Results 91 to 100 of about 2,110,315 (345)

Fast approximation of search trees on trees with centroid trees

open access: yes, 2022
Search trees on trees (STTs) generalize the fundamental binary search tree (BST) data structure: in STTs the underlying search space is an arbitrary tree, whereas in BSTs it is a path. An optimal BST of size $n$ can be computed for a given distribution of queries in $O(n^2)$ time [Knuth 1971] and centroid BSTs provide a nearly-optimal alternative ...
Berendsohn, Benjamin Aram   +3 more
openaire   +4 more sources

Detecting Dengue in Flight: Leveraging Machine Learning to Analyze Mosquito Flight Patterns for Infection Detection

open access: yesAdvanced Biology, EarlyView.
Dengue infection alters mosquito flight behavior, enabling detection using machine learning classifiers. This study analyzes 3D flight trajectories and evaluates multiple models, showing that longer sequence lengths improve classification performance.
Nouman Javed   +3 more
wiley   +1 more source

Key traits influencing the resistance of Eucalyptus camaldulensis to wind damage in coastal areas of South China

open access: yesFrontiers in Plant Science
AimsChina is one of the countries in the world most seriously affected by typhoons, which pose a great threat to the eucalyptus plantation industry.
Xiuhua Shang   +5 more
doaj   +1 more source

RRP9 Promotes Esophageal Squamous Cell Carcinoma Progression through E2F1 Transcriptional Regulation of CDK1

open access: yesAdvanced Biology, EarlyView.
The study reveals that RRP9 is abnormally highly expressed in ESCC tissues and is closely associated with poor prognosis in patients. Furthermore, it is found that RRP9 promotes ESCC progression through enhancing the E2F1‐mediated transcriptional regulation of CDK1.
Gang He   +14 more
wiley   +1 more source

Unrolling of Syngonium podophyllum: Functional Anatomy, Morphology and Modelling of Its Peltate Leaves

open access: yesAdvanced Biology, EarlyView.
The unrolling of the peltate leaves in Syngonium podophyllum is analyzed and quantified (left‐hand side to center). These measurements serve to verify a mathematical model for leaf unrolling based on the model used in Schmidt (2007). An additional formula for obtaining a layer mismatch from a prescribed radius is derived.
Michelle Modert   +4 more
wiley   +1 more source

Bridging Nature and Technology: A Perspective on Role of Machine Learning in Bioinspired Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
Machine learning (ML) is revolutionizing the development of bioinspired ceramics. This article investigates how ML can be used to design new ceramic materials with exceptional performance, inspired by the structures found in nature. The research highlights how ML can predict material properties, optimize designs, and create advanced models to unlock a ...
Hamidreza Yazdani Sarvestani   +2 more
wiley   +1 more source

A comparative analysis of the ticket purchase behaviour of live theatre attendees versus film theatre attendees. [PDF]

open access: yesAfrican Journal of Hospitality, Tourism and Leisure, 2016
Afrikaans live theatre and Afrikaans film theatre often make use of the same actors, writers and producers; and the sustainability of these industries are dependent on the ticket purchases of a very specific and selective market segment.
Prof K Botha   +2 more
doaj  

Static and Dynamic Behavior of Novel Y‐Shaped Sandwich Beams Subjected to Compressive Loadings: Integration of Supervised Learning and Experimentation

open access: yesAdvanced Engineering Materials, EarlyView.
In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi   +4 more
wiley   +1 more source

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

open access: yesAdvanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani   +4 more
wiley   +1 more source

Home - About - Disclaimer - Privacy