The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Therefore, this paper proposes a financial fraud detection model based on Stacking ensemble learning algorithm, which integrates many basic learners such as logical regression (LR), decision tree (DT), random forest (RF), Gradient Boosting Tree (GBT), support vector machine (SVM) and neural network (NN), and introduces feature importance weighting and dynamic weight adjustment mechanism to improve the model performance. …”
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Deep learning-based multi-criteria recommender system for technology-enhanced learning by Latifat Salau, Hamada Mohamed, Yunusa Simpa Abdulsalam, Hassan Mohammed

“…To evaluate its performance, the model is tested on two multi-criteria datasets: ITM-Rec (TEL domain) and Yahoo Movies (non-TEL domain). …”
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Prediction of Shear Capacity of FRP Reinforced Concrete Beams Using Deep Neural Networks Based on Hyperparameter Optimization by Mohammed Sharif

“…The results indicate that DNNs performed better than regression models in predicting shear capacity.…”
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A Garbage Detection and Classification Method Based on Visual Scene Understanding in the Home Environment by Yuezhong Wu, Xuehao Shen, Qiang Liu, Falong Xiao, Changyun Li

“…The ESA attention mechanism is added to the backbone network part of the YOLOv5 network, aiming to improve the feature extraction ability of the network, combining with the built multimodal knowledge graph to form the YOLOv5-Attention-KG model, and deploying it to the service robot to perform real-time perception on the items in the scene. …”
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Prognosis of COVID-19 Using Artificial Intelligence: A Systematic Review and Meta-analysis by Saeed Reza Motamedian, Negin Cheraghi, Sadra Mohaghegh, Elham Babadi Oregani, Mahrsa Amjadi, Parnian Shobeiri, Niusha Solouki, Nikoo Ahmadi, Yassine Bouchareb, Arman Rahmim

“…These studies also demonstrate that combining patient demographic, clinical data, laboratory tests and radiomic features improves model performances. …”
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Multiomics integration and machine learning reveal prognostic programmed cell death signatures in gastric cancer by Zihao Bai, Hao Wang, Jingru Han, Jia An, Zhaocong Yang, Xuming Mo

“…This study applied multiomics approaches, integrating transcriptomic, epigenetic, and somatic mutation data, with consensus clustering algorithms to classify GC molecular subtypes and assess their biological and immunological features. A machine learning model was developed to create the Gastric Cancer Multi-Omics Programmed Cell Death Signature (GMPS), targeting PCD-related genes. …”
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Risk-factor differences for nonsuicidal self-injury and suicide attempts in Mexican psychiatric patients by Fresán A, Camarena B, González-Castro TB, Tovilla-Zarate CA, Juárez-Rojop IE, López-Narvaez ML, González-Ramón AE, Hernandez-Díaz Y

“…Comparison analyses between groups were performed and a logistic regression model used to determine the factors associated with nonsuicidal with self-injury behavior and suicidal behavior.Results: Different predictive factors were observed for nonsuicidal self-injury and suicidal behavior. …”
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Theoretical Insights into the Impact of Pyrrole and Imidazole Substituents on the BODIPY Chromophore by Patrycja Piękoś, Paweł Lipkowski, Wim Dehaen, Robert Wieczorek, Aleksander Filarowski

“…Computational studies were carried out in order to reveal the most effective method of modeling of the spectral features of fluorescent BODIPY dyes. …”
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phylospatial: An R package for spatial phylogenetic analysis with quantitative community data by Matthew M. Kling

“…While abundance data are partially supported by existing PD tools, these lack features such as geospatial data integration and flexible null model analysis. …”
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Recognition Method of Corn and Rice Crop Growth State Based on Computer Image Processing Technology by Li Tian, Chun Wang, Hailiang Li, Haitian Sun

“…The traditional image capturing and processing models have problems of large image segmentation error, excessive feature extraction time, and poor recognition output. …”
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An instructional emperor pigeon optimization (IEPO) based DeepEnrollNet for university student enrolment prediction and retention recommendation by Sunil Kumar Sharma

“…The framework integrates advanced preprocessing techniques for both numeric and textual data. Feature extraction is performed with statistical measures for numeric data, and advanced text techniques like GloVe embeddings, Latent Dirichlet Allocation (LDA) for topic modeling, and SentiWordNet for sentiment analysis. …”
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Histogram-based gradient boosting machine with SHAP-driven interpretability for predicting intensity of urban heat Island effect by Nhat-Duc Hoang

“…The input features include topographical, spatial, and urban morphological factors. …”
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Expanding and improving analyses of nucleotide recoding RNA-seq experiments with the EZbakR suite. by Isaac W Vock, Justin W Mabin, Martin Machyna, Alexandra Zhang, J Robert Hogg, Matthew D Simon

“…The fastq2EZbakR pipeline can assign reads to a diverse set of genomic features (e.g., genes, exons, splice junctions), and EZbakR can perform analyses on any combination of these features. …”
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Global channel attention boosted active millimeter wave image object detection by Jiang Tiantian, Ye Xueyi, Li Gang, Yang Menghao, Chen Huahua

“…The results demonstrate that both for array image dataset and line sweep image dataset, the detection model enhances the attention of hidden objects feature and improves the detection performance on the basis of meeting the security real-time performance.…”
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Machine Learning-Based Alfalfa Height Estimation Using Sentinel-2 Multispectral Imagery by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Rami Albasha, Md Saifuzzaman, Maxime Leduc

“…Several feature selection strategies were utilized and compared with the situation where all features are used. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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Fault Diagnosis of the Traction System Based on Wavelet Analysis and Deep Belief Network by TANG Lizhe, LI Shan, ZHAN Yanhao, JIANG Ping

“…Finally, the recording off-line fault data of locomotive was used to test and verify the performance of our model. Results suggest that our method enables diagnosing the fault of locomotive traction system with high accuracy.…”
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Soil moisture retrieval and spatiotemporal variation analysis based on deep learning by Zihan Zhang, Jinjie Wang, Jianli Ding, Jinming Zhang, Liya Shi, Wen Ma

“…The optimal model was then used to perform spatiotemporal mapping of soil moisture. …”
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An artificial intelligence approach to palaeogeographic studies: a case study of the Late Ordovician brachiopods of Laurentia by Akbar Sohrabi

“…In order to measure the reliability of the neural network model, the mean square error performance function was used. …”
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Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework by Ravikiran Keshavamurthy, Karl T Pazdernik, Colby Ham, Samuel Dixon, Samantha Erwin, Lauren E Charles

“…ResultsWhile no single best model was suitable for all disease, region, and country combinations, our ensemble technique selects the best-performing model for each given scenario to achieve the closest prediction. …”
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