Distinct role of primate DLPFC and LIP in hierarchical control of learned saccade sequences by Qingjun Wang, Binchao Shi, Jing Jia, Jingyu Hu, Haoran Li, Xin Jin, Aihua Chen

“…Summary: Learned action sequences are suggested to be organized hierarchically, but how the various hierarchical levels are processed by different cortical regions remains largely unknown. …”
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Earthquake induced liquefaction hazard analysis for Chittagong City using machine learning by Md. Mehedi Hasan, Md. Zillur Rahman, Abul Kashem Faruki Fahim

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Mesenchymal Stem Cells: What We Have Learned and How to Manage Them by Nadia Lampiasi

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From Flipped Classroom to Flipped Learning: Evolution of the Concept and Its Philosophical Foundations by I. I. Gnutova

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Exploring Deep Learning–Based Models for Sociocultural African Food Recognition System by Grace Ataguba, Mona Alhasani, James Daniel, Emeka Ogbuju, Rita Orji

“…We present the design and evaluation of a sociocultural app for African food recognition using deep learning models such as transfer learning. Deep learning models have multiple processing layers that make them robust in image recognition. …”
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Federated Learning Based on Kernel Local Differential Privacy and Low Gradient Sampling by Yi Chen, Dan Chen, Niansheng Tang

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Incorporating climate data with machine learning can improve rice phenology estimation by Yiqing Liu, Weihang Liu, Tao Ye, Shuo Chen, Xuehong Chen, Zitong Li, Ning Zhan, Ran Sun

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Maritime mobile edge computing offloading method based on deep reinforcement learning by Xin SU, Leilei MENG, Yiqing ZHOU, Wu CELIMUGE

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Domain adaptation-based multistage ensemble learning paradigm for credit risk evaluation by Xiaoming Zhang, Lean Yu, Hang Yin

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Using low-discrepancy points for data compression in machine learning: an experimental comparison by S. Göttlich, J. Heieck, A. Neuenkirch

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Mood Detection from Physical and Neurophysical Data Using Deep Learning Models by Zeynep Hilal Kilimci, Aykut Güven, Mitat Uysal, Selim Akyokus

“…Another novelty is that the emotion classification task is performed by both conventional machine learning algorithms and deep learning models. For this purpose, Feedforward Neural Network (FFNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM) neural network are employed as deep learning methodologies. …”
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UTR-Insight: integrating deep learning for efficient 5′ UTR discovery and design by Saichao Pan, Hanyu Wang, Hang Zhang, Zan Tang, Lianqiang Xu, Zhixiang Yan, Yong Hu

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Classification of the optimal rebalancing frequency for pairs trading using machine learning techniques by Mahmut Bağcı, Pınar Kaya Soylu

“…This study proposes a machine learning (ML) approach to predict ORF ranges. To improve ML accuracy, pairs were categorized into three subgroups based on their correlation levels: positively, weakly, and negatively correlated. …”
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Forecasting CDS Term Structure Based on Nelson–Siegel Model and Machine Learning by Won Joong Kim, Gunho Jung, Sun-Yong Choi

“…Among the machine learning approaches, GMDH demonstrates the best performance in forecasting the CDS term structure. …”
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Dual Convolution Neural Networks of Ensemble Learning with Attention Mechanism for Rice Classification by Cheng Linfeng

“…The aim of this project is to develop a dual convolutional neural network for ensemble learning based on the initial model and the res network model, and apply the ensemble model to the rice classification problem. …”
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Deep Learning Based Proactive Caching for Effective WSN-Enabled Vision Applications by Fangyuan Lei, Jun Cai, Qingyun Dai, Huimin Zhao

“…Firstly, based on Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies, a distributed deep learning network SSAE is constructed in the sink nodes and control nodes of the WSN network. …”
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COVID-19 World Vaccination Progress Using Machine Learning Classification Algorithms by Nasiba M. Abdulkareem, Adnan Mohsin Abdulazeez, Diyar Qader Zeebaree, Dathar A. Hasan

Subjects: “…COVID-19 Vaccine, Machine learning, Classification algorithm, Dataset, weka…”
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An Intelligent Framework Based on Deep Learning for SMS and e-mail Spam Detection by Umair Maqsood, Saif Ur Rehman, Tariq Ali, Khalid Mahmood, Tahani Alsaedi, Mahwish Kundi

“…In previous studies using machine learning (ML), spam detection using a small dataset has resulted in lower accuracy. …”
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Deep Learning-Enabled Integration of Histology and Transcriptomics for Tissue Spatial Profile Analysis by Yongxin Ge, Jiake Leng, Ziyang Tang, Kanran Wang, Kaicheng U, Sophia Meixuan Zhang, Sen Han, Yiyan Zhang, Jinxi Xiang, Sen Yang, Xiang Liu, Yi Song, Xiyue Wang, Yuchen Li, Junhan Zhao

“…We introduce GIST, a deep learning-enabled gene expression and histology integration for spatial cellular profiling. …”
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RETRACTED: Machine learning as an integral part of the security strategy of production business processes by Ponamareva Svetlana, Zhukov Aleksandr, Skripachev Vladimir, Kartsan Igor

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