A Multi-Source Transfer Joint Matching Method for Inter-Subject Motor Imagery Decoding by Fulin Wei, Xueyuan Xu, Tianyuan Jia, Daoqiang Zhang, Xia Wu

“…The superiority of this framework is verified on two common public MI datasets from BCI competition IV. The average classification accuracy of the MSTJM and wMSTJ methods outperformed other state-of-the-art methods by at least 4.24% and 2.62% respectively. …”
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An interpretable machine learning method for fault diagnosis of oil-immersed transformers based on edge inference by Dong Hu, Yong Yang, Hao Dai, Chao Tang, Jufang Xie

“…However, the inherent “black box” nature of these models limits interpretability, and traditional methods that upload local data to central servers raise data security concerns. To address these issues, this study proposes an interpretable fault diagnosis model for edge deployment. …”
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A new verification approach for nowcasting based on intensity and spatial-temporal feature correction by Jun Liu, Tong Zhang, Yuanzhao Chen, Rui Wang, Mingjie Wang, Shuxin Wang, Ting Xu, Chunyang Zhao, Xunlai Chen

“…The current conventional verification method for nowcasting uses a binary classification event verification method, which exists with double punishment, leading to low scoring issues. …”
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A DeBERTa-Based Semantic Conversion Model for Spatiotemporal Questions in Natural Language by Wenjuan Lu, Dongping Ming, Xi Mao, Jizhou Wang, Zhanjie Zhao, Yao Cheng

“…Then, based on the encoding results, it performs classification and semantic parsing of spatiotemporal questions to achieve question intent recognition and conversion to Cypher query language. …”
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Complementary Local–Global Optimization for Few-Shot Object Detection in Remote Sensing by Yutong Zhang, Xin Lyu, Xin Li, Siqi Zhou, Yiwei Fang, Chenlong Ding, Shengkai Gao, Jiale Chen

“…In addition, a Teacher-Guided Dual-Branch Head (TG-DH) is developed to supervise both classification and regression using pseudo-labels generated by the teacher model to further stabilize and enhance the semantic features of novel classes. …”
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Deep Learning-Based Real-Time 6D Pose Estimation and Multi-Mode Tracking Algorithms for Citrus-Harvesting Robots by Hyun-Jung Hwang, Jae-Hoon Cho, Yong-Tae Kim

“…Particularly, fruit harvesting relies heavily on manual labor, leading to issues with an unstable labor supply and rising costs. …”
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Bacteriophage-based strategies for biocontrol and treatment of infectious diseases by Trinh Thi Trang Nhung, Swati Verma, Saravanaraman Ponne, Gautam Kumar Meghwanshi, Thomas Schön, Rajender Kumar

“…Among the novel aspects, phage display-based strategies are used for epitope mapping and the development of immunotherapy. A recent classification system has been developed based on the recent sequencing methods and bioinformatic tools. …”
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Harnessing infrared thermography and multi-convolutional neural networks for early breast cancer detection by Omneya Attallah

“…Despite being considered the gold standard for breast cancer evaluation, conventional mammography possesses inherent drawbacks, including accessibility issues, especially in rural regions, and discomfort associated with the procedure. …”
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GLAI-Net: Global–Local Awareness Integrated Network for Semantic Change Detection in Remote Sensing Images by Qing Ding, Fengyan Wang, Mingchang Wang, Ying Zhang, Gui Cheng

“…Recently, multitask networks have become the main paradigm for SCD, but their detection performance is still affected by limited multi-scale feature extraction and insufficient cross-task information interaction. To address these issues, we propose a global–local awareness integrated network (GLAI-Net) for SCD in remote sensing images. …”
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Design Optimization of a Marine Propeller Shaft for Enhanced Fatigue Life: An Integrated Computational Approach by Víctor Tuninetti, Diego Martínez, Sunny Narayan, Brahim Menacer, Angelo Oñate

“…Analytical calculations based on classification society rules determined acceptable shaft diameter ranges, considering torsional shear stress limits for SAE 1030 steel. …”
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BERT-based network for intrusion detection system by Yong Yang, Xing Peng

