of a predictive model from a first tenant to a second tenant by comparing value distribution of parameters between data inputs of the first tenant and the second tenant. The analytics server further automatically detects source data changes over a configurable time horizon as relevant to predictive model inputs, by comparing value distribution of parameters between two data inputs from a same tenant separated by a selected time horizon.

Abstract: A system comprises an autonomous vehicle (AV) and a control device operably coupled with the AV. The control device detects a series of events within a threshold period of time, where a number of series of events in the series of events is above a threshold number. The series of events taken in the aggregate within the threshold period of time deviates from a normalcy mode. The normalcy mode comprises events that are expected to the encountered by the AV. The control device determines whether the series of events corresponds to a malicious event, where the malicious event indicates tampering with the AV. In response to determining that the series of events corresponds to the malicious event, the series of events are escalated to be addressed.

Abstract: A method for managing pool device resources, the method comprising obtaining, by a resource use manager, a plurality of data points, generating a resource prediction model based on the plurality of data points, and initiating access to a PCI bus device operating on a pool device using a virtual switch operating on a second pool device based on the resource prediction model.

Abstract: A sequential data analysis apparatus extracts a pattern of two or more sets of items based on an appearance frequency of each of different sets of items in first sequential data, selects a pattern of two or more sets of items based on an appearance frequency of a sub-pattern formed of a portion of the extracted pattern, creates a related pattern including the same last set of items as and the other sets of items different from the selected characteristic pattern, calculates an evaluation value of the related pattern, creates a prediction model by organizing data of the characteristic pattern and the related pattern, and applies second sequential data to the prediction model to determine a result which the second sequential data is likely to lead to.

Abstract: The present disclosure provides methods and an apparatuses for building a data identification model. One exemplary method for building a data identification model includes: performing logistic regression training using training samples to obtain a first model, the training samples comprising positive and negative samples; sampling the training samples proportionally to obtain a first training sample set; identifying the positive samples using the first model, and selecting a second training sample set from positive samples that have identification results after being identified using the first model; and performing Deep Neural Networks (DNN) training using the first training sample set and the second training sample set to obtain a final data identification model. The methods and the apparatuses of the present disclosure improve the stability of data identification models.

Abstract: A charging control apparatus includes: a prediction unit configured to predict a change in temperature of a battery over time during charging; a calculation unit configured to calculate, based on the change in temperature over time predicted by the prediction unit, a degree of influence that the battery receives from the temperature of the battery exceeding a predetermined upper-limit temperature control value; and a charging control unit configured to allow the temperature of the battery to exceed the upper-limit temperature and charge the battery when the degree of influence is less than a predetermined reference value.

Abstract: A system for predictive analysis and/or process control, preferably including one or more communication and/or computing systems, and optionally including one or more entities and/or sensors. A method for predictive analysis and/or machine operation, preferably including receiving entity data and determining one or more latent features, and optionally including determining one or more response reconstructions, determining a processed representation of the entity data, determining entity information, and/or acting based on entity information.

Abstract: This invention implements a work system high in flexibility and speedy system development. The work system includes a plurality of modules each having software for work which performs predetermined in-module processing, and a service base unit which inputs and outputs event information to and from the modules. The event information includes an identifier and a payload. The service base unit has a function of receiving the event information from any of the modules, and a function of transferring the event information to the other module. The other module to which the event information is transferred determines based on the identifier included in the transferred event information whether the in-module processing is performed within its own module.

Abstract: A computer-implemented method comprising receiving user preference information, based on the received user preference information, determining one or more user settings, processing data to determine a data condition, wherein, to determine the data condition, a plurality of alternate data inputs of different types are processed and normalized, and applied to a series of operations to generate a forecast having a degree of confidence, and the data condition is compared with third party information; providing an electronic notification indicative of the data condition to the user device, wherein the electronic notification includes the data condition compared with the third party information, a confidence indicator associated with the data condition, and a user prompt; in response to a single user input, the user device generating an instruction to execute the user request; and based on the instruction, executing the user request based on the determined one or more user settings.

Abstract: Embodiments include predicting transactions by an entity and identifying promotions to offer the entity. Aspects include parsing a plurality of event records corresponding to a plurality of entities respectively. Aspects also include identifying a sequence of events corresponding to the entity and discretizing time durations and event values of the sequence of events into discrete symbolic values. Aspects further include generating a temporal pattern of events in the sequence of events, the temporal pattern including a sequence of transaction-symbols representative of the time duration and the event value of the events in the sequence of events of the entity and predicting a next transaction based on the temporal pattern.

