Security Trade-Off and Energy Efficiency Analysis in Wireless Sensor Networks by Damian Rusinek, Bogdan Ksiezopolski, Adam Wierzbicki

“…Moreover, an advanced communication module is proposed as an extension of the QoP-ML language, which enhances the abilities to analyze complex wireless sensor networks. …”
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Lightweight joint source-channel coding method based on MIMO-CSI prediction by YU Chuangyu, XU Yanyan, PAN Shaoming

“…Finally, to adapt the semantic information to the time-varying quality of MIMO channels, a channel adaptive module was designed. This module assigns appropriate transmission subchannels and time slots to different features based on their importance, thereby enhancing the semantic accuracy of image reconstruction. …”
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Rough-and-Refine Model for Scene Graph Generation by Li Junliang, Lv Shirong, Li Wei

“…The model represented in the first row of the table, which excludes all four modules, is equivalent to the Rough Part, showing an average decrease of 24.9%.ConclusionsTo address the issue of insufficient predicate representation, a scene graph generation method based on a Rough-and-Refine network is proposed. …”
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S²PNet: An Interactive Learning Framework for Addressing Spatial–Spectral Heterogeneity in H² Imagery Classification by Shuai Zhang, Yonghua Jiang, Chengjun Wang, Meilin Tan, Bin Du, Feng Tian

“…First, a multistage spectral purification module is designed to purify noisy information and mitigate spectral heterogeneity, achieving interaction between spectral optimization and classification. …”
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Building Surface Defect Detection Based on Improved YOLOv8 by Xiaoxia Lin, Yingzhou Meng, Lin Sun, Xiaodong Yang, Chunwei Leng, Yan Li, Zhenyu Niu, Weihao Gong, Xinyue Xiao

“…Methodologically, the first step involves a normalization-based attention module (NAM). This module minimizes irrelevant features and redundant information and enhances the salient feature expression of cracks, delamination, and other defects, improving feature utilization. …”
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MFFCI–YOLOv8: A Lightweight Remote Sensing Object Detection Network Based on Multiscale Features Fusion and Context Information by Sheng Xu, Lin Song, Junru Yin, Qiqiang Chen, Tianming Zhan, Wei Huang

“…Last, we employ the multiscale fusion lightweight neck module for more efficient multiscale feature fusion, preventing the loss of small objects. …”
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CIA-UNet: An Attention-Enhanced Multi-Scale U-Net for Single Tree Crown Segmentation by Jiapeng Duan, Chuanzhao Tian, Wansi Liu, Lixiang Cao, Teng Feng, Xiaomin Tian

“…The Convolutional Block Attention Module (CBAM) is employed to increase the weight of key features, and mitigate false segmentation caused by feature confusion. …”
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YOLOv11-BSD: Blueberry maturity detection under simulated nighttime conditions evaluated with causal analysis by Runqing Zhang, Wenhui Dong, Pengzhi Hou, Huiqin Li, Xiongwei Han, Qingqiang Chen, Fuzhong Li, Xiaoying Zhang

“…To address these challenges, this study proposes an improved model, YOLOv11-BSD: it enhances the C3k2 module with a Bi-directional Feature Attention Mechanism to strengthen feature representation capabilities; enhances the C2PSA module using an Squeeze-and-Excitation mechanism to heighten focus on critical channel features; optimizes the PANet feature fusion pathway to improve multi-scale feature integration; and introduces the DySample module to resolve feature adaptation issues during upsampling. …”
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Enhancing Crack Segmentation Network with Multiple Selective Fusion Mechanisms by Yang Chen, Tao Yang, Shuai Dong, Like Wang, Bida Pei, Yunlong Wang

“…Initially, a star feature enhancement module is designed to resolve the issues of insufficient local feature processing and feature redundancy during the feature extraction process. …”
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Implications for developing global health education in China: evidence from an undergraduate teamwork with role-play by Chen Chen, Taufique Joarder, Chenkai Wu, Yi Cai, Hong Chen, Junxiong Pang

“…However, their inadequate background knowledge of global health issues hindered their ability to undertake the tasks in depth. …”
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Deep nested U-structure network with frequency attention for building semantic segmentation by Khaled Moghalles, Zaid Al-Huda, Dalal AL-Alimi, Yeong Hyeon Gu, Mugahed A. Al-antari

“…We have introduced a novel approach to address these issues: an end-to-end residual U-structure embedded within a U-Net, enhanced by a frequency attention module and a hybrid loss function. …”
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Brightness adjustment and contrast matching in low-light underwater images using feedforward neural networks by Zahra Raeisi, Reza Ahmadi Lashaki, Maryam Deldadehasl, Alireza Golkarieh, Maral mirza Mohammadi

“…Light scattering and light absorption are two fundamental issues in improving the quality of underwater images. …”
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YOLOv8n-RF: A Dynamic Remote Control Finger Recognition Method for Suppressing False Detection by Yawen Wang, Gaofeng Wang, Yining Yao

“…This algorithm utilizes the CRVB-DSConvEMA module in the feature extraction network, adopts the SPPF-DSConvEMA module in the downsampling process, and introduces BiFPN in the Neck layer. …”
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A Fractal Curve-Inspired Framework for Enhanced Semantic Segmentation of Remote Sensing Images by Xinhua Wang, Botao Yuan, Zhuang Li, Heqi Wang

“…The classification and recognition of features play a vital role in production and daily life; however, the current semantic segmentation of remote sensing images is hampered by background interference and other factors, leading to issues such as fuzzy boundary segmentation. To address these challenges, we propose a novel module for encoding and reconstructing multi-dimensional feature layers. …”
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Multi-Scale Convolutional Attention and Structural Re-Parameterized Residual-Based 3D U-Net for Liver and Liver Tumor Segmentation from CT by Ziwei Song, Weiwei Wu, Shuicai Wu

“…By incorporating a structural re-parameterized residual module (ELANRes) and a multi-scale convolutional attention module (MSCA), the network significantly improves feature extraction and boundary optimization, particularly excelling in segmenting small targets. …”
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Liver segmentation network based on detail enhancement and multi-scale feature fusion by Lu Tinglan, Qin Jun, Qin Guihe, Shi Weili, Zhang Wentao

“…The MSFF module enhances the capture of global features, thus improving the accuracy of the liver segmentation model. …”
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A Novel Framework for Remote Sensing Image Synthesis with Optimal Transport by Jinlong He, Xia Yuan, Yong Kou, Yanci Zhang

“…Remote sensing images (RSIs) are characterized by large intraclass variance and small interclass variance, which pose significant challenges for image synthesis. To address these issues, we design and incorporate two distinct attention modules into our GAN framework. …”
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Multi-phase attention network for face super-resolution. by Tao Hu, Yunzhi Chen

“…The above two attention modules form the multi-phase attention mechanism. …”
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Investigation of thermal-mechanical performance of dual-chip SiC power devices based on Cu clip interconnection by LIAO Linjie, FAN Yi, MEI Xiaoyang, WANG Liancheng

“…This leads to high parasitic inductance and reliability issues, limiting the development of silicon carbide (SiC) power devices. …”
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MDCFVit-YOLO: A model for nighttime infrared small target vehicle and pedestrian detection. by Huiying Zhang, Qinghua Zhang, Yifei Gong, Feifan Yao, Pan Xiao

“…An MDCFVit-YOLO model based on the YOLOv8 algorithm is proposed to address issues in nighttime infrared object detection such as low visibility, high interference, and low precision in detecting small objects. …”
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