Mathematical Modeling and Optimization of Supply Chain for Bioethanol by Yunzile Dzhelil, T. Mihalev, B. Ivanov, D. Dobrudzhaliev

“…Their environmental performance is also a good feature in environmental protection. …”
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Designing the outsourcing model in central government organizations by Mahnaz Moradi, Morteza Ghasemi, Maryam Majidi, Gholamreza Amjadi

“…Also, information technology outsourcing has seven components of information technology system performance, providing system support services, green information technology, application gap of information technology, strategic importance, features of the organization, and the project and the characteristics of the project suppliers. …”
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An interpretable machine learning model to predict hospitalizations by Hagar Elbatanouny, Hissam Tawfik, Tarek Khater, Anatoliy Gorbenko

“…Leveraging a comprehensive dataset sourced from the Mexican government, various supervised learning algorithms including Random Forest, Gradient Boosting, Support Vector Machine, K-Nearest Neighbors, and Multilayer Perceptron are trained and evaluated to discern factors contributing to hospitalizations. Feature importance analysis and dimensionality reduction techniques are employed to enhance models predictive performance. …”
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Machine learning to evaluate the effects of non-clinical social determinant features in predicting colorectal Cancer mortality in a medically underserved Appalachian population by Aisha Montgomery, Ravi Vadapalli, Frank A. Dinenno, Josh Schilling, Praduman Jain, Aasems Jacob, David Chism, Anil Shanker

“…It is demonstrated that the ML model performs better when SDOH features are included, and that rurality significantly impacts CRC survival in Appalachia. …”
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Value Chain Modeling in Digital Strategic Management by I. M. Stepnov, Yu. A. Kovalchuk

“…Within the defned task for modeling it is technically possible to create the models which perform the operation-by-operation analysis of interaction in the value added chains. …”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…Accordingly, the remote sensing imagery sample datasets have become crucial in ensuring robust training models with satisfactory performance across various AI (Artificial Intelligence)-enabled remote sensing applications. …”
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Machine learning based multi-stage intrusion detection system and feature selection ensemble security in cloud assisted vehicular ad hoc networks by C. Christy, A. Nirmala, A. Mary Odilya Teena, A. Isabella Amali

“…A new method for improving VANET security, a multi-stage Lightweight IntrusionDetection System Using Random Forest Algorithms (MLIDS-RFA), focuses on feature selection and ensemble models based on machine learning (ML). …”
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Semantic Segmentation of Archaeological Features on Public Lands: Case Study of Historical Cotton Terraces within the Piedmont National Wildlife Refuge, Georgia, USA by Claudine Gravel-Miguel, Grant Snitker, Jayde N. Hirniak, Katherine Peck, Alex Fetterhoff

“…It combines Python scripts that fine-tune models to recognize archaeological features in lidar-derived imagery with denoising QGIS steps that improve the predictions’ performance and applicability. …”
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Comparing traditional natural language processing and large language models for mental health status classification: a multi-model evaluation by Thomas Kallstenius, Andrea Johansson Capusan, Gerhard Andersson, Adam Williamson

“…While fine-tuning for three epochs yielded optimal results, further training led to overfitting and decreased performance. This study demonstrates the significant benefits of applying advanced text preprocessing and feature engineering techniques to traditional NLP models, alongside fine-tuning LLMs, such as GPT-4o-mini, for mental health classification tasks. …”
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An Improved Ant Colony Optimization to Uncover Customer Characteristics for Churn Prediction by Ibrahim Al-Shourbaji, Abdoh Jabbari, Shaik Rizwan, Mostafa Mehanawi, Phiros Mansur, Mohammed Abdalraheem

“…Customer churn prediction is a critical task in the telecommunication (telecom) industry, where accurate identification of customers at risk of churning plays a vital role in reducing customer attrition. Feature selection (FS) is an integral part in Machine Learning (ML) models which aims to improve performance and reduce computational time (CT). …”
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DRST-Net: A Dual-Branch Feature Fusion Network Combining ResNet50 and Swin Transformer for Welding Light Strip Recognition by Yuan Lu, Qingjiu Huang

“…The model performs especially well in complex environments with noisy backgrounds and intricate details. …”
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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…MobileNet, VGG16, NasNetMobile, DenseNet201, InceptionV3, and Xception were experimented with in the feature extraction and performance evaluation process. …”
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Expression levels of β1, β3 integrins and MMP2 and features of morphological heterogeneity of pancreatic ductal adenocarcinoma associated with distant metastasis by Yu. Yu. Rakina, N. V. Krakhmal, D. S. Pismenny, A. V. Zavyalov, S. V. Vtorushin, S. G. Afanasyev, M. V. Zavyalova

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DOG: An Object Detection Adversarial Attack Method by Jinpeng Li, Xiaoyu Ji, Wenyuan Xu, Yushi Cheng

“…The DOG leverages the C&W adversarial example generation framework, DAG model activation value selection, and R-AP object label resetting. …”
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Machine Learning Enabled Prediction of Biologically Relevant Gene Expression Using CT‐Based Radiomic Features in Non‐Small Cell Lung Cancer by Shrey S. Sukhadia, Christoph Sadée, Olivier Gevaert, Shivashankar H. Nagaraj

“…Combining the data from two cohorts post binarization (of gene expression) or batch normalization (of radiomic features) in each cohort proved to be a better approach as compared to training the model on one cohort and validating on the other. …”
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Preoperative prediction of lymph node metastasis in patients with ovarian cancer using contrast-enhanced computed tomography-based intratumoral and peritumoral radiomics features by Jing Zhang, Qiyuan Li, Haoyu Liang, Yao Wang, Li Sun, Qingyuan Zhang, Chuanping Gao

“…The DCA results showed that the combined radiomics signature had better clinical application than the clinical model and the radiomics nomogram.ConclusionsA CT-based combined radiomics signature incorporating intratumoral and peritumoral radiomics features can predict LNM in patients with OC before surgery.…”
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FEATURES OF MELTING IN THE THERMOCHEMICAL PLUME CONDUIT AND HEAT AND MASS TRANSFER DURING CRYSTALLIZATION DIFFERENTIATION OF BASALTIC MELT IN A MUSHROOM-SHAPED PLUME HEAD by A. A. Kirdyashkin, A. G. Kirdyashkin, N. V. Surkov

“…The features of melting in the plume conduit are elucidated on the basis of the phase diagram of the CaO-MgO-Al2O3-SiO2 model system. …”
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AI-Enhanced Photovoltaic Power Prediction Under Cross-Continental Dust Events and Air Composition Variability in the Mediterranean Region by Pavlos Nikolaidis

“…A distinguishing feature of this work is the integration of cross-continental dust events and diverse atmospheric parameters into a structured forecasting model. …”
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Enhancing Visitor Forecasting with Target-Concatenated Autoencoder and Ensemble Learning by Ray-I Chang, Chih-Yung Tsai, Yu-Wei Chang

“…Previous autoencoders for feature selection do not simultaneously incorporate feature and target information simultaneously, potentially limiting their effectiveness in improving predictive performance. …”
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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

“…Initially, four deep learning models—DenseNet161, ResNet152, and MobileNetV3 variants—are explored to determine the most suitable feature extraction method. …”
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