Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

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MODIFICATION OF STUDENT ASSESSMENT CRITERIA AS A CONDITION OF MOTIVATION INCREASING FOR PHYSICAL EDUCATION LESSONS by E. M. Revenko

“…The obligatory accounting of specific features of age development is necessary for optimization of the organization of physical training.Methods. …”
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Development of Recurrent Neural Networks for Thermal/Electrical Analysis of Non-Residential Buildings Based on Energy Consumptions Data by Elisa Belloni, Flavia Forconi, Gabriele Maria Lozito, Martina Palermo, Michele Quercio, Francesco Riganti Fulginei

“…Consumptions trends for a building are generated using the EnergyPlus™ dynamic simulation software over a timespan of a year in different locations, and the data are then used to train neural network models. …”
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Techno-Economic Operation and Environmental Life-Cycle Assessment of a Solar PV-Driven Islanded Microgrid by M. A. Parvez Mahmud, Nazmul Huda, Shahjadi Hisan Farjana, Candace Lang

“…Microgrids (MGs) are playing an important role in the maximum utilization of distributed energy resources. The optimal economic operation and low-carbon electricity generation can enhance MGs effectiveness. …”
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Microstructural characterization and hardness prediction of AlCuCrFeNi high entropy alloys using Transformer-based Physics-Informed Neural Networks (T-PINN) by Mohamed Yasin Abdul Salam, Enoch Nifise Ogunmuyiwa, Victor Kitso Manisa, Abid Yahya, Irfan Anjum Badruddin

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Spatiotemporal Land Use Change Detection Through Automated Sampling and Multi-Feature Composite Analysis: A Case Study of the Ebinur Lake Basin by Yi Yang, Liang Zhao, Ya Guo, Shihua Liu, Xiang Qin, Yixiao Li, Xiaoqiong Jiang

“…This study proposes an innovative technical framework that integrates automated sample generation, multi-feature optimization, and classification model refinement to enhance the accuracy of land use classification and enable detailed spatiotemporal analysis in the Ebinur Lake Basin. …”
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Dissipative Magneto-thermo-convection of Nanofluid Past through a Semi-infinite Vertical Surface with Ohmic Heating by Asra Anjum, Shaik Abdul Gaffar, Sateesh Kumar, Samdani Peerusab

“…The Buongiorno model offers a thorough framework for evaluating nanofluid dynamics since it considers both thermophoresis (Nt), Buoyancy ratio (Nr), and Brownian motion (Nb). …”
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Enhancing Fracture Detection in Remote Settings: Evaluating the Efficacy of FIXUS AI Deep Learning Algorithms in Identifying Fifth Metatarsal Fractures Using Mixed-Quality X-rays by Atta Taseh MD, Alireza Gholipour PhD, Mani Eftekhari, Alireza Ebrahimi MD, Alexandra F. Flaherty MD, MS, Alexandra F. Flaherty MD, MS, Sumner Jones, Varun Nukala, Gregory R. Waryasz MD, Daniel Guss MD, MBA, John Y. Kwon MD, Christopher W. DiGiovanni MD, Lorena Bejarano-Pineda MD, Soheil Ashkani-Esfahani MD

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PERFORMANCE STUDY OF THE DTU MODEL FOR RELATIONAL DATABASES ON THE AZURE PLATFORM by Serhii Minukhin

“…The aim of the study is to develop a system of indicators for monitoring the current state of work with the database for reasonable decision-making on the choice of a certain price category of the DTU model of the MS Azure cloud service, which will optimize the results of working with the database. platforms Achieving the set goals involves the following tasks: to analyze modern tools and services for working with databases, in particular relational databases, on Azure and AWS cloud platforms, the features of their application and implementation; develop software for generating test relational databases of different sizes; test the generated databases on a local resource; taking into account the characteristics of the levels of the Azure DTU model, develop a new system of performance indicators, which includes 2 groups - time indicators and indicators of the load on existing platform resources; develop and implement queries of varying complexity for the generated test database for different levels of the DTU model and analyze the results. …”
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A multi-dimensional performance evaluation of large language models in dental implantology: comparison of ChatGPT, DeepSeek, Grok, Gemini and Qwen across diverse clinical scenarios by Xing Wu, Guofei Cai, Bin Guo, Leizi Ma, Siqi Shao, Jun Yu, Yuchen Zheng, Linhong Wang, Fan Yang

