Abstract: A disease development risk prediction system 10 includes: a data generation means 11 which generates combination data by combining at least two different types of receipt data using a combination key, wherein the receipt data includes an insured person number for an insured person which was converted using a predetermined method, a birth date or birth year and month which are both age-identifiable items, and gender, and the combination key combines the converted insured person number, age-identifiable items, and gender; and a model generation means 12 which uses the generated combination data to generate a prediction model predicting a risk of the insured person of developing a predetermined disease.

Abstract: The health condition prediction apparatus 10 includes an estimation model learning unit 11 for learning a model indicating a relationship between lifestyle and a check value for a preset check item, using actual data regarding individuals' lifestyle and the check value as training data, a check value prediction unit 12 for acquiring actual data regarding lifestyle of a user and predicting a future check value of the user by using the acquired actual data and the model, and a display unit 13 for displaying, on a screen, the future check value predicted by the check value prediction unit 12.

Abstract: A disease development risk prediction system 10 includes: a data generation means 11 which generates combination data by combining at least two different types of receipt data using a combination key, wherein the receipt data includes an insured person number for an insured person which was converted using a predetermined method, a birth date or birth year and month which are both age-identifiable items, and gender, and the combination key combines the converted insured person number, age-identifiable items, and gender; and a model generation means 12 which uses the generated combination data to generate a prediction model predicting a risk of the insured person of developing a predetermined disease.

Abstract: The purpose of the present invention is to estimate response information with which it is possible to quickly relieve problems caused by agitation, the state of the patient, etc. A biological information processing system comprises: a determination unit that, on the basis of the features of biological information of a subject patient to be entered, determines discrimination information indicating whether the condition of the patient has changed in comparison with a normal state, and an estimation unit that estimates countermeasure information oriented for the patient on the basis of the discrimination information and countermeasure prediction parameters learned in advance.

Abstract: A pulsed discharge device according to an exemplary aspect of the present invention includes a controller configured to determine an interruption time to a discharge time based on a predetermined time ratio between the discharge time and the interruption time when performing a pulsed discharge to repeat alternately a discharge and a pause in discharging of a chemical battery.

Abstract: A data analysis device includes: a data acquiring unit that acquires a designation of a target field being a field from which relevance is to be extracted, from among fields included in health condition data being information relating to a health condition of an employee, and the health condition data of two or more employees and attendance data being information relating to a work condition; an attribute data generating unit that performs aggregation, and generates attribute data; a model learning unit that learns a model, the model being represented by a polynomial, by using a content of the target field of the health condition data, and a content of the attribute data, of the two or more employees; a related field extracting unit that extracts an attribute field; and a summarizing unit that summarizes and outputs attendance data, based on information on the extracted attribute field.

Abstract: A pulsed discharge device according to an exemplary aspect of the present invention includes a controller configured to determine an interruption time to a discharge time based on a predetermined time ratio between the discharge time and the interruption time when performing a pulsed discharge to repeat alternately a discharge and a pause in discharging of a chemical battery.

Abstract: A lithium ion secondary battery system allowing a high power efficiency and large effective capacity is provided. The system includes an external power source for charging a lithium ion secondary battery, and a controller for switching output modes including a continuous discharge mode, in which electric power is continuously supplied from the lithium ion secondary battery to the load, and a pulsed charge and discharge mode, in which pulsed electric power is supplied from the lithium ion secondary battery to the load, and pulsed electric power is supplied from the external power source to charge the lithium ion secondary battery during a low-level pulsed discharge period(s), which are periods during which electric power is not supplied to the load, wherein the controller switches the output modes to the pulsed charge and discharge mode when the lithium ion secondary battery has a voltage lower than a predetermined upper switching voltage.

Abstract: A molecular structure prediction method for predicting the most stable molecular structure of a molecule based on results obtained by a plurality of appraisal systems includes steps of: generating a plurality of data sets by re-sampling from a training data set, determining a parameter set for each data set that has been generated to obtain a plurality of parameter sets, using the plurality of parameter sets to calculate energy of a molecule for molecular data for prediction, taking a consensus based on the results of a plurality of energies or three-dimensional structures, and predicting the most stable molecular structure based on the results of consensus.

Abstract: The present invention provides a system, method, and program for evaluating the performance of an intermolecular interaction predicting apparatus. A performance evaluation system evaluates the performance of an intermolecular interaction predicting apparatus using a correlation between structure factors and physicochemical parameters of classification model construction compounds with high and low scores calculated by the intermolecular interaction predicting apparatus.

Abstract: A molecular structure prediction method for predicting the most stable molecular structure of a molecule based on results obtained by a plurality of appraisal systems includes steps of: generating a plurality of data sets by re-sampling from a training data set, determining a parameter set for each data set that has been generated to obtain a plurality of parameter sets, using the plurality of parameter sets to calculate energy of a molecule for molecular data for prediction, taking a consensus based on the results of a plurality of energies or three-dimensional structures, and predicting the most stable molecular structure based on the results of consensus.

Abstract: In molecular simulation including the step of calculating non-bonding interactions in a system having particles with electric charges, using a multigrid method, upon determining the electric charges at grid points in a coarser grid of a higher level that is one step higher than the level to be observed, when a pair of grid points in the observed level, or a pair of particles in the observed level, both coincide with the grid points of the grid of the higher level, the charges at the grid points of the higher level are determined so that the energy of the pair in the higher level becomes equal to the correct energy value in the observed level.