Abstract: An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

Abstract: An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

Abstract: An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

Abstract: An object of the present invention is to achieve both suppression of data amount of an image processing system that learns a collation image to be used for image identification using a discriminator and improvement of identification performance of the discriminator. In order to achieve the above object, there is proposed an image processing system including a discriminator that identifies an image using a collation image, the image processing system further including a machine learning engine that performs machine learning of collation image data required for image identification. The machine learning engine searches for a successfully identified image using an image for which identification has been failed, and adds information, obtained based on a partial image of the image for which identification has been failed and which has been selected by an input device to the successfully identified image obtained by the search to generate corrected collation image data.

Abstract: To improve diagnostic accuracy in diagnosing for abnormality of a machine, it is necessary to adjust a parameter regarding diagnosis such as the number of clusters. In such an adjustment operation, each time a diagnostic parameter is modified, a checking operation by an analysis operator is required to see whether a diagnosis result has been improved. The present invention assists in the checking operation to see whether diagnostic accuracy has been improved by comparing diagnosis results before and after parameter modification. If there are many items of sensor data for diagnosis, many items of abnormality degree data arise as analysis result. Many items of data pose a problem that comparing diagnosis results takes time. In the data display system, abnormality degree data that has changed largely before and after parameter modification is automatically found and displayed to the analysis operator. How much an abnormality degree has changed is determined as an abnormality degree change rate, i.e.

Abstract: An abnormality detection procedure development apparatus (10) includes: a parameter setting unit (14) that sets a parameter verification range, with respect to the parameter relating to abnormality determination which is included in an abnormality detection procedure for a mechanical apparatus; an evaluation unit (15) that causes the value of the parameter to be changed in the parameter verification range, and, with respect to each of the values of the parameter that are changed, evaluates abnormality detection performance of the abnormality detection procedure; and a display unit (19) on which a performance evaluation table that is a listing of abnormality detection performances which are evaluated by the evaluation unit (15) is displayed with respect to each of the values of the parameter.

Abstract: In the conventional technique, network performances of a machine and a server become different due to the diagnosis target machine when a fault symptom diagnosis function is provided to a plurality of different diagnosis target machines. Therefore, the plurality of different machines are not able to be handled using one system. The present invention is a fault symptom diagnosis system including: a diagnosis execution unit; an arrangement unit; a diagnosis target machine; a diagnosis server; and a network, wherein the diagnosis execution unit includes processing modules of a sensor input processing, a preprocessing, a diagnosis processing, and a postprocessing, and a common interface that connects the processing modules, and wherein the arrangement unit arranges and executes the processing modules in the diagnosis target machine or the diagnosis server.

Abstract: Times in association with a portion of data designated by an input device from a graph indicating distribution of data of a certain item are divided into plural groups based on the respective time intervals, data relating to desired items included in time ranges respectively regulated by the plural groups are searched from a storage device, and time waveforms of data relating to the desired items are created for each of the groups based on the search results. With this configuration, around the time of generating a portion of data included in a set of data relating to a certain item, aspects of temporal changes of data of a certain item or other items can be easily recognized.

Abstract: The present invention includes four types of component diagrams, namely, an input/output data memory management component diagram, an input data value setup component diagram, a library execution component diagram, and an output data value acquisition component diagram, with respect to image processing library functions for a programming language and to an input/output data structure for the image processing library functions. The present invention also includes upper-level component diagrams, which are prepared by connecting the four types of component diagrams as lower-level component diagrams in the order of use, writes an algorithm by combining the lower- and upper-level component diagrams, and executes the written algorithm. From the written algorithm, the present invention generates a programming language source code for calling an image processing library.

Abstract: The present invention includes four types of component diagrams, namely, an input/output data memory management component diagram, an input data value setup component diagram, a library execution component diagram, and an output data value acquisition component diagram, with respect to image processing library functions for a programming language and to an input/output data structure for the image processing library functions. The present invention also includes upper-level component diagrams, which are prepared by connecting the four types of component diagrams as lower-level component diagrams in the order of use, writes an algorithm by combining the lower- and upper-level component diagrams, and executes the written algorithm. From the written algorithm, the present invention generates a programming language source code for calling an image processing library.

