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). …”

The flow of the SP-DRL algorithm. by Jie Fang (306330)

“…Finally, instances are used to analyze the optimization effect of the algorithm. The experimental results show that the proposed algorithm can produce three better and five comparable results compared with some classical heuristic algorithms. …”

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). …”

The loss curve for model training. by Jie Fang (306330)

“…Finally, instances are used to analyze the optimization effect of the algorithm. The experimental results show that the proposed algorithm can produce three better and five comparable results compared with some classical heuristic algorithms. …”

Coordinate system on a rectangular plate. by Jie Fang (306330)

“…Finally, instances are used to analyze the optimization effect of the algorithm. The experimental results show that the proposed algorithm can produce three better and five comparable results compared with some classical heuristic algorithms. …”

Test instance and packing result information. by Jie Fang (306330)

“…Finally, instances are used to analyze the optimization effect of the algorithm. The experimental results show that the proposed algorithm can produce three better and five comparable results compared with some classical heuristic algorithms. …”

The neural network architecture. by Jie Fang (306330)

“…Finally, instances are used to analyze the optimization effect of the algorithm. The experimental results show that the proposed algorithm can produce three better and five comparable results compared with some classical heuristic algorithms. …”

Video_1_Simulating human walking: a model-based reinforcement learning approach with musculoskeletal modeling.MP4 by Binbin Su (640741)

Accelerated Design of Catalytic Water-Cleaning Nanomotors via Machine Learning by Minxiang Zeng (1734502)

“…However, the vast variety of nanoparticle designs prevents rapid identification of the optimal composition for a given application. In this study, we applied machine learning methods to predict the self-propulsion speed and water-cleaning efficiency of micro/nanomotors (MNMs), where the quality of machine learning predictions was evaluated based on the statistical values. …”

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. …”

DataSheet_1_Stronger wind, smaller tree: Testing tree growth plasticity through a modeling approach.docx by Haoyu Wang (429641)

“…To test this hypothesis in silico, a functional–structural plant model, which simulates both the primary and secondary growth of stems, is coupled with a biomechanical model which computes forces, moments of forces, and breakage location in stems caused by both wind and self-weight increment during plant growth. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is adopted to maximize the multi-objective function (stem biomass and tree height) by determining the key parameter value controlling the biomass allocation to the secondary growth. …”

Data_Sheet_1_The impact of speech type on listening effort and intelligibility for native and non-native listeners.PDF by Olympia Simantiraki (17057304)

“…The findings of the current study motivate the search for speech modification algorithms that are optimized for both intelligibility and listening effort.…”