Abstract: According to one embodiment, an information processing apparatus includes an estimator configured to estimate a state of an observation target on a first time, based on data on the first time included in time-series data obtained from the observation target. Also, an information processing method for estimating a state of an observation target on a first time, based on data on the first time included in time-series data obtained from the observation target is provided.

Abstract: An information processing device is disclosed. In the information processing device, a derivation unit derives, for each of sensors, a constraint expression obtained by substituting an observation value for a term of an observation value variable in an error model. The observation value indicates the number of present objects observed by the sensors. The error model represents correspondence between: the number of present objects in an observation range represented by the observation value variable and an error term related to an assumed detection error range of the sensor, and the number of present objects in an observation range represented by a variable indicating the number of present objects in an observation unit space. A range calculation unit calculates a possible range of the number of present objects. A reliability calculation unit calculates reliability of an estimation value of the number of present objects for each of the areas.

Abstract: According to an embodiment, an information processing apparatus includes one or more hardware processors configured to calculate a prediction value of an amount of electric power consumed for a movement to be predicted, based on a prediction model in which the amount of electric power consumed by a moving object is an objective variable, one or more factor values that affect the amount of electric power consumed for the movement of the moving object to be predicted, and an error between the prediction value obtained by the prediction model and an actual measured value.

Abstract: According to one embodiment, information processing device includes a storage and a processing circuit. The storage is configured to store configuration data of a plurality of devices and error history data including a plurality of entries each with a type of error. The processing circuit is configured to: extract the entries with a specific type of error which are positive examples; extract the remaining entries which are negative examples; select a part of the negative examples with each type of error; generate learning data based on the positive examples, the selected negative examples and the configuration data at a time when the specific type of error occurred; and generate a diagnosis model for estimation of possibility the specific type of error occurs by using the learning data.

Abstract: According to an embodiment, an information processing device includes one or more processors. The one or more processors are configured to: build a prediction model for predicting prediction data for a second region included in a plurality of regions based on acquired data acquired for one or more first regions included in the plurality of regions; and predict the prediction data based on the acquired data by using the prediction model.

Abstract: An information processing apparatus according to one embodiment includes one or more hardware processors coupled to a memory. The hardware processors function as an acquisition unit, a model generation unit, and a model generation unit. The acquisition unit serves to acquire one or more patterns from among multiple patterns each representing temporal variation of first data being data to be predicted. The patterns are determined for a first region designated out of regions serving as prediction targets of the first data. The model generation unit serves to generate a prediction model for predicting the temporal variation of the first data in the first region. The prediction model is generated on the basis of the acquired patterns. The model generation unit serves to determine a parameter of the prediction model.

Abstract: According to one embodiment, a genotype estimation device includes: an acquirer configured to acquire a clustering strength of genotype data of a plurality of specimens including an unknown specimen whose genotype is not known and known specimens whose genotypes are known; and an estimator configured to estimate the genotype of the unknown specimen on the basis of the genotype data in response to the clustering strength being larger than a first threshold, and output an estimation result.

Abstract: According to one embodiment, a sensor design support apparatus includes: an inter-data feature calculator and a model constructor. The inter-data feature calculator combines any two pieces of data based on first to k-th data acquired from each of a plurality of sensors in response to first to k-th conditions being satisfied to generate a plurality of data pairs for each of sensors, the sensors monitoring a target; and calculates a plurality of inter-data features based on the plurality of data pairs. The model constructor calculates a plurality of coefficients corresponding to the plurality of inter-data features in a classification model based on state data indicating states of the monitoring target at times which the first to k-th conditions are satisfied, wherein the classification model associates the plurality of coefficients and the plurality of inter-data features with a value identifying a state of the monitoring target.

