Nippon Steel Corporation

Oki Electric Industry Co., Ltd.

Krosakiharima Corporation

Oki Electric Industrial Co., Ltd.

Masashi Oikawa

Katsuhiro Minamida

Shinichi Fukunaga

Atsushi Kitahara

Atsushi Sugihashi

Kunio Kanai

Mamoru Takeda

Akira Ishibashi

Kouji Kawarada

Kohei Tani

Toshiaki Takamune

In a sliding nozzle comprising three plates consisting of an upper plate, an intermediate plate capable of a sliding movement, and a lower plate, it is intended to suppress adhesion and deposition of metal oxides and others on wall surfaces of inner bores of the three plates. The intermediate plate has: a first inclined portion whose surface defines a slidingly closing directional leading-side wall surface of an inner bore thereof and extends obliquely downwardly in a diametrically contracting direction; a second inclined portion whose surface defines an upper part of a slidingly closing directional trailing-side wall surface of the inner bore thereof and extends obliquely downwardly in a diametrically contracting direction, and a third inclined portion whose surface defines a lower part of the slidingly closing directional trailing-side wall surface of the inner bore thereof and extends obliquely downwardly in a diametrically expanding direction.

Sliding nozzle

A machine learning device includes a state variable acquiring section, a teaching data acquiring section, and a learned model generating section. The state variable acquiring section acquires, as state variables: feature information that is information regarding a feature of an actual printed matter on which printing has been actually performed by an image forming apparatus; medium information that is information regarding a print medium used in the actual printed matter; and first control information that is information regarding control performed when the actual printed matter has been outputted. The teaching data acquiring section acquires, as teaching data, second control information that is information regarding control that causes the feature information to fall within a predetermined threshold. The learned model generating section generates a learned model by performing machine learning on the basis of the pieces of information acquired by the state variable acquiring section and the teaching data.

Machine learning device, data processing system, printing system, machine learning method, and data processing method

The present invention is a honeycomb panel comprising metal face sheets respectively disposed on upper and lower faces of said honeycomb core characterized in that said honeycomb panel has a metal side plate disposed on at least one side face thereof, for mutually connecting honeycomb panels to each other, and a process for producing a honeycomb panel, said process characterized by comprising the steps of: welding a corrugated honeycomb core at an end face of its corrugation to a side plate along the end face of said corrugation; welding the honeycomb core at top portions of its corrugation to an upper face sheet from the side of the honeycomb core by means of an energy beam; welding bottom portions of the corrugation of the honeycomb core to a lower face sheet from the side of the face sheet by means of an energy beam; and welding the face sheets to the side plate before or after welding the honeycomb core to the face sheets.

Honeycomb panel and process for producing same

Page printer having a printing drum rotating at predetermined speeds and

Growing community of inventors

Tokyo, Japan

Masashi Oikawa