Graph-Based Data Analysis for Building Chemistry–Phase Design Rules for High Entropy Alloys by Scott R. Broderick, Stephen A. Giles, Debasis Sengupta, Krishna Rajan

“…The number and types of phases formed in high entropy alloys (HEAs) have significant impacts on the mechanical properties. While various machine learning approaches were developed for predicting whether an HEA is single or multiphase, changes in chemistry and/or composition can lead to other changes across length scales, which affect material performance. …”
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Creating non-fungible token (NFT)-backed emoji art from user conversations on blockchain by Maedeh Mosharraf, Mohammad Hossein Khorrami

“…It utilizes natural language processing and machine learning methods to extract key sentences from user conversations and match them with emojis that reflect their sentiments. …”
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Artificial Intelligence and Physics-Based Anomaly Detection in the Smart Grid: A Survey by Giovanni Battista Gaggero, Paola Girdinio, Mario Marchese

“…Anomaly detection methods increasingly rely on Machine Learning techniques, that represent a game-changer tool for data analysis. …”
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Development of malaria diagnosis with convolutional neural network architectures: a CNN-based software for accurate cell image analysis. by Emrah ASLAN

“…The traditional method of diagnosis relies on experts examining red blood cells under a microscope and is inefficient as it is dependent on expert knowledge and experience. Nowadays, machine learning methods that provide high accuracy are increasingly used in disease detection. …”
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Investigating the electric vehicle adoption initiatives for achieving sustainable development goals by Shashi Kant Tripathi, Ravi Kant, Ravi Shankar

“…A novel research framework of sentence boundary extraction, a machine learning approach, and multi-criteria decision-making is proposed to achieve the research objective. …”
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Application of Spatial Transcriptomics in Digestive System Tumors by Bowen Huang, Yingjia Chen, Shuqiang Yuan

“…This review also discusses the importance of combining spatial transcriptomics with single-cell RNA sequencing (scRNA-seq), artificial intelligence, and machine learning in digestive system cancer research.…”
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Strong wind is one of the important factors that trigger landslides by Yuan-Chien Lin, Jui-Yun Hsieh, Hua-San Shih, Wen-Hsin Wang

“…The significance of the combined rain–wind influence on landslides is examined using Mann–Whitney U test and 3D histogram, and a Random Forest machine learning model is constructed to predict the occurrences of landslides based on factors, such as heavy rain, strong winds, traditional geological conditions, and topographical factors. …”
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Study on the Impact of LDA Preprocessing on Pig Face Identification with SVM by Hongwen Yan, Yulong Wu, Yifan Bo, Yukuan Han, Gaifeng Ren

“…In this study, the implementation of traditional machine learning models in the intelligent management of swine is explored, focusing on the impact of LDA preprocessing on pig facial recognition using an SVM. …”
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Predicting amyloid proteins using attention-based long short-term memory by Zhuowen Li

“…Recently, although several machine learning methods proposed for amyloid protein identification have shown promising results, most of them have not yet fully exploited the sequence information of the amyloid proteins. …”
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A Modified Fully Convolutional Network for Crack Damage Identification Compared with Conventional Methods by Meng Meng, Kun Zhu, Keqin Chen, Hang Qu

“…With the development of artificial intelligence especially the combination of deep learning and computer vision, greater advantages have been brought to the concrete crack detection based on convolutional neural network (CNN) over the traditional methods. However, these machine learning (ML) methods still have some defects, such as it being inaccurate or not strong, having poor generalization ability, or the accuracy still needs to be improved, and the running speed is slow. …”
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Forecasting the Treasury Yield Spread for FRED T10Y2Y Data Based on Multiple Approaches by Leu Ying Chen

“…With this in mind. this study looks into the usage of machine learning models to predict the yield spread between 10-year and 2-year US Treasury bonds (T10Y2Y). …”
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Education, Quality and the Digital Transformation by N. E. Serditova, A. V. Belotserkovsky

“…The necessity to develop universal competencies in the field of information and communication technologies, as well as skills for using methods of pattern recognition theory, which is fundamental for deep machine learning, is noted. Possibilities of using both Mass Open Online Courses (MOOC) and Online Program Management (OPM) services in academic programs are considered.…”
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Multimodal Interaction, Interfaces, and Communication: A Survey by Elias Dritsas, Maria Trigka, Christos Troussas, Phivos Mylonas

“…With advancements in sensor technology and machine learning (ML), multimodal systems are becoming increasingly important in various applications, including virtual assistants, intelligent environments, healthcare, and accessibility technologies. …”
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A Kernel-Based Approach for Biomedical Named Entity Recognition by Rakesh Patra, Sujan Kumar Saha

“…Support vector machine (SVM) is one of the popular machine learning techniques used in various text processing tasks including named entity recognition (NER). …”
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Systematic Review of Remote Sensing Prediction Models and Tools for Estimating Surface Soil Moisture Content of an Area by P. Yamakili, M. R. Nicholaus, K. A. Greyson

“…As a result, this systematic review paper presents a wide range of comparative assessments of RS SM estimation models and tools by assessing their technique and methods, their performance Evaluation level (Coefficient of Determination R), the environment where the model could suitably perform better and the essential parameters considered for improving the known Machine Learning models for SM prediction further attention as discussed under this paper. …”
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Geographical Origin Identification of <italic>Panax notoginseng</italic> Using a Modified K-Nearest Neighbors Model With Near-Infrared Spectroscopy by Xuefeng Cheng, Min Liao, Juan Liu

“…These results demonstrate the potential of combining spectral data processing with advanced machine learning techniques for efficient and accurate geographical origin identification, providing a robust tool for quality assurance and traceability in traditional Chinese medicine.…”
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Transfer learning for linear regression with differential privacy by Yiming Hou, Yunquan Song, Zhijian Wang

“…Abstract Transfer learning, as a machine learning approach to enhance model generalization, has found widespread applications across various domains. …”
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An Efficient and Accurate 2W-PE Method for Solving Spatial Field Strength Based on CVNN and PINN by An-Qi Li, Cheng-You Yin, Qian-Qian Zhang, Han Liu

“…The proposed 2W-PE method has high computational accuracy and efficiency, which reflects the applicability of machine learning in solving the computational efficiency problem of radio wave propagation. …”
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Experiments on Detection of Voiced Hesitations in Russian Spontaneous Speech by Vasilisa Verkhodanova, Vladimir Shapranov

“…In this paper we address an issue of voiced hesitations (filled pauses and sound lengthenings) detection in Russian spontaneous speech by utilizing different machine learning techniques, from grid search and gradient descent in rule-based approaches to such data-driven ones as ELM and SVM based on the automatically extracted acoustic features. …”
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Optimizing cryptographic protocols against side channel attacks using WGAN-GP and genetic algorithms by Purushottam Singh, Prashant Pranav, Sandip Dutta

“…This study underscores the potential of leveraging machine learning and evolutionary algorithms to advance cryptographic protocol security and efficiency, laying a robust foundation for future advancements in cybersecurity.…”
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