Nippon Telegraph and Telephone Corporation

Tokyo Institute of Technology

Masataka Yamaguchi

Noboru Harada

Kunio Kashino

Kaoru Hiramatsu

Yuma Koizumi

Go Irie

Tadashi Ohokubo

Saeko Yamaguchi

An anomaly detection technique which realizes high accuracy while reducing cost required for normal model learning is provided. An anomaly detection apparatus includes an anomaly degree estimating unit configured to estimate an anomaly degree indicating a degree of anomaly of anomaly detection target equipment from sound emitted from the anomaly detection target equipment (hereinafter, referred to as anomaly detection target sound) based on association between a first probability distribution indicating distribution of normal sound emitted from one or more pieces of equipment different from the anomaly detection target equipment and normal sound emitted from the anomaly detection target equipment (hereinafter, referred to as normal sound for adaptive learning).

Anomaly detection apparatus, probability distribution learning apparatus, autoencoder learning apparatus, data transformation apparatus, and program

Clustering can be performed using a self-expression matrix in which noise is suppressed. A self-expression matrix is calculated that minimizes an objective function that is for obtaining, from among matrices included in a predetermined matrix set, a self-expression matrix whose elements are linear weights when data points in a data set are expressed by linear combinations of points, the objective function being represented by a term for obtaining the residual between data points in the data set and data points expressed by linear combinations of points using the self-expression matrix, a first regularization term that is multiplied by a predetermined weight and is for reducing linear weights of the data points that have a large Euclidean norm in the self-expression matrix, and a second regularization term for the self-expression matrix. A similarity matrix defined by the calculated self-expression matrix is then calculated. Then a clustering result is obtained by clustering the data set based on the similarity matrix.

Clustering device, method and program

A tow opening apparatus for opening tow of chemical filaments wherein a plurality of opening disks each with the interior peripheral surface formed with a plurality of small ridges and valleys and a plurality of opening disks each with the peripheral surface formed with a plurality of ridges and valleys are alternately disposed and vertically spaced apart from each other by a suitable distance, and tow filaments are brought into alternate contact with the interior peripheral surfaces of the opening rings and the peripheral surfaces of the opening disks whereby said filaments are opened and oriented in parallel relationship.

Tow opening apparatus

Growing community of inventors

Tokyo, Japan

Masataka Yamaguchi