Abstract: For a time-series, a baseline error value is reduced to compute a target forecast error value by maximizing a net benefit value of a forecasted value of the time-series. For each forecasting model in a set of models, a corresponding model error value related to the time-series is computed. From the set, a subset of models is selected where each model in the subset has a cost that will produce a positive value for the net benefit. A selected model from the subset is associated with the time-series such that a model error value of the selected model is at most equal to the target forecast error. The time-series is forecasted using the selected model such that the forecasted value has an error of less than the baseline error at a future time, and the forecasted value produces a positive net benefit at the future time.

Abstract: Systems, methods, devices, and non-transitory media of the various embodiments provide for a volumetric approach to determining orbital encounters that may determine the number of encounters over a specified length of time. Such information may be used to determine how often during an orbit or period of time an object might trigger a conjunction warning for a neighboring satellite. The various embodiments may be used as a planning and characterization tool to estimate satellite encounter rates for a prospective orbit regime and may provide an efficient, in-line approach to assess the number of encounters occurring within a user-specified span of time.

Abstract: A measurement instrument, i.e. a mobile body, measures distances between a current position of the mobile body and obstacles in the environment of the mobile body by: a) taking at least N measurements of distances between the mobile body and the obstacles, by consecutive angular steps of A/N (A is a predetermined angular sector), and combining the distances with the respective angular steps in order to establish map data; b) moving the mobile body and repeating step a) for a new current position of the mobile body; and c) simultaneously determining, according to the distances measured for each angular step of the current position of step b) and the preceding position of step a), the current position of the mobile body in step b) on the map relative to the initial position thereof in step a), and new data of the map.

Abstract: A method of predicting growth of a crack in a member includes memorizing, for each portion on the member, stress distribution ??(a) in the depth direction obtained in the case that no crack is present, a relationship between depth of growing cracks and creep contribution, and a relationship between creep contribution and parameters C and m of the Paris's law, receiving from a user an indication of a certain portion on the member, acquiring the stress distribution ??(a) in the depth direction for the certain portion, acquiring a creep contribution at the depth of a growing crack for the certain portion, from the relationship between depth of cracks and creep contribution memorized for the certain portion, and acquiring parameters C and m corresponding to the acquired creep contribution, from the relationship between creep contribution and parameters C and m of the Paris's law memorized for the certain portion.

Abstract: A Fin-FET device and its fabrication method are provided. The method for fabricating the Fin-FET device includes forming a plurality of fin structures on a substrate, forming an isolation film on the substrate between neighboring fin structures, removing a portion of the isolation film to form an initial isolation layer with a top surface of the initial isolation layer lower than top surfaces of the fin structures, and implanting doping ions into the initial isolation layer. Further, the method also includes removing a portion of the initial isolation layer to form an isolation layer.

Abstract: A method operates a safety-critical system, which system contains at least one first data device having approved, safety-relevant software and at least one reference data device having the same approved, safety-relevant software. In the method, after a type check of the system, the at least one first data device is equipped with at least one piece of non-safety-relevant additional software and the at least one reference data device is blocked from software modifications. Before safety-related data information is output, output information of the at least one first data device and of the at least one reference data device are checked for a match with regard to the safety-relevant software by a comparison device, and the safety-related data information is output in the case of a match.

Abstract: A computer system-based method and system for modeling, planning and analyzing distributed systems in view of environmental considerations in the deployment of said distributed system is disclosed. The method comprises the steps of representing selected ones of a plurality of components and relationships among selected components with said distributed system, wherein said representation includes attributes and characteristics associated with environmental considerations, identifying a location of each of said selected components in said distributed system determining an environmental aspect of each of said identified locations, and providing a recommendation based on said environmental aspects. In one aspect of the invention, an analysis is performed that determines a cause of changes in environmental conditions and a recommendation is made to correct the cause of the environment changes.

Abstract: According to some embodiments, a thermoelectric system includes a thermoelectric device having a first surface and a second surface and a power source configured to deliver a voltage across the thermoelectric device to selectively activate or deactivate the thermoelectric device, wherein the first surface is configured to heat and the second surface is configured to cool when the thermoelectric device is activated. The system further includes a processor configured to determine a potential between the first surface and the second surface when the thermoelectric device is deactivated, correlate the potential to a temperature of the first surface and adjust the correlated temperature of the first surface based on an ambient temperature.

