Abstract: A catalyst for purification of exhaust gas in which Pd-based nanoparticles and ceria nanoparticles are supported on a composite metal oxide support containing alumina, ceria, and zirconia, wherein a molar ratio (Ce/Pd) of Ce and Pd supported on the support is 1 to 8, a proximity ? between Pd and Ce is 0.15 to 0.50, wherein the proximity ? is determined, based on Pd and Ce distribution maps in an element mapping image of energy dispersive X-ray analysis, by the following formula (1): ? = ? j = 0 N - 1 ? ? i = 0 M - 1 ? ( ( I ? ( i , j ) - I ave ) ? ( T ? ( i , j ) - T ave ) ) ? j = 0 N - 1 ? ? i = 0 M - 1 ? ( I ? ( i , j ) - I ave ) 2 - ? j = 0 N - 1 ? ? i = 0 M - 1 ? ( T ? ( i , j ) - T ave ) 2 , ( 1 ) a Pd dispersity after a heat-resistance test at 1050° C. for 25 hours is 0.8% or more.

Abstract: A learning apparatus includes: a learning unit that learns a first parameter and a second parameter that are included in a mapping model for mapping, to a region set based on a subspace set in advance and a distance from the subspace, a feature vector generated based on normal data input as training data, the first parameter being for generating the feature vector and the second parameter being for adjusting the distance.

Abstract: A time series data processing apparatus according to the present invention includes an extracting unit configured to extract, from normal period time series data that is time series data of a period during which a measurement target is determined to be in a normal state of time series data including a plurality of parameters based on data measured from the measurement target, a combination of the plurality of parameters in which a value of another parameter with respect to a value of a predetermined parameter is maximum among combinations of the plurality of parameters, as a normal period maximum value.

Abstract: In order to accurately estimate the behavior suitable for transforming a customer into a good customer, an estimation system 100 is configured to comprise: an acquisition unit 101; an estimation unit 102; and an output unit 103. The acquisition unit 101 acquires purchase data including at least one among the purchase product, the total purchase amount, and the visit frequency of a target customer. The estimation unit 102 estimates a purchasing behavior for transforming the target customer into a good customer, on the basis of the purchase data acquired by the acquisition unit 101, by using an estimation model generated on the basis of the purchase data on a plurality of customers and the conditions of good customers. The output unit 103 outputs the purchasing behavior estimated by the estimation unit 102.

Abstract: A plurality of event types associated with a plurality of events which emerge in the future with high emergence probability is selected by use of event series representing at least multiple types of events output from a target system in the past time interval and output times of events and a selection model configured to select event types to emerge in the future with high emergence probability among multiple types of events included in the event series. An order of the selected events to emerge in the future and time intervals therebetween are predicted by use of the selected event types and a series prediction model configured to estimate the order of the selected events to emerge in the future and the time intervals therebetween.

Abstract: The information processing device includes a matching unit 32A and a display control unit 33A. The matching unit 32A is configured to match a database 21A, which associates first detection data indicative of a past state of maintenance target equipment 3 with first maintenance information relating to maintenance of the maintenance target equipment 3 in the past state, with second detection data indicative of a current state of the maintenance target equipment 3. The display control unit 33A is configured to display, based on a result of the matching by the matching unit 32A, second maintenance information relating to maintenance in accordance with the current state of the maintenance target equipment 3 on a display unit 45A.

Abstract: A monitoring method, to be performed by a monitoring device that performs analysis of time-series data, includes calculating statistical information corresponding to a comparison result between time-series data of a search object and past time-series data, and outputting the calculated statistical information.

Abstract: A time series data processing apparatus according to the present invention includes an extracting unit configured to extract, from normal period time series data that is time series data of a period during which a measurement target is determined to be in a normal state of time series data including a plurality of parameters based on data measured from the measurement target, a combination of the plurality of parameters in which a value of another parameter with respect to a value of a predetermined parameter is maximum among combinations of the plurality of parameters, as a normal period maximum value.

Abstract: A fraud detection device 80 for detecting a fraudulent transaction in an operation of a financial institution includes a target data extraction unit 81 which extracts target data by excluding normal transaction data from the transaction data in the operation by unsupervised learning, a first learning unit 82 which learns a first hierarchical mixed model using training data, among the target data, which takes positive examples for the data indicating the fraudulent transaction and takes negative examples for the remaining data other than the positive examples, and a data exclusion unit 83 which excludes, from the target data, the target data which is set as negative example training data and is classified as a negative example by the first hierarchical mixed model.

Abstract: An information processing apparatus, a data generation method, and a program capable of obtaining useful information about a person from video data are provided. An information processing apparatus (1) according to an example embodiment includes a base-information acquisition unit (2) that acquires a plurality of types of pieces of base information based on video data in which at least one person is shown, the pieces of base information being pieces of information used to monitor a person, and a base-information integration unit (3) that generates integrated information by integrating, among the plurality of pieces of base information, those that satisfy a predetermined relation as information of one and the same person.

Abstract: An information processing apparatus, a data generation method, and a program capable of obtaining useful information about a person from video data are provided. An information processing apparatus (1) according to an example embodiment includes a base-information acquisition unit (2) that acquires a plurality of types of pieces of base information based on video data in which at least one person is shown, the pieces of base information being pieces of information used to monitor a person, and a base-information integration unit (3) that generates integrated information by integrating, among the plurality of pieces of base information, those that satisfy a predetermined relation as information of one and the same person.

