Abstract: A stream processing execution engine evaluates development-time performance characteristic estimates in combination with run-time parameters to schedule execution of stream processing software components in a stack of a stream processing application that satisfy a defined performance criterion in a heterogeneous hardware device. A stream processing application includes a stack of interdependent stream processing software components. A stream processing execution engine evaluates one or more performance characteristics of multiple computational resources in the heterogeneous hardware device. Each performance characteristic is associated with performance of a computational resource in executing a computational-resource-dependent instance of a stream processing software component. The stream processing execution engine schedules within the run-time environment a computational resource on which to execute a computational-resource-dependent instance of one of the stream processing software components.

Abstract: A container is combined with a base having insect combating features, i.e. for trapping and/or poisoning of insects, preferably but not necessarily combined with insect attracting elements. In particular, the container may be a waste basket, and the targeted insects may be bed bugs, and/or roaches, and/or ants. The assembly has a container portion and a base portion. The interior of the base portion is accessible by insects via one or more small gaps or openings, and contains the trapping and/or poisoning elements, which may include a replaceable glue strip or the like. Preferably, the assembly is also be provided with insect attracting means, which may include chemical attractants, carbon dioxide generation, and/or heat. In some embodiments, separate areas may be provided to combat different insects.

Abstract: The invention is directed at joint assembly which includes a first part and a second part to be assembled together. The first and second part are secured together via a set of fasteners and a set of attachment portions. The set of attachment portions cooperate with one of the first or second parts and receive the set of fasteners.

Abstract: System fault codes, component fault codes, and failure modes may be received at a system. A first level model comprising first level causal relationships and first level causal weights between the system fault codes and the component fault codes may be generated. A second level model comprising second level causal relationships and second level causal weights between the component fault codes and the failure modes may be generated. The first level model and the second level model may be combined to generate a model such as graphical model. One or more causal probabilities may be determined using the graphical model.

Abstract: A method for correcting service manual textual inconsistencies. Extracting textual procedures from service documents stored in a memory of a service document storage device. Each term of an extracted textual procedure terminology is compared to a correlating target name terminology for identifying any matching terms by a processor. An overlap similarity is computed as a function of the identified matching terms from the extracted textual procedure terminology and the correlating target name terminology. A determination is made whether the overlap similarity is greater than a predetermined similarity threshold. The service documents are modified to change the extracted textual procedure terminology to the correlating target name terminology in response to the overlap similarity being greater than the predetermined similarity threshold and the extracted textual procedure terminology not exactly matching the correlating target name terminology.

Abstract: A detection and/or control device (1) for bed bugs and other arthropods has at least one surface (9,10) having sufficient texture for a bed bug or other arthropod to climb, leading to a confinement area (6) having surrounding surfaces (7, 8) being sufficiently smooth that the bed bug or other arthropod cannot climb out of the confinement area. The confinement area has a preferably removable and replaceable glue pad or other such trap (16, 26, 66, 85) to trap the bed bug or other arthropod in a specific location within the confinement area. A variety of specific devices are described, including a coaster-type device (1) for placement under bed posts and the like, a frame (21) for light switches and electrical outlets, a cover (80) for heat or air conditioning air outlets, and various extruded rails (50, 52, 60) to act as barriers.

Abstract: A carbon dioxide generator includes: a storage chamber at the bottom, which is charged with solid that can produce carbon dioxide by adding fluid; a gas chamber above the storage chamber; a fluid inlet and a carbon dioxide outlet on the top of the gas chamber. The storage chamber and the fluid chamber are connected by at least two holes which permit fluid to enter the storage chamber and carbon dioxide to escape from the storage to the fluid chamber. A method of using this generator to produce carbon dioxide includes adding fluid to the generator. It can supply an even and targeted carbon dioxide output, making it useful for attracting bed bugs or mosquitos to bed bug or mosquito traps for detection and/or elimination.