Abstract: Methods, systems, and computer-readable media are provided for facilitating mapping of semantically similar terms between and among two or more information systems. In particular, to facilitate automatic discovery, establishment, and/or statistical validation of linkages between a plurality of different nomenclatures employed by a plurality of information systems, such as multiple electronic health record systems. In embodiments, the imputation of latent synonymy in corpora comprised of samples of historical records from each system enables automated terminology mapping between disparate systems' records, thereby establishing reliable linkages that may subsequently be utilized for realtime decision support, data mining-based research, or other valuable purposes.

Abstract: A system and method of identifying part failures is provided. The system may comprise monitoring a sensor, detecting a failure mode, selecting a row from a lookup table corresponding to the failure mode, looking up a line replaceable unit (LRU) failure probability for the detected failure mode, and reporting the LRU failure probability for the detected failure mode.

Abstract: Processing time sequence data for multiple sensors, wherein the multiple sensors are divided into multiple sensor groups and each data comprises a time stamp and a value associated with the timestamp. The method comprises: receiving time series data from each sensor; assigning the time series data received to a sensor group to which the sensor belongs; storing time series data in a first database of a first memory, such that multiple time series data assigned to the same sensor group in the multiple sensor groups are stored in at least one database record of the first database; obtaining the time series data of each sensor among the multiple sensors from the first database; storing time series data in a second database of a second memory, such that the multiple time series data from the same sensor are stored in at least one database record of the second database.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a component of a time-series performance metric associated with a server-side root cause of an anomaly in the time-series performance metric. Next, the system obtains a call graph representation of the component, wherein the call graph representation includes a parent node having a parent value of the component and a set of child nodes of the parent node, each child node having a corresponding child value of the component. The system then analyzes the call graph representation to identify one or more of the child nodes as sources of the anomaly. Finally, the system outputs an alert that identifies the sources of the anomaly.

Abstract: Systems, methods, and media for outputting a dataset based upon anomaly detection are provided. In some embodiments, methods for outputting a dataset based upon anomaly detection: receive a training dataset having a plurality of n-grams, which plurality includes a first plurality of distinct training n-grams each being a first size; compute a first plurality of appearance frequencies, each for a corresponding one of the first plurality of distinct training n-grams; receive an input dataset including first input n-grams each being the first size; define a first window in the input dataset; identify as being first matching n-grams the first input n-grams in the first window that correspond to the first plurality of distinct training n-grams; compute a first anomaly detection score for the input dataset using the first matching n-grams and the first plurality of appearance frequencies; and output the input dataset based on the first anomaly detection score.

Abstract: A method and a system including a processor performing a failure region exploration through uniform sampling of plurality of variables related to a circuit, the processor shifting probability distributions to explore failure probability, the processor estimating the failure probability and standard deviation by determining mean and standard deviation of failure probability of a circuit, the processor terminating sampling when a confidence interval bounds converge, and a peripheral device providing a report on the failure of the circuit when the sampling is terminated by the processor.

Abstract: Anomaly detection is provided. A first component of a first data resource of a plurality of data resources is identified. Each data resource of the plurality of data resources includes one or more components. A score of the first component is determined based, at least in part, on underlying data of the first component and underlying data of one or more other components of data resources of the plurality of data resources that correspond to the first component. An interest level of the first data resource is determined. A relationship between the score of the first component and the interest level of the first data resource is modeled.

Abstract: Methods, systems, and computer readable media for integrating medical imaging data in a data warehouse are disclosed. According to one method, the method occurs at a data warehouse management server that manages a data warehouse system. The data warehouse management server includes at least one processor. The method includes receiving medical imaging data including imaging metadata from an imaging related data source. The method also includes storing the imaging metadata in the data warehouse. The method further includes performing data processing using the imaging metadata and other healthcare related data stored in the data warehouse, wherein the other healthcare related data is from one or more different data sources.