Abstract: According to one embodiment, an information processing apparatus includes: a difference calculator configured to calculate, based on a plurality of data items each including an objective variable and at least one explanatory variable, a plurality of differences between the objective variable and prediction values of the objective variable predicted from the explanatory variable; a candidate generator configured to generate at least one division condition candidate which divides the explanatory variable into a plurality of sections; and a division condition selector configured to select a first division condition from the at least one division condition candidate, based on the differences calculated by the difference calculator.

Abstract: According to one embodiment, a sensor control support apparatus includes: a sensor selector configured to, based on measurement data of a plurality of sensors for at least one monitoring target and state data indicating an state of the at least one monitoring target, select a sensor to be used for state prediction of the monitoring target from among the plurality of sensors; and a sensor controller configured to control the plurality of sensors based on a selection result of the sensor selector.

Abstract: According to one embodiment, an information processing apparatus includes an estimator configured to estimate a state of an observation target on a first time, based on data on the first time included in time-series data obtained from the observation target. Also, an information processing method for estimating a state of an observation target on a first time, based on data on the first time included in time-series data obtained from the observation target is provided.

Abstract: According to one embodiment, information processing device includes a storage and a processing circuit. The storage is configured to store configuration data of a plurality of devices and error history data including a plurality of entries each with a type of error. The processing circuit is configured to: extract the entries with a specific type of error which are positive examples; extract the remaining entries which are negative examples; select a part of the negative examples with each type of error; generate learning data based on the positive examples, the selected negative examples and the configuration data at a time when the specific type of error occurred; and generate a diagnosis model for estimation of possibility the specific type of error occurs by using the learning data.

Abstract: According to one embodiment, a route estimation apparatus includes an information communicator and a route estimator. The information communicator is configured to acquire position history information of a mobile body from an information apparatus via a communication network. The route estimator is configured to estimate a movement route used by the mobile body to move from a first position to a second position, using the position history information and route information indicating routes among a plurality of positions and characteristics of the routes.

Abstract: According to one embodiment, a sensor control support apparatus includes: a sensor selector configured to, based on measurement data of a plurality of sensors for at least one monitoring target and state data indicating an state of the at least one monitoring target, select a sensor to be used for state prediction of the monitoring target from among the plurality of sensors; and a sensor controller configured to control the plurality of sensors based on a selection result of the sensor selector.

Abstract: According to one embodiment, a sensor design support apparatus includes: an inter-data feature calculator and a model constructor. The inter-data feature calculator combines any two pieces of data based on first to k-th data acquired from each of a plurality of sensors in response to first to k-th conditions being satisfied to generate a plurality of data pairs for each of sensors, the sensors monitoring a target; and calculates a plurality of inter-data features based on the plurality of data pairs. The model constructor calculates a plurality of coefficients corresponding to the plurality of inter-data features in a classification model based on state data indicating states of the monitoring target at times which the first to k-th conditions are satisfied, wherein the classification model associates the plurality of coefficients and the plurality of inter-data features with a value identifying a state of the monitoring target.

Abstract: According to one embodiment, a genotype estimation device includes: an acquirer configured to acquire a clustering strength of genotype data of a plurality of specimens including an unknown specimen whose genotype is not known and known specimens whose genotypes are known; and an estimator configured to estimate the genotype of the unknown specimen on the basis of the genotype data in response to the clustering strength being larger than a first threshold, and output an estimation result.

Abstract: A genotyping device includes a representative value calculator, a first labeler, a model creator, a second labeler. The representative value calculator calculates a representative value for each of one or more clusters with respect to each of a plurality of SNPs. The representative value being calculated based on signal intensities of specimens included in each of the clusters. The first labeler assigns genotypes to clusters of an SNP pertaining to three clusters among the SNPs on basis of the representative values of the clusters. The model creator creates a model indicative of a relationship between the genotypes of the clusters of the SNP pertaining to the three clusters among the SNPs and the representative values of the clusters. The second labeler assigns genotypes to clusters of an SNP pertaining to one or two clusters among the SNPs on basis of the representative values of the clusters and the model.