Investigation on the Role of Artificial Intelligence in Measurement System by P. A. Rezvy, Venkata Lakshmi Narayana Komanapalli

“…When transmitters measure process variables like temperature, pressure, flow, level, and quality in process industries, due to wear and tear, ambient conditions, process variations and electromagnetic interference, measured values always deviate from their actual value, and controlled variables will start to oscillate near setpoint. …”
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Small object detection in side-scan sonar images based on SOCA-YOLO and image restoration by Xiaodong Cui, Jiale Zhang, Lingling Zhang, Qunfei Zhang, Jing Han

“…Subsequently, the SPDConv (Space-to-Depth Convolution) module is incorporated to optimize the feature extraction network, effectively preserving discriminative characteristics of small targets. …”
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Development of a New Generation MWCNT/TiO2/TiO2‐Based Voltammetric Sensors for the Detection of Daptomycin in Soil and Different Water Samples by Nida Aydogdu Ozdogan, Ersin Demir, Sibel A. Ozkan

“…The surface characterization of the supported sensor was researched. Under optimized conditions, the linear range for the unmodified electrode and MWCNT/TiO2/TiO2/GCE was 0.2–1.0 μM and 0.06–5.0 μM, with detection limits of 0.086 μM and 0.001 μM. …”
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HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…SDDE-Module integrates spatial coordinate encoding and multidirectional convolution to reduce localization interference and overcome fixed sampling limitations for geometric deformations. …”
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Application research and effectiveness evaluation mechanism of hybrid intelligent algorithm integrating cognitive computing and deep learning for dynamically adjusting employee per... by Zhenlin Luo, Kebin Lu

“…Additional experiments involving noise interference indicate that the hybrid algorithm exhibits strong adaptability across varying data volumes. …”
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TSD-Net: A Traffic Sign Detection Network Addressing Insufficient Perception Resolution and Complex Background by Chengcheng Ma, Chang Liu, Litao Deng, Pengfei Xu

“…Additionally, we introduce a high-resolution detection branch and an Adaptive Dynamic Feature Fusion (ADFF) detection head to optimize cross-scale feature fusion and preserve critical details of small objects. …”
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An Aerodynamic Method for the Analysis of Isolated Horizontal-Axis Wind Turbines by Christian Masson, Idriss Ammara, Ion Paraschivoiu

“…In most existing performance-analysis methods, wind turbines are considered isolated so that interference effects caused by other rotors or by the site topology are neglected. …”
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A Study on the SLAM of Automotive Vehicles Using Bumper-Mounted Dual LiDAR by Jae-Hun Jang, Hyeong-Jun Kim, Kyung-Chang Lee

“…The proposed approach addresses these challenges by installing two LiDAR sensors at the ends of the vehicle bumper, optimizing the bumper-level FOV while minimizing interference from ground-level obstacles. …”
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Earthquake landslide detection method combining post-earthquake coherence increase and polarized vegetation damage by Haoran Liu, Ping Duan, Jia Li, Kang Zhao, Xinrui Yu

“…Therefore, a landslide detection method based on Combining Coherence Increase and Polarized Vegetation Damage (CCI-PVD) is proposed. The method first optimizes coherence data to minimize interference from decoherence factors, then introduces the dual-polarization radar vegetation index (DpRVI) to quantify post-earthquake vegetation damage, and finally uses wavelet transform (WT) to fuse this information with coherence increase data for improved detection accuracy. …”
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InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations by Hao Sun, Shaosen Li, Hao Li, Jianxiang Huang, Zhuqiao Qiao, Jialei Wang, Xincui Tian

“…To overcome these issues, we propose InvMOE, a novel fault detection algorithm with two core components: (1) invariant representation learning, which captures task-relevant features and mitigates background noise interference, and (2) multi-task training using a mixture of experts (MOE) framework to adaptively optimize feature learning across tasks and address label sparsity. …”
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AC-YOLO: A lightweight ship detection model for SAR images based on YOLO11. by Rui He, Dezhi Han, Xiang Shen, Bing Han, Zhongdai Wu, Xiaohu Huang