Abstract: A method for target motion analysis for calculating the track between an observer and a target and estimating its uncertainty includes initializing strongly observable state components into strong state vectors and weakly observable state components to form a weak state analysis grid. Initial probability density functions are calculated from all components. The method then iteratively calculates strong state gradients, target track direction, and updates strong state vectors over the analysis grid. Probability density functions are recalculated. Calculations are reiterated if the probability density functions change more than an information threshold. The strong state vectors and weak state probability density functions are provided as output if the information threshold is not exceeded.

Abstract: A system and method is provided for enhancing the detectability of objects in medical images. The method includes providing medical imaging data acquired using a medical imaging system, integrating dynamic noise with the imaging data to generate a modified set of images that achieves improved detection accuracy, and displaying the modified images.

Abstract: Methods and systems to identify log write instructions of a source code as potential sources of an event message of interest are described. Methods identify non-parametric tokens, such as text strings and natural language words and phrases, of an event message of interest. Candidate log write instructions and associated line numbers in a source code are identified. Non-parametric tokens of each event message of the one or more candidate log write instructions are determined. A confidence score is calculated for each candidate log write instruction based the number of non-parametric tokens the event message of interest and event message of the candidate log write instruction have in common. The candidate log write instructions are rank ordered based on the corresponding one or more confidence scores and the rank ordered candidate log write instructions and associated line numbers of the source code may be displayed in a graphical user interface.

Abstract: A controller is configured with a description of a building automation project, including attributes of the structure itself as well as the locations and configurations of the devices. The controller generates the appropriate schema in a control memory structure, and links it to an environment controller. The controller then generates a set of instructions for system installation and preconfigures the environment controller with the project attributes and sets the environment controller up for interaction with the devices.

Abstract: A structured light imaging (SLI) system includes a projection system, image sensor system and processing module. The projection system is operable to project a single SLI pattern into an imaging area. The image sensor system is operable to capture images of a 3D object moving through the imaging area. The image sensor system outputs a subset of camera pixels corresponding to a subwindow of a camera frame to generate subwindow images. The processing module is operable to create a 3D surface map of the 3D object based on the subwindow images.

Abstract: A system and method for integrating business logic into a database system is disclosed herein. A database system may comprise a first database cluster H and a second database cluster L. After records are separated into the first database cluster H and the second database cluster L, the total number of records in the second database cluster L is compared to a target number of records. If there are too many records in the second database cluster L, a randomly generated number is used to randomly move records from second database cluster L into first database cluster H. In a situation where the first database cluster H is faster and accessed more often, such a method results in more products being placed in the faster database cluster and become more likely to become purchased. Other embodiments are also disclosed herein.

Abstract: In an embodiment, an apparatus receives report(s) of raw motion data detected in IoT environment, and also receives report(s) indicating user-initiated event(s) detected by a set of IoT devices within the IoT environment. The apparatus scans the raw motion data within a threshold period of time preceding particular detected user-initiated events to identify motion sequence(s) within the IoT environment that occurred during the threshold period of time. Certain motion sequence(s) are correlated with user-initiated event(s) based on a confidence level that the user-initiated event(s) will follow the motion sequence(s). Upon detection of the motion sequence(s) at some later point in time, the correlated event(s) is preemptively triggered without user interaction.

Abstract: Relational clustering has attracted more and more attention due to its phenomenal impact in various important applications which involve multi-type interrelated data objects, such as Web mining, search marketing, bioinformatics, citation analysis, and epidemiology. A probabilistic model is presented for relational clustering, which also provides a principal framework to unify various important clustering tasks including traditional attributes-based clustering, semi-supervised clustering, co-clustering and graph clustering. The model seeks to identify cluster structures for each type of data objects and interaction patterns between different types of objects. Under this model, parametric hard and soft relational clustering algorithms are provided under a large number of exponential family distributions.

Abstract: One or more user interactions, selected from a plurality of user interactions, and one or more visualization types, selected from a plurality of visualization types are received. Predetermined visualization data associated with displaying an interactive data analysis document is determined based at least in part on the selected user interactions and the selected visualization types. The predetermined visualization data is output.

Abstract: Generally discussed herein are systems and apparatuses that are configured to and techniques for matching track fragments. According to an example, a technique can include receiving data indicating a first and second actual ToA of first and second SIGINT signals at a collector, estimating first and second sets of estimated ToAs of the first and second SIGINT signals at a collector, respectively, each of the first and second sets of estimated ToAs based on a different track fragment of a first plurality of track fragments active at the first time and a different track fragment of a second plurality of track fragments active at the second time, respectively, or matching a track fragment of the first plurality of track fragments with a track fragment of the second plurality of track fragments based on the first and second sets of estimated ToAs and the first and second actual ToAs.

