Abstract: Disclosed are methods for cleaning of devices, such as heat exchangers, in particular to methods wherein machine learning systems, such as trained neural networks are used for indicating the fouling status the during the cleaning processes.

Abstract: Disclosed are methods for cleaning of devices, such as heat exchangers, in particular to methods wherein machine learning systems, such as trained neural networks are used for indicating the fouling status the during the cleaning processes.

Abstract: Systems, methods, and machine-readable media for identifying a geometric footprint of a point of interest (POI) based on location sharing events received from mobile devices are provided. The geometric footprint may be calculated based on the received location sharing events and stored in the POI listing for that POI. In one aspect, the geometric footprint may be further refined based on subsequently received location sharing events. The system, according to certain aspects, may include an interface module, a POI module, and a footprint module. The interface module may be configured to receive a location sharing event from a mobile device, the location sharing event including an event location coordinate and a POI identifier. The POI module may be configured to identify the POI listing in the database based on the POI identifier, the POI listing including a POI location coordinate.

Abstract: A method is provided for determining a true geometry of a point of interest including identifying one or more geometries associated with one or more places according to one or more relationships, generating a candidate set of geometries for a first place of the one or more places including one or more candidate geometries including one or more of the one or more geometries being associated with the first place according to the one or more relationships, ranking the one or more candidate geometries of the candidate set according to a ranking criteria, where the ranking sorts the one or more candidate geometries according to the likelihood of a candidate geometry to be the true geometry of the place and selecting a first candidate geometry of the one or more candidate geometries of the candidate set as the true geometry for the first place according to the ranking.

Abstract: Systems, methods, and machine-readable media for identifying a geometric footprint of a point of interest (POI) based on location sharing events received from mobile devices are provided. The geometric footprint may be calculated based on the received location sharing events and stored in the POI listing for that POI. In one aspect, the geometric footprint may be further refined based on subsequently received location sharing events. The system, according to certain aspects, may include an interface module, a POI module, and a footprint module. The interface module may be configured to receive a location sharing event from a mobile device, the location sharing event including an event location coordinate and a POI identifier. The POI module may be configured to identify the POI listing in the database based on the POI identifier, the POI listing including a POI location coordinate.

Abstract: A pattern-based data matching system matches pattern-based data. The data matching system generates a regular expression pattern for input datasets and describes similarity measures between the generated patterns. The data matching system analyzes an input dataset in terms of symbol classes, generalizing input values into a general pattern to allow identification or extrapolation of overlap between input datasets, aiding in matching fields in databases that are being merged and in learning a pattern for an input dataset. For each sequence of data values, the present system computes a compact pattern describing the sequence. Embodiments of the data matching system comprise noise reduction and repetitive pattern discovery in the input dataset and calculation of recall and precision of the generated pattern.

Abstract: A system for automatic proximity-based preloading of relevant information in portable devices pre-loads a portable device such as a mobile telephone, a personal digital assistant (PDA) or portable computer before the occurrence of a trip or event, with information relevant to the user's current or upcoming tasks. The system locates and loads into the portable device only the information required by the user for near term projects, meetings, or trips. The system is generally comprised of an information catalog, a proximity estimator, a relevance estimator, an information retriever, and a device loader. The information catalog contains a list of the information sources and items to which the user has access and from which the system of the invention will retrieve data to be loaded into the mobile device. The proximity estimator determines the proximity of various relevant information items to the user's tasks based on distance, time, and/or association.

Abstract: A pattern-based data matching system matches pattern-based data. The data matching system generates a regular expression pattern for input datasets and describes similarity measures between the generated patterns. The data matching system analyzes an input dataset in terms of symbol classes, generalizing input values into a general pattern to allow identification or extrapolation of overlap between input datasets, aiding in matching fields in databases that are being merged and in learning a pattern for an input dataset. For each sequence of data values, the present system computes a compact pattern describing the sequence. Embodiments of the data matching system comprise noise reduction and repetitive pattern discovery in the input dataset and calculation of recall and precision of the generated pattern.

Abstract: A pattern-based data matching method matches pattern-based data. The data matching method generates a regular expression pattern for input datasets and describes similarity measures between the generated patterns. The data matching method analyzes an input dataset in terms of symbol classes, generalizing input values into a general pattern to allow identification or extrapolation of overlap between input datasets, aiding in matching fields in databases that are being merged and in learning a pattern for an input dataset. For each sequence of data values, the present method computes a compact pattern describing the sequence. Embodiments of the data matching method comprise noise reduction and repetitive pattern discovery in the input dataset and calculation of recall and precision of the generated pattern.

Abstract: The present invention provides a manner for providing Web crawlers capable of efficiently accessing Web content not accessible via static hyperlinks. Log files are maintained of communications between a Web browser and a Web server resulting from real user accesses to the content associated with dynamic hyperlinks. These log files represent past user's accesses to the content and are used to generate Web crawler accesses. This approach allows a crawler to accurately mimic real users, resulting in a capability of the crawler to automatically access all the content that real users would have access to.

