Abstract: The present disclosure provides anti-BTC antibodies, methods of producing said antibodies, pharmaceutical compositions comprising said antibodies, and methods of using said antibodies. The present disclosure also provides multi-specific binding molecules, e.g., bispecific antibodies, comprising a BTC binding moiety and an anti-VEGF binding moiety.

Abstract: The present disclosure provides anti-BTC antibodies, methods of producing said antibodies, pharmaceutical compositions comprising said antibodies, and methods of using said antibodies. The present disclosure also provides multi-specific binding molecules, e.g., bispecific antibodies, comprising a BTC binding moiety and an anti-VEGF binding moiety.

Abstract: The present disclosure provides anti-BTC antibodies, methods of producing said antibodies, pharmaceutical compositions comprising said antibodies, and methods of using said antibodies. The present disclosure also provides multi-specific binding molecules, e.g., bispecific antibodies, comprising a BTC binding moiety and an anti-VEGF binding moiety.

Abstract: The present disclosure provides anti-BTC antibodies, methods of producing said antibodies, pharmaceutical compositions comprising said antibodies, and methods of using said antibodies. The present disclosure also provides multi-specific binding molecules, e.g., bispecific antibodies, comprising a BTC binding moiety and an anti-VEGF binding moiety.

Abstract: The present invention envisages a system and method for automating the generation of business decision analytic models. The system uses a plurality of predictor variables stored in a plurality of data sets, to automatically create a business decision analytic model. The system includes a processor configured to process the data sets and determine the total number of records present in each of the data sets and the number of columns containing only numerical values. The processor selects a column containing only numerical values, from a dataset under consideration, and counts the number of unique numerical values in the selected column, and the total number of records present in the selected column. The two counts are compared and the selected column is transformed using a non-linear transformation to obtain a column of transformed values. The transformed values and corresponding time stamps are utilized for the purpose of model generation.

Abstract: A computer implemented system for automating the generation of an analytic model includes a processor configured to process a plurality of data sets. Each data set includes values for a plurality of variables. A time-stamping module is configured to derive values for a plurality of elapsed-time variables for each data set, and the plurality of variables and plurality of elapsed-time variables are included in a plurality of model variables. A model generator is configured to create a plurality of comparison analytic models each based on a different subset of model variables. Each comparison analytic model is configured to operate on new data sets associated with current leads, and to output a likelihood of successfully closing an associated transaction. A model testing module is configured to select an operational analytic model from among the comparison analytic models based on a quality metric.

Abstract: A computer implemented system for automating the generation of an analytic model includes a processor configured to process a plurality of data sets. Each data set includes values for a plurality of variables. A time-stamping module is configured to derive values for a plurality of elapsed-time variables for each data set, and the plurality of variables and plurality of elapsed-time variables are included in a plurality of model variables. A model generator is configured to create a plurality of comparison analytic models each based on a different subset of model variables. Each comparison analytic model is configured to operate on new data sets associated with current opportunities, and to output a likelihood of successfully closing each current opportunity. A model testing module is configured to select an operational analytic model from among the comparison analytic models based on a quality metric.

Abstract: The present invention envisages a system and method for automating the generation of business decision analytic models. The system uses a plurality of predictor variables stored in a plurality of data sets, to automatically create a business decision analytic model. The system includes a processor configured to process the data sets and determine the total number of records present in each of the data sets and the number of columns containing only numerical values. The processor selects a column containing only numerical values, from a dataset under consideration, and counts the number of unique numerical values in the selected column, and the total number of records present in the selected column. The two counts are compared and the selected column is transformed using a non-linear transformation to obtain a column of transformed values. The transformed values and corresponding time stamps are utilized for the purpose of model generation.

Abstract: A computer implemented system for automating the generation of an analytic model includes a processor configured to process a plurality of data sets. Each data set includes values for a plurality of variables. A time-stamping module is configured to derive values for a plurality of elapsed-time variables for each data set, and the plurality of variables and plurality of elapsed-time variables are included in a plurality of model variables. A model generator is configured to create a plurality of comparison analytic models each based on a different subset of model variables. Each comparison analytic model is configured to operate on new data sets associated with current leads, and to output a likelihood of successfully closing an associated transaction. A model testing module is configured to select an operational analytic model from among the comparison analytic models based on a quality metric.

Abstract: A computer implemented system for automating the generation of an analytic model includes a processor configured to process a plurality of data sets. Each data set includes values for a plurality of variables. A time-stamping module is configured to derive values for a plurality of elapsed-time variables for each data set, and the plurality of variables and plurality of elapsed-time variables are included in a plurality of model variables. A model generator is configured to create a plurality of comparison analytic models each based on a different subset of model variables. Each comparison analytic model is configured to operate on new data sets associated with current opportunities, and to output a likelihood of successfully closing each current opportunity. A model testing module is configured to select an operational analytic model from among the comparison analytic models based on a quality metric.

Abstract: The present invention envisages a system and method for automating the generation of business decision analytic models. The system uses a plurality of predictor variables stored in a plurality of data sets, to automatically create a business decision analytic model. The system includes a processor configured to process the data sets and determine the total number of records present in each of the data sets and the number of columns containing only numerical values. The processor selects a column containing only numerical values, from a dataset under consideration, and counts the number of unique numerical values in the selected column, and the total number of records present in the selected column. The two counts are compared and the selected column is transformed using a non-linear transformation to obtain a column of transformed values. The transformed values and corresponding time stamps are utilized for the purpose of model generation.