Abstract: In an invariant relation analysis, a capability to detect abnormalities is improved and erroneous abnormality reports are reduced. A system analysis device (100) includes a correlation model generation unit (130) and a learning reliability calculation unit (140). The correlation model generation unit (130) generates, based on time series of a plurality of metrics in a system in a learning period, a correlation model that includes a correlation between metrics. The learning reliability calculation unit (140) calculates learning reliability of the correlation, based on a behavior of a time series of each of metrics relevant to the correlation included in the correlation model, in the learning period.

Abstract: This invention provides a monitoring device and the like which exhibit high capability of detecting a state related to a system even when the system allows a plurality of objects to be monitored to complexly cooperate with each other. A monitoring device 1 includes a first model generation unit which divides, of first time-series information related to an object to be monitored, second time-series information associated with each item and generates models related to the pieces of divided information, and a determination unit which by applies third time-series information to the models to determine whether a correlation is maintained and performs determination related to each item based on results of the determining.

Abstract: A system analysis device 100 includes a whole model generation unit 1021 which generates a whole model which is obtained by modeling elements or whole of a system and which includes a plurality of partial models, a core model generation unit 1023 which extracts, from a plurality of whole models generated on the basis of the same event, the partial models whose prediction precision satisfies a predetermined criteria, and generates a core model by integrating the extracted partial models, and a threshold setting unit 1024 which calculates a distance between the core model and the plurality of whole models using a predetermined definition, and outputs the distance as a threshold value for error determination using the core model.

Abstract: In an invariant relation analysis, a capability to detect abnormalities is improved and erroneous abnormality reports are reduced. A system analysis device (100) includes a correlation model generation unit (130) and a learning reliability calculation unit (140). The correlation model generation unit (130) generates, based on time series of a plurality of metrics in a system in a learning period, a correlation model that includes a correlation between metrics. The learning reliability calculation unit (140) calculates learning reliability of the correlation, based on a behavior of a time series of each of metrics relevant to the correlation included in the correlation model, in the learning period.

Abstract: An assessment device (1) includes: a request acquirer (11) that accepts an evaluation target from a user terminal (7); a model acquirer (13) and a data acquirer (14) that select a main model for evaluating the evaluation target accepted by the request acquirer (11) from a plurality of models and select supplemental data to be supplemented for using the main model (data to be input into the main model, a sub-model, or data to be input into the sub-model) when the data to be input into the main model is insufficient; an executor (15) that evaluates the evaluation target based on the main model and supplemental data selected by the model acquirer (13) and the data acquirer (14); and a transmitter (16) that provides a result of the evaluation by the executor (15) to the outside.

Abstract: A steel sheet, including: as chemical components, by mass %, 0.05% to 0.35% of C; 0.05% to 2.0% of Si; 0.8% to 3.0% of Mn; 0.01% to 2.0% of Al; equal to or less than 0.1% of P; equal to or less than 0.05% of S; equal to or less than 0.01% of N; and the balance including iron and inevitable impurities, wherein the steel sheet comprises 50% or more of a ferrite phase, a bainite phase, and a tempered martensite phase, 3% or more of a retained austenite phase, and 50% or more of the crystal grains of the retained austenite phase satisfy Expression 1, wherein a carbon concentration at a position of center of gravity is Cgc and a carbon concentration at a grain boundary is Cgb.

Abstract: In the inter-element influence determination apparatus, a receiver receives request information from a user terminal. A system information storage device stores system information containing attribute information indicating attributes of each element in a system. A relationship information storage device stores relationship information indicating relationships in which direct interaction is provided between elements. On the basis of the attribute information and the relationship information, an influence determiner virtually connects each element included in the system, thereby creating a system network model which models the system, and on the basis of the system network model, determines whether a second element is influenced when a change is made to a first element. A transmitter transmits to the user terminal determination result information indicating the result of the determination by the influence determiner.

Abstract: A system analysis device 100 includes a whole model generation unit 1021 which generates a whole model which is obtained by modeling elements or whole of a system and which includes a plurality of partial models, a core model generation unit 1023 which extracts, from a plurality of whole models generated on the basis of the same event, the partial models whose prediction precision satisfies a predetermined criteria, and generates a core model by integrating the extracted partial models, and a threshold setting unit 1024 which calculates a distance between the core model and the plurality of whole models using a predetermined definition, and outputs the distance as a threshold value for error determination using the core model.

Abstract: The invention provides a cold-rolled steel sheet excellent in paint bake hardenability and ordinary-temperature non-aging property comprising, in mass %, C: 0.0005-0.0040%, Si: 0.8% or less, Mn: 2.2% or less, S: 0.0005-0.009%, Cr: 0.4-1.3%, O: 0.003-0.020%, P: 0.045-0.12%, B: 0.0002-0.0010%, Al: 0.008% or less, N: 0.001-0.007%, and a balance of Fe and unavoidable impurities. Ultra-low-carbon steel retaining solute N and containing added Cr, P, B and O is used to produce hot-rolled and cold-rolled steel sheet and hot-dip galvanized cold-rolled steel sheet that exhibit both high paint bake hardenability and ordinary-temperature non-aging property.