A Risk-Optimized Framework for Data-Driven IPO Underperformance Prediction in Complex Financial Systems by Mazin Alahmadi

“…To fill this gap, we present a practical framework utilizing tree-based ensemble learning, including Bagging Classifier (BC), Random Forest (RF), AdaBoost (Ada), Gradient Boosting (GB), XGBoost (XG), Stacking Classifier (SC), and Extra Trees (ET), with Decision Tree (DT) as a base estimator. …”
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Seismic Attribute Extraction and Application Based on the Gabor Wavelet Transform by Ran Xiong, Xuri Huang, Liang Guo, Xuan Zou, Haonan Tian

“…Finally, the validity of the extracted seismic attributes is verified by a field data. In this process, the seismic amplitude, spectrum data and Gabor attributes are used as sample data for the support vector machine (SVM), random forest (RF), extreme gradient boosting (XGBoost) models and deep residual shrinkage network (DRSN) for comparison. …”
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Fuzzy evaluation and explainable machine learning for diagnosis of rheumatic and autoimmune diseases by Mohammed Fadhil Mahdi, Arezoo Jahani, Dhafar Hamed Abd

“…Local interpretable model explanations (LIME) were used as explanations and significantly increased the transparency and reliability of the clinical decision-making process. The results show that the FDOSM yields gradient boosting with a 0.1333 score and a rank of 1, is the best model with an accuracy of 86.89%, precision of 87.35%, and kappa of 84.51%. …”
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A Comparative Analysis of Black-Box and Glass-Box Models for Poplar Plantation Mapping with Remote Sensing Data by M. Y. Ozturk, I. Colkesen

“…The study also assessed the most important features influencing the classification process. For this, while 15 features were selected employing the visual charts provided by EBM for interpreting the decision-making process, the SHAP technique was applied to examine the most prominent features in the XGBoost model structure. …”
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Enhanced photovoltaic efficiency through 3D-Printed COC/Al₂O₃ anti-reflective coversheets by Naif Almakayeel, Gobinath Velu Kaliyannan, Raja Gunasekaran, Rajasekar Rathanasamy

“…An optical loss is a crucial factor that impacts the performance of the photovoltaic conversion process. This loss occurs when incoming sunlight is reflected back on the outer layer of the photovoltaic cells. …”
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Visual Automatic Localization Method Based on Multi-level Video Transformer by Qiping ZOU, Botao LI, Saian CHEN, Xi GUO, Taohong ZHANG

“…This frame is critical feedback for adjusting the robotic arm, ensuring that the camera aligns precisely with the position where the focal length is accurately calibrated to the workpiece’s surface. This process guarantees the high quality of captured images and boosts the overall efficiency of the machining process. …”
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Estimation of Genetic Parameters for Body Weight and Its Stability in Huaxi Cows from Xinjiang Region by Ye Feng, Wenjuan Zhao, Xubin Lu, Xue Gao, Qian Zhang, Bin Zhang, Bao Wang, Fagang Zhong, Mengli Han, Zhi Chen

“…The analysis focused on four weight traits while considering non-genetic factors such as parity, season, year, and birth weight. Data were processed and corrected using a MIXED procedure and a multi-trait animal model. …”
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Creating electrochemical accessibility in covalent organic frameworks for uranium extraction via electrodeposition by Yanpei Song, Linxiao Hou, Pui Ching Lan, Zhiwei Xing, Qi Sun, Jia Lv, Jingwei Li, Daliang Zhang, Zhifeng Dai, Thamraa AlShahrani, Shengqian Ma

“…This strategy offers a blueprint for designing electrodes with better electronic access to active sites, boosting performance in electrically driven processes.…”
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Learning transactions representations for information management in banks: Mastering local, global, and external knowledge by Alexandra Bazarova, Maria Kovaleva, Ilya Kuleshov, Evgenia Romanenkova, Alexander Stepikin, Aleksandr Yugay, Dzhambulat Mollaev, Ivan Kireev, Andrey Savchenko, Alexey Zaytsev

“…Our method outperforms classical models, boosting accuracy by up to 20%.…”
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Online Face Detection and Recognition in a Video Stream by Maha Hasso Al-Ghurery, Manar Zidan Al-Abaji