Abstract: A method and system for comparing and merging fault models which are derived from different data sources. Two or more fault models are first represented as bipartite weighted graphs, which define correlations between failure modes and symptoms. The nodes of the graphs are compared to find failure modes and symptoms which are the same even though the specific terminology may be different. A graph matching method is then used to compare the graphs and determine which failure mode and symptom correlations are common between them. Finally, smoothing techniques and domain expert knowledge are used to merge and update the fault models, producing an integrated fault model which can be used by onboard vehicle systems, service facilities, and others.

Abstract: A method includes collecting vehicle health data from a plurality of vehicles. A peer group is identified among the plurality of vehicles. The collected vehicle health data from the peer group into a collaborative vehicle health model, the collaborative vehicle health model being applicable to a current vehicle to predict a state of at least a component of the current vehicle.

Abstract: A method and system for developing fault models from structured text documents, such as service procedures. A service procedure or other structured text document is parsed using diagnostic rules to extract symptoms, failure modes, and correlations. Testing procedures and repair instructions are also parsed to create a fault tree and identify additional symptoms and failure modes. Reachability analysis is then used to find hidden dependencies in the fault tree, thus yielding additional correlations. The resultant symptoms, failure modes, and correlations are then assembled into a fault model, which can be used for real-time fault diagnosis onboard a vehicle, or for off-board diagnosis at service shops.

Abstract: A method is provided for identifying a root cause of a fault in a serviced vehicle based on analytical symptoms. Parameter identification data associated with identified DTCs is retrieved. Parameter identification data from a plurality of vehicles experiencing the DTCs is collected. A first set of diagnostic rules is generated that identify vehicle operating parameters for executing a DTC algorithm or for triggering a DTC. A second set of diagnostic rules is generated that identify vehicle operating parameters used for selecting field failure data obtained when the DTC is triggered. Statistically significant rules are extracted from the second set of diagnostic rules. The first set of rules and the statistically significant rules are cooperatively applied to the parameter identification data for identifying a subset of the parameter identification data that represents anomalies. A subject matter expert analyzes the anomalies for identifying a root cause of the fault.

Abstract: A system and method for fault diagnosis includes receiving information defining a relationship between failure modes and diagnostic trouble codes and extracting diagnostic trouble code data, including set times, frequency data and diagnostic trouble code sequence information for a plurality of diagnostic trouble codes relating to a plurality of failure modes. The system and method further include constructing a Markov chain using the diagnostic trouble code data for each of the plurality of failure modes, training the Markov chain to learn a set of state parameters using the diagnostic trouble code data, and computing a likelihood of a diagnostic trouble code sequence for each of the plurality of failure modes using the trained Markov chains.

Abstract: A method for verifying and improving a vehicle fault model is disclosed. The method includes analyzing the available field failure data that includes vehicle symptoms and failures for many vehicles. The method performs an analysis using the field failure data that includes using subject matter expert knowledge to determine the most significant failure modes and the most significant symptoms. The method also includes learning simulation parameters from the field failure data and simulating faults using the learned simulation parameters. The method further includes verifying and validating the fault model based on the most significant failure modes and the most significant symptoms from the what-if analysis and the faults identifies by the simulation, and using a diagnostic reasoner to analyze the revised fault model to generate estimated faults. The method then compares the estimated faults to the simulated faults to determine true detection and false alarm rates for a benefit analysis.

Abstract: System fault codes, component fault codes, and failure modes may be received at a system. A first level model comprising first level causal relationships and first level causal weights between the system fault codes and the component fault codes may be generated. A second level model comprising second level causal relationships and second level causal weights between the component fault codes and the failure modes may be generated. The first level model and the second level model may be combined to generate a model such as graphical model. One or more causal probabilities may be determined using the graphical model.

