Evaluation of combat effectiveness of unmanned aerial vehicle group in uncertain situations by SUN Pengyao, HUANG Yanyan, WANG Kaisheng, WU Kui

“…Secondly, design a combat method calculation module based on the various steps of the closed-loop combat environment, and combine the designed parameter setting module, battlefield situation generation and recording module, global progress controller, and combat data recording module to form a complete simulation system for unmanned aerial vehicle group observation and combat process. …”
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An object detection method in foggy weather based on novel feature enhancement and fusion by ZHU Lei, ZHAO Han, WANG Weili

“…Firstly, a novel feature enhancement module was constructed by means of multiple branch convolution in the Neck structure. …”
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ACLC-Detection: A Network for Remote Sensing Image Detection Based on Attention Mechanism and Lightweight Convolution by Shaodong Liu, Faming Shao, Chenshan Yang, Juying Dai, Jinhong Xue, Qing Liu, Tao Zhang

“…In addition, the C3k2 module in the neck fusion network part, where C3k = True, is replaced by the Convolutional Attention Module with Ghost Module (CAF-GM). …”
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Facial recognition targeted attack algorithm based on multiscale frequency decomposition and meta-learning by CAI Jun, HUANG Tianqiang, ZHENG Aokun, YE Feng, XU Chao

“…The meta-learning attack module addressed the overfitting and generalization issues present in previous white-box model ensemble attacks, thereby enhancing the efficacy and generalization ability of the generated adversarial examples. …”
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CF-YOLO for small target detection in drone imagery based on YOLOv11 algorithm by Chengcheng Wang, Yuqi Han, Chenggui Yang, Mingjie Wu, Zaiqing Chen, Lijun Yun, Xuesong Jin

“…Secondly, to overcome the problems of positional information deviation and feature redundancy during multi-scale feature fusion, we design a Feature Recalibration Module (FRM) and a Sandwich Fusion Module. We advocate for initial feature fusion through the FRM module, followed by feature enhancement using the Sandwich module. …”
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Applying a deployment strategy and data analysis model for water quality continuous monitoring and management by Fan-Lun Chen, Bo-Chieh Yang, Shu-Yi Peng, Tzu-Chi Lin

“…We designed an automatic continuous monitoring and early warning analysis module for automatic analysis of environmental and instrumental anomalies for decision makers, a “pollution source analysis module” utilizing static and dynamic cross-environment data to swiftly trace upstream pollution sources, and a “pollution hotspot analysis module” to evaluate the impact area of pollutants, and immediate response measures to achieve early warning and swift evaluation for the prevention of water pollution. …”
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Self-Supervised ECG Anomaly Detection Based on Time-Frequency Specific Waveform Mask Feature Fusion by Chongrui Tian, Fengbin Zhang

“…Specifically, the proposed method incorporates an auto-encoder module, a time-frequency mask module, and a contrastive learning module to extract masked time-frequency domain features of ECG signals. …”
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Museum Display Showcase Furniture System Research Based on Internet of Things Technology in Intelligent Environment by Jiaojiao Hu, Zhihui Wu, Lei Jin

“…Before the start of the experiment, we developed the overall design of the system, including three functional modules: temperature module, illumination module, and monitoring module. …”
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Improvement of RT-DETR model for ground glass pulmonary nodule detection. by Siyuan Tang, Qiangqiang Bao, Qingyu Ji, Tong Wang, Naiyu Wang, Min Yang, Yu Gu, Jinliang Zhao, Yuhan Qu, Siriguleng Wang

“…This article proposed an algorithm based on RT-DETR model with the following enhancement: 1) optimize the backbone network with FCGE blocks to increase the detection accuracy of small-sized and blurred edge nodules; 2) replace the AIFI module with HiLo-AIFI module to reduce redundant computation and improve the detection accuracy of pure ground glass pulmonary nodules and mixed ground glass pulmonary nodules; 3) replace the DGAK module with CCFF module to address the issue of capturing complex features and recognition of irregularly shaped ground glass nodules. …”
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Cross-Scale Spatial Refinement Graph Convolutional Network for Skeleton-Based Action Recognition by Chengyuan Ke, Sheng Liu, Zhenghao Ke, Yuan Feng, Shengyong Chen

“…In detail, we introduce an Attention-based Graph Pooling (AGP) module and a Cross-scale Feature Aggregation (CFA) module. …”
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Editors’ Note by Alberto Raposo, Cléber Corrêa