“…Faces detection and recognition process received considerable attention during the past decade, it is still considered one of the most important studies in the field of Image Processing, Pattern Recognition, and Computer Vision, where it drew the attention of many researchers from both the academic and industrial environments because of the broad scope of its practical applications. …”
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DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…The pre-processing stage involves cropping images to retain the relevant maps, which were subjected to contrast enhancement to improve image quality. …”
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Retinal fundus imaging-based diabetic retinopathy classification using transfer learning and fennec fox optimization by Indresh Kumar Gupta, Shruti Patil, Supriya Mahadevkar, Ketan Kotecha, Awanish Kumar Mishra, Joel J.P.C. Rodrigues

“…Fennec Fox Optimization (FFO) fine-tunes the GRU hyperparameters, boosting classification accuracy, with its effectiveness demonstrated on benchmark datasets. 3. …”
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Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

“…First, NASA’s Fire Information for Resource Management System (FIRMS) dataset spanning +20 years is processed using a spatio-temporal clustering algorithm to create refined wildfire datasets. …”
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Bacterial Cellulose for Scalable and Sustainable Bio-Gels in the Circular Economy by Giovanni Venturelli, Federica Villa, Mariagioia Petraretti, Giuseppe Guagliano, Marinella Levi, Paola Petrini

“…They offer considerable structural properties and process reproducibility compared to other bio-based materials. …”
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CRISPR-Cas9 in basic and translational aspects of cancer therapy by Maryam Samareh Salavatipour, Zahra Poursalehi, Negin Hosseini Rouzbahani, Sohaib Mohammadyar, Mohammad Vasei

“…Finally, we described the progress made by this technology in boosting immune-mediated cell therapy in oncology, such as CAR-T cells, CAR-NK cells, and CAR-M cells. …”
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Protective Effects of Tormentic Acid on Unilateral Ureteral Obstruction-Induced Renal Injury, Inflammation, and Fibrosis: A Comprehensive Approach to Reducing Oxidative Stress, Apo... by Ah Young Yang, Jung-Yeon Kim, Mi-Gyeong Gwon, Hyun Hee Kwon, Jaechan Leem, Eon-Ju Jeon

“…TA also mitigated oxidative stress by attenuating lipid peroxidation and boosting antioxidant defenses. Additionally, it inhibited apoptosis and ferroptosis by reducing oxidative stress and modulating key cell death markers. …”
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Advanced evaluation of performance of machine learning models for soapstock splitting optimisation under uncertainty by Bartosz Szeląg, Krzysztof Barbusiński, Michał Stachura, Przemysław Kowal, Adam Kiczko, Eldon R. Rene

“…Machine learning algorithms—Extreme Gradient Boosting (XGBoost) and Support Vector Machines (SVM)—were assessed in comparison with Response Surface Methodology (RSM). …”
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Levenberg-Marquardt Algorithm-Based Neural Network Smart Control Strategy for a Low-Input Current Ripple and High-Voltage Gain Power Converter in Fuel-Cells Energy Systems by Mustafa Ozden, Davut Ertekin, Pierluigi Siano

“…The control process of this proposed converter is executed using an artificial neural network based on the Levenberg-Marquardt learning algorithm. …”
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High-density natural active sites for efficient nitrogen reduction on Kagome surfaces promoted by flat bands by Yuyuan Huang, Yanru Chen, Shunhong Zhang, Zhenyu Zhang, Ping Cui

“…Abstract Recent studies have shown that single- or few-atom catalysts, with local states near the Fermi level, can promote nitrogen activation and the entire electrocatalytic nitrogen reduction reaction (eNRR) process, but are facing limitations in loading densities and stability. …”
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Prediction of mung bean production using machine learning algorithms by Azanu Mirolgn Mequanenit, Aleka Melese Ayalew, Ayodeji Olalekan Salau, Eyerusalem Alebachew Nibret, Million Meshesha

“…Therefore, the outcome of this research is essential to support the decision-making process of experts and it will enable them take corrective measures on the factors affecting mung bean production.…”
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