Abstract: The invention provides a low current consumption control switch device and method related thereto. The control switch device includes a switch control component, a microprocessor, a wireless signal receiver for receiving control signal and a DC power supply. The DC power supply draws an AC current from the AC power supply to power the wireless signal receiver, the microprocessor and the switch control component. The switch control component has a control input for receiving control instructions to control current supply from the AC power supply. The microprocessor is operatively connected to the switch control component for providing control instructions to alter its switching state. The control signal comprises a preamble and a message portion. The wireless signal receiver is configured to alternate between at least two current consumption modes and to remain in a higher current consumption mode upon detection of the preamble.

Abstract: A universal remote control system is disclosed. The universal remote control includes a receiver that has a wireless signal receiver unit, an electric motor that drives a mechanical arm and a microprocessor. When the receiver receives a control signal from a wireless signal transmitter, the microprocessor will energize the motor which drives the mechanical arm toward a pushbutton switch of a controlled device, such as a garage door opener, and depresses the push button, therefore activating the garage door opener. A feedback signal, for example, from the mechanical arm or the motor, may be provided to the microprocessor to inform the microprocessor when the pushbutton switch is sufficiently depressed and is in an engaged state. When the switch is in the engaged state, the motor will reverse its direction, causing the mechanical arm to raise and move back to a standby position.

Abstract: A universal remote control system is disclosed. The universal remote control includes a receiver that has a wireless signal receiver unit, an electric motor that drives a mechanical arm and a microprocessor. When the receiver receives a control signal from a wireless signal transmitter, the microprocessor will energize the motor which drives the mechanical arm toward a pushbutton switch of a controlled device, such as a garage door opener, and depresses the push button, therefore activating the garage door opener. A feedback signal, for example, from the mechanical arm or the motor, may be provided to the microprocessor to inform the microprocessor when the pushbutton switch is sufficiently depressed and is in an engaged state. When the switch is in the engaged state, the motor will reverse its direction, causing the mechanical arm to raise and move back to a standby position.

Abstract: The invention provides a low current consumption control switch device and method related thereto. The control switch device includes a switch control component, a microprocessor, a wireless signal receiver for receiving control signal and a DC power supply. The DC power supply draws an AC current from the AC power supply to power the wireless signal receiver, the microprocessor and the switch control component. The switch control component has a control input for receiving control instructions to control current supply from the AC power supply. The microprocessor is operatively connected to the switch control component for providing control instructions to alter its switching state. The control signal comprises a preamble and a message portion. The wireless signal receiver is configured to alternate between at least two current consumption modes and to remain in a higher current consumption mode upon detection of the preamble.

Abstract: A method of monitoring and optionally controlling the biological activity in a boiler condensate and/or feedwater system is disclosed. The methodology involves looking at the amount of ATP in a boiler fluid.

Abstract: Techniques are provided for performing structural joins for answering containment queries. Such inventive techniques may be used to perform efficient structural joins of two interval lists which are neither sorted nor pre-indexed. For example, in an illustrative aspect of the invention, a technique for performing structural joins of two element sets of a tree-structured document, wherein one of the two element sets is an ancestor element set and the other of the two element sets is a descendant element set, and further wherein each element is represented as an interval representing a start position and an end position of the element in the document, comprises the following steps/operations. An index is dynamically built for the ancestor element set. Then, one or more structural joins are performed by searching the index with the interval start position of each element in the descendant element set.

Abstract: Most recent research of scalable inductive learning on very large streaming dataset focuses on eliminating memory constraints and reducing the number of sequential data scans. However, state-of-the-art algorithms still require multiple scans over the data set and use sophisticated control mechanisms and data structures. There is discussed herein a general inductive learning framework that scans the dataset exactly once. Then, there is proposed an extension based on Hoeffding's inequality that scans the dataset less than once. The proposed frameworks are applicable to a wide range of inductive learners.

Abstract: The present invention relates to the problem of scheduling work for employees and/or other resources in a help desk or similar environment. The employees have different levels of training and availabilities. The jobs, which occur as a result of dynamically occurring events, consist of multiple tasks ordered by chain precedence. Each job and/or task carries with it a penalty which is a step function of the time taken to complete it, the deadlines and penalties having been negotiated as part of one or more service level agreement contracts. The goal is to minimize the total amount of penalties paid. The invention consists of a pair of heuristic schemes for this difficult scheduling problem, one greedy and one randomized. The greedy scheme is used to provide a quick initial solution, while the greedy and randomized schemes are combined in order to think more deeply about particular problem instances.

