Abstract: A method and apparatus for providing virtual weather data are described. Embodiments retrieve a plurality of weather data snapshots of historical weather data and provide an API through which a plurality of remote clients request weather data. A request specifying a first set of geographical and spatial coordinates and further specifying a first set of time and date coordinates is received. In response to the request, a first set of weather data is determined from the plurality of weather data snapshots of historical weather data, based on the first set of geographical and spatial coordinates and the first set of time and date coordinates and transmitted to the first remote client. A plurality of follow-on sets of geographical and spatial weather data are also requested and transmitted to the first remote client.

Abstract: Systems and methods for filtering objects of interest associated with an investigation. One method includes receiving a role identifier. The method includes retrieving metadata corresponding to the plurality of objects of interest. The method includes determining, with a classifier, a plurality of relationships between at least two of the objects of interest based on the metadata. The method includes identifying, based on the metadata, a subset of the plurality of relationships that are associated with the role identifier, the subset of the plurality of relationships including a subset of the plurality of objects of interest. The method includes generating a graphical representation including a first indication of the subset of the objects of interest and a second indication of the subset of the plurality of relationships. The method includes presenting the graphical representation on a display communicatively coupled to the electronic processor.

Abstract: Embodiments of the present invention provide a system for identifying and pooling resources, as well as tools that enable users to manage the pooled resources. In particular, the system may identify resource data provided by an authenticated user and assign a classification to the resource based on the data type. The system may further create logical links between and amongst the resources provided by all authenticated users within the system according to their respective classifications, grouping like resources or related resources together. Resources may be assigned to one or more classifications and may be “tagged” for later identification and retrieval by the system based on the data contained within the resources. The system may then provide the aggregated data to the user for further processing and input.

Abstract: A computing device automatically classifies an observation vector. A label set defines permissible values for a target variable. Supervised data includes a labeled subset that has one of the permissible values. A converged classification matrix is computed based on the supervised data and an unlabeled subset using a prior class distribution matrix that includes a row for each observation vector. Each column is associated with a single permissible value of the label set. A cell value in each column is a likelihood that each associated permissible value of the label set occurs based on prior class distribution information. The value of the target variable is selected using the converged classification matrix. A weighted classification label distribution matrix is computed from the converged classification matrix. The value of the target variable for each observation vector of the plurality of observation vectors is output to a labeled dataset.

Abstract: The current disclosure generally relates to database management systems (DBMSs) and may be generally directed to methods and systems of using artificial intelligence (i.e. machine learning and/or anticipation functionalities, etc.) to learn a user's use of a DBMS, store this “knowledge” in a knowledgebase, and anticipate the user's future operating intentions. The current disclosure may also be generally directed to associative methods and systems of constructing DBMS commands. The current disclosure may also be generally directed to methods and systems of using a simplified DBMS command language (SDCL) for associative DBMS command construction. The current disclosure may also be generally directed to artificially intelligent methods and systems for associative DBMS command construction. The current disclosure may also be generally directed to methods and systems for associative DBMS command construction through voice input.

Abstract: Embodiments of the present invention relate to providing business customers with predictive capabilities, such as identifying valuable customers or estimating the likelihood that a product will be purchased. An adaptive sampling scheme is utilized, which helps generate sample data points from large scale data that is imbalanced (for example, digital website traffic with hundreds of millions of visitors but only a small portion of them are of interest). In embodiments, a stream of sample data points is received. Positive samples are added to a positive list until the desired number of positives is reached and negative samples are added to a negative list until the desired number of negative samples is reached. The positive list and the negative list can then be combined, shuffled, and fed into a prediction model.

Abstract: A device may receive multimedia data, metadata, and/or policy data. The device may process the policy data using a first set of techniques to determine a first set of embeddings for the policy data. The device may process the multimedia data or the metadata using a second set of techniques to determine a second set of embeddings for the multimedia data or the metadata. The device may process the first set of embeddings and the second set of embeddings using a knowledge graph to determine whether the multimedia content or the access by the user violates the policy. The device may perform an action based on a result of processing the first set of embeddings and the second set of embeddings. The action may relate to the multimedia content or the access to the multimedia content by the user.

