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: 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 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: 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: 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: 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: 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: 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: 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: 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.

Abstract: A system for transforming time series data into data that is accessible by a data warehouse identifies a data table comprising the time series data. The system creates a virtual view of the data table where the time series data is represented as at least one standard relational table in the virtual view, where the virtual view is presented as a virtual table. The system partitions the virtual table into a plurality of virtual partitions according to a time interval. The virtual table is partitioned across a data time range, where the data time range comprises at least one time interval, and where each of the plurality of virtual partitions has a respective partition time range that spans the time interval. The virtual partitions are created to optimize loading of the data into the data warehouse by incrementally refreshing the data according to the respective partition time range.

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 supplemental rescue resources system can receive an emergency alert message from a mobile device and use data from the message and other sources to determine and select appropriate supplemental rescue resources, which may include may include any person that has volunteered or is otherwise a participant in the system that is not an on-duty emergency responder. The supplemental rescue resources system may select a supplemental rescue resources based on the location of such resources relative to the location of an incident, and/or the qualifications and/or preferences of such resources. The supplemental rescue resources system may direct resources to the incident and notify emergency services providers of the supplemental resources.

Abstract: The inventive subject matter is generally directed to a cross channel optimization system, methods, and related software which provide for the conducting of experiments and/or optimization of digital content across a plurality of external content systems to user of the external content systems.

Abstract: A switch unit has one frame buffer pool for storing received frames and another frame buffer pool for storing large frames. The frame size in the large frame buffer pool may be optimized to the largest amount of data the switch unit that an FCoE switching is running on can support (i.e., a limitation of zone entries). Should free space be unavailable in the large frame buffer pool, or if a sequence grows bigger than can be supported, the switch unit may still continue to send response frames back to the sender. While the switch unit may store header information of the frame, the switch unit does not store the data of subsequent frames any longer. Once the sequence has been received completely, a rejection message is sent back with an appropriate error or reason code. The rejection message enables the sender to attempt a retransmission or cancel the current request altogether.

Abstract: Providing a reminder of a task to be performed at a task location includes receiving location information identifying a location of a user via a mobile communication device associated with the user, receiving information that identifies a task, receiving information that identifies a task location, and providing a reminder for the task based on a current location of the user and on a comparison of an estimated probability of the user traveling in a trajectory leading toward the task location and an estimated probability of the user traveling in a trajectory leading away from the task location.

Abstract: A computer system is monitored for conditions bearing on the effective age of various hardware components of the system. Upon detecting an age adjustment condition, the affected hardware components are identified. An age adjustment is determined for each of the affected hardware components. The adjusted age is stored for reference when taking actions based on the adjusted age, such a component replacement and/or workload placement.

Abstract: Performance of a manufacturing tool is optimized. Optimization relies on recipe drifting and generation of knowledge that capture relationships among product output metrics and input material measurement(s) and recipe parameters. Optimized recipe parameters are extracted from a basis of learned functions that predict output metrics for a current state of the manufacturing tool and measurements of input material(s). Drifting and learning are related and lead to dynamic optimization of tool performance, which enables optimized output from the manufacturing tool as the operation conditions of the tool changes. Features of recipe drifting and associated learning can be autonomously or externally configured through suitable user interfaces, which also can be drifted to optimize end-user interaction.

Abstract: Provided is a system for testing mobile handover which makes it possible to test a handover operation on a mobile side by providing an actual base station with a radio wave environment for causing mobile devices to move. The system is intended to test whether or not a handover operation of a mobile present in the service areas of at least three base stations is performed without interrupting service while the mobile moves from the service area of a currently connected base station to another spot.

Abstract: An apparatus and method for building a map of probability distribution are provided. The apparatus for building the map of probability distribution includes: a sensor information collector configured to collect sensor information from a plurality of sensors; as object recognizer configured to recognize an object by integrating and inferring the sensor information, and to acquire object information; and a probability distribution creator configured to determine whether to apply an object property model including at least one of kinematic properties, shape properties, and probabilistic properties in correspondence to the object information, to acquire object properties corresponding to the object information, and to create a probability distribution based on foe object properties. Accordingly, it is possible to build a map with high reliability.

