Apple Trajectory Prediction in Orchards: A YOLOv8-EK-IPF Approach by Jinxing Niu, Zhengyi Liu, Shuo Wang, Jiaxi Huang, Junlong Zhao

“…To address the challenge of accurate apple harvesting by orchard robots, which is hindered by dynamic changes in apple position due to wind interference and branch swaying, this study proposes an optimized prediction algorithm based on an integration of the extended Kalman filter (EKF) and an improved particle filter (IPF), built upon initial apple detection and recognition using YOLOv8. …”
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Intelligent Reflecting Surfaces (IRS)-Enhanced Cooperative NOMA: A Contemporary Review by Sanjeev Sharma, Amit Kumar Mishra, M. Hemant Kumar, Kuntal Deka, Vimal Bhatia

“…The integration of intelligent reflecting surfaces (IRS) into cooperative non-orthogonal multiple access (NOMA) systems revolutionizes wireless networks by enhancing signal strength, mitigating interference, and optimizing spectral efficiency. The cooperative NOMA (CNOMA) framework, empowered by IRS technology, further promises enhanced performance, robustness, and scalability for next-generation wireless networks as compared to NOMA only systems. …”
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LIO-CSI: LiDAR inertial odometry with loop closure combined with semantic information. by Gang Wang, Saihang Gao, Han Ding, Hao Zhang, Hongmin Cai

“…Moreover, a registration based on a geometric feature is vulnerable to the interference of a dynamic object, resulting in a decline of accuracy. …”
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An adaptive hexagonal deployment model for resilient wireless sensor networks in precision agriculture by Zhang Yinjun

“…The AFHSS mechanism dynamically adjusts frequency channels, mitigating interference and fortifying the network’s robustness against external disruptions. …”
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Prediction using inelastic constitutive artificial neural networks for impact of dead-time on inverters in wireless power transfer systems by Mr. Franklin J, Dr. Pongiannan R K

“…Dead time in Wireless Power Transfer Systems (WPTS) affects inverters in several ways, including higher switching losses, electromagnetic interference, and system instability, necessitating innovative mitigation strategies for enhanced efficiency and reliability. …”
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Deep learning-enhanced signal detection for communication systems. by Yang Liu, Peng Liu, Yu Shi, Xue Hao

“…Overall, the research model has achieved significant results in improving detection accuracy, optimizing real-time performance, and reducing resource consumption. …”
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Three-dimensional localization algorithm of mobile nodes based on received signal strength indicator-angle of arrival and least-squares support-vector regression by Lieping Zhang, Huihao Peng, Jiajie He, Shenglan Zhang, Zuqiong Zhang

“…For example, the localization accuracy of the localization algorithm based on received signal strength indicator will be reduced sharply when affected by signal reflection, multipath propagation, and other interference factors. To solve the problem, a three-dimensional localization algorithm of mobile nodes was proposed in this article based on received signal strength indicator–angle of arrival and least-squares support-vector regression, which fused the ranging information of received signal strength indicator algorithm and the angle of arrival algorithm and optimized the estimated distance of unknown nodes. …”
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Hybrid POF-VLC Systems: Recent Advances, Challenges, Opportunities, and Future Directions by Rola Abdallah, Mohamed Atef, Nasir Saeed

“…Hybrid Polymer Optical Fiber and Visible Light Communication (POF-VLC) systems are emerging as a promising solution for high-speed, interference-free connectivity, especially in environments where traditional RF communication is constrained. …”
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Reduced Graphene Oxide/β-Cyclodextrin Nanocomposite for the Electrochemical Detection of Nitrofurantoin by Al Amin, Gajapaneni Venkata Prasad, Venkatachalam Vinothkumar, Seung Joo Jang, Da Eun Oh, Tae Hyun Kim

“…Furthermore, the fabricated electrode exhibited good anti-interference ability, stability, precision, and real-time applicability for NFT detection in a wastewater sample. …”
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Multi-head deep Q-learning for continuous beamforming with selective MC-CDMA operation in V2X highway communications by Nguyen Huu Trung, Nguyen Thuy Anh, Fuqiang Liu

“…To ensure robust and adaptive performance under fast-varying conditions, we propose an integrated framework that combines resource block-based MC-CDMA modulation with dynamic beamforming optimized for complex propagation environments. A custom code mapper and resource element (RE) allocator are introduced to support interference-aware transmission and enhance signal robustness in dense deployment scenarios. …”
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Unlocking Superior MFH Performance Below Hergt’s Biological Safety Limit: SPION-Based Magnetic Nanoplatforms Deliver High Heating Efficiency at Low AMF by Atul Sudame, Dipak Maity

“…This study investigates the synthesis and optimization of SPIONs encapsulated in TPGS-stabilized PLGA nanoparticles (TPS-NPs) using a modified single emulsion solvent evaporation (M-SESE) method. …”
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The self supervised multimodal semantic transmission mechanism for complex network environments by Jiajun Zou, Zhiping Wan, Feng Wang, Shitong Ye, Shaojiang Liu

“…Abstract With the rapid development of intelligent transportation systems, the challenge of achieving efficient and accurate multimodal traffic data transmission and collaborative processing in complex network environments with bandwidth limitations, signal interference, and high concurrency has become a key issue that needs to be addressed. …”
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Feature Selection Using Pearson Correlation for Ultra-Wideband Ranging Classification by Gita Indah Hapsari, Rendy Munadi, Bayu Erfianto, Indrarini Dyah Irawati

“…These conditions cause signal attenuation, reflection, and interference, leading to decreased localization precision. …”
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Research on Fault Diagnosis Method for Marine Diesel Engines Based on Multi-Scale Attention Mechanism Transformer by Manyi Chen, Huibing Gan, Hangjie Wu

“…This multi-scale strategy enhances the extraction of detailed and coarse-grained features, improving the model’s capacity to detect and characterize complex diesel engine faults. Additionally, an optimized Nadam optimizer is employed to refine convergence speed and accuracy, surpassing the Adam-based baseline by 0.71%. …”
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Energy efficient multi hop clustering using Artificial Bee Colony metaheuristic in WSN by Shiwei Zhang, Xinghan Liu, Mohammad Trik

“…Parameters are automatically optimized using ABC to minimize energy imbalance and increase network lifetime.…”
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TCAINet an RGB T salient object detection model with cross modal fusion and adaptive decoding by Hong Peng, Yunfei Hu, Baocai Yu, Zhen Zhang

“…Specifically, the CA module enhances the model’s feature selection ability, while the CAF and AAD modules optimize the integration and processing of multimodal information. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…This paper addresses the issue of noise interference and variable working conditions in the production and machining environment, which lead to weak tool life features and reduced prediction accuracy. …”
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Discharge Experiment and Structure Optimisation Simulation of Impulse Sound Source by Xu Gao, Jing Zhou, Haiming Xie, Xiao Du

“…Additionally, the propagation of these waves in formations is prone to loss and noise interference, restricting detection to only a few tens of meters around the well. …”
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Early Warning for the Construction Safety Risk of Bridge Projects Using a RS-SSA-LSSVM Model by Gang Li, Ruijiang Ran, Jun Fang, Hao Peng, Shengmin Wang

“…Then, the LSSVM with the strongest nonlinear modelling ability was selected to build the bridge construction early-warning model and adopted the SSA to optimize the LSSVM parameter combination, improving the early warning accuracy. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…This study provides a new optimization approach for knowledge graph and semantic-driven recommendation systems, enabling more accurate capture of user preferences and alleviating the problem of noise interference.…”
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