Abstract: A logic decoder circuit capable of performing Boolean or fuzzy logic has one or more logic components configured to perform a logic function of an AND-NOT gate, each AND-NOT gate comprising a circuit that performs a conjunction of an excitatory input X and an inhibitory input Y to obtain an output X-AND-NOT-Y substantially linearly for given ranges for X and Y. Certain preferred designs are provided for an X-AND-NOT-Y logic gate and a family of fast fuzzy decoders composed of such gates.

Abstract: A method, device, and computer program product for monitoring the physiological state of a subject is disclosed. A first plurality of physiological signals are acquired from the subject and a second plurality of signal parameters are determined based on the first plurality of physiological signals. Relevant signal information is selected from among the signal information produced and at least one screen page is displayed at a time, thereby to make at least part of the signal information visible to a user. The signal information visible to the user on the at least one screen page may then be revised based on the selection and without user interaction, thereby to accelerate clinical decision-making and to diminish the possibility of undetected changes in the state of the subject.

Abstract: A modeling method of neuro-fuzzy system including a rule-defining process and a network-building process is disclosed. The rule-defining process divides a plurality of training data into a plurality of groups to accordingly define a plurality of fuzzy rules, and the network-building process constructs a fuzzy neural network based on the fuzzy rules obtained by the rule-defining process. The provided modeling method of neuro-fuzzy system is capable of building a neuro-fuzzy system extremely similar to an original function that generates training data of the neuro-fuzzy system.

Abstract: Methods and systems for controlling a prosthesis using a brain imager that images a localized portion of the brain are provided according to one embodiment of the invention. For example, the brain imager can provide motor cortex activation data using near infrared imaging techniques and EEG techniques among others. EEG and near infrared signals can be correlated with brain activity related to limbic control and may be provided to a neural network, for example, a fuzzy neural network that maps brain activity data to limbic control data. The limbic control data may then be used to control a prosthetic limb. Other embodiments of the invention include fiber optics that provide light to and receive light from the surface of the scalp through hair.

Abstract: In one embodiment, a method of generating annotation tags (28) for a digital image (22) includes maintaining a library (16) of human-meaningful words or phrases organized as category entries (72) according to a number of defined image description categories (70), and receiving context metadata (20) associated with the capture of a given digital image (22). The method further includes selecting particular category entries (72-1, 72-2) as vocabulary metadata (24) for the digital image (22) by mapping the context metadata (20) into the library (16), and generating annotation tags (28) for the digital image (22) by logically combining the vocabulary metadata (24) according to a defined set of deductive logic rules (30) that are predicated on the defined image description categories (70). In another embodiment, a processing apparatus (12), such as a digital processor (18, 26) and supporting memory (14), etc., is configured to carry out the above method, or to carry out variations of the above method.

Abstract: An input feature vector is computed from an input text record, the input feature vector comprising one or more features, each feature including a subsequence of characters and a frequency of occurrence of the associated subsequence. A input fingerprint is generated out of the input feature vector by choosing one or more features with non-zero frequencies and alphabetizing the features chosen. One or more input indices are generated by alphabetizing features in the input fingerprint and concatenating features occurring in subsequent locations of the input fingerprint. The input text record is matched against a target text record if (1) one or more of the input indices match a target index corresponding to the target text record and (2) the corresponding input fingerprint matches a target fingerprint corresponding to the target text record. The target text record is outputted as a search result if it matches the input text record.

Abstract: A first graph embedded in a Euclidean space is modeled by a globally rigid first model graph that includes all vertices and edges of the first graph and has a preselected maximum clique size. The modeling is configured to maintain the preselected maximum clique size by employing an edge adding process that replicates a vertex of a vertex pair connected by an edge. A mapping between vertices of the first graph and vertices of a second graph is computed by optimizing a mapping between vertices of the first model graph and vertices of the second graph.

Abstract: A method for implementing production processes includes a step of programming a state machine for each production process. The programming step includes a definition of a plurality of states and a definition of a plurality of transitions between states, corresponding to possible actions which the corresponding production process may execute. The programming step further includes the steps of detecting whether or not one or more states to be defined for a state machine have already been defined for state machines already programmed for other production processes, and executing the definition of states only for states not detected in the detecting step.

Abstract: 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 . . .

Abstract: An example method is illustrated as including receiving a first content set, the first content set organized according to a rules set, using the rules set to parse the first content set to generate a first pattern set having a plurality of members, assigning a weighted value to each member of the first and a second pattern set based on a frequency of occurrence of each member in the first and second pattern sets, wherein each member of the first and second pattern sets includes digital content, and determining a relevancy score linking each of the members of the first and second pattern set in a one to one mapping of the members of the first pattern set to each of the members of the second pattern set, wherein the relevancy score is based upon the weighted value assigned to each member of the first and second pattern sets.