Abstract: Methods and apparatus are provided for generating a decision trees using linear discriminant analysis and implementing such a decision tree in the classification (also referred to as categorization) of data. The data is preferably in the form of multidimensional objects, e.g., data records including feature variables and class variables in a decision tree generation mode, and data records including only feature variables in a decision tree traversal mode. Such an inventive approach, for example, creates more effective supervised classification systems. In general, the present invention comprises splitting a decision tree, recursively, such that the greatest amount of separation among the class values of the training data is achieved. This is accomplished by finding effective combinations of variables in order to recursively split the training data and create the decision tree. The decision tree is then used to classify input testing data.

Abstract: A computer implemented method, apparatus, and computer usable program code for processing multi-way stream correlations. Stream data are received for correlation. A task is formed for continuously partitioning a multi-way stream correlation workload into smaller workload pieces. Each of the smaller workload pieces may be processed by a single host. The stream data are sent to different hosts for correlation processing.

Abstract: Improved techniques are disclosed for detecting patterns of interaction among a set of entities and analyzing community evolution in a stream environment. By way of example, a technique for processing data from a data stream includes the following steps/operations. A data point of the data stream representing an interaction event is obtained. An interaction graph is updated on-line based on the data point representing the interaction event. The updated interaction graph is stored in a nonvolatile memory. An interaction evolution is determined off-line from the updated interaction graph stored in the nonvolatile memory.

Abstract: The present invention provides a ViST (or “virtual suffix tree”), which is a novel index structure for searching XML documents. By representing both XML documents and XML queries in structure-encoded sequences, it is shown that querying XML data is equivalent to finding (non-contiguous) subsequence matches. A variety of XML queries, including those with branches, or wild-cards (‘*’ and ‘//’), can be expressed by structure-encoded sequences. Unlike index methods that disassemble a query into multiple sub-queries, and then join the results of these sub-queries to provide the final answers, ViST uses tree structures as the basic unit of query to avoid expensive join operations. Furthermore, ViST provides a unified index on both content and structure of the XML documents, hence it has a performance advantage over methods indexing either just content or structure.

Abstract: The method trains an inductive model to output multiple models from the inductive model and trains an error correlation model to estimate an average output of predictions made by the multiple models. Then the method can determine an error estimation of each of the multiple models using the error correlation model.

Abstract: Improved privacy preservation techniques are disclosed for use in accordance with data mining. By way of example, a technique for preserving privacy of data records for use in a data mining application comprises the following steps/operations. Different privacy levels are assigned to the data records. Condensed groups are constructed from the data records based on the privacy levels, wherein summary statistics are maintained for each condensed group. Pseudo-data is generated from the summary statistics, wherein the pseudo-data is available for use in the data mining application.

Abstract: There is provided a method for determining reachability between any two nodes within a graph. The inventive method utilizes a dual-labeling scheme. Initially, a spanning tree is defined for a group of nodes within a graph. Each node in the spanning tree is assigned a unique interval-based label, that describes its dependency from an ancestor node. Non-tree labels are then assigned to each node in the spanning tree that is connected to another node in the spanning tree by a non-tree link. From these labels, reachability of any two nodes in the spanning tree is determined by using only the interval-based labels and the non-tree labels.

Abstract: Streaming environments typically dictate incomplete or approximate algorithm execution, in order to cope with sudden surges in the data rate. Such limitations are even more accentuated in mobile environments (such as sensor networks) where computational and memory resources are typically limited. Introduced herein is a novel “resource adaptive” algorithm for spectrum and periodicity estimation on a continuous stream of data. The formulation is based on the derivation of a closed-form incremental computation of the spectrum, augmented by an intelligent load-shedding scheme that can adapt to available CPU resources. Experimentation indicates that the proposed technique can be a viable and resource efficient solution for real-time spectrum estimation.

Abstract: Techniques for monitoring abnormalities in a data stream are provided. A plurality of objects are received from the data stream and one or more clusters are created from these objects. At least a portion of the one or more clusters have statistical data of the respective cluster. It is determined from the statistical data whether one or more abnormalities exist in the data stream.

Abstract: A technique for classifying data from a test data stream is provided. A stream of training data having class labels is received. One or more class-specific clusters of the training data are determined and stored. At least one test instance of the test data stream is classified using the one or more class-specific clusters.

Abstract: A technique of clustering data of a data stream is provided. Online statistics are first created from the data stream. Offline processing of the online statistics is then performed when offline processing either required or desired. Online statistics may be created through the reception of data points from the data stream and the formation and updating of data groups. Offline processing may be performed by reclustering groups of data points around sampled data points and reporting the newly formed clusters.

Abstract: There are provided a method, a computer program product, and a system for maintaining a materialized view defined on a relation of a relational database. The method includes the step of performing content-based filtering on the relation to identify an update to the relation as being irrelevant with respect to the materialized view.