Trends of climate variability and its association with farmers’ perceptions of climate change in Gassera district, southeastern Ethiopia by Henok W/Yohannes Aniye, Tsegaye Bekele, Walelign Worku

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DS-SwinUNet: Redesigning Skip Connection With Double Scale Attention for Land Cover Semantic Segmentation by Zirui Shen, Wanjie Liu, Sheng Xu

“…Experiments demonstrate that the transformer module proposed in this article improves the mIoU by 2.73% and 0.41% over the original Swin-UNet when the WHDLD and OpenEarthMap dataset are used as the segmentation task.…”
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MAF-CNER : A Chinese Named Entity Recognition Model Based on Multifeature Adaptive Fusion by Xuming Han, Feng Zhou, Zhiyuan Hao, Qiaoming Liu, Yong Li, Qi Qin

“…In order to fully test the entity recognition performance of this model, we compared the basic model and other mainstream models on Microsoft Research Asia (MSRA) and “China People’s Daily” dataset from January to June 1998. Experimental results show that this model is better than other models, with F1 values of 97.01% and 96.78%, respectively.…”
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Effects of infliximab biosimilar on retinal microvasculature in Crohn’s disease patients evaluated by optical coherence tomography angiography by Hesham M. El Mazar, El sayed E. El Shayeb, Asmaa M. Ebrahim, Ayatullah S.A. Motawe, Esraa S. El-Ghoubashy

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Ventral Prostate Fibrosis in the Akita Mouse Is Associated with Macrophage and Fibrocyte Infiltration by Sanghee Lee, Guang Yang, William Mulligan, Jerry Gipp, Wade Bushman

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A hybrid multiscale feature fusion model for enhanced cardiovascular arrhythmia detection by Md. Alamin Talukder

“…To mitigate class imbalance, we integrate SMOTE-Tomek Link (STL) and Random Oversampling (RO) strategies, ensuring robust representation of minority classes. Using the MIT-BIHA Dataset, our HMFF approach demonstrated substantial improvements over baseline models, which achieved an accuracy of 97.35% without feature fusion or data balancing. …”
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Numerical and Experimental Study on Energy Performance of Photovoltaic-Heat Pipe Solar Collector in Northern China by Hongbing Chen, Xilin Chen, Sai Chu, Lei Zhang, Yaxuan Xiong

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Enhanced SOC estimation method for lithium-ion batteries using Bayesian-optimized TCN–LSTM neural networks by Taotao Hu, Xiting Zhu, Maokai Tian

“…This study leverages the CALCE dataset and employs the random forest algorithm for dimensionality reduction, selecting voltage, discharge capacity, and discharge energy as key input features. …”
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Aspirin does not confer protection against major ischemic vascular events in patients diagnosed with rheumatoid arthritis by Chao Gao, Qiqi Hou, Hongxia Cao, Cangtuo Li, Xu Peng, Quanle Han, Shouling Wu, Kangbo Li

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Automated strabismus detection and classification using deep learning analysis of facial images by Mahsa Yarkheir, Motahhareh Sadeghi, Hamed Azarnoush, Mohammad Reza Akbari, Elias Khalili Pour

“…The proposed methodology leverages Convolutional Neural Networks (CNNs) to achieve high accuracy in both binary (strabismus vs. normal) and multi-class (eight-class deviation angle for esotropia and exotropia) classification tasks. The dataset for binary classification consisted of 4,257 facial images, including 1,599 normal cases and 2,658 strabismus cases, while the multi-class classification involved 480 strabismic and 142 non-strabismic images. …”
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Enhancing Abstractive Multi-Document Summarization with Bert2Bert Model for Indonesian Language by Aldi Fahluzi Muharam, Yana Aditia Gerhana, Dian Sa'adillah Maylawati, Muhammad Ali Ramdhani, Titik Khawa Abdul Rahman

“…The results of the model evaluation with the Liputan6 dataset using ROUGE-1, ROUGE-2, ROUGE-L, and BERTScore show that the proposed models have slight improvements over previous research models with Bert2Bert being better than Bert2Bert+Xtreme. …”
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Evaluation of Cells Cracks Impact on PV Module’s Performance by Christine Abdel Nour, Julien Dupuis, Paul Lefillastre, Axel Becker

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Improved YOLOv8n based helmet wearing inspection method by Xinying Chen, Zhisheng Jiao, Yuefan Liu

“…Experimental results on the expanded SHWD dataset demonstrate a 46.63% reduction in model volume, a 44.19% decrease in parameter count, a 54.88% reduction in computational load, and an improvement in mean Average Precision (mAP) to 93.8% compared to the original YOLOv8 algorithm. …”
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Older adults do not consistently overestimate their action opportunities across different settings by Isabel Bauer, Milena S. Gölz, Lisa Finkel, Maddalena Blasizzo, Sarah E. M. Stoll, Jennifer Randerath

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Data-Driven versus Köppen–Geiger Systems of Climate Classification by Vajira Lasantha, Taikan Oki, Daisuke Tokuda

“…We applied three clustering algorithms—k-means, ISODATA, and unsupervised random forest classification—to a dataset comprising 10 climatic variables and elevation; we then compared the obtained results with those from the Köppen–Geiger classification system. …”
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Declarative Terrain Modeling for Military Training Games by Ruben M. Smelik, Tim Tutenel, Klaas Jan de Kraker, Rafael Bidarra

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Analysis of 6G and B5G waveforms using hybrid MF-ED and ECG-ED spectrum sensing techniques by Arun Kumar, Aziz Nanthaamornphong

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Using an SGB Decision Tree Approach to Estimate the Properties of CRM Made by Biomass Pretreated with Ionic Liquids by Ya-Qing Gu, Tao Shu, Bin Ge, Ping Wang, Chen Gao, Hamid Heydari

“…That being the case, the dataset of the empirical output values was gathered and was randomly broken down into datasets for testing and training. …”
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Detection of UAV GPS Spoofing Attacks Using a Stacked Ensemble Method by Ting Ma, Xiaofeng Zhang, Zhexin Miao

“…First, we applied the synthetic minority oversampling (SMOTE) technique to the dataset to address the issue of class imbalance. Then, we used a CNN model to extract high-level features, combined with the original features as input for the stacked model. …”
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Residential Building Duration Prediction Based on Mean Clustering and Neural Network by Fanrong Ji, Yunquan Nan, Aifang Wei, Peiyan Fan, Zhaoyuan Luo, Xiaoqing Song

“…To enhance the predictive accuracy of the GA-BP neural network model, this research utilized an artificial bee colony (ABC)-improved K-means clustering algorithm to categorize 111 experimental datasets and 33 new datasets. The results indicated that the ABC-K-means-GA-BP model exhibited robust generalization capabilities and high predictive accuracy, with the fitness function showing optimal performance after 10, 15, and 35 generations, and the best validation performances recorded as 0.0019156, 0.00035905, and 0.0036914. …”
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