Abstract: The present invention relates to a process for the purification of Carfiizomib of Formula I that reduces the level of an acetamide impurity of Formula II preferably below 0.10 wt %. Formula I Formula II.

Abstract: In one embodiment, a method selects a new job to schedule for execution on a data processing system. The new job includes a. Performance information for a set of current jobs that are being executed in the data processing system is retrieved where the set of jobs are assigned to queues and currently classified with a current classification. The method analyzes the performance information to determine when one or more current jobs in the set of current jobs should be re-classified due to resource usage of a respective current job when being executed in the data processing system and re-classifies the classifications for the one or more current jobs in the queues. Then, the new job is assigned to one of the queues based on the classification of the new job and the classifications of jobs in the queues including the re-classified classifications for the one or more current jobs.

Abstract: A method of identifying an optimum treatment for a patient suffering from coronary artery disease, comprising: (i) providing patient information selected from: (a) status in the patient of one or more coronary disease associated biomarkers; (b) one or more items of medical history information selected from prior condition history, intervention history and medication history; (c) one or more items of diagnostic history, if the patient has a diagnostic history; and (d) one or more items of demographic data; (ii) aggregating the patient information in: (a) a Bayesian network; (b) a machine learning and neural network; (c) a rule-based system; and (d) a regression-based system; (iii) deriving a predicted probabilistic adverse event outcome for each intervention comprising percutaneous coronary intervention by placement of a bare metal stent, or a drug-coated stent; or by coronary artery bypass grafting; and (iv) determining the intervention having the lowest predicted probabilistic adverse outcome.

Abstract: A method and system for cooperative diversity visual cognition in a wireless sensor network is disclosed. The method and system are capable of solving distributed visual cognition tasks (for example, online simultaneous reconstruction of 3D models of a large area) by using multiple video streams and exploiting cooperative diversity video sensing information while ensuring an optimal tradeoff between energy consumption and video quality of images received from said multiple video streams.

Abstract: A system is provided that manages consigned inventory. The system consumes consigned inventory items. The system further generates a consumption advice in response to the consumption of the consigned inventory items, where the consumption advice references a consignment agreement, a consignment order and a receipt. The system further communicates the consumption advice to a supplier. The consumption advice includes at least one of: a consumption advice number; a business unit; an inventory organization; a supplier; a supplier site; a start date; or an end date. The consumption advice includes one or more consumption advice lines, and each consumption advice line includes one or more consumption transactions.

Abstract: Multiple cameras are configured for use in video analytics. A single configuration tool is provided. The interrelationships between cameras are included within the configuration. Using a combination of text entry fields, registration of the cameras on a floor or other map, and marking on images from the cameras, an efficient workflow for configuration may be provided.

Abstract: An active set of discrete texture traces to a target point is determined in a first video frame and is applied to a second video frame to detect the target location in a second video frame. An estimate is made of the target location in the second video frame. A score map is computed of an area of locations. A location with a highest score in the score map is the new target location. If a threshold value is not met the active set of texture traces is stored. A score map for each of stored active sets is computed to determine the target location. If no score meets the threshold the target location in a previous video frame is made the current target location and a new active set of discrete texture traces is determined. Systems that implement the steps of the methods are also provided.

Abstract: A method of detecting an object in image data that is deemed to be a threat includes annotating sections of at least one training image to indicate whether each section is a component of the object, encoding a pattern grammar describing the object using a plurality of first order logic based predicate rules, training distinct component detectors to each identify a corresponding one of the components based on the annotated training images, processing image data with the component detectors to identify at least one of the components, and executing the rules to detect the object based on the identified components.

Abstract: A requirements management tool, where each requirement is defined by one or more design element values. Each of the design element values is a unique value and is a member of a group of design element values defined for the project. As each requirement is created, the design element values for the requirement are selected from the group of design element values, or alternatively, a new design element value may be entered by a user, and the new design element value will be added to the group of element values. Each design element value corresponds to a category that each of the requirements are broken down into. Design element values in the created requirement are compared to design element values in existing requirements, and results of this duplication check are presented to a user of the requirements management tool.