Abstract: Embodiments include predicting transactions by an entity and identifying promotions to offer the entity. Aspects include parsing a plurality of event records corresponding to a plurality of entities respectively. Aspects also include identifying a sequence of events corresponding to the entity and discretizing time intervals and event values of the sequence of events into discrete symbolic values. Aspects further include generating a temporal pattern of events in the sequence of events, the temporal pattern including a sequence of transaction-symbols representative of the time interval and the event value of the events in the sequence of events of the entity and predicting a next transaction based on the temporal pattern.

Abstract: Some embodiments provide a mapping application that displays a transit map including a group of transit lines. The mapping application receives a request to display a transit route in the transit map. The mapping application also, in response to the received request, displays the transit route by modifying portions of transit lines along the route to emphasize the portions of the transit lines while modifying other transit lines not along the route to de-emphasize the transit lines not along the route.

Abstract: The disclosed embodiments illustrate a method for real time management of transportation services. The method includes determining a discrete control process with respect to a plurality of states of a vehicle. Each state in the plurality of states corresponds to a station and a count of vacant seats in the vehicle at the station. A set of rules is generated to maximize a key performance parameter of the vehicle, based on at least the determined discrete control process. A valuation parameter is determined, in real time, for one or more vacant seats in the vehicle at each of one or more subsequent stations based on the generated set of rules. The determined valuation parameter for the one or more vacant seats corresponding to each of the one or more subsequent stations is transmitted to a plurality of mobile computing devices associated with a plurality of commuters.

Abstract: A computer implemented system for automating the generation of an analytic model includes a processor configured to process a plurality of data sets. Each data set includes values for a plurality of variables. A time-stamping module is configured to derive values for a plurality of elapsed-time variables for each data set, and the plurality of variables and plurality of elapsed-time variables are included in a plurality of model variables. A model generator is configured to create a plurality of comparison analytic models each based on a different subset of model variables. Each comparison analytic model is configured to operate on new data sets associated with current leads, and to output a likelihood of successfully closing an associated transaction. A model testing module is configured to select an operational analytic model from among the comparison analytic models based on a quality metric.

Abstract: Systems are provided to estimate autoregressive moving average (ARMA) models using maximum likelihood estimation and analytical derivatives, and to use such models for forecasting. The evaluation of the analytical derivatives during estimation of the model parameters may be performed using a state space representation with certain characteristics. An ARMA model estimated using maximum likelihood estimation, analytical derivatives, and the state space representation with certain characteristics can be used to forecast/predict values that are likely to occur in the future, given some set of previously-occurring values.

Abstract: Geographical regions are each characterized using a distribution of terms, tags, etc. A model may be generated that identifies characteristics of each geographic region. The geographic regions may be organized using a geographical hierarchical model.

Abstract: A system includes a normal behavior characterization module configured to receive values for a first metric of a plurality of metrics and generate a baseline profile indicating normal behavior of the first metric based on the received values. The system also includes an anomaly identification module configured to identify an anomaly in response to present values of the metric deviating outside the baseline profile. The system also includes an anomaly behavior characterization module configured to analyze a plurality of prior anomalies identified by the anomaly identification module and develop a model of the anomalies of the first metric. The system also includes an anomaly scoring module configured to determine a first score for a present anomaly detected by the anomaly identification module for the first metric. The first score is based on characteristics of the present anomaly and the model of the anomalies of the first metric.

Abstract: Disclosed is a time-series management device capable of filtering time-series data having a possibility of matching a specified search pattern and reading in the data from a storage device when performing a time-series analysis. A data accumulation unit (120) creates a time-series index having a feature value of a data series calculated at a specific regular time interval. In addition, a data search unit (130) makes a decision as to the feature value for each regular time interval included in the time-series index using an evaluation formula of a specified search condition, identifies a time period of a complying data series group, and performs a time-series analysis for only the data series of the identified time period.

Abstract: Methods for processing data. A first spacetime event observation is received. A second spacetime event observation is received. A singularity of presence indicator is received for a zone of space and a range of time corresponding to one or more of: the first spacetime event observation and the second spacetime event observation. It is determined whether the first spacetime event observation and the second spacetime event observation belong to a same entity using the singularity of presence indicator.

Abstract: A mattress age indicating device (10) includes an enclosure (20) and an indicating assembly (30) contained within the enclosure (20). The age indicating device (10) may be configured to present an indication related to the mattress's age and may be coupled to the mattress (2) or other bedding or seating product.

