Addressing imbalanced data classification with Cluster-Based Reduced Noise SMOTE. by Javad Hemmatian, Rassoul Hajizadeh, Fakhroddin Nazari

“…In recent years, the challenge of imbalanced data has become increasingly prominent in machine learning, affecting the performance of classification algorithms. This study proposes a novel data-level oversampling method called Cluster-Based Reduced Noise SMOTE (CRN-SMOTE) to address this issue. …”
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Evaluation of the Decision Tree Model for Air Condition Classification on the Global Air Pollution Dataset by Cindy Dinda Sabella, Yoga Pristyanto

“…The SVM model showed an improvement of 94.89% to 99.32%, while Random Forest recorded an accuracy of 96.87% with no significant improvement after tuning. …”
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Artificial Intelligence Applications in Pediatric Craniofacial Surgery by Lucas M. Harrison, Ragan L. Edison, Rami R. Hallac

“…Artificial intelligence is rapidly transforming pediatric craniofacial surgery by enhancing diagnostic accuracy, improving surgical precision, and optimizing postoperative care. …”
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Integrating holographic counterparts for intelligent IoT consumer devices by M. Rajesh, M. Usha, Sathishkumar Veerappampalayam Easwaramoorthy

“…Abstract A new paradigm for improving consumer electronics’ real-time data interaction, autonomous decision-making, and system scalability is introduced by integrating Holographic Counterparts (HCs) into Internet of Things (IoT) ecosystems. …”
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An Empirical Evaluation of Supervised Learning Methods for Network Malware Identification Based on Feature Selection by C. Manzano, C. Meneses, P. Leger, H. Fukuda

“…The selected features were used to train the algorithms using binary and multiclass classification. …”
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A deep multiple self-supervised clustering model based on autoencoder networks by Ling Zhu, Zijin Liu, Guangyu Liu

“…Compared to the performance of traditional fuzzy C-Means clustering algorithms on various public datasets, our proposed method significantly reduces computation time and noticeably improves iteration efficiency.…”
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Marine Voyage Optimization and Weather Routing with Deep Reinforcement Learning by Charilaos Latinopoulos, Efstathios Zavvos, Dimitrios Kaklis, Veerle Leemen, Aristides Halatsis

“…These algorithms are computationally costly, so we split optimization into an offline phase (costly pre-training for a route) and an online phase where the algorithms are fine-tuned as updated weather data become available. …”
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A Review of Personalised Cardiac Computational Modelling Using Electroanatomical Mapping Data by Ovais A Jaffery, Lea Melki, Gregory Slabaugh, Wilson W Good, Caroline H Roney

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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…Our evaluation focuses on various aspects: torque and flux ripple reduction, speed tracking improvement, switching losses minimization, algorithmic complexity simplification, and sensitivity reduction to parameter variations. …”
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Predicting Mesothelioma Using Artificial Intelligence: A Scoping Review of Common Models and Applications by Malihe Ram MS, Mohammad Reza Afrash PhD, Khadijeh Moulaei PhD, Erfan Esmaeeli, Mohadeseh Sadat Khorashadizadeh, Ali Garavand PhD, Parastoo Amiri PhD, Azam Sabahi PhD

“…Introduction Mesothelioma is a type of lung cancer caused by asbestos exposure, and early diagnosis is crucial for improving survival chances. Artificial intelligence offers a potential solution for the timely diagnosis and staging of the disease. …”
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Multi-objective optimization of HESS control for optimal frequency regulation in a power system with RE penetration by Ousama M.T. Ajami, Rodney H.G. Tan, Mithulan Nadarajah, Farah Adilah Jamaludin, Adlan Bagus Pradana

“…The Simultaneously Optimized Virtual Synchronous Generator Controlled HESS (SO VSG-HESS) provides the best frequency nadir, with an average improvement of 0.63 %, but with a slight increase in settling time.…”
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Implementation of personalized frameworks in computational thinking development: implications for teaching in software engineering by Josué Guevara-Reyes, Mariuxi Vinueza-Morales, Erick Ruano-Lara, Cristian Vidal-Silva

“…The development of computational thinking (CT) is crucial in software engineering education, as it enables students to analyze complex problems, design algorithmic solutions, and adapt to an evolving digital landscape. …”
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Attention-enhanced StrongSORT for robust vehicle tracking in complex environments by Wei Xu, Xiaodong Du, Ruochen Li, Bingjie Li, Yuhu Jiao, Lei Xing

“…This design enhances cross-dimensional feature interaction through localized channel-spatial attention gates, significantly improving occlusion-resistant feature representation (IDF1  $$\uparrow$$  9.99%, IDsw  $$\downarrow$$  9.85%). …”
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A Review of Approaches for Rapid Data Clustering: Challenges, Opportunities, and Future Directions by Mahnoor, Imran Shafi, Mahnoor Chaudhry, Elizabeth Caro Montero, Eduardo Silva Alvarado, Isabel de la Torre Diez, Md Abdus Samad, Imran Ashraf

“…The paper includes a brief introduction to clustering, discussing various clustering algorithms, improvements in handling various data types, and appropriate evaluation metrics. …”
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Application and prospects of machine learning for rockfalls, landslides and debris flows by Jiazhu WANG, Yongbo TIE, Yongjian BAI, Yanchao GAO, Donghui WANG, Mingzhi ZHANG

“…Artificial intelligence, notably machine learning algorithms, has emerged as a hot point in this domain. …”
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Development of a machine learning prognostic model for early prediction of scrub typhus progression at hospital admission based on clinical and laboratory features by Youguang Lu, Zixu Wang, Junhu Wang, Yingqing Mao, Chuanshen Jiang, Jinpiao Wu, Haizhou Liu, Haiming Yi, Chao Chen, Wei Guo, Liguan Liu, Yong Qi

“…The models can help clinicians assess the potential risks of their patients early on, thereby improving patient outcomes.…”
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Convolutional neural networks and vision transformers for Plankton Classification by Loris Nanni, Alessandra Lumini, Leonardo Barcellona, Stefano Ghidoni

“…Final results show that the ensemble-based approach achieves a remarkable accuracy improvement over individual CNN models and over standalone Vision Transformers.…”
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Slip and tractive efficiency of an electric tractor with a 4WID E-axle system by SeungYun Baek, HyeonHo Jeon, CheolGyu Park, YongJoo Kim

“…The results indicate that reducing travel speed decreases slip, which in turn improves tractive efficiency and enhances energy efficiency. …”
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Trust in Smart City Mobility Applications: A Multi-Agent System Perspective by Maryam Javaherian

“…Real-world data will validate the approach, enhancing decision-making and improving urban mobility. …”
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Using AI in Optimizing Oral and Dental Diagnoses—A Narrative Review by Amelia Surdu, Dana Gabriela Budala, Ionut Luchian, Liliana Georgeta Foia, Gina Eosefina Botnariu, Monica Mihaela Scutariu

“…AI technologies, such as machine learning, deep learning, and computer vision, are increasingly being integrated into dental practice to analyze clinical images, identify pathological conditions, and predict disease progression. By utilizing AI algorithms, dental professionals can detect issues like caries, periodontal disease and oral cancer at an earlier stage, thus improving patient outcomes.…”
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