Abstract: The present invention envisages a system and method for automating the generation of business decision analytic models. The system uses a plurality of predictor variables stored in a plurality of data sets, to automatically create a business decision analytic model. The system includes a processor configured to process the data sets and determine the total number of records present in each of the data sets and the number of columns containing only numerical values. The processor selects a column containing only numerical values, from a dataset under consideration, and counts the number of unique numerical values in the selected column, and the total number of records present in the selected column. The two counts are compared and the selected column is transformed using a non-linear transformation to obtain a column of transformed values. The transformed values and corresponding time stamps are utilized for the purpose of model generation.

Abstract: The present invention envisages a system and method for automating the generation of business decision analytic models. The system uses a plurality of predictor variables stored in a plurality of data sets, to automatically create a business decision analytic model. The system includes a processor configured to process the data sets and determine the total number of records present in each of the data sets and the number of columns containing only numerical values. The processor selects a column containing only numerical values, from a dataset under consideration, and counts the number of unique numerical values in the selected column, and the total number of records present in the selected column. The two counts are compared and the selected column is transformed using a non-linear transformation to obtain a column of transformed values. The transformed values and corresponding time stamps are utilized for the purpose of model generation.

Abstract: The present invention envisages a system and method for automating the generation of business decision analytic models. The system uses a plurality of predictor variables stored in a plurality of data sets, to automatically create a business decision analytic model. The system includes a processor configured to process the data sets and determine the total number of records present in each of the data sets and the number of columns containing only numerical values. The processor selects a column containing only numerical values, from a dataset under consideration, and counts the number of unique numerical values in the selected column, and the total number of records present in the selected column. The two counts are compared and the selected column is transformed using a non-linear transformation to obtain a column of transformed values. The transformed values and corresponding time stamps are utilized for the purpose of model generation.

Abstract: A distributed inter-domain constraints-based routing technique is provided herein. A problem solving request is sent to nodes in a plurality of network domains that have a potential path between a source node and the destination node. The problem solving request includes one or more constraints associated with a routing function for traffic between the source node and destination node. Local path solutions are generated at nodes in domains that receive the problem solving request, where the local path solutions representing possible paths from a previous neighbor network domain to a next neighbor network domain that satisfy the one or more constraints. Based on the local path solutions, a determination is made as to whether there is at least one path from the source node to the destination node that satisfies the one or more constraints.

Abstract: Techniques are described for reporting and monitoring network devices using microblog messaging. Embodiments monitor network traffic traversing a network device and performance metrics of the network device to detect occurrences of network and performance events. In response to detecting an occurrence of an event, a microblog message is generated. The microblog message contains at least a description of the occurrence. The microblog message is transmitted to a microblog service, which in turn forwards the message to subscribers. The microblog message may then be analyzed by the subscribers to determine operational attributes of the network device.

Abstract: A distributed inter-domain constraints-based routing technique is provided herein. A problem solving request is sent to nodes in a plurality of network domains that have a potential path between a source node and the destination node. The problem solving request includes one or more constraints associated with a routing function for traffic between the source node and destination node. Local path solutions are generated at nodes in domains that receive the problem solving request, where the local path solutions representing possible paths from a previous neighbor network domain to a next neighbor network domain that satisfy the one or more constraints. Based on the local path solutions, a determination is made as to whether there is at least one path from the source node to the destination node that satisfies the one or more constraints.

Abstract: Data packets from different layers of a layered data stream are correlated in time. The layered data stream has a base layer and one or more enhancement layers. The method builds a table of entries, with each entry including one or more received data packets. Each data packet has a corresponding time stamp indicating when that data packet can be sent to a decoder for processing. The entries in the table are indexed according to the time stamps of the received data packets, where each entry is associated with a temporal window and data packets that have time stamps within a given temporal window are included within the entry associated with the given temporal window.

Abstract: A method and apparatus for composing and presenting multimedia programs using the MPEG-4 standard at a multimedia terminal (100). A composition engine (120) maintains and updates a scene graph (124) of the current objects, including their relative position in a scene and their characteristics, and provides a corresponding list of objects (126) to be displayed to a presentation engine (150). In response, the presentation engine begins to retrieve the corresponding decoded object data that is stored in respective composition buffers (176, . . . 186). The presentation engine assembles the decoded objects to provide a scene for presentation on output devices such as a video monitor (240) and speakers (242), or for storage. A terminal manager (110) receives user commands and causes the composition engine to update the scene graph and list of objects accordingly. The terminal manager also forwards the information contained in the object descriptors to a scene decoder (122) at the composition engine.

Abstract: Temporal and spatial scaling of video images including video object planes (VOPs) in an input digital video sequence is provided. Coding efficiency is improved by adaptively compressing scaled field mode video. Upsampled VOPs in the enhancement layer are reordered to provide a greater correlation with the input video sequence based on a linear criteria. The resulting residue is coded using a spatial transformation such as the DCT. A motion compensation scheme is used for coding enhancement layer VOPs by scaling motion vectors which have already been determined for the base layer VOPs. A reduced search area whose center is defined by the scaled motion vectors is provided. The motion compensation scheme is suitable for use with scaled frame mode or field mode video. Various processor configurations achieve particular scaleable coding results. Applications of scaleable coding include stereoscopic video, picture-in-picture, preview access channels, and ATM communications.