Artificial intelligence-empowered functional design of semi-transparent optoelectronic and photonic devices via deep Q-learning by Caglar Cetinkaya, Erman Cokduygulular, Muhammed Yusuf Aykut, Okan Erkal, Fatma Aydogmus, Baris Kinaci

“…This study, for the first time, employs deep Q-learning, a reinforcement learning algorithm, to address this challenge, integrating transfer matrix method for precise optical calculations. …”
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Intelligent Evaluation of Permeability Function of Porous Asphalt Pavement Based on 3D Laser Imaging and Deep Learning by Rui Xiao, Jingwen Liu, Xin Li, You Zhan, Rong Chen, Wenjie Li

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High resolution soil moisture mapping in 3D space and time using machine learning and depth functions by Mo Zhang, Yong Ge, Gerard B.M. Heuvelink, Yuxin Ma

“…To address these challenges, we utilized an equal-area spline depth function combined with machine learning to map high spatial-vertical-resolution daily soil moisture across the Qinghai-Tibet Plateau. …”
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Improving the functionality of wireless sensor networks through the use of reinforcement learning and metaheuristic based energy efficient system by Shiwei Zhang, Xinghan Liu

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Cognitive, Behavioral, and Learning Profiles of Children with Above-Average Cognitive Functioning: Insights from an Italian Clinical Sample by Daniela Pia Rosaria Chieffo, Valentina Arcangeli, Valentina Delle Donne, Giulia Settimi, Valentina Massaroni, Angelica Marfoli, Monia Pellizzari, Ida Turrini, Elisa Marconi, Laura Monti, Federica Moriconi, Delfina Janiri, Gabriele Sani, Eugenio Maria Mercuri

Subjects: “…above-average cognitive functioning…”
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Abnormal intrinsic brain functional network dynamics in patients with retinal detachment based on graph theory and machine learning by Yuanyuan Wang, Yu Ji, Jie Liu, Lianjiang Lv, Zihe Xu, Meimei Yan, Jialu Chen, Zhijun Luo, Xianjun Zeng

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Study protocol: How does cognitive flexibility relate to other executive functions and learning in healthy young adults? by Ke Tong, Yuan Ni Chan, Xiaoqin Cheng, Bobby Cheon, Michelle Ellefson, Restria Fauziana, Shengchuang Feng, Nastassja Fischer, Balázs Gulyás, Natalie Hoo, David Hung, Kastoori Kalaivanan, Christelle Langley, Kean Mun Lee, Li Ling Lee, Timothy Lee, Irene Melani, Nadhilla Melia, Jia Ying Pei, Lisha Raghani, Yoke Loo Sam, Peter Seow, John Suckling, Yan Fen Tan, Chew Lee Teo, Ryutaro Uchiyama, Hui Shan Yap, Georgios Christopoulos, Henriette Hendriks, Annabel Chen, Trevor Robbins, Barbara Sahakian, Zoe Kourtzi, Victoria Leong, CLIC Phase 1 Consortium

“…The current study aims to (1) establish the construct validity of CF in relation to other executive function skills and intelligence, and (2) elucidate specific relationships between CF, structure learning, creativity, career decision making and planning, and other life skills.…”
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Short-Term Energy Consumption Forecasting Analysis Using Different Optimization and Activation Functions with Deep Learning Models by Mehmet Tahir Ucar, Asim Kaygusuz

“…Regression methods, machine learning, and deep learning methods are used to learn different patterns from data and develop a consumption prediction model. …”
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Heterogeneous virus classification using a functional deep learning model based on transmission electron microscopy images by Niloy Sikder, Md. Al-Masrur Khan, Anupam Kumar Bairagi, Mehedi Masud, Jun Jiat Tiang, Abdullah-Al Nahid

“…The methodology of this study includes two coherent image processing techniques to reduce the noise present in raw microscopy images and a functional Convolutional Neural Network (CNN) model for classification. …”
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Adaptive temporal-difference learning via deep neural network function approximation: a non-asymptotic analysis by Guoyong Wang, Tiange Fu, Ruijuan Zheng, Xuhui Zhao, Junlong Zhu, Mingchuan Zhang

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Joint Clearing Model of Day-Ahead Energy Market and Down Regulation Service Market for Accommodation of Renewable Energy by Mingli ZHANG, Na ZHANG, Zhikai WU, Jing GAO, Xilin XU, Jian LI, Quan LV

“…In the background of the integrated market operation of the day-ahead energy trading and deep regulation service trading in Northeast China, a joint clearing model of the two market is established. The objective function of the model is to minimum the sum of the generation cost, start-up cost, and deep regulation compensation cost of thermal power units, as well as the compensation cost for renewable energy curtailment. …”
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Statistical learning-driven parameter tuning in injection molding using modified simplex method by Pongchanun Luangpaiboon, Walailak Atthirawong, Anucha Hirunwat, Pasura Aungkulanon

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Deep-learning-assisted reconfigurable metasurface antenna for real-time holographic beam steering by Ma Hyunjun, Kim Jin-Soo, Choe Jong-Ho, Park Q-Han

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Combining semiparametric and machine learning approaches for short-term prediction of satellite clock bias by Lihong Jin, Wanzhuo Zhao, Xiong Pan, Qingsong Ai, Mao Cai, Xiaoli Ruan

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Bioinformatics prediction of function of T-cell exhaustion related genes in ischemic stroke by Yajun Gao, Ruyu Bai, Bo Gao, Ma Li

“…Functional enrichment analysis revealed that these genes were involved in immune response and cellular processes, which were closely related to the level of immune cell infiltration. …”
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FLavourite: Horizontal and Vertical Federated Learning Setting Comparison by Walter Riviera, Ilaria Boscolo Galazzo, Gloria Menegaz

Subjects: “…Federated learning…”
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Construction and Validation of a Machine Learning-Based Risk Prediction Model for Sleep Quality in Patients with OSA [Response to Letter] by Guo B

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Multi-spatial urban function modeling: A multi-modal deep network approach for transfer and multi-task learning by Zhaoya Gong, Chenglong Wang, Bin Liu, Binbo Li, Wei Tu, Yuting Chen, Zhicheng Deng, Pengjun Zhao

Subjects: “…Urban functions…”
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PAQR6 as a prognostic biomarker and potential therapeutic target in kidney renal clear cell carcinoma by Tao Zou, Zongming Jia, Jixiang Wu, Xuxu Liu, Minghao Deng, Xuefeng Zhang, Yuxin Lin, Yuxin Lin, Jigen Ping

“…However, its biological function in kidney renal clear cell carcinoma (KIRC) and its potential as a therapeutic target remain underexplored.MethodsIn this study, PAQR6 was identified as a critical oncogene by WGCNA algorithm and differential gene expression analysis using TCGA - KIRC and GSE15641 data. …”
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Improving image reconstruction to quantify dynamic whole-body PET/CT: Q.Clear versus OSEM by Sam Springer, Jeremy Basset-Sagarminaga, Tineke van de Weijer, Vera B. Schrauwen-Hinderling, Walter H. Backes, Roel Wierts

“…Results Compared to OSEM, Q.Clear showed 40–55% lower noise levels for all tissue types (p < 0.05). …”
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