Abstract: A vehicle repair assist system for repairing a vehicle fault in a vehicle. A symptom input module is provided for entering vehicle symptom information relating to the fault. A diagnostic code module retrieves diagnostic trouble codes from the vehicle. The diagnostic trouble codes are generated in response to a fault occurrence. A knowledge-based fault module identifies potential causes of the vehicle fault based on at least one of the symptom information and diagnostic trouble codes. A repair assistant module identifies recommended repair parts and repair procedures for repairing the cause of the vehicle fault. The repair assistant module communicates with the knowledge-based fault module for obtaining a prioritized listing of the recommended repair parts and repair procedures for repairing the vehicle fault.

Abstract: A parameter identification-based fault isolation technique is provided for improving fault code settings and isolating faults. DTCs and PIDs are retrieved from a current serviced vehicle. PID data is obtained from prior serviced vehicles having same vehicle specifications as and under substantially similar operating conditions as the current serviced vehicles. A plurality of clusters is formed using PID data of the prior serviced vehicles using mutual dependence to one another. A joint probability distribution is determined as a function of a mutual dependence of the PID data. PID data is selected of the current serviced vehicle having coherence to the PID of the prior service vehicles. A mutual dependence of the PID data of the current serviced vehicle is projected on onto the corresponding joint probability distribution.

Abstract: A method is provided for identifying a root cause of a fault in a serviced vehicle based on analytical symptoms. Parameter identification data associated with identified DTCs is retrieved. Parameter identification data from a plurality of vehicles experiencing the DTCs is collected. A first set of diagnostic rules is generated that identify vehicle operating parameters for executing a DTC algorithm or for triggering a DTC. A second set of diagnostic rules is generated that identify vehicle operating parameters used for selecting field failure data obtained when the DTC is triggered. Statistically significant rules are extracted from the second set of diagnostic rules. The first set of rules and the statistically significant rules are cooperatively applied to the parameter identification data for identifying a subset of the parameter identification data that represents anomalies. A subject matter expert analyzes the anomalies for identifying a root cause of the fault.

Abstract: A stream processing execution engine evaluates development-time performance characteristic estimates in combination with run-time parameters to schedule execution of stream processing software components in a stack of a stream processing application that satisfy a defined performance criterion in a heterogeneous hardware device. A stream processing application includes a stack of interdependent stream processing software components. A stream processing execution engine evaluates one or more performance characteristics of multiple computational resources in the heterogeneous hardware device. Each performance characteristic is associated with performance of a computational resource in executing a computational-resource-dependent instance of a stream processing software component. The stream processing execution engine schedules within the run-time environment a computational resource on which to execute a computational-resource-dependent instance of one of the stream processing software components.

Abstract: Systems and methods for capturing and analyzing significant parameter data from vehicle systems whenever a diagnostic trouble code (DTC) is triggered. A multi-dimensional matrix is constructed, with vehicles, DTCs, and parameter data comprising three dimensions of the matrix. The data matrix is populated with DTC and parameter data from many different vehicles, either when vehicles are taken to a dealer for service, or via wireless data download. Time can be added as a fourth dimension of the matrix, providing an indication of whether a particular system or component is temporally degrading. When sufficient data is accumulated, the data matrix is pre-processed, features are extracted from the data, and the features are classified, using a variety of mathematical techniques. Trained classifiers are then used to diagnose the root cause of any particular fault signal, and also to provide a prognosis of system health and remaining useful life.

Abstract: A bed bug trap includes heat, carbon dioxide and/or semiochemicals (pheromones and/or kairomones), to attract and trap bed bugs. The trap may be combined with the appearance and/or function of another appliance, such as an air freshener. The release of semiochemicals may be combined with the release of air freshening compositions. The bed bug trap may provide one attraction mode, or two attraction modes, namely one which uses heat, carbon dioxide and/or kairomones to attract bed bugs seeking a meal, and the other which uses pheromones to attract bed bugs seeking a safe harbor, i.e. a hiding place. The bed bug trap may be combined with a wide variety of appliances, such as air fresheners, alarm clocks, clock radios, humidifiers, desk or table lamps, power bars, etc..