Abstract: Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Abstract: Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Abstract: Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Abstract: Techniques for scenario planning are provided. In one example, a computer-implemented method can comprise analyzing, by a device operatively coupled to a processor, content using a topic model. The content can be associated with a defined source and is related to one or more current events. The computer-implemented method can also comprise determining, by the device, one or more portions of the analyzed content that are relevant to one or more key risk drivers using a risk driver model. The computer-implemented method can also comprise aggregating, by the device, the determined one or more portions into one or more emerging storylines based on values of one or more attributes of the topic model.

Abstract: A system, computer program and method for inspection of a system under inspection. The system may include an inspection program configured to access information available at the system under inspection and generate inspection data for the system under inspection. A runtime platform independent from the inspection program at the system under inspection is configured to limit the limit the contents of the inspection data to a maximum information content. A trusted third-party computer system may assist in selecting the inspection program and transferring the resulting inspection data.

Abstract: A method for operating a data communication system comprises the steps of (a) originating an electronic commerce transaction at a first party, (b) transmitting the electronic commerce transaction through the data communications network towards a second party, (c) during the step of transmitting, inputting the electronic commerce transaction to an electronic commerce transaction filter that is interposed between two network components, and (e) operating the electronic commerce transaction filter to take some action with respect to the electronic commerce transaction.

Abstract: Text and graphics are justified along one physical dimension to a predetermined line of justification. A plurality of physical parameters are employed in the justification, each of the parameters is assigned a compression and an expansion adjustment ratio. Such ratios define the maximum adjustment range of each of the parameters. A priority of adjustment is assigned to each of the parameters such that one parameter being adjusted and capable of meeting justification needs is adjusted to the exclusion of all other possible parameter adjustments. In vertical justification of a plurality of columns, text distribution precedes the vertical adjustment. For such vertical justification, the priority of adjustment is based upon natural text/graphics breaks; top priority is use of lead outs, second is skips, third is spaces and last is textual adjustments. Justification is preferably proportional, i.e., the ratios are adjusted when the maximum permitted adjustment is not required for justification.

Abstract: A large plurality of electronically-stored fonts are managed and selected for use in a particular presentation (printing, display) of a document represented by electrical signals by either an explicit or implicit method. A new font by either selecting a completely defined font or by selecting predetermined characteristics of font graphics, such as italics, bold, point size, and the like which enable an implicit selection of a completely defined font. Such defined characteristics are interpreted by an automatic machine to complete font definitions for use by a document presentation device. A begin font command can specify a plurality of internal fonts with the order of specification indicating priority of selection for use in document presentation. Whether or not a specified internal font results in a defined font being activated is selectable by font definitions embedded with a received-text-data stream representing text/graphics to be presented.

Abstract: Text and graphics are recursively (includes iteratively) distributed among a set of balanceable columns capable of receiving text and graphics. The recursive distributions are at successively varying columnar depths (all columns in each recursion have a common target depth), upon completing each recursion, the difference between the resulting shortest and longest column depths is measured and compared with a standard. If the standard is met, the distribution is made final, otherwise subsequent recursions up to a predetermined number of recursions are employed. If the standard is not met, then after the predetermined number of recursions, the distribution yielding the least differential is selected as the final distribution. Vertical justification of the columns follows.

Abstract: Machine-implemented text/graphics formatting is based upon a logical page area on a presentation-receiving medium, such as a CRT face, sheet of paper and the like. Named text and graphics receiving areas are selectively assignable to the logical pages of a document being formatted for visual presentation and are addressable and formattable independent of other formatting in any logical page. The named areas are machine defined such that one area can have portions thereof automatically assigned to and presented with any arbitrary number of logical pages. Such areas are managed in a text formatting machine to facilitate formatting headers based upon text contained in a succession of logical pages that are outside the named area. A first class of such named areas is placed upon the page when formatting to the page is ended, while a second class of such named areas is placed on the page in response to a command. The placement of the second class on a page can result in starting formatting new pages.