Abstract: A fault detection system for use with a solar hot water system may include a data acquisition module which may, in turn, include a plurality of sensors. Input data may include a sensed condition. The system may also include a neural network to receive the input data which may be a multi-layer hierarchical adaptive resonance theory (ART) neural network. The neural network may perform an analysis on the input data to determine existence of a fault or a condition indicative of a potential fault. The fault and the condition indicative of the potential fault are prioritized according to the analysis performed by the neural network. A warning output relating to the fault and the condition indicative of the potential fault is generated responsive to the analysis, and is displayed on the user interface.

Abstract: The method for generating an integrated guidance law for aerodynamic missiles uses a strength Pareto evolutionary algorithm (SPEA)-based approach for generating an integrated fuzzy guidance law, which includes three separate fuzzy controllers. Each of these fuzzy controllers is activated in a unique region of missile interception. The distribution of membership functions and the associated rules are obtained by solving a nonlinear constrained multi-objective optimization problem in which final time, energy consumption, and miss distance are treated as competing objectives. A Tabu search is utilized to build a library of initial feasible solutions for the multi-objective optimization algorithm. Additionally, a hierarchical clustering technique is utilized to provide the decision maker with a representative and manageable Pareto-optimal set without destroying the characteristics of the trade-off front. A fuzzy-based system is employed to extract the best compromise solution over the trade-off curve.

Abstract: The control optimization method for helicopters carrying suspended loads during hover flight utilizes a controller based on time-delayed feedback of the load swing angles. The controller outputs include additional displacements, which are added to the helicopter trajectory in the longitudinal and lateral directions. This simple implementation requires only a small modification to the software of the helicopter position controller. Moreover, the implementation of this controller does not need rates of the swing angles. The parameters of the controllers are optimized using the method of particle swarms by minimizing an index that is a function of the history of the load swing. Simulation results show the effectiveness of the controller in suppressing the swing of the slung load while stabilizing the helicopter.

Abstract: The fuzzy logic-based control method for helicopters carrying suspended loads utilizes a controller based on fuzzy logic membership distributions of sets of load swing angles. The anti-swing controller is fuzzy-based and has controller outputs that include additional displacements added to the helicopter trajectory in the longitudinal and lateral directions. This simple implementation requires only a small modification to the software of the helicopter position controller. The membership functions govern control parameters that are optimized using a particle swarm algorithm. The rules of the anti-swing controller are derived to mimic the performance of a time-delayed feedback controller. A tracking controller stabilizes the helicopter and tracks the trajectory generated by the anti-swing controller.

Abstract: Methods, apparatuses, computer program products, devices and systems are described that carry out specifying at least one of a plurality of user-health test functions responsive to an interaction between a user and at least one advertiser-specified attribute; and transmitting at least one output of the at least one user-health test function related to the at least one advertiser-specified attribute.

Abstract: A method for recognition between a first and second object represented by at least one first image and at least one second image, includes defining rectangular assemblies of random pixels; filtering the first image with first n filters obtained from the assemblies of pixels to obtain n first filtered matrices; classifying the n first filtered matrices by providing a first center and a first radius within a space of N dimensions; filtering the second image with the first n filters to obtain n second filtered matrices; classifying the n second filtered matrices by providing a second center within the space of N dimensions; and comparing the first center and first radius with the second center.

Abstract: A computerized data equidistant-mapping method and a computer system using the same are provided. The computerized data equidistant-mapping method is used for mapping M sets of K-dimensional original data into a D-dimensional space in a manner of equidistance. The computerized data equidistant-mapping method includes the following steps. M sets of D-dimensional mapping data each corresponding to each original data respectively and sequentially are generated. An initial mapping data and an initial original data are chosen arbitrarily, wherein the initial mapping data corresponds to the initial original data. The mapping distance between each mapping data and the initial mapping data is computed. The original distance between each original data and the initial original data is computed. Each mapping data is amended according to each mapping distance and each original distance for enabling each mapping data and each original data to have equidistant-mapping relationship gradually.

Abstract: Methods and systems for controlling a prosthesis using a brain imager that images a localized portion of the brain are provided according to one embodiment of the invention. For example, the brain imager can provide motor cortex activation data using near infrared imaging techniques and EEG techniques among others. EEG and near infrared signals can be correlated with brain activity related to limbic control and may be provided to a neural network, for example, a fuzzy neural network that maps brain activity data to limbic control data. The limbic control data may then be used to control a prosthetic limb. Other embodiments of the invention include fiber optics that provide light to and receive light from the surface of the scalp through hair.

