Landscape17 by Vlad Carare (22092515)

“…The two-phase procedure is applied until a complete discrete path is obtained, using the missing connection algorithm to propose new pairs of minima for additional searches.…”

Table1_GTasm: a genome assembly method using graph transformers and HiFi reads.DOCX by Junwei Luo (7593224)

“…Then, GTasm scores the edges by graph transformer model, and adopt a heuristic algorithm to find optimal paths in the assembly graph, each path corresponding to a contig. …”

Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 by Andrew Rogers (17623239)

“…</p><h2>3. VRE Siting Algorithm and Optimization</h2><p><br></p><p dir="ltr">The VRE siting model uses a cost-minimization optimization approach to select the most cost-efficient project sites to meet a projected energy mix target.…”

Data Sheet 1_Paediatric anaemia in rural Kenya and the role of travel time to emergency care services.pdf by Moses M. Musau (15324683)

“…Travel time from a patient's village to the hospital was calculated using a least cost path algorithm. Anaemia severity was categorised as mild (Hb ≥ 7–<10 g dl⁻¹), moderate (Hb ≥ 5–<7 g dl⁻¹) and severe (Hb < 5 g dl⁻¹). …”

Data Sheet 1_Evaluating the effectiveness of AI-enhanced “One Body, Two Wings” pharmacovigilance models in China: a nationwide survey on medication safety and risk management.pdf... by Jian Yang (12136)

“…</p>Results<p>The survey revealed that 43% of participants were hospital staff and 46% had more than 10 years of experience, with these expert groups expressing strong support for AI's role. Path analysis indicated that AI's effectiveness in processing ADR reports was strongly related to enhanced monitoring capabilities (standardized path coefficient: 0.85). …”

Model-Free UAV Navigation in Unknown Complex Environments Using Vision-Based Reinforcement Learning by Satoshi Suzuki (20437556)

“…To overcome these limitations and enable obstacle-avoidance navigation for UAVs, this paper proposes an end-to-end autonomous navigation algorithm that integrates visual perception with reinforcement learning, capable of planning optimal navigation paths without requiring high-precision models. …”

Scalable software infrastructures for knowledge graphs by Ariful Azad (21773021)

“…The second layer implements highly optimized parallel algorithms for these operations. …”

Optical Neuromorphic Eikonal Solver - Benchmark Datasets by Francisco Angulo de Lafuente (22601234)

“…# Optical Neuromorphic Eikonal Solver - Benchmark Datasets Benchmark datasets for evaluating GPU-accelerated pathfinding algorithms. ## Content 5 synthetic pathfinding test cases: - sparse_128.npz (128×128, 10% obstacles) - medium_256.npz (256×256, 20% obstacles) - gradient_256.npz (256×256, gradient speeds) - maze_511.npz (511×511, perfect maze) - complex_512.npz (512×512, 30% obstacles) Plus benchmark results showing GPU solver performance. ## Performance - 134.9× average speedup vs CPU Dijkstra - 0.64% mean absolute error - 1.025× optimal path length - 2-4ms per query on 512×512 grids ## Format NumPy .npz archives containing: - obstacles: (H,W) float32 array - speeds: (H,W) float32 array - source: (2,) int32 array - target: (2,) int32 array - metadata: JSON string See DATASETS.md for complete specification. ## Links - Code: https://github.com/Agnuxo1/Optical-Neuromorphic-Computing-for-Real-Time-Pathfinding-A-GPU-Accelerated-Eikonal-Solver - Paper: https://github.com/Agnuxo1/Optical-Neuromorphic-Computing-for-Real-Time-Pathfinding-A-GPU-Accelerated-Eikonal-Solver/blob/main/optical_neuromorphic_paper.html - Datasets: https://huggingface.co/datasets/Agnuxo/optical-neuromorphic-eikonal-benchmarks - Demo: https://huggingface.co/spaces/Agnuxo/optical-neuromorphic-pathfinding-demo ## Citation See README or paper for citation information.…”

Data Sheet 1_Deep reinforcement learning for time-critical wilderness search and rescue using drones.pdf by Jan-Hendrik Ewers (20657870)

“…Drones offer a faster and more flexible solution, but optimizing their search paths is crucial for effective operations. …”

<b>A virtual tracer experiment to assess the temporal origin of root water uptake, evaporation, and </b><b>drainage</b> by Paolo Nasta (19710883)

“…The RWU (<i>t</i>_<em>R</em>), evaporation (<i>t</i>_<em>E</em>), and drainage (<i>t</i>_<em>D</em>) transit times (<i>t</i>) were determined by using the actual dispersivity optimized in a prior study.<a href="" target="_blank"> First, </a><i>t</i>_<em>R</em> and <i>t</i>_<em>D</em> were compared to RWU (<i>t</i>_{<em>PT,R</em>}) and drainage (<i>t</i>_{<em>PT,D</em>}) advective transit times estimated using the particle tracking algorithm. …”

Figures and Tables by Divya C D (22799186)

“…Robots Comput. Vision XXXI: Algorithms and Techniques, Burlingame, CA, USA, Jan. 23–24, 2012.…”