Abstract: First order predicate logics are provided, extended with a bilattice based uncertainty handling formalism, as a means of formally encoding pattern grammars, to parse a set of image features, and detect the presence of different patterns of interest implemented on a processor. Information from different sources and uncertainties from detections, are integrated within the bilattice framework. Automated logical rule weight learning in the computer vision domain applies a rule weight optimization method which casts the instantiated inference tree as a knowledge-based neural network, to converge upon a set of rule weights that give optimal performance within the bilattice framework. Applications are in (a) detecting the presence of humans under partial occlusions and (b) detecting large complex man made structures in satellite imagery (c) detection of spatio-temporal human and vehicular activities in video and (c) parsing of Graphical User Interfaces.

Abstract: Multiple cameras are configured for use in video analytics. A single configuration tool is provided. The interrelationships between cameras are included within the configuration. Using a combination of text entry fields, registration of the cameras on a floor or other map, and marking on images from the cameras, an efficient workflow for configuration may be provided.

Abstract: An active set of discrete texture traces to a target point is determined in a first video frame and is applied to a second video frame to detect the target location in a second video frame. An estimate is made of the target location in the second video frame. A score map is computed of an area of locations. A location with a highest score in the score map is the new target location. If a threshold value is not met the active set of texture traces is stored. A score map for each of stored active sets is computed to determine the target location. If no score meets the threshold the target location in a previous video frame is made the current target location and a new active set of discrete texture traces is determined. Systems that implement the steps of the methods are also provided.

Abstract: A requirements management tool, where each requirement is defined by one or more design element values. Each of the design element values is a unique value and is a member of a group of design element values defined for the project. As each requirement is created, the design element values for the requirement are selected from the group of design element values, or alternatively, a new design element value may be entered by a user, and the new design element value will be added to the group of element values. Each design element value corresponds to a category that each of the requirements are broken down into. Design element values in the created requirement are compared to design element values in existing requirements, and results of this duplication check are presented to a user of the requirements management tool.

Abstract: A method and system for cooperative diversity visual cognition in a wireless sensor network is disclosed. The method and system are capable of solving distributed visual cognition tasks (for example, online simultaneous reconstruction of 3D models of a large area) by using multiple video streams and exploiting cooperative diversity video sensing information while ensuring an optimal tradeoff between energy consumption and video quality of images received from said multiple video streams.

Abstract: A method of detecting an object in image data that is deemed to be a threat includes annotating sections of at least one training image to indicate whether each section is a component of the object, encoding a pattern grammar describing the object using a plurality of first order logic based predicate rules, training distinct component detectors to each identify a corresponding one of the components based on the annotated training images, processing image data with the component detectors to identify at least one of the components, and executing the rules to detect the object based on the identified components.

Abstract: A framework for securing a source code base during the development phase of a software development lifecycle is provided. The framework includes an aspect package module and a validator package module. The aspect package module integrates security routines into the source code base. The aspect package module includes a custom interface module and a validator aspect module. The custom interface module includes a function declaration, wherein the custom interface module is implemented by at least one class of the one or more classes. The validator aspect module includes a controller code for controlling the flow of the execution, based on the context for the security validation of the at least one class, wherein one or more security routine integration points are defined in the at least one class. The validator package module validates the at least one class, based on the defined context, by using one or more validation classes.

Abstract: First order predicate logics are provided, extended with a bilattice based uncertainty handling formalism, as a means of formally encoding pattern grmmars, to parse a set of image features, and detect the presence of different patterns of interest implemented on a processor. Information from different sources and uncertainties from detections, are integrated within the bilattice framework. Automated logical rule weight learning in the computer vision domain applies a rule weight optimization method which casts the instantiated inference tree as a knowledge-based neural network, to converge upon a set of rule weights that give optimal performance within the bilattice framework. Applications are in (a) detecting the presence of humans under partial occlusions and (b) detecting large complex man made structures in satellite imagery (c) detection of spatio-temporal human and vehicular activities in video and (c) parsing of Graphical User Interfaces.

Abstract: A framework for securing a source code base during the development phase of a software development lifecycle is provided. The framework includes an aspect package module and a validator package module. The aspect package module integrates security routines into the source code base. The aspect package module includes a custom interface module and a validator aspect module. The custom interface module includes a function declaration, wherein the custom interface module is implemented by at least one class of the one or more classes. The validator aspect module includes a controller code for controlling the flow of the execution, based on the context for the security validation of the at least one class, wherein one or more security routine integration points are defined in the at least one class. The validator package module validates the at least one class, based on the defined context, by using one or more validation classes.