Abstract: Methods and systems of forecasting consumption of a consumable for a machine are disclosed. A computing device receives consumption time series data for a consumable for a plurality of machines. The consumption time series data for each machine includes an amount of the consumable consumed by the machine during each of multiple time periods. For at least one of the plurality of machines, the computing device determines a model consumption forecast for the machine for each of multiple dynamic linear models based on the consumption time series data for the consumable for the machine and the dynamic linear model. The computing device further determines, for at least one of the machines, a final consumption forecast based on the model consumption forecasts. An amount of the consumable is provided for the at least one machine based on the final consumption forecast.

Abstract: Methods and apparatus are directed to geofencing applications that utilize machine learning. A computing device can receive a plurality of geofence-status indications, where a geofence-status indication includes training data associated with a geofence at a first location. The geofence is associated with a geographical area. The computing device trains a geofence-status classifier to determine a geofence status by providing the training data as input to the geofence-status classifier. The training data includes data for a plurality of training features. After the geofence-status classifier is trained, the computing device receives query data associated with a second location. The query data includes data for a plurality of query features. The query features include a query feature that corresponds to a training feature. The query data is input to the geofence-status classifier. After providing the query data, the trained geofence-status classifier indicates the geofence status.

Abstract: A system that utilizes a plurality of time series of metric data to more accurately detect anomalies and model and predict metric values. Streams of time series metric data are processed to generate a set of independent metrics. In some instances, the present system may automatically analyze thousands of real-time streams. Advanced machine learning and statistical techniques are used to automatically find anomalies and outliers from the independent metrics by learning latent and hidden patterns in the metrics. The trends of each metric may also be analyzed and the trends for each characteristic may be learned. The system can automatically detect latent and hidden patterns of metrics including weekly, daily, holiday and other application specific patterns. Anomaly detection is important to maintaining system health and predicted values are important for customers to monitor and make planning and decisions in a principled and quantitative way.

Abstract: Methods and systems for providing and processing data are disclosed. An example method can comprise determining a first weighted probability based on a probability of occurrence of a noise signal and a first likelihood ratio. The first likelihood ratio is based on a frequency distribution of the noise signal. An example method can comprise determining a second weighted probability based on a probability of non-occurrence of the noise signal and a second likelihood ratio. An example method can comprise determining a combination of the first weighted probability and the second weighted probability, and providing the combination to a decoder configured to decode a value based on the combination.

Abstract: Apparatus, computer readable medium, program code, and methods for performing a parameter recalibration on parameters for an electrical submersible pump application model, are provided. An example of a method can include generating a data set containing a plurality of winning data sets or rows containing ESP application model input parameters and associated theoretical output parameters for an ESP application model substantially matching a corresponding set of measured ESP output parameters, through application of a self-organizing map analysis on a substantial number of training data sets. An averaging analysis is performed on the plurality of winning data sets or rows to obtain a set of ESP application model input parameters that can be used to recalibrate the ESP application model.

Abstract: Various technologies described herein pertain to generating a video loop. An input video can be received, where the input video includes values at pixels over a time range. An optimization can be performed to determine a respective input time interval within the time range of the input video for each pixel from the pixels in the input video. The respective input time interval for a particular pixel can include a per-pixel loop period and a per-pixel start time of a loop at the particular pixel within the time range from the input video. Moreover, an output video can be created based upon the values at the pixels over the respective input time intervals for the pixels in the input video.

Abstract: Systems and methods for determining an appropriate parameter order for a building energy use model are provided. A described method includes receiving an energy use model for a building site, obtaining a plurality of data points, calculating a first regression statistic indicating a fit of the energy use model to the plurality of data points under a null hypothesis and a second regression statistic indicating a fit of the energy use model to the plurality of data points under an alternative hypothesis, and comparing a test statistic to a threshold value. The test statistic is a function of the first regression statistic and the second regression statistic. The method further includes determining an appropriate parameter order for the energy use model based on a result of the comparison.

Abstract: A method of determining the performance of a chip of an integrated-circuit design comprises instantiating a plurality of HPM in the integrated-circuit design to generate the performance of the chip according to a performance function defined by a polynomial comprising a plurality of terms, wherein each term of the polynomial comprises an exponent of a value generated by a corresponding one of the plurality of HPM(s) and a corresponding coefficient, wherein the coefficients are determined through a regression process with sample chips of the integrated-circuit design having known performance, so that the performance of each chip other than the sample chips can be determined by the performance function and the values of the plurality of HPM(s) of the chip.