Abstract: A carrying device with a built-in security system including a security unit (10) having components housed in an integral unit, where the components include a camera (1) with a light sensor (2); a speed sensor (4); a distance sensor (9); a GPS tracker (8); a transponder (7) for sending and accepting digital data; a microcontroller (15), and a rechargeable power supply (5) in electrical communication with the microcontroller (15), the camera (1), the speed sensor (4), the distance sensor (9), the GPS tracker (8), and the transponder (7), to monitor the location and contents of the carrying device and to provide real time feedback to the user.

Abstract: A system and method is provided for implementing platform security on a consumer electronic device having an open development platform. The device is of the type which includes an abstraction layer operable between device hardware and application software. A secure software agent is provided for embedding within the abstraction layer forming the operating system. A secure store is provided for storing security information unique to one or more instances of the application software. The secure software agent uses the security information for continuous runtime assurance of ongoing operational integrity of the operating system and application software and thus operational integrity of the device.

Abstract: Embodiments of the present disclosure provide a method and an apparatus for determining a similar document set to a target document from a plurality of documents. Each of the multiple documents and the target document may include a plurality of words, and each of words corresponds to a different integer. The method comprises: for each document among the plurality of documents and the target document, obtaining a set of integers associated with a document based on a set of words associated with the document, converting the set of integers associated with the document into a vector with a same dimension based on a predefined conversion rule; and determining the similar document set based on differences between the corresponding vectors for the multiple documents and the vector for the target document.

Abstract: An approach for identifying and managing tasks in an e-mail system. An e-mail task manager, receives an e-mail and creates n-grams based on e-mail data content and metadata content. The e-mail task manager identifies the e-mail as a task e-mail based on analyzing the n-grams to detect a task and a task owner. The e-mail task manager determines task details associated with the task e-mail based on the n-grams and determines a collection of recommended actions based on the task details. The e-mail task manager stores the collection of recommended actions and associated action states in a task history store. The e-mail task manager outputs the collection of recommended actions and the action states associated with the task e-mail based on the task owner and updates the collection of recommend actions and the associated action states based on interactions by the task owner.

Abstract: A system and method is described for protecting applications against malicious URL links by identifying a final destination. The system and method also includes enabling a user process to directly connect to the final destination, bypassing the original URL altogether; thereby bypassing the hacker's ability to use that URL to programmatically send the application to a malicious site.

Abstract: Functionality is disclosed herein for providing temporary access to a resource. A software product that is executing in response to a request from a customer may access one or more resources of a software provider. The resources that may be accessed by a software product may be identified within an access policy. The customer is prevented from accessing the resource when the software product is not executing.

Abstract: Embodiments of the invention provide techniques which utilize crowdsourced reports of environmental conditions to predict and/or prevent disease outbreaks. In one aspect, a method comprises receiving one or more crowdsourced reports about one or more environmental conditions; inferring one or more input parameters for at least one disease outbreak model based at least in part on the one or more crowdsourced reports; applying the at least one disease outbreak model to at least the one or more inferred parameters to predict one or more characteristics of at least one potential disease outbreak associated with the reported one or more environmental conditions; and, based at least in part on the predicted one or more characteristics, implementing one or more corrective actions to mitigate the at least one potential disease outbreak.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein for a Clustering Engine that determines that respective actions, performed in a first instance of a virtual environment by a first user during a first time range, correspond with a first latent state. The Clustering Engine determines that respective actions, performed in a second instance of the virtual environment by a second user during the first time range, correspond with a second latent state. The Clustering Engine triggers a first virtual environment feature based on a first latent state parameter space for the first user. The Clustering Engine triggers a second virtual environment feature based on a second latent state parameter space for the second user.

Abstract: A system for detecting an unknown undesirable event comprises an input device configured to receive a dataset comprising a plurality n of multidimensional datapoints (MDDPs), a processor configured to embed the MDDPs in an lower dimension embedded space to obtain embedded MDDPs, and a detection engine configured to calculate distributions of distances Dnni, i=1, . . . , n of each embedded MDDP from a plurality of nearest-neighbors (nn) to compute a threshold Dnnt and to classify a particular MDDP of the dataset or a newly arrived MDDP (NAMDDP) as an abnormal MDDP based on comparison with threshold Dnnt, wherein the classification is automatic and unsupervised without relying on a signature, rules or domain expertise and wherein the particular MDDP classified as abnormal is indicative of the unknown undesirable event.

