Temperature-dependent compressive strength modeling of geopolymer blocks utilizing glass powder and steel slag by Supriya Janga, Ashwin Raut, Alireza Bahrami, T. Vamsi Nagaraju, Sridevi Bonthu

“…The support vector regressor (SVR) model outperformed other regression and boosting models, obtaining a high coefficient of determination (R2) value of 0.95, indicating superior predictive accuracy. The reduced error levels and high R2 values highlighted the enhanced performance of the SVR model. …”
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A big data analysis algorithm for massive sensor medical images by Sarah A. Alzakari, Nuha Alruwais, Shaymaa Sorour, Shouki A. Ebad, Asma Abbas Hassan Elnour, Ahmed Sayed

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Multiple objectives escaping bird search optimization and its application in stock market prediction based on transformer model by Dedai Wei, Zimo Wang, Minyu Qiu, Juntao Yu, Jiaquan Yu, Yurun Jin, Xinye Sha, Kaichen Ouyang

“…In the context of stock price prediction, we select the closing price datasets of Amazon, Google, and Uniqlo, using MOEBS to optimize the core hyper parameters of the Transformer while considering multiple objectives, including training set RMSE, testing set RMSE, and testing set error variance. In the experiments, this paper first compares CNN, LSTM, BiLSTM, GRU, and traditional Transformer models to establish the Transformer as the optimal model for stock market prediction. …”
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Price discovery and market efficiency of cardamom in India by A.N. Vijayakumar

“…Design/methodology/approach – This study used Johansen co-integration, vector error correction model, Granger causality and regression with dummy variables to understand a day of the week effect in high-value agri-commodity of cardamom e-auction prices. …”
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Regional Frequency Analysis Using L-Moments for Determining Daily Rainfall Probability Distribution Function and Estimating the Annual Wastewater Discharges by Pau Estrany-Planas, Pablo Blanco-Gómez, Juan I. Ortiz-Vallespí, Javier Orihuela-Martínez, Víctor Vilarrasa

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Jointing Adjacent Environmental Variation Into a Deep Learning Model for Gap-Filling Passive Microwave-Based Land Surface Temperature by Weizhen Ji, Yunhao Chen, Haiping Xia, Han Gao, Lei Zhu

“…According to the results, the proposed model achieves root mean squared error (RMSE) of 1.87 K/1.89 K and 1.69 K/1.71 K for the two AMSR LST-based validations during the daytime/nighttime. …”
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Predicting depression and unravelling its heterogeneous influences in middle-aged and older people populations: a machine learning approach by Ling Zhang, Ruigang Wei, Jingwen Zhou, Lin Tan, Xiaolong Che, Minqinag Zhang, Xiaoyue Ning, Zhiliang Zhong

“…Results The LSTM model effectively predicted depression-related variables (mean square error = 0.067). The average AUC of the five ML models ranged from 0.78 to 0.82. …”
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Cytochrome P450 2J2*7 Single-nucleotide Polymorphism and Nocturnal Hypertension in an Elderly Turkish Population by Elif Hilal Vural, Arzu Güneş Granberg, Atiye Çengel, Marja-Liisa Dahl, Hakan Zengil

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Machine Learning-Based Objective Evaluation Model of CTPA Image Quality: A Multi-Center Study by Sun Q, Liu Z, Ding T, Shi C, Hou N, Sun C

“…However, the limited sample size may affect the model’s generalizability, so it’s essential to conduct further research with larger datasets.Keywords: CT pulmonary angiography, machine learning, image quality, data interpretation…”
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Reliability of the use of foot pressure pain threshold in adults: a test-retest analysis by Lidia Mayorga-Vega, Ana Maria Jimenez-Cebrian, Francisco Javier Barón-López, Alonso Montiel-Luque, Juan Carlos Benavente-Marín, Julia Warnberg

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Robust Image Steganography Approach Based on Edge Detection Combined With CNN Algorithm by Rana Al-Rawashdeh, Md Mahfuzur Rahman, Mahmood Niazi

