Abstract: Examples of techniques for anomaly detection with feedback are described. An instance includes a technique is receiving a plurality of unlabeled data points from an input stream; performing anomaly detection on a point of the unlabeled data points using an anomaly detection engine; pre-processing the unlabeled data point that was subjected to anomaly detection; classifying the pre-processed unlabeled data point; determining the anomaly detection was not proper based on a comparison of a result of the anomaly detection and a result of the classifying of the pre-processed unlabeled data point; and in response to determining the anomaly detection was not proper, providing feedback to the anomaly detection engine to change at least one emphasis used in anomaly detection.

Abstract: A research analytics system and method, includes an Internet-based data storage service maintaining, using an integrated database scheme, standardized research process flows, organizational tasks, and research outcomes for a plurality of research programs. The system maintains definitions of research performance indicators, identifies targets for the research performance indicators that are aligned with goals associated with a research organization, maps performance-related data from various data sources to the integrated database scheme and stores the standardized research process flows, the organizational tasks, and the research outcomes, grouped by the research programs.

Abstract: Systems and methods for treating a subject are provided. A first dataset comprising timestamped autonomous glucose measurements of the subject over a first time course is obtained. A second dataset, associated with a standing insulin regimen for the subject over the first time course and comprising insulin medicament records, is also obtained. Each record comprises a timestamped injection event including an amount and type of insulin medicament injected into the subject by an insulin pen. The first and second datasets serve to calculate a glycaemic risk measure and an insulin sensitivity factor of the subject during the first time course, which are used to obtain a basal titration schedule and a fasting blood glucose profile model over a subsequent second time course for the subject. The model predicts the fasting blood glucose level of the subject based upon amounts of basal insulin medicament injected into the subject.

Abstract: The invention shows how to use noise-like perturbations to improve the speed and accuracy of Markov Chain Monte Carlo (MCMC) estimates and large-scale optimization, simulated annealing optimization, and quantum annealing for large-scale optimization.

Abstract: A data collection apparatus includes: a collection unit which collects data relating to respective vehicles from vehicular devices installed in the respective vehicles; a reception unit which receives a data collection condition specified by a user; an analysis unit which calculates a probability of occurrence of an event for collection of data specified in the collection condition based on past data collection results; and a providing unit which provides the user with information that is based on the probability of occurrence calculated by the analysis unit.

Abstract: One embodiment can provide a system for estimating useful life of a load-bearing structure. During operation, the system can perform a degradation measurement on the structure to obtain degradation data for a predetermined time interval, apply a constraint convex regression model to the degradation data, estimate a total useful life (TUL) of the structure based on outputs of the constraint convex regression model, and predicting a remaining useful life (RUL) based on the TUL and a current time.

Abstract: Ensemble classification algorithms having subclass resolution are disclosed. An example disclosed apparatus includes a fingerprint generator to generate a fingerprint of class probabilities of each of a plurality of samples, a distribution creator to create a distribution of the samples based on the generated fingerprints, and a distribution applicator to apply the distribution to a population to predict sub-class probabilities of each of the population.

Abstract: A plurality of basic simulations independent of one another are carried out, which determine respective remaining service life predictions for the machine. The remaining service life predictions and characteristic data are fed to a neural network, which outputs weights for the remaining service life predictions. A final prediction is calculated from the remaining service life predictions by weighting the remaining service life predictions relative to one another. A hybrid model is produced, which results from the combination of the basic simulations with the neural network. The remaining service life can be predicted not only for a small number of machines for which a specific simulation model has been manually created. The hybrid model enables condition monitoring for any further types and configurations of machines that merely belong to the same machine class. The basic simulations can therefore also be applied to previously unknown machines.

Abstract: Embodiments of the invention are directed to techniques for detecting anomalous values in data streams using forecasting models. In some embodiments, a computer can receive a value of a data stream comprising a plurality of data values, where the received value corresponds to a time interval and previously received values each correspond to a previous time interval. Models can be selected based on the time interval, where each of the models has a different periodicity. For each of the selected models, the computer may generate a score by generating a prediction value based on the model and generating the score based on the prediction value and the received value. A final score can then be generated based on the scores. Next, a score threshold can be generated. If the final score exceeds the score threshold, the computer may generate a notification that indicates that the data value is an anomaly.

