FL-Joint: joint aligning features and labels in federated learning for data heterogeneity by Wenxin Chen, Jinrui Zhang, Deyu Zhang

“…Abstract Federated learning is a distributed machine learning paradigm that trains a shared model using data from various clients, it faces a core challenge in data heterogeneity arising from diverse client settings and environments. …”
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Emerging technologies and language learning: mining the past to transform the future by Hubbard Philip

“…Today’s emerging technologies—artificial intelligence, machine learning, conversational robots, virtual worlds, virtual reality, augmented reality, automated assessment, and so on—are full of promise and seem poised to revolutionize language teaching and learning over the next decade. …”
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Beyond predefined ligand libraries: a genetic algorithm approach for de novo discovery of catalysts for the Suzuki coupling reactions by Julius Seumer, Jan H. Jensen

“…Limitations in the applicability of machine learning models are overcome by calculating thermodynamic properties from first principle. …”
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Exploring the Behavior-Driven Crash Risk Prediction Model: The Role of Onboard Navigation Data in Road Safety by Xiao-chi Ma, Jian Lu, Yiik Diew Wong

“…The behavioral RUSBoost model surpasses other models, achieving an AUC prediction metric of 0.782 and outperforming traditional traffic-flow-driven machine learning models. PDP analysis demonstrates that the sudden-braking behavior is the leading contributory factor of expressway crashes, particularly when the acceleration exceeds 0.5 G. …”
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The Machine as an Autonomous Explanatory Agent by Dilek Yargan

“…The third part delves into whether and to what extent the state-of-the-art machine learning models function as autonomous explanatory agents, based on the exploration in the second part and considering the field of Human-Computer Interaction.…”
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Precomputed Clustering for Movie Recommendation System in Real Time by Bo Li, Yibin Liao, Zheng Qin

“…In this paper, we present a novel idea that applies machine learning techniques to construct a cluster for the movie by implementing a distance matrix based on the movie features and then make movie recommendation in real time. …”
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Reliable detection of doppelgängers based on deep face representations by Christian Rathgeb, Daniel Fischer, Pawel Drozdowski, Christoph Busch

“…The proposed detection system employs a machine learning‐based classifier, which is trained with generated doppelgänger image pairs utilising face morphing techniques. …”
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Visceral condition assessment through digital tongue image analysis by Siu Cheong Ho, Yiliang Chen, Yao Jie Xie, Wing-Fai Yeung, Shu-Cheng Chen, Jing Qin

“…Our method simulates the TCM diagnostic process while leveraging modern machine learning techniques. To support this research, we have created a comprehensive tongue image dataset specifically tailored for these five visceral pattern assessment. …”
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Research on image generation technology based on deep learning by Li Jinchen

“…In the realm of image creation, deep learning stands out as an effective and valuable machine learning technique. Deep learning can automatically learn the intrinsic features of images， reaching the goal of generating high-quality images by utilizing multi-layer neural network models. …”
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Experimental and computational investigation of the effect of machining parameters on the turning process of C45 steel by Tien-Thinh Le, Hang Thi Pham, Hiep Khac Doan, Panagiotis G. Asteris

“…Finally, for practical purposes, an artificial neural network model based on machine learning is developed to predict the average temperature near the turning insert nose.…”
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Development and validation of an automated machine for self-injury assessment via young Koreans' natural writings. by Seoyoung Kim, Dong-Gwi Lee

“…Based on 16,645 online posts, Study 1 developed a machine called the Korean Self-Injurious Text Reviewer (K-SITR) using Latent Dirichlet Allocation topic modeling and machine learning. The K-SITR's text-assessment results were statistically indistinguishable from those of professional counselors. …”
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Detection of Data Integrity Attack Using Model and Data-Driven-Based Approach in CPPS by G. Y. Sree Varshini, S. Latha

“…The convolutional neural network- (CNN-) based data-driven anomaly detection technique outperforms other machine learning (ML) techniques such as support vector machine (SVM), K-nearest neighbour (KNN), and random forest (RF). …”
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Lip print‐based identification using traditional and deep learning by Wardah Farrukh, Dustin van derHaar

“…The first pipeline is a traditional method with Speeded Up Robust Features with either an SVM or K‐NN machine learning classifier, which achieved an accuracy of 95.45% and 94.31%, respectively. …”
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AI-Powered Sustainable Environmental Practices using Laser-Induced Breakdown Spectroscopy (LIBS) by Al-Juboori Haider, Rizvi Syed Zuhaib H., bin Roslan Muhammad S., Liew Josephine Y.

“…The research will focus on designing an innovative system architecture that integrates laser-induced breakdown spectroscopy (LIBS) with a robust machine learning (ML) framework, significantly advancing sustainable environmental practices, especially since LIBS offers rapid and precise multi-elemental analysis, while AI enhances data processing and predictive capabilities. …”
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More than just sentiment: Using social, cognitive, and behavioral information of social media to predict stock markets with artificial intelligence and big data by Yunus Emre Akdogan, Adem Anbar

“…Relationships between Twitter-obtained features and BIST indices were analyzed using machine learning methods such as linear regression, Lasso regression, random forest, and XGBoost. …”
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An Overview of Structured Lipid in Food Science: Synthesis Methods, Applications, and Future Prospects by Chi Rac Hong, Byeong Jun Jeon, Kyung-Min Park, Eun Ha Lee, Sung-Chul Hong, Seung Jun Choi

“…In addition, we discuss innovative approaches, including metagenomics, and machine learning, to discover, and classify new lipases and the use of gene editing technologies for lipase engineering. …”
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Credit Risk Prediction Using Fuzzy Immune Learning by Ehsan Kamalloo, Mohammad Saniee Abadeh

“…Two real world credit data sets in UCI machine learning repository are selected as experimental data to show the accuracy of the proposed classifier. …”
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Vietnamese Sentiment Analysis under Limited Training Data Based on Deep Neural Networks by Huu-Thanh Duong, Tram-Anh Nguyen-Thi, Vinh Truong Hoang

“…Several experiments have been performed for both well-known machine learning-based classifiers and deep learning models. …”
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Understanding tourism consumer behavior using biometric technologies: bibliographic review and research agenda by Nuria Ruiz-Lacaci, Ana Reyes-Menendez, Ana Vico Belmonte

“…Through a bibliographic review of 422 recent papers, employing machine learning and artificial intelligence techniques, we extracted keywords, topics, and frequencies using the methodological approach of corpus linguistics and latent Dirichlet allocation algorithm. …”
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Support Vector Machine for Behavior-Based Driver Identification System by Huihuan Qian, Yongsheng Ou, Xinyu Wu, Xiaoning Meng, Yangsheng Xu

“…Then we compare fast Fourier transform (FFT), principal component analysis (PCA), and independent component analysis (ICA) for data preprocessing. Using machine learning method of support vector machine (SVM), we derive the individual driving behavior model and we then demonstrate the procedure for recognizing different drivers by analyzing the corresponding models. …”
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