“…The developed model also provides a higher capacity of 8 bits per pixel (BPP) and have ensured the robustness of the system against common image processing attacks (e.g., JPEG compression, Gaussian noise, salt-and-pepper, speckle, and filtering) which is validated with PSNR values up to 76.2 dB and error rates (Re) ranging between 0.32 and 0.47. Security testing using state-of-the-art steganalyzers (Xu-Net and Ye-Net) shows detection accuracy around 0.45-0.67 only, indicating strong resistance to steganalysis.…”
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Frequency of Diabetic Nephropathy in Type 2 Diabetic Patients Using Spot Urine ACR and Its Associated Risk Factors by Asad Ullah, Sayed Ali Zeeshan Kausar, Muhammad Ayaz, Muhammad Shabbir Khan, Sami Ullah, Rida Fatima Saeed

“…Place and Duration of Study: This research was carried out at the Department of Medicine, Muhammad Teaching Hospital (MTH) Peshawar, Pakistan from February 01, 2023, to July 31, 2023. …”
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COMPARISON OF POROSITY PREDICTION FROM SEISMIC DATA IN THE F3 BLOCK, NETHERLANDS USING MACHINE LEARNING by Urip Nurwijayanto Prabowo, Sudarmaji Sudarmaji, Jarot Setyowiyoto, Sismanto Sismanto

“…The results indicate that the cycle-GAN produces the most accurate porosity estimates, with a mean square error (MSE) of 0.603 and a Pearson correlation coefficient (PCC) of 0.713. …”
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Bridging human and machine intelligence: Reverse-engineering radiologist intentions for clinical trust and adoption by Akash Awasthi, Ngan Le, Zhigang Deng, Rishi Agrawal, Carol C. Wu, Hien Van Nguyen

“…Additionally, it holds the potential for automated error correction, guiding junior radiologists, and fostering more effective training and feedback mechanisms. …”
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Clinical usefulness of hemoencephalography beyond the neurofeedback by Serra-Sala M, Timoneda-Gallart C, Pérez-Álvarez F

“…It is available to any research group for its relative simplicity and low cost and is a useful tool for assessing prefrontal-dependent functions. …”
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Analysis of Abnormal Sea Level Rise in Offshore Waters of Bohai Sea in 2024 by Song Pan, Lu Liu, Yuyi Hu, Jie Zhang, Yongjun Jia, Weizeng Shao

“…WRF-derived wind speeds (0.05° grid resolution) were validated against Haiyang-2 (HY-2) scatterometer observations, yielding a root mean square error (RMSE) of 1.88 m/s and a correlation coefficient (Cor) of 0.85. …”
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Evaluation of a coastal acoustic buoy for cetacean detections, bearing accuracy and exclusion zone monitoring by Kaitlin J. Palmer, Sam Tabbutt, Douglas Gillespie, Jesse Turner, Paul King, Dominic Tollit, Jessica Thompson, Jason Wood

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Detection and Theoretical Numerical Simulation of the Failure Depth of the Bottom Plate in Belt Pressure Mining by Xipeng Cui, Shuancheng Gu, Jinhua Li, Jiahao Wen, Kailei Zhao, Xinlei Liu

“…It provides important technical parameters for the safe setting of the effective water barrier layer and the selection and timing of the grouting layer of the floor, which can bring considerable economic and social benefits. The research results have important popularization value.…”
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A High-Precision ID-TIMS U-Pb Dating Method of Apatite by Jiarun TU, Hongying ZHOU, Yurong CUI, Guozhan LI, Jianzhen GENG, Jian ZHANG

“…Moreover, taking MAP-3 as a calibration standard, LA-ICP-MS U-Pb dating was performed on apatite in Durango and Otter Lake, resulting in lower intercept ages of 32.1±0.6Ma (MSWD=1.3, n=36) and 910±13Ma (MSWD=1.6, n=36) in a Tera-Wasserburg diagram, which were consistent with the previous research results within error. This gives further evidence that MAP-3, with extremely low common lead content, is an ideal apatite in situ U-Pb dating standard. …”
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Investigating the Influence of the Weed Layer on Crop Canopy Reflectance and LAI Inversion Using Simulations and Measurements in a Sugarcane Field by Longxia Qiu, Xiangqi Ke, Xiyue Sun, Yanzi Lu, Shengwei Shi, Weiwei Liu

“…Recent research in agricultural remote sensing mainly focuses on how soil background affects canopy reflectance and the inversion of LAI, while often overlooking the influence of the weed layer. …”
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