Abstract: A method of sealing an end of a polymer with a carbodiimide compound without liberating an isocyanate compound. A compound including a cyclic structure having one carbodiimide group whose first nitrogen and second nitrogen are bonded together by a bond group is used as an end-sealing agent for the polymer.

Abstract: A resin composition which comprises a polyester and is free from a smell produced from a free isocyanate compound. The resin composition comprises a polyester (component A) whose end is modified and a compound including a cyclic structure having one carbodiimide group whose first nitrogen and second nitrogen are bonded together by a bond group (component B).

Abstract: According to one embodiment, a semiconductor storage device comprises a main memory, a request issue module, a delay module, and an access module. The main memory is configured to store candidate information for determining a compaction candidate for a nonvolatile memory. The request issue module is configured to issue an access request for the candidate information in the main memory. The delay module is configured to delay the access request issued from the request issue module. The access module is configured to access the candidate information in the main memory based on an access request delayed by the delay module.

Abstract: An information processing device includes an acquisition unit acquiring a viewing log including information representing content of an operation for viewing content and time of the operation, a learning unit learning, based on the viewing log acquired by the acquisition unit, a viewing behavior model which is a stochastic state transition model representing a viewing behavior of a user, a recognition unit recognizing, using the viewing behavior model obtained through learning by the learning unit, a current viewing state of the user, a prediction unit predicting, using the viewing behavior model, the viewing behavior of the user after a predetermined period of time with the current viewing state of the user recognized by the recognition unit as a starting point, and a display control unit displaying information relating to content predicted to be viewed through the viewing behavior predicted by the prediction unit.

Abstract: A learning apparatus includes a storage unit configured to store a network formed by a plurality of nodes each holding dynamics; a learning unit configured to learn the dynamics of the network in a self-organizing manner on the basis of observed time-series data; a winner-node determiner configured to determine a winner node, the winner node being a node having dynamics that best match the time-series data; and a weight determiner configured to determine learning weights for the dynamics held by the individual nodes according to distances of the individual nodes from the winner node. The learning unit is configured to learn the dynamics of the network in a self-organizing manner by degrees corresponding to the learning weights.

Abstract: An information processing device includes: an object module determining unit for determining of a learning model having a time series pattern storage model for storing a time series pattern as a module which is the minimum component, a maximum likelihood module having the maximum likelihood, or a new module to be an object module that is a module having a model parameter of the storage model to be updated; and an updating unit for updating the model parameter of the object module using learned data to be used for learning that is the time series of an observed value; with the object module determining unit using the learned data to determine the maximum likelihood module or the new module to be the object module based on the posterior probability of the learning model in the case that learning of the maximum likelihood module or the new module has been performed.

Abstract: An information processing device comprising: a likelihood calculating unit configured to take the time series of an observed value to be successively supplied as learned data to be used for learning, and with regard to each module making up a learning model having an HMM (Hidden Markov Model) as a module which is the minimum component, to obtain likelihood that the learned data may be observed at the module; an object module determining unit configured to determine, based on the likelihood, a single module of the learning model, or a new module to be an object module that is an object module having an HMM parameter to be updated; and an updating unit configured to perform learning for updating the HMM parameter of the object module using the learned data.

Abstract: An information processing device includes: a hierarchy processing unit for generating a unit to connect the unit in a hierarchical structure, the unit including an input control unit for performing input control for storing an observed value, and outputting the time series of the observed value as input data to be given to a learning model having an HMM (Hidden Markov Model) as a minimum component module, a model processing unit for performing processing using the learning model, including a module learning unit for obtaining likelihood of the input data being observed with the module, to determine one module of the learning model, or new module to be an object module having HMM parameters to be updated, and to perform module learning processing for updating the HMM parameters, and a recognizing unit for recognizing the input data using the learning model, and an output control unit for performing output control.

Abstract: The present invention is intended to provide a quick search of a plurality of sets. A common representative point setting block sets a common representative point common to sets on the basis of a feature vector stored in a vector information storage block and stores the set point into a common representative point information storage block. A neighborhood table group creation block creates a neighborhood table for each set on the basis of the vector information and common representative point information and stores the created table in a neighborhood table group storage block. A nearest neighborhood vector group search block, upon acquisition of an input vector, searches each set for a nearest neighborhood vector of the input vector on the basis of the vector information, the common representative point information, and the neighborhood table group and outputs the retrieved nearest neighborhood vector as a comparison result. The present invention is applicable to image processing apparatuses.

Abstract: A data processing apparatus includes an obtaining unit configured to obtain time-series data from a wearable sensor, an activity model learning unit configured to learn an activity model representing a user activity state as a stochastic state transition model from the obtained time-series data, a recognition unit configured to recognize a current user activity state by using the activity model of the user obtained by the activity model learning unit, and a prediction unit configured to predict a user activity state after a predetermined time elapses from a current time from the current user activity state recognized by the recognition unit.