Abstract: An approach is provided that detects when multiple apps are being displayed on a display screen with each of the apps having any number of user interface controls. A set of user interface controls is identified from the user interface controls being displayed. The identified set of user interface controls have an increased display preference. The identified set of user interface controls are enlarged on the display screen making such controls easier to read and select.

Abstract: A log-to-metrics transformation system includes a log-to-metrics application executing on a processor. The log-to-metrics transformation system receives a format associated with machine data, and further receives, via a first graphical control, a first set of metric identifiers corresponding to a first set of metrics associated with the machine data. The log-to-metrics transformation system generates a first set of mappings between the first set of metric identifiers and a first set of field values included in the machine data. The log-to-metrics transformation system stores the first set of mappings and an association with the format of the machine data. The log-to-metrics transformation system, based on the first set of mappings, causes the first set of field values to be extracted from the machine data. Further, a first metric included in the first set of metrics is determined based on at least a portion of the first set of field values.

Abstract: Disclosed herein are computer-implemented methods and systems for forecasting security ratings for an entity. The methods and systems can include generating a plurality of simulated instantiations of a security scenario for the entity, in which the security scenario characterized by a plurality of security events associated with at least one event type. The methods and systems can further include determining a security rating for each instantiation of the plurality of instantiations; and generating a forecast cone based on the determined security ratings for the plurality of instantiations. In some examples, for each event type of the at least one event type, the methods and systems can include determining a rate, duration, and/or temporal placement of the security events associated with the event type over a forecasting period.

Abstract: This application relates to apparatus and methods for identifying anomalies within a time series. In some examples, a computing device receives sales data identifying a sale of at least one item, and aggregates the received data in a database. The computing device may generate a plurality of time series based on the aggregated sales data. The computing device may extract features from the plurality of time series, and generate an alerting algorithm that is based on clusters of the extracted features. The computing device may apply the alerting algorithm to a time series generated from received sales data to determine whether the time series is an anomaly. Based on the determination, the computing device may generate and transmit anomaly data identifying whether the time series is an anomaly, such as to another computing device.

Abstract: Described is a system for predicting future social activity. The system extracts social activities from spatial-temporal social network data collected in a first time period ranging from hours to days to capture spatial structures of social activities in a graph network representation. A graph matching technique is applied over a set of spatial-temporal social network data collected in a second time period ranging from weeks to months to capture temporal structures of the social activities. A spatial-temporal structure of each social activity is represented as an activity core, where each activity core is defined as active nodes that participate in the social activity with a frequency over a predetermined threshold over the second time period. For each activity core, the system computes statistics of the social activity and uses the statistics to generate a prediction of future behaviors of the social activity.

Abstract: A reading device includes wireless slave devices that communicate via a multihop wireless network, a measuring unit that measures the state of an inspection target to generate measurement data, a measurement data analysis unit, and a failure cause analysis unit that analyzes a failure cause when the analysis of the failure cause analysis unit fails. The reading device transmits the measurement data to the data collecting device by associating the measurement data with failure cause information. The data collecting device includes a wireless master device, a measurement data acquisition unit that acquires measurement data from each reading device, a recording unit that records the measurement data when the measurement data is not associated with failure cause information, and a retry control unit that retries data acquisition according to the type of the failure cause when the measurement data is associated with the failure cause information.

Abstract: A media curation system configured to perform operations that include, capturing an image at a client device, wherein the image includes a depiction of an object, identifying an object category of the object based on the depiction of the object within the image, accessing media content associated with the object category within a media repository, generating a presentation of the media content, and causing display of the presentation of the media content within the image at the client device.

Abstract: A video packaging and origination service can process requests for content segments from requesting user devices. The video packaging and origination service can receive multiple inputs from content sources and determine events in the depictions of the inputs. The video packaging and origination service can generate content streams from the detected events. The content streams can be provided according to subscription requests.

Abstract: Techniques for training and evaluating seasonal forecasting models are disclosed. In some embodiments, a network service generates, in memory, a set of data structures that separate sample values by season type and season space. The set of data structures may include a first set of clusters corresponding to different season types in the first season space and a second set of clusters corresponding to different season types in the second season space. The network service merges two or more clusters the first set and/or second set of clusters. Clusters from the first set are not merged with clusters from the second set. After merging the clusters, the network service determines a trend pattern for each of the remaining clusters in the first and second set of clusters. The network service then generates a forecast for a metric of a computing resource based on the trend patterns for each remaining cluster.

