Abstract: According to one embodiment, a failure prognosis device includes circuitry configured to determine whether a sign of failure exists in a head, based on a signal quality value and a floating quantity of the head, the signal quality value being based on an error between a reproducing signal acquired from the head when reading data stored on a storage surface of a disk and a predetermined target signal, and output a determination result.

Abstract: According to one embodiment, physical position information on errors on a recording medium is acquired, physical position relationship between the errors on the recording medium is calculated based on the position information, and a failure mode related to the errors is determined based on the position relationship.

Abstract: A server includes a distribution difference calculator and a determining unit. The distribution difference calculator calculates difference information between a first distribution of features calculated from operating data of terminal devices of a first machine type and a second distribution of features calculated from operating data of terminal devices of a second machine type. The determining unit determines whether a model is applicable to the terminal devices of the first machine type to predict occurrence possibility of a failure in each terminal device of the first machine type on basis of the difference information wherein the model is generated on basis of operating data of the terminal devices of the second machine type and is configured to predict occurrence possibility of a failure in each terminal device of the second machine type on basis of each of the features calculated from the operating data thereof.

Abstract: According to one embodiment, a failure prognosis device includes circuitry configured to determine whether a sign of failure exists in a head, based on a signal quality value and a floating quantity of the head, the signal quality value being based on an error between a reproducing signal acquired from the head when reading data stored on a storage surface of a disk and a predetermined target signal, and output a determination result.

Abstract: According to an embodiment of the present invention, a storage management apparatus to manage a plurality of storage combinations which are combinations of storages included in a storage group, includes a combination failure probability calculator and an allocation ratio calculator. The combination failure probability calculator calculates a failure probability of the storage combination based on a failure probability of each of the storages. The allocation ratio calculator calculates an allocation ratio of received data with respect to the storage combination based on the failure probability of the storage combination.

Abstract: According to one embodiment, there is provided a quality controlling device including: a predictor, a frequency calculator, and an implementing signal creator. The predictor employs a prediction model that associates an inspection result value of a first inspection with a predicted value being a value relating to a possibility of pass or failure in a second inspection and calculates the predicted value from an inspection result value that is obtained for an inspection target in the first inspection. The frequency calculator calculates, for the inspection target, an implementation frequency to implement the second inspection in accordance with the predicted value calculated by the predictor. The implementing signal creator creates a signal that indicates, for the inspection target, necessity of implementing the second inspection in accordance with the implementation frequency.

Abstract: A data preserving apparatus includes: a generator generating scenarios that represent presence or absence of occurrence of a failure, presence or absence of a failure symptom, a time point of occurrence of a failure, and a time point of occurrence of a failure symptom; an evaluator calculating the amount of data loss in the case of occurrence of a failure for the scenario based on first and second backup intervals before and after occurrence of a failure symptom; an backup interval evaluator calculating a number of backups performed until earlier one of a time point of occurrence of a failure and a time point after a predetermined time period; a cost evaluator calculating a cost evaluation values for the scenarios based on the amount of data loss and the number of backups; and a calculator calculating the first and second backup intervals based on cost evaluation values for scenarios.

Abstract: In a model parameter calculation device, the comparator compares a first evaluation value calculated from a first model and operating data on a terminal device with a second evaluation value calculated from a second model and the operating data. The requester transmits an inspection request to inspect the terminal device to the terminal device or a management device thereof in accordance with a comparative relation between the first evaluation value and the second evaluation value. The parameter determiner determines a third parameter included in a third model in accordance with a model reference of a predefined model type, on basis of an inspection result indicating an operating status of the terminal device and the operating data of the terminal device, wherein the third model associates the third parameter with a third output variable regarding the occurrence possibility of the failure in the terminal device.

Abstract: A server includes a distribution difference calculator and a determining unit. The distribution difference calculator calculates difference information between a first distribution of features calculated from operating data of terminal devices of a first machine type and a second distribution of features calculated from operating data of terminal devices of a second machine type. The determining unit determines whether a model is applicable to the terminal devices of the first machine type to predict occurrence possibility of a failure in each terminal device of the first machine type on basis of the difference information wherein the model is generated on basis of operating data of the terminal devices of the second machine type and is configured to predict occurrence possibility of a failure in each terminal device of the second machine type on basis of each of the features calculated from the operating data thereof.

Abstract: According to one embodiment, a measurement unit periodically measures a usage status of a measurement target, and measures each test item of the measurement target at an arbitrary timing according to a test schedule. A first storage unit stores the usage status and a test result in time series. A second storage unit stores statistic information representing a relationship between the usage status and the test result. A probability calculation unit calculates a first evaluation value representing a load of the measurement target at a recent timing and a second evaluation value representing a load of the measurement target at the arbitrary timing, based on the usage status, and calculates a specific probability of each test item, based on the statistic information, the first evaluation value and the second evaluation value. A test schedule creation unit creates a new test schedule having selected test items, based on the specific probability.

