Abstract: A diagnosis device (10) includes an acquirer (101) and a diagnoser (140). The acquirer (101) acquires a series of input values as an input signal to be diagnosed as to presence or absence of abnormality. The diagnoser (140) diagnoses the presence or absence of the abnormality from (i) a first index value indicating a distance between an input vector and a predetermined first reference vector, the input vector having components that are the input values of the series acquired by the acquirer (101), and (ii) a second index value indicating an angle between the input vector and a predetermined second reference vector.

Abstract: An image processing device includes a template analyzer to transform a pattern included in a template into multiple transformed patterns and generate multiple extended templates consisting of the template and multiple transformed templates including the respective transformed patterns. Further, there is a search processor to perform a first search that searches a to-be-searched image by using multiple first extended templates selected from the multiple extended templates, and perform a second search that searches the to-be-searched image by using multiple second extended templates selected from the multiple extended templates on a basis of a result of the first search. The first search is performed by using the template and two or more transformed templates selected at coarse boundaries from the multiple extended templates, and the second search is performed by using two or more extended templates near one of the extended templates that has been detected in the first search.

Abstract: A plurality of clients including a platform (200) and at least one client (100) communicate with each other in accordance with a publish-subscribe model. A topic common key manager (260) of the platform (200) provides, to the client (100), a topic common key associated with a topic and being for encryption and decryption of a message directed to the topic. A message manager (270) transmits the message encrypted with the topic common key associated with the topic, and decrypts a received message with the topic common key associated with the topic. A topic common key storage (150) of the client (100) stores the topic common key provided from the platform (200) in association with identification information of the topic. A message manager (170) transmits the message encrypted with the topic common key, and decrypts a received message with the topic common key.

Abstract: A machine tool machining dimensions prediction device (100) includes: a data collector (10) to acquire driving state information of a machine tool; a feature amount extractor (211) to extract a feature amount from the driving state information; a data analyzer (311) to analyze the extracted feature amount; and a machining quality prediction model generator (312) to generate, from the analyzed information, a prediction model of a machining dimension of a workpiece. The machine tool machining dimensions prediction device (100) applies the feature amount and the driving state information to the prediction model during machining of the workpiece to predict a machining quality and refers to a machining dimension quality regulation to determine whether the machining quality satisfies a standard.

Abstract: A data processing apparatus (10) includes multiple data processors (300) that each perform a set subprocess of multiple sequential subprocesses included in a process sequence and a data distributor (210) that mediates data exchange between the multiple data processors (300) in accordance with a publish-subscribe model. An ID checker (330) determines, based on identification information assigned to received data received from the data distributor (210), whether received data is to be processed in the subprocess set to be performed by the data processor (300). A data processing executor (340) performs the set subprocess when the ID checker (330) determines that the received data is to be processed in the set subprocess. A data converter (310) assigns new identification information to data resulting from the set subprocess performed by the data processing executor (340) and transmits the data assigned with the new identification information to the data distributor (210).

Abstract: A diagnostic device (10) includes an acquirer (101) and a diagnoser (140). The acquirer (101) acquires a plurality of input signals including a target signal to be diagnosed for abnormality. The diagnoser (140) diagnoses, using a first index value relating to the target signal and a second index value relating to the plurality of input signals based on a correlation between the plurality of input signals, whether an abnormality occurs. The first index value indicates a degree of similarity of a waveform of the target signal to a predetermined reference waveform. The second index value is a value that is based on comparison between the target signal and a predetermined pattern and is calculated from values of the plurality of input signals.

Abstract: A development support device includes a document analyzing unit (130) that analyzes a described matter in development documents created in a development process and specifies functions described in the development documents; a component analyzing unit (140) that specifies a model corresponding to the specified functions and uses the analysis results of the described matter to generate multiple components conforming to a standardized format with respect to the specified model; and a model generating unit (150) that generates the specified model by incorporating components selected from the multiple components in accordance with the standardized format.

Abstract: Provided is a data amount sufficiency determination device capable of determining the sufficiency of the data amount of learning data with higher accuracy. A data amount sufficiency determination device according to the present disclosure includes a time series data acquisition unit to acquire time series data, a data division unit to divide the time series data into a plurality of pieces of substring data, a data set generation unit to generate a plurality of substring data sets that are sets of substring data, a feature amount calculation unit to calculate a feature amount of the substring data, a probability distribution generation unit to generate probability distribution of the feature amount for each substring data sets, and a determination unit to determine whether or not the probability distribution has converged.

Abstract: A data processing apparatus includes a first processing unit that executes real-time processing with respect to data, a second processing unit that executes batch processing with respect to data that is output from the first processing unit as a result of processing by the first processing unit, and a monitor that monitors a status of the processing by the first processing unit and a status of processing by the second processing unit. The first processing unit includes a plurality of subprocessing units and buffers, and the second processing unit also includes a plurality of subprocessing units and buffers. The second processing unit includes a storage. The monitor includes a first monitor that monitors, for each of the buffers included in the first processing unit, an amount of the data stored in the corresponding buffer and a second monitor that monitors a total amount of the data stored in the buffers included in the second processing unit and the data stored in the storage.

Abstract: A data processing device (10), which is connectable to another data processing device (20), includes a data collector (150) to collect data from a machine (31, 32), a data processor (120) to process input data, a coordination processor (160) to provide the data collector (150) or the data processor (120) with data transmitted from the another data processing device (20) and provide the another data processing device (20) with the data collected by the data collector (150) or the data processed by the data processor (120), and an execution controller (130) to control collection of data by the data collector (150), processing of data by the data processor (120), and transmission and reception of data to and from the another data processing device (20) by the coordination processor (160) in accordance with predetermined setting information for a data processing flow.

