Shale volume estimation using machine learning methods from the southwestern fields of Iran by Parirokh Ebrahimi, Ali Ranjbar, Yousef Kazemzadeh, Ali Akbari

“…The models were evaluated based on performance metrics such as correlation coefficient (R2), average relative error (ARE), root mean square error (RMSE), and mean squared error (MSE). …”
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Multilane Microscopic Modeling to Measure Mobility and Safety Consequences of Mixed Traffic in Freeway Weaving Sections by Mudasser Seraj, Tony Z. Qiu

“…Weaving sections are components of highway networks that introduce a heightened likelihood for bottlenecks and collisions. …”
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Mortality Prediction in COVID-19 Using Time Series and Machine Learning Techniques by Tanzina Akter, Md. Farhad Hossain, Mohammad Safi Ullah, Rabeya Akter

“…This study compares time series and machine learning methods, including support vector machines (SVMs) and neural networks (NNs), to forecast the mortality rate in seven countries: the United States, India, Brazil, Russia, France, China, and Bangladesh. …”
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A Novel Over-The-Air Measurement Method for Linear Frequency Modulation Signals Using Continuous Wave Receiver by Sungpil Cheon, Byungkwan Kim

“…The findings suggest the method’s potential for real-time applications, including cooperative and networked radar systems, where OTA measurements are essential for efficient operation.…”
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An Integrated New Product Development Evaluation Model in an Interval Type-2 Fuzzy Environment for PLM Strategy Setting by Sanja Puzović, Jasmina Vesić Vasović, Danijela Tadić, Dragan D. Milanović

“…Product Lifecycle Management (PLM) provides a paradigmatic model that enables companies to operate more effectively in the face of shorter product lifecycles, global networking, and increasing complexity. However, despite strengthening the PLM initiative, companies still struggle to implement this concept. …”
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Controls on lacustrine shale reservoir characteristics: insights from deposition, diagenesis, and geochemistry in the Jurassic Qianfoya Formation by Lixue Cheng, Lixue Cheng, Jun Peng

“…Laminated facies exhibit optimal reservoir quality compared to blocky or banded types, with positive correlations between clay-organic content and storage capacity. …”
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Magnetically tunable 4 × 2 encoder utilizing Terfenol-D-embedded phononic crystal ring resonators by Ehsan Mehdizadeh Omrani, Fakhroddin Nazari

“…The encoder's performance was assessed through the application of the finite element method, yielding an average contrast ratio of 10.16 dB. This proposed encoder offers a straightforward and effective solution for acoustic communication systems and networks, demonstrating significant potential for practical applications.…”
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Analysis of the Energy Complex Member of the EАEU Countries and the Formation of Groups-Technologies of its Digitalization by M. I. Rusetskaya, T. F. Mancerova, E. P. Korsak

“…The article provides an overview of the dynamics of the main economic indicators of the Union countries and the main indicators of their electric power industries, examines the structure of electricity production, energy portfolio, average electricity prices, total electricity consumption by sector. …”
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The innovation path of VR technology integration into music classroom teaching in colleges and universities by Yupeng Han, Lin Han, Chun Zeng, Wei Zhao

“…Experimental results indicate that the IIMT model generates images and audio with detail richness and clarity scores ranging from 0.7 to 1.0. The optimized system maintains a response time between 85 and 115 milliseconds and an average frame rate of 55 to 65 frames per second, ensuring smooth interaction. …”
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A Secure IIoT Environment That Integrates AI-Driven Real-Time Short-Term Active and Reactive Load Forecasting with Anomaly Detection: A Real-World Application by Md. Ibne Joha, Md Minhazur Rahman, Md Shahriar Nazim, Yeong Min Jang

“…The Industrial Internet of Things (IIoT) revolutionizes both industrial and residential operations by integrating AI (artificial intelligence)-driven analytics with real-time monitoring, optimizing energy usage, and significantly enhancing energy efficiency. …”
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The Role of Artificial Intelligence in Sports Analytics: A Systematic Review and Meta-Analysis of Performance Trends by Przemysław Pietraszewski, Artur Terbalyan, Robert Roczniok, Adam Maszczyk, Kajetan Ornowski, Daria Manilewska, Szymon Kuliś, Adam Zając, Artur Gołaś

