Abstract: Testing J2EE applications, wherein J2EE applications comprise modules, the testing including identifying (204), from an application deployment descriptor, modules comprised within the J2EE application; identifying, from an identified module, at least one QOS element; and identifying, from the identified QOS element, a software resource to be tested. Typical embodiments further including generating Java test code; identifying, for the software resource to be tested, a user identification and a user password for a user that is a member of a role intended to protect the software resource; and testing the software resource to be tested by use of the Java test code, including passing as parameters to the Java test code at run time the user identification and user password.

Abstract: Managing a data mining environment, the data mining environment having a data mining tool and a data mining model. Embodiments include registering in a data set control table registered data sets, the registered data sets including the model training input data sets, model training results data sets, the scoring input data sets, and the scoring output data sets, registering the data mining model in a mining model control table, the mining model control table being related to the data set control table through a mining model control table foreign key, and registering the scoring output data sets in a scoring control table, the scoring control table being related to the data set control table through a scoring control table data set foreign key, the scoring control table being related to the mining model control table through a scoring control table mining model foreign key.

Abstract: Development of domain-specific analytic applications having predefined data mining models, including identifying a business problem to be solved; selecting a data mining algorithm appropriate for solving the business problem; defining data schema for use as inputs and outputs to and from the mining algorithm, the data schema including input data schema and output data schema; and defining a mining model based on the data schema to solve the business problem; whereby a domain-specific analytic application is developed, the analytic application having at least one predefined data mining model, the analytic application having the capabilities of: populating the input data schema with sample historical data; production training the mining model using the sample historical data in the input data schema, whereby a production trained mining model is created; and production scoring production data using the production trained mining model, production scoring further comprising applying the production trained mining m

Abstract: Navigating a UAV including orbiting a waypoint including defining four bracket lines surrounding a waypoint, flying the UAV from a course segment having coordinate values in a range into a course segment not having coordinate values in the range, wherein a bounding bracket line defines a boundary between the segments; selecting, a heading parallel to a bracket line in dependence upon an orbital direction; the UAV in the orbital direction to fly on a the heading; and repeatedly: flying the UAV from a course segment having coordinate values in a range into a course segment not having coordinate values in the range, wherein a bounding bracket line defines a boundary between the segments; and turning the UAV in the orbital direction to fly on a heading parallel to the bounding bracket line.

Abstract: Automated data mining using domain-specific analytic applications for solving predefined problems, including populating input data schema, the input data schema having a format appropriate to solution of a predefined problem. Production training a predefined data mining model to produce a trained data mining model, the predefined data mining model comprising a predefined data mining model definition, production training having an output of a knowledge base. Executing a preselected data mining algorithm in production training mode. Production scoring input data from the input data schema. The method typically includes scheduling the steps of populating input data schema, production training, and production scoring. Typically the analytic application includes predefined problems, predefined data mining algorithms, predefined data schema, and at least one predefined data mining model definition.

Abstract: Storing data mining clustering results in a relational database for querying and reporting, including reading, from a hierarchical clustering node, clustering data describing a clustering, and recording the clustering data in a relational clustering record; reading, from a hierarchical cluster node embodied in the hierarchical representation of data mining results, cluster data describing a cluster, and recording the cluster data in a relational cluster record; reading, from a hierarchical cluster attribute node embodied in the hierarchical representation of data mining results, cluster attribute data describing a cluster attribute, and recording the cluster attribute data in a relational cluster attribute record; reading, from a hierarchical cluster attribute bin node embodied in the hierarchical representation of data mining results, cluster attribute bin data describing a cluster attribute bin, and recording the cluster attribute bin data in a relational cluster attribute bin record.

Abstract: A method, system, and program for controlling advertising output during hold periods are provided. A context for a call on hold is detected. An advertisement is selected for output during a hold space a hold period of the call according to the context. Output of the advertisement during the hold space is controlled, wherein the advertisement is specified according to the context. The advertisement may include text messages, audio messages, video messages, for advertising a product or service or making an announcement.

Abstract: A method for toggling check box status, implemented as a software program installed and operating on a computer comprising a computer processor coupled to computer memory. Embodiments of the invention include detecting a touch event on a check box, toggling the status of the check box, and repeatedly, for a multiplicity of repetitions, carrying out the steps of detecting a drag event for each additional check box onto which a user drags the pointer, wherein the user drags the pointer onto at least one additional check box, and toggling the status of each additional touch box for which a drag event is detected.

Abstract: Automated data mining using domain-specific analytic applications for solving predefined problems, including populating input data schema, the input data schema having a format appropriate to solution of a predefined problem. Production training a predefined data mining model to produce a trained data mining model, the predefined data mining model comprising a predefined data mining model definition, production training having an output of a knowledge base. Executing a preselected data mining algorithm in production training mode. Production scoring input data from the input data schema. The method typically includes scheduling the steps of populating input data schema, production training, and production scoring. Typically the analytic application includes predefined problems, predefined data mining algorithms, predefined data schema, and at least one predefined data mining model definition.