Benchmark dataset on feeding intensity of the pearl gentian grouper(Epinephelus fuscoguttatus♀×E. lanceolatus♂) by Haijing Qin, Yunchen Tian, Jianing Quan, Xueqi Cong, Qingfei Li, Jinzhu Sui

“…In order to solve these problems, this study constructs a benchmark dataset of the feeding intensity of pearl gentian groupers in a factory circulating water environment, which is divided into feeding fish groups and fish aggregation areas by training Unet semantic segmentation network and compares standard clustering algorithms through clustering evaluation indexes to maximally select the optimal clustering method and the number of clusters that are suitable for this paper's dataset. …”
Get full text

A data-driven intelligent fault diagnosis framework for permanent magnet in PMSM by Huizhen Wang, Lei Wang, QiYa Wu, Haoying Pei, Lijun Diao

“…Second, fault diagnosis is carried out using the Genetic Algorithm-Support Vector Machine (GA-SVM) to accurately classify demagnetization faults. …”
Get full text

Emerging Strategies in Cartilage Repair and Joint Preservation by Mircea Adrian Focsa, Sorin Florescu, Armand Gogulescu

“…Future research should focus on refining integrated therapeutic protocols, conducting long-term clinical evaluations, and embracing personalised treatment models driven by artificial intelligence and predictive algorithms.…”
Get full text

A Fusion Method Incorporating Dual-Attention Mechanism and Transfer Learning Into UNet++ for Remote Sensing Image Coastline Extraction by Yanru Song, Bai Xue, Yueyue Meng, Xiang Qin, Yixiao Li, Qi Liu

“…Experimental results using the GID dataset for coastline segmentation demonstrate that compared to the latest algorithms such as PSPNet, CS-Deeplab v3+, and UNet++, the improved UNet++ network achieves lower boundary blurriness and more accurate segmentation results for coastlines, with fewer missed and false detections. …”
Get full text

SSMM: Semi-supervised manifold method with spatial-spectral self-training and regularized metric constraints for hyperspectral image dimensionality reduction by Bei Zhu, Yao Jin, Xuehua Guan, Yanni Dong

“…In the dimensionality reduction experiments, the overall accuracy of SSMM in any dimension is higher than that of other algorithms. In the classification experiments, the KAPPA coefficient of SSMM on the three data sets is improved by 1.41%, 0.61%, and 0.27% respectively. …”
Get full text

Online learning: Attitudes of Russian students by D. V. Rudenkin

“…The research materials can be used for the optimisation of Internet technologies implementation in the learning process and for the clarification of optimal algorithms for using such technologies when working with students.…”
Get full text

A Survey of Matrix Completion Methods for Recommendation Systems by Andy Ramlatchan, Mengyun Yang, Quan Liu, Min Li, Jianxin Wang, Yaohang Li

“…We focus on the mathematical models for matrix completion and the corresponding computational algorithms as well as their characteristics and potential issues. …”
Get full text

Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

“…This leads to significant economic and time costs, while the complexity of instruments and algorithms further raises the barrier for DLD design and optimization. …”
Get full text

Assessing the effects of therapeutic combinations on SARS-CoV-2 infected patient outcomes: A big data approach. by Hamidreza Moradi, H Timothy Bunnell, Bradley S Price, Maryam Khodaverdi, Michael T Vest, James Z Porterfield, Alfred J Anzalone, Susan L Santangelo, Wesley Kimble, Jeremy Harper, William B Hillegass, Sally L Hodder, National COVID Cohort Collaborative (N3C) Consortium

“…Then, the most accurate model is utilized by eXplainable Artificial Intelligence (XAI) algorithms to provide insights about the learned treatment combination impacts on the model's final outcome prediction.…”
Get full text

PCCN: Polarimetric Contexture Convolutional Network for PolSAR Image Super-Resolution by Lin-Yu Dai, Ming-Dian Li, Si-Wei Chen

“…Compared with state-of-the-art algorithms, experimental studies demonstrate and validate the effectiveness and superiority of the proposed method in both visualization examination and quantitative metrics. …”
Get full text

Anomaly Detection Using Explainable Random Forest for the Prediction of Undesirable Events in Oil Wells by Nida Aslam, Irfan Ullah Khan, Aisha Alansari, Marah Alrammah, Atheer Alghwairy, Rahaf Alqahtani, Razan Alqahtani, Maryam Almushikes, Mohammed AL Hashim

