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5366 results about "Software system" patented technology

A software system is a system of intercommunicating components based on software forming part of a computer system (a combination of hardware and software). It "consists of a number of separate programs, configuration files, which are used to set up these programs, system documentation, which describes the structure of the system, and user documentation, which explains how to use the system".

Real-time receipt, decompression and play of compressed streaming video/hypervideo; with thumbnail display of past scenes and with replay, hyperlinking and/or recording permissively intiated retrospectively

Streaming compressed digital hypervideo received upon a digital communications network is decoded (decompressed) and played in a client-computer-based "video on web VCR" software system. Scene changes, if not previously marked upstream, are automatically detected, and typically twenty-one past scenes are displayed as thumbnail images. Hyperlinks within the main video scene, and/or any thumbnail image, show as hotspots, with text annotations typically appearing upon a cursor "mouse over". All hyperlinks-as are provided and inserted by, inter alia, the upstream network service provider (the "ISP")-may be, and preferably are, full-custom dynamically-resolved to each subscriber/user/viewer ("SUV") upon volitional "click throughs" by the SUV, including retrospectively on past hypervideo scenes as appear within the thumbnail images. Hyperlinking permits (i) retrieving information and commercials, including streaming video/hypervideo, from any of local storage, a network (or Internet) service provider ("ISP"), a network content provider, and/or an advertiser network site, (ii) entering a contest of skill or a lottery of chance, (iii) gambling, (iv) buying (and less often, selling), (v) responding to a survey, and expressing an opinion, and/or (vi) sounding an alert.

Methods and systems for generating natural language descriptions from data

The invention is directed to a natural language generation (NLG) software system that generates rich, content-sensitive human language descriptions based on unparsed raw domain-specific data. In one embodiment, the NLG software system may include a data parser / normalizer, a comparator, a language engine, and a document generator. The data parser / normalizer may be configured to retrieve specification information for items to be described by the NLG software system, to extract pertinent information from the raw specification information, and to convert and normalize the extracted information so that the items may be compared specification by specification. The comparator may be configured to use the normalized data from the data parser / normalizer to compare the specifications of the items using comparison functions and interpretation rules to determine outcomes of the comparisons. The language engine may be configured to cycle through all or a subset of the normalized specification information, to retrieve all sentence templates associated with each of the item specifications, to call the comparator to compute or retrieve the results of the comparisons between the item specifications, and to recursively generate every possible syntactically legal sentence associated with the specifications based on the retrieved sentence templates. The document generator may be configured to select one or more discourse models having instructions regarding the selection, organization and modification of the generated sentences, and to apply the instructions of the discourse model to the generated sentences to generate a natural language description of the selected items.

System and method for conditional tracing of computer programs

A software system is disclosed which facilitates the process of tracing the execution paths of a program, called the client. The tracing is performed without requiring modifications to the executable or source code files of the client. Trace data collected during the tracing operation is collected according to instructions in a trace options file. At run time, the tracing library attaches to the memory image of the client. The tracing library is configured to monitor execution of the client and to collect trace data, based on selections in the trace options file. Conditional tracing, through the use of triggers and actions taken in response to the triggers, allows the developer to control the tracing operation. The triggers can be conditional triggers in which the corresponding action is taken only if a conditional expression is satisfied. The system can trace multiple threads and multiple processes. The tracing system provides a remote mode and an online mode. In remote mode, the developer sends the trace control information (which can include triggers and corresponding actions) to a remote user site together with a small executable image called the agent that enables a remote customer, to generate a trace file that represents execution of the client application at the remote site. In online mode, the developer can generate trace options (including triggers and corresponding actions), run and trace the client, and display the trace results in near real-time on the display screen during execution of the client program.

System and methodology and adaptive, linear model predictive control based on rigorous, nonlinear process model

A methodology for process modeling and control and the software system implementation of this methodology, which includes a rigorous, nonlinear process simulation model, the generation of appropriate linear models derived from the rigorous model, and an adaptive, linear model predictive controller (MPC) that utilizes the derived linear models. A state space, multivariable, model predictive controller (MPC) is the preferred choice for the MPC since the nonlinear simulation model is analytically translated into a set of linear state equations and thus simplifies the translation of the linearized simulation equations to the modeling format required by the controller. Various other MPC modeling forms such as transfer functions, impulse response coefficients, and step response coefficients may also be used. The methodology is very general in that any model predictive controller using one of the above modeling forms can be used as the controller. The methodology also includes various modules that improve reliability and performance. For example, there is a data pretreatment module used to pre-process the plant measurements for gross error detection. A data reconciliation and parameter estimation module is then used to correct for instrumentation errors and to adjust model parameters based on current operating conditions. The full-order state space model can be reduced by the order reduction module to obtain fewer states for the controller model. Automated MPC tuning is also provided to improve control performance.
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