A Diffusion-Based Detection Model for Accurate Soybean Disease Identification in Smart Agricultural Environments by Jiaxin Yin, Weixia Li, Junhong Shen, Chaoyu Zhou, Siqi Li, Jingchao Suo, Jujing Yang, Ruiqi Jia, Chunli Lv

Get full text

Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation by Quentin Malé, Corentin J. Lapeyre, Nicolas Noiray

“…Third, a CNN is trained to approximate the filtered burning rates as a function of LES scalar quantities: progress variable, local equivalence ratio, and flame thickening due to filtering. …”
Get full text

Energy management strategy for hybrid electric vehicle based on improved PPO algorithm by Chao MA, Tong SUN, Lei CAO, Kun YANG, Wenjing HU

“…In order to effectively explore the environment and learn more efficient strategies,the strategy entropy was added to the loss function to promote the intelligence to strike a balance between exploration and utilization and to avoid premature convergence of strategies to local optimal solutions. …”
Get full text

GBsim: A Robust GCN-BERT Approach for Cross-Architecture Binary Code Similarity Analysis by Jiang Du, Qiang Wei, Yisen Wang, Xingyu Bai

“…Recent advances in graph neural networks have transformed structural pattern learning in domains ranging from social network analysis to biomolecular modeling. …”
Get full text

Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8 by Jiang Liu, Jingxin Yu, Changfu Zhang, Huankang Cui, Jinpeng Zhao, Wengang Zheng, Fan Xu, Xiaoming Wei

Get full text

Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). …”
Get full text

Bearing Fault Diagnosis Based on IPOA-VMD and SSA-HKELM by Baoxian Chang, Xing Zhao, Dawei Guo, Siyu Zhao, Jiyou Fei, Hua Li, Xiaodong Liu

“…A novel comprehensive indicator is introduced as the fitness function during the parameter selection phase of IPOA. …”
Get full text

Yours Truly: A Credibility Framework for Effortless LLM-Powered Fact Checking by Vallidevi Krishnamurthy, Varshini Balaji

Get full text

Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…Comparative evaluations on benchmark test functions demonstrate that the improved algorithm (CDMOS) outperforms the original DMO in optimization performance, convergence precision, and overall stability, achieving an average improvement of 53.5% in convergence accuracy and 35.1% in solution stability across 29 benchmark functions. …”
Get full text

Pneumothorax detection and segmentation from chest X-ray radiographs using a patch-based fully convolutional encoder-decoder network by Jakov Ivan S. Dumbrique, Jakov Ivan S. Dumbrique, Reynan B. Hernandez, Reynan B. Hernandez, Juan Miguel L. Cruz, Ryan M. Pagdanganan, Prospero C. Naval

“…Ablation studies further reveal that using a mixed Tversky and Focal loss function significantly improves performance compared to using solely the Tversky loss. …”
Get full text

An Iterative Pseudo Label Generation framework for semi-supervised hyperspectral image classification using the Segment Anything Model by Zheng Zhao, Guangyao Zhou, Qixiong Wang, Jiaqi Feng, Hongxiang Jiang, Guangyun Zhang, Yu Zhang

“…Hyperspectral image classification in remote sensing often encounters challenges due to limited annotated data. Semi-supervised learning methods present a promising solution. However, their performance is heavily influenced by the quality of pseudo labels. …”
Get full text

EEG-Based Emotion Detection Using Roberts Similarity and PSO Feature Selection by Mustafa Hussein Mohammed, Mustafa Noaman Kadhim, Dhiah Al-Shammary, Ayman Ibaida

“…Traditional machine learning classifiers machine learning such as k-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), Logistic Regression (LR), and Random Forest (RF), often struggle to accurately capture both linear and nonlinear patterns in EEG signals and face limitations in handling high-dimensional datasets. …”
Get full text

P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…Secondly, after analyzing the image set characteristics to be detected in this research, the point-line distance bounding box loss function is utilized to calculate the coordinate distance of the prediction box and target box, and aimed at improving detection speed. …”
Get full text

Deformable Feature Fusion and Accurate Anchors Prediction for Lightweight SAR Ship Detector Based on Dynamic Hierarchical Model Pruning by Yue Guo, Shiqi Chen, Ronghui Zhan, Wei Wang, Jun Zhang

Get full text

Fault Diagnosis of Semi-Supervised Electromechanical Transmission Systems Under Imbalanced Unlabeled Sample Class Information Screening by Chaoge Wang, Pengpeng Jia, Xinyu Tian, Xiaojing Tang, Xiong Hu, Hongkun Li

“…Secondly, a cost-sensitive function driven by data imbalance is constructed to address the class imbalance problem in unlabeled sample screening, adaptively adjusting the weights of different class samples during model training to guide the training of the supervised model. …”
Get full text

AED-Net: A High-Resolution Remote Sensing Image Road Extraction Method Integrating Atrous Spatial Pyramid Pooling and Efficient Channel Attention Mechanism by Jintong Ren, Lizhi Liu, Zixuan Xia, Yang Liu

“…We propose a road extraction model named AED-Net, which employs a lightweight MobileNet v2 as the feature extractor, combines the multi-scale feature extraction capability of ASPP with an encoder-decoder structure, and integrates an ECA mechanism to enhance feature learning ability. During the training process, the BCE-DL loss function is adopted to optimize model performance. …”
Get full text

iKcr-DRC: prediction of lysine crotonylation sites in proteins based on a novel attention module and DenseNet by Xin Wei, Xin Wei, Xin Wei, Siqin Hu, Jian Tu, Muhammad Akmal Remli, Muhammad Akmal Remli

“…Increasing evidence has linked Kcr to the pathogenesis of major diseases such as cancer, highlighting the importance of accurately identifying Kcr sites for understanding disease mechanisms and normal cellular function.MethodsIn this study, we present a novel deep learning-based computational model, named iKcr-DRC, for the accurate prediction of lysine crotonylation sites. …”
Get full text

MSUD-YOLO: A Novel Multiscale Small Object Detection Model for UAV Aerial Images by Xiaofeng Zhao, Hui Zhang, Wenwen Zhang, Junyi Ma, Chenxiao Li, Yao Ding, Zhili Zhang

Get full text

Tracking Long-Term Ozone Pollution Dynamics in Chinese Cities with Meteorological and Emission Attribution by Hongrui Li, Xiaoyong Liu, Zijian Liu, Mengyang Li, Tong Wu, Peicheng Li, Peng Zhou

Get full text

Multi-omics analysis of the effects of pla2g4a on the prognosis of various cancers and its experimental validation in breast cancer cell lines by Yao Qian, Quan Yuan, Hao Yu, Rongjie Ye, Ming Niu, Feng Liu

“…Methods Download cancer-related data from databases such as UCSC Xena and ExMdb, use LASSO Cox regression and various machine learning algorithms to screen genes associated with BC survival, and perform functional and pathway enrichment analysis. …”
Get full text