“… It is our pleasure to introduce you the second issue of JIS in 2017. This issue contains six papers of the Special Issue of the 15th Brazilian Symposium on Human Factors in Computing Systems (IHC 2016). …”
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Neutronics-thermal-hydraulics-material coupling study of lead-bismuth cooled reactor single rod based on oxidative corrosion characteristics by JI Xu, CHAI Xiang, ZHANG Lefu, LIU Xiaojing

“…Two coupling relationships in the coupling framework, i.e., (1) the neutron physics module for transferring power distribution to the thermal-hydraulics module, and the thermal-hydraulics module transferring temperature distribution to the neutron physics module; (2) the thermal-hydraulics module transferring temperature field and flow field to the oxidative corrosion module, and the oxidative corrosion module transferring oxide layer thickness distribution to the thermal-hydraulics module, were investigated. …”
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Underwater instance segmentation: a method based on channel spatial cross-cooperative attention mechanism and feature prior fusion by Zhiqian He, Lijie Cao, Lijie Cao, Xiaoqing Xu, Jianhao Xu

“…However, due to the inherent unique optical characteristics and high noise in underwater imagery, existing underwater instance segmentation models struggle to accurately capture the global and local feature information of objects, leading to generally lower detection accuracy in underwater instance segmentation models. To address this issue, this study proposes a novel Channel Space Coordinates Attention (CSCA) attention module and a Channel A Prior Attention Fusion (CAPAF) feature fusion module, aiming to improve the accuracy of underwater instance segmentation. …”
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Remote sensing image semantic segmentation network based on multi-scale feature enhancement fusion by Feiting Wang, Yuan Zhang, Qiongqiong Hu, Yu Zhu

“…We also propose a network structure that combines the C-ASPP module with the efficient channel attention (ECA) module in parallel, which performs better to extract contextual information. …”
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Enhancing Mirror and Glass Detection in Multimodal Images Based on Mathematical and Physical Methods by Jiyuan Qiu, Chen Jiang

“…However, these approaches often overlook the inherent limitations in the raw data caused by sensor deficiencies when facing mirrors and glass surfaces. To address this issue, we applied mathematical and physical methods, such as three-point plane determination and steady-state heat conduction in two-dimensional planes, along with an RGB enhancement module, to reconstruct RGB, depth, and thermal data for mirrors and glass in two publicly available datasets: an RGB-D mirror detection dataset and an RGB-T glass detection dataset. …”
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An unsupervised underwater image enhancement method based on generative adversarial networks with edge extraction by Yanfei Jia, Ziyang Wang, Liquan Zhao

“…Second, we propose an edge extraction block based on the Laplacian operator, an attention module with an edge extraction block, a multi-scale feature module, a novel upsampling module, and a new downsampling module. …”
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Triboelectric sensor gloves for real-time behavior identification and takeover time adjustment in conditionally automated vehicles by Xiao Lu, Haiqiu Tan, Haodong Zhang, Wuhong Wang, Shaorong Xie, Tao Yue, Facheng Chen

“…Here, we propose an intelligent takeover assistance system consisting of all-round sensing gloves, a non-driving behavior identification module, and a takeover time budget determination module. …”
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Adversarial Hierarchical-Aware Edge Attention Learning Method for Network Intrusion Detection by Hao Yan, Jianming Li, Lei Du, Binxing Fang, Yan Jia, Zhaoquan Gu

“…Specifically, AH-EAT includes three main modules: an edge-based graph attention embedding module, a hierarchical multi-grained detection module, and an adversarial training module. …”
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A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation by Qingxu Meng, Weijiang Wang, Hang Qi, Hua Dang, Minli Jia, Xiaohua Wang

“…We propose a 3D Spatial Shift Convolution and Pixel Shuffle (SSCPS) module, the SSCPS module present a low-parameter, low-computational-cost spatial shift convolution that overcomes the limitation of receptive field and improves the ability to extract global contextual information, Pixel Shuffle (PS) module extracts spatial information from feature dimensions, efficiently replacing traditional upsampling module. …”
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TLINet: A defects detection method for insulators of overhead transmission lines using partially transformer block. by Xun Li, Yuzhen Zhao, Yang Zhao, Zhun Guo, Yongming Zhang, Xiangke Jiao, Baoxi Yuan

“…Next, a Dynamic Downsampling Module (DyDown) is introduced to mitigate the issue of small-scale defect information blurring. …”
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