Abstract: One embodiment provides a system for facilitating a graph search engine. During operation, the system receives, by a server from a client computing device, a search request which includes a user-inputted graph. The system performs a search based on a structure of the user-inputted graph for a plurality of relevant graphs. The system orders the plurality of relevant graphs from a most relevant ranking to a least relevant ranking. The system returns, to the client computing device, the ordered plurality of relevant graphs for display on a user interface of the client computing device, thereby enhancing the search for relevant graphs by allowing the graph search engine to take as an input the user-inputted graph and return as an output the relevant graphs.

Abstract: The present invention relates to enzymes which possess desaturase, conjugase, epoxidase and/or hydroxylase activity that can be used in methods of synthesizing fatty acids.

Abstract: A method of deep graph representation learning includes: calculating a plurality of base features from a graph and adding the plurality of base features to a feature matrix. The method further includes generating, by a processing device, a current feature layer from the feature matrix and a set of relational feature operators, wherein the current feature layer corresponds to a set of current features, evaluating feature pairs associated with the current feature layer, and selecting a subset of features from the set of current features based on the evaluated feature pairs. The method further includes adding the subset of features to the feature matrix to generate an updated feature matrix.

Abstract: The present invention relates to extracted lipid with high levels, for example 90% to 95% by weight, oleic acid. The present invention also provides genetically modified plants, particularly oilseeds such as safflower, which can used to produce the lipid. Furthermore, provided are methods for genotyping and selecting plants which can be used to produce the lipid.

Abstract: System and methods for relational time-series learning are provided. Unlike traditional time series forecasting techniques, which assume either complete time series independence or complete dependence, the disclosed system and method allow time series forecasting that can be performed on multivariate time series represented as vertices in graphs with arbitrary structures and predicting a future classification for data items represented by one of nodes in the graph. The system and methods also utilize non-relational, relational, temporal data for classification, and allow using fast and parallel classification techniques with linear speedups. The system and methods are well-suited for processing data in a streaming or online setting and naturally handle training data with skewed or unbalanced class labels.

Abstract: A method and system for searching a graph in parallel which constructs an abstract representation of an AND/OR graph using state-space abstraction. The abstract representation of the graph includes one or more abstract nodes having duplicate detection scopes and one or more abstract edges having operator groups adjusted for AND node outcomes. The duplicate detection scopes of the abstract nodes are partitioned into smaller duplicate detection scopes using edge partitioning, wherein the abstract edges are used to define the smaller duplicate detection scopes. Nodes in the current search layer are expanded by a processing unit using the adjusted operator groups of outgoing abstract edges of the abstract nodes mapped into by the nodes, wherein the nodes expanded in parallel use adjusted operator groups associated with abstract edges having disjoint duplicate detection scopes.

Abstract: Embodiments of the present invention provide a time- and space-efficient system for representing and searching a set of intervals to find all the intervals that overlap with a given query interval or point. A new structure called an interval hash table is introduced to significantly reduce the average search time, thereby improving computing and search technology. During operation, the system obtains data indicating a set of intervals to be hashed. The system divides a respective interval into a set of sub-intervals based on a locality-preserving hashing. The system then obtains a hash code associated with a respective sub-interval, and inserts the respective sub-interval into an interval hash table at a location corresponding to the hash code. The system may further search the interval hash table.

Abstract: A molecular network-based web search and information aggregation system and a process for creating a synthetic molecular network are disclosed. The amount of information and data available through the Internet is growing rapidly, yet current search through natural language-based keyword and page rank algorithm or directory search often cannot provide satisfactory relevant results. The process creates the synthetic molecular network according to a set of rules and chemistry knowledge. The synthetic molecular network is structured such that molecular information can be aggregated in ways that conform to contemporary graphing theory and chemistry rules. In this way, the molecular network-based web search and information aggregation system reduces reliance on natural language by leveraging strong relational associations between molecules that do not correlate to a set of natural language keywords.

Abstract: Provided is a high-performance implementation of the k-means clustering algorithm on a graphics processing unit (GPU), which leverages a set of GPU kernels with complimentary strengths for datasets of various dimensions and for different numbers of clusters. The concepts of non-dominated GPU kernels and efficient strategies to select high-throughput kernels that match the arguments of the clustering problem with the underlying GPU hardware for maximum speedup are provided.

Abstract: The present invention relates to extracted lipid with high levels, for example 90% to 95% by weight, oleic acid. The present invention also provides genetically modified plants, particularly oilseeds such as safflower, which can used to produce the lipid. Furthermore, provided are methods for genotyping and selecting plants which can be used to produce the lipid.