Abstract: A process for improving dispatch of different types of law enforcement patrols (LEPs) for achieving a desired deterrent effect includes first receiving patrol route information indicating patrol routes taken by first LEPs, and then determining, as a function of a type of each of the first LEPs, a threshold level of deterrence reached for each of the patrol routes taken. Subsequently, a threshold level of deterrence desired (TLoDD) for each of the plurality of patrol routes is determined as a function of historical and/or real-time crime information. A first patrol route having a threshold level of deterrence reached (TLoDR) that is less than a TOoDD is identified and, as a function of the difference, a particular type of second LEP having a sufficient deterrent effect factor to compensate for the difference is identified. An available responding second LEP of the particular type is then identified for dispatch.

Abstract: Described is a system for real-time object recognition. During operation, the system extracts convolutional neural network (CNN) feature vectors from an input image. The input image reflects a scene proximate the system, with the feature vector representing an object in the input image. The CNN feature vector is matched against feature vectors stored in a feature dictionary to identify k nearest neighbors for each object class stored in the feature dictionary. The matching results in a probability distribution over object classes stored in the feature dictionary. The probability distribution provides a confidence score that each of the object classes in the feature dictionary are representative of the object in the input image. Based on the confidence scores, the object in the input image is then recognized as being a particular object class when the confidence score for the particular object class exceeds a threshold.

Abstract: A tagging drone (TD) responds to a received query of availability initiated from a command and control drone (CCD) or command and control station (CCS), over a network, for investigating or tagging a designated target. The TD receives one or more dispatching instructions and heads to the designated target. The TD performs tagging of the designated target and determines whether the designated target was successfully tagged as a tagged target. The tagged target is tracked and tracking data is provided for recovery resource capture of the tagged target.

Abstract: Embodiments relate to converting semi-structured spatial data. Initially, semi-structured spatial data is recursively traversed to determine a dynamically nested structure. The dynamically nested structure is translated into an application specific layer structure based on feature type grouping and display capabilities of a geographic information system (GIS) application. Next, an input symbology is determined for each feature in the semi-structured spatial data. The input symbology of each feature is analyzed to determine an application symbology for each map layer in the GIS application. A spatial database is created for the GIS application based on the application specific layer structure. The features are translated from the semi-structured spatial data into the spatial database, and the application symbology of each map layer is used to render the features in the GIS application.

Abstract: Methods are provided for implementing schemes for embedding a particular optimization problem into a particular hardware solution employing unique graph embedding techniques. The disclosed methods implement an adiabatic quantum optimization in a quantum computing device or a quantum processor. Heuristics for graph minor embedding are employed to map a problem graph structure of a particular binary unconstrained optimization problem onto a physical graph structure (topology) of the quantum computing device or quantum processor to provide an optimized hardware implementation. Known constraints that are presented with current schemes in their application to particular hardware solutions are avoided, including limited qubit connectivity and the presence of faulty qubits.

Abstract: Techniques are disclosed for determining a possible cause of a problem in a computer system. A trouble-shooting component of the computer system may perform forward chaining on the available data to determine one or more hypotheses of the cause of the problem. The component may then perform backward chaining on the hypotheses to determine missing information that, if known, would increase or decrease the likelihood of the hypotheses being true. Then, the component may perform Bayesian probability analysis on the known and missing information to determine a probability that each hypothesis is correct.

Abstract: A computing device automatically classifies an observation vector. (a) A converged classification matrix is computed that defines a label probability for each observation vector. (b) The value of the target variable associated with a maximum label probability value is selected for each observation vector. Each observation vector is assigned to a cluster. A distance value is computed between observation vectors assigned to the same cluster. An average distance value is computed for each observation vector. A predefined number of observation vectors are selected that have minimum values for the average distance value. The supervised data is updated to include the selected observation vectors with the value of the target variable selected in (b). The selected observation vectors are removed from the unlabeled subset. (a) and (b) are repeated. The value of the target variable for each observation vector is output to a labeled dataset.

