公开(公告)号：US20250155852A1

公开(公告)日：2025-05-15

申请号：US18838420

申请日：2023-02-21

Applicant: NITTO DENKO CORPORATION

Inventor： Kei YOSHIDA ,  Yoichi KIGAWA ,  Satoshi MATSUOKA ,  Jun MATSUNAMI

IPC: G05B13/02

Abstract: A condition optimization device includes an actual reaction value obtainment unit to obtain an actual reaction value by observing a predetermined physical property value at a predetermined condition value; a condition value calculation unit to calculate a new condition value by Bayesian optimization; an optimum condition value prediction unit to predict, by a response surface method, a best physical property value and an optimum condition value at which the best physical property value is obtainable; a first determination unit to determine whether or not convergence has occurred based on the condition value corresponding to the actual reaction value and based on the new condition value; and a second determination unit to determine, upon the first determination unit determining that the convergence has occurred, whether or not convergence has occurred based on a difference between the physical property value observed at the optimum condition value and the best physical property value.

公开(公告)号：US20240242778A1

公开(公告)日：2024-07-18

申请号：US18275076

申请日：2023-04-10

Applicant: Nitto Denko Corporation

Inventor： Kei YOSHIDA ,  Yoichi KIGAWA ,  Shinsuke SUGIURA ,  Eri MAETA ,  Jun MATSUNAMI

IPC: G16B40/10 ,  G01N21/3577 ,  G01N21/65 ,  G16B50/30

CPC classification number: G16B40/10 ,  G01N21/3577 ,  G01N21/65 ,  G16B50/30

Abstract: A nucleoside phosphoramidite identifying system for improving a nucleoside phosphoramidite identification accuracy includes a memory unit configured to store spectra of solutions of a plurality of different nucleoside phosphoramidites, a detecting unit configured to detect a spectrum of a solution of a nucleoside phosphoramidite, and an identifying unit configured to identify the nucleoside phosphoramidite based on cosine similarity between the spectra stored in the memory unit and the spectrum detected by the detecting unit.

公开(公告)号：US20230102979A1

公开(公告)日：2023-03-30

申请号：US17909121

申请日：2021-03-03

Applicant: Nitto Denko Corporation

Inventor： Nobuyuki KOZONOI ,  Yoichi KIGAWA ,  Wenjing LI ,  Yugo KASEDA ,  Hiromi YOKOYAMA ,  Ryosuke HIRAMOTO

IPC: A01K29/00 ,  A01K11/00

Abstract: An abnormality detecting system includes a first identification unit configured to identify a state of an animal that is a monitoring target in each time range, based on time-series data from a motion sensor placed on a predetermined portion of the animal that is a monitoring target; a first calculation unit configured to calculate a transition probability from the state at a predetermined timing of each time range identified by the first identification unit to a next state; and a determining unit configured to determine that an abnormality of the animal that is a monitoring target is detected when a score calculated based on the transition probability to the next state satisfies a predetermined condition.

公开(公告)号：US20220053737A1

公开(公告)日：2022-02-24

申请号：US17296696

申请日：2019-11-20

Applicant: Nitto Denko Corporation

Inventor： Nobuyuki KOZONOI ,  Yoichi KIGAWA ,  Kazumasa OKADA ,  Tatsuya KITAHARA ,  Naruyoshi ITADANI

IPC: A01K29/00 ,  G06N20/00

Abstract: A BRDC sign detecting system includes: a processor, and a memory storing program instructions that cause the processor to obtain, with respect to a bovine developing bovine respiratory disease complex (BRDC) within a time period required for a fattening process, data indicating a condition of the bovine during a predetermined time period in which the bovine did not yet develop the BRDC, and obtain data indicating a condition, during a predetermined time period, of a bovine that has not developed BRDC perform machine learning with respect to a correspondence relation between the obtained data indicating the condition during the predetermined time period and information indicating whether BRDC is developed, and infer, by inputting data indicating a condition of a new bovine during the predetermined time period into a learned model generated by performing the machine learning, information indicating whether the new bovine will develop BRDC and output an inference result.