An annotated morphological dataset for Uzbek word forms: Towards rule-based and machine learning approachesMendeley Data by Nilufar Abdurakhmonova, Raima Shirinova, Rano Sayfullayeva, Davlatyor Mengliev, Bahodir Ibragimov, Manzura Ernazarova

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Application and Research of Attention Mechanism Combined with Data Visualisation for Entrepreneurial Learning Course Recommendation System in Universities and Colleges by Chunhua Dong

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The data visualization and intelligent text analysis for effective evaluation of English language teaching by Zihe Wu, Ye Zhang

Subjects: “…Data visualization analysis…”
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Bimodal data analysis for early detection of lameness in dairy cows using artificial intelligence by Yashan Dhaliwal, Hangqing Bi, Suresh Neethirajan

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Discovering language discovering language properties through corpus-based dictionary data analysis by Paul A. Lyddon

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Intelligent corrosion analysis and life prediction of ductile iron pipe systems using machine learning and electrochemical sensors by Bingqin Wang, Long Zhao, Yongfeng Chen, Lingsheng Zhu, Chao Liu, Xuequn Cheng, Xiaogang Li

“…A corrosion decision model based on a machine learning framework was developed for data mining. The results show that the developed model provides accurate corrosion prediction strategies. …”
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Analysis of Risk Bus Driver Characteristics and Research on Risk Level Evaluation Methods for Bus Drivers by Tongqiang Ding, Huijuan Yin, Zhiqiang Li, Xinyu He, Lili Zheng, Jianfeng Xi

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Harnessing multi-source data for AI-driven oncology insights: Productivity, trend, and sentiment analysis by Wissal EL HABTI, Abdellah AZMANI

“…The most prominent article emphasized the Explainability of AI methods (XAI) with a profound discussion of their potential implications and privacy in data fusion contexts. Current trends involve the utilization of supervised learning methods such as CNN, Bayesian networks, and extreme learning machines for various cancers, particularly breast, lung, brain, and skin cancer. …”
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Landslide data sample augmentation and landslide susceptibility analysis in Nyingchi City based on the MCMC model by Lianchen Liu, Peiqing Wang, Libin Su, Feng Li

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Revolution in flow cytometry: using artificial intelligence for data processing and interpretation by Szymon Bierzanowski, Szymon Bierzanowski, Krzysztof Pietruczuk

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Data-Driven and Mechanistic Soil Modeling for Precision Fertilization Management in Cotton by Miltiadis Iatrou, Panagiotis Tziachris, Fotis Bilias, Panagiotis Kekelis, Christos Pavlakis, Aphrodite Theofilidou, Ioannis Papadopoulos, Georgios Strouthopoulos, Georgios Giannopoulos, Dimitrios Arampatzis, Evangelos Vergos, Christos Karydas, Dimitris Beslemes, Vassilis Aschonitis

“…This study introduces a novel methodology for predicting cotton yield by integrating machine learning (ML) with mechanistic soil modeling. This hybrid approach enhances yield prediction by combining data-driven ML techniques with soil process modeling. …”
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Digital Footprint as a Source of Big Data in Education by T. M. Shamsutdinova

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Behavioral trace data in an online learning environment as indicators of learning engagement in university students by Marc Winter, Julia Mordel, Julia Mendzheritskaya, Daniel Biedermann, George-Petru Ciordas-Hertel, Carolin Hahnel, Carolin Hahnel, Daniel Bengs, Ilka Wolter, Frank Goldhammer, Hendrik Drachsler, Cordula Artelt, Holger Horz

“…Learning analytics provides a fruitful framework to analyze students' learning processes and LE via trace data. …”
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Research review of federated learning algorithms by Jianzong WANG, Lingwei KONG, Zhangcheng HUANG, Linjie CHEN, Yi LIU, Anxun HE, Jing XIAO

“…In recent years,federated learning has been proposed and received widespread attention to overcome data isolated island challenge.Federated learning related researches were adopted in areas such as financial field,healthcare domain and smart city related application.Federated learning concept was introduced into three different layers.The first layer introduced the definition,architecture,classification of federated learning and compared the federated learning with traditional distributed learning.The second layer presented comparison and analysis of federated learning algorithms from machine learning and deep learning aspects.The third layer separated federated learning optimization algorithms into three aspects to optimize federated learning algorithm through reducing communication cost,selecting proper clients and different aggregation method.Finally,the current research status and three main challenges on communication,heterogeneity of system and data to be solved were concluded,and the future prospects in federated learning domain were proposed.…”
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IMPROVING AGRICULTURAL YIELDS IN THE DEMOCRATIC REPUBLIC OF CONGO USING MACHINE LEARNING ALGORITHMS by Rodolphe Nsimba Malumba, Mardochee Longo Kayembe, Fiston Chrisnovic Balanganayi Kabutakapua, Bopatriciat Boluma Mangata, Trésor MAZAMBI KILONGO, Rufin Tabiaki Tandele, Emmanuel Ntanyungu Ndizieye, Parfum Bukanga Christian

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Dataset Construction Using Item Response Theory for Educational Machine Learning Competitions by Takeaki Sakabe, Yuko Sakurai, Emiko Tsutsumi, Satoshi Oyama

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Convergence Analysis for Differentially Private Federated Averaging in Heterogeneous Settings by Yiwei Li, Shuai Wang, Qilong Wu

Subjects: “…federated learning…”
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Explainable Survival Analysis of Censored Clinical Data Using a Neural Network Approach by Lisa Anita De Santi, Francesca Orlandini, Vincenzo Positano, Laura Pistoia, Francesco Sorrentino, Giuseppe Messina, Maria Grazia Roberti, Massimiliano Missere, Nicolò Schicchi, Antonino Vallone, Maria Filomena Santarelli, Alberto Clemente, Antonella Meloni

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Performance Analysis of Data Augmentation Approaches for Improving Wrist-Based Fall Detection System by Yu-Chen Tu, Che-Yu Lin, Chien-Pin Liu, Chia-Tai Chan

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Adding Data Quality to Federated Learning Performance Improvement by Ernesto Gurgel Valente Neto, Solon Alves Peixoto, Valderi Reis Quietinho Leithardt, Juan Francisco de Paz Santana, Julio C. S. Dos Anjos

“…Massive data generation from Internet of Things (IoT) devices increases the demand for efficient data analysis to extract relevant and actionable insights. …”
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