Abstract: Embodiments are directed towards a machine learning repository for managing machine learning (ML) model envelopes, ML models, model objects, or the like. Questions and model objects may be received by a ML model answer engine. Machine learning (ML) model envelopes may be received based on the questions. The model objects may be compared to parameter models associated with the ML model envelopes. ML model envelopes may be selected based on the comparison such that the model objects satisfy the parameter models of each of the selected ML model envelopes. ML models included in each selected ML model envelope may be executed to provide score values for the model objects and the score values may be included in a report.

Abstract: An apparatus is provided to interface with users to perform group assessment processing and display of results in conjunction with the selection of items.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for aggregating source code metric values. One of the methods includes obtaining data representing a directed graph, wherein one or more nodes of the graph are associated with a respective set of one or more metric instances, wherein each set of metric instances for each node includes all metric instances occurring in sets of any node descendant from the node in the graph, wherein each metric instance identifies a location in a source code base, and wherein each metric instance has a respective metric value, a respective identifier, and a respective attribute type. An attribute value is computed for a first node in the graph from the respective metric value of each metric instance in a first set of metric instances associated with the first node.

Abstract: Disclosed is an method and apparatus for electric power distribution in an energy storage system. The electric power distribution method of the energy storage system (ESS) includes computing a total power amount on the basis of a received user output target power amount and a deviation amount, determining a power distribution power conditioning system (PCS) to which the total power amount is distributed out of the PCSs included in the ESS, and distributing the total power amount on the basis of the power distribution PCS. The deviation amount is a difference between an existing user output target power amount used in an existing power distribution process and an existing total power amount.

Abstract: A method of forming semiconductor elements in an artificial neural network, the method including forming a substrate including an oxide layer, forming a Silicon layer on the oxide layer, depositing a thin film dopant layer on the Silicon layer, and controlling a concentration of the dopant in the thin film dopant layer.

Abstract: Methods and apparatus are provided involving adaptive content inspection. In one embodiment, a content inspection processor may identify information with respect to input data and provide the information to a host controller. The host controller may adapt search criteria or other parameters and provide the adapted parameter to the content inspection processor. Other embodiments may include a content inspection processor having integrated feedback, such that results data is fed back to the content inspection processor. The results data may be processed before being provided to the content inspection processor.

Abstract: The invention relates to a system (SYS) for automatically extracting a location of an abnormality with respect to an anatomical structure from a report, the system comprising a tokenizer (U10) for tokenizing the report or a part of it, thereby producing a plurality of tokens, and an analyzer (U20) for identifying a semantic structure comprising identified tokens of the plurality of tokens, describing the location of the abnormality with respect to the anatomical structure. Optionally, the system further comprises a mapper (U30) for annotating a diagram representing the anatomical structure, based on the identified semantic structure describing the location of the abnormality with respect to the anatomical structure. Using the system, the location of the abnormality with respect to the anatomical structure can be extracted from each report of the plurality of reports produced over the period of time. The extracted locations may be used by a clinician for diagnostic purposes.

Abstract: A method, computer system, and a computer program product for determining the reliability of a claim is provided. The present invention may include receiving an input data from a user. The present invention may also include analyzing the claim associated with the received input data to determine a reliability score associated with the input data, wherein the claim is semantically similar to the received input data. The present invention may further include generating, from a prediction model, the reliability score for the claim associated with the received input data. The present invention may also include presenting the reliability score for the claim associated with the received input data to the user.

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

Abstract: An input is selected from a set of inputs used by a prediction model to produce an initial predicted value of an outcome. A changed predicted value of the outcome is produced by removing the selected input from the inputs to the model. An actual value of the outcome is obtained. A label residual is computed using the actual value and the changed predicted value. A second prediction model is formed to predict a value of the selected input. A variable residual is computed using an actual value and the predicted value of the selected input. An expression is generated of a plot of the label residual and the variable residual. The selected input is transformed, to form a transformed selected input, where the model produces a second predicted value of the outcome by using the transformed selected input.

Abstract: In a system for triggering generation of an alert for delivery to a remote device, the system can include memory having a user profile database, and a content library database. The system can include a recipient user device having a network interface and a recipient I/O subsystem. The system can include a supervisor device having a network interface and a supervisor I/O subsystem. The system can include a content management server than can direct the generation of a placement interface in the graphical user interface by the recipient I/O subsystem, direct the generation of a presentation interface direct the generation of a coupling interface at each of the recipient user device and the supervisor user device, and generate and send an alert to the recipient user device and the supervisor device.