Abstract: A classifier learning image production program, method, and system are provided which are capable of efficiently acquiring learning images to be employed in development of a discrimination application, or more particularly, efficiently acquiring initial learning images to be employed in an early stage of development of a discrimination algorithm.

Abstract: Problem to be Solved: To cut down individual development and reduce a design load in image analysis functions with different objects and information to be recognized.

Abstract: The design support system regarding the present invention comprises a node data storage means that stores node data to generate functional models which present a group of function nodes which are functions divided from performance function of apparatus which is an objective to be designed and a group of part nodes which realize the functions in mutual relations, a functional model generating means that generates the functional models in reference to the node data storage means, a node designation receiving means that receives the designation of a node among the functional models, a node selection means that selects a node which has a mutual relation with nodes to which the designation are given, a display unit that displays the node selected by the node selection means.

Abstract: A classifier learning image production program, method, and system are provided which are capable of efficiently acquiring learning images to be employed in development of a discrimination application, or more particularly, efficiently acquiring initial learning images to be employed in an early stage of development of a discrimination algorithm.

Abstract: The design support system regarding the present invention comprises a node data storage means that stores node data to generate functional models which present a group of function nodes which are functions divided from performance function of apparatus which is an objective to be designed and a group of part nodes which realize the functions in mutual relations, a functional model generating means that generates the functional models in reference to the node data storage means, a node designation receiving means that receives the designation of a node among the functional models, a node selection means that selects a node which has a mutual relation with nodes to which the designation are given, a display unit that displays the node selected by the node selection means.

Abstract: The design support system regarding the present invention comprises a node data storage means that stores node data to generate functional models which present a group of function nodes which are functions divided from performance function of apparatus which is an objective to be designed and a group of part nodes which realize the functions in mutual relations, a functional model generating means that generates the functional models in reference to the node data storage means, a node designation receiving means that receives the designation of a node among the functional models, a node selection means that selects a node which has a mutual relation with nodes to which the designation are given, a display unit that displays the node selected by the node selection means.

Abstract: The information processing apparatus for project management comprises: a function of displaying on a screen a task area 12 where a symbol 123 representing a document relating to a task constituting a project is displayed; and a function of performing document work according to an operation instruction for the symbol 125 representing the document displayed in the task area 12. The task area 12 has a work area 121 which displays a symbol 123 representing the document, and an output area 122. When a symbol 126 representing a document is moved within the output area 122, the output area 122 displays a symbol representing the document in a task area of another associated task constituting the project.

Abstract: The information processing apparatus for project management comprises: a function of displaying on a screen a task area 12 where a symbol 123 representing a document relating to a task constituting a project is displayed; and a function of performing document work according to an operation instruction for the symbol 125 representing the document displayed in the task area 12. The task area 12 has a work area 121 which displays a symbol 123 representing the document, and an output area 122. When a symbol 126 representing a document is moved within the output area 122, the output area 122 displays a symbol representing the document in a task area of another associated task constituting the project.

Abstract: Simulation for evaluating approval/rejection of an action plan of the type in which work breakdown struction is changed by influences of external risk factors is achieved. A simulation apparatus includes a plan/risk input portion for accepting input of action plan data and risk scenario data, a plan/risk simulation portion for conducting simulation of an action plan by using the action plan data and the risk scenario data so accepted, and a plan evaluation output portion for evaluating a simulation result. The plan/risk simulation portion simulates occurrence of a risk phenomenon by using the risk scenario data, determines influence information given by the risk phenomenon to the action plan when the risk phenomenon is simulated as occurring and conducts simulation of the action plan by reflecting the influences of the risk scenario on the action plan by using the influence information so determined.

Abstract: The design support system regarding the present invention comprises a node data storage means that stores node data to generate functional models which present a group of function nodes which are functions divided from performance function of apparatus which is an objective to be designed and a group of part nodes which realize the functions in mutual relations, a functional model generating means that generates the functional models in reference to the node data storage means, a node designation receiving means that receives the designation of a node among the functional models, a node selection means that selects a node which has a mutual relation with nodes to which the designation are given, a display unit that displays the node selected by the node selection means.