Paint shop vehicle sequencing based on quantum computing considering color changeover and painting quality by Jing Huang, Qing Chang, Hua-Tzu Fan

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Computationally Efficient Design of an LNA Input Matching Network Using Automatic Differentiation by Kiran A. Shila

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Evaluating the Efficiency of Work of the Department of Computed Tomography and Magnetic Resonance Imaging by K. K. Osadchiy, E. A. Mershina, A. E. Bragina, V. E. Sinitsyn

“…Objectives. (1) To evaluate the efficiency of work of the Department of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI); (2) to study of its work processes; and (3) to elaborate recommendations for their optimization.Material and methods. …”
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Mitigating malicious denial of wallet attack using attribute reduction with deep learning approach for serverless computing on next generation applications by Amal K. Alkhalifa, Mohammed Aljebreen, Rakan Alanazi, Nazir Ahmad, Sultan Alahmari, Othman Alrusaini, Ali Alqazzaz, Hassan Alkhiri

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Optimization of Hydrogen Supercritical Oxy-Combustion in Gas Turbines by Sylwia Oleś, Jakub Mularski, Dariusz Pyka, Halina Pawlak-Kruczek, Artur Pozarlik

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Computed tomography-based radiomics model for predicting station 4 lymph node metastasis in non-small cell lung cancer by Yanru Kang, Mei Li, Xizi Xing, Kaixuan Qian, Hongxia Liu, Yafei Qi, Yanguo Liu, Yi Cui, Hua Zhang

“…Methods We included a total of 356 NSCLC patients at pN0-pN2 stage, divided into training (n = 207), internal test (n = 90), and independent test (n = 59) sets. Station 4 mediastinal lymph nodes (LNs) regions of interest (ROIs) were semi-automatically segmented on venous-phase computed tomography (CT) images for radiomics feature extraction. …”
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Developing and Analyzing the Defect-Based Surface Codes Using Optimization Algorithms by Samira Sayedsalehi, Nader Bagherzadeh, Alberto A. Del Barrio, Guillermo Botella, Ratko Pilipović

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Computational models based on machine learning and validation for predicting ionic liquids viscosity in mixtures by Bader Huwaimel, Jowaher Alanazi, Muteb Alanazi, Tareq Nafea Alharby, Farhan Alshammari

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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

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AI and IoT-powered edge device optimized for crop pest and disease detection by Jean Pierre Nyakuri, Celestin Nkundineza, Omar Gatera, Kizito Nkurikiyeyezu, Gervais Mwitende

“…The experimental results demonstrated that Tiny-LiteNet achieved up to 98.6% accuracy, 98.4% F1-score, 98.2% Recall, 80 ms inference time, while maintaining a compact model size of 1.2 MB with 1.48 million parameters, outperforming traditional CNN architectures such as VGGNet-16, Inception, ResNet50, DenseNet121, MobileNetv2, and EfficientNetB0 in terms of efficiency and suitability for edge computing. …”
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Computational design of mechanical metamaterials through misaligned periodic microstructure by Jiaxin Zhou, Ikumu Watanabe, Keita Kambayashi

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SecuNet 4D a comprehensive framework for distributed SDN security and resilience by Sumit Badotra, Mohan Gurusamy

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A Computational Framework for Automated Puncture Trajectory Planning in Hemorrhagic Stroke Surgery by Ziyue Ma, Feng Yan, Yongzhi Shan, Yaming Wang, Hong Wang

“…Results The framework demonstrated high accuracy in puncture trajectory planning, with the optimized L2 path achieving a mean surgeon satisfaction score of 4.4/5 (Likert scale) compared to manual methods. …”
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Optimization of the Predicting of the Influenza Vaccine Strains by E. P. Kharchenko

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HIGH-THROUGHPUT SIMULATIONS OF PROKARYOTIC COMMUNITY EVOLUTION WITH HAPLOID EVOLUTIONARY CONSTRUCTOR by Z. S. Mustafin, Yu. G. Matushkin, S. A. Lashin

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Adaptive AI-enhanced computation offloading with machine learning for QoE optimization and energy-efficient mobile edge systems by Dinesh Kumar Nishad, Vandna Rani Verma, Pushkar Rajput, Sandeep Gupta, Anurag Dwivedi, Dharti Raj Shah

“…Abstract Mobile Edge Computing (MEC) systems face critical challenges in optimizing computation offloading decisions while maintaining quality of experience (QoE) and energy efficiency, particularly in dynamic multi-user environments. …”
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Optimization of Retrospective Gated-ECG Coronary Computed Tomography Angiography by Dose Reduction in Patients with Different Body Mass Indexes by Behzad Fazlkhah, Mona Fazel Ghaziyanii, Leyla Dinparast, Vahid Alinejad, Yunus Soleymani, Davood Khezerloo

“…Background: The reduction of patient radiation dose in coronary Computed Tomography Angiography (CCTA) with acceptable image quality is considered an important factor in the research.Objective: This study aims to optimize the CCTA protocol using a retrospective Electrocardiogram (ECG)-gated axial scan protocol in patients with different Body Mass Indexes (BMIs).Material and Methods: In this cross-sectional study, 66 patients into three main groups: 80 kVp (Group A), 100 kVp (Group B), and 120 kVp (Group C), underwent CCTA. …”
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Radiologic assessment of the optimal point for tube thoracostomy using the sternum as a landmark: a computed tomography‐based analysis by Jaeik Jang, Jae-Hyug Woo, Mina Lee, Woo Sung Choi, Yong Su Lim, Jin Seong Cho, Jae Ho Jang, Jea Yeon Choi, Sung Youl Hyun

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A novel optimized computational approach to investigate the motion of a single-walled carbon nanotube conveying fluid flow by J. Vahidi, S.M. Golmaei, Morteza Jamshidi

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From immune evasion to broad in silico binding: computational optimization of SARS-CoV-2 RBD-targeting nanobody by Shuyuan Cao, Bo Sun, Feng Gao, Feng Gao, Feng Gao

“…This study uses molecular dynamics (MD) simulations to analyze the immune evasion mechanisms of class 1 nanobodies against emerging SARS-CoV-2 variants, and to develop an efficient in silico pipeline for rapid affinity optimization.MethodsWe employed MD simulations and binding free energy calculations to investigate the immune evasion mechanisms of four class 1 nanobodies (R14, DL4, VH ab6, and Nanosota9) against wild-type (WT) and Omicron variants, including BA.2, JN.1, and KP.3/XEC. …”
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