Abstract: An identification value generator included in a data processing apparatus generates, from data pieces collected from an FA device, at least one identity identification value. The identity identification value is a value for determining an identity of the data pieces. The update determiner determines whether current data and previous data are identical based on a current identification value and a previous identification value. The current data includes the data pieces currently collected, and the previous data includes the data pieces previously collected. The current identification value includes the identity identification value generated from the current data, and the previous identification value includes the identity identification value generated from the previous data. A data distribution controller distributes the current data to a data processor when the update determiner determines that the current data and the previous data are not identical.

Abstract: A receiver (131) receives an acquisition request to acquire a value of real resource information associated with a device (20) connected to a network or a value of virtual resource information associated with a calculation result of calculation performed using a value of the real resource information. A real resource information acquirer (1352) acquires the value of the real resource information by causing a collector (140) to collect a value from the device (20) associated with the real resource information. A virtual resource information acquirer (1353) acquires the value of the virtual resource information by causing a calculator (1354) to perform calculation using the value of the real resource information. A responder (136) returns a response including the value of the real resource information or a response including the value of the virtual resource information based on the received acquisition request.

Abstract: A data processing apparatus (10) includes multiple data processors (300) that each perform a set subprocess of multiple sequential subprocesses included in a process sequence and a data distributor (210) that mediates data exchange between the multiple data processors (300) in accordance with a publish-subscribe model. An ID checker (330) determines, based on identification information assigned to received data received from the data distributor (210), whether received data is to be processed in the subprocess set to be performed by the data processor (300). A data processing executor (340) performs the set subprocess when the ID checker (330) determines that the received data is to be processed in the set subprocess. A data converter (310) assigns new identification information to data resulting from the set subprocess performed by the data processing executor (340) and transmits the data assigned with the new identification information to the data distributor (210).

Abstract: A plurality of clients including a platform (200) and at least one client (100) communicate with each other in accordance with a publish-subscribe model. A topic common key manager (260) of the platform (200) provides, to the client (100), a topic common key associated with a topic and being for encryption and decryption of a message directed to the topic. A message manager (270) transmits the message encrypted with the topic common key associated with the topic, and decrypts a received message with the topic common key associated with the topic. A topic common key storage (150) of the client (100) stores the topic common key provided from the platform (200) in association with identification information of the topic. A message manager (170) transmits the message encrypted with the topic common key, and decrypts a received message with the topic common key.

Abstract: An abnormal portion detecting device (10) includes a determiner (101) to determine whether received data contains any abnormality, a diagnostic target data transmitter (102) to transmit diagnostic target data to the determiner (101), a modification target portion determiner (103) to determine a modification target portion in the diagnostic target data determined to contain an abnormality by the determiner (101), a modifier (104) to modify the modification target portion in the diagnostic target data and generate modified data, a modified data transmitter (105) to transmit the modified data to the determiner (101), and an abnormal portion detector (106) to detect the modification target portion determined by the modification target portion determiner (103) as an abnormal portion in the diagnostic target data when the determiner (101) determines that the modified data contains no abnormality.

Abstract: A signal selection device (10) selects, from a plurality of candidate signals, a training signal for learning a model (20) usable for data analysis. The signal selection device (10) includes a first acquirer (11) that acquires the plurality of candidate signals and training labels associated with the plurality of candidate signals and being status values corresponding to results of analysis performed using the model, a feature calculator (13) that calculates one or more features for each of the plurality of candidate signals, and a selector (16) that selects the training signal from the plurality of candidate signals based on a degree of relevance between the one or more features and the training labels.

Abstract: A data management device (10) includes an insertion position determiner (121) to determine an insertion position of dummy data to be inserted into transmission target data, a dummy data inserter (122) to insert the dummy data in the insertion position of the transmission target data to create dummy-inserted data, an insertion position encryptor (123) to encrypt data indicating the insertion position with a public key (PUBa) to create insertion-position-encrypted data; and a deliverer (110) to deliver the dummy-inserted data and the insertion-position-encrypted data.

Abstract: A data analysis device (1) according to the present disclosure includes a data collector (131) and a data organizer (135). The data collector (131) collects an input signal that is input from an apparatus connected to the data analysis device (1). The data organizer (135) removes, from among waveforms included in the input signal collected by the data collector (131), a waveform that has an appearance frequency lower than a reference frequency. The data organizer (135) generates learning data by collecting, from among the waveforms included in the input signal, waveforms that have an appearance frequency higher than the reference frequency.

Abstract: A data processing apparatus (10) includes a receiver (120), a storage (141), a determiner (142), and a flow controller (143). The receiver (120) receives a setting for data processing to be executed with respect to data. The storage (141) stores setting information indicating the setting received by the receiver (120). The determiner (142) determines whether a first validity is present for the setting information and whether a second validity relating to a processing unit (130) for execution of the data processing is present. The flow controller (143) transmits data to the processing unit (130) and a collection processing unit (160) when the determiner (142) determines that the first validity is present and the second validity is present, thereby causing the processing unit (130) and the collection processing unit (160) to execute the data processing.

Abstract: An identification value generator included in a data processing apparatus generates, from data pieces collected from an FA device, at least one identity identification value. The identity identification value is a value for determining an identity of the data pieces. The update determiner determines whether current data and previous data are identical based on a current identification value and a previous identification value. The current data includes the data pieces currently collected, and the previous data includes the data pieces previously collected. The current identification value includes the identity identification value generated from the current data, and the previous identification value includes the identity identification value generated from the previous data. A data distribution controller distributes the current data to a data processor when the update determiner determines that the current data and the previous data are not identical.