Machine learning models for predicting the bearing capacity of shallow foundations: A Comparative study and sensitivity analysis by Hamid Mohammadnezhad, Seyedmohammad Eslami

“…With the development of new methods such as Machine Learning (ML) algorithms in recent decades, a resolution to these challenges has been identified. …”
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The Synergy of Minds and Machines: Rethinking the AI-HI Relationship through Dialectical Reconstruction by Ridwan Ishola MOGAJI, Adewale Oluwaseun MOTADEGBE

“…Artificial intelligence on the other hand is the simulation of human cognitive functions by machines, especially in tasks such as problem-solving, pattern recognition, and decision-making, which often operates based on algorithms and data, both of which are unique and important in themselves. …”
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Enhanced CLIP-GPT Framework for Cross-Lingual Remote Sensing Image Captioning by Rui Song, Beigeng Zhao, Lizhi Yu

“…Remote Sensing Image Captioning (RSIC) aims to generate precise and informative descriptive text for remote sensing images using computational algorithms. Traditional “encoder-decoder” approaches face limitations due to their high training costs and heavy reliance on large-scale annotated datasets, hindering their practical applications. …”
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STATE-OF-THE-ART OF MACHINE LEARNING IN NEURO DEVELOPMENT DISORDER: A SYSTEMATIC REVIEW by Lilian Yen Wei Lee, Ag Asri Ag Ibrahim, Rayner Alfred

“…This paper presents a comprehensive literature review focusing on the utilization of machine learning (ML) and deep learning (DL) methods for predicting and detecting Neurodevelopmental Disorders (NDDs), such as Intellectual Disability (ID), Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), Dyslexia, among others. While existing reviews often lack detailed discussions on the specific ML algorithms, datasets, and performance metrics employed in NDD prediction and detection, this study aims to address this gap by examining two primary aspects: prediction and detection. …”
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Assessing the Impact of Mixed Pixel Proportion Training Data on SVM-Based Remote Sensing Classification: A Simulated Study by Jianyu Gu, Russell G. Congalton

“…Support vector machine (SVM) algorithms have been widely utilized in the remote sensing community due to their high performance with small training datasets. …”
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AAD-YOLO: An Improved YOLOv8 Model for Complex Remote Sensing Scenarios by Yue Hong, Yi Shu, Shuo Guo

“…A comparative analysis with several state-of-the-art detection algorithms further validates the effectiveness and robustness of the proposed method.…”
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Research on Security Enhancement for Abnormal Content Release in Unified Audio Video Information service Systems by FENG Junhao

“…The system efficiently detects prohibited content while ensuring that legitimate content remains unaffected. …”
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Detecting Unbalanced Network Traffic Intrusions With Deep Learning by S. Pavithra, K. Venkata Vikas

“…To overcome these challenges, this project proposes a novel hybrid Intrusion Detection System using machine learning algorithms, which includes XGBoost, Long Short-Term Memory (LSTM), Mini-VGGNet, and AlexNet, which is used to handle the unbalanced network traffic data. …”
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Comparative Analysis of Machine Learning Models for Predicting Innovation Outcomes: An Applied AI Approach by Marko Martinović, Kristian Dokic, Dalibor Pudić

“…The results showed that tree-based boosting algorithms consistently outperformed other models in accuracy, precision, F1-score, and ROC-AUC, while the kernel-based approach excelled in recall. …”
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Lung Cancer Detection Utilizing Mixed Sensor Based Electronic Nose by Umit Ozsandikcioglu, Ayten Atasoy, Yusuf Sevim

“…Data dimension reduction was achieved using linear discriminant analysis and principal component analysis algorithms. The individual classification accuracies for the metal oxide semiconductor and quartz crystal microbalance sensor data are 81.54% and 73.18%, respectively. …”
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Long-Short Term Memory Networks and Synthetic Data for Heavy Vehicle Rollover Prevention by Guido Perboli, Antonio Tota, Filippo Velardocchia

“…In details, an heavy vehicle model was designed in IPG Carmaker®, while experimental data on its physical alter ego were acquired. …”
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Evaluative representations of the student audience in the context of current processes in Donbas: comparison of studies by L. B. Vnukova

“…Accordingly, a dichotomy of opinions appears: some share the belief that Russia is a strong power with an independent path of development, while others see themselves as part of a European (global) civilization. …”
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Medication Adherence: does Patient Participation in Randomized Clinical Trials Affect on it? by N. O. Vasyukova, Yu. V. Lukina, N. P. Kutishenko, S. Yu. Martsevich, O. I. Zvonareva

“…Nevertheless, the article discusses the existing doctor-patient interaction model, which strictly regulates the algorithms and technical means to achieve the best medication adherence. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…Other methods, such as Generative Adversarial Networks (GANs) and Autoencoders, are used for feature extraction, while Recurrent Neural Networks (RNNs) are employed for time-sequence modeling. …”
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Twitter Sentiment Classification towards Telecommunication Provider Users in Indonesia by Fernanda Mulya Syah Putra, Sindhu Rakasiwi, Noval Ariyanto

“…By applying machine learning algorithms such as Naïve Bayes and Support Vector Machine (SVM), this research analyzes customer perceptions of telecommunication service providers in Indonesia. …”
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Machine learning with sparse nutrition data to improve cardiovascular mortality risk prediction in the USA using nationally randomly sampled data by Joseph Rigdon, Sanjay Basu

“…Nutrition data alone failed to improve performance while machine learning alone improved calibration to 1.18 (0.92 to 1.44) and discrimination to 0.91 (0.90 to 0.92). …”
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B-UMCS: Blockchain-enabled Unified Medical Consultancy Service. by Albatoul Almohana, Iman Almomani, Walid El-Shafai

“…This work details the B-UMCS's components, interactions, smart contracts, protocols, algorithms, storage and transmission of EHRs, and their corresponding implementations. …”
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From Misinformation to Insight: Machine Learning Strategies for Fake News Detection by Despoina Mouratidis, Andreas Kanavos, Katia Kermanidis

“…Beyond technical advancements, we explore the ethical implications of automated misinformation detection, addressing concerns related to censorship, algorithmic bias, and the trade-off between content moderation and freedom of expression. …”
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Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches by Emmy Bhatti, Prabhpreet Kaur

“…Abstract Early detection of breast cancer, a deadly disease affecting millions of women worldwide, is crucial for better survival rates while minimizing the complexity of treatment procedures. …”
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Scalable earthquake magnitude prediction using spatio-temporal data and model versioning by Rahul Singh, Bholanath Roy

“…The results reveal that Gradient Boosting performs optimally on smaller datasets, while LightGBM demonstrates superior accuracy with larger datasets, showcasing the pipeline’s flexibility and scalability. …”
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