Honda Motor Co., Ltd.

Shimadzu Corporation

Advanced Telecommunications Research Institute International

Advanced Telecommunications Research Institute Research Institute International

Tatsuya Okabe

Masaaki Sato

Kentaro Yamada

Akihiro Ishikawa

Tokitomo Ariyoshi

Akihiro Toda

Mitsuo Kawato

Okito Yamashita

Yuki Okuma

Masahiro Kimura

Takahiro Fukushige

Yusuke Uda

Takahito Tamagawa

Yusuke Takeda

A performance predicting apparatus includes an approximate model storage unit configured to store approximate models each of which is associated with one of categories, and which are used to calculate functional performance based on feature values, a feature value extracting unit configured to extract the feature values from shape data representing a shape of an object, a selection unit configured to select one of the approximate models to be used from the approximate models stored in the approximate model storage unit depending on the feature values extracted by the feature value extracting unit, and a performance calculating unit configured to calculate functional performance based on the feature values extracted by the feature value extracting unit using the approximate model selected by the selection unit.

Performance predicting apparatus, performance predicting method, and program

A brain information output apparatus includes an intention determination information storage unit in which two or more pieces of intention determination information can be stored, with each intention determination information including a pair of an intention identifier, and a learning feature amount group including one or more feature amounts extracted from second learning data that is obtained by converting first learning data into intracerebral brain activity data, the first leaning data being acquired from the outside of the cranium of a user when the user performs a trial according to one intention; a first brain activity data acquiring unit that acquires first brain activity data from the outside of the cranium of a user; a second brain activity data acquiring unit that converts the first brain activity data to intracerebral brain activity data, and acquires second brain activity data; a feature amount group acquiring unit that acquires, from the second brain activity data, an input feature amount group including one or more feature amounts; an intention identifier acquiring unit that acquires an intention identifier corresponding to the input feature amount group based on the two or more pieces of intention determination information; and an intention identifier output unit that outputs the intention identifier.

Brain information output apparatus, robot, and brain information output method

A real-time simultaneous measurement apparatus includes: a hemoglobin information-receiving portion that sequentially receives hemoglobin information, which is information relating to the amount of hemoglobin in a head portion of a test subject, from a NIRS brain-measuring apparatus that receives a synchronization signal output by a synchronization signal output apparatus and acquires the hemoglobin information when the synchronization signal has been received; a brain wave information-receiving portion that sequentially receives the brain wave information of the test subject, from an EEG brain wave-measuring apparatus that receives a synchronization signal output by the synchronization signal output apparatus and acquires the brain wave information when the synchronization signal has been received; a synchronization processing portion that performs processing that synchronizes the hemoglobin information and the brain wave information; and an output portion that outputs the synchronized hemoglobin information and brain wave information.

Real-time simultaneous measurement system, real-time simultaneous measurement apparatus, real-time simultaneous measurement method, and storage medium in which program is stored

A parallel computer system automatically detects various troubles that may occur during computations using the parallel computer system so as to automatically cope with those troubles in such environment as in a design optimization using an evolutionary optimization in which a long time is required for one computation. A parallel computer system, includes a plurality of computing nodes for executing a calculation program and a master node connected to the computing nodes through networks, for performing a parallel computation process in an environment where a long time is required for one time computation as in a design optimization using an evolutionary algorithm. The system includes abnormality handling unit for automatically performing a series of processes of monitoring, periodically or on the basis of process unit, crash or hang-up of the calculation program, suspending the execution of the calculation program in the computing node in which abnormality has been detected and making another computing node execute the relevant calculation program.

Parallel computer system

Growing community of inventors

Wako, Japan

Tatsuya Okabe