Reconstruction of Three-Dimensional Porous Media Using Deep Transfer Learning by Yi Du, Jie Chen, Ting Zhang

“…Currently, as one of the important branches of machine learning methods, the deep transfer learning (DTL) method has shown good performance in extracting features and transferring them to the predicted objects, which can be used for the reconstruction of porous media. …”
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Reinforcement learning for deep portfolio optimization by Ruyu Yan, Jiafei Jin, Kun Han

“…DPO not only has the advantages of machine learning methods in investment decision-making, but also retains the essence of modern portfolio theory in portfolio optimization. …”
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Optimizing Credit Card Fraud Detection: A Genetic Algorithm Approach with Multiple Feature Selection Methods by Sunil Kumar Patel, Devina Panday

“…This study dives into the realm of machine learning, evaluating the performance of various algorithms - logistic regression (LR), decision tree (DT), and random forest (RF) - in detecting credit card fraud. …”
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Prediction of individual patient outcomes to psychotherapy vs medication for major depression by Devon LoParo, Boadie W. Dunlop, Charles B. Nemeroff, Helen S. Mayberg, W. Edward Craighead

“…Individual response to treatment, however, is variable, implying individual differences that could allow for prospective differential prediction of treatment response and personalized treatment recommendation. We used machine learning to develop predictor variables that combined demographic and clinical items from a randomized clinical trial. …”
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Stokes flows in a two-dimensional bifurcation by Yidan Xue, Stephen J. Payne, Sarah L. Waters

“…We parametrize the flow conductances of 2D bifurcation as functions of the dimensionless parameters of bifurcation geometry and a fixed object using a machine learning approach, which is simple to use and provides more accurate approximations than Poiseuille’s law. …”
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Comparison of the Performance of the C.45 Algorithm with Naive Bayes in Analyzing Book Borrowing at the Library Pringsewu Muhammadiyah University by Dani Wilian, Sriyanto Sriyanto

“…This research underscores the potential of data mining techniques to optimize library management and proposes avenues for future investigation, such as exploring advanced machine learning algorithms and expanding datasets for use in broader library contexts.…”
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Mining Stack Overflow for API class recommendation using DOC2VEC and LDA by Wai Keat Lee, Moon Ting Su

“…The benchmarking of the proposed approach against state‐of‐the‐art approaches, RACK and NLP2API, by using four performance metrics show that it is possible to produce comparable API recommendation results using a less complex approach that makes use of some basic machine learning models, in particular, Doc2Vec and LDA. …”
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AutoPVPrimer: A comprehensive AI-Enhanced pipeline for efficient plant virus primer design and assessment. by Abozar Ghorbani, Mahsa Rostami, Elham Ashrafi-Dehkordi, Pietro Hiram Guzzi

“…We present AutoPVPrimer, an innovative pipeline that integrates artificial intelligence (AI) and machine learning to accelerate the development of plant virus primers. …”
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Battery Energy Forecasting in Electric Vehicle Using Deep Residual Neural Network by Mohamad Reda A. Refaai, Jyothilal Nayak Bharothu, T. V. V. Pavan Kumar, Chodagam Srinivas, M. Sudhakar, Anirudh Bhowmick

“…Traditional SOH estimation techniques have demonstrated that they have limits that can be overcome by data-driven methods. TCN, a new machine learning technique, combines the advantages of residual neural networks (ResNet) with the computing efficiency of neural networks to produce a technique that is both efficient and effective. …”
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Double layer federated security learning architecture for artificial intelligence of things by ZHENG Chengbo, YAN Haonan, FU Caili, ZHANG Dong, LI Hui, WANG Bin

“…Federated learning, as a distributed machine learning architecture, can complete model co-training while protecting data privacy, and is widely used in Artificial Intelligence of Things. …”
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Comparative Analysis of Federated and Centralized Learning Systems in Predicting Cellular Downlink Throughput Using CNN by Kukuh Nugroho, Hendrawan, Iskandar

“…This study utilized Federated Learning (FL) as a machine learning paradigm and employed CNN as a model to predict throughput in the cellular network. …”
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Global Impact Assessment of Internal Climate Variability on Maize Yield Under Climate Change by Guoyong Leng

“…By combining initial condition large ensembles from multiple climate models with machine‐learning based crop model emulators, an ensemble of 2002 global maize yield simulations are conducted. …”
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Fuzzy Aspect Based Opinion Classification System for Mining Tourist Reviews by Muhammad Afzaal, Muhammad Usman, A. C. M. Fong, Simon Fong, Yan Zhuang

“…Such sentences make the data noisy and degrade the classification accuracy of the machine learning algorithms. This paper presents a fuzzy aspect based opinion classification system which efficiently extracts aspects from user opinions and perform near to accurate classification. …”
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Composite Bayesian Optimization in function spaces using NEON—Neural Epistemic Operator Networks by Leonardo Ferreira Guilhoto, Paris Perdikaris

“…Abstract Operator learning is a rising field of scientific computing where inputs or outputs of a machine learning model are functions defined in infinite-dimensional spaces. …”
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Prediction of hemolytic peptides and their hemolytic concentration by Anand Singh Rathore, Nishant Kumar, Shubham Choudhury, Naman Kumar Mehta, Gajendra P. S. Raghava

“…Among classification models, including machine learning (ML), quantum ML, and protein language models, a hybrid model combining random forest (RF) and a motif-based approach achieves the highest area under the receiver operating characteristic curve (AUROC) of 0.921. …”
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Applications of artificial neural networks in health care organizational decision-making: A scoping review. by Nida Shahid, Tim Rappon, Whitney Berta

“…Health care organizations are leveraging machine-learning techniques, such as artificial neural networks (ANN), to improve delivery of care at a reduced cost. …”
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Accelerating materials property prediction via a hybrid Transformer Graph framework that leverages four body interactions by Mohammad Madani, Valentina Lacivita, Yongwoo Shin, Anna Tarakanova

“…Abstract Machine learning has advanced the rapid prediction of inorganic materials properties, yet data scarcity for specific properties and capturing thermodynamic stability remains challenging. …”
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Artificial neural networks for stability analysis and simulation of delayed rabies spread models by Ramsha Shafqat, Ateq Alsaadi

“…This approach aimed to expand our understanding of rabies transmission, illustrating the potential of advanced mathematical tools and machine learning in epidemiological modeling.…”
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Application of IoT and Cloud Computing in Automation of Agriculture Irrigation by Khongdet Phasinam, Thanwamas Kassanuk, Priyanka P. Shinde, Chetan M. Thakar, Dilip Kumar Sharma, Md. Khaja Mohiddin, Abdul Wahab Rahmani

“…This system is designed to measure soil moisture and humidity and then process this data in the cloud using a variety of machine learning techniques. Farmers are given the correct information about water content rules. …”
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Integrins identified as potential prognostic markers in osteosarcoma through multi-omics and multi-dataset analysis by Lei Cui, Shuai Zhao, Hai long Teng, Biao Yang, Qian Liu, An Qin

“…This study utilized 209,268 osteosarcoma cells from the GEO database to identify integrin-associated genes using advanced analysis methods. A novel machine learning framework combining 10 algorithms was developed to construct an Integrin-related Signature (IRS), which demonstrated robust predictive power across multiple datasets. …”
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