Application of Machine Learning for Real-Time Phishing Attack Detection by Akshay Shankar Agrawal, Sanketi Raut, Andrina Dsouza, Jimit Mehta, Prajwal Naik

“…To be able to detect suspicious websites is a potential first step in reducing the amount of phishing attacks occurring daily. …”
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Bioinformatics and machine learning-driven key genes screening for vortioxetine by Sabire Kılıçarslan, Meliha Merve Hız

“…The original datasets were preprocessed in the second step by detecting and correcting missing and noisy data and then merged. …”
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Herobot Learning Media for Grade IV Elementary School Students by Tri Widiastuti, Irfai Fathurohman, Erik Aditia Ismaya

“…The method used is a research & development method using research steps developed until the fourth step, namely: potential and problems analysis, data collection, product design, and validation design. …”
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Review on Deep Learning and Neural Network Implementation for Emotions Recognition by Renas Rajab Asaad

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Interpretable Machine Learning Techniques for an Advanced Crop Recommendation Model by Mohamed Bouni, Badr Hssina, Khadija Douzi, Samira Douzi

“…By balancing advanced predictive capabilities with user-centric explanations, our model represents a substantial step forward in developing data-driven, transparent, and trustworthy agricultural advisories.…”
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Robust Distribution-Aware Ensemble Learning for Multi-Sensor Systems by Payman Goodarzi, Julian Schauer, Andreas Schütze

“…This paper introduces a novel, robust multi-sensor ensemble framework that integrates principles of automated machine learning (AutoML) to address the challenges of domain shifts and variability in sensor data. …”
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Enhancing breast cancer diagnosis through machine learning algorithms by Javad Amraei, Aboulfazl Mirzapoor, Kiomars Motarjem, Mohammad Abdolahad

“…These findings are an important step forward in the application of Machine Learning to improve diagnostic accuracy, thus enabling early detection and mitigating the major consequences of breast cancer on global health.…”
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Industrial Maturity of Machine Learning Solutions Within the Food Industry by Laura Gradl, Luisa Reis, Ricardo Buettner

“…Existing solutions are categorized according to the addressed process step within the food value chain and the covered dimension of the maturity framework. …”
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MEFL: Meta-Equilibrize Federated Learning for Imbalanced Data in IoT by Jialu Tang, Yali Gao, Xiaoyong Li, Jia Jia

“…This imbalance can lead to skewness and accuracy degradation, ultimately affecting the generalization ability and robustness of Federated Learning (FL) models. Our work addresses these critical challenges by proposing a novel method, Meta-Equilibrized Federated Learning (MEFL), which integrates meta-learning with gradient-descent preservation and an equilibrated optimization aggregation mechanism based on gradient similarity and variance weighted adjustment. …”
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Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

“…However, they remain rarely explored because deep learning models are overparameterized and seldom tractable. …”
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Federated knee injury diagnosis using few shot learning by Chirag Goel, Anita X, Jani Anbarasi L

“…The model is trained incorporating Stochastic Gradient Descent (SGD), Cross-Entropy Loss, and a MultiStep Learning Rate scheduler to enhance few-shot classification. …”
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Native learning ability and not age determines the effects of brain stimulation by Pablo Maceira-Elvira, Traian Popa, Anne-Christine Schmid, Andéol Cadic-Melchior, Henning Müller, Roger Schaer, Leonardo G. Cohen, Friedhelm C. Hummel

“…Our results show that individuals with less efficient learning mechanisms benefit from stimulation, while those with optimal learning strategies experience none or even detrimental effects. …”
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Ambiguity-aware semi-supervised learning for leaf disease classification by Tri-Cong Pham, Tien-Nam Nguyen, Van-Duy Nguyen

“…To tackle the problem, we propose an Ambiguity-Aware Semi-Supervised Learning method for Leaf Disease Classification. Specifically, we present a per-disease ambiguity rejection algorithm that eliminates ambiguous results, thereby enhancing the precision of pseudo labels for the subsequent semi-supervised training step and improving the precision of the final classifier. …”
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Deep learning-based edge detection for random natural images by Kanija Muntarina, Rafid Mostafiz, Sumaita Binte Shorif, Mohammad Shorif Uddin

“…In recent years, the emergence of deep learning technology has revolutionized this field by utilizing its ability to automatically learn complex features from natural images. …”
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Ensemble prediction modeling of flotation recovery based on machine learning by Guichun He, Mengfei Liu, Hongyu Zhao, Kaiqi Huang

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Lighting Spectrum Optimization With Deep Learning for Moss Species Classification by Kenichi Ito, Pauli Falt, Markku Hauta-Kasari, Shigeki Nakauchi

“…Hence, we propose a method for obtaining spectral information on moss in the forest using a deep learning model to train convolutional neural network models while optimizing a suitable light source for moss identification. …”
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Analysis and prediction of atmospheric ozone concentrations using machine learning by Stephan Räss, Stephan Räss, Markus C. Leuenberger, Markus C. Leuenberger

“…We analyzed data recorded by Switzerland's National Air Pollution Monitoring Network (NABEL) to showcase the capabilities of machine learning (ML) for the prediction of ozone concentrations (daily averages) and to document a general approach that can be followed by anyone facing similar problems. …”
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Muographic Image Upsampling with Machine Learning for Built Infrastructure Applications by William O’Donnell, David Mahon, Guangliang Yang, Simon Gardner

“…Our results demonstrate significant improvements in both acquisition speed and image quality, marking a substantial step toward making muography more practical for reinforced concrete infrastructure monitoring applications.…”
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Multi-Spectral Optimization for Tissue Probing Using Machine Learning by Yarden Tzabari Kelman, Hadas Lupa Yitzhak, Nadav Shabairou, Shahaf Finder, Zeev Zalevsky

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Filming a Series as a Performative Method of Learning German by Maria V. Petrova

“…Creating a series in German is a multi-step process that not only involves students but also contributes to the development of various language skills in learners. …”
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