Abstract: In one embodiment, a device obtains temperature and utilization measurements for a set of network interface transceivers in a network. The device computes, for each of the transceivers, a correlation coefficient between its temperature and utilization measurements. The device applies a k-nearest neighbor classifier to the correlation coefficients, to predict a correlation coefficient. The device uses the predicted correlation coefficient to determine an impact of temperature on utilization of a particular network interface transceiver. The device initiates a mitigation action, when the determined impact of temperature on the utilization of the particular network interface transceiver exceeds a predefined threshold.

Abstract: A failure positioning method for positioning leakage defect cell between the gate and the active region of transistor cells arranged in an array. The positioning method includes the steps of: measuring the resistance between a first metal wire connecting the active regions and a second metal wire connecting the gates, and positioning a first region where the defect cell is located by resistance ratio; electrically isolating the active region contact holes and the gate contact holes from each other; shorting the gate contact holes in the first region; and performing active voltage contrast analysis on the plurality of columns of transistor cells in the first region to position the leakage defect in the first region by comparing the voltage contrast images. With the positioning method, the transistor cell having a leakage defect at nA level may be accurately found from a plurality of transistor cells arranged in an array.

Abstract: Securing a network device by forecasting an attack event using a recurrent neural network. In one embodiment, a method may include collecting event sequences of events that occurred on multiple network devices, generating training sequences, validation sequences, and test sequences from the event sequences, training a recurrent neural network using the training sequences, the validation sequences, and the test sequences, collecting an event sequence of the most recent events that occurred on a target network device, forecasting, using the recurrent neural network and based on the event sequence of the most recent events that occurred on the target network device, the next event that will occur on the target network device, and in response to the forecasted next event being an attack event, performing a security action to prevent harm to the target network device from the attack event.

Abstract: An evaluating apparatus includes a notifying unit and an evaluating unit. The notifying unit notifies a terminal device of a reply request. The evaluating unit calculates subjective data which expresses a subjective intuition of a target person by an evaluation value, from objective data which is calculated based on plural touch operations performed by the target person on the terminal device which is notified of the reply request in consideration of intervals between the touch operations.

Abstract: A recommendation engine for works of literature uses patterns of flow and element similarities for scoring a first user-rated work of literature against one or more recommendation candidate works of literature. Cluster models are created using meta-data modeling the works of literature, the meta-data having literary element categories and instances within each category. Each instance is described by an index value (position in the literature) and significance value (e.g. weight or significance). Cluster finding process(es) invoked for each instance in each category find Similarity Concept clusters and Consistency Trend clusters, which are recorded into the cluster models representing each work of literature. The cluster model can be printed or displayed so that a user can visually understand the ebb and flow of each literary element in the literature, and may be digitally compared to other cluster models of other works of literature for potential recommendation to a user.

Abstract: Certain aspects of the disclosure are directed to providing aggregated context information in a data communications network. According to a specific example, a data communications server can operate to provide user-data communications sessions each involving a client-specific endpoint device and another participating endpoint device, where the client-specific endpoint device is associated with a client-entity among a plurality of remotely-situated client entities. User-data communications between the client-specific endpoint device and the other participating endpoint device can be retrieved from a plurality of disparate interconnected data communications systems, where the data communications systems each provide at least one data communications service to the client entity on a subscription basis.

Abstract: A method for operating a data processing system to analyze data sets for groupings and a computer readable medium having instructions to execute that method are disclosed. The method includes causing the data processing system to receive a plurality of data sets, each data set including a plurality of values characterized by a statistical distribution and a label. The method also includes causing the data processing system to compute a plurality of statistical parameters for each of the plurality of data sets, to generate a data set vector having components equal to the plurality of statistical parameters for each of the plurality of data sets, to assign each data set to a cluster based on the data set vectors using a clustering algorithm, and to generate a display of the statistical distributions as a function of the labels in which the statistical distributions belonging to the same cluster are grouped together.

Abstract: An embodiment provides a method, including: obtaining, from a multi-sensor pipe inspection robot that traverses through the interior of a pipe, sensor data, such as structured laser light sensor data and Light Detection and Ranging (LIDAR) sensor data, for the interior of the pipe; identifying a pipe feature using one or more of the sensor data types; selecting an image processing technique based on the pipe feature identified using a stored association between the pipe feature and an image processing technique; and forming an image of the interior of the pipe by implementing the selected image processing technique. Other embodiments are described and claimed.

