Synthetic Dataset for Analyzing Geometry-Dependent Optical Properties of All-Pass Micro-Ring Resonators by Sebastian Valencia-Garzon, Esteban Gonzalez-Valencia, Nelson Gómez-Cardona, Andres Calvo-Salcedo, J. A. Jaramillo-Villegas, Jorge Montoya-Cardona, Erick Reyes-Vera

“…The results confirm that variations in geometric configurations can significantly affect MRR performance, and the dataset provides valuable insights into the optimization process. Furthermore, machine learning techniques can be applied to the dataset to automate and improve the design process, reducing simulation times and increasing accuracy. …”
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Observation of a rare beta decay of the charmed baryon with a Graph Neural Network by The BESIII Collaboration

“…This work highlights a new approach to further understand fundamental interactions in the charmed baryon sector, and showcases the power of modern machine learning techniques in experimental high-energy physics.…”
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English Grammar Error Correction Algorithm Based on Classification Model by Shanchun Zhou, Wei Liu

“…Classification model is the core of machine learning and data mining, which can be applied to extracting information from English text data and constructing a reliable grammar correction method. …”
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Research on multi-source microstructure image recognition of foam ceramics using convolutional network combine with frequency domain by Yi Yin, Jianwei Pan, Fang Wang, Peihang Li, Zhen Cai, Xin Xu

“…However, their complex microstructure presents significant challenges for image analysis. Traditional machine learning methods often fall short in capturing both global feature dependencies and detailed representations. …”
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Gray-Related Support Vector Machine Optimization Strategy and Its Implementation in Forecasting Photovoltaic Output Power by Bo Xiao, Hai Zhu, Sujun Zhang, Zi OuYang, Tandong Wang, Saeed Sarvazizi

“…The photovoltaic output power variable is evaluated in this study using a powerful machine learning approach called the support vector machine model based on gray-wolf optimization. …”
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Secure Two-Party Decision Tree Classification Based on Function Secret Sharing by Kun Liu, Chunming Tang

“…Overall, the paper delivers an efficient, modular framework for practical two-party secure decision tree evaluation that advances the capability of privacy-preserving machine learning.…”
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Computer Vision-Based Drowsiness Detection Using Handcrafted Feature Extraction for Edge Computing Devices by Valerius Owen, Nico Surantha

“…These are integrated with traditional machine learning models, such as Support Vector Machines, Random Forests, and XGBoost. …”
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ROBO-SPOT: Detecting Robocalls by Understanding User Engagement and Connectivity Graph by Muhammad Ajmal Azad, Junaid Arshad, Farhan Riaz

“…The trust score of the callers is then used along with machine learning models to classify them as legitimate or robo-caller. …”
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Fast binary logistic regression by Nurdan Ayse Saran, Fatih Nar

“…This study presents a novel numerical approach that improves the training efficiency of binary logistic regression, a popular statistical model in the machine learning community. Our method achieves training times an order of magnitude faster than traditional logistic regression by employing a novel Soft-Plus approximation, which enables reformulation of logistic regression parameter estimation into matrix-vector form. …”
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Bus Ridership Prediction and Scenario Analysis through ML and Multi-Agent Simulations by Pasqual Martí, Alejandro Ibáñez, Vicente Julian, Paulo Novais, Jaume Jordán

“…This paper introduces an innovative approach to predicting bus ridership andanalysing transportation scenarios through a fusion of machine learning (ML) techniques and multi-agent simulations. …”
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In search of prosociality in rodents: A scoping review. by Valérie Charron, Joey Talbot, Patrick R Labelle, Anne T M Konkle, Hélène Plamondon

“…An update using a semi-supervised machine learning approach (ASReview) was then conducted to collect studies from 2021-2023. …”
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Stability Assessment of Concrete Gravity Dams via Multifidelity Surrogate Models by Rodrigo José de Almeida Torres Filho, Rocio L. Segura, Patrick Paultre

“…In recent years, many researchers have studied the potential of machine learning techniques to reduce the computational burden of dam assessment. …”
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Artificial Intelligence as a Catalyst for Management System Adaptability, Agility and Resilience: Mapping the Research Agenda by Ion Popa, Simona Cătălina Ștefan, Andrei Josan, Corina-Elena Mircioiu, Nicoleta Căruceru

“…Likewise, its thematic and strategic evolution is characterized as a surprising one, managing to incorporate and relate concepts with a strong technical and IT character such as feature extraction, machine learning, reinforcement learning with concepts of a managerial nature as supporting customer-tailored interaction, employee skills development, company productivity, and innovation.…”
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Chaotic gradient based optimization with fuzzy temporal optimized CNN for heart failure prediction by G. Kajeeth Kumar, S. Muthurajkumar

“…Furthermore, a tenfold cross-validation process ensures a comprehensive evaluation and the proposed method outperforms different Machine Learning (ML) / Deep Learning (DL) classifiers. …”
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A Rectal Cancer Surgery Dataset: Use of artificial intelligence to aid automation of error identification by Walaa Ghamrawi, Nathan Curtis, Jialang Xu, Matt Boal, Evangelos Mazomenos, Eddie Edwards, Danail Stoyanov, Nader Francis

“…This dataset can inform machine learning to assist progress toward a fully automated, objective assessment of surgical skills.…”
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Hybrid Model Based on Genetic Algorithms and SVM Applied to Variable Selection within Fruit Juice Classification by C. Fernandez-Lozano, C. Canto, M. Gestal, J. M. Andrade-Garda, J. R. Rabuñal, J. Dorado, A. Pazos

“…Given the background of the use of Neural Networks in problems of apple juice classification, this paper aim at implementing a newly developed method in the field of machine learning: the Support Vector Machines (SVM). Therefore, a hybrid model that combines genetic algorithms and support vector machines is suggested in such a way that, when using SVM as a fitness function of the Genetic Algorithm (GA), the most representative variables for a specific classification problem can be selected.…”
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Peptidomic analysis of whey protein hydrolysates and prediction of their antioxidant peptides by Jesus Morales García, Chibuike C. Udenigwe, Jorge Duitama, Andrés Fernando González Barrios

“…We also developed an ensemble machine learning predictor to classify peptides obtained from whey hydrolysis. …”
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Improving Diabetes Prediction by Selecting Optimal K and Distance Measures in KNN Classifier by Emad Majeed Hameed, Hardik Joshi

“…This paper discusses diabetes prediction by using the K-Nearest Neighbors (KNN) classifier, which is a widely used algorithm in machine learning. Most studies only dealt with investigating the optimal value of k in the KNN algorithm and did not address the best method to measure distance alone or together with the optimal value of k to improve the efficiency of diabetes prediction. …”
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A Multi-Index Generative Adversarial Network for Tool Wear Detection with Imbalanced Data by Guokai Zhang, Haoping Xiao, Jingwen Jiang, Qinyuan Liu, Yimo Liu, Liying Wang

“…Experimental results show that our method obtains 97% accuracy in tool wear detection based on imbalanced data without manual feature extraction, which outperforms traditional machine learning methods.…”
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End-to-End Semantic Leaf Segmentation Framework for Plants Disease Classification by Khalil Khan, Rehan Ullah Khan, Waleed Albattah, Ali Mustafa Qamar

“…Plant disease detection and classification is a much-developed research area due to enormous development in machine learning (ML). Over the last ten years, computer vision researchers proposed different algorithms for plant disease identification using ML. …”
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