Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…In addition, the study devises a reward function that integrates linear and Gaussian components to guide the agent's learning and decision-making processes. …”
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Desensitized Financial Data Generation Based on Generative Adversarial Network and Differential Privacy by Fan Zhang, Luyao Wang, Xinhong Zhang

“…This paper proposes a Noise Visibility Function-Differential Privacy Generative Adversarial Network (NVF-DPGAN) model, which generates privacy preserving data similar to the original data, and can be applied to data augmentation for deep learning. …”
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Leading Degree: A Metric for Model Performance Evaluation and Hyperparameter Tuning in Deep Learning-Based Side-Channel Analysis by Junfan Zhu, Jiqiang Lu

“…At last, we apply LD as a reward function to better solve the reward function design problem in reinforcement learning-based model hyperparameter tuning of side-channel analysis, and obtain better CNN model architectures compared with the state-of-the-art models obtained by previous hyperparameter tuning methods. …”
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A predictive framework using advanced machine learning approaches for measuring and analyzing the impact of synthetic agrochemicals on human health by Sahezpreet Singh, Puneet Kaur, Inderdeep Kaur, Gurpreet Singh, Satinder Kaur, Parminder Kaur

“…This study investigates the impact of synthetic agrochemicals on human health using advanced machine learning techniques, leveraging multi-level feature selection, hybrid ensemble learning, SHAP, and custom loss function to improve prediction accuracy. …”
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Forecasting Stock Market Volatility Using Housing Market Indicators: A Reinforcement Learning-Based Feature Selection Approach by Pourya Zareeihemat, Samira Mohamadi, Jamal Valipour, Seyed Vahid Moravvej

“…To directly address these issues, our innovative approach utilizes a spatial attention-based Transductive Long Short-Term Memory (TLSTM) model combined with a Reinforcement Learning (RL) strategy, which is further enhanced by a novel scope loss function for refined feature selection and an Artificial Bee Colony (ABC) algorithm for hyperparameter optimization. …”
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Real-Time Polarimetric Imaging and Enhanced Deep Learning Model for Automated Defect Detection of Specular Additive Manufacturing Surfaces by Dingkang Li, Xing Peng, Hongbing Cao, Yuanpeng Xie, Shiqing Li, Xiang Sun, Xinjie Zhao

“…Secondly, the original CIoU loss function is replaced with the Alpha-IoU loss function to accelerate network convergence and strengthen system robustness. …”
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Brain-Inspired Multisensory Learning: A Systematic Review of Neuroplasticity and Cognitive Outcomes in Adult Multicultural and Second Language Acquisition by Evgenia Gkintoni, Stephanos P. Vassilopoulos, Georgios Nikolaou

“…Background: Multicultural education and second-language acquisition engaged neural networks, supporting executive function, memory, and social cognition in adulthood, represent powerful forms of brain-inspired multisensory learning. …”
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Aktan dalam Novel The Maze Runner Karya James Dashner: Kajian Naratologi A. J. Greimas (Actants in James Dashner's The Maze Runner Novel: A Study of Narrative A. J. Greimas) by Ayu Misriyani, Endry Boeriswati, Herlina Herlina

“…The results of the research show that there are three acts which are divided into three chapters in this novel. The actant and functional structures in The Maze Runner novel are complex and have fulfilled all stages. …”
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Novel genes involved in vascular dysfunction of the middle temporal gyrus in Alzheimer’s disease: transcriptomics combined with machine learning analysis by Meiling Wang, Aojie He, Yubing Kang, Zhaojun Wang, Yahui He, Kahleong Lim, Chengwu Zhang, Li Lu

“…Using the CellChat results, AUCell evaluation of the pathway activity of specific cells showed that the obvious changes in vascular function in the middle temporal gyrus in Alzheimer’s disease were directly related to changes in the vascular endothelial growth factor (VEGF)A–VEGF receptor (VEGFR) 2 pathway. …”
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Multivariate Modelling and Prediction of High-Frequency Sensor-Based Cerebral Physiologic Signals: Narrative Review of Machine Learning Methodologies by Nuray Vakitbilir, Abrar Islam, Alwyn Gomez, Kevin Y. Stein, Logan Froese, Tobias Bergmann, Amanjyot Singh Sainbhi, Davis McClarty, Rahul Raj, Frederick A. Zeiler

