Neonicotinoid Residues in Tea Products from China: Contamination Patterns and Implications for Human Exposure by Yulong Fan, Hongwei Jin, Jinru Chen, Kai Lin, Lihua Zhu, Yijia Guo, Jiajia Ji, Xiaming Chen

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Enhanced residual attention-based subject-specific network (ErAS-Net): facial expression-based pain classification with multiple attention mechanisms by Mahdi Morsali, Aboozar Ghaffari

“…Through transfer learning and multiple attention mechanisms, the proposed deep learning model is designed to mimic human perception of facial expressions, thereby enhancing its pain recognition ability and capturing the unique features of each individual’s facial expressions based on their specific patterns. …”
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Epileptic seizure detection in EEG signals via an enhanced hybrid CNN with an integrated attention mechanism by Sakorn Mekruksavanich, Wikanda Phaphan, Anuchit Jitpattanakul

“…Nevertheless, the intricate characteristics of electroencephalography (EEG) signals, noise, and the want for real-time analysis require enhancement in the creation of dependable detection approaches. Despite advances in machine learning and deep learning, capturing the intricate spatial and temporal patterns in EEG data remains challenging. …”
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Sliding window based rare partial periodic pattern mining algorithms over temporal data streams by K. Jyothi Upadhya, Ronan Lobo, Mini Shail Chhabra, Aman Paleja, B. Dinesh Rao, Geetha M., Prachi Sisodia, Bolusani Akshita Reddy

“…A limited amount of literature demonstrated how periodicity is essential in mining low-support rare patterns. In addition, attention must be placed on temporal datasets that analyze crucial information about the timing of pattern occurrences and stream datasets to manage high-speed streaming data. …”
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UAV rice panicle blast detection based on enhanced feature representation and optimized attention mechanism by Shaodan Lin, Deyao Huang, Libin Wu, Zuxin Cheng, Dapeng Ye, Haiyong Weng

“…Results The ConvGAM model, leveraging the ConvNeXt-Large backbone network and the Global Attention Mechanism (GAM), achieves outstanding performance in feature extraction, crucial for detecting small and complex disease patterns. …”
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PARS: A Position-Based Attention for Rumor Detection Using Feedback From Source News by Hanieh Asadi G., Ali Hamzeh, Niloofar Mozafari

“…A post reordering mechanism is applied to reflect the actual dissemination pattern, ensuring that position-sensitive attention captures the most relevant signals. …”
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Real time blood detection in CCTV surveillance using attention enhanced InceptionV3 by Adnan Khalil, Fakhre Alam, Dilawar Shah, Irshad khalil, Shujaat Ali, Muhammad Tahir

“…The model is further optimized through a proposed attention module that intensifies attention to small and minute blood-related patterns, even under challenging conditions such as occlusions, motion blur, and low visibility. …”
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Explainable AI for zero-day attack detection in IoT networks using attention fusion model by Deepa Krishnan, Swapnil Singh, Vijayan Sugumaran

“…The proposed attention fusion classification model utilizes both long-term and short-term attention mechanisms to capture temporal patterns and protocol-specific features, which improves the differentiation between benign and malicious traffic. …”
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DFANet: A Deep Feature Attention Network for Building Change Detection in Remote Sensing Imagery by Peigeng Lu, Haiyong Ding, Xiang Tian

“…Second, we introduce a GatedConv module to improve the network’s capability for building edge detection. Finally, Transformer is introduced to capture long-range dependencies across bitemporal images, enabling the network to better understand feature change patterns and the relationships between different regions and land cover categories. …”
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Few-shot network intrusion detection method based on multi-domain fusion and cross-attention. by Congyuan Xu, Donghui Li, Zihao Liu, Jun Yang, Qinfeng Shen, Ningbing Tong

“…To address this challenge, we propose a novel few-shot intrusion detection method that integrates multi-domain feature fusion with a bidirectional cross-attention mechanism. …”
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An Attention-Enhanced 3D-CNN Framework for Spectrogram-Based EEG Analysis in Epilepsy Detection by Ziaullah Khan, Aakanksha Dayal, Hee-Cheol Kim

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Detection of Student Engagement via Transformer-Enhanced Feature Pyramid Networks on Channel-Spatial Attention by A. Naveen, I. Jeena Jacob, Ajay Kumar Mandava

“…One of the most important aspects of contemporary educational systems is student engagement detection, which involves determining how involved, attentive, and active students are in class activities. …”
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Securing Industrial IoT Environments: A Fuzzy Graph Attention Network for Robust Intrusion Detection by Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa

“…Ablation studies confirm the essential roles of both fuzzy logic and attention mechanisms in boosting detection accuracy. …”
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Power transmission system’s fault location, detection, and classification: Pay close attention to transmission nodes by Chiagoziem C. Ukwuoma, Dongsheng Cai, Olusola Bamisile, Ejiyi J. Chukwuebuka, Ekong Favour, Gyarteng S.A. Emmanuel, Acen Caroline, Sabirin F. Abdi

“…The model's capacity to manage unusual data input and unidentified application situations is improved by the inclusion of multi-scale attention. Furthermore, it enables the model to precisely pinpoint fault areas by identifying patterns and connections among system parts, concentrating on specific areas or nodes. …”
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Novel developmental analyses identify longitudinal patterns of early gut microbiota that affect infant growth. by Richard A White, Jørgen V Bjørnholt, Donna D Baird, Tore Midtvedt, Jennifer R Harris, Marcello Pagano, Winston Hide, Knut Rudi, Birgitte Moen, Nina Iszatt, Shyamal D Peddada, Merete Eggesbø

“…We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem developing), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. …”
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Spatial Identification and Distribution Pattern of the Complexity of Rural Poverty in China Using Multisource Spatial Data by Zhenyu Qi, Jinghu Pan, Yaya Feng

“…At the same time, the flexible spatial scanning detection method was used to detect the differentiation mechanism of poverty spatial patterns.…”
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Investigation of Preknowledge Cheating via Joint Hierarchical Modeling Patterns of Response Accuracy and Response Time by Ebru Balta, Celal Deha Dogan

“…This study explores the rate of Type I error in detecting preknowledge cheating behaviors, the power of the Kullback-Leibler (KL) divergence measure, and the L person fit statistic under various conditions by modeling patterns of response accuracy (RA) and RT using a joint hierarchical model. …”
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Windows Malware Detection via Enhanced Graph Representations with Node2Vec and Graph Attention Network by Nisa Vuran Sarı, Mehmet Acı, Çiğdem İnan Acı

“…Therefore, developing innovative detection frameworks that can effectively analyze and interpret these complex patterns has become critical. …”
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Design of an Improved Model for Anomaly Detection in CCTV Systems Using Multimodal Fusion and Attention-Based Networks by V. Srilakshmi, Sai Babu Veesam, Mallu Shiva Rama Krishna, Ravi Kumar Munaganuri, Dulam Devee Sivaprasad

“…Long Short-Term Memory (LSTM) can capture long-range dependencies in sequential data, while Temporal Convolutional Network (TCN) efficiently models temporal patterns using convolutional layers and Transformer Networks fathom the relative importance of temporal features against one another through self-attention, thus improving their detection accuracy for anomalies that happen over a long duration. …”
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Enhanced detection of accounting fraud using a CNN-LSTM-Attention model optimized by Sparrow search by Peifeng Wu, Yaqiang Chen

“…This paper proposes an enhanced approach to fraud detection by integrating convolutional neural networks (CNN) and long short-term memory (LSTM) networks, complemented by an attention mechanism to prioritize relevant features. …”
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