Multi-Channel Sparse-Frequency-Scanning White-Light Interferometry with Adaptive Mode Locking for Pulse Wave Velocity Measurement by Yifei Xu, Laiben Gao, Cheng Qian, Yiping Wang, Wenyan Liu, Xiaoyan Cai, Qiang Liu

“…Compared to normal MLCC algorithm, the Fibonacci-optimized algorithm reduces the number of computational iterations by 57 times while maintaining sub-nanometer resolution under dynamic perturbations. …”
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Zero-shot performance analysis of large language models in sumrate maximization. by Ali Abir Shuvro, Md Shahriar Islam Bhuiyan, Faisal Hussain, Md Sakhawat Hossen

“…In the field of Networking, LLMs can also play a major role when it comes to resource optimization and sharing. While Sumrate maximization has been a crucial factor for resource optimization in the networking domain, the optimal or sub-optimal algorithms it requires can be cumbersome to comprehend and implement. …”
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Research on Network Handover Based on User Movement Prediction in Visible Light Communication and Wi-Fi Heterogeneous Networks by Chenghu Ke, Mengfan Wang, Huanhuan Qin, Xizheng Ke

“…Extracting meaningful and important location points from massive trajectory data for clustering, an improved hidden Markov model is used to predict the user’s next location by analyzing the patterns of the user’s historical mobile trajectory data. The Q-learning algorithm is then used to determine the optimal network handover based on the current network state, while a seamless handover protocol is introduced to ensure successful network transition and uninterrupted data transmission. …”
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Gaussian Process Regression with Soft Equality Constraints by Didem Kochan, Xiu Yang

“…Additionally, we introduce an adaptive learning algorithm to optimize the selection of constraint locations to further enhance the flexibility of the method. …”
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Multi task detection method for operating status of belt conveyor based on DR-YOLOM by Yongan LI, Tengjie CHEN, Hongwei WANG, Zhihao ZHANG

“…Secondly, as the model requires target recognition and segmentation of different types of tasks, an efficient layer aggregation network (RepGFPN) with skip layer connection structure is adopted to optimize the feature fusion part, greatly improving the detection accuracy of the model for different detection tasks while controlling the number of model parameters and inference speed; Finally, to address the detection tasks of three different label shapes, the Inner CIOU loss function is introduced to compensate for the weak generalization ability of the CIoU loss function in different detection tasks. …”
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A location semantic privacy protection model based on spatial influence by Linghong Kuang, Wenlong Shi, Xueqi Chen, Jing Zhang, Huaxiong Liao

“…Finally, the problem of synthesizing dummy trajectories is transformed into a matching problem for directed bipartite graphs and the optimal k-anonymity set is obtained using the Kuhn Munkres algorithm. …”
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Smart IoT-driven precision agriculture: Land mapping, crop prediction, and irrigation system. by Gourab Saha, Fariha Shahrin, Farhan Hasin Khan, Mashook Mohammad Meshkat, Akm Abdul Malek Azad

“…The experimental results demonstrated that fuzzy logic has faster calibration rate of 66.23% and helps to save around 61% water in comparison to average logic algorithm. The implementation of a fuzzy logic algorithm significantly optimized water usage compared to traditional manual irrigation methods. …”
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A method of identification and localization of tea buds based on lightweight improved YOLOV5 by Yuanhong Wang, Yuanhong Wang, Jinzhu Lu, Jinzhu Lu, Qi Wang, Qi Wang, Zongmei Gao

“…The Fuding white tea bud image dataset was established by collecting Fuding white tea images; then the lightweight network ShuffleNetV2 was used to replace the YOLOV5 backbone network; the up-sampling algorithm of YOLOV5 was optimized by using CARAFE modular structure, which increases the sensory field of the network while maintaining the lightweight; then BiFPN was used to achieve more efficient multi-scale feature fusion; and the introduction of the parameter-free attention SimAm to enhance the feature extraction ability of the model while not adding extra computation. …”
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Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications, sensing and computing by Ruijin Sun, Yao Wen, Nan Cheng, Wei Wang, Rong Chai, Yilong Hui

“…Although this non-convex problem can be handled by the alternating minimization (AM) algorithm that alternatively minimizes the divided four sub-problems, it leads to high computational complexity and local optimal solution. …”
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Auxiliary Stopping Area Layout Method for High-Speed Maglev considering Multiple Speed Profiles and Bidirectional Operation by Danyang Dong, Yi Yu, Huahua Zhao, Pengzi Chu, Hui Lin

