A Detection Method for Conveyor Belt Damage with Small Size and Low Contrast by HAN Yajie, HAO Xiaoli, NIU Baoning, XUE Jindong

“…Aiming at the low contrast between damage and background, first, the coordinate attention mechanism is embedded in the deep network layer of the backbone network to enhance the model′s attention to damage characteristics and reduce the interference of background noise. Second, the accurate decoupled head is designed to improve detection accuracy by solving the contradiction between classification and location requirements for features. …”
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GRU2-Net: Global response double U-shaped network for lesion segmentation in ultrasound images by Xiaokai Jiang, Xuewen Ding, Jinying Ma, Chunyu Liu, Xinyi Li

“…Furthermore, we design a Multi-Scale Linear Attention Gate to refine skip connections by emphasizing salient features and suppressing redundancy, thereby mitigating noise interference and improving decoding efficiency. …”
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Cognitive constraints in bilingual processing—an entropy-based discrimination between translation and second language production by Chuanhong Tang, Danfeng Huang, Danfeng Huang, Andrew K. F. Cheung

“…Specifically, word and part-of-speech n-gram features are computed in the machine learning models to compare the three productions. …”
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A novel edge crop method and enhanced YOLOv5 for efficient wind turbine blade damage detection by Boyu Feng, Bo Liu, Li Song, Yongyan Chen, Xiaofeng Jiao, Baiqiang Wang

“…This procedure effectively mitigates the interference from complex background features and augments the utilization of image pixels. …”
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Identification of Defects in Low-Speed and Heavy-Load Mechanical Systems Using Multi-Fusion Analytic Mode Decomposition Method by Yanlei Liu, Kun Zhang, Miaorui Yang, Xu Zhang, Yonggang Xu

“…In view of the higher requirements of modern machinery for multi-sensor information acquisition and fusion technology, this paper proposes a novel multi-fusion analytic mode decomposition (MFAMD) method to separate and demodulate fault features in signals. In low-speed and heavy-load equipment, the signals collected by multiple sensors contain unknown and unequal fault features and interference. …”
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Fault Diagnosis for Rolling Bearings Under Complex Working Conditions Based on Domain-Conditioned Adaptation by Xu Zhang, Gaoquan Gu

“…To address the issue of low diagnostic accuracy caused by noise interference and varying rotational speeds in rolling bearings, a fault diagnosis method based on domain-conditioned feature correction is proposed for rolling bearings under complex working conditions. …”
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Research status and future prospects on ultraviolet Ad-Hoc network by GUO Jia, YUAN Renzhi, WANG Siming, PENG Mugen, YANG Chuang

“…These include self-interference issues in the physical layer due to the full-duplex mode, node energy consumption and synchronization problems in the data link layer’s media access control (MAC) protocol, and poor network connectivity and scalability of routing protocols in the network layer. …”
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ROLLING BEARING FAULT DIAGNOSIS BASED ON LMD AND ICA by CHEN ChongYang, XIONG BangShu, HUANG JianPing, MO Yan, LI XinMin

“…For the problem of Local Mean Decomposition（ LMD） was easily affected by noise interference when in the extraction of fault features,a rolling bearing fault diagnosis method which based on LMD and Independent Component Analysis（ ICA） was proposed. …”
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基于峭度和小波包能量特征的齿轮箱早期故障诊断及抗噪研究 by 陈水宣, 邹俊, 易际明, 谢丹

“…It is difficult to dectect the gear fault signal in early stage because of weak intensity and strong interference.To solve this problem,a method for incipient fault diagnosis of gears is proposed based on vibration signals using kurtosis,wavelet packet energy features extraction and discriminative weighted probabilistic neural networks.The method uses the advantages of the kurtosis statistics on the impact load feature extraction method in feature extraction and reserves the merit of wavelet packet decomposition in extracting energy characteristics of various frequency bands.Meanwhile,the discriminative weight probabilistic neural network（DWPNN） is introduced to solve the problem of the scene noise pollution.The experimental results show that the method achieves a good identification of incipient faults of gears and has strong robustness against noise disturbance.…”
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A novel approach to palm vein image segmentation combining multi-scale convolution and swin-transformer networks by Wenshun Sheng, Ziling Zheng, Hanzhi Zhu

“…A feature fusion module suppresses background interference by integrating cross-layer information. …”
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Wireless May Benefit Blockchain by Seungmo Kim, Junsung Choi

“…It features a comprehensive analytical framework that mathematically derives metrics quantifying the scalability and the level of decentralization of the three consensus mechanisms, constituting a key contribution of this work. …”
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Idiopathic Hypertrophy of the Masseter Muscle by S. S. Rawat, Kamla Sharma

“…A short summary of the literature on masseter hypertrophy has been given along with the findings from our own series of eight cases. The salient features of our findings are that the condition is perhaps related to some type of work hypertrophy, in our cases bitel-nut chewing; that only for marked cosmetic deformity is surgical interference indicated; we prefer the extraoral appre ach with excision of the external portion of the muscle, which may be combined with excision of the hyperostotic bone where necessary; ordinary histological examination does not reveal any changes in the muscle histology but special technique like silver staining could help. …”
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Research on VoNR voice wireless optimization strategy by Xinchao ZANG, Ronglin LI

