Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
a decrease » _ decrease (Expand Search), _ decreased (Expand Search), _ decreases (Expand Search)
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1741
mAP0.5 Curves of various models.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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1742
Network loss function change diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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1743
Comparative diagrams of different indicators.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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1744
YOLOv8n structure diagram.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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1745
Geometric model of the binocular system.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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1746
Enhanced dataset sample images.
Published 2025“…Results on a specialized dataset reveal that YOLOv8n-BWG outperforms YOLOv8n by increasing the mean Average Precision (mAP) by 4.2%, boosting recognition speed by 21.3% per second, and decreasing both the number of floating-point operations (FLOPs) by 28.9% and model size by 26.3%. …”
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1747
General participant characteristics.
Published 2025“…The hepatic transcriptome changed significantly during a standardized meal and these changes were blunted in patients with NAFLD and cirrhosis. …”
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1748
Investigating the Influence of Transition Metal Substitution in Lithium Argyrodites on Structure, Transport, and Solid-State Battery Performance
Published 2024“…This leads to blocking of Li<sup>+</sup> transport pathways within the Li<sup>+</sup> cages causing a decrease of ionic conductivities along with increasing activation energies for Li<sup>+</sup> transport. …”
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1749
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1750
5.HT<sub>1A</sub> binding difference between known cause of death (KCOD) controls and SIDS.
Published 2025“…When SIDS is compared to all KCOD controls, the HG, NTS, and MAO show a significant mean difference in 5-HT<sub>1A</sub> receptor binding. …”
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1751
Heat map showing correlations between comet assay parameters, and warm and cold ischemia times.
Published 2025“…<p>Red values are significant at p < 0.05. Negative values mean that there is a “the more, the less” relationship between the quantities, i.e., as one quantity increases, the other quantity decreases. …”
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1752
Original data.
Published 2024“…Additionally, a statistically significant improvement was observed in the Japanese Zarit Caregiver Burden Interview score at 6 months from baseline (p < 0.001).…”
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1753
Home-based rehabilitation program.
Published 2024“…Additionally, a statistically significant improvement was observed in the Japanese Zarit Caregiver Burden Interview score at 6 months from baseline (p < 0.001).…”
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1754
Baseline characteristics of study participants.
Published 2024“…Additionally, a statistically significant improvement was observed in the Japanese Zarit Caregiver Burden Interview score at 6 months from baseline (p < 0.001).…”
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1755
Value ranges of three representative points.
Published 2025“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”
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1756
Signalized intersection in Kunshan.
Published 2025“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”
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1757
Dynamic system state in demand scenarios 2.
Published 2025“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”
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1758
Survey data of the intersection.
Published 2025“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”
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1759
The main notations used in this paper.
Published 2025“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”
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1760
Feedback elimination for feedback queue.
Published 2025“…Numerical experiments using actual survey data from Kunshan City yield several noteworthy findings: (1) An optimal moderate-sized time step exists for rolling optimization to minimize either the average delay time or total costs; specifically, an excessively small time step may increase vehicle average delay time or total costs; (2) The percentage of delay reduction achieved by our method, compared to Synchro software, reaches a maximum of approximately 70% when traffic demand is moderate and the initial state is low; and (3) The percentage reduction in average delay or total costs compared to Synchro initially increases and then decreases with rising traffic intensity.…”