Anti-packet-loss joint encoding for voice-over-IP steganography by Zhan-zhan GAO, Guang-ming TANG, Wei-wei ZHANG

“…Furthermore, the influences of key parameters on the performance of joint coding were studied. The selection algorithm for optimal parameters was also given. Experimental results show that the proposed joint coding can effectively improve steganographic resistance to packet loss, and decrease the number of modifications to the voice stream.…”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…XGBoost emerged as the top performing algorithm, achieving an AUC of 0.94 and an accuracy of 0.875 on the test set, marking substantial improvements over previously reported best results. …”
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EPIGENETIC REGULATION OF GENE EXPRESSION IN HEAD AND NECK SQUAMOUS CELL CARCINOMA: THERAPEUTIC PERSPECTIVES by R. B. Samsonov, Z. A. Radzhabova, Yu. V. Cheburkin, V. A. Klyuge, E. V. Tkachenko, A. V. Malek

“…Despite the fact that tumors of head and neck are generally available for visual inspection, about 60–70 % of the patients are diagnosed with it at advanced (III or IV) stages of the disease. Unfortunately, optimization of diagnostic algorithms and wide implementation of instrumental diagnostics (ultrasound examination, computed tomography, fiber endoscopy) do not improve the situation. …”
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Real-time mobile broadband quality of service prediction using AI-driven customer-centric approach by Ayokunle A. Akinlabi, Folasade M. Dahunsi, Jide J. Popoola, Lawrence B. Okegbemi

“…Three (3) classification algorithms including Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were trained using the QoS dataset and then evaluated in order to determine the most effective model based on certain evaluation metrics – accuracy, precision, F1-Score and recall. …”
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Dynamic Inversion Analysis of Structural Layer Modulus of Semirigid Base Pavement considering the Influence of Temperature and Humidity by Bei Zhang, Xu Zhang, Yanhui Zhong, Xiaolong Li, Meimei Hao, Jinbo Liu

“…The firefly algorithm was adapted to optimize the selection of support vector machine (SVM) parameters. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. …”
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PP-QADMM: A Dual-Driven Perturbation and Quantized ADMM for Privacy Preserving and Communication-Efficient Federated Learning by Anis Elgabli

“…This design prevents the PS from performing model inversion, as the individual model updates are obfuscated within the transmitted combination. …”
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A Lightweight YOLO-Based Architecture for Apple Detection on Embedded Systems by Juan Carlos Olguín-Rojas, Juan Irving Vasquez, Gilberto de Jesús López-Canteñs, Juan Carlos Herrera-Lozada, Canek Mota-Delfin

“…In Mexico, the manual detection of damaged apples has led to inconsistencies in product quality, a problem that can be addressed by integrating vision systems with machine learning algorithms. The YOLO (You Only Look Once) neural network has significantly improved fruit detection through image processing and has automated several related tasks. …”
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A Quantitative Evaluation of UAV Flight Parameters for SfM-Based 3D Reconstruction of Buildings by Inho Jo, Yunku Lee, Namhyuk Ham, Juhyung Kim, Jae-Jun Kim

“…In conclusion, this study clearly demonstrates that hierarchical strategic approaches are essential for optimizing UAV-SfM data collection. Additionally, it provides important empirical data, a validated methodological framework, and specific quantitative guidelines for standardizing UAV data collection workflows, thereby improving existing empirical or case-specific approaches.…”
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UAV target tracking method based on global feature interaction and anchor-frame-free perceptual feature modulation. by Yuanhong Dan, Jinyan Li, Yu Jin, Yong Ji, Zhihao Wang, Dong Cheng

“…In this study, in order to refine the feature representation and reduce the computational effort to improve the efficiency of the tracker, we perform feature fusion in deep inter-correlation operations and introduce a global attention mechanism to enhance the model's field of view range and feature refinement capability to improve the tracking performance for small targets. …”
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‘Machine Learning’ multiclassification for stage diagnosis of Alzheimer’s disease utilizing augmented blood gene expression and feature fusion by Manash Sarma, Subarna Chatterjee

“…When assessed with GSE3061 test data, the model achieved optimal AUC scores of 0.81, 0.75, and 0.78, and F1 scores of 0.74, 0.67, and 0.73.This research identified MAPK14, MID1, TEP1, PLG, DRAXIN, USP47 as genes associated with AD. …”
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High Precision Navigation and Positioning for Multisource Sensors Based on Bibliometric and Contextual Analysis by Jiayi Wei, Min Song, Yunbin Yuan

“…The study concludes by summarizing existing research findings and identifying gaps, with future research focusing on optimizing multisensor fusion algorithms, enhancing system adaptability, improving error models, and enhancing sensor performance in adverse environmental conditions.…”
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Radiomic Features of Mesorectal Fat as Indicators of Response in Rectal Cancer Patients Undergoing Neoadjuvant Therapy by Francesca Treballi, Ginevra Danti, Sofia Boccioli, Sebastiano Paolucci, Simone Busoni, Linda Calistri, Vittorio Miele

“…Key clinical and imaging parameters, such as age, TNM stage, CRM involvement, and EMVI presence, were recorded. A radiomic model was developed using the LASSO algorithm for feature selection and regularization from 107 extracted radiomic features. …”
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A localization strategy combined with transfer learning for image annotation. by Zhiqiang Chen, Leelavathi Rajamanickam, Jianfang Cao, Aidi Zhao, Xiaohui Hu

“…Experiments on the Corel5k multilabel image dataset verify that CNN-2L improves the labeling precision by 18% and 15% compared with the traditional multiple-Bernoulli relevance model (MBRM) and joint equal contribution (JEC) algorithms, respectively, and it improves the recall by 6% compared with JEC. …”
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Deep coal fluidization mining ropeless hoisting system and its cooperative driving control strategy by Shuai LIU, Jiusheng BAO, Jinhao DAI, Yan YIN, Liang ZHAO, Zhongbin WANG, Shirong GE

“…The research results show that the fuzzy PI loop coupling control algorithm can optimize the motor response characteristics and improve the following and synchronization performance among multiple motors. …”
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A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning by Xin Huang, Rongwu Xu, Ruibiao Li

“…However, the labeled data available for the training of URN prediction model is limited. Semi-supervised learning (SSL) can improve the model performance by using unlabeled data in the case of a lack of labeled data. …”
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A 3D reconstruction platform for complex plants using OB-NeRF by Sixiao Wu, Changhao Hu, Boyuan Tian, Yuan Huang, Shuo Yang, Shanjun Li, Shengyong Xu

“…Furthermore, the precision of the reconstruction was enhanced by optimizing camera poses. An exposure adjustment phase was integrated to improve the algorithm's robustness in uneven lighting conditions. …”
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Research on the Impact of Partial Shading on Large-scale by CHENG Yuxu, LI Jianquan, WU Xiaoyun, ZHAI Wenjie

“…With simulation, it analyzed the limitations of traditional single channel, single peak MPPT tracking algorithm in partial shading applications, proposed several measures to improve the performance against partial shading of PV arrays. …”
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Adaptive Multiobjective Evolutionary Generative Adversarial Network for Metaverse Network Intrusion Detection by Dikai Xu, Bin Cao

“…This paper further introduces a double mutation multiobjective evolutionary neural architecture search algorithm, integrating both the multiobjective evolutionary algorithm and the neural architecture search to optimize accuracy, real-time performance, and model diversity—a crucial aspect for Metaverse devices with diverse hardware constraints. …”
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Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…In terms of intelligent control, deep reinforcement learning is used to optimize irrigation decision-making, and adaptive algorithms are combined to improve the flexibility of agricultural equipment scheduling. …”
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