Abstract: There is provided an analysis apparatus including: a first storage to store operation data on an electronic device; a second storage to store a span characteristic concerning a time span in which each of values of a plurality of explanatory variables is changed; an explanatory variable calculator to calculate the explanatory variables based on the operation data; a failure state information calculator to calculate failure state information for the electronic device based on the explanatory variables calculated by the explanatory variable calculator, and calculate, when the failure state information represents a risky state, an overall span concerning in what time span the failure state information is possibly to represent a safe state due to changes in the values of the explanatory variables; and a diagnosis unit to diagnose the electronic device based on the failure state information and the overall span characteristic.

Abstract: A data preserving apparatus includes: a generator generating scenarios that represent presence or absence of occurrence of a failure, presence or absence of a failure symptom, a time point of occurrence of a failure, and a time point of occurrence of a failure symptom; an evaluator calculating the amount of data loss in the case of occurrence of a failure for the scenario based on first and second backup intervals before and after occurrence of a failure symptom; an backup interval evaluator calculating a number of backups performed until earlier one of a time point of occurrence of a failure and a time point after a predetermined time period; a cost evaluator calculating a cost evaluation values for the scenarios based on the amount of data loss and the number of backups; and a calculator calculating the first and second backup intervals based on cost evaluation values for scenarios.

Abstract: A user evaluation apparatus includes a parameter determination module which determines parameters of a user evaluation model required to calculate a degree of usage influence so as to maximize a target function. The target function may be defined using weight values, measurement data, and a failure information counting result. The apparatus also includes a user evaluation module which calculates and displays the degree of usage influence using the measurement data and the parameters of the user evaluation model.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.

Abstract: According to one embodiment, an evaluating apparatus includes an operation data storage unit, a labeling unit, a learning unit, and an evaluating unit. The labeling unit applies a failure label, indicating that a product is broken down, to operation data of the product that is broken down within a designated period of time from the observation date of the operation data, while applies a non-failure label, indicating that the product is not broken down, to the operation data of the product that is not broken down within a designated period of time from the observation date of the operation data. The labeling unit applies neither the failure label nor the non-failure label to the operation data of the product, which is not certain that it is broken down or not within a designated period of time from the observation date of the operation data.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.

Abstract: A medical image retrieval system includes an image database which stores medical images. An interpretation unit acquires a currently diagnosed image for use in performing interpretation of one of the medical images and provides the currently diagnosed image to a computer terminal. An image requesting unit issues an image request associated with the currently diagnosed image. An image retrieval unit retrieves a reference image from the image database in accordance with the image request and provides the reference image to the computer terminal in order to propose the reference image as references for diagnosis. An evaluation input unit prompts to input an evaluation indicating whether the reference image has been helpful for diagnosis based on the currently diagnosed image.

Abstract: A first module calculates a failure occurrence risk index of each data storage area address. A second module calculates a power saving index of each data storage area address. A third module calculates an access speed index per unit data volume necessary to access each data storage area address. A fourth module generates a distribution table that represents the failure occurrence risk index, the power saving index, and the access speed index for each candidate address, with respect to data to be distributed. A fifth module selects a candidate address in the distribution table such that the power saving index and the access speed index meet restricting conditions and the failure occurrence risk index is minimized, and distributes the data to the candidate address.

Abstract: There is provided an electronic apparatus system. The system includes: an electronic apparatus; and a server configured to receive usage information about usage status of the electronic apparatus. The server includes: a first database; a second database; a writer configured to store the usage information in the first database and to write a flag value into the second database, wherein the flag value indicates whether or not the usage information is transmitted from the electronic apparatus through a network; a generator configured to generate a first parameter for calculating a failure probability of the electronic apparatus, based on the usage information and repair information of the electronic apparatus, wherein the repair information is stored in the server in advance; and a transmitter configured to transmit the first parameter to the electronic apparatus.

Abstract: According to one embodiment, a first reading unit reads, from a defect database, first identification information corresponding to a first product type. A second reading unit reads, from a monitoring database, defect monitoring information corresponding to the first identification information and non-defect monitoring information that corresponds to the first product'type and that is other than the defect monitoring information. A generating unit generates a defect, model that models a probability of products becoming defective within a predetermined time period with respect to the monitoring information, based on the defect monitoring information and the non-defect monitoring information. A first calculating unit calculates a defect probability of products of a second product type by inputting the monitoring information corresponding to the second product type into the defect model. A second calculating unit calculates a defect rate of the products of the second product type based on the defect probability.