“…Furthermore, we propose an optimized bounding box regression loss function, the Minimum Point Distance Intersection over the Union (MPDIoU), which establishes multi-dimensional geometric metrics to accurately characterize discrepancies in overlap area, center distance, and scale variation between predicted and ground truth boxes. …”
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A study on the detection of conductor quantity in cable cores based on YOLO-cable by Xiaoguang Xu, Jiale Ding, Qi’an Ding, Qikai Wang, Yi Xun

“…Challenges such as high density, adhesion, and knife mark interference in cable conductor images make intelligent detection of conductor quantity particularly difficult. …”
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Modeling nitric oxide diffusion and plasticity modulation in cerebellar learning by Alessandra Maria Trapani, Carlo Andrea Sartori, Benedetta Gambosi, Alessandra Pedrocchi, Alberto Antonietti

“…This metaplasticity mechanism enhances the cerebellum's capacity to prioritize relevant inputs and mitigate learning interference, selectively modulating synaptic efficacy. …”
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Distortion and Compensation of Doppler Shift Characteristics of Vortex Beam Superposition Due to Rotating Rough Surfaces and Occlusion by Hongyang Wang, Zijing Zhang, Chengshuai Cui, Yuan Zhao

“…This research provides valuable insights for optimizing the precise measurement of rotational velocity in free-space RDE applications.…”
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A Novel Pseudo-Siamese Fusion Network for Enhancing Semantic Segmentation of Building Areas in Synthetic Aperture Radar Images by Mengguang Liao, Longcheng Huang, Shaoning Li

“…Finally, the model was optimized using the combined CE-Dice loss function to achieve superior performance. …”
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Improved Aerial Surface Floating Object Detection and Classification Recognition Algorithm Based on YOLOv8n by Lili Song, Haixin Deng, Jianfeng Han, Xiongwei Gao

“…The proposed algorithm introduces several key enhancements: (1) an enhanced HorBlock module to facilitate multi-gradient and multi-scale superposition, thereby intensifying critical floating object characteristics; (2) an optimized CBAM attention mechanism to mitigate background noise interference and substantially elevate detection accuracy; (3) the incorporation of a minor target recognition layer to augment the model’s capacity to discern floating objects of differing dimensions across various environments; and (4) the implementation of the WIoU loss function to enhance the model’s convergence rate and regression accuracy. …”
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Energy-efficient and reliable dual closed-loop DC control system for intelligent electric vehicle charging infrastructure. by Jun Li, Wan Chen, Xiaoqiong Zhu, Baoguo Zang, Cong Zhang, Hengxiao Hu, Ming Zhang, Wenbao Lei

“…Advanced computational intelligence and optimization techniques are highlighted as essential for tackling the complex challenges of modern EV charging systems. …”
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A Review of Research Progress on Separation and Purification Methods of Lithium Isotopes Using Cation Exchange Resin and Their Applications by Yilong SONG, Min LIU, Kejun HOU

“…Efficient separation of lithium from natural samples is essential due to potential interference from isobaric isotopes during analysis. …”
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Prediction of Urban Rail Transit Train Door Faults Based on FOA-BP Neural Network Model by WEN Kaiyue, QIU Weibin, DING Xianze, OU Hongxiang

“…[Result & Conclusion] The FIR filter+Hanning Window function method can effectively remove the interference of high-frequency noise and retain the low-frequency signal part that can correctly reflect the current change trend. …”
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Dynamic Aerial Small Target Detection Algorithm Based on Compound Zoom Scaling by Jiang Yuan, Zhu Gaofeng, Zhu Fenghua, Xiong Gang

“…However, during multi-angle imaging, UAVs often encounter challenges such as a low target pixel ratio and significant background interference, leading to missed detection and false detection. …”
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