“…This review explores the use of multivariate machine learning models in cerebral physiology as a whole, with an emphasis on sensor-derived signals related to hemodynamics, cerebral oxygenation, metabolism, and other modalities such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) where applicable. …”
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UAV Swarm Rounding Strategy Based on Deep Reinforcement Learning Goal Consistency with Multi-Head Soft Attention Algorithm by Zhaotian Wei, Ruixuan Wei

“…Firstly, in order to make the model closer to reality, the reward function when the target is at different positions and the target escape strategy are set, respectively. …”
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Pengembangan dan Penerapan Sistem Persuasif pada E-learning : Aspek Perceived System Credibility dan Social Influence by Vanya Anjani Mupti, Yohana Dewi Lulu Widyasari, Indah Lestari

“…And the features of the social influence are chat, comment, give emotion, and see online user. Functional testing results indicate the function of e-learning is as expected. …”
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Long non‐coding RNA CASC15 enhances learning and memory in mice by promoting synaptic plasticity in hippocampal neurons by Yuankang Zou, Bo Gao, Jiaqiao Lu, Keying Zhang, Maodeng Zhai, Ziyan Yuan, Michael Aschner, Jingyuan Chen, Wenjing Luo, Lei Wang, Jianbin Zhang

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A Stable Distributed Neural Controller for Physically Coupled Networked Discrete-Time System via Online Reinforcement Learning by Jian Sun, Jie Li

“…Each controller includes a critic network and action network for approximating strategy utility function and desired control law, respectively. For avoiding a large number of trials and improving the stability, the training of action network introduces supervised learning mechanisms into reduction of long-term cost. …”
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Quantifying task-locked information transmission between cortical areas with TMS-EEG by Zhaohuan Ding, Wenbo Ma, Leixiao Feng, Mingsha Zhang, Xiaoli Li

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Machine learning-based diagnostic model for neonatal intestinal diseases in multiple centres: a cross-sectional study protocol by Xiang Guo, Jing Shi, Yue Han, Qi Zhao, Jun Tang, Tao Xiong, Yi Yang, Jin Zhang, Qian Gao, Ling He

“…Early assessment of abnormal bowel function is critical for timely intervention and improving prognosis, underscoring the clinical importance of reducing mortality related to these conditions through rapid diagnosis and treatment. …”
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Wavelet-Based Topological Loss for Low-Light Image Denoising by Alexandra Malyugina, Nantheera Anantrasirichai, David Bull

“…The results indicate that the proposed loss function enables neural networks to learn noise characteristics better. …”
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Novel dual gland GAN architecture improves human protein localization classification using salivary and pituitary gland inspired loss functions by Hanaa Salem Marie, Moatasem M. Draz, Waleed Abd Elkhalik, Mostafa Elbaz

“…This paper introduces a novel approach that employs two complementary loss functions within a Generative Adversarial Network (GAN) framework for processing images from the Human Protein Atlas dataset. …”
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A Short-Term Wind Speed Forecasting Hybrid Model Based on Empirical Mode Decomposition and Multiple Kernel Learning by Yuanyuan Xu, Genke Yang

“…In this paper, for highly complex wind speed signals, we propose a multiple kernel learning- (MKL-) based method to adaptively assign the weights of multiple prediction functions, which extends conventional wind speed forecasting methods using a support vector machine. …”
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PENGEMBANGAN PERANGKAT PEMBELAJARAN BERBASIS PROBLEM BASED LEARNING BERBANTUAN MACROMEDIA FLASH UNTUK MENINGKATKAN KEMAMPUAN PEMECAHAN MASALAH by Novalisa Pratiwi, Yarman Yarman

“…So it can be concluded that the learning tool based on problem based learning assisted by Macromedia Flash on relationship and function material is said to be valid, practical and effective.…”
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