Abstract: Classification of objects using the best boolean expression that represents the most optimal combination of the underlying features is disclosed.

Abstract: A device for expressing robot autonomous emotions comprises: a sensing unit; a user emotion recognition unit, recognizing current user emotional states after receiving sensed information from the sensing unit, and calculating user emotional strengths based on the current user emotional states; a robot emotion generation unit, generating robot emotional states based on the user emotional strengths; a behavior fusion unit, calculating a plurality of output behavior weights by a fuzzy-neuro network based on the user emotional strengths and a rule table; and a robot reaction unit, expressing a robot emotional behavior based on the output behavior weights and the robot emotional states.

Abstract: In one embodiment, a method comprises creating and storing an ontology for a data store in response to receiving first user input defining the ontology, wherein the ontology comprises a plurality of data object types and a plurality of object property types; creating one or more parser definitions in response to receiving second user input defining the parser definitions, wherein each of the parser definitions specifies one or more sub-definitions of how to transform first input data into modified input data that is compatible with one of the object property types; and storing each of the one or more parser definitions in association with one of the plurality of object property types.

Abstract: A system and method for authenticating a subscriber of a first network to access application services through a second network, wherein the second network is a packet data network.

Abstract: A learning controller overcomes tuning problems in vehicle simulation programs by estimating requisite vehicle-specific parameters, effectively learning from its mistakes, as the vehicle is automatically driven around a track. After a sufficient period of calibration, the learned parameters are automatically saved to a car-specific file. The file parameters may be loaded in the controller in the future to optimally control a vehicle without the need to re-run the learning procedure.

Abstract: Documents to be accessed over a computer network are stored in network data storage such that each document is associated with a document archive and a task is associated with each stored document. An escalation list is created for each task and is associated with the document archive so as to specify an ordered list of escalation items to be satisfied until fulfillment of the task. When a parameter associated with each escalation list item has been satisfied, process operations associated with the next escalation list item are performed. Fulfillment of the task results in appending a verification of task fulfillment to the document archive.

Abstract: A method and the device are provided for determining state of health of the battery, in addition to the power supply system using the device, to reduce operational and processing load by expanding the data sampled at the time when the battery is caused to discharge square wave pulses into the square wave is provided. The method includes determining state of health of a battery by causing the battery to discharge square wave pulses with a prescribed cycle at a prescribed current value. Response voltages are sampled at a time of a pulse-discharge. The sampled response voltages are sampled into orthogonal square wave components. An amplitude of the square wave component is divided by the current value of the pulse-discharge to obtain a pseudo-impedance. A state of health of the battery based on the pseudo-impedance is determined.

Abstract: The present invention provides an electronic nose device based on chemically sensitive field effect transistors. In particular, the sensors of the electronic nose device are composed of non-oxidized, functionalized silicon nanowires which can detect volatile organic compounds with very high sensitivity. Methods of use in diagnosing diseases including various types of cancer are disclosed.

Abstract: An apparatus for assessing health of a device comprising a data alignment module for receiving a plurality of sensory outputs and outputting a synchronized data stream, an analysis module for receiving the synchronized data stream and outputting at least one device health feature, and a high level diagnostic feature information fusion module for receiving the at least one device health feature and outputting a device health assessment.

Abstract: Electronic nose device having a plurality of sensors composed of nanowires of columnar discotic liquid crystals, the device having low sensitivity to humidity. The device is designed to determine the composition and concentration of volatile organic compounds in a sample with very high sensitivity. Methods for use of the device in applications such as diagnosis of disease and food quality control are disclosed.

Abstract: Methods and systems for controlling a prosthesis using a brain imager that images a localized portion of the brain are provided according to one embodiment of the invention. The brain imager provides motor cortex activation data by illuminating the motor cortex with near infrared light (NIR) and detecting the spectral changes of the NIR light as passes through the brain. These spectral changes can be correlated with brain activity related to limbic control and may be provided to a neural network, for example, a fuzzy neural network that maps brain activity data to limbic control data. The limbic control data may then be used to control a prosthetic limb. Other embodiments of the invention include fiber optics that provide light to and receive light from the surface of the scalp through hair.

Abstract: Anomaly prediction of battery parasitic load includes processing input data related to a state of charge for a battery and a durational factor utilizing a machine learning algorithm and generating a predicted start-up state of charge. Warnings are issued if the predicted start-up state of charge drops below a threshold level within an operational time.