Abstract: A method, non-transitory computer readable medium, and data manager computing device comprises retrieving a time series data of a monitored asset based on one or more tags in response to a request. Further, a heterogeneous data based on the one or more tags is retrieved. Furthermore, a cause of an anomaly period in retrieved time series data of the monitored asset is determined based on the retrieved heterogeneous data. Finally, the determined cause of the anomaly period in the time series data in the monitored asset is provided.

Abstract: A workflow is presented that facilitates defining geocontextual information as a set of rules for multiple seismic attributes. Modeling algorithms may be employed that facilitate analysis of multiple seismic attributes to find candidate regions that are most likely to satisfy the set of rules. These candidates may then be sorted based on how well they represent the geocontextual information.

Abstract: A method includes generating a system model representative of a socio-technical system having a plurality of system parameters. The method further includes selecting one or more essential system parameters from the plurality of system parameters. The method also includes determining a plurality of probability distributions corresponding to the one or more essential system parameters. The method further includes determining at least one hyperbox using a sampling optimization technique based on the one or more essential system parameters. The at least one hyperbox is representative of a confidence region corresponding to a rare event of the socio-technical system. The method also includes determining a probability of the rare event using a variance reduction technique based on a plurality of particles obtained from the at least one hyperbox. The probability of the rare event is representative of a performance of the socio-technical system.

Abstract: A system and method for forwarding network traffic includes receiving a first flow of network traffic at an ingress port on a switch, collecting flow control metrics for a plurality of egress ports assigned to a link aggregation group of the switch, selecting a first egress port from the plurality of egress ports using a hashing strategy based on at least information associated with the flow control metrics, assigning the first flow to the first egress port, directing the first flow to the first egress port, and transmitting network traffic associated with the first flow using the first egress port.

Abstract: A method that calibrates a device for echo cancellation and a device with calibration for echo cancellation are provided. Devices may be calibrated such that the echo residual error is less than a threshold determined by the calibration accuracy. Non-ideal factors such as mismatch may be eliminated during calibration.

Abstract: A hierarchical modeling tool or process is provided that represents the fill range of behavior of a hydrocarbon system, accurately including uncertainties and potential events affecting the system. The potential events may include actions taken and information learned. The hierarchical modeling tool may be embedded within a decision support system or used in a stand-alone fashion. Disclosed aspects may link from accurate (high-detail) physics models to an accurate uncertainty representation, and then reduce the accurate uncertainty representation to a high-speed representation of both the physics model and the uncertainty that can be used in an optimizer.

Abstract: A computer utilizes correlation matrix data including a value indicating correlation between indicators and comprises a graph process unit that includes a control factor calculation unit configured to calculate a control factor for generating compressed graph data based on a constraint condition on a process; and a graph generation unit configured to generate graph data from the correlation matrix data by using the control factor. The control factor calculation unit obtains a target process time as the constraint condition; calculates a maximum of a number of edges to be included in the graph data; calculates a threshold for extracting the elements converted from the correlation matrix data to the graph data based on the maximum of the number of edges; and outputs the threshold as the control factor. The graph generation unit extracts the elements from the correlation matrix data based on the threshold, and generates the graph data.

Abstract: An example apparatus includes a crossbar array of signal lines and control lines. The example apparatus also includes an input controller in circuit with the control lines. The input control is to select one of the control lines. The example apparatus also includes first resistive elements connected between corresponding ones of the control lines and corresponding ones of the signal lines. The first resistive elements have first conductances set to operate as a matrix of probabilities that define a fixed transition kernel of a Markov Chain. The example apparatus also includes second resistive elements in circuit with the signal lines. The second resistive elements have second conductances set to select one of the signal lines exclusive of others of the signal lines based on a subset of the probabilities in the matrix of the probabilities.

