Impact of TMDI on pounding mitigation of insufficiently separated buildings exposed to earthquakes with varying frequencies by Ayman Abd-Elhamed, Sayed Mahmoud, Alaa Sherif, Haytham Essam Amin

“…The TMDI’s optimal design parameters are determined by solving a constrained optimization problem employing an evolutionary algorithm to minimize the displacement response. The obtained numerical results clearly indicate that, TMDI is an effective mechanism in controlling the induced displacements and mitigating the pounding forces between insufficiently separated buildings subjected to earthquake motions of different frequency contents. …”
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Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

“…However, current DLD design lacks clear guidance and heavily depends on expert experience, requiring extensive repetitive microfluidic experiments and numerical simulations. …”
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Detection of Wormhole Attack in Vehicular Ad-hoc Network over Real Map using Machine Learning Approach with Preventive Scheme by Shahjahan Ali, Parma Nand, Shailesh Tiwari

“…The collected data is pre-processed and the k-NN & Random Forest algorithms are applied on this data, to make the model such type so that it can memorize the wormhole attack. …”
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Assessing the temporal transferability of machine learning models for predicting processing pea yield and quality using Sentinel-2 and ERA5-land data by Michele Croci, Manuele Ragazzi, Alessandro Grassi, Giorgio Impollonia, Stefano Amaducci

“…This study aims to rigorously quantify this temporal transferability gap for both pea yield and TR prediction. Four ML algorithms (RF, XGBoost, GPR, SVMr) were evaluated using Sentinel-2 and ERA5-Land data from 2018 to 2024 in northern Italy. …”
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Artificial Intelligence in Education: Analysis and Assessment of Legal Knowledge Using AI Tools by Anvar J. Khurramov, Mavluda A. Axmedshaeva, Fiyuza A. Mukhitdinova, Gulnora A. Xudayberdiyeva, Shahnoza S. Almosova, Makhmud M. Makhamatov, Sherzod R. Khayitov

“…The study examined ethical concerns such as algorithmic bias, transparency, and student privacy, as well as legal dimensions related to consent, data protection, and institutional responsibility. …”
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Non-Destructive Monitoring of External Quality of Date Palm Fruit (<i>Phoenix dactylifera</i> L.) During Frozen Storage Using Digital Camera and Flatbed Scanner by Younes Noutfia, Ewa Ropelewska, Zbigniew Jóźwiak, Krzysztof Rutkowski

“…The general architecture exhibited clear differences in classification accuracy depending mainly on the frozen storage period and imaging device. …”
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Priorities of ensuring hygiene and occupational safety of medical personnel and the resilience of healthcare facilities in emergency situations by R. P. Brukhno, O. P. Yavorovskyi, Yu. M. Skaletskyi, T. O. Zinchenko

“…There is an urgent need to develop clear response algorithms for healthcare facilities to cope with emergency situations that could influence them. …”
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Goal-oriented autonomous decision-making for social robots via collaborative interactive inverse reinforcement learning approach by Mingyue Luo, Hui Li, Wanbo Luo, Hewei Li, Jianan Li

“…However, social robots typically have clear navigation goals, and the practicality of the aforementioned methods is debatable. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…This study implements multivariate time series forecasting using gradient boosting algorithms (XGBoost, CatBoost, and LightGBM) to predict cash flow patterns in banking transactions, focusing on constructing reliable prediction intervals. …”
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Predicting mortality risk in Alzheimer’s disease using machine learning based on lifestyle and physical activity by Ruihong Tang, Liang Tan, Xia Chen, Zhengwu Shan, Zhao Zhang, Panpan Cheng

“…Lifestyle and physical activity levels were identified as significant predictors influencing mortality risk. ML algorithms, notably RSF, effectively predict mortality risk in AD patients, demonstrating clear advantages over traditional statistical models. …”
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Methods of creating a multimedia online gallery by Є.М. Грабовський

“…To test the working hypothesis of the study, such scientific tasks were achieved to achieve goals as algorithmization of the choice of the structure of a multimedia online gallery, coordination of the basic set of functions, classification of functions and sections by clustering. …”
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Quantifying the Accuracy of UAS-Lidar Individual Tree Detection Methods Across Height and Diameter at Breast Height Sizes in Complex Temperate Forests by Benjamin T. Fraser, Russell G. Congalton, Mark J. Ducey

“…This analysis suggests clear distinctions in the performance (true positive and false positive rates) based on tree sizes and ITD method. …”
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Clinical applications of photon-counting CT in neuroimaging by LÜ Haiying, LU Yong, HE Naying

“…., BV72-BV80), PCCT enables clear visualization of intracranial arterial stents and residual aneurysms, offering a new noninvasive alternative to DSA for postope-rative monitoring of intracranial artery treatments. …”
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Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…Its benefits include, being non-invasive, cost-effective, readily accessible, and providing the anaesthetist with clear visualization of essential anatomical landmarks, needle progression, and the spread of local anaesthetic. …”
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Responsible artificial intelligence in public health: a Delphi study on risk communication, community engagement and infodemic management by Keyrellous Adib, David Novillo-Ortiz, Ben Duncan, Daniela Mahl, Mike S Schäfer, Stefan Adrian Voinea, Cristiana Salvi

“…Challenges and risks affect all three components of RCCE-IM equally, with algorithmic bias and privacy breaches being of particular concern. …”
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A Web-Based Interface That Leverages Machine Learning to Assess an Individual&#x2019;s Vulnerability to Brain Stroke by Divyansh Bhandari, Arnav Agarwal, R. Reena Roy, Rajaram Priyatharshini, Rodriguez Rivero Cristian

“…We compare a range of algorithms-including traditional classifiers and deep learning models-and report comprehensive performance metrics (accuracy, precision, recall, F1-score, and AUC-ROC) for each. …”
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Methods of evaluation the quality of teaching in higher education institutions by Irina V. Barannikova, Elena N. Shaforostova

“…A method of assessing the quality of education at universities, based on the criteria of quality of education, the method of expert evaluation, formalization and algorithmization of the process is proposed. The generalized assessment of the group of experts is formed on the basis of average values. …”
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ARTIFICIAL INTELLIGENCE IN ACADEMIA: OPPORTUNITY OR CHALLENGE? by L.H. Grigoryan, M. V. Badalyan, A.Z. Grigoryan

“…On the other hand, the growing reliance on AI raises serious concerns related to academic integrity, data privacy, algorithmic bias, and the potential deskilling of educators. …”
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Advancement of Artificial Intelligence in Cost Estimation for Project Management Success: A Systematic Review of Machine Learning, Deep Learning, Regression, and Hybrid Models by Md. Mahfuzul Islam Shamim, Abu Bakar bin Abdul Hamid, Tadiwa Elisha Nyamasvisva, Najmus Saqib Bin Rafi

“…ML models, including ANNs and deep learning models, represent approximately 70% of the reviewed studies, demonstrating a clear trend toward the adoption of advanced AI techniques. …”
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Spatiotemporal Monitoring of Cyanobacterial Blooms and Aquatic Vegetation in Jiangsu Province Using AI Earth Platform and Sentinel-2 MSI Data (2019–2024) by Xin Xie, Ting Song, Ge Liu, Tiantian Wang, Qi Yang

“…This system integrates phenology-based algorithms with Sentinel-2 MSI imagery, leveraging the AI Earth (AIE) platform developed by Alibaba DAMO Academy. …”
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