Conformal symplectic and constraint-preserving model order reduction of constrained conformal Hamiltonian systems by Vidushi Sachan, Ashish Bhatt

“…In this paper, we reduce and solve high-dimensional parameterized constrained and damped nonlinear differential equations with structure-preserving algorithms. These algorithms preserve the constrained equation's geometric properties, such as conformal symplecticness and phase-space, through model order reduction and numerical integration. …”
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Enhancing Security in Industrial IoT Networks: Machine Learning Solutions for Feature Selection and Reduction by Ahmad Houkan, Ashwin Kumar Sahoo, Sarada Prasad Gochhayat, Prabodh Kumar Sahoo, Haipeng Liu, Syed Ghufran Khalid, Prince Jain

“…The article emphasizes the critical role of feature engineering, with a specific focus on feature selection and reduction, and elaborates on applying MRMR and PCA algorithms to various feature sets. …”
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Joint Tomek Links (JTL): An Innovative Approach to Noise Reduction for Enhanced Classification Performance by Goksu Tuysuzoglu, Yunus Dogan, Elife Ozturk Kiyak, Mustafa Ersahin, Bita Ghasemkhani, Kokten Ulas Birant, Derya Birant

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Dimension Reduction Using Quantum Wavelet Transform on a High-Performance Reconfigurable Computer by Naveed Mahmud, Esam El-Araby

“…In this work, we propose combining dimension reduction techniques with quantum information processing for application in domains that generate large volumes of data such as HEP. …”
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Research on fusion prediction model of wind speed, gas and dust concentration under wind flow control in fully-mechanized heading face by Xiaoyan GONG, Hao ZOU, Zhuangzhuang LIU, Long CHEN, Haoran FU, Yuheng SUN, Hao LI, Xinyu WANG, Huming NIU

Subjects: “…differential evolution algorithm…”
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The Diagnosis of Diabetes Using a Hybrid Algorithm Consisting of the Flower Pollination Algorithm and an Ensemble of a Subset of K-NN Classifiers by Zeinab Hassani, Najmeh Samadiani

“…Therefore, it is essential to diagnose diabetes. Since hybrid algorithms have a high ability to predict and diagnose various diseases, this article presents an intelligent approach to the diagnosis of this disease, using a hybrid algorithm of flower pollination and K-nearest neighbor ensemble. …”
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Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought: Algorithm Development and Validation Study by Sanghwan Kim, Sowon Jang, Borham Kim, Leonard Sunwoo, Seok Kim, Jin-Haeng Chung, Sejin Nam, Hyeongmin Cho, Donghyoung Lee, Keehyuck Lee, Sooyoung Yoo

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Long-term survival prediction in patients with acute brain lesions using ensemble machine learning algorithms: a cohort study with combined national health insurance service and its self-run hospital database by Dougho Park, Daeyoung Hong, Suntak Jin, Jong Hun Kim, Hyoung Seop Kim

“…Random forest (RF), extreme gradient boosting (XGB), and algorithm stacking methods were used for prediction. …”
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Statistical Inferences to the Parameter and Reliability Characteristics of Gamma-mixed Rayleigh Distribution under Progressively Censored Data with Application by Kousik Maiti, Suchandan Kayal

Subjects: “…Expectation-Maximization (EM) algorithm…”
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Predictable and non-stationary processes of interval PREDICTION BASED ON stochastic differential equations by A. V. Ausiannikau

“…Predictability of such processes is defined. Algorithms of interval prediction in the discrete and continuous time are received.…”
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Neoantigen vaccines: advancing personalized cancer immunotherapy by Alaa A. A. Aljabali, Yassmen Hamzat, Alaa Alqudah, Lorca Alzoubi

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Prediction and Impact Analysis of Soil Nitrogen and Salinity Under Reclaimed Water Irrigation: A Case Study by Zeyu Liu, Kai Fang, Xiaoqin Sun, Yandong Wang, Zhuo Tian, Jing Liu, Liying Bai, Qilin He

“…This study employs genetic-algorithm-optimized random forest models (GA-RF1 and GA-RF2) to examine the dynamics of nitrogen indicators (NO₃⁻-N, NH₄⁺-N, and TN) and salinity indicators (EC and Cl⁻) under reclaimed water irrigation. …”
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Predicting the Magnitude of Earthquakes Using Grammatical Evolution by Constantina Kopitsa, Ioannis G. Tsoulos, Vasileios Charilogis

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Leveraging Explainable Artificial Intelligence (XAI) for Expert Interpretability in Predicting Rapid Kidney Enlargement Risks in Autosomal Dominant Polycystic Kidney Disease (ADPKD... by Latifa Dwiyanti, Hidetaka Nambo, Nur Hamid

“…Utilizing historical patient data, we aim to predict rapid kidney enlargement in ADPKD patients to support clinical decision-making. …”
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Machine learning approach for revealing the nickel grade and recovery optimization in reduction process of laterite ores by Vuri Ayu Setyowati, Fakhreza Abdul

“…Data sets were collected from published studies that feature nickel ore grade (Ni and Fe content) and reduction process (temperature, additives, reductant, etc.), while prediction models for Ni grade and recovery were formed from four types of regression algorithms. …”
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Learning-Based Variable Admittance Control Combined with NMPC for Contact Force Tracking in Unknown Environments by Yikun Zhang, Jianjun Yao, Chen Qian

Subjects: “…deterministic policy gradient algorithm…”
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HAP-COVID: Hybrid Model Integrating Machine Learning and Neutrosophic Statistics to Estimate Mortality Risk in COVID-19 Comorbid Patients by Daniel Iturburu-Salvador, Lorenzo Cevallos-Torres, Rosangela Caicedo-Quiroz, Irma Naranjo-Peña, Rosa Hernández-Magallanes, Rosa Gonzáles-Quiñones

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Microservice Deployment Based on Multiple Controllers for User Response Time Reduction in Edge-Native Computing by Zhaoyang Wang, Jinqi Zhu, Jia Guo, Yang Liu

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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

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Novel concept for the healthy population influencing factors by Yuhao Shen, Jichao Wang, Lihua Ma, Huizhe Yan

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