Abstract: A neuro-fuzzy controller is provided. The neuro-fuzzy controller includes a predictor that receives inputs and makes prediction inputs. The prediction inputs are passed to a fuzzy cluster module that includes a neural network fuzzifing said prediction inputs and passing the result to an inference engine. The output of the inference engine is defuzzified and provided as an output of the controller. The fuzzifier and defuzzifier preferably represent a neural network employing a trigonometrical series. The inference engine preferably employs rules that are determined using genetic programming.

Abstract: A work model (or an image) is displayed on an image plane of a robot simulator (201), and a measuring portion and a measuring method are designated (202, 203) and a work shape and a work loading state are designated (204), and then it is judged whether or not the measuring portion and the measuring method are good (205). When the measuring portion and the measuring method are good, a program is generated and the processing is completed (207, 208). When the measuring portion and the measuring method are not good, an alarm is given (206), and the continuation (207) or the repetition (201) of the processing is directed. At the time of analyzing the program, the loading (101), the analysis and display of the measuring portion and the measuring method (102, 103) and the work information (104) are designated, and then it is judged whether or not the measuring portion and the measuring method, which have been analyzed, are good (105).

Abstract: This is a method and apparatus for the detection of a noninvasive method by which illegal riders can be detected. This will save tremendous amounts of time and money with regard to the inspection of individual trains and also minimize the necessity of randomly stopping a train and randomly inspecting cars on the train.

Abstract: A system and method is provided to enable an e-mail to display a Web-based form. A definition concerning an e-mail address may include form schema owned by a Web site. Alternatively, the definition may contain a link to a Web service that provides the form schema. An e-mail client may download the form schema from the Web service, preferably along with additional data such as information concerning previous e-mails sent to the e-mail address, a FAQ list concerning an e-mail distribution list if the e-mail address represents the e-mail distribution list, etc. The Web site owning the form schema may receive and process e-mail containing the form according to the metadata of the Web-based form.

Abstract: In a method for acquisition, analysis and representation of at least one medical image data set created in a medical examination, an image data set of an examination region of an examination subject is acquired with a medical imaging apparatus, at least one display specification regarding an orientation to be retained in a graphical representation of the acquired image data set is retrieved from a data processing device in which it is stored, the image data set is checked with regard to the display specification by the data processing device, and of at least one part of the image data set is adapted and displayed corresponding to the display specification, dependent on the check result.

Abstract: A process for the computer creation of fuzzy cognitive maps (see FIG. 7) that are used to explore causal relationships between a group of factors and a phenomenon. These fuzzy cognitive maps are constructed using the data derived from Expanded Meta Models. These Expanded Meta Models are generated from Monte Carlo simulations that supply the factors under investigation with values, then by incrementing or decrementing these factor values one can generated an Expanded Meta Model.

Abstract: The method of indexing multimedia documents comprises the following steps: a) for each document identifying and extracting terms ti constituted by vectors characterizing properties of the; b) storing terms ti in a term base comprising P terms; c) determining a maximum number N of desired concepts that group together the most pertinent terms ti; d) calculating the matrix T of distances between the terms ti of the term base; e) decomposing the set P of terms ti of the term base into N portions Pj (1?j?N) such that P=P1? P2 . . . ? Pj . . .

Abstract: An evolvable synthetic neural system includes an evolvable neural interface operably coupled to at least one neural basis function. Each neural basis function includes an evolvable neural interface operably coupled to a heuristic neural system to perform high-level functions and an autonomic neural system to perform low-level functions. In some embodiments, the evolvable synthetic neural system is operably coupled to one or more evolvable synthetic neural systems in a hierarchy.

Abstract: A behavior is associated with a syndicated feed. The syndicated feed is associated with a content page, and provided from a server over a network. The syndicated feed may be an RSS feed or some other type of syndicated feed associated with a content page. The feed is accessed by an application and then associated with the behavior. The feed with the associated behavior is then provided to a user through an interface. A binding can be used to associate a behavior with a feed. The binding may include resources, scripts and other bindings, all of which may be distributed over a system or network.

Abstract: Anomaly prediction of battery parasitic load includes processing input data related to a state of charge for a battery and a durational factor utilizing a machine learning algorithm and generating a predicted start-up state of charge. Warnings are issued if the predicted start-up state of charge drops below a threshold level within an operational time.