Abstract: A diagnostic test system includes a housing, a reader, and a data analyzer. The housing includes a port constructed and arranged to receive a test strip that includes a flow path for a fluid sample, a sample receiving zone couple to the flow path, a label that specifically binds a target analyte, a detection zone coupled to the flow path and comprising a test region exposed for optical inspection and having an immobilized test reagent that specifically binds the target analyte, and at least one reference feature. The reader is operable to obtain light intensity measurements from exposed regions of the test strip when the test strip is loaded in the port.

Abstract: A system and method for efficient sparse matrix processing are provided in one embodiment. A compressed representation of a sparse matrix, the sparse matrix including one or more non-zero entries in one or more of a plurality of portions of the matrix, is obtained by at least one server including one or more streaming multiprocessors, each of the streaming multiprocessors including one or more graphics processing unit (GPU) processor cores. Each of the portions are assigned into one of a plurality of partitions based on a number of the non-zero entries in that portion. For each of the partitions, a predefined number of the GPU processor cores are assigned for processing each of the portions assigned to that partition based on the numbers of the non-zero entries in the portions assigned to that partition. For each of the partitions, each of the portions associated with that partition are processed.

Abstract: A method for resource allocation includes: a base station determining a user equipment UE to which a resource block is to be allocated; and if the index number of any resource block among the allocated resource blocks of the UE falls within a preset first index number range, judging whether the number of the allocated resource blocks of the UE is less than the preset first parameter value.

Abstract: To preserve job integrity and minimize multi-site coordination overhead such as shipping, a technique to control the amount of outsourcing activities in a distributed manufacturing environment is provided. This approach to multi-site scheduling allows outsourcing control for distributed cellular manufacturing based on scheduling constraints called outsourcing group constraints.

Abstract: A method of deep graph representation learning includes: calculating a plurality of base features from a graph and adding the plurality of base features to a feature matrix. The method further includes generating, by a processing device, a current feature layer from the feature matrix and a set of relational feature operators, wherein the current feature layer corresponds to a set of current features, evaluating feature pairs associated with the current feature layer, and selecting a subset of features from the set of current features based on the evaluated feature pairs. The method further includes adding the subset of features to the feature matrix to generate an updated feature matrix.

Abstract: A system and a method perform matrix factorization. According to the system and the method, at least one matrix is received. The at least one matrix is to be factorized into a plurality of lower-dimension matrices defining a latent feature model. After receipt of the at least one matrix, the latent feature model is updated to approximate the at least one matrix. The latent feature model includes a plurality of latent features. Further, the update performed by cycling through the plurality of latent features at least once and alternatingly updating the plurality of lower-dimension matrices during each cycle.

Abstract: Embodiments described herein provide a system for facilitating hybrid task management across a central processing unit (CPU) and a graphics processing unit (GPU) of a computer. During operation, the system determines a set of tasks for performing data mining on a data set and storing the set of tasks in a data structure in an ascending order of uniformity associated with a respective task. The uniformity of a task indicates how uneven and skewed the task is compared to other tasks in the set of tasks. The system then allocates a subset of tasks to a core of the CPU from a front of the data structure and a subset of tasks to a core of the GPU from a back of the data structure.

Abstract: A method includes receiving a selection of a predefined implementation variation for a variable service component in at least one computing device configured to implement a service-oriented application; and executing source code associated with the variable service component in response to receiving the selection, wherein the source code performs a predetermined rebuilding of at least a portion of the service-oriented application such that the variable service component is redefined according to the selected implementation variation.

Abstract: Embodiments of the present invention provide a system for fast parallel graph compression based on identifying a set of large cliques, which is used to encode the graph. The system provides both permanently-stored and in-memory graph encoding and reduces the space needed to represent and store a graph, the I/O traffic to use the graph, and the computation needed to perform algorithms involving the graph. The system thereby improves computing technology and graph computation. During operation, the system obtains data indicating vertices and edges of a graph. The system executes a clique-finding method to identify a maximum clique in the graph. The system then removes the clique from the graph, adds the clique to a set of found cliques, and generates a compressed representation of the graph based on the set of found cliques.

Abstract: An assay test strip includes a flow path, a sample receiving zone, a label, a detection zone that includes a region of interest, and at least one position marker. The at least one position marker is aligned with respect to the region of interest such that location of the at least one position marker indicates a position of the region of interest. A diagnostic test system includes a reader that obtains light intensity measurement from exposed regions of the test strip, and a data analyzer that performs at least one of (a) identifying ones of the light intensity measurements obtained from the test region based on at least one measurement obtained from the at least one reference feature, and (b) generating a control signal modifying at least one operational parameter of the reader based on at least one measurement obtained from the at least one reference feature.