Abstract: An apparatus, and related method, for identifying one or more association variables is described. The apparatus includes at least one processor, at least one memory, and at least one program module stored in the memory configured to be executed by the processor. The program module includes instructions for selecting a subset of temporal onsets in a set of temporal onsets, instructions for determining a statistical relationship between the subset and a pattern of occurrence of a variable, and instructions for identifying the variable as an association variable in accordance with the statistical relationship. The subset includes one or more first temporal onsets corresponding to one or more instances of an event, and the set of temporal onsets includes the subset of temporal onsets and one or more second temporal onsets corresponding to one or more instances of a reoccurrence event.

Abstract: An apparatus for determining a future outage window in which to perform work on a server may include an input for receiving historical performance data about at least one server, a non-transitory memory and a processor communicatively coupled to the input and the memory. The processor may be configured to use instructions stored in the memory to predict one or more likely future time windows to be recommended as possible outage windows in which to perform work on the server. The processor may analyze historical performance data about the at least one server to determine one or more historical time windows corresponding to low CPU utilization of the at least one server. In some cases, the processor may then predict one or more future time windows to be recommended for use as the outage window using, at least in part, the determined historical time windows.

Abstract: A method for predicting the duration of a future charging process for a vehicle battery. The method comprises estimating a future charge amount of the battery corresponding to the start of the future charging process. The method further comprises estimating a future temperature of the battery. The method still further comprises determining a future charging power or a characteristic thereof to be applied to the battery during the future charging process, wherein the future charging power or characteristic thereof is based on the estimated future charge amount and the estimated future temperature and is representative of a charging amount or characteristic thereof that will maintain the temperature of the battery at or below a threshold temperature during the future charging process. The method still further comprises predicting a duration of the future charging process based on the estimated future charge amount and the determined future charging power or characteristic thereof.

Abstract: A method and system of detecting the activity of “bots” in an online community, by measuring the time elapsed between user actions and comparing this time to a timespan established as normal for users performing the same user actions without the assistance of bots. The timespan may be adjusted when other suspicion characteristics are detected. When detecting actions suspected to be bot-assisted, the method and system respond by executing one or more response instructions against the user suspected of using the bot, with the aim of preventing further bot activity. The response instructions are stored by associating them with a type of user action and a total number of suspect user actions. As a result, the response instructions may be set to increase in severity with each additional suspect act by a user.

Abstract: A method of adapting an event processing component. The method comprises designating an event processing component having a plurality of event processing agents which carry out a plurality of rules to process a plurality of events, selecting at least one rules correctness requirement, and automatically adjusting, using a processor, the plurality of event processing rules to comply with the at least one correctness requirement.

Abstract: A requirements testing system facilitates the review and analysis of requirement statements for software applications. The requirements testing system generates test artifacts from the requirement statements. The test artifacts characterize the requirements statements to provide valuable analysis information that aids understanding whether the requirement statements are testable, what the intentions of the requirement statements are, and other useful analysis information. Because the system generates the analysis information from the requirement statements, the system provides benefits in terms of early feedback along the software application development timeline.

Abstract: Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyzes on such extracted content and present graphical representations of such analyzes on a display of a client device.

Abstract: A method and system are disclosed for determining relative connectedness from temporal data. A user iterates through a list of items implemented on a mobile device. As each item on the list is located it is marked to generate a corresponding timestamp. The timestamps are then used to generate a timestamped list, which in turn is processed to determine the amount of elapsed time between each item on the list being located. The timestamped list data is then processed to generate relative connectedness data, which in turn is processed to generate a relative connectedness graph. The relative connectedness graph is then processed to assign coordinates to each item on the list. In turn, the coordinates are used to generate a map of the items.

Abstract: A method for maintaining an asset. The method receives data associated with an one asset and other assets to which the one asset is directly or indirectly physically connected. The method determines, based on the received data, a dependency between the one asset and one or more of the other assets. The method predicts, based on the determined dependency, a failure of the one asset within a future time period.

Abstract: Techniques, systems, and articles of manufacture for determining related data points from multi-modal inputs. A method includes collecting multiple items of multi-modal data comprising at least one dimension from multiple data sources, wherein said at least one dimension comprises a geographic dimension, a temporal dimension and/or an event-related dimension, determining a window of relevance for each of the multiple items of multi-modal data with respect to the at least one dimension, and identifying two or more of the multiple items of multi-modal data as related, by determining an overlap of the window of relevance corresponding to each of the two or more items of multi-modal data with respect to the at least one dimension.

Abstract: The disclosure provides a method and system for elastic computing that includes the steps of presenting an interface for user entry of a threshold upper limit for compute pool consumption, a threshold lower limit for compute pool consumption, and a threshold time for the out of range condition. The policy engine of the controller node monitors consumption and expands or shrinks the compute pool.

