Abstract: The present invention conveys a fractionation method to isolate different bioactive Phytocannabinoids by solid phase extraction using HP-20 resins and one step method to synthesize C— and O-?-D-glycoside derivatives of Cannabinoid by using a ?-D-glucose donor (O-Glycosyl trichloroacetimidate donor) to obtain glycosidic derivatives. The novel C-glycosides of Cannabinoids displayed significant anti-proliferative properties against wide range of human cancer cell lines as compared to their respective parent molecules. Furthermore, the C— and O glycosides of Cannabinoids also showed anti-invasive and anti-migratory activities against metastatic cancer cells of breast and pancreatic origin. When applied in combination with DNA damaging agent (5-Fluorouracil) to colorectal cancer cells, the C— and O-glycosides of Cannabinoids potentiate DNA damaging property and thus augment apoptosis resulting in an increment in the efficacy of DNA damaging drugs.

Abstract: A portable electronic device that selectively performs a remedial action is described. During operation, the portable electronic device may measure wireless signals associated with communication with the second electronic device. Then, based at least in part on the measured wireless signals, the portable electronic device may diagnose a communication problem. Moreover, when the portable electronic device is able to correct the communication problem, the portable electronic device may automatically and selectively perform the remedial action based at least in part on the communication problem, where the remedial action corrects the communication problem. For example, the remedial action may include: re-establishing a connection between the second electronic device and a controller; changing one or more configuration parameters of the second electronic device; and/or upgrading software in the second electronic device.

Abstract: A radio mapping architecture for applying machine learning techniques to mobile wireless radio access networks, including a base station, a user equipment (UE), and a network is provided. The radio mapping architecture includes a spectrum monitoring unit and a server and utilizes the UE. The server includes a radio mapping database and a Machine Learning module. The UE or the spectrum monitoring unit captures Radio parameters to derive an input schema for the radio mapping database. The spectrum monitoring unit extracts the Radio parameters that correspond to the base station and the UE and updates them in the radio mapping database periodically. The input schema for the radio mapping database is updated with the Radio parameters sensed by the spectrum monitoring unit and the UE.

Abstract: During operation, a computer system may establish a connection with an electronic device. Then, the computer system may receive, from a port in a firewall, a packet associated with the electronic device, where the packet includes an IP address of the electronic device. Moreover, the computer system may provide, to the port, a response addressed to the IP address. Next, the computer system may receive an acknowledgment associated with the electronic device that indicates that the response was received. Furthermore, the computer system may provide, addressed to the electronic device, a second IP address of a second electronic device and a second port in a second firewall associated with the second electronic device. Additionally, the computer system may provide, addressed to the second electronic device, the IP address of the electronic device and the port in the firewall.

Abstract: An electronic device that assesses communication performance is described. During operation, the electronic device receives information specifying a location in an environment. For example, the information may correspond to user-interface activity associated with a user interface. Notably, the user interface may include an augmented reality and the user-interface activity may include defining the location, such as by dropping a pin in the augmented reality. Then, the electronic device provides the information to an access point and/or a controller of the access point, where the location is within communication range of the access point. Next, the electronic device receives, from the access point and/or the controller, measurements of one or more communication performance metrics at or proximate to the location during a time interval. Moreover, the electronic device provides a graphical representation of the communication performance at or proximate to the location based at least in part on the measurements.

Abstract: An electronic device that assesses communication performance is described. During operation, the electronic device receives information specifying a location in an environment. For example, the information may correspond to user-interface activity associated with a user interface. Notably, the user interface may include an augmented reality and the user-interface activity may include defining the location, such as by dropping a pin in the augmented reality. Then, the electronic device provides the information to an access point and/or a controller of the access point, where the location is within communication range of the access point. Next, the electronic device receives, from the access point and/or the controller, measurements of one or more communication performance metrics at or proximate to the location during a time interval. Moreover, the electronic device provides a graphical representation of the communication performance at or proximate to the location based at least in part on the measurements.

Abstract: An electronic device that assesses communication performance is described. During operation, the electronic device receives information specifying a location in an environment. For example, the information may correspond to user-interface activity associated with a user interface. Notably, the user interface may include an augmented reality and the user-interface activity may include defining the location, such as by dropping a pin in the augmented reality. Then, the electronic device provides the information to an access point and/or a controller of the access point, where the location is within communication range of the access point. Next, the electronic device receives, from the access point and/or the controller, measurements of one or more communication performance metrics at or proximate to the location during a time interval. Moreover, the electronic device provides a graphical representation of the communication performance at or proximate to the location based at least in part on the measurements.

