Abstract: The purpose of the present invention is to provide a suitable user-friendliness to a user regarding a recommendation of application software on a portable information terminal. In order to accomplish the purpose, this portable information terminal is configured to set an application as a recommendation candidate when the status of the portable information terminal matches a condition corresponding to the application, and recommend the application when the application further matches a pre-set recommendation permitting condition. Hence, the portable information terminal and the application recommending method thereof capable of providing a preferable user-friendliness to the user can be provided.

Abstract: A method for determining a class to which an input image belongs in an inference process, includes: storing a frequent feature for each class in a frequent feature database; inputting an image as the input image; extracting which class the input image belongs to; extracting a plurality of features that appear in the inference process; extracting one of the features that satisfies a predetermined condition as a representative feature; reading out the frequent feature corresponding to an extracted class from the frequent feature database; extracting one or a plurality of ground features based on the frequent feature and the representative feature; storing a concept data representing each feature in an annotation database; reading out the concept data corresponding to the one or the plurality of ground features from the annotation database; generating explanation information; and outputting the ground feature and the explanatory information together with the extracted class.

Abstract: At least one device is configured to perform a predetermined process associated with a vehicle using data; and send, to a server system, the data used by the predetermined process as learning data. The server system is configured to obtain the learning data sent from the at least one device, and perform a learning process on at least a factor defining the predetermined process using the obtained learning data to generate update data for updating at least the factor defining the predetermined process. The server system is configured to send the update data to the at least one device. The at least one device is further configured to update at least the factor defining the predetermined process based on the update data sent from the server system.

Abstract: In a method or a device for learning of a neural network, a mathematical expression is calculated, represents an output with respect to an input in each layer of a neural network, and is expressed by F(X)=K(WTX) when the output is defined as F, the input is defined as X, nonlinear conversion is defined as K, and a parameter matrix is defined as W. Multiple eigenvalues of a matrix obtained by inputting the parameter matrix to the input of the mathematical expression and squaring the matrix are calculated as multiple square eigenvalues.

Abstract: A method for determining a class to which an input image belongs in an inference process, includes: storing a frequent feature for each class in a frequent feature database; inputting an image as the input image; extracting which class the input image belongs to; extracting a plurality of features that appear in the inference process; extracting one of the features that satisfies a predetermined condition as a representative feature; reading out the frequent feature corresponding to an extracted class from the frequent feature database; extracting one or a plurality of ground features based on the frequent feature and the representative feature; storing a concept data representing each feature in an annotation database; reading out the concept data corresponding to the one or the plurality of ground features from the annotation database; generating explanation information; and outputting the ground feature and the explanatory information together with the extracted class.

Abstract: The disclosure includes a system, method and tangible memory for providing application assurance for an open platform in-vehicle infotainment system. The system includes an open platform in-vehicle infotainment system including a tangible memory, a processor and an untrusted application including a monitor module. The untrusted application is stored in the tangible memory. The monitor module included in the untrusted application is generated based on a set of one or more runtime rules describing desired behavior of the untrusted application that complies with a specification for an application programming interface of the open platform in-vehicle infotainment system. The untrusted application runs on the open platform in-vehicle infotainment system.

Abstract: At least one device is configured to perform a predetermined process associated with a vehicle using data; and send, to a server system, the data used by the predetermined process as learning data. The server system is configured to obtain the learning data sent from the at least one device, and perform a learning process on at least a factor defining the predetermined process using the obtained learning data to generate update data for updating at least the factor defining the predetermined process. The server system is configured to send the update data to the at least one device. The at least one device is further configured to update at least the factor defining the predetermined process based on the update data sent from the server system.

Abstract: Whether or not an integration test between or among software components is necessary is judged. Corresponding information between features is acquired, which configures a feature model expressing characteristics of a group of products produced by the software product line, and a type and variations of each software component. For each software component, a set of state variables of all of the features corresponding to the software components is produced based on the corresponding information. For each software component, a specific logical formula is produced. Two or more software components are designated. A necessity judgment formula is produced by logical-product combining all the specific judgment formulas, for the software components designated. It is judged that the integration test is necessary when the necessity judgment formula always shows FALSE (inconsistent formula) and not necessary when the necessity judgment formula shows unclearness as to TRUE or FALSE, or always shows TRUE (valid formula).

Abstract: Whether or not an integration test between or among software components is necessary is judged. Corresponding information between features is acquired, which configures a feature model expressing characteristics of a group of products produced by the software product line, and a type and variations of each software component. For each software component, a set of state variables of all of the features corresponding to the software components is produced based on the corresponding information. For each software component, a specific logical formula is produced. Two or more software components are designated. A necessity judgment formula is produced by logical-product combining all the specific judgment formulas, for the software components designated. It is judged that the integration test is necessary when the necessity judgment formula always shows FALSE (inconsistent formula) and not necessary when the necessity judgment formula shows unclearness as to TRUE or FALSE, or always shows TRUE (valid formula).

Abstract: Ceramic powders selected from the group (a) consisting of ZrB.sub.2, HfB.sub.2, ZfC, ZrN and HfN and ceramic powders selected from the group (b) consisting of TiC, TiN and TiO.sub.2 are mixed, the mixture is sintered in a non-oxidizing atmosphere, a substitution reaction of chemical elements between the compound of the ceramic powders of the group (a) and the compound of the ceramic powders of the group (b) is caused in the sintering, and a ceramic composite substantially comprising compounds which do not belong to the groups (a) and (b) is produced by the substitution reaction. By this process, the affection of the particle size and the aggregation of raw powders to the sintering can be greatly reduced, the ranges of the applicable sintering conditions can be broadened, and dense ceramic composites having fine crystal grains and having excellent mechanical properties can be obtained.