Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

“…MobileNetV2, ResNet50, and EfficientNet-B0 hyperparameters have been optimized using a modified grey wolf optimization (GWO) approach for better performance. …”
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Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine by Toru Aonishi, Tatsuya Nagasawa, Toshiyuki Koizumi, Mastiyage Don Sudeera Hasaranga Gunathilaka, Kazushi Mimura, Masato Okada, Satoshi Kako, Yoshihisa Yamamoto

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Robust and Unified Semi-Supervised Unmixing of Hyperspectral Imaging for Linear and Multilinear Models by Daniel Ulises Campos-Delgado, Juan Nicolas Mendoza-Chavarria, Omar Gutierrez-Navarro, Laura Quintana-Quintana, Raquel Leon, Samuel Ortega, Himar Fabelo, Carlos Lopez, Marylene Lejeune, Gustavo M. Callico

“…All scripts for the proposed algorithms are freely available in <uri>https://github.com/Nicothe4th/ESSEAE-NESSEAE</uri>.…”
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Response mitigations of adjacent structure with MPTMD under real and stochastic excitations by Mohammad Alibabaei Shahraki

“…The performance of the MPTMD system is optimized using the Particle Swarm Optimization (PSO) algorithm. …”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…This model utilizes the RSA to optimize the parameters K and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula> of the VMD algorithm. …”
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Construction cost prediction model for agricultural water conservancy engineering based on BIM and neural network by Kun Han, Tieliang Wang, Wenhe Liu, Chunsheng Li, Xiaochen Xian, Yingying Yang

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User scheduling and power allocation strategy for cell-free networks based on federated learning by WANG Huahua, HUANG Yexia, LI Ling

“…Simulation results demonstrate that compared to other comparison algorithms, the proposed algorithm achieves a 47.19% increase in downlink throughput, a 22.60% increase in uplink throughput, and a 57.33% reduction in FL task time consumption, while minimizing time overhead for achieving the same model accuracy…”
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Neural Architecture Search for Generative Adversarial Networks: A Comprehensive Review and Critical Analysis by Abrar Alotaibi, Moataz Ahmed

“…Neural Architecture Search (NAS) has emerged as a pivotal technique in optimizing the design of Generative Adversarial Networks (GANs), automating the search for effective architectures while addressing the challenges inherent in manual design. …”
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Improving quantum metrology protocols with programmable photonic circuits by de las Heras Alberto Muñoz, Porras Diego, González-Tudela Alejandro

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Simulation of Patch Field Effect in Space-Borne Gravitational Wave Detection Missions by Mingchao She, Xiaodong Peng, Li-E Qiang

“…These results establish a foundation for optimizing mitigation strategies against patch-induced noise in future space missions.…”
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Coordinated Truck Loading and Routing Problem: A Forestry Logistics Case Study by Cristian Oliva, Manuel Cepeda, Sebastián Muñoz-Herrera

“…The results show that an Ant Colony System (ACS–CTLRP) algorithm reduces total distance traveled by 23%, travel time by 22%, and the number of trucks used by 13 units, while increasing fleet utilization from 54% to 83%. …”
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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

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Information Bottleneck-Based Domain Adaptation for Hybrid Deep Learning in Scalable Network Slicing by Tianlun Hu, Qi Liao, Qiang Liu, Georg Carle

“…Each target domain slice can deploy this estimator to predict its QoS and optimize slice resource allocation using the IDLA algorithm. …”
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Intelligent approach to detecting online fraudulent trading with solution for imbalanced data in fintech forensics by Saad M. Darwish, Amr Ibrahim Salama, Adel A. Elzoghabi

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Data stream mining techniques for real-time monitoring and control of smart power grids in Kenya: challenges and opportunities by Cornelius Mutuku Mulevu, George Onyango Okeyo, Joseph Muliaro Wafula

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A Novel Deep Learner for Human Behavior Prediction Over Public Video Surveillance by Bayan Alabdullah, Bisma Batool Fatima, Haifa F. Alhasson, Mohammed Alshehri, Yahya AlQahtani, Nouf Albhassabi, Hui Liu

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Battery Charging Simulation of a Passenger Electric Vehicle from a Traction Voltage Inverter with an Integrated Charger by Evgeniy V. Khekert, Boris V. Malozyomov, Roman V. Klyuev, Nikita V. Martyushev, Vladimir Yu. Konyukhov, Vladislav V. Kukartsev, Oleslav A. Antamoshkin, Ilya S. Remezov

“…The experiments show the achievement of a realized capacity of 8.9 Ah and an integral efficiency of 85.5%, while the temperature regime remains within safe limits. …”
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A dual layer secure and energy-efficient model for border surveillance using sea lion inspired strategy in wireless sensor networks by Jayachandran J, Vimaladevi K

“…This paper presents a Dual Layer Sea Lion Optimization algorithm (DL-SLnOA) model, a bio-inspired, clustering and routing that focuses on energy efficiency and security to enhance performance under challenging conditions. …”
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DCOOL: Dynamic computation offloading and resource allocation for LEO satellite-assisted edge computing in a ground-space integrated framework by Jeonghwan Kim, Jeongho Kwak

“…To this end, this paper introduces a dynamic computation offloading and resource allocation framework in the LEO satellite MEC architecture. Using Lyapunov optimization, we propose an efficient DCOOL algorithm to minimize average power consumption and propagation delay constrained by queue stability. …”
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Construction of a risk prediction model for pulmonary infection in patients with spontaneous intracerebral hemorrhage during the recovery phase based on machine learning by Jixiang Xu, Yuan Li, Fumin Zhu, Fumin Zhu, Xiaoxiao Han, Liang Chen, Yinliang Qi, Yinliang Qi, Xiaomei Zhou, Xiaomei Zhou

“…Seven ML algorithms were employed to build predictive models, with performance evaluated based on the area under the receiver operating characteristic (AUC) curve, sensitivity, specificity, and accuracy. …”
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