“…Accordingly, this study aimed to utilize ML techniques to reduce the time spent manually to establish rules that detect abnormalities in oil wells, leading to rapid and more precise detection. Four ML algorithms were utilized, including random forest (RF), logistic regression (LR), k-nearest neighbor (K-NN), and decision tree (DT). …”
Get full text

Optimizing Parkinson’s Disease Prediction: A Comparative Analysis of Data Aggregation Methods Using Multiple Voice Recordings via an Automated Artificial Intelligence Pipeline by Zhengxiao Yang, Hao Zhou, Sudesh Srivastav, Jeffrey G. Shaffer, Kuukua E. Abraham, Samuel M. Naandam, Samuel Kakraba

“…We developed a customized AI pipeline that incorporates twelve machine learning algorithms along with the four aggregation methods to detect Parkinson’s disease (PD) using multiple voice recordings from individuals available in the UCI Machine Learning Repository, which includes 756 voice recordings from 188 PD patients and 64 healthy individuals. …”
Get full text

Fully Automated Bone Age Assessment on Large-Scale Hand X-Ray Dataset by Xiaoying Pan, Yizhe Zhao, Hao Chen, De Wei, Chen Zhao, Zhi Wei

“…In the end, a variety of ensemble regression algorithms are applied to perform BAA. Besides, we choose a specific CNN to extract features and explain why we select that CNN. …”
Get full text

Mf-net: multi-feature fusion network based on two-stream extraction and multi-scale enhancement for face forgery detection by Hanxian Duan, Qian Jiang, Xin Jin, Michal Wozniak, Yi Zhao, Liwen Wu, Shaowen Yao, Wei Zhou

“…Current face forgery detection algorithms achieve high detection accuracy within-dataset. …”
Get full text

RETRACTED ARTICLE: Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients by Xiliang Zhang, Hanjie Guo, Xiaolong Li, Wei Tao, Xiaoqing Ma, Yuxing Zhang, Weidong Xiao

“…These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. …”
Get full text

Harnessing AI for Enhanced Weather Prediction: A Focus on Rainfall by Hira Farman, Noman Islam, Noman Hasany

“…The stacking model method seemed to be less optimal as the results derived from it were not as satisfactory as the ones achieved by the individual modelsAmong all the algorithms experimented with in this work, the best one was AdaBoost. …”
Get full text

Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit by Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

“…Experiments demonstrate that the optimization capacity of the IDBO algorithm is conspicuously superior to other intelligent optimization algorithms, and the IDBO-GRU algorithm surpasses the probabilistic neural network (PNN) and the GRU algorithm in the denoising accuracy of WFEM data. …”
Get full text

Efficient diagnosis of diabetes mellitus using an improved ensemble method by Blessing Oluwatobi Olorunfemi, Adewale Opeoluwa Ogunde, Ahmad Almogren, Abidemi Emmanuel Adeniyi, Sunday Adeola Ajagbe, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Asif Mehmood, Habib Hamam

“…The second phase employed the same algorithms alongside sequential ensemble methods—XG Boost, AdaBoostM1, and Gradient Boosting—using an average voting algorithm for binary classification. …”
Get full text

DualTransAttNet: A Hybrid Model with a Dual Attention Mechanism for Corn Seed Classification by Fei Pan, Dawei He, Pengjun Xiang, Mengdie Hu, Daizhuang Yang, Fang Huang, Changmeng Peng

“…Existing classification algorithms often suffer from limitations such as reliance on single information sources, constrained feature extraction capabilities, time consumption, low accuracy, and the potential to cause irreversible damage to seeds. …”
Get full text

3D Gravity Modeling of Complex Salt Features in the Southern Gulf of Mexico by Mauricio Nava-Flores, Carlos Ortiz-Aleman, Mauricio G. Orozco-del-Castillo, Jaime Urrutia-Fucugauchi, Alejandro Rodriguez-Castellanos, Carlos Couder-Castañeda, Alfredo Trujillo-Alcantara

“…By integrating results from different shape- and depth-source estimation algorithms, we built an initial model for the gravity anomaly inversion. …”
Get full text