A Comprehensive Review of Smartphone and Other Device-Based Techniques for Road Surface Monitoring by Saif Alqaydi, Waleed Zeiada, Ahmed El Wakil, Ali Juma Alnaqbi, Abdelhalim Azam

“…Future work could focus on improving sensor calibration, data synchronization, and machine learning models to handle diverse real-world conditions. …”
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Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification by Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah

“…These findings contribute to the field of statistical modeling by demonstrating how ensemble methods can improve classification accuracy and provide valuable insights for data-driven policymaking, thus enhancing regional development planning and supporting future HDI-related research.…”
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Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning by Q. Cheng, J. Bai, X. Wang, B. Shi, W. Gao, F. Shu

“…Simulation results show that the proposed algorithms can effectively improve the rate performance compared to fixed PA strategies, only optimizing PA factor, aided by passive IRS, and without IRS.…”
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Student Dropout Prediction Using Random Forest and XGBoost Method by Lalu Ganda Rady Putra, Didik Dwi Prasetya, Mayadi Mayadi

“…Predicting student attrition accurately can help institutions implement timely interventions to improve retention. Objective: This study aims to evaluate the effectiveness of the Random Forest and XGBoost algorithms in predicting student attrition based on demographic, socioeconomic, and academic performance factors. …”
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A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

“…To realize the full potential of this unique Active RFID and TinyML-based livestock localization system in Pakistan, further research should focus on optimizing localization algorithms, enhancing TinyML models, and exploring interaction with upcoming technologies …”
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Applications, Challenges, and Future Perspectives of Artificial Intelligence in Psychopharmacology, Psychological Disorders and Physiological Psychology: A Comprehensive Review by Mohammad Hossein Salemi, Elham Foroozandeh, Molouk Khademi Ashkzari

“…This review examines AI’s transformative role, applications, challenges, and future directions in these fields. AI tools improve diagnostic accuracy by analyzing brain imaging, health records, and behavioral data, enabling precise identification of disorders like depression and schizophrenia. …”
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Enhancing predictive maintenance in automotive industry: addressing class imbalance using advanced machine learning techniques by Yashashree Mahale, Shrikrishna Kolhar, Anjali S. More

“…Six machine learning models, including logistic regression, support vector machine, decision tree, and random forest, along with gradient boosting algorithms using extreme gradient boost (XGBoost) and light gradient boosting machine frameworks, were implemented. …”
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DNA familial binding profiles made easy: comparison of various motif alignment and clustering strategies. by Shaun Mahony, Philip E Auron, Panayiotis V Benos

“…In addition, multiple-alignment strategies for binding profiles and tree-building methods are tested for their efficiency in constructing generalized binding models. A new method for automatic determination of the optimal number of clusters is developed and applied in the construction of a new set of familial binding profiles which improves upon TF classification accuracy. …”
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synax: A Differentiable and GPU-accelerated Synchrotron Simulation Package by Kangning Diao, Zack Li, Richard D. P. Grumitt, Yi Mao

“…We further demonstrate the potential of AD in enabling full posterior inference using gradient-based inference algorithms. Using synax with HMC to perform inference over a four-parameter test model, we attain a twofold improvement compared to standard random walk Metropolis–Hastings (RWMH). …”
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Isfahan Artificial Intelligence Event 2023: Macular Pathology Detection Competition by Farnaz Sedighin, Maryam Monemian, Zahra Zojaji, Ahmadreza Montazerolghaem, Mohammad Amin Asadinia, Seyed Mojtaba Mirghaderi, Seyed Amin Naji Esfahani, Mohammad Kazemi, Reza Mokhtari, Maryam Mohammadi, Mohadese Ramezani, Mahnoosh Tajmirriahi, Hossein Rabbani

“…Researchers tested their algorithms and competed for the best classification results. …”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…This paper introduces an innovative approach to address this issue, leveraging a combination of neural network-based reduced order modeling and a multi-objective genetic algorithm. This methodology aims to optimize the aerodynamic and aero-acoustic characteristics of an S8xx-series airfoil, including the trailing edge serration geometry. …”
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Measuring the impact of technological innovation, green energy, and sustainable development on the health system performance and human well-being: Evidence from a machine learning-... by Alaeddine Mihoub, Montassar Kahia, Mohannad Alswailim

“…Within this context, this study intended to examine the impact of recent innovations, logistical measures, Information and Communication Technology (ICT) diffusion, environmental quality improvements, economic growth, and green (renewable) energy exploitation on health performance and well-being, in Saudi Arabia from 1990 to 2022, by implementing machine learning models (random forest and gradient boosting) and regression algorithms (ridge and lasso). …”
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An Approach using Skeleton-based Representations and Neural Networks for Yoga Pose Recognition by Nguyen Hai Thanh, Truong Nguyen Nhat, Pham Linh Thuy Thi, Pham Ngoc Huynh

“…Negative and evil auras will be pushed away, and the worldview will improve. Yoga practice has incorrectly caused many unwanted injuries for practitioners. …”
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Effect of tool angle in nanocutting of single crystal GaN using diamond cutter by Yongqiang WANG, Hao XIA, Zhihang HU, Shuaiyang ZHANG, Shaohui YIN

“…Large-scale MD simulations are meticulously performed to model the nanoscale cutting process of single-crystal GaN using a diamond tool. …”
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Integrated Platform for Bio-Image Processing and Identification of Cervical Cancer by Larisa-Dalina LAZĂR, Diogen BABUC, Todor IVAŞCU

“…Following this, the cervical cells are segmented and classified using a combination of machine learning algorithms, such as shallow machine learning models and Convolutional Neural Networks (CNN). …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Artificial intelligence and machine learning are rapidly evolving fields that have the potential to transform women's health by improving diagnostic accuracy, personalizing treatment plans, and building predictive models of disease progression leading to preventive care. …”
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Enhanced pulmonary nodule detection using a transformer framework with dual fusion and gated mechanism by Kelei Sun, Yihang Wang, Huaping Zhou

“…Furthermore, a Gated Sampling and Dual Fusion Enhanced Path Aggregation Network (GDPAN) is proposed, which dynamically extracts informative features by embedding weight information into the feature maps and performs efficient multiscale fusion, thereby improving the detection of small-sized nodules. The experimental results show that GD-RTDETR increases AP, $$\hbox {AP}_{50}$$ AP 50 , $$\hbox {AP}_{75}$$ AP 75 , and $$\hbox {AP}_{S}$$ AP S by 4.1%, 1.0%, 8.1%, and 4.0%, respectively, achieving the best performance among all the models compared.…”
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Architectural Gaps in Generative AI: Quantifying Cognitive Risks for Safety Applications by He Wen, Pingfan Hu

“…The study advocates for the development of AI architectures that better reflect human cognitive structures to reduce these risks and improve reliability in safety applications.…”
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In Vitro Oral Cavity Permeability Assessment to Enable Simulation of Drug Absorption by Pankaj Dwivedi, Priyata Kalra, Haiying Zhou, Khondoker Alam, Eleftheria Tsakalozou, Manar Al-Ghabeish, Megan Kelchen, Giovanni M. Pauletti

“…The tissue-associated dose fraction recovered at the end of the transport experiment was significantly increased in the buccal EpiOral™ tissue model, reaching up to 8.5% for sufentanil. <b>Conclusions</b>: Experimental permeation data collected for selected APIs in FDA-approved oral cavity products will serve as a training set to aid the development of predictive computational models for improving algorithms that describe drug absorption from the oral cavity. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…The XGBoost models exhibited moderate improvement (+0.01683) post-validation. …”
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