Federated Learning for Multimodal Sentiment Analysis: Advancing Global Models With an Enhanced LinkNet Architecture by P. Vasanthi, V. Madhu Viswanatham

“…In this article, the Enhanced LinkNet (EnLNet)-based Federated Learning (FL) approach is proposed for MSA. This approach utilizes an EnLNet model within an FL framework to manage and process multimodal data, including text, signals, and images. …”
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Advanced deep learning models based on neutrosophic logic for the analysis of brain tumor medical images by Dina Atef, Doaa El Shaha

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Analysing the effectiveness of unsignalized crossing infrastructure in improving pedestrian safety using multiple data-driven approaches by Shengqi Liu, Harry Evdorides

“…While numerous studies have applied predictive models to traffic crash data, few have systematically analysed pedestrian crash severity at unsignalized crossings using multiple machine learning algorithms. …”
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Predicting cancer mortality using machine learning methods: a global vs. Iran analysis by Hossein Sadeghi, Fatemeh Seif

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Comparative analysis prediction of prostate and testicular cancer mortality using machine learning: accuracy study by Aurélio Gomes de Albuquerque Neto, David Medeiros Nery, João Paulo Araújo Braz, Carla Ferreira do Nascimento, Tiago Almeida de Oliveira, Brígida Gabriele Albuquerque Barra, Leonardo Thiago Duarte Barreto Nobre, Diego Bonfada, Janine Karla França da Silva Braz

“…DESIGN AND SETTING: A comparative analysis of the pyMannKendall and Prophet machine-learning algorithms was conducted to develop predictive models using data from DATASUS (TabNet) to Caicó (Brazil) and Rio Grande do Norte (Brazil). …”
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Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization by Shuangqing Chen, Shun Zhou, Zhe Xu, Yongbin Liu, Bing Guan, Xiaoyu Jiang, Wencheng Li

“…Subsequently, the pipeline risk analysis is conducted based on statistical data from the Pipeline and Hazardous Materials Safety Administration (PHMSA). …”
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Discovering Breach Patterns on the Internet of Health Things: A Graph and Machine Learning Anomaly Analysis by Prabin B Lamichhane, Hannah Mannering, William Eberle

“…In this work, we use the ARMA model for statistical analysis. We also use several machine learning approaches such as multinomial naive bayes, ran- dom forest, neural networks, XGBClassifier, and support vector machines (SVM). …”
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Efficacy of adaptive e-learning for health professionals and students: a systematic review and meta-analysis by Guillaume Fontaine, Sylvie Cossette, Marc-André Maheu-Cadotte, Tanya Mailhot, Marie-France Deschênes, Gabrielle Mathieu-Dupuis, José Côté, Veronique Dubé

“…Studies were included in the meta-analysis if they had a non-adaptive e-learning environment control group and had no missing data. …”
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Problems of using phenol (hydroxybenzene) and parabens as pharmaceutical stabilizers: analysis using machine learning methods by I. Yu. Torshin, O. A. Gromova

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Sentiment analysis of telecom official micro-blog users based on LSTM deep learning model by Xin CAI, Jingsheng LOU

“…As an internet media,China Telecom official micro-blog is an important channel for the company to publish information and get feedback from users.Users’ comments on telecom official micro-blog messages reflect different attitudes towards telecom brand,products and services.The message content and comment data of the micro-blog was crawled,and the Word2vec was used to express the text information after data cleaning,and the deep learning platform was chosen to carry out the positive and negative emotional classification of the user interaction text based on the LSTM deep neural network model,and sentiment analysis of telecom official micro-blog users was realized.…”
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Comparative Analysis of Machine learning Methods to Identify signs of suspicious Transactions of Credit Institutions and Their Clients by Yu. M. Beketnova

“…The paper provides a comparative analysis of the results of processing data on the activities of credit institutions using classification methods — logistic regression, decision trees. …”
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Aspect-Based Sentiment Analysis for Afaan Oromoo Movie Reviews Using Machine Learning Techniques by Obsa Gelchu Horsa, Kula Kekeba Tune

“…Aspect-based sentiment analysis (ABSA) is the subfield of natural language processing that deals with essentially splitting data into aspects and finally extracting the sentiment polarity as positive, negative, or neutral. …”
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Load balancing based on clustering analysis and deep learning for multi-frequency and multi-mode network by Yaxing QIU, Xidong WANG, Sen BIAN, Lei YUE

“…Load balancing is a huge challenge for LTE multi-frequency and multi-mode network.Hundreds of parameters are involved in load balancing for the complex network structure.Therefore,it is difficult to perform precise and meticulous configuration only relying on human experience.In order to cope with the challenge,a load balancing scheme based on clustering analysis and deep learning was proposed.Firstly,the key indicators were selected to identify the network scenes,and then big data and deep learning technologies were used to mine the relationship between data.Finally,the optimum system parameters for different network scenes were found.It has been proved that machine learning technology can greatly improve the accuracy and the efficiency of parameter configuration.…”
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Enhanced Rolling Bearing Fault Diagnosis Using Multimodal Deep Learning and Singular Spectrum Analysis by Yunhang Wang, Hongwei Wang, Ruoyang Bai, Yuxin Shi, Xicong Chen, Qingang Xu

“…First, key features are extracted from the multimodal signal set using singular spectrum analysis (SSA), and these features are transformed into a composite dataset that combines short-time Fourier transform (STFT) images and time series data. …”
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Deep Learning for Ore Haulage Monitoring: Vibrational Analysis Using a VGG16 Network by Artur Skoczylas, Pawel Stefaniak, Sergii Anufriiev, Wioletta Koperska

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Real-Time Monitoring and Simulation of Multi-User Electricity Metering Anomaly Data Based on Distributed System by Kai Liu, Xuchao Jia, Junlong Wang, Xun Ma, Jiadong Li

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Landslide and Collapse Susceptibility Analysis in Wenchuan Earthquake-damaged Area Based on Ensemble Learning Methods by DING Jiawei, WANG Xiekang

“…Recent advancements in data science and machine learning provide promising solutions. …”
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Deep learning for sea surface temperature applications: A comprehensive bibliometric analysis and methodological approach by Redouane Larbi Boufeniza, Luo Jingjia, Kemal Adem Abdela, Karam Alsafadi, Mohammad M Alsahli

“…Abstract This study explored the potential application of deep learning techniques in sea surface temperature (SST) investigations using a mixed method, bibliometric analysis and methodological approach. …”
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IDEEA: information diffusion model for integrating gene expression and EEG data in identifying Alzheimer’s disease markers by Enes Ozelbas, Tuba Sevimoglu, Tamer Kahveci

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Time series analysis and prediction of the trends of COVID-19 epidemic in Singapore based on machine learning by Wenbin Yang, Xin Chang

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