Transformer-based multiple instance learning network with 2D positional encoding for histopathology image classification by Bin Yang, Lei Ding, Jianqiang Li, Yong Li, Guangzhi Qu, Jingyi Wang, Qiang Wang, Bo Liu

“…TMIL incorporates a 2D positional encoding module, based on the Transformer, to model positional information and explore correlations between instances. …”
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Fault Diagnosis Method of Permanent Magnet Synchronous Motor Demagnetization and Eccentricity Based on Branch Current by Zhiqiang Wang, Shangru Shi, Xin Gu, Zhezhun Xu, Huimin Wang, Zhen Zhang

“…However, in practical applications, the fault characteristics in current signals are relatively weak, leading to diagnostic performance that falls short of expected standards. To address this issue and improve diagnostic accuracy, this paper proposes a novel diagnostic method. …”
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TDNN achitecture with efficient channel attention and improved residual blocks for accurate speaker recognition by Wenzao Li, Sai Yao, Bing Wan, Linsong Xiao, Chengyu Hou, Yanchuan Zhong, Wengang Zhou

“…After multi-scale feature extraction, the Selective State Space (SSS) module is introduced to improve the model’s ability to capture temporal sequence features. …”
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Hyperspectral Reconstruction Method Based on Global Gradient Information and Local Low-Rank Priors by Chipeng Cao, Jie Li, Pan Wang, Weiqiang Jin, Runrun Zou, Chun Qi

“…To address this issue, we propose a hyperspectral reconstruction method based on global gradient information and local low-rank priors. …”
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SChanger: Change Detection From a Semantic Change and Spatial Consistency Perspective by Ziyu Zhou, Keyan Hu, Yutian Fang, Xiaoping Rui

“…To address the data scarcity issue, we develop a fine-tuning strategy called the semantic change network. …”
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DiffTST: Diff Transformer for Multivariate Time Series Forecast by Song Yang, Wenyong Han, Yaping Wan, Tao Zhu, Zhiming Liu, Shuangjian Li

“…Subsequently, the Differential Transformer module is employed to process the sequence features of these patches, alleviating the tendency of Transformer-based models to allocate excessive attention to irrelevant sequence information. …”
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A Method for Automatic Feature Points Extraction of Pelvic Surface Based on PointMLP_RegNet by Wei Kou, Rui Zhou, Hongmiao Zhang, Jianwen Cheng, Chi Zhu, Shaolong Kuang, Lihai Zhang, Lining Sun

“…PointMLP_RegNet, a modified PointMLP, was introduced to address this issue. It retains the feature extraction module of PointMLP but replaces the classification layer with a regression layer to predict the coordinates of feature points instead of conducting regular classification. …”
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Mining privacy-preserving association rules using transaction hewer allocator and facile hash algorithm in multi-cloud environments by D. Dhinakaran, S. Gopalakrishnan, D. Selvaraj, M.S. Girija, G. Prabaharan

“…However, in outsourced data for tasks like frequent itemset mining, privacy is an important issue. The difficulty is to secure sensitive data while delivering the insights of the data. …”
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YOLO-Ssboat: Super-Small Ship Detection Network for Large-Scale Aerial and Remote Sensing Scenes by Yiliang Zeng, Xiuhong Wang, Jinlin Zou, Hongtao Wu

“…YOLO-ssboat integrates the C2f_DCNv3 module to extract fine-grained features of small vessels while mitigating background interference and preserving critical target details. …”
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Embedding Trust in the Media Access Control Protocol for Wireless Networks by Chaminda Alocious, Hannan Xiao, Bruce Christianson, Joseph Spring

“…However, the potential for non-cooperative nodes exists, nodes that may purposefully misbehave in order to, for example, obtain extra bandwidth, conserve their resources, or disrupt network performance. This issue is further compounded when receivers such as Wi-Fi hotspots, normally trusted by other module nodes, also misbehave. …”
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MFHG-DDI: An Enhanced Hybrid Graph Method Leveraging Multiple Features for Predicting Drug–Drug Interactions by Xiang Li, Xiangmin Ji, Chengzhen Xu, Jie Hou, Xiaoyu Zhao, Guodong Peng