Abstract: A method for operating a machine component under stress. The method comprises determining a probability of failure PoF(N) of the component as a function of N cycles, selecting a time-based acceptable risk limit for the component and selecting an operational profile for the component, converting the time-based acceptable risk limit to a cycle-based acceptable risk limit using the operational profile, comparing the cycle-based acceptable risk limit with the PoF(N) values to determine an operational status of the component, comparing the cycle-based acceptable risk limit with the PoF(N) values, and operating the machine component responsive to results of the comparing step.

Abstract: A dynamic risk management system for operating systems that provides monitoring, detection, assessment, and follow-up action to reduce the risk whenever it rises. The system enables an operating system to protect itself automatically in dynamic environments. The risk management system monitors a diverse set of attributes of the system which determines the security state of the system and is indicative of the risk the system is under. Based on a specification of risk levels for the various attributes and for their combinations, the risk management system determines whether one or more actions are required to alleviate the overall risk to the system.

Abstract: Operational parameters of a single-photon detector are determined with a continuous wave laser source. At a fixed trigger, a dark count probability and a series of count probabilities at different optical powers are determined. A particular optical power is selected by using a wide-range variable attenuator to attenuate the optical power of the continuous wave laser. The dark count probability and the count probabilities are determined for different trigger rates. The operational parameters include efficiency, afterpulsing constant, and detrap time. The operational parameters are computed by fitting the computed dark count probabilities and count probabilities to a user-defined relationship.

Abstract: A method for locating an electronic mobile device capable of wireless communication, the method including obtaining a probability map structure for the area of interest, the probability map structure associating environment data values, preferably including cellular network based data, with location data, obtaining a number of probabilistic temporospatial motion models for different types of motion, the models at least partly defining transition probabilities between location estimates relative to time, obtaining at least environment data captured or determined by the mobile device at a plurality of sequential time instances, and determining the most probable location estimate of the mobile device based on combining probability data from both the probability map structure and the motion models, wherein the at least environment data is best fitted in the motion models and probability map structure according to predefined criteria. Related two arrangements and a computer program are presented.

Abstract: A cardiac implant includes a classifier configured analyze the data for comparison to thresholds prioritized according to a Boolean decision tree. The implant can generate an indicator of alert status (i.e., alert or no alert). A supervisory device operated, for example, by a doctor can associate each indicator a marker (AE/no AE) indicating the presence or absence of an observed adverse event. In the presence of a false positive, a command for update of the thresholds of the decision tree is transmitted to the implant. A database of reference patients can be used to recreate or further update the decision tree to avoid the occurrence of false negatives.

Abstract: Embodiments are disclosed for detecting anomalies in time series using statistical models. In some embodiments, a linear regression model is built for the time series for predicting future values of the time series. Furthermore, the standard deviation of the difference between a prediction and an ideal value of the time series at any point is then estimated. An anomaly is detected when the difference between the prediction and the observed value is greater than a certain threshold based on the estimated standard deviation.

Abstract: Profiles characterizing each of a plurality of consumers are received. Thereafter, each profile is associated with one of a plurality of customer segments (e.g., matched pairs, etc.). Thereafter, a coupon effectiveness index is determined for each of the plurality of consumers for an offering based on the associated customer segment. The coupon effectiveness indices model characterizes causal effects estimates determined using historical data of purchases of individuals having varying coupon treatments for the offering. Subsequently, provision of at least a portion of the determined coupon effectiveness indices is initiated. Related apparatus, systems, techniques and articles are also described.

Abstract: Embodiments of the present invention provide systems and methods to robustly inter-convert between polarization-entangled photon pairs and time-entangled photon pairs, such that produced polarization-entangled photons pairs can be converted into time-entangled photon pairs, stored as time-entangled photon pairs to preserve the entanglement for longer periods of time, and then converted back to polarization-entangled photon pairs when ready for manipulation, processing, and measurement by a quantum application.

Abstract: A flow rate prediction device to predict a flow rate determines, based on time-series data of a measured flow rate, whether the state of the flow rate is stationary or non-stationary. The flow rate prediction device identifies a stochastic process model defining the flow rate as a stochastic variable based on the result of determination of whether the state is stationary or non-stationary and calculates a parameter for use in the identified stochastic process model based on the time-series data. The flow rate prediction device calculates a probability distribution function or a probability density function defining the flow rate to be predicted as the stochastic variable based on the identified stochastic process model and the parameter.