Abstract: A “Compatibility Tester” extracts observable behaviors from different system implementations (e.g., software, operating systems, device drivers, hardware interfaces, etc.), then performs compatibility testing via comparisons of the extracted behaviors. Traces (e.g., bus level signals between controllers and hardware devices or commands between software components) representing observable behaviors of different implementations of a system are captured. Temporal and structural rules are then mined from these traces. The mined rules (or a model constructed from those rules) are used by a “Rule Checking” process that determines whether reference rules (mined from a known compatible system) are compatible with rules mined from test traces of a second system. Invalid rules are flagged as behavioral compatibility bugs.

Abstract: A system and method for implementing a learning model for predicting the geographic location of an Internet Protocol (IP) address are disclosed. A particular embodiment of the system and method includes receiving a model to predict a geographic coordinates position of an Internet Protocol (IP) address, the model including one or more parameters and one or more variables associated with coordinates of the IP address and corresponding information associated with the IP address; receiving training data including a plurality of pairs of coordinates of a target IP address and corresponding information associated with the target IP address; determining, by use of a processor, the one or more parameters based on the training data and the model; and returning a result including information indicative of the determined parameters.

Abstract: A technique includes fitting an autoregressive integrated moving average (ARIMA) model to time-series data. The technique further includes the computation of autoregression coefficients from the ARIMA model applied to the time-series data. The autoregression coefficients may be usable for data classification purposes.

Abstract: A mobile storage system is disclosed that in one aspect identifies a geographical location change of a user, such as movement from a first geographical location to a second geographical location. In response, the mobile storage system may move the user's information to a storage device associated with the second geographical location so that the user's information may be accessed by the user more efficiently.

Abstract: A computer implemented method includes determining whether a time of day corresponds to a charging window, responsive to a determination that a vehicle is in a non-charging state. The method also includes retrieving a start time and charge requirement for an upcoming journey. The method further includes determining if sufficient time remains to charge a vehicle to the charge requirement, responsive to a determination that the time of day corresponds to the charging window. Also, the method includes alerting a user to the non-charging state, responsive to a determination that insufficient time remains to charge the vehicle to the charge requirement.

Abstract: Methods and devices for statistical determination of medication dosage level such as bolus amount based on contextual information are provided.

Abstract: In one embodiment, techniques are shown and described relating to traffic-based inference of influence domains in a network by using learning machines. In particular, in one embodiment, a management device computes a time-based traffic matrix indicating traffic between pairs of transmitter and receiver nodes in a computer network, and also determines a time-based quality parameter for a particular node in the computer network. By correlating the time-based traffic matrix and time-based quality parameter for the particular node, the device may then determine an influence of particular traffic of the traffic matrix on the particular node.

Abstract: An information acquiring apparatus acquires, when a travel object such as a traveler travels with transportation, passage time at which the travel object passes through each passage point at a departure/arrival facility, transportation specifying information indicating transportation, situation information indicating a situation and so forth. The travel process prediction apparatus stores the acquired information in an associated manner, and obtains a regression equation representing the relationship between items included in the transportation specifying information or situation information and passage time at a specific passage point, elapsed time while the travel object passes through two specific passage points or a result of comparison between the passage time and boarding completion time.

Abstract: A multi-social network discovery system and method enables users to select multiple social networks comprising activity streams and to receive recommendations sourced from the selected multiple social networks. The multi-social network discovery system and method generates affinity values based on inferred affinity levels between topics, which may be associated with tags, and objects that are associated with the activity streams. The inferred affinity values may be derived from usage behaviors such as tagging and/or based on an automatic analysis of the content of the objects. The affinity values inform the selection of the objects to be recommended to a user, and the selection may be further informed by inferred affinity levels between the user and the topics. The recommendations may be tuned by the user through application of a recommendation tuning control.

Abstract: Embodiments of the present invention provide a system, method, and program product for recommending a digital publication. A computing device identifies a time interval for consuming a digital publication, based on schedule information in an electronic calendar. The computing device determines, based on characteristics of the time interval and a criteria, a digital publication, from a plurality of digital publications, for human consumption within the identified time interval.

Abstract: Some embodiments of a simulation and test framework for a rule engine have been presented. In one embodiment, a simulator runs a simulation in a time-aware environment. A rule engine, coupled to the simulator, may execute a set of business logic in response to the simulation in order to test behavior of the business logic. The business logic may include rules, workflow, and event processing.

Abstract: A method includes receiving search queries. Images are generated that represent the volume of each search query relative to all search queries over a period of time. The images are processed to generate wavelets for each image. Related queries having similar increases or decreases in volume are identified by comparing at least some of the wavelets corresponding to a first query to wavelets corresponding to other queries.