Abstract: A system receives a time series of data values from instrumented software executing on an external system. Each data value corresponds to a metric of the external system. The system stores a level value representing a current estimate of the time series and a trend value representing a trend in the time series. The level and trend values are based on data in a window having a trailing value. In response to receiving a most recent value, the system updates the level value and the trend value to add an influence of the most recent value and remove an influence of the trailing value. The system forecasts based on the updated level and trend values, and in response to determining that the forecast indicates the potential resource shortage event, takes action.

Abstract: Provided is a method for forecasting future operating states of machine components, which includes the respective machine component considered, a parameter that is selected that is representative of the state of the machine component, the parameter is recorded as a measured value during ongoing use of the machine component and, taking into account the use case for which the machine component is used, the measured value recorded is fed into an automatically running process for finding a recommendation for action. A system is also disclosed.

Abstract: An intersection management system (IMS) may receive one or more traversing requests from one or more Connected Autonomous Vehicles (CAVs). The IMS may determine a solution space for each of the one or more traversing requests in a space-time resource model of the intersection, find a CAV trajectory allocation in the space-time resource model for each of the one or more traversing requests. The IMS may send an approved reservation to each CAV corresponding to each of the one or more CAV trajectory allocations that have been found. Each of the one or more CAVs may, when an approved reservation corresponding to the CAV may have been received from the IMS, move through the intersection zone as specified in the approved reservation.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in a search system supported by or configured with search servers, applications or platforms. The systems interact to identify and retrieve data across platforms, which data can be used to improve the quality of results data used in processing interactions between or among processors in such systems. The disclosed systems and methods provide an incident management and response software (IMRS) system that accelerates security incident detection and response. The IMRS provides an adaptive, event-driven workflow automation platform that can be customized to suit a large range of infrastructure environments and asset classes. The IMRS encompasses the management, automation and orchestration technologies applied in the detection and remediation of a computer network security incident (e.g., malware, advanced persistent threat, insider crime, denial of service attack, and the like).

Abstract: Systems, methods, non-transitory computer readable media can be configured to accessing a target sensor log corresponding to a first machine; accessing one or more prior sensor logs corresponding to the first machine and one or more prior sensor logs corresponding to a plurality of second machines which are of the same type as the first machine; accessing a plurality of computer readable logs corresponding to the first machine and the second machines, the computer readable logs for each second machine comprising a maintenance log comprising a plurality of maintenance task objects, each maintenance task object comprising a time and a maintenance task type; determining a set of statistical metrics characterising a difference between the target sensor log and each prior sensor log; selecting a sub-set of the prior sensor logs in dependence upon the statistical metrics; analysing the maintenance logs to correlate each prior sensor log included in the subset to one or more correlated maintenance tasks; selecting a

Abstract: A computational system for solving a non-deterministic polynomial problem, involving a parellel processor operable by a set of self-updatable executable instructions storable on a non-transient memory device and configuring the parallel processor to interface with an information acquisition program, heuristically acquire information, through the information acquisition program, via a first transference and a second transference, whereby heuristic information is acquired, parametrically evolve the heuristic information, whereby parametrically evolved heuristic information is provided, reuse the parametrically evolved heuristic information to further heuristically acquire information, whereby iterative parametrically evolved heuristic information is provided, and self-update the set of executable instructions based on the iterative parametrically evolved heuristic information, whereby a self-updated set of executable instructions is provided, whereby the self-updated set of executable instructions facilitates i

Abstract: Disclosed is a technique of determining a driver's tension level (tension state degree) in vehicle driving in detail with a simple configuration. According to the technique, a nonlinear analyzing unit 110 of a driver's tension level determining apparatus 100 determining the tension level in driving of a driver acquires the driving operation amounts relating to driving operations of a driver (the operation amounts relating to operations of an accelerator pedal, a brake pedal, a handle, and the like), and then calculates the Lyapunov exponents about the driving operation amounts by performing nonlinear analysis processing. A frequency spectrum analyzing unit 120 calculates the power spectral density of time series data of the Lyapunov exponents, and then calculates an integrated value of a predetermined low frequency band in the calculated power spectral density.