“…We employed an enhanced hybrid graph module that integrates a graph convolutional network, graph attention network, and global average pooling to learn latent features, ultimately applying a prediction function to predict DDIs. …”
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Marine motor fault diagnosis based on CEEMDAN and BRECAN under strong noise conditions by Renjie ZHU, Enzhe SONG, Chong YAO, Yun KE

“…ObjectiveThe background noise in the engine room during actual ship navigation leads to the poor accuracy in fault diagnosis methods. To address this issue, this paper proposes a ship motor fault diagnosis method based on complementary ensemble empirical mode decomposition (EEMD) with adaptive noise (CEEMDAN) and a Bayesian residual efficient channel attention network (BRECAN). …”
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Numerical study on PWR fuel rod cladding ballooning and burst behavior with the thermo-mechanical coupling finite element method by Xin Zhang, Gen Li, Runhua Gao, Xinhai Zhao, Peitao Yao

“…The ballooning behavior of fuel rod cladding is an important issue of nuclear reactor, which may initiate a severe nuclear reactor accident. …”
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Hierarchical cross-modal attention and dual audio pathways for enhanced multimodal sentiment analysis by D. Vamsidhar, Parth Desai, Aniket K. Shahade, Shruti Patil, Priyanka V. Deshmukh

“…Specifically, its main innovation is a dual audio pathway augmented with a dynamic gating module and a cross-modal self-attention layer that enables fine-grained interaction among modalities. …”
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MSLKSTNet: Multi-Scale Large Kernel Spatiotemporal Prediction Neural Network for Air Temperature Prediction by Feng Gao, Jiaen Fei, Yuankang Ye, Chang Liu

“…The spatiotemporal forecasting of temperature is a critical issue in meteorological prediction, with significant implications for fields such as agriculture and energy. …”
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Development of a Baby Cry Identification System Using a Raspberry Pi-Based Embedded System and Machine Learning by Mohcin Mekhfioui, Wiam Fadel, Fatima Ezzahra Hammouch, Oussama Laayati, Marouan Bouchouirbat, Nabil El Bazi, Amal Satif, Tarik Boujiha, Ahmed Chebak

“…The module analyzes audio techniques to capture, analyze, classify, and remotely monitor a baby’s cries. …”
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Pansharpening Based on Adaptive Spatial Detail Fusion and Injection Weights Refinement by Huan Dai, Yong Yang, Shuying Huang, Hangyuan Lu, Weiguo Wan, Kang Wang

“…First, a multistage intensity enhancement module is constructed to enhance the intensity component I of an MS image for spatial-spectral preservation. …”
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Fault detection algorithm for underground conveyor belt deviation based on improved RT-DETR by AN Longhui, WANG Manli, ZHANG Changsen

“…The method requires setting specific thresholds and is easily affected by environmental factors, resulting in slow detection speed and low accuracy. To address the issue, an underground conveyor belt deviation fault detection algorithm based on an improved real-time detection transformer (RT-DETR) was proposed. …”
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Screening differentially expressed genes between endometriosis and ovarian cancer to find new biomarkers for endometriosis by Zhenzhen Lu, Ying Gao

“…Due to its high recurrence rate, searching for potential therapeutic biomarkers involved in the pathogenesis of endometriosis is an urgent issue.Methods Due to the similarities between endometriosis and ovarian cancer, four endometriosis datasets and one ovarian cancer dataset were downloaded from Gene Expression Omnibus (GEO) database. …”
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A Remote Sensing Semantic Self-Supervised Segmentation Model Integrating Local Sensitivity and Global Invariance by Buxun Zhang, Xiaoyan Guo, Sen Yang

“…Self-supervised semantic segmentation is a crucial approach for addressing the issue of insufficient labeled data. However, traditional self-supervised learning methods designed for natural images are often unsuitable for remote sensing images, as they struggle to capture both local and global information simultaneously. …”
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