2654results about "Fuzzy logic based systems" patented technology

A controller for a building management system is configured to analyze faults in the building management system. The controller detects a fault in the building management system by evaluating data of building management system using a system of rules. The controller determines a conditional probability for each of a plurality of possible fault causes given the detected fault. The controller determines the most likely fault cause by comparing the determined probabilities and electronically reports the most likely fault cause.

The present invention relates to a system and method for configuring and managing network devices. The arrival (and departure) of devices on a network can be detected by a monitor. Upon detection, network devices can be simply and dynamically configured with little or no end-user intervention, for instance by automatically loading device drivers and allocating resources for the devices. Furthermore, network devices can be associated with other network devices such as a personal computer to facilitate seamless integration of network devices with a computer operating system.

Transaction scoring is performed in a distributed manner across a client-server computing system. A computing system for processing a transaction includes a server system and a client system. The server system is arranged to process information associated with the transaction, while the client system communicates with the server system and includes a key engine which is arranged to generate keys. The client system and the server system are arranged to cooperate to make probabilistic determinations associated with the transaction. The client is arranged to send the keys generated by the key engine as a transaction to the server system.

The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure. According to various embodiments, methods, systems and interfaces for associating experimental data, features and groups of data related by structure and/or function with chemical, medical and/or biological terms in an ontology or taxonomy are provided. According to various embodiments, methods, systems and interfaces for filtering data by data source information are provided, allowing dynamic navigation through large amounts of data to find the most relevant results for a particular query.

In general, in one embodiment, a computing system that evaluates a fraud probability score for an identity event relevant to a user first queries a data store to identify the identity event. A fraud probability score is then computed for the identity event using a behavioral module that models multiple categories of suspected fraud.

A method for predicting risk and designing safety management systems of complex production and process systems which has been applied to an FPSO System operating in deep waters. The methods for the design were derived from the inclusion of a weight index in a fuzzy class belief variable in the risk model to assign the relative numerical value or importance a safety device or system has contain a risk hazards within the barrier. The weights index distributes the relative importance of risk events in series or parallel in several interactive risk and safety device systems. The fault tree, the FMECA and the Bow Tie now contains weights in fizzy belief class for implementing safety management programs critical to the process systems. The techniques uses the results of neural networks derived from fuzzy belief systems of weight index to implement the safety design systems thereby limiting use of experienced procedures and benchmarks. The weight index incorporate Safety Factors sets SFri {0, 0.1, 0.2 . . . 1}, and Markov Chain Network to allow the possibility of evaluating the impact of different risks or reliability of multifunctional systems in transient state process. The application of this technique and results of simulation to typical FPSO/Riser systems has been discussed in this invention.

Systems, methods, devices, and computer programming products useful for the gathering and use of data relating to structural loading and other operational use of transit and other vehicles, and their systems. Systems according to the invention can, for example, comprise one or more data acquisition devices such as strain gauges, accelerometers, or other sensors; data processors; memories; and communications systems. Such systems, methods, and programming are useful in a wide variety of ways, including, for example, monitoring the structural status and use of vehicles and their systems, including fatigue other operational analyses; gathering and applying data useful in the maintenance of such vehicles and the routes they travel; monitoring the use/abuse of such vehicles by operators and other individuals; reporting traffic events or anomalies; and routing transit and other vehicles around such events or anomalies. Rainflow, level-crossing and other peak-counting or event-counting algorithms are applied to advantage, such that required data storage is greatly reduced, and life-long monitoring is feasible.

Various embodiments of a diabetes management system are provided. One exemplary system may include an analyte measurement device and a therapeutic agent delivery device. The measurement device includes a measurement unit, display, and first wireless module. The therapeutic agent delivery device has a delivery device housing, delivery mechanism disposed in the housing that delivers a dosage of the agent to the user upon actuation by the user or health care provider, and a second wireless module. The second module, automatically, without prompting from a user or any active input or action by the user, transmits a signal to the first wireless module indicative of: (a) type of therapeutic agent delivered; and (b) amount of therapeutic agent delivered to the user; or (c) type of therapeutic agent device from which the therapeutic agent was administered. Also described are diabetes management devices and methods.

A system for personal medical care, intelligent analysis and diagnosis may include: at least one source of medical information; at least one source of personal medical data for at least one patient; and one or more servers, where the medical information and the personal medical data are accessible to the server(s). The server(s) may include: an artificial intelligence (AI) component for analyzing the personal medical data with the medical information and identifying at least one issue requiring follow-up by the patient or by at least one external authorized entity; and at least one real-time communication link for bi-directional communication with at least one external authorized entity.

A system and method for measuring a performance of an entity and for predicting its future performance is disclosed. Raw information about the entity is collected from internal and external sources. The information is cleaned to exclude false positives. Using performance categories, the information is organized and transformed into meaningful data for the performance analysis engine. The information is normalized by scaling the meaningful data by industry type. A performance score is calculated by the performance analysis engine based on the normalized data. Further, a competitive relationship score is calculated based on the performance score and the normalized data. These scores are reported in a user interface displaying the performance of the entity and are used as inputs, among other factors, to a predictive analysis engine that assesses the future performance of the entities.

