In terms of social, economic, sustainability, and environmental challenges, ride-sharing services play a significant role in reducing traffic congestion and the number of automobiles on the road. The objective of this...
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This study examines the utilization and comparison of four distinct techniques for multi-criteria decision-making (MCDM). The aim is to select the most favorable pareto-optimal solution derived from multi-objective op...
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This paper proposes the Modified Light GBM to classify the Malicious Users (MUs) and legitimate Secondary Users (SUs) in the cognitive-radio network. The proposed method is to avoid the consequences of malicious users...
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DNA sequencing is a critical tool in genetics, helping to identify disease-causing mutations, predict disease risks, screen for genetic diseases, and monitor disease progression. By determining the order of nucleotide...
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Dynamic crop morphology capture aids real-time precision in field spraying decisions. Ultrasonic radar and costly LiDAR can't maximize their high precision. They may slow down decision speed because the current sp...
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This paper investigates a cooperative motion planning problem for large-scale connected autonomous vehicles (CAVs) under limited communications, which addresses the challenges of high communication and computing resou...
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This paper investigates a cooperative motion planning problem for large-scale connected autonomous vehicles (CAVs) under limited communications, which addresses the challenges of high communication and computing resource requirements. Our proposed methodology incorporates a parallel optimization algorithm with improved consensus ADMM considering a more realistic locally connected topology network, and time complexity of $\mathcal {O}(N)$ is achieved by exploiting the sparsity in the dual update process. To further enhance the computational efficiency, we employ a lightweight evolution strategy for the dynamic connectivity graph of CAVs, and each sub-problem split from the consensus ADMM only requires managing a small group of CAVs. The proposed method implemented with the receding horizon scheme is validated thoroughly, and comparisons with existing numerical solvers and approaches demonstrate the efficiency of our proposed algorithm. Also, simulations on large-scale cooperative driving tasks involving up to 100 vehicles are performed in the high-fidelity CARLA simulator, which highlights the remarkable computational efficiency, scalability, and effectiveness of our proposed development. Demonstration videos are available at https://***/icadmm_cmp_carla. IEEE
Alzheimer's disease (AD) is a devastating neurological disorder that progressively worsens cognitive function and memory. Early detection is critical to avoiding worse symptoms. While computational approaches have...
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Neural Radiance Field (NeRF) has become an increasingly popular approach for modeling the geometry and appearance of scenes/objects. Various datasets for training and testing the rendered view quality have been introd...
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Post-harvest losses of onion incurred during storage pose a significant global concern. To reduce post-harvest losses, this study explores the applications of fuzzy logic to predict the storage lifespan of onions. Thi...
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Growing concerns about identity theft and privacy are brought on by the increased sharing of digital information, which leaves data open to quick changes while in transit. Digital data must be protected from hackers. ...
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