Abstract: In a computer-implemented method for visualization of anomalies in time series data on a graphical user interface, a plurality of time series data is dynamically displayed in a graph of the graphical user interface, the plurality of time series data including data points represented as numerical measurements. An indication that a time series data of the plurality of time series data includes an anomaly is received. Responsive to receiving the indication that the time series data of the plurality of time series data includes an anomaly, a visualization of at least a region of the time series data including the anomaly is changed.

Abstract: An object of the present invention is to provide an index generating method and index generating apparatus capable of accurately and stably generating an index for measuring a width of a subject, and a measuring method capable of accurately and stably measuring a width of a subject. An index generating method according to one embodiment of the present invention includes: an image input step of inputting an image obtained by imaging a linear subject; a density distribution acquiring step of acquiring, from the input image, a plurality of density distributions along a direction orthogonal to a width direction of the linear subject, which are density distributions in the width direction of the linear subject; a function calculating step of calculating a probability distribution function corresponding to the acquired plurality of density distributions; and an index generating step of generating an index indicating a width of the subject based on the calculated probability distribution function.

Abstract: Various examples are directed to systems and methods for network virtualization for web applications. For example, a WAN controller may receive from a backend query processor, a first tenant user query table that describes a first set of query types for a first user. The first set of query types may comprises a first query type having a first computational weight and a second query type having a second computational weight less than the first computational weight. The WAN controller may determine that a first network path to a web application data center is less congested that a second network path to the web application data center. The WAN controller may send a first flow entry to a first network appliance on the first network path instructing the first network appliance on the first network path to send packets associated with queries of the first set of query types to a second network appliance on the first network path.

Abstract: A computer-implemented method for optimizing research of an abstracted issue with a plurality of analytics engines is described. The method includes receiving a problem report at an analytics engine controller. The problem report includes symptoms of a problem in a computing system. The analytics engine forwards the problem report to a research optimization engine that abstracts one or more issues associated with the problem based on the symptoms of the problem. The research optimization engine then obtains anomaly research data for one or more of diagnosing the problem and fixing the problem. The anomaly research data is based on the one or more abstracted issues. The research optimization engine associates the abstracted issues with corresponding portions of the anomaly research data, then assigns the abstracted issues and corresponding portions of the anomaly research data to at least one of the plurality of analytics engines.

Abstract: Sensor data is received from a plurality of sensors contained in an electrical submersible pump (ESP) deployed in a well hole. An early indication of an ESP failure that is imminent is determined in real time using a pattern recognition methodology based on the sensor data and a pattern detection model that correlates historical ESP failures with historical sensor readings. A notification of the imminence of the ESP failure is provided.

Abstract: The present disclosure pertains to novel systems and methods that incorporate advanced inference algorithms can be developed to detect floating neutrals using phasor measurements. In one aspect, the present disclosure relates to the use of phasor measurements to detect and localize floating neutrals in a distributed power network.

Abstract: Techniques for qualifying for use in an overall manufacturing process items produced by a bulk manufacturing process that has a plurality of batch effects are presented. The techniques can include obtaining a collection of items produced by a bulk manufacturing process that has a plurality of batch effects; measuring a quantifiable property of a sample of items from the collection of items; developing a linear mixed model for the quantifiable property based on the measuring; determining a statistical process control standard deviation for the collection of items based on the linear mixed model; computing a statistical process control parameter from the statistical process control standard deviation; determining that at least a portion of the collection of items conform to the statistical process control parameter; accepting at least a portion of the collection of items; and using at least a portion of the collection of items in the overall manufacturing process.

Abstract: Methods, systems, and computer program products for measuring effective utilization of a service practitioner for ticket resolution via a wearable device are provided herein. A computer-implemented method includes determining one or more keywords related to multiple information technology action item categories; matching the determined keywords to a set of keystroke data, wherein the keystroke data are captured (i) by a remote device associated with an information technology action item practitioner (ii) over a fixed duration of time; computing, based on said matching the amount of the fixed duration of time spent by the information technology action item practitioner attempting to resolve an information technology action item from among the multiple categories; and outputting the computed amount of time to at least one user.