“…There are two 5G voice solutions, EPS Fallback and VoNR.In the early stage of 5G network construction, 5G base station coverage rate and terminal penetration rate were not high, so EPS Fallback was used as a 5G voice transition solution.At present, with the deployment of 2.6 GHz and 700 MHz networks, the SA network achieves independent networking, and VoNR will be the main solution for 5G voice.In order to actively respond to the deployment of VoNR and analyze the advantages of VoNR from multiple dimensions, an in-depth research on VoNR features, parameters, and application scenarios were conducted, VoNR wireless strategy deployment was formulated, for uplink weak field, interference, large traffic characteristics of all kinds of scenarios functions such as deployment and optimization to provide suggestion and scheme, and prepares for VoNR’s official commercial use.…”
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Face recognition using decision fusion of multiple sparse representation-based classifiers by Biao TANG, Wei JIN, Randi FU, Fei GONG

“…A new approach to face recognition combining decision fusion and multiple sparse representation-based classifiers was proposed to improve the robustness of the traditional methods.Different types of facial features were extracted,followed by training multiple sparse representation sub-classifiers,and then decision fusion was used to obtain the recognition result of the system.The significant advantage of the proposed scheme lines in that the final recognition results were not driven by averaging outputs of multiple sub-classifiers,but driven by combining multiple outputs via weighted fusion method.In particular,the fusion weights were adaptively determined by an iterative pro-cedure according to the different classification performance of each sub-classifier.Extensive experiments on Yale B,JAFFE and AR face databases demonstrate that the proposed approach is much more effective than state-of-the-art methods in dealing with lighting changes,expression changes and face occlusion and multi factor mixed interference.…”
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Tea disease identification based on ECA attention mechanism ResNet50 network by Lanting Li, Yingding Zhao

“…By optimizing the ResNet50 architecture, adopting a multi-layer small convolution kernel strategy to enhance feature extraction capabilities, and introducing the ECA attention mechanism to focus on key features, the model achieves a 93.06% accuracy rate in tea disease identification, representing a 3.18% improvement over the original model, demonstrating industry-leading performance advantages. …”
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Face recognition using decision fusion of multiple sparse representation-based classifiers by Biao TANG, Wei JIN, Randi FU, Fei GONG

“…A new approach to face recognition combining decision fusion and multiple sparse representation-based classifiers was proposed to improve the robustness of the traditional methods.Different types of facial features were extracted,followed by training multiple sparse representation sub-classifiers,and then decision fusion was used to obtain the recognition result of the system.The significant advantage of the proposed scheme lines in that the final recognition results were not driven by averaging outputs of multiple sub-classifiers,but driven by combining multiple outputs via weighted fusion method.In particular,the fusion weights were adaptively determined by an iterative pro-cedure according to the different classification performance of each sub-classifier.Extensive experiments on Yale B,JAFFE and AR face databases demonstrate that the proposed approach is much more effective than state-of-the-art methods in dealing with lighting changes,expression changes and face occlusion and multi factor mixed interference.…”
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Resting Posture Recognition Method for Suckling Piglets Based on Piglet Posture Recognition (PPR)–You Only Look Once by Jinxin Chen, Luo Liu, Peng Li, Wen Yao, Mingxia Shen, Longshen Liu

“…This strengthens the model’s ability to capture and differentiate subtle posture features. Additionally, in the post-processing stage, the relative positions between sows and piglets are utilized to filter out piglets located outside the sow region, eliminating interference from sow nursing behaviors in resting posture recognition, thereby ensuring the accuracy of posture classification. …”
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Cross Layer Power Allocation by Graph Neural Networks in Heterogeneous D2D Video Communications by Shu-Ming Tseng, Sz-Tze Wen, Chao Fang, Mehdi Norouzi

“…Therefore, in this paper, we propose the video-optimized heterogeneous interference graph neural network (VD-HIGNN) as a cross-layer D2D resource allocation method for video transmission, which introduces the following contributions: 1) joint source encoder rate and beamforming/power control, 2) incorporating video rate distortion function parameters from the application layer into the node features, and 3) changing the loss function from data rate to Peak-Signal-to-Noise-Ratio (PSNR), a function of video rate distortion and a metric of video quality. …”
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SE-TransUNet-Based Semantic Segmentation for Water Leakage Detection in Tunnel Secondary Linings Amid Complex Visual Backgrounds by Renjie Song, Yimin Wu, Li Wan, Shuai Shao, Haiping Wu

“…Using a hybrid leakage dataset partitioned by k-fold cross-validation, the roles of SE-Block and ViT modules were examined through ablation experiments, and the model’s attention mechanism for leakage features was analyzed via Score-CAM heatmaps. Results indicate: (1) SE-TransUNet achieved mean values of 0.8318 (IoU), 0.8304 (Dice), 0.9394 (Recall), 0.8480 (Precision), 0.9733 (AUC), 0.8562 (MCC), 0.9218 (F1-score), and 6.53 (FPS) on the hybrid dataset, demonstrating robust generalization in scenarios with dent shadows, stain interference, and faint leakage traces. (2) Ablation experiments confirmed both modules’ necessity: The baseline model’s IoU exceeded the variant without the SE module by 4.50% and the variant without both the SE and ViT modules by 7.04%. (3) Score-CAM heatmaps showed the SE module broadened the model’s attention coverage of leakage areas, enhanced feature continuity, and improved anti-interference capability in complex environments. …”
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AG-Yolo: Attention-Guided Yolo for Efficient Remote Sensing Oriented Object Detection by Xiaofeng Wang, Chengshan Han, Liang Huang, Ting Nie, Xin Liu, Hao Liu, Mingxuan Li

“…An attention branch is further introduced to generate attention maps from shallow input features, guiding feature aggregation to focus on foreground objects and suppress complex background interference. …”
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