Abstract: The systems and methods described herein relate to mapping and identifying expert resources. The systems and methods described herein may provide a set of technologies, that work together as one solution, to effectively and efficiently resolve user questions. A cognitive engine may autonomously learn which experts have the knowledge to quickly solve a question or whether a previous question is similar enough to provide a solution instantly. Using machine learning, a know-how map may be created, linking all of the users of the system with their areas of expertise. Expert resources among the users may be mapped by determining connections between topics (and their corresponding tags) and calculating an expert score related to each topic for each user. These connections and expert scores are subsequently used during expert routing for each new question, to find those users with the expertise to give the best possible solution.

Abstract: A method includes receiving a plurality of recommendations for content items from a plurality of sending users for a recipient user through a plurality of sources, determining that the recipient user is interested in viewing a subset of the plurality of recommendations for content items from a first sending user of the plurality of sending users, and generating a first sending user playlist including the subset of the plurality of recommendations for content items from the first sending user but not from other sending users of the plurality of sending users.

Abstract: Embodiments disclosed include data center infrastructure management (DCIM) systems and methods configured to, collect data center compute systems, power systems, and facility systems data, trigger an action or actions based on a diagnosed or predicted condition according to the collected data, and thereby control via a compute, power, and facilities module, the compute systems, power systems and facility systems in the data center. According to an embodiment, the control via the compute, power, and facilities module comprises calibrating the compute, power, and facility systems based on an estimated compute requirement, and an associated power, cooling, and network data resource requirement. The estimated compute requirement comprises estimating compute density per real-time power wattage, and storage density per real-time power wattage.

Abstract: A method is proposed for real-time economic dispatch in power system operation, especially in systems that include renewable power sources that may cause heavy deviations from a generation schedule due to their uncertain outputs. According to the method an optimal generation schedule is obtained based on forecasted load data. This schedule has to be adjusted if the actual load and renewable energy source outputs unexpectedly deviate from the forecasted value. An algorithm employed in the method is capable of dictating generation adjustments which minimize total generation costs. The algorithm is a modification of the base point and participation factor method. It differs from existing methods in that a precise model of transmission losses is adopted in the algorithm to achieve higher accuracy in optimization. The proposed method also has significant advantage in execution speed so that it is suitable for real-time operation.

Abstract: Route search systems, methods, and programs acquire movement paths of a plurality of users, and acquire difference values for a plurality of characteristics. The difference values each indicate a difference between a characteristic of a reference route and a characteristic of the movement paths of the plurality of users. Systems, methods, and programs classify the movement paths of each of the users into a plurality of types such that movement paths with a plurality of similar difference values belong to a same type, set a cost of a road for each of the types; and search for a route on the basis of the set cost.

Abstract: A method for performing assisted knowledge discovery includes receiving a dataset. Each of a plurality of analytical techniques is applied to the received data set to generate a plurality of corresponding analytical results. A composite validation metric is applied to each of the plurality of analytical results. The composite validation metric is a single scoring/ranking function that is created from a plurality of different scoring/ranking functions. The plurality of analytical results is presented to a user arranged in accordance with the results of the applying the composite validation metric to each of the plurality of analytical results. A selection from the user from among the plurality of analytical results is recorded. The user's selection is used to modify the composite validation metric such that the analytical techniques responsible for generating the selected analytical result is scored/ranked more highly.

Abstract: A method of predicting battery test results includes using a battery test computer to predict a battery test result for a battery undergoing testing. The battery test computer comprises a tangible, non-transitory computer-readable medium storing a battery test management system implemented as one or more sets of instructions. The battery test management system includes a predictive module configured to predict the battery test result using less than all data required for the battery test to be complete, a validation module configured to validate the prediction, and a training module configured to re-train the predictive module based on results generated by the validation module. The battery test computer also includes processing circuitry configured to execute the one or more sets of instructions, and outputting, via a user interface, the prediction of the result and a confidence level associated with the prediction.

