Harnessing smartphone RGB imagery and LiDAR point cloud for enhanced leaf nitrogen and shoot biomass assessment - Chinese spinach as a case study by Aravind Harikumar, Aravind Harikumar, Itamar Shenhar, Itamar Shenhar, Itamar Shenhar, Miguel R. Pebes-Trujillo, Miguel R. Pebes-Trujillo, Lin Qin, Menachem Moshelion, Menachem Moshelion, Jie He, Jie He, Kee Woei Ng, Kee Woei Ng, Kee Woei Ng, Matan Gavish, Matan Gavish, Ittai Herrmann, Ittai Herrmann

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Explainable artificial intelligence to estimate the Sri Lankan (Ceylon) Tea crop yield by Lakindu Mampitiya, Harindu S. Sumanasekara, Namal Rathnayake, Yukinobu Hoshino, Upaka Rathnayake

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Dispersive surface-response formalism to address nonlocality in extreme plasmonic field confinement by Babaze Antton, Neuman Tomáš, Esteban Ruben, Aizpurua Javier, Borisov Andrei G.

“…An explicit comparison with time-dependent density functional theory (TDDFT) results shows that the dispersive SRF correctly describes the plasmonic response of planar and nonplanar systems featuring extreme field confinement. This work thus significantly extends the applicability range of the SRF, contributing to the development of computationally efficient semiclassical descriptions of light–matter interaction that capture quantum effects.…”
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Combining Generative Adversarial Networks (GANs) With Gaussian Noise for Anomaly Detection in Internet of Things (IoT) Traffic by Roya Morshedi, S. Mojtaba Matinkhah

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Lightweight deep learning method for end-to-end point cloud registration by Linjun Jiang, Yue Liu, Zhiyuan Dong, Yinghao Li, Yusong Lin

“…Point cloud registration, a fundamental task in computer science and artificial intelligence, involves rigidly transforming point clouds from different perspectives into a common coordinate system. …”
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Triple band lateral 4-port flexible MIMO antenna for millimeter wave applications at 24/28/38 GHz by Rakesh N. Tiwari, Deepti Sharma, Prabhakar Singh, Bandrevu Guru Kullayappa, Pradeep Kumar, Boya Ranga Swamy, Gulimi Pavan Kumar, S. Rajasekaran

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Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique by Karim Gasmi, Najib Ben Aoun, Najib Ben Aoun, Khalaf Alsalem, Ibtihel Ben Ltaifa, Ibrahim Alrashdi, Lassaad Ben Ammar, Manel Mrabet, Abdulaziz Shehab

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Mathematical modeling of donor liver cooling during hypothermic perfusion by A. V. Bukharov, A. F. Ginevsky, I. S. Seregin, B. I. Yaremin, E. Yu. Anosova, B. I. Kazymov, M. S. Novruzbekov

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An Image and State Information-Based PINN with Attention Mechanisms for the Rapid Prediction of Aircraft Aerodynamic Characteristics by Yiduo Kan, Xiangdong Liu, Haikuo Liu

“…Prediction of aircraft aerodynamic parameters is crucial for aircraft design, yet traditional computational fluid dynamics methods remain time-consuming and labor-intensive. …”
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A lightweight power quality disturbance recognition model based on CNN and Transformer by ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian

“…A lightweight power quality disturbances (PQDs) recognition model that integrates convolutional neural network (CNN) and Transformer (CaT) is proposed to address the high number of parameters and computational complexity in existing deep learning-based models. …”
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Development and Validation of a Prediction Model Using Sella Magnetic Resonance Imaging–Based Radiomics and Clinical Parameters for the Diagnosis of Growth Hormone Deficiency and I... by Kyungchul Song, Taehoon Ko, Hyun Wook Chae, Jun Suk Oh, Ho-Seong Kim, Hyun Joo Shin, Jeong-Ho Kim, Ji-Hoon Na, Chae Jung Park, Beomseok Sohn

“…The mean absolute Shapley values were computed to quantify the impact of each parameter. …”
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Polar protic and aprotic solvents induced nonlinear optical and optical limiting properties of Xanthene dye: A DFT Study by Natarajan Arumugam, Abdulrahman I. Almansour, Rohith Ramasamy, Rajadurai Vijay Solomon, A.G. Bharathi Dileepan, Madhappan Santhamoorthy, S. Jeyaram

“…The computational results highlight a clear solvent effect on the enhancement of NLO responses. …”
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Predicting age at first calving of dairy breed calves using whale optimization-based ensemble learning framework by Tewodros Shekure, Hussien Seid Worku, Sudhir Kumar Mohapatra, Tapan Kumar Das

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Basrah Score: a novel machine learning-based score for differentiating iron deficiency anemia and beta thalassemia trait using RBC indices by Salma A. Mahmood, Asaad A. Khalaf, Saad S. Hamadi

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Very high frequency radio receiver preselector design by E. V. Gurov, S. U. Uvaysov, V. V. Chernoverskaya, R. M. Uvaysov

“…This is true even if short lines with a length of about 5 mm are used at frequencies of about 100 MHz. These features must be taken into account for RF network design. …”
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DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling by Zongren Li, Shuping Luo, Hongwei Li, Yanbin Li

“…This study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computational complexity that stem from the utilization of large convolutional kernels. …”
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SAR Image Target Segmentation Guided by the Scattering Mechanism-Based Visual Foundation Model by Chaochen Zhang, Jie Chen, Zhongling Huang, Hongcheng Zeng, Zhixiang Huang, Yingsong Li, Hui Xu, Xiangkai Pu, Long Sun

“…When the ground-truth is used as a prompt, SARSAM improves <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>m</mi><mi>I</mi><mi>O</mi><mi>U</mi></mrow></semantics></math></inline-formula> by more than 10%, and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>A</mi><msubsup><mi>P</mi><mrow><mi>mask</mi><mspace width="4.pt"></mspace></mrow><mn>50</mn></msubsup></mrow></semantics></math></inline-formula> by more than 5% from the baseline. In addition, the computational cost is greatly reduced because the number of parameters and FLOPs of the structures that require fine-tuning are only 13.5% and 10.1% of the baseline, respectively.…”
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Buckling Analysis of Sandwich Timoshenko Nanobeams with AFG Core and Two Metal Face-Sheets by Masoumeh Soltani

“…Then, the numerical differential quadrature technique is used to estimate the endurable axial critical loads. The most beneficial feature of the proposed technique is to simplify and decrease the essential computational efforts to obtain the endurable axial buckling loads of sandwich shear-deformable nano-scale beams with AFG core. …”
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Goalie: Defending Against Correlated Value and Sign Encoding Attacks by Rongfei Zhuang, Ximing Fu, Chuanyi Liu, Peiyi Han, Shaoming Duan

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MHD analysis of couple stress nanofluid through a tapered non-uniform channel with porous media and slip-convective boundary effects by P. Deepalakshmi, G. Shankar, E.P. Siva, D. Tripathi, O. Anwar Bég

“…Increasing Brownian motion nanoscale parameter elevates nanoparticle concentrations. A strong modification is also computed with thermophoretic nanoscale parameter. …”
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