Abstract: An information processing apparatus includes a storage unit configured to store a node holding dynamics; an input-weight-coefficient adjuster configured to adjust input-weight coefficients on a dimension-by-dimension basis, the input-weight coefficients being weight coefficients for individual dimensions of input data input to input units of the node, the input data being observed time-series data having a plurality of dimensions; and an output-weight-coefficient adjuster configured to adjust output-weight coefficients on a dimension-by-dimension basis, the output-weight coefficients being weight coefficients for individual dimensions of output data having a plurality of dimensions and output from output units of the node.

Abstract: An information processing apparatus includes a feature amount extraction unit extracting a feature amount of each frame of an image, a maximum likelihood state series estimation unit estimating maximum likelihood state series using the feature amount, a highlight label generation unit generating highlight label series with respect to the attention detector learning content, and a learning unit learning the highlight detector that is the state transition probability model using learning label series that is a pair of the maximum likelihood state series obtained from the attention detector learning content and the highlight label series.

Abstract: There are provided a resin composition comprising a polylactic acid which (i) comprises a poly-L-lactic acid (component B-1) and a poly-D-lactic acid (component B-4), (ii) has a weight ratio of the component B-1 to the component B-4 (component B-1/component B-4) of 10/90 to 90/10, and (iii) shows a proportion of melt peaks at 195° C. or higher to all melt peaks in a temperature rising process in measurement by a differential scanning calorimeter (DSC) of at least 20%; a molded article of the resin composition; and methods for producing the resin composition and the molded article.

Abstract: A manufacturing apparatus of polylactic acid having at least an inlet and an outlet of a substance to be reacted and an exhaust port provided in a horizontal reaction vessel not having continuous rotating shafts in a direction of center line of a rotating shaft of a stirring blade provided in the reaction vessel and a manufacture method. By removing low molecular weight substance in the polylactic acid, high-quality polylactic acid can be stably manufactured.

Abstract: A polylactic acid composition wherein a ratio (L/D) of an L-lactic acid unit and a D-lactic acid unit is from 30/70 to 70/30; a weight average molecular weight (Mw) is from 100,000 to 300,000; a stereocomplex crystal content (S) is 80% or more; a melting point (Tm) of a stereocomplex crystal is 200° C. or higher; and a degree of randomization (R) is from 0.001 to less than 2.5%, and a fiber thereof.

Abstract: It is an object of the present invention to provide a polylactic acid composition having excellent crystallinity, wet heat stability and melt stability. It is another object of the present invention to provide a molded article which is obtained from the polylactic acid composition and excellent in appearance and color. The present invention is a composition and molded article thereof which comprises a polylactic acid (component A), a carbodiimide compound (component B) and a phosphoric acid ester metal salt (component C).

Abstract: A learning system is provided, which includes network storage means for storing a network including a plurality of nodes, each of which holds a dynamics; and learning means for self-organizationally updating the dynamics of the network on the basis of measured time-series data.

Abstract: A method of producing a stereocomplex polylactic acid having a high melting point and a high molecular weight, wherein only stereocomplex crystals are grown even when melting and crystallization are repeated. The method comprises the steps of: (1) obtaining a first polylactic acid by the ring-opening polymerization of a first lactide composed of lactic acid units of the same chirality; (2) obtaining a purified first polylactic acid by removing the lactide from the first polylactic acid in a molten state under reduced pressure; (3) obtaining a second polylactic acid by the ring-opening polymerization of a second lactide which differs from the first lactide in chirality in the presence of the purified first polylactic acid; and (4) obtaining a purified second polylactic acid by removing the lactide from the second polylactic acid in a molten state under reduced pressure.

Abstract: In an image recognition apparatus, feature point extraction sections and extract feature points from a model image and an object image. Feature quantity retention sections extract a feature quantity for each of the feature points and retain them along with positional information of the feature points. A feature quantity comparison section compares the feature quantities with each other to calculate the similarity or the dissimilarity and generates a candidate-associated feature point pair having a high possibility of correspondence. A model attitude estimation section repeats an operation of projecting an affine transformation parameter determined by three pairs randomly selected from the candidate-associated feature point pair group onto a parameter space. The model attitude estimation section assumes each member in a cluster having the largest number of members formed in the parameter space to be an inlier.

Abstract: An information processing apparatus includes: model learning means for self-organizing, on the basis of a state transition model having a state and state transition to be learned by using time series data as data in time series, an internal state from an observation signal obtained by a sensor; and controller learning means for performing learning for allocating a controller, which outputs an action, to each of transitions of a state or each of transition destination states in the state transition model indicating the internal state self-organized by the model learning means.