Abstract: An apparatus for predicting structural degradation and performing maintenance induction for a plurality of in-service aircraft is provided. The apparatus identifies maintenance requirements for the plurality of in-service aircraft and receives fatigue metric values on historical usage and structural health condition of the plurality of in-service aircraft. The apparatus predicts levels of structural degradation to the plurality of in-service aircraft based on the fatigue metric values and assigns maintenance priorities to the plurality of in-service aircraft based on the levels of structural degradation. The apparatus generates an instruction to route an aircraft of the plurality of in-service aircraft to a maintenance facility for maintenance based on a maintenance priority of the maintenance priorities assigned to the aircraft.

Abstract: A method for performing multiple simulations for a circuit using a first plurality of samples is provided. The method includes obtaining a model of the circuit based on a result of the simulations, determining a failure rate and a confidence interval of the failure rate for the circuit with the performance model. The method includes determining an importance distribution based on the failure rate for the first plurality of samples, wherein the importance distribution is indicative of a probability that a sample value for the circuit will fail the simulation, selecting a second plurality of samples based on the importance distribution, performing a second set of simulations using the second plurality of samples to reduce the confidence interval of the failure rate. When the confidence interval is larger than a value, obtaining an updated performance model and performing new Monte Carlo simulations with new samples.

Abstract: A computer-implemented method for identifying and tracking application performance incidents may include (1) receiving, by an incident tracking system, data representative of a time series, the time series including a time-ordered plurality of values of a performance metric associated with a program, (2) identifying, by the incident tracking system, a discontinuity in the time series, (3) associating, by the incident tracking system, the identified discontinuity in the time series with a change in source code associated with the program, and (4) executing, by the incident tracking system, an automated action based on the association of the identified discontinuity with the change in the source code. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A service design assistance apparatus includes an input apparatus, a storage, a display, and an arithmetic apparatus. The arithmetic apparatus, in response to a specific request received via an input apparatus, placing objects for a service of a new design target in corresponding areas on the design screen, the objects representing a relevant business, a problem with the business, a value to be obtained by solving the problem, a service to provide the value, and an apparatus or technology needed for the service.

Abstract: A Bluetooth chip designed to track proximity and play a sound, along with an accelerometer, that is embedded inside of a golf ball is disclosed. The technology inside the balls allows it to be found quickly through proximity and sound, and the app gives a golfer helpful analytical data.

Abstract: A method for detecting and/or tracking an object in surroundings of a vehicle is described. The method ascertains, at a first time, on the basis of sensor data from one or more ambient sensors of the vehicle, measurement data for a multiplicity of cells of a grid of the surroundings of the vehicle, the measurement data for a first cell indicating an object probability. Moreover, the method ascertains an occupancy probability of the first cell being occupied by an object that was already detected at a preceding time. The method further assigns the first cell to the object in dependence on the object probability and in dependence on the occupancy probability.

Abstract: A computer-implemented method is disclosed that operates in conjunction with machine learning binary classification of an event. The method generates a rule relating to whether or not the event will occur. In one embodiment, the method includes obtaining foreground sequences corresponding to the event happening and background sequences corresponding to the event not happening. For each foreground sequence of a number of foreground sequences, the computer computes a plurality of difference values. The rule may be determined based on a largest difference value for one of the plurality of foreground sequences. A corresponding system is also disclosed.

Abstract: Aspects of the present disclosure address systems and methods for shortening clock-tree wirelength based on target offsets in connected routes. A clock tree comprising routes that interconnect a plurality of clock-tree instances is accessed from memory. A clock-tree instance is selected for evaluation. A baseline power consumption measurement corresponding to a sub-tree of the clock-tree instance with the clock-tree instance at a first size is determined. An alternative power consumption measurement corresponding to the sub-tree of the clock-tree instance with the clock-tree instance at a second size is determined. Based on determining that the baseline power consumption measurement is less than the alternative power consumption measurement, the clock-tree instance is resized according to the second size.

Abstract: A method and system is provided for evaluating an application manufacturer's credibility to produce or maintain a mobile device application. The method includes gathering information about an application manufacturer, wherein the information includes at least one of: (i) publicly available information about the manufacture; (ii) private information provided by the manufacturer; and (iii) source code information for the application developed by the manufacturer. With the computer system, the gathered information is stored in a manufacturer profile, which includes a plurality of attributes of the manufacturer. The computer system uses the manufacturer profile to calculate a score for the manufacturer, which is then used to calculate an application risk score associated with applications produced or maintained by the manufacturer. The risk score reflects, at least in part, the credibility of the manufacturer to produce or maintain the mobile device application.