ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture by Ju He, Yang Yu, Hongyu Wei, Hu Xu

“…Therefore, existing tracking algorithms face difficulty in direct application to underwater object tracking. …”
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Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data. by Daphne Ezer, Victoria Moignard, Berthold Göttgens, Boris Adryan

“…In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. …”
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Fusion of Masked Autoencoder for Adaptive Augmentation Sequential Recommendation by SUN Xiujuan, SUN Fuzhen, LI Pengcheng, WANG Aofei, WANG Shaoqing

“…Finally, the sequential recommender module integrates position information, global context, and the personalized user interaction sequence to obtain the final item representation and predict the user's future possible interaction items based on the representation, thereby providing more reliable recommendation results for users. …”
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Applications of machine learning in gravitational-wave research with current interferometric detectors by Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger

“…In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. …”
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IDENTIFYING IMPORTANT GENES IN OVARIAN CANCER FROM HIGH-DIMENSIONAL MICROARRAY DATA USING SIFS-CART METHOD by Ni Kadek Emik Sapitri, Umu Sa'adah, Nur Shofianah

“…By using a hybrid Supervised Infinite Feature Selection (SIFS) method with Classification and Regression Tree (CART) or SIFS-CART, this research aims to predict ovarian cancer and identify potential genes for ovarian cancer cases. …”
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Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…It offers sophisticated algorithms that can identify and discover hidden patterns and provide insights into complex biological networks. …”
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A New High-Performance Photovoltaic Emulator Suitable for Simulating and Validating Maximum Power Point Tracking Controllers by Ambe Harrison, Njimboh Henry Alombah

“…Based on input environmental conditions, an artificial neural network (ANN) was constructed to assist the linearization process by predicting the current-voltage boundary coordinates of these segments. …”
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An Interpretable Machine Learning-Based Hurdle Model for Zero-Inflated Road Crash Frequency Data Analysis: Real-World Assessment and Validation by Moataz Bellah Ben Khedher, Dukgeun Yun

“…The first stage uses binary classification to identify road segments with potential crash occurrences, applying a customized loss function to tackle data imbalance. The second stage predicts crash frequency, also utilizing a customized loss function for count data. …”
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COMPARATIVE EVALUATION OF INDICATORS OF STRUCTURAL AND MECHANICAL PROPERTIES OF WHEAT GRAIN by P. V. Medvedev, V. A. Fedotov, E. S. Lukyanova

“…The vitreous nature of wheat allows us to predict the bakery and pasta advantages of flour from this grain. …”
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FedQP: Large-Scale Private and Flexible Federated Query Processing by Hussain M. J. Almohri, Layne T. Watson

“…The server communicates with selected clients only to predict future values. Our scheme only requires one communication round between each client and the server for model initialization without the need for a training phase. …”
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Ethical Challenges of Using the Internet of Behavior in the Medical and Healthcare Practice by Zahra Sadeqi-Arani, Esmaeil Mazroui Nasrabadi

“…By integrating technology, data analytics, and behavioral science, IoB provides a robust framework for predicting and influencing human behavior. This technology is particularly transformative in the healthcare sector, where it leverages data from wearable devices and other digital tools to offer comprehensive insights into patients' physical and behavioral health. …”
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Diagnosis of Coronary Heart Diseases Using Gene Expression Profiling; Stable Coronary Artery Disease, Cardiac Ischemia with and without Myocardial Necrosis. by Nabila Kazmi, Tom R Gaunt

“…With the recent advances in genomic tools and technologies there is potential to predict and diagnose heart disease using molecular data from analysis of blood cells. …”
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Intelligent Processing Methods by Veronika V. Tolmanova, Denis A. Andrikov

“…The importance of the wavelet transform and stochastic methods in the context of analyzing large amounts of data and predicting various phenomena was confirmed.…”
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Underwater Acoustic MAC Protocol for Multi-Objective Optimization Based on Multi-Agent Reinforcement Learning by Jinfang Jiang, Yiling Dong, Guangjie Han, Gang Su

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Optical Cryptanalysis Method Using Wavefront Shaping by Meihua Liao, Dajiang Lu, Wenqi He, Xiang Peng

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Ultrasensitive bionic photonic-electronic skin with wide red-shift mechanochromic response by Tianqi Wang, Lei Chen, Haogeng Liu, Haoran Zhu, Zijie Zeng, Yixin Lu, Ping Zhang, Yaofei Chen, Yue Huang, Gui-Shi Liu, Yunhan Luo, Zhe Chen

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Coordinated frequency regulation for thermal power unit and battery energy storage using dynamic proportional control by Gangui Yan, Qianli Sha, Junhui Li, Zheng Fang, Shuaishuai Lv, Shuo Zhan, Lin Yue

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Estimation of potato leaf area index based on spectral information and Haralick textures from UAV hyperspectral images by Jiejie Fan, Jiejie Fan, Yang Liu, Yang Liu, Yiguang Fan, Yihan Yao, Riqiang Chen, Mingbo Bian, Yanpeng Ma, Huifang Wang, Haikuan Feng, Haikuan Feng, Haikuan Feng

“…The results indicated that: (1) Spectral data demonstrate greater sensitivity to LAI than Haralick textures, with sensitivity decreasing in the order of VIs, FDSR and OSR; (2) spectral data alone provide more accurate LAI estimates than Haralick textures, with VIs achieving an accuracy of R² = 0.63, RMSE = 0.38, NRMSE = 28.36%; and (3) although Haralick textures alone were not effective for LAI estimation, they can enhance LAI prediction when combined with spectral data, with the GPR method achieving R² = 0.70, RMSE = 0.30, NRMSE = 20.28%. …”
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Tapering (deprescribing) of benzodiazepine tranquilizers by D. A. Sychev, A. V. Zhuchkov, O. V. Tereshchenko, D. V. Ivashchenko

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A Stackelberg Game Approach to Model Reference Adaptive Control for Spacecraft Pursuit–Evasion by Gena Gan, Ming Chu, Huayu Zhang, Shaoqi Lin

“…Simulations show that the MSE strategy outperforms Nash Equilibrium (NE) and Single–step Prediction Stackelberg Equilibrium (SSE) methods, achieving 25.46% faster convergence than SSE and 39.11% lower computational cost than NE.…”
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