Adaptive applications of affinity propagation are described to facilitate effective and computationally efficient means of clustering computer-based objects such as items of content, and/or to determine exemplars associated with a set of objects. Affinity propagation is also applied by the present invention to define system user affinity groups and/or exemplar users. The present invention applies usage behaviors as a basis for influencing clustering through methods such as initializing exemplar attractor values based on usage behaviors and/or basing similarity values between pairs of objects or users on usage behaviors associated with system objects, or usage behaviors that are associated with, directly or indirectly, specific system users.

Methods are disclosed for estimating parameters of a probability model that models user behavior of shared devices offering different classes of service for carrying out jobs. In operation, usage job data of observed users and devices carrying out the jobs is recorded. A probability model is defined with an observed user variable, an observed device variable, a latent job cluster variable, and a latent job service class variable. A range of job service classes associated with the shared devices is determined, and an initial number of job clusters is selected. Parameters of the probability model are learned using the recorded job usage data, the determined range of service classes, and the selected initial number of job clusters. The learned parameters of the probability model are applied to evaluate one or more of: configuration of the shared devices, use of the shared devices, and job redirection between the shared devices.

A usage based pattern authenticator for monitoring and reporting on user usage patterns in an operating system using a set of security rules and user usage patterns. This computer system security tool authenticates users at the operating system level in multi-user operating systems. It supports system administrators in limiting the ability of unauthorized users to disrupt system operations using a neural network and set of rules to track usage patterns and flag suspicious activity on the system. The data collection mode collects and stores usage patterns of authenticated users. The training mode trains an artificial neural network and sets the interconnection weights of the network. The production mode monitors and reports on usage patterns, and optionally performs automatic responses when confronted with non-authenticated users.

An adaptive recommendation system and a mobile adaptive recommendation system are disclosed. The adaptive recommendation system and the mobile adaptive recommendation system include algorithms for monitoring user usage behaviors across a plurality of usage behavior categories associated with a computer-based system, and generating recommendations based on inferences on user preferences and interests. Privacy control functions and compensatory functions related to insincere usage behaviors can be applied. Adaptive recommendation delivery can take the form of visual-based or audio-based formats.

This invention provides a process and system for a comprehensive surgical assist system, called a Therapy Imaging and Model Management System (TIMMS), which combines and integrates all of the necessary information and communication technology; workflow analysis, data processing and data synthesis; interactive interfaces between surgeon and mechatronic devices; and, cognitive agents; to provide comprehensive assistance and guidance throughout complex medical and surgical therapies, such as image guided surgery. The components of this invention, which are modular, scalable and may be distributed in location, act synergistically to provide functionality and utility that exceeds the sum of its individual parts.

A method of performing surgery on a patient comprising the step of comparing a chosen patient's data to statistical data in a repository of patient data to develop a patient specific model, wherein the data comprises information from two or more sub databases selected from the group consisting of workflow data, electronic medical records, diagnostic data, biological data, measurement data, anatomical data, physiological data, genetic data, molecular data, imaging data, chemical data, clinical laboratory data, simulated data, coordinate data and surgical result and wherein the patient specific model aids in the preoperative, operative or post operative phase of surgery performed in real time on the patient.

Systems and methods are disclosed for routing callers to agents in a contact center utilizing a multi-layer processing approach to matching a caller to an agent. A first layer of processing may include two or more different computer models or methods for scoring or determining caller-agent pairs in a routing center. The output of the first layer may be received by a second layer of processing for balancing or weighting the outputs and selecting a final caller-agent match. The two or more methods may include conventional queue based routing, performance based routing, pattern matching algorithms, affinity matching, and the like. The output or scores of the two or more methods may be processed be the second layer of processing to select a caller-agent pair and cause the caller to be routed to a particular agent.

A ridesharing system and method involving selected negotiated participation of riders and ride providers. The ridesharing system in a specific implementation involves a computer-implemented capability for computational matching of potential participants in a ridesharing arrangement, wherein such system is adapted for prioritized ranking of target ridesharing attributes by such potential participants, involving allocation by potential participants of quantitative weight within a quantitative total budget of allocatable value to predetermined selection criteria, with such system having an input capability for inputting the allocations of potential participants, and the system being constructed and arranged for effecting the computational matching based on the allocations, with communication capability for outputting results of the computational matching to the potential participants.

According to various embodiments, a ratings matrix including matrix values is generated, each row of the ratings matrix identifying one of a plurality of users, each column of the ratings matrix identifying one of a plurality of items, and each of the matrix values corresponding to a known affinity rating describing a degree of affinity associated with one of the users and one of the items. The ratings matrix may include a missing entry representing an unknown affinity rating. According to various embodiments, a revised ratings matrix is generated by factoring the ratings matrix into a user matrix and an item matrix, the revised ratings matrix being the product of the user matrix and the item matrix and including at least one entry representing a predicted affinity rating in place of the missing entry.