General procedural flow of clustering algorithm. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Optimal cluster head approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Optimal cluster formation approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Technical route. by Ke Peng (2220973)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

CH leaving at SCH approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

AVOCA approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Cluster merging approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Cluster joining approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Cluster leaving approach. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

To mitigate hidden node challenges. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

General procedural flow chart for AVOCA. by Sandeep Yerrathi (17775761)

“…The results show that AVOCA generates 40% less clusters when compared to the Clustering Algorithm Based on Moth-Flame Optimization for VANETs (CAMONET). …”

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png by Minjin Guo (22751300)

Data Sheet 1_A multimodal travel route recommendation system leveraging visual Transformers and self-attention mechanisms.pdf by Zhang Juan (11780753)

“…However, traditional methods often fail to effectively integrate visual and sequential information, leading to recommendations that are both less accurate and less personalized.</p>Methods<p>This paper introduces SelfAM-Vtrans, a novel algorithm that leverages multimodal data—combining visual Transformers, LSTMs, and self-attention mechanisms—to enhance the accuracy and personalization of travel route recommendations. …”

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”