Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…The novelty of this research lies in the application of a data aggregation technique to address class imbalance, significantly improving machine learning model performance and optimizing training time. …”
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Bird Species Detection Net: Bird Species Detection Based on the Extraction of Local Details and Global Information Using a Dual-Feature Mixer by Chaoyang Li, Zhipeng He, Kai Lu, Chaoyang Fang

“…Currently, most deep learning algorithms focus on designing local feature extraction modules while ignoring the importance of global information. …”
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3D rock strength prediction by an innovative approach that integrates geostatistics with machine deep learning models by Hichem Horra, Ahmed Hadjadj, Elfakeur Abidi Saad, Khalil Moulay Brahim

“…The results reveal marked improvements in both the prediction range and spatial resolution of rock strength through the proposed methodology. …”
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Sex bias consideration in healthcare machine-learning research: a systematic review in rheumatoid arthritis by Coziana Ciurtin, Shruti Turner, Anahita Talwar, Claudia Maw, Georgina Quayle, Thomas N Watt, Sunir Gohil, Emma Duckworth

“…No paper attempted to mitigate any type of sex bias.Conclusions The findings demonstrate the need for increased promotion of inclusive and equitable ML practices in healthcare to address unchecked sex bias in ML algorithms.PROSPERO registration number CRD42023431754.…”
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Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions by Serdar Erisen

“…Our enhancements showed improvements in the test performance of InternImage-H on the Cityscapes test set (86.2 % mean IoU), on BDD100K (74.1 % mean IoU), and ADE20K datasets (64.0 % mean IoU). …”
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A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. …”
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Deep convolutional neural network (DCNN)-based model for pneumonia detection using chest x-ray images by S. I. Ele, U. R. Alo, H. F. Nweke, A. H. Okemiri, E. O. Uche-Nwachi

“…This could revolutionize healthcare by augmenting the diagnostic process and improving patient outcomes. …”
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Research on the Integration of Sensing and Communication Based on Fractional-Order Fourier Transform by Mingyan Qi, Yuelong Su, Zhaoyi Wang, Kun Lu

“…Second, the three search algorithms and the performance of the integrated sensing and communication waveform are simulated. …”
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Research on Maneuvering Motion Prediction for Intelligent Ships Based on LSTM-Multi-Head Attention Model by Dongyu Liu, Xiaopeng Gao, Cong Huo, Wentao Su

“…The results demonstrate that our proposed model significantly improves the accuracy of ship maneuvering predictions compared to standalone LSTM and MHAM algorithms and exhibits superior generalization performance.…”
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Behavioral economics: science or exoticism? by I. N. Drogobytsky

“…This behavior is inherent in human nature, and therefore subject to scrutiny, learning and improvement. Actually it is engaged and behavioral economics, the main provisions of which are considered in this article.…”
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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Existing object detection algorithms often underperform in such scenarios due to their limited capability in handling fine-grained details and multi-scale objects. …”
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Automated Microservices Identification Through Business Process Analysis: A Semantic-Driven Clustering Approach by Idris Oumoussa, Rajaa Saidi

“…This work marks a step forward in optimizing system modularity and provides a foundation for future scalability improvements.…”
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3Mont: A multi-omics integrative tool for breast cancer subtype stratification. by Miray Unlu Yazici, J S Marron, Burcu Bakir-Gungor, Fei Zou, Malik Yousef

“…Notably, among different BRCA molecular sub-types, Hormone Receptor negative (HR-) BRCA cases, especially Basal-like BRCA sub-types, lack estrogen and progesterone hormone receptors and they exhibit a higher tumor growth rate compared to HR+ cases. Improving survival time and predicting prognosis for distinct molecular profiles is substantial. …”
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Gamification Elements in the Process of Ukrainian Language Training of Pedagogy Specialists by Iryna Humeniuk

“…The article studies the problem of using gamification elements in the process of training future preschool and primary school teachers on the example of the methodology of teaching Ukrainian Language for Professional Purposes. The necessity of improving the methodology of teaching the language to students of different age groups while taking into account the main educational trends and public demand has been substantiated. …”
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Optimising Connectivity and Energy: The Future of LoRaWAN Routing Protocols for Mobile IoT Applications by Izzah N. Buang, K. Zen, Syahrul N. Junaini

“…These approaches have demonstrated improvements in packet delivery ratios (PDRs), latency reduction, and energy efficiency within mobile IoT contexts. …”
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Intelligent SDN to enhance security in IoT networks by Safi Ibrahim, Aya M. Youssef, Mahmoud Shoman, Sanaa Taha

“…This study employs multiclassification algorithms to precisely detect and categorise diverse security threats in SDN. …”
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Influenza virus genotype to phenotype predictions through machine learning: a systematic review by Laura K. Borkenhagen, Martin W. Allen, Jonathan A. Runstadler

“…Machine learning techniques have demonstrated promise in addressing this critical need for other pathogens because the underlying algorithms are especially well equipped to uncover complex patterns in large datasets and produce generalizable predictions for new data. …”
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Energy Demand Forecasting Scenarios for Buildings Using Six AI Models by Khaled M. Salem, Francisco J. Rey-Martínez, A. O. Elgharib, Javier M. Rey-Hernández

“…Understanding and forecasting energy consumption patterns is crucial for improving energy efficiency and human well-being, especially in diverse infrastructures like Spain. …”
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Prediction of Myocardial Infarction Based on Non-ECG Sleep Data Combined With Domain Knowledge by Changyun Li, Yonghan Zhao, Qihui Mo, Zhibing Wang, Xi Xu

“…Multiple features related to HR and RR were extracted and integrated with clinical features; four algorithms—MLP, SVM, XGBoost, and CNN—were employed for model construction. …”
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Breaking the field phenotyping bottleneck in maize with autonomous robots by Jason DeBruin, Thomas Aref, Sara Tirado Tolosa, Rebecca Hensley, Haley Underwood, Michael McGuire, Chinmay Soman, Grace Nystrom, Emma Parkinson, Catherine Li, Stephen Patrick Moose, Girish Chowdhary

“…Abstract Understanding phenotypic plasticity in maize (Zea mays L.) is a current grand challenge for continued crop improvement. Measuring the interactive effects of genetics, environmental factors, and management practices (GxExM) on crop performance is time-consuming, expensive, and a major bottleneck to yield advancement. …”
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