“…Aiming at the layout of the ASA along the track, this article constructs an optimized model of ASA layout and proposes a solving algorithm based on the single target genetic algorithm by analyzing the influence factors of ASA layout. …”
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RWP-NSGA II: Reinforcement Weighted Probabilistic NSGA II for Workload Allocation in Fog and Internet of Things Environment by Hafsa Raissouli, Samir Brahim Belhaouari, Ahmad Alauddin Bin Ariffin

“…This method uses domain-specific knowledge to improve convergence and solution quality, resulting in reduced delay and better energy efficiency compared to traditional NSGA II and other evolutionary algorithms. The results demonstrate that the proposed algorithm reduces delay by nearly 2 s while also achieving an improvement in energy efficiency, surpassing the state of the art by nearly 3 units.…”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…Additionally, a lightweight cross-attention fusion module is introduced, optimizing the use of differential and shared features while minimizing computational complexity. …”
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Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

“…Traditional detection methods are time-consuming and subjective, and they can lead to economic waste, while deep learning image recognition techniques offer a new approach. …”
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Thermal-aware resource allocation in earliest deadline first using fluid scheduling by Muhammad Naeem Shehzad, Qaisar Bashir, Ghufran Ahmad, Adeel Anjum, Muhammad Naeem Awais, Umar Manzoor, Zeeshan Azmat Shaikh, Muhammad A Balubaid, Tanzila Saba

“…This article proposes an improvement in earliest deadline first, a uni-processor scheduling algorithm, without compromising its optimality in order to reduce the thermal peaks and variations. …”
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Research on Lightweighting Methods for 3D Building Models Based on Semantic Constraints by J. Wu, T. Shen, L. Huo

“…In the transition from LOD2 to LOD1, a concave-convex face movement and merging algorithm is utilized to reduce redundant data while maintaining geometric similarity and optimizing the model's topological structure, ultimately producing a lightweight LOD1 model. …”
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Time series segmentation for recognition of epileptiform patterns recorded via microelectrode arrays in vitro. by Gabriel Galeote-Checa, Gabriella Panuccio, Angel Canal-Alonso, Bernabe Linares-Barranco, Teresa Serrano-Gotarredona

“…While initially trained specifically for detecting ictal activity, these algorithms can be fine-tuned for improved interictal detection, aiming at seizure prediction. …”
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Hybrid multi-objective node deployment for energy-coverage problem in mobile underwater wireless sensor networks by Salmah Fattah, Ismail Ahmedy, Mohd Yamani Idna Idris, Abdullah Gani

“…This study evaluated the solution to substantiate its efficacy, particularly regarding the nodes’ coverage rate, energy consumption and the system’s Pareto optimal metrics and execution time. The results and comparative analysis indicate that the Multi-Objective Optimisation Genetic Algorithm based on Adaptive Multi-Parent Crossover and Fuzzy Dominance (MOGA-AMPazy) is a better solution to the multi-objective sensor node deployment problem, outperforming the non-dominated sorting genetic algorithm II, SPEA2 and MOEA/D algorithms. …”
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Water-Based Metaheuristics: How Water Dynamics Can Help Us to Solve NP-Hard Problems by Fernando Rubio, Ismael Rodríguez

“…Many water-based optimization metaheuristics have been introduced during the last decade, both for combinatorial and for continuous optimization. …”
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Quantum-Inspired Control Strategies for Reducing DC-Link Voltage Fluctuations in DFIG Wind Energy Converters by Sarika Shrivastava, Saifullah Khalid, Dinesh Kumar Nishad

“…The approach integrates quantum computing principles into classical control frameworks, creating a hybrid methodology that leverages quantum-inspired optimization while maintaining implementation feasibility on conventional hardware. …”
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GNSS Precipitable Water Vapor Prediction for Hong Kong Based on ICEEMDAN-SE-LSTM-ARIMA Hybrid Model by Jie Zhao, Xu Lin, Zhengdao Yuan, Nage Du, Xiaolong Cai, Cong Yang, Jun Zhao, Yashi Xu, Lunwei Zhao

“…Enhanced by local mean optimization and adaptive noise regulation, the ICEEMDAN algorithm effectively suppresses pseudo-modes and minimizes residual noise, enabling its decomposed intrinsic mode functions (IMFs) to more accurately capture the multi-scale features of GNSS-PWV. …”
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