Abstract: A method for creating a web service to programmatically access a network addressable location via an intermediate gateway includes analyzing a network at the location; generating, at the gateway, a service description file and an executable code for the network page; translating the service description file into a standard Web service format; deploying the service to the gateway, making the service available to a client application; providing a runtime process to enable the client application to automatically make a programmatic request of the location; translating the structure of the request to a syntax of location using SOAP; submitting the request to the location which executes the submitted request to obtain a response; translating the response to extract data satisfying the request; wrapping the extracted data in a SOAP envelope; translating the wrapped response to a host data structure of the client application; and compiling the executable code.

Abstract: A target device's location is estimated by a location estimation module (LEM) that comprises a probabilistic model (PM) for a plurality of sample points, each of which comprises a sample location and an expected distribution of signal values at that sample point. The location estimation module (LEM) makes a sequence (OS) of observations on, n=1, 2, 3 . . . , of signal values. Each observation corresponds to a respective location qn along the target device's path. The sequence of observations and the respective location constitute a hidden Markov model. The module estimates the target device's location qn based on the probabilistic model (PM) and the sequence of observations, wherein the sequence of observations comprises one or more future observations on+m for which m is a positive integer. In other words, the target device's location is estimated, at least partially, based on knowledge of its future.

Abstract: A system and method for communication of information that has particular significance to a specific location only to those individuals that are at or near that geo-spatial location. In particular, providing safety factor data and alerts is a preferred use of the invention. The invention allows information to be tailored to the individual at that location by selectively filtering what is communicated and what is not. The system includes a transmitting proximity event server, a GPS client wireless component that can be a personal wireless communication device (such as Palm Pilot, cellular digital phones, etc.) or personal computer configured for use within a global position satellite network.

Abstract: A method for estimating a receiver's location in a wireless communication environment having several channels. Each channel has at least one signal parameter that varies with location differently from the other channels. A set of calibration data is determined for each calibration point, each set including the location and at least one measured signal parameter for each of several channels. The calibration data serve as a basis for a statistical model of the signal parameters versus a receiver's location. A set of observed signal parameters is determined, the set including at least one signal parameter for each of several channels at the receiver's location. A location estimate approximating the location of the receiver is determined on the basis of the statistical model and the set of observed signal parameters.

Abstract: A model construction module for constructing a probabilistic model of a wireless environment in which a target device communicates using signals that have a measurable signal value, such as signal strength. The model construction module forms several submodels of the wireless environment. Each submodel indicates a probability distribution for signal values at one or more locations in the wireless environment. The module combines the submodels to a probabilistic model of the wireless environment, such that the probabilistic model indicates a probability distribution for signal values at several locations in the wireless environment. Alternatively, the model may insert new locations to a single model based on a combination of existing locations. The combination of submodels or existing locations includes combining the inverse cumulative distribution functions of the submodels or existing locations.

Abstract: A method for determining an error estimate concerning a target device's location. The target device moves and communicates in a wireless environment using signals having at least one measurable signal value. A probabilistic model of the wireless environment indicates a probability distribution for signal values at several sample points in the wireless environment. A set of observations of signal values is made and the target device's location is estimated based on the probabilistic model and the set of observations. The error estimate is determined as a combination of products over several sample points. Each product comprises a probability distribution for the sample point in question being the target device's location and a distance function between the sample point in question and the target device's estimated location.

Abstract: A model construction module (MCM) for constructing a probabilistic model (PM) of a wireless environment (RN) in which a target device (T) communicates using signals that have a measurable signal value (x), such as signal strength. The model construction module forms several submodels (611–631) of the wireless environment (RN). Each submodel indicates a probability distribution (F1–F3) for signal values at one or more locations (Q1–QY) in the wireless environment. The module combines the submodels to a probabilistic model (PM) of the wireless environment (RN), such that the probabilistic model indicates a probability distribution for signal values at several locations in the wireless environment. Alternatively, the model may insert new locations to a single model based on a combination of existing locations. The combination of submodels or existing locations includes combining the inverse cumulative distribution functions of the submodels or existing locations.

Abstract: A system (and method and programmable storage medium for storing program steps of the method) for locating an alternate communication mechanism in case of a failure of a wireless device, includes a location tracker for continuously transmitting information to the wireless communication device for allowing a user to locate an alternate communication mechanism after the failure has occurred.

Abstract: A computer program product is provided as a system for use with the Internet to determine the physical location of IP addresses. The system of the invention includes a locator broker and various databases. The locator broker is the intermediary between the locator sources that estimate the physical location of an IP address and the online sites requesting the physical location of the IP address. The locator broker aggregates and validates the results from its location queries of the locator sources then returns to the online site the most likely location for a given IP address. The locator broker also tracks the reliability of each locator source and thus targets its location queries to those services most likely to provide an accurate result. The locator broker digests location data from multiple geolocation services and presents a coherent view of the location data to the online site.

Abstract: A system, method and computer program product for enabling a user to detect nearby RFID tags and identify nearby RFID readers to enhance user privacy. A portable RFID reader scans for nearby tags, and a universal RFID tag detects nearby readers. The invention can alert the user of nearby RFID tags or readers, unless the user has disabled the alerting feature or unless a particular tag or reader is already known to the user and has been deemed allowable. A memory includes editable lists of allowable tags and readers. Exemplary alerts include outputs from a sound emitter, a vibrator, a light, or a display readout. The invention thus prevents surreptitious identification and tracking of a user and a user's possessions. The invention may be integrated into items typically carried by users so that the detection and alerting may be performed without outward indication.