Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: An adjustable shower device includes a water diversion valve body, a water inlet pipe, and more than one water outlet pipe. The water diversion valve body has a water inlet and more than one water outlet. The water inlet pipe is fixedly connected to the water inlet of the water diversion valve body. An inlet end of the more than one water outlet pipe is connected to the more than one water outlet. Because the water outlet pipe is a universal pipe that is a bendable metal shaping hose, the shower head on the water pipe can be swung to any height, which is more convenient for use.

Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: This disclosure provides, among other things, amplifiable nucleic acid constructs for expressing a gene of interest in a cell, e.g., an erythroid cell. The amplifiable nucleic acid construct may contain the gene of interest and an RNA-dependent RNA polymerase (RdRP)-responsive 5? UTR, and may optionally further contain an RdRP-responsive 3? UTR. RdRP may also be provided, e.g., on the same construct or a different construct.

Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: This disclosure provides a computer-implemented method for code suggestion. The method comprises collecting a set of runtime context features of a program that is being edited. The method further comprises comparing the set of runtime context features with at least one set of stored context features to find at least one matching set of stored context features. Each of the at least one set of stored context features is extracted from a corresponding code segment. The method further comprises presenting at least one code segment with its set of stored context features matching the set of runtime context features, for the user to choose to add into the program.

Abstract: This disclosure provides a computer-implemented method for automatically creating a macro-service. The method includes: converting source code of an analytic program that includes a set of operation units into a graph representation. Each of the set of operation units performs at least an operation to a data object, and the method further includes performing a query associated with the macro-service on the graph representation to determine a subset of the graph representation. The method further includes generating code for the macro-service based on the determined subset of the graph representation.

Abstract: A method for detecting deviations between an event log and a process model includes converting the process model into a probability process model, the probability process model comprising multiple nodes in multiple hierarchies and probability distribution associated with the multiple nodes, a leaf node among the multiple nodes corresponding to an activity in the process model; detecting differences between at least one event sequence contained in the event log and the probability process model according to a correspondence relationship; and identifying the differences as the deviations in response to the differences exceeding a predefined threshold; wherein the correspondence relationship describes a correspondence relationship between an event in one event sequence of the at least one event sequence and a leaf node in the probability process model.

Abstract: This disclosure provides a computer-implemented method for automatically creating a macro-service. The method includes: converting source code of an analytic program that includes a set of operation units into a graph representation. Each of the set of operation units performs at least an operation to a data object, and the method further includes performing a query associated with the macro-service on the graph representation to determine a subset of the graph representation. The method further includes generating code for the macro-service based on the determined subset of the graph representation.

Abstract: A method for using a plurality of decision engines to produce a single decision comprises: receiving heterogeneous data from the plurality of decision engines comprising a set of class labels from each of the plurality of decision engines, wherein the set of class labels from at least a first decision engine differs from the set of class labels from at least a second decision engine; generating a single set of unified class labels from the heterogeneous data; calculating at least one value corresponding to each of at least a subset of the unified class labels; and performing decision fusion on at least the subset of the unified class labels and corresponding values to produce the single decision.

Abstract: Techniques are provided that facilitate determining, by a system operatively coupled to a processor, respective performance scores for a first set of candidate transformation scripts based on a performance criterion, wherein the candidate transformation scripts are related to extract, transform, load (ETL) processing of a new data source to a data target. Techniques are also provided that facilitate generating, by the system, a recommendation of one or more of the first set of candidate transformation scripts based on the respective performance scores for performance of the ETL processing.

Abstract: Systems, computer-implemented methods and/or computer program products that facilitate providing treatment suggestions are described herein. In one example, a computer-implemented method comprises: generating, by a system operatively coupled to a processor, treatment directed graphs associated with a plurality of treatment regimens, wherein, in connection with generating respective treatment directed graphs, penalties are applied during weighting of respective regimens as a function of an associated confidence level; identifying a treatment directed graph that corresponds to the patient directed graph; and outputting a set of treatment suggestions associated with the treatment directed graph that corresponds to the patient directed graph.

Abstract: Disclosed are a computer-implemented method for converting a procedural process model for a process to a hybrid process model, a system and a computer program product. In this method, a plurality of steps of the process which are included in the procedural process model may be clustered selectively according to historical execution information of the plurality of steps, to generate a plurality of candidate cluster set. One candidate cluster set satisfying a first condition may be selected from the plurality of candidate cluster sets. Then, the procedural process model may be converted into the hybrid process model according to the selected candidate cluster set.

Abstract: A method, device, and computer program storage product for generating a query to extract clinical features into a set of electronic medical record (EMR) tables based on clinical knowledge. A knowledge tree is constructed according to a set of clinical knowledge data. An EMR graph corresponding to a set of EMR tables is obtained. The EMR graph comprises at set of table nodes and a set of attribute nodes. The set of table nodes and the set of attribute nodes represent a structure of each EMR table in the set of EMR tables and a reference relationship among attributes of set of EMR tables. A plurality of sub-queries is generated based on the knowledge tree and the EMR graph. At least one query is generated by combining the plurality of sub-queries according to the knowledge tree.

Abstract: This disclosure provides a computer-implemented method for code suggestion. The method comprises collecting a set of runtime context features of a program that is being edited. The method further comprises comparing the set of runtime context features with at least one set of stored context features to find at least one matching set of stored context features. Each of the at least one set of stored context features is extracted from a corresponding code segment. The method further comprises presenting at least one code segment with its set of stored context features matching the set of runtime context features, for the user to choose to add into the program.

Abstract: The present invention relates to Angiopoietin-3 (Ang-3) and Angiopoietin-4 (Ang-4). The present invention also relates to methods of modulating an activity of Ang-3 or Ang-4. The present invention further relates to methods of treating cancer, diabetes, and arthritis.

Abstract: A method for using a plurality of decision engines to produce a single decision comprises: receiving heterogeneous data from the plurality of decision engines comprising a set of class labels from each of the plurality of decision engines, wherein the set of class labels from at least a first decision engine differs from the set of class labels from at least a second decision engine; generating a single set of unified class labels from the heterogeneous data; calculating at least one value corresponding to each of at least a subset of the unified class labels; and performing decision fusion on at least the subset of the unified class labels and corresponding values to produce the single decision.

Abstract: The present invention provides a light string with reinforced wires. The light string includes a plurality of reinforced wires and a plurality of lamps electrically connected in series via the plurality of reinforced wires. Each reinforced wire includes a plurality of conducting wires, an outer insulating sheath covering the plurality of conducting wires and one or more reinforcing strands configured between an inner side surface and an outer side surface of the outer insulating sheath and extending along a direction parallel to a central longitudinal axis of the reinforced wire. The bending resistant performance of the electric wire between each two adjacent lamps is improved greatly, the fatigue strength of the electric wire is much better than that of an ordinary electric wire, and the tensile strength of the electric wire is improved.

Abstract: Disclosed are a computer-implemented method for converting a procedural process model for a process to a hybrid process model, a system and a computer program product. In this method, a plurality of steps of the process which are included in the procedural process model may be clustered selectively according to historical execution information of the plurality of steps, to generate a plurality of candidate cluster set. One candidate cluster set satisfying a first condition may be selected from the plurality of candidate cluster sets. Then, the procedural process model may be converted into the hybrid process model according to the selected candidate cluster set.