Abstract: An apparatus comprising a housing, a gearing system disposed within the housing and comprising a plurality of targets, a plurality of sensors incorporated within the housing, a processor in electrical signal communication with the sensors, and a user interface in signal communication with the processor. A method comprising providing a drive system comprising a drive system power measuring and diagnostic system, wherein the drive system is configured to rotate one or more components comprising a plurality of targets, sense the targets with a sensor pair, thereby producing a data signal, process the data signal from the one or more sensor pairs, thereby producing a processed data signal, and output the processed data signal to a user.

Abstract: A wafer acceptance test (WAT) system and method that, in one embodiment, includes: (1) a saturation current WAT subsystem operable to generate a weighted standard deviation based on target NMOS and PMOS saturation currents and saturation current WAT results, (2) a wafer IC speed WAT subsystem operable to generate a speed performance probability distribution of wafer ICs based on the weighted standard deviation and speed WAT results, (3) a wafer IC power WAT subsystem operable to employ the speed WAT results and power WAT results to generate a power performance model of wafer ICs, and (4) a yield calculator operable to generate a power performance variance probability distribution of wafer ICs based on the power performance model and the power WAT results, and to employ the speed performance probability distribution and the power performance variance probability distribution to generate the yield forecast with respect to a target performance profile.

Abstract: A system and a method, implemented on a computer, for calculating property distribution uncertainty of spatially correlated petrophysical data. The method includes inputting, into the computer, a sample petrophysical data comprising correlated data; applying, using the computer, a variogram to the sample petrophysical data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample petrophysical data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating data distributions for each of the obtained plurality of bootstrap data sets; ranking the data distributions by using a selected statistical parameter to obtain ranked data distributions; and characterizing the uncertainty based on the ranked data distributions.

Abstract: Visualizing content change of a data collection over time. A topic may be split into multiple linear, non-overlapping sub-topics along a timeline by satisfying a diverse set of semantic, temporal, and visualization constraints simultaneously. For each derived sub-topic, a set of representative keywords may be automatically selected to summarize the main content of the sub-topic.

Abstract: A computer-implemented system and method for capability zone-based manufacturing quality control are provided. A specification for manufacturing a part feature is obtained, the specification including a nominal and a tolerance. A plurality of measurements for the feature are obtained. A difference is determined between the nominal and each of the measurements. The difference for each of the measurements is compared to the tolerance. Each of the measurements is assigned into one of a plurality of capability zones of measurements based on the comparison. Visual representations of the capability zones into which the measurements were assigned are displayed.

Abstract: A method for detecting a fall by a user includes a method of detecting a fall by a user. The method includes processing measurements obtained from one or more sensors to extract a respective value for a plurality of features associated with a fall. A respective log likelihood ratio for each of the values is determined. Whether the user has fallen is determined based on the determined log likelihood ratios.

Abstract: In one aspect, a method for displaying measurement information from at least one sensor of a machine is provided. In another aspect, a computing device for displaying measurement information from at least one sensor of a machine is provided. In another aspect, a system for displaying measurement information from at least one sensor of a machine is provided.

Abstract: A method, implemented on a computer, for calculating vertical trend curve uncertainty of spatially correlated reservoir data. The method includes inputting, into the computer, a sample reservoir data comprising correlated data; applying, using the computer, a variogram to the sample reservoir data to select a plurality of subsets of data, the subsets of data being substantially less correlated than the sample reservoir data; and applying, using the computer, a bootstrap process on each of the plurality of subsets of data to obtain a plurality of bootstrap data sets from each of the plurality of subsets of data. The method further includes calculating vertical trend curves for each of the obtained plurality of bootstrap data sets, ranking the vertical trend curves by using a selected statistical parameter to obtain ranked vertical trend curves, and characterizing the uncertainty based on the ranked vertical trend curves.

Abstract: A system is disclosed for obtaining and aggregating opinions generated by multiple sources with respect to one or more objects. The disclosed system uses observed variables associated with an opinion and a probabilistic model to estimate latent properties of that opinion. With those latent properties, the disclosed system may enable publishers to reliably and comprehensively present object information to interested users.

Abstract: Techniques for detecting, analyzing, and/or reporting code clone are described herein. In one or more implementations, clone-code detection is performed on one or more source code bases to find true and near clones of a subject code snippet that a user (e.g., a software developer) expressly or implicitly selected. In one or more other implementations, code clone is analyzed to estimate the code-improvement-potential (such as bug-potential and code-refactoring-potential) properties of clones. One or more other implementations present the results of code clone analysis with indications (e.g., rankings) of the estimated properties of the respective the clones.