Results 151 to 160 of about 69,954 (309)

Autonomous Machine Learning‐Based Classification and Arrangement of Submillimeter Objects Using a Capillary Force Gripper

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study presents an automated system integrating a capillary force gripper and machine learning‐based object detection for sorting and placing submillimeter objects. The system achieved stable and simultaneous manipulation of four object types, with an average task time of 86.0 seconds and a positioning error of 157 ± 84 µm, highlighting its ...
Satoshi Ando   +4 more
wiley   +1 more source

Lettere autografe di A. Cesalpino, C. Linné, A. Haller, L. Spallanzani, Brocchi, Sangiorgio, Viali, Allioni, Arduino [e altri] - 008

open access: yes
Lettera autografa di Carl Linné (1707-1778) diretta a Pietro Arduino (1728-1805). Si tratta di un bifolio già piegato a formare una lettera, che inizia con «Viro Nobili D.no Arduini» con la data «Dabam Upsaliae 1764, d. 20 Aprilis».
Linné, Carl von [viaf:34594730]
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FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

open access: yesAdvanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker   +3 more
wiley   +1 more source

ЗАПИСЬ БИНАРНЫХ ДАННЫХ НА SD КАРТУ ARDUINO DUE

open access: yes, 2016
The short review of microcontrollers of family Arduino, their characteristics and application fields is given. Importance of record of parameters of researched object is marked to produce debugging of control systems on microcontrollers Arduino.
В. Михайлов Г.; Мидивисана ООО, Минск   +1 more
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Self‐Driving Laboratory Optimizes the Lower Critical Solution Temperature of Thermoresponsive Polymers

open access: yesAdvanced Intelligent Discovery, EarlyView.
A low‐cost, self‐driving laboratory is developed to democratize autonomous materials discovery. Using this "frugal twin" hardware architecture with Bayesian optimization, the platform rapidly converges to target lower critical solution temperature (LCST) values while self‐correcting from off‐target experiments, demonstrating an accessible route to data‐
Guoyue Xu, Renzheng Zhang, Tengfei Luo
wiley   +1 more source

2D pozícionálás Arduino alapon

open access: yes, 2015
Egy kamera 2 dimenziós pozícionálásának megvalósítása léptetőmotorok segítségével, amelyeket egy számítógéppel összekötött Arduino mikrokontrollerrel vezérlünk.BSc/BAMérnök ...
Frendrich, Károly
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Accurate and Anti‐Interference Control of Computer Vision‐Assisted Light‐Driven Liquid Crystal Elastomer Actuator

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article introduces a computer vision‐assisted control strategy for light‐driven liquid crystal elastomer actuators. Through negative feedback regulation, the liquid crystal elastomer actuator exhibits accurate and stable bending deformation in complex environments.
Wei Zhang   +6 more
wiley   +1 more source

以Arduino為基礎-養魚實驗系統

open access: yes, 2017
[[abstract]]本組專題是一套以Arduino為基礎的養魚實驗系統。以現在來說養魚不只是因為興趣,有些人要靠養魚賣魚來維生,而養魚很重要的一個注意事項是顧好水的品質,可是現在人可能因為忙碌或長期不在家而沒有時間去管理水質,本專題考量兩種狀況,首先是隨著時間經過水被蒸發時,需要自動補水。其次是當魚缸水質太混濁,需要自動換水的功能,因此本專題設計並實作完成了一套以Arduino來控制自動化換水、補水的養魚實驗系統 ...
胡名翔   +3 more
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Haptic In‐Sensor Computing Device Based on CNT/PDMS Nanocomposite Physical Reservoir

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Using a porous carbon nanotube‐polydimethylsiloxane nanocomposite, a sensor array integrated with a physical reservoir computing paradigm capable of in‐sensor computing is demonstrated. The device is able to classify between nine objects with an accuracy above 80%, opening the possibility for low‐power sensing/computing for future robotics.
Kouki Kimizuka   +7 more
wiley   +1 more source

Adaptive secure malware efficient machine learning algorithm for healthcare data

open access: yesCAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Malware software now encrypts the data of Internet of Things (IoT) enabled fog nodes, preventing the victim from accessing it unless they pay a ransom to the attacker. The ransom injunction is constantly accompanied by a deadline. These days, ransomware attacks are too common on IoT healthcare devices.
Mazin Abed Mohammed   +8 more
wiley   +1 more source

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