“…The PCA results further indicate that Gemini-2.0-flash-thinking demonstrated the best comprehensive ability in both types of tasks, and reveal the existing differences in the performance of various LLMs. Conclusion This study reveals diverse LLMs differentiated capabilities in dental implantology, recommending context-specific model selection to different clinical scenario, as Gemini-2.0-flash-Thinking demonstrates optimal performance, notably for high-level clinical support. …”
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A genetic programming-based ensemble method for long-term electricity demand forecasting by Hayat Ahmed Issa, Hasan Hüseyin Çevik, Ahmet Yilmaz, Mehmet Cunkas

“…The preliminary forecast values generated in this stage were further refined in the second stage. …”
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A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

“…Using the cropped lung images, we trained several pre-trained Deep Convolutional Neural Networks (DCNNs) on the images with hyperparameters optimized by a Bayesian algorithm. Different combinations of trained DCNNs were compared, and the combination with the maximum accuracy was retained as the winning combination. …”
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Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images by Sarah Oraby, Ahmed Emran, Basel El-Saghir, Saeed Mohsen

“…The CNN model undergoes hyperparameter optimization and incorporates data augmentation strategies to maximize its efficiency. …”
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Assessment of transmission network connection solutions based on HVAC for offshore wind by Mattia Deriu, Michela Migliori, Corrado Gadaleta, Marco Cortese, Enrico Maria Carlini, Maria Dicorato, Giuseppe Forte, Gioacchino Tricarico

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Fault detection and assessment in an AC microgrid system using modified complex plane via positive sequence current measurement by Chinmayee Biswal, Pravat Kumar Rout, Binod Kumar Sahu, Manohar Mishra

“…Integrating distributed generations (DGs) into microgrids leads to many significant issues and challenges in fault detection due to bidirectional power flow, inertia change, fault current variation under different operating conditions, and topological changes. …”
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Illumination-adaptative granularity progressive multimodal image fusion method by Chuanyun WANG, Dongdong SUN, Mingqi ZHOU, Tian WANG, Qian GAO, Zhaokui LI

“…During the training phase, prior knowledge is used to generate augmented images as pseudo-labels. Homogeneous and heterogeneous loss functions are constructed based on different environmental conditions, enabling adaptive learning. …”
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A comparative study of deep reinforcement learning for crop production management by Joseph Balderas, Dong Chen, Yanbo Huang, Li Wang, Ren-Cang Li

“…However, these methods have not yet been systematically evaluated under identical conditions. In this study, we evaluated PPO and DQN against static baseline policies across three different RL tasks, fertilization, irrigation, and mixed management, provided by the gym-DSSAT environment. …”
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The relative data hungriness of unpenalized and penalized logistic regression and ensemble-based machine learning methods: the case of calibration by Peter C. Austin, Douglas S. Lee, Bo Wang

“…Abstract Background Machine learning methods are increasingly being used to predict clinical outcomes. Optimism is the difference in model performance between derivation and validation samples. …”
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RESEARCH ON ACTIVE CONTROL OF VARIABLE MASS SEAT SUSPENSION USING PD CONTROL by AN CunSheng, CHEN XiaoLiang, WEI WeiZhen, LIU Kui

“…The proposed control system structure was based on several different controllers. The primary controller was used to evaluate the actual value of the main force that should be generated in the suspension system, and the secondary controller was used to calculate the instantaneous value of the signal that controled the active element through its reverse model. …”
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Nighttime light intensity and brightness suitability in urban functional zones by Ming Liu, Ruicong Li, Yiwei Li, Ezzaddeen Ali Mohammed Saeed AL-Mowallad, Chenglong Wu, Wenjing Wang

“…Abstract The identification and distribution of urban functional zones play a crucial role in optimizing urban planning and resource allocation. The differences in brightness of the nocturnal light environment further reveal the characteristics of urban functions. …”
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