Displacement cloud maps. by Maogang Tian (21485116)

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Displacement cloud map (geology). by Hui Cheng (195456)

“…The primary trend indicates an increase in clay content of loess, a decrease in grit content, a relative increase in cohesion, and a relative decrease in the internal friction angle. …”

CNN Model Architecture. by Mudhafar Jalil Jassim Ghrabat (22177655)

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Flowchart of Proposed SMO_CNN. by Mudhafar Jalil Jassim Ghrabat (22177655)

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CNN Model Layers Summary. by Mudhafar Jalil Jassim Ghrabat (22177655)

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GPT-4 results in decreased error rate for all tasks with increasing complexity when compared to GPT-3.5-turbo. by Jacqueline A. Jansen (14894276)

Point cloud fusion instance effect. by Hongliang Zou (20707270)

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Positioning trajectories and pose truths of different simultaneous localization and mapping algorithms under Sequence 1. by Hongliang Zou (20707270)

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Positioning trajectories and pose truths of different simultaneous localization and mapping algorithms under Sequence 6. by Hongliang Zou (20707270)

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Positioning trajectories and pose truths of different simultaneous localization and mapping algorithms under Sequence 5. by Hongliang Zou (20707270)

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Performance Results of Proposed SMO_CNN Model. by Mudhafar Jalil Jassim Ghrabat (22177655)

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Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

“…After ChatGPT-4.5 was publicly released, reliability decreased notably (e.g. ICC = −0.046 for BVMT-R Trial 3), and average scoring discrepancies per test increased (e.g. …”

CNN framework. by Sajid Mehmood (6689843)

“…These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”

CNN frameworks. by Sajid Mehmood (6689843)

“…These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”

CNN model. by Longfei Gao (698900)

“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”

Differential miRNA target gene pathway enrichment bubble map. by Zhaowen Tan (12283502)

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Interaction plot with 95% confidence intervals generated from the GAM regression model 1 in Table 2 examining initial ED SBP and management group interactions. by Randeep S. Jawa (20489181)

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Architecture of the proposed shallow CNN. by Shruti Atul Mali (21300851)

“…Classification analysis revealed that ComBat increased average AUC by 15.19%, whereas GAN decreased AUC by 2.56%.</p><p>Conclusion</p><p>While GAN qualitatively enhances image harmonization, ComBat provides superior statistical improvements in feature stability and classification performance, highlighting the importance of robust feature-level harmonization in radiomics.…”

Mitigation (decreasing) scenario. by Fabio Correddu (12501799)