Results 111 to 120 of about 249,549 (273)

Use of Machine Learning to Identify Markers of Risk for Fragile X‐Associated Tremor/Ataxia Syndrome: A Preliminary Analysis

Annals of Neurology, EarlyView.
Objective The objective of this study was to examine whether machine learning has the capacity to prospectively identify and predict the emergence of Fragile X‐associated tremor/ataxia syndrome (FXTAS) among male fragile X premutation carriers (PCs). Methods We explored neuropsychological and motor evaluation metrics, brain magnetic resonance imaging ...
Chitrabhanu Gupta, Angeela Poudel, Jun Yi Wang, Randi Hagerman, Glenda Espinal, Jessica Famula, Andrea Schneider, Flora Tassone, Susan M. Rivera, Chen‐Nee Chuah, David Hessl   +10 more
wiley   +1 more source

Stability control of adsorption robot considering external disturbance and parameter uncertainty using RMPC

Measurement + Control
This paper mainly studies the stability of a sea cucumber adsorption robot (SCAR) under external disturbances and parameter uncertainty. As a fishing robot with a suction effect, a dynamic model of its vertical operation is established, taking into ...
Changbin Wang, Dalei Song, Chong Li, Qianli Jiang, Weicheng Sun   +4 more
doaj   +1 more source

Optimizing hydropower scheduling through accurate power load prediction: A practical case study

Heliyon
Hydropower stations that are part of the grid system frequently encounter challenges related to the uneven distribution of power generation and associated benefits, primarily stemming from delays in obtaining timely load data.
Guangqin Huang, Ming Tan, Zhihang Meng, Jiaqi Yan, Jin Chen, Qiang Qu   +5 more
doaj   +1 more source

Data Processing and Interpretation of Antarctic Ice-Penetrating Radar Based on Variational Mode Decomposition

Remote Sensing, 2019
In the Arctic and Antarctic scientific expeditions, ice-penetrating radar is an effective method for studying the bedrock under the ice sheet and ice information within the ice sheet.
Siyuan Cheng, Sixin Liu, Jingxue Guo, Kun Luo, Ling Zhang, Xueyuan Tang   +5 more
doaj   +1 more source

Short‐Term Scheduling Optimization of a Single‐Pipeline Refining System With High Melting Point Crude Oil

Asia-Pacific Journal of Chemical Engineering, EarlyView.
ABSTRACT In order to reflect the actual production situation more comprehensively and optimize the production cost, this paper solves the short‐term scheduling optimization problem for a single pipeline containing high melting point crude oil. Based on the refining plan given by the upper layer, a multi‐objective optimization model with high melting ...
Jing Yao, Xianxin Liu, Zhen Pan, Chengming Hao, Xiangwei Xu, Wei Jia   +5 more
wiley   +1 more source

Variance Reduction Optimization Algorithm Based on Random Sampling [PDF]

Jisuanji kexue yu tansuo
The stochastic gradient descent (SGD) algorithms have been applied to machine learning and deep learning due to their superior performance. However, SGD requires the stochastic gradient of a single sample to approximate the full gradient of all samples ...
GUO Zhenhua, YAN Ruidong, QIU Zhiyong, ZHAO Yaqian, LI Rengang
doaj   +1 more source

Twist Engineering of Hybrid 2D van der Waals‐Transition Metal Oxide Membranes

Advanced Physics Research, EarlyView.
The integration of transition metal oxide membranes with 2D van der Waals materials offers exciting opportunities to study new interfacial phenomena. These interactions can create complex moiré patterns that change the materials' properties. Understanding these interactions, influenced by symmetry and distortion, poses significant challenges and ...
Mar Garcia Hernandez, Peter Bøggild, Mads Brandbyge, Jacobo Santamaria, Nini Pryds   +4 more
wiley   +1 more source

A Hybrid Semi‐Inverse Variational and Machine Learning Approach for the Schrödinger Equation

Advanced Physics Research, EarlyView.
A hybrid semi‐inverse variational and machine‐learning framework is presented for solving the Schrödinger equation with complex quantum potentials. Physics‐based variational solutions generate high‐quality training data, enabling Random Forest and Neural Network models to deliver near‐perfect energy predictions.
Khalid Reggab, Houssam Eddine Hailouf, Kingsley Onyebuchi Obodo, Mireille Megnidio‐Tchoukouegno, Mohammed Benali Kanoun, Souraya Goumri‐Said   +5 more
wiley   +1 more source

Progressive Adoption of RINA in IoT Networks: Enhancing Scalability and Network Management via SDN Integration

Applied Sciences
Thousands of devices are connected to the Internet as part of the Internet of Things (IoT) ecosystems. The next generation of IoT networks is expected to support this growing number of Intelligent IoT devices and tactile Internet solutions to provide ...
David Sarabia-Jácome, Sergio Giménez-Antón, Athanasios Liatifis, Eduard Grasa, Marisa Catalán, Dimitrios Pliatsios   +5 more
doaj   +1 more source

Game‐based learning for undergraduate consolidation: A qualitative study of how game‐based learning provides much more than knowledge acquisition

Anatomical Sciences Education, EarlyView.
Abstract Game‐based learning (GBL) is increasingly used in medical education to supplement traditional didactic learning methods. Adult learners in particular may benefit from GBL, given the autonomous and iterative nature of a well‐designed educational game.
Thomas J. Paddock, Erin P. Fillmore
wiley   +1 more source