Abstract: A portable electronic device that selectively performs a remedial action is described. During operation, the portable electronic device may measure wireless signals associated with communication with the second electronic device. Then, based at least in part on the measured wireless signals, the portable electronic device may diagnose a communication problem. Moreover, when the portable electronic device is able to correct the communication problem, the portable electronic device may automatically and selectively perform the remedial action based at least in part on the communication problem, where the remedial action corrects the communication problem. For example, the remedial action may include: re-establishing a connection between the second electronic device and a controller; changing one or more configuration parameters of the second electronic device; and/or upgrading software in the second electronic device.

Abstract: An electronic device that assesses communication performance is described. During operation, the electronic device receives information specifying a location in an environment. For example, the information may correspond to user-interface activity associated with a user interface. Notably, the user interface may include an augmented reality and the user-interface activity may include defining the location, such as by dropping a pin in the augmented reality. Then, the electronic device provides the information to an access point and/or a controller of the access point, where the location is within communication range of the access point. Next, the electronic device receives, from the access point and/or the controller, measurements of one or more communication performance metrics at or proximate to the location during a time interval. Moreover, the electronic device provides a graphical representation of the communication performance at or proximate to the location based at least in part on the measurements.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A method and system for automating the decision-making process used in underwriting of insurance applications is described. While this approach is demonstrated for insurance underwriting, it is broadly applicable to diverse decision-making applications in business, commercial, and manufacturing processes. A structured methodology is used based on a multi-model parallel network of multivariate adaptive regression splines (“MARS”) models to identify the relevant set of variables and their parameters, and build a framework capable of providing automated decisions. The parameters of the MARS-based decision system are estimated from a database consisting of a set of applications with reference decisions against each. Cross-validation and development/hold-out combined with re-sampling techniques are used to build a robust set of models that minimize the error between the automated system's decision and the expert human underwriter.

Abstract: The invention provides systems and methods for determining the allocation of securities in a portfolio. The method includes providing a collection of securities in a portfolio, each security being associated with associated attributes; providing risk factor data related to the portfolio; pooling the securities into a plurality of security clusters based on the attributes associated with each security and the risk factor data, each security being assigned to an security cluster, the pooling being performed using multivariate decision tree processing; processing the security clusters using a nonlinear programming optimizer to generate optimization results; and presenting the optimization results in a risk-return space for determination of a security allocation.

Abstract: The invention provides systems and methods for determining an efficient frontier, which comprises a collection of security allocations in a portfolio, with multiple, conflicting objectives in a multi-factor portfolio problem. The method includes providing a mathematical model of a relaxation of a problem; generating a sequence of additional constraints; and sequentially applying respective nonlinear risk functions to generate respective adjusted maximum return solutions to obtain an efficient frontier.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: An automated method and system estimates income of an individual loan applicant using credit bureau information and loan attributes. The method and system can use the credit bureau and loan information to calibrate an applicant's debt-burden in cases where such information is not readily available or is unverifiable. The method and system can automatically verify income for applicants who choose to state their income in lieu of providing adequate documentation. Further, the method and system can be applicable to any retail lending business including, but not limited to, mortgage, auto loan, and credit cards, where credit bureau information forms a part of the data collection process and is available along with applicant's information.

Abstract: Methods and apparatus are disclosed for a combined bulk and transactional database synchronization scheme. A dynamically changing primary database is initially duplicated to a secondary database using bulk and transactional updates. Then, the secondary database is maintained in synchronization with the primary database using transactional updates. In one implementation, the primary database is divided into synchronization groups. Initially, all the groups are marked as requiring bulk synchronization. Systematically, entries from a group are combined into a bulk update message and relayed to a secondary device or component to bulk update the secondary database. When a new update to the primary database is made, if the group to which it belongs is in the process of, or still requires bulk updating, this new update will be propagated to the secondary database in due course with a subsequent bulk update. Otherwise, the new update is placed in transactional update message.

Abstract: A method and system for designing a neural network classifier and such a neural network for an automated insurance underwriting system and/or its quality assurance is described. While the design method is demonstrated for quality assurance of automated insurance underwriting, it is broadly applicable to diverse decision-making applications in business, commercial, and manufacturing processes. Specifically, multi-class classification problems are solved by decomposing a multi-class classifier into multiple binary-classifiers, which reduces the complexity of the neural network structure, thus reducing the training time and improving the classification performance. Furthermore, the invention also describes a method to incorporate the domain knowledge into the neural network classifier. Both methods work to improve the performance of the classifier.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A method and system for automating the decision-making process used in underwriting of insurance applications is described. While this approach is demonstrated for insurance underwriting, it is broadly applicable to diverse decision-making applications in business, commercial, and manufacturing processes. A structured methodology is used based on a multi-model parallel network of multivariate adaptive regression splines (“MARS”) models to identify the relevant set of variables and their parameters, and build a framework capable of providing automated decisions. The parameters of the MARS-based decision system are estimated from a database consisting of a set of applications with reference decisions against each. Cross-validation and development/hold-out combined with re-sampling techniques are used to build a robust set of models that minimize the error between the automated system's decision and the expert human underwriter.