Identification of a Gene Signature That Predicts Dependence upon YAP/TAZ-TEAD by Kanai, Ryan, Norton, Emily, Stern, Patrick, Hynes, Richard O., Lamar, John M.

“…We found that the genes in this signature are TEAD-dependent in several melanoma cell lines, and that their expression strongly correlates with YAP/TAZ activation in human melanomas. Using DepMap dependency data, we found that this YAP/TAZ signature was predictive of melanoma cell dependence upon YAP/TAZ or TEADs. …”
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Language, Camera, Autonomy! Prompt-engineered Robot Control for Rapidly Evolving Deployment by Macdonald, Jacob P., Mallick, Rohit, Wollaber, Allan B., Peña, Jaime D., McNeese, Nathan, Siu, Ho Chit

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Avoidance of Concave Obstacles Through Rotation of Nonlinear Dynamics by Huber, Lukas, Slotine, Jean-Jacques, Billard, Aude

“…We introduce a sequence of mappings to extend the approach for general nonlinear dynamics. …”
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Learning Bit Allocations for Z-Order Layouts in Analytic Data Systems by Gao, Jenny, Ding, Jialin, Sudhir, Sivaprasad, Madden, Samuel

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Semantic embedding for quantum algorithms by Rossi, Zane M, Chuang, Isaac L

“…This work constructs and characterizes the runtime and expressivity of QSP/QSVT protocols where circuit manipulation maps naturally to the algebraic manipulation of functional transforms (termed semantic embedding). …”
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Towards Efficient Planning for Navigation using Global Information in Large and Uncertain Environments by Kurtz, Martina Stadler

“…For example, many planners assume access to complete global information in the form of full environment maps, or they assume that locally good planning decisions under uncertainty will result in globally good planning outcomes. …”
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Theoretical Design of Molecular Nanostructures for Exciton Control by Castellanos, Maria A.

“…In Chapter 2, I develop a novel approach to map unitary quantum computing operations to Hamiltonians describing excitonic circuits in the presence of a model bath. …”
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Enabling Perspective-Aware Ai with Contextual Scene Graph Generation by Platnick, Daniel, Alirezaie, Marjan, Rahnama, Hossein

“…We evaluated PASGG-LM pipelines using state-of-the-art SGG models, including Motifs, Motifs-TDE, and RelTR, and showed that fine-tuning LLMs, particularly GPT-4o-mini and Llama-3.1-8B, improves performance in terms of R@K, mR@K, and mAP. Our method is capable of generating scene graphs that capture complex contextual aspects, advancing human–machine interaction by enhancing the representation of diverse perspectives. …”
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Decoding Surface Touch Typing from Hand-Tracking by Richardson, Mark, Durasoff, Matt, Wang, Robert

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Semantic sensitive satellite image retrieval by Li, Yikun

“…The main difficulty is that users think in terms of high-level semantics, which cannot be directly mapped onto extracted low-level features / signals. …”
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Tripartite partnership for the transformation of the Singapore maritime industry - Part B : Industry's perspective by Tan, Xian Jun

“…In responses to the threat of the changing economy, the Singapore government have launched several initiatives including the Industry Transport Maps (ITMs) to facilitate an effective tripartite partnership towards the transformation of Singapore’s Maritime Industry. …”
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Imaging and processing of tree trunk by Hong, Yuan Ming

“…Therefore, further investigations were conducted to better understand the peak time differences between 2D simulation and 3D simulation where the results can help to map the 2D simulations into 3D simulation using machine learning.…”
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Deep visual saliency on stereoscopic images by Nguyen, Anh-Duc, Kim, Jongyoo, Oh, Heeseok, Kim, Haksub, Lin, Weisi, Lee, Sanghoon

“…Our results from thorough experiments confirm that the predicted saliency maps are up to 70% correlated with human gaze patterns, which emphasize the need for the hand-crafted features as input to deep neural networks in S3D saliency detection.…”
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Ultra-low power real-ime object detection based on quantized CNNs by Chew, Jing Wei

“…Using this approach, the proposed model can run at 37.7 FPS on an NVIDIA Jetson Nano with a peak memory footprint of 17.1 MB, while attaining a reasonable mAP@0.50 Intersection over Union (IoU) of 0.37 on the Pascal Visual Object Classes (VOC) dataset. …”
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Multi-view human action recognition in meeting scenarios by Yin, Haixiang

“…The method proposed in this project can improve by up to nearly 10 percent of the mAP (Mean Average Precision) on AMI meeting corpus compared to single-view recognition approaches.…”
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Visual place recognition for autonomous robots using deep learning by Huang, Yifeng

“…In autonomous and unmanned aerial vehicles, visual location recognition helps to detect actual destinations and locations In order to match standard features from different angles of a scene, we propose a global feature matching method, which is separate from the current popular local feature matching method. We build attention maps from two dimensions to refine the calculation methods of residuals in VLAD, channel and spatial, and get better results than the original NetVLAD model. …”
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Mobile robot localization in geometrically symmetric environments by Lyu, Yaozeng

“…In addition, the similar magnetic field single fingerprint information can easily cause mismatches in the magnetic field map, then lead to localization failures. This project will explore and propose novel magnetic field-based localization algorithms for mobile robots to achieve highly robust and precise localization in geometrically symmetric environment.…”
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Thermodynamic properties of Xenon storage system under adsorption condition by Koh, Darren Shi Hao

“…Furthermore, through the entropy and temperature maps analysis, a typical heat storage system can be represented where the charging and discharging of Xenon (Xe) gas is represented by the change of entropy in a closed loop.…”
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Hydrological & hydrodynamic modelling of the Baliem River in Highland Papua, Indonesia by Wee, Khai Zher

“…We first delineated the watersheds for these pour points in ArcMap to characterise their attributes. Thereafter, we generated simulated river discharges at these pour points with meteorological data in the Génie Rural à 4 paramètres Journalier (GR4J) rainfall-runoff hydrological model. …”
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Deep neural network model for hypertension risk level detection using ECG signal by Lau, Kai Yun

“…The deep convolutional network consists of 1D convolution and max pooling layers, which extract feature mappings and perform risk level classifications. It classifies the ECGs into ‘normotensive’ (no risk), ‘hypertension’ (low risk), and ‘hypertension + any recorded event within 12 months of recording’ (high risk). …”
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