E-learning Platform and Pedagogical Monitoring in the Context of Digital Transformation by A. V. Khaperskaya, М. G. Minin

“…In particular, the implementation of an expert assessment method using image theory and machine learning is presented. The article argues that electronic didactics makes it possible to expand the functionalities of pedagogical monitoring in conditions of digitalization, while maintaining the principles of traditional pedagogy. …”
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Deep Learning-Based Dzongkha Handwritten Digit Classification by Yonten Jamtsho, Pema Yangden, Sonam Wangmo, Nima Dema

“…With the advancement in deep learning technology, many machine learning algorithms were developed to tackle the problem of pattern recognition. …”
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Deep phenotyping platform for microscopic plant-pathogen interactions by Stefanie Lück, Salim Bourras, Dimitar Douchkov

“…Building on accumulated experience and leveraging automated microscopy and software, we developed BluVision Micro, a modular, machine learning-aided system designed for high-throughput microscopic phenotyping. …”
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Deep learning for object recognition: A comprehensive review of models and algorithms by Paschalis Tsirtsakis, Georgios Zacharis, George S. Maraslidis, George F. Fragulis

“…The rapid advancements in artificial intelligence (AI) and machine learning (ML) have significantly enhanced progress in computer vision, opening doors to innovative technological possibilities and enabling a range of real-world applications. …”
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Enhancing Privacy While Preserving Context in Text Transformations by Large Language Models by Tymon Lesław Żarski, Artur Janicki

“…Our approach utilizes natural language processing methods, combining machine learning tools such as MITIE and spaCy with rule-based text analysis. …”
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Application Research of Intelligent Classification Technology in Enterprise Data Classification and Gradation System by Lina Yu, Chunwei Wang, Huixian Chang, Sheng Shen, Fang Hou, Yingwei Li

“…This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. …”
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Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks by Mo Yang, Dezhi Zhou

“…A comprehensive dataset of ignition delays was generated using a random sampling technique across different temperatures and pressures, focusing on hydrocarbon fuels with 1–4 carbon atoms. Two machine learning models, an artificial neural network and a graph convolutional network, are trained on this dataset, and their prediction performance was evaluated. …”
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Bibliometric Analysis of Studies on the Artificial Intelligence in Science Education with VOSviewer by Hayriye Nevin Genc, Nuriye Kocak

“…The most cited used keywords were "Machine Learning" and "Artificial Intelligence", followed by "Learning Analytics", "Data Science" and "Higher Education". …”
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A CLUSTERING TECHNIQUE FOR THE VIETNAMESE WORD CATEGORIZATION by Nguyễn Minh Hiệp, Nguyễn Thị Minh Huyền, Ngô Thế Quyền, Trần Thị Phương Linh

“…This could be solved using unsupervised machine learning methods. This paper presents an application of the DBSCAN clustering algorithm to classify Vietnamese words from a large corpus. …”
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International Gold Price Forecast Based on CEEMDAN and Support Vector Regression with Grey Wolf Algorithm by Wanbo Lu, Tingting Qiu, Wenhui Shi, Xiaojun Sun

“…This hybrid model combines the methodology of complex systems with machine learning techniques, making it more appropriate for analyzing relationships such as high-frequency dependences and solving complex nonlinear problems. …”
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A Customized Deep Neural Network Approach to Investigate Travel Mode Choice with Interpretable Utility Information by Zhengchao Zhang, Congyuan Ji, Yineng Wang, Yanni Yang

“…This is because, by using DNNs, mode choice can be assimilated with the classification problems within the machine learning community. This article proposes a newly designed DNN framework for traffic mode choice in the style of two hidden layers. …”
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Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization by S. Sakinah S. Ahmad, Witold Pedrycz

“…Finally, a series of numeric experiments using several machine learning data sets is presented.…”
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A Model and Complexity Analysis of the Relationship Based on Organizational Justice and Embeddedness Theories by Xin Su, Hui Zhang, Shubing Guo

“…Taking 245 members of 18 agricultural cooperatives as samples, this paper makes an empirical test by using the machine learning method. Through the analysis of the data, we find that interactive justice has a significant positive impact on the governance performance. …”
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Advancement of Hydraulic Fracture Diagnostics in Unconventional Formations by Ali Mahmoud, Ahmed Gowida, Murtada Saleh Aljawad, Mustafa Al-Ramadan, Ahmed Farid Ibrahim

“…Hence, the applications of machine learning in fracture diagnostics and DFIT analysis were discussed. …”
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Diagnosis of Coronary Heart Disease by Using Hybrid Intelligent Systems Based on the Whale Optimization Algorithm, Simulated Annealing and Support Vector Machine by Zeinab Hassani, Mahin Khosravi

“…In recent years, machine learning algorithms are widely used for diagnosis and timely treatment of diseases. …”
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A Systematic Literature Review on Robust Swarm Intelligence Algorithms in Search-Based Software Engineering by Alam Zeb, Fakhrud Din, Muhammad Fayaz, Gulzar Mehmood, Kamal Z. Zamli

“…These metaheuristics have applications in various domains such as global optimization, bioinformatics, power engineering, networking, machine learning, image processing, and environmental applications. …”
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Link Quality Prediction via a Neighborhood-Based Nonnegative Matrix Factorization Model for Wireless Sensor Networks by Yuxin Zhao, Shenghong Li, Jia Hou

“…By introducing complex network theory and machine learning techniques, we propose a neighborhood-based nonnegative matrix factorization model to predict link quality in wireless sensor networks. …”
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Development of Integrated Actinide Chemistry Application, AACE, for Acceleration of Actinide Chemistry Experiments by Nakase Masahiko, Nishihara Takahiro, Ikhwan Fauzia Hanum, Okamura Tomohiro, Matsui Kota

“…To efficiently find the candidate molecules we developed Acceleration of Actinide Chemistry Experiment (AACE), which can deploy transfer learning (TL) and human-in-the-loop machine learning (HITL-ML). Our approach utilizes Hansen’s solubility parameters derived from molecular structures to predict solubility and extractability, create extraction models for MA surrogate Lanthanide (Ln) and MA. …”
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An Efficient Feature Subset Selection Algorithm for Classification of Multidimensional Dataset by Senthilkumar Devaraj, S. Paulraj

“…Multidimensional medical data classification has recently received increased attention by researchers working on machine learning and data mining. In multidimensional dataset (MDD) each instance is associated with multiple class values. …”
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Does Price Really Matter for Generic Alternatives? Supervised learning Approaches in Deciding the Right Price for Acceptable Quality Attributes of Amlodipine Besylate among Generic... by Laltanpuii Chenkual, Mahindran Mariyappan, Dimple S. Lalchandani, Khajapeer Shaikh, Pavan Kumar Sathala, Pawan Kumar Porwal

“…The price and safety of finished pharmaceutical preparations are two major concerns while prescribing medicine. In this work, machine learning-based classification models were developed with respect to the quality attributes of 258 samples covering 9 marketed amlodipine (AMLO) formulations. …”
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