Asahi Glass Company, Limited

Preferred Networks, Inc.

Meiji Seika Kaisha, Ltd.

Mitsubishi Aircraft Corporation

Toru Nishikawa

Hajime Itoh

Yuji Endo

Hironobu Yamamichi

Tetsuya Koyama

Daisuke Okanohara

Seiya Tokui

Justin B Clayton

Shohei Hido

Nobuyuki Kubota

Nobuyuki Ota

Keiji Wada

Yasuyuki Ichimaru

Hiroaki Hamamoto

Aiko Sawa

Kensuke Matsumoto

Toyakazu Hiranuma

Kazuo Ninomiya

The method of forming reinforced fiber base material is provided with: arranging, on the mold having a projection with a upper surface, a platform that is adjacent to the projection and has a flat upper surface at the same height as the upper surface of the projection; forming the laminate by placing reinforced fiber base material in layers on the upper surface of the projection; placing an end of the laminate in the width direction extending out of the upper surface of the projection, on the upper surface of the platform, with the end of the laminate in the width direction sandwiched in a vertical direction by a pair of the films of which outer ends in the width direction are fixed to each other; and removing the platform and pulling out the pair of the films while shaping the laminate along the projection.

Method of forming reinforcing fiber substrate

Machine learning with model filtering and model mixing for edge devices in a heterogeneous environment is disclosed. In an example embodiment, an edge device includes a communication module, a data collection device, a memory, a machine learning module, and a model mixing module. The edge device analyzes collected data with a model for a first task, outputs a result, and updates the model to create a local model. The edge device communicates with other edge devices in a heterogeneous group, transmits a request for local models to the heterogeneous group, and receives local models from the heterogeneous group. The edge device filters the local models by structure metadata, including second local models, which relate to a second task. The edge device performs a mix operation of the second local models to generate a mixed model which relates to the second task, and transmits the mixed model to the heterogeneous group.

Machine learning with model filtering and model mixing for edge devices in a heterogeneous environment

A machine learning heterogeneous edge device, method, and system are disclosed. In an example embodiment, an edge device includes a communication module, a data collection device, a memory, a machine learning module, a group determination module, and a leader election module. The edge device analyzes collected data with a model, outputs a result, and updates the model to create a local model. The edge device communicates with other edge devices in a heterogeneous group. The edge device determines group membership and determines a leader edge device. The edge device receives a request for the local model, transmits the local model to the leader edge device, receives a mixed model created by the leader edge device performing a mix operation of the local model and a different local model, and replaces the local model with the mixed model.

Machine learning heterogeneous edge device, method, and system

A vacuum degassing apparatus for molten glass is comprised of an uprising pipe, a vacuum degassing vessel, a downfalling pipe, an upstream side pit that supplies molten glass to the uprising pipe, and a downstream side pit that receives molten glass from the downfalling pipe. The vacuum degassing apparatus for molten glass is further comprised of a separating mechanism that separates a part of molten glass moving from the downfalling pipe to the downstream side pit, and a returning pipe that returns separated molten glass to the upstream side pit.

Vacuum degassing apparatus and vacuum degassing method for molten glass

Remedies for spinocerebellar degeneration or compositions for treating the same which contain as the active ingredient one or more members selected from among D-cycloserine, D-serine esters, D-serine and salts thereof. A method for treating spincerebellar degeneration which comprises administering to a patient with this disease in an efficacious dose of one or more members selected from among D-cycloserine, D-serine esters, D-serine and salts thereof.

Remedies for spinocerebellar ataxia and compositions for treating spinocerebellar ataxia

Growing community of inventors

Tokyo, Japan

Toru Nishikawa