Abstract: A device may obtain information regarding a security situation of a set of computing resources associated with a cloud-based platform. The information may be related to an ongoing security threat or a potential security threat. The information may be obtained utilizing one or more internet security resources. The device may determine a threat assessment level, of a set of threat assessment levels, for the security situation based on the information regarding the security situation. The information regarding the security situation may satisfy a set of threshold criteria for the threat assessment level. The device may perform one or more response actions associated with the threat assessment level based on the security situation. The one or more response actions may include providing an alert notification regarding the security situation that identifies the threat assessment level.

Abstract: A method includes receiving historical monitoring data for components of a system, the historical monitoring data comprising a plurality of events, each triggered by an associated component, and a plurality of alarms, each triggered by detection of a particular type of condition in the components. The method also includes determining common event sequences in the plurality of events, each event sequence culminating in one of the plurality of alarms. The method further includes correlating the common event sequences into an event pattern. The method also includes receiving a plurality of real-time events triggered by the components. The method additionally includes detecting the event pattern in the plurality of real-time events to predict a potential future instance of the particular type of condition in the components of the system.

Abstract: A dynamical hierarchical tagging system connected to a user site through a remote communications network. The system may comprise a master controller, a job management server connected to the master controller, one or more scanners in communication with the job management server, wherein the one or more scanners are configured to scan for one or more user assets located at the user site, resulting in scan results, a scan logic processor connected to the master controller, wherein the scan logic processor is configured to store the scan results in a user database, a tagging logic engine connected to the master controller, wherein the tagging logic engine is configured to tag the scan results stored in the user database, and an indexing logic processor connected to the master controller, wherein the indexing logic processor is configured to search and index the tagged scan results stored in the user database.

Abstract: Threat detection is improved by monitoring variations in observable events and correlating these variations to malicious activity. The disclosed techniques can be usefully employed with any attribute or other metric that can be instrumented on an endpoint and tracked over time including observable events such as changes to files, data, software configurations, operating systems, and so forth. Correlations may be based on historical data for a particular machine, or a group of machines such as similarly configured endpoints. Similar inferences of malicious activity can be based on the nature of a variation, including specific patterns of variation known to be associated with malware and any other unexpected patterns that deviate from normal behavior. Embodiments described herein use variations in, e.g., server software updates or URL cache hits on an endpoint, but the techniques are more generally applicable to any endpoint attribute that varies in a manner correlated with malicious activity.

Abstract: A method and apparatus for warning a driver of a motor vehicle of a predicted collision with a stationary object. A proximity sensor is used to determine a position of an obstacle relative to the vehicle. A steering angle of the vehicle is determined and used to predict a trajectory of the vehicle. A collision zone on the vehicle is identified based on the vehicle trajectory, the collision zone being that spot or location on the vehicle which is predicted to contact the obstacle. A visual display within the vehicle (on the control panel, for example) provides a visual indication to the driver of the position of the collision zone on the vehicle and a predicted trajectory of the collision zone as the vehicle moves in accordance with the steering angle.

Abstract: According to one embodiment, a device state estimation apparatus includes a detector and an operating state estimator. The detector detects devices in the ON operating state, based on a comparison between a calculated one of a first characteristic of a current or power harmonic in a power feed line and a reference one of the first characteristic which has been predetermined for at least one device. The operating state estimator extracts at least one set of the second characteristics from plural sets of second characteristics associated with harmonic, which have been predetermined. Each set of the second characteristics is for operating states of each of the devices. The one set of the second characteristics is for operating states of the device in the ON operating state which is detected by the detector.

Abstract: Devices, systems, and methods of detecting user identity, differentiating between users of a computerized service, and detecting a cyber-attacker. An end-user device interacts and communicates with a server of a computerized server (a banking website, an electronic commerce website, or the like). The interactions are monitored, tracked and logged. User Interface (UI) interferences or irregularities are introduced; and the server tracks the response or the reaction of the end-user to such interferences. The system determines whether the user is a legitimate user, or a cyber-attacker or automated script posing as the legitimate user. The system utilizes classification of users into classes or groups, to deduce or predict how a group-member would behave when accessing the service through a different type of device. The system identifies user-specific traits that are platform-independent and thus can be further monitored when the user switches from a first platform to a second platform.