Abstract: A computerized data equidistant-mapping method and a computer system using the same are provided. The computerized data equidistant-mapping method is used for mapping M sets of K-dimensional original data into a D-dimensional space in a manner of equidistance. The computerized data equidistant-mapping method includes the following steps. M sets of D-dimensional mapping data each corresponding to each original data respectively and sequentially are generated. An initial mapping data and an initial original data are chosen arbitrarily, wherein the initial mapping data corresponds to the initial original data. The mapping distance between each mapping data and the initial mapping data is computed. The original distance between each original data and the initial original data is computed. Each mapping data is amended according to each mapping distance and each original distance for enabling each mapping data and each original data to have equidistant-mapping relationship gradually.

Abstract: An extended state machine that makes use of an inference engine as the infrastructure for adding inferential capabilities to the state machine's execution. The result is a state machine that may operate on partial or disordered information, inferring intermediate states that have yet to be formally traversed. In addition, controls such as state timeouts and transition priorities allow for finer control of the state machine's execution, particularly in unexpected circumstances.

Abstract: A method for generating a manufacturing process map comprises obtaining sets of N-dimensional expert data from at least three sources, defining a membership function for each set of expert data, applying fuzzy logic operations to said membership functions to generate new membership functions, the new membership functions defining N-dimensional regions within an N-dimensional design space and using one of said N-dimensional regions to generate the manufacturing process map.

Abstract: A therapeutic device has a first chamber that retains an oxalic ester solution, and a second chamber that retains a hydrogen peroxide and fluorescer solution. The therapeutic device is activated by causing the oxalic ester solution to mix with the hydrogen peroxide and fluorescer solution, which produces chemiluminescent light for treating a wound.

Abstract: A modulation recognition method and device for digitally modulated signals with multi-level magnitudes are provided. The modulation recognition method includes selecting plural quantization sizes used to construct plural statistic histograms related to the magnitude of a sequence of data, setting up an off-line processing to extract plural useful feature patterns for each modulation type of interest, receiving a sequence of samples of a modulated object signal and constructing plural statistic histograms related to the magnitude of these samples, and adopting a hierarchical classification method for modulation recognition. It can be applied to the adaptive-modulation communication system, software defined radio, digital broadcasting systems and military communication systems. It can also be integrated with modulation recognition techniques for other types of modulated signals to function in a universal demodulator.

Abstract: Techniques for determining the eagerness of a call processing unit within a multiple processor call processing system to accept a new call or call upgrade, as well as call admission control and other call event processing, as well as systemwide load balancing through query of such eagerness are disclosed. Fuzzy logic and associated analysis is used to determine this eagerness. Eagerness for a particular call processing unit is determined in part with reference to the actual load of a call as well as an estimated load approximated using a probabilistic distribution function, such as a Gaussian distribution.

Abstract: It is an object of the present invention to provide means for efficiently obtaining peptides that exhibit a high affinity toward a given target.

Abstract: A method and an apparatus for predicting intake manifold pressure are presented, to compensate for a large lag or a large time delay without producing an overshot or discontinuous behaviors of a predicted value. The method comprises the step of obtaining a difference of values of a variable to be predicted and a difference of values of another variable ahead of the variable to be predicted. The method further comprises the step of filtering the differences with adaptive filters. The method further comprises the step of obtaining a predicted difference of values of the variable to be predicted, through algorithm of estimation with fuzzy reasoning. The method further comprises the step of adding the predicted difference of values of the variable to be predicted, to a current value of the variable to be predicted, to obtain a predicted value of the variable to be predicted.

Abstract: A system and method for software estimation. In one embodiment, the software estimation system comprises a pre-processing neuro-fuzzy inference system used to resolve the effect of dependencies among contributing factors to produce adjusted rating values for the contributing factors, a neuro-fuzzy bank used to calibrate the contributing factors by mapping the adjusted rating values for the contributing factors to generate corresponding numerical parameter values, and a module that applies an algorithmic model (e.g. COCOMO) to produce one or more software output metrics.

Abstract: One embodiment of the present invention provides a system that uses interval techniques to solve a multi-objective optimization problem. During operation, the system receives a representation of multiple objective functions (ƒ1, . . . , ƒn) at a computer system, wherein (ƒ1, . . . , ƒn) are scalar functions of a vector x=(x1, . . . , xn). The system also receives a representation of a domain of interest for the multiple objective functions. Next, the system performs an interval optimization process to compute guaranteed bounds on a Pareto front for the objective functions (ƒ1, . . . , fn), wherein for each point on the Pareto front, an improvement in one objective function cannot be made without adversely affecting at least one other objective function. While performing the interval optimization process, the system applies a direct-comparison technique between subdomains of the domain of interest to eliminate subdomains that are certainly dominated by other subdomains.