“…Methods applied encompassed Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, reinforcement learning, and predictive modeling architectures. …”
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Advancing Breast Cancer Detection: SE-Conformer Framework for Malignancy Detection in Histopathology Images by Lekha S. Nair, K. R. Amarnath, Jyothisha J. Nair

“…Experimental results, obtained through K-fold cross-validation, indicate that the model performs optimally on <inline-formula> <tex-math notation="LaTeX">$200\times $ </tex-math></inline-formula> magnification images, achieving an average accuracy, precision, and recall of 0.97. …”
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Development of PM_2.5 Forecast Model Combining ConvLSTM and DNN in Seoul by Ji-Seok Koo, Kyung-Hui Wang, Hui-Young Yun, Hee-Yong Kwon, Youn-Seo Koo

“…Future work will focus on optimizing the network structure to improve long-term forecast accuracy.…”
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A algorithm for low light image enhancement in coal mine underground based on illumination constraints by Yuchen BAI, Zuohua MIAO, Houyou XU, Mengting WANG

“…Results indicate that this algorithm surpasses others in visual information fidelity (VIF), structural similarity index metric (SSIM), and peak signal to noise ratio (PSNR), achieving averages of 0.58, 0.61, and 16.58 respectively. Compared to the original model, it showed improvements of approximately 23.40%, 16.07%, and 20.45% in these metrics, demonstrating optimal image enhancement effectiveness.…”
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Morphological Analysis and Subtype Detection of Acute Myeloid Leukemia in High-Resolution Blood Smears Using ConvNeXT by Mubarak Taiwo Mustapha, Dilber Uzun Ozsahin

“…Automated AML subtype detection is especially important for underrepresented subtypes to ensure equitable diagnostics; (2) Methods: This study explores the potential of ConvNeXt, an advanced convolutional neural network architecture, for classifying high-resolution peripheral blood smear images into AML subtypes. …”
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A hybrid LSTM-transformer model for accurate by Tianren Zhao, Yanhui Zhang, Minghao Wang, Wei Feng, Shengxian Cao, Gong Wang

“…The regression task is optimized using the Mean Squared Error loss function and trained with the Adam optimizer. …”
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Machine learning-guided construction of an analytic kinetic energy functional for orbital free density functional theory by Sergei Manzhos, Johann Lüder, Pavlo Golub, Manabu Ihara

“…A hybrid Gaussian process regression—neural network method was used to understand the type of functional dependence of $\overline\tau$ on the features which contained cell-averaged terms of the 4th order gradient expansion and the product of the electron density and Kohn–Sham (KS) effective potential. …”
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Deep Learning-Based Detection of Tuberculosis Using a Gaussian Chest X-Ray Image Filter as a Software Lens by Luca Eisentraut, Christopher Mai, Johanna Hosch, Amelie Benecke, Pascal Penava, Ricardo Buettner

“…Convolutional neural networks have proven effective in detecting such diseases from medical images, achieving high accuracy in identifying tuberculosis from chest X-rays. …”
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Can the nutritional geometric framework unveil how macronutrients in pollen shape solitary bee foraging and survival? by Jaya Sravanthi Mokkapati, Natalie Boyle, Pierre Ouvrard, Adrien Sicard, Christina M. Grozinger

“…Paired-choice experiments further revealed that bees regulated nutrient intake, converging on an average intake of 6.6 : 1 ± 1.6 P : L. These results suggest that M. rotundata exhibits a clear macronutrient preference and regulation behaviour, optimizing nutrient intake consistent with a functional nutritional target. …”
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Improved cholera control in Kenya: A retrospective analysis of 2017–2019 in Nairobi and Homabay by Kyeng Mercy, Ganesh Pokhariyal, Noah T. Fongwen, Nicaise Ndembi, Lucy Kivuti-Bitok

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