Abstract: Various aspects of the subject technology related to systems and methods for mapping communication content based on topic analysis to determine user knowledge scores. A system may be configured to receive communication content including spoken and non-spoken content. The system may convert spoken content to non-spoken content and a data set of the communication content may be generated. The system may construct a generative statistical model identifying a list of topics in the data set. The generative statistical model may also identify the topic percentage of words in the data set that are associated with a given topic. The system may generate a communication content graph identifying user nodes and word edges. The system may calculate a topic strength for each word edge and determine a user knowledge score for each user associated with each identified topic. The system may output the user knowledge score.

Abstract: The present invention relates to a method for processing data by a server (1) including at least one data-processing unit and a data storage means, the method being characterized in that it includes the following steps, following the activation of at least one trigger implemented by the processing unit(s), said trigger(s) being capable of being activated in response to a predefined event: (a) an attempt by the processing unit(s) to determine a state of at least one index selected, on the basis of the activated trigger, from among a set of observable indices relating to personal data of a user and/or relating to general data; (b) the generation and storage, in the storage means, of a situational signature of the user in accordance with the results of said attempt to determine the state of at least one index; (c) the comparison of said situational signature of the user with a plurality of masks, each mask being associated with a reference situation and corresponding to a situational signature space, so as to id

Abstract: Embodiments relate to supporting analysis of evaluations found on the internet. An aspect includes acquiring evaluation information comprising evaluations of each a first plurality of evaluation targets made by any of a plurality of evaluators. Another aspect includes generating consensus information regarding an evaluation of a predetermined evaluation target by determining a coincidence between a dispersion degree of evaluations with respect to the predetermined evaluation target and a central value of dispersion degrees of evaluations with respect to individual ones of the first plurality of evaluation targets. Another aspect includes generating distinctiveness information regarding the evaluations made by a predetermined evaluator by determining coincidence between a dispersion degree of evaluations made by the predetermined evaluator and a central value of dispersion degrees of evaluations made by individual ones of the plurality of evaluators.

Abstract: Route search systems, methods, and programs acquire movement paths of a plurality of users, and classify, on the basis of a plurality of characteristics of the movement paths of the plurality of users, the movement paths of each of the users into a plurality of types such that movement paths with a plurality of similar characteristics belong to a same type. The systems, methods, and programs set a cost for each of the types and each attribute of a road on the basis of the plurality of movement paths of each of the types, classify, on the basis of a plurality of characteristics of a movement path of a route searcher, the route searcher into one of the types, and search for a route on the basis of the cost which is set for the type of the route searcher.

Abstract: Techniques disclosed herein describe joining processing elements (e.g., of a streams processing environment) using optimization techniques, such as by whole program optimization. An optimization tool evaluates multiple processing elements based on one or more optimization rules. The optimization tool identifies, based on the evaluation, processing elements that can be merged. The optimization tool joins the identified processing elements together.

Abstract: Techniques disclosed herein describe joining processing elements (e.g., of a streams processing environment) using optimization techniques, such as by whole program optimization. An optimization tool evaluates multiple processing elements based on one or more optimization rules. The optimization tool identifies, based on the evaluation, processing elements that can be merged. The optimization tool joins the identified processing elements together.

Abstract: A selected document from corpus of a cognitive computing system is processed according to its association with a category of documents already contained within the corpus, such as a topical category. Then, the cognitive computing system is engaged automatically to query one or more questions previously-associated with the category to discover discrepancies between the selected document and the other corpus documents. If a discrepancy is found, a confidence factor based upon extracted natural language entities and relationships is assigned to the discrepancy, and it is flagged and reported to a user for reconciliation.

Abstract: A content subject matter area of interest to a user is determined, using eye-gaze analysis of a user viewing existing activity stream content, according to content at a content location viewed by the user within the existing activity stream content. User-specific activity stream content augmentations are configured that are applicable to new activity stream content viewed by the user that includes the content subject matter area of interest to the user determined from the eye-gaze analysis. Using the configured user-specific activity stream content augmentations, portions of the new activity stream content viewed by the user determined to include the content subject matter area of interest to the user are augmented.

Abstract: A system aggregates data related to a non-conformance system in an aircraft and allocates resources to repairing the non-conformance condition. The system includes a service bus that receives and distributes the non-conformance condition and an optimizer tool that generates repair alternatives. The optimizer tool allows dynamic reconfiguration of rules to activate and deactivate or change a weight of individual rules in a rule set.