Incidental Findings of Asymptomatic Fungal Infection by Nisha Manila, Madhu Nair, Hui Liang

“…Computed tomography (CT) scan of the maxillofacial region, specifically paranasal sinuses, plays a considerable role in diagnosing fungal sinusitis. …”
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Model Updating Method Based on Kriging Model for Structural Dynamics by Hong Yin, Jingjing Ma, Kangli Dong, Zhenrui Peng, Pan Cui, Chenghao Yang

“…Model updating in structural dynamics has attracted much attention in recent decades. And high computational cost is frequently encountered during model updating. …”
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Finite element analysis and artificial neural network for stress distribution of an aircraft model in a wind tunnel by Ahmed Al-Mulla Khalaf, Sinan Al-Haddad, Bilal Al-Oubaidi, Naseem Ibrahim, Fawaz Abdulwahed, Athraa Hilal

“…In addition, the methodology is significant in computations since the ANN works quicker than conventional FEA. …”
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Machine Learning Model for Gas–Liquid Interface Reconstruction in CFD Numerical Simulations by Tamon Nakano, Michele Alessandro Bucci, Jean-Marc Gratien, Thibault Faney

“…., normal, location, and curvature). Accurate computation of the local interface curvature is essential for evaluation of the surface tension force at the interface. …”
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Limits and Risks of Digital Transformation by T. S. Akhromeeva, G. G. Malinetskiy, S. A. Posashkov

“…In a number of problems associated with a computational experiment this can be quite significant.Great risks arise when passing to the "fast world", approaching the "Lem's barrier". …”
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A chaotic digital signature algorithm based on a dynamic substitution box by Rolando Flores-Carapia, Víctor Manuel Silva-García, Manuel Alejandro Cardona-López, Miguel Gabriel Villarreal-Cervantes

“…A key challenge is minimizing computationally intensive operations, such as modular inverses, without compromising security. …”
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Deep Learning in Music Generation: A Comprehensive Investigation of Models, Challenges and Future Directions by Kong Xiangchen

“…However, each model faces its own set of limitations, such as computational inefficiency, data dependency, and challenges in capturing complex emotional nuances. …”
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Scalable circuit depth reduction in feedback-based quantum optimization with a quadratic approximation by Don Arai, Ken N. Okada, Yuichiro Nakano, Kosuke Mitarai, Keisuke Fujii

“…Combinatorial optimization problems are one of the areas where near-term noisy quantum computers may have practical advantage against classical computers. …”
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Emergency Trajectory Structure for UAVs by Maëva Ongale-Obeyi, Damien Goubinat, Daniel Delahaye, Pierre-Loïc Garoche

“…The primary aim of these tests is to benchmark the computational time of the overall architecture, ensuring that this adaptable framework is fully capable of handling the problem’s complexity. …”
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SSCANL decoder based joint iterative detection and decoding algorithm by Chongyang LIU, Rui GUO

“…In order to improve the receiver performance of the sparse code multiple access (SCMA) system based on polar codes, the cyclic redundancy check (CRC) aided joint iterative detection and decoding receiver scheme based on simplify soft cancellation list (SSCANL) decoder (C-JIDD-SSCANL) was proposed.A polar code decoder in the C-JIDD-SSCANL receiver used the SSCANL algorithm.In this algorithm, decoding node deletion technology was used to simplify L times of soft cancellation (SCAN) decoding required by soft cancellation list (SCANL) algorithm by deleting frozen bit nodes, then the computational process of soft information update between nodes was simplified, and the computational complexity of decoding algorithm was reduced.The simulation results show that the SSCANL algorithm can obtain the same performance as the SCANL algorithm, and its computational complexity is reduced compared with the SCANL algorithm.Compared with the joint iterative detection and decoding scheme based on SCAN decoder (JIDD-SCAN) and the CRC aided joint iterative detection and decoding scheme based on SCAN decoder (C-JIDD-SCAN), the performance of C-JIDD-SSCANL receiver scheme based on SSCANL decoder is improved by about 0.65 dB and 0.59 dB respectively when the bit error rate is 10^-4.…”
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Theoretical Study of the Structural and Electronic Properties of NIPAM Polymer Dosimetry Gel by Swait S. Mohammed, Israa F. Al-sharuee, Akram Mohammed Ali, Adil Elrayah

“…The computations of the structure, as well as the vibrational frequencies and chemical shift, demonstrated a satisfactory theoretical approximation. …”
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Ways to improve the accuracy of the harmonic method for simulating two-dimensional signals by V.V. Syuzev, A.V. Proletarsky, D.A. Mikov, I.I. Deykin

“…The effect of the discovered properties on the computational complexity of the method is described. …”
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High Performance GPU-Based Fourier Volume Rendering by Marwan Abdellah, Ayman Eldeib, Amr Sharawi

“…The introduction of the compute unified device architecture (CUDA) technology enables embarrassingly-parallel algorithms to run efficiently on CUDA-capable GPU architectures. …”
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RELAP5 Calculations of Bethsy 9.1b Test by Andrej Prošek

“…Recently, several advanced computational tools for simulating reactor system behavior during real and hypothetical transient scenarios were developed. …”
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XTNSR: Xception-based transformer network for single image super resolution by Jagrati Talreja, Supavadee Aramvith, Takao Onoye

“…However, challenges still need to be addressed in handling grid-like image patches with higher computational demands and addressing issues like over-smoothing in visual patches. …”
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An Investigation Into a Lightweight Safety Helmet Detection Approach Utilizing the MSS-YOLO Framework by Bing Zeng, Zhanpeng Liao, Yu Zhou, Dilin He, Zhihao Zhou, Kexin Yi, Yuwen Li, Xiaopin Yang, Yunmin Xie

“…Motivated by the challenges of low detection accuracy, false positives, false negatives, and the excessive computational demand in safety helmet detection within complex power scenarios, this paper introduces a lightweight safety helmet object detection algorithm based on MSS-YOLO. …”
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Machine learning and Fuzzy logic fusion approach for osteoporosis risk prediction by Rabia Khushal, Dr. Ubaida Fatima

“…Machine learning implementation on these factors took a large computation time and has shown poor accuracy. Thus fuzzy concept has been introduced leading to the development of a fusion of machine learning and fuzzy logic approach. …”
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Method on Efficient Operation of Multiple Models for Vision-Based In-Flight Risky Behavior Recognition in UAM Safety and Security by Byeonghun Kim, Byeongjoon Noh, Kyowon Song

“…Recently, with the significant spread of technology in the field of computer vision, research has been conducted to manage passenger safety and security with vision-based approaches. …”
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Survey of optical-based physical domain adversarial attacks and defense by CHEN Jinyin, ZHAO Xiaoming, ZHENG Haibin, GUO Haifeng

“…This poses a huge security threat to computer vision systems that are based on deep learning. …”
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Calculating torque, back-EMF, inductance, and unbalanced magnetic force for a hybrid electrical vehicle by in-wheel drive application by Alireza Hosseinpour, Akbar Rahideh, Ahmed Abbas, Atif Iqbal, Claude Ziad El-Bayeh, Aymen Flah, Enas Ali, Ramy N. R. Ghaly

“…Then, the self-inductance of the stator and rotor windings, the mutual inductance between the stator and rotor windings, and the mutual inductance between the stator phases are computed. Next, the components of the unbalanced magnetic force (UMF) in the direction of the x and y axes and its amplitude are computed. …”
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