“…By treating network traffic as a “language,” our approach resolves issues that traditional methods struggle with while being scalable and adaptable to various network environments and attack patterns.…”
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An algorithm for the management of chronic obstructive pulmonary disease patients in units of internal medicine by Ombretta Para, Carmen Stabile, Donato Cinquepalmi, Maria Sandra Magnoni, Francesco Nasso, Flavio Tangianu, Mauro Silingardi, Antonella Valerio, Dario Manfellotto, Francesco Dentali

“… Patients with acute exacerbations of chronic obstructive pulmonary disease (COPD) are often hospitalized in internal medicine units (IMUs), and their management is challenging due to a multiplicity of factors affecting the outcome, such as correct patient classification, appropriate pharmacologic therapy, patient discharge, and follow-up. …”
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MobNas ensembled model for breast cancer prediction by Tariq Shahzad, Sheikh Muhammad Saqib, Tehseen Mazhar, Muhammad Iqbal, Ahmad Almogren, Yazeed Yasin Ghadi, Mamoon M. Saeed, Habib Hamam

“…Thus, while substantial progress has been made in developing machine learning algorithms, deep learning, and transfer learning models, issues with diagnostic accuracy and minimizing diagnostic errors persist. …”
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Echoes From the Void: Detecting DNS Tunneling With Blackhole Features in Encrypted Scenarios With High Accuracy by Wafa S. Alorainy

“…A five-fold cross-validation with a random forest classifier achieved 99.9% classification accuracy, a 99.9% F1 score, and 100% precision and recall. …”
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Prolonged length of stay for acute hospital admissions as the increasing of age: A nationwide population study for Taiwan's patients with cerebral palsy by Kuo-Liang Chiang, Chin-Yin Huang, Hueng-Chuen Fan, Fang-Chuan Kuo

“…The reasons specific to children included orthopedic issues; ear, nose, and throat problems; and urinary tract infections (UTIs). …”
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Cloud Computing Resource Scheduling Algorithm Based on Unsampled Collaborative Knowledge Graph Network by Haichuan Sun, Liang Gu, Chenni Dong, Xin Ma, Zeyu Liu, Zhenxi Li

“…A cloud computing resource scheduling algorithm based on sampled collaborative knowledge graph network is designed to address the issues of lag in the process of cloud computing resource scheduling, high overall load rate, and large transient amplitude and phase errors. …”
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A secure and efficient deep learning-based intrusion detection framework for the internet of vehicles by Hasim Khan, Ghanshyam G. Tejani, Rayed AlGhamdi, Sultan Alasmari, Naveen Kumar Sharma, Sunil Kumar Sharma

“…Abstract This swift growth in Internet of Vehicle (IoV) networks has created serious security issues, primarily in intrusion detection due to the fact that these are complex, dynamic, and large-scale networks. …”
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Optimization and Enhancement of Oral Bioavailability of Dabrafenib as Nanobubbles Using Quality by Design Approach by Bijili Vijaya Laxmi, Darna Bhikshapathi, Sailaja Rao

“…Background: The use of Poly (lactic-co-glycolic acid) (PLGA) nanobubbles (NBs) aimed at functioning as a delivery system that encounter solubility issues for drugs like dabrafenib (DBF), which belonged to the Biopharmaceutical Classification System (BCS) class II category. …”
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Early and Late Fusion for Multimodal Aggression Prediction in Dementia Patients: A Comparative Analysis by Ioannis Galanakis, Rigas Filippos Soldatos, Nikitas Karanikolas, Athanasios Voulodimos, Ioannis Voyiatzis, Maria Samarakou

“…Aggression in patients with dementia poses significant caregiving and clinical issues. In this work, fusion approaches—Early Fusion and Late Fusion—were compared to classify aggression using audio and visual signals. …”
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Intelligent fault diagnosis of rotating machinery based on improved hybrid dilated convolution network for unbalanced samples by Qianqian Zhang, Caiyun Hao, Ying Wang, Kun Zhang, Haitao Yan, Zhongwei Lv, Qiuxia Fan, Chan Xu, Lei Xu, Zhuang Wen, Weihuang Liu

“…As a result, there are frequently significantly fewer defect samples obtained than healthy samples, and the data samples that are obtained typically have a high noise level. To overcome these issues, this paper introduces a novel approach termed the improved hybrid dilated convolution network (HDCN) to address these limitations and enhance classification accuracy. …”
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