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The effect of activation function choice on the performance of convolutional neural networks

Wang et al. | Sep 15, 2023

The effect of activation function choice on the performance of convolutional neural networks
Image credit: Tara Winstead

With the advance of technology, artificial intelligence (AI) is now applied widely in society. In the study of AI, machine learning (ML) is a subfield in which a machine learns to be better at performing certain tasks through experience. This work focuses on the convolutional neural network (CNN), a framework of ML, applied to an image classification task. Specifically, we analyzed the performance of the CNN as the type of neural activation function changes.

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The Cohesiveness of the Oscillating Belousov-Zhabotinsky Reaction

Gottlieb et al. | Dec 18, 2018

The Cohesiveness of the Oscillating Belousov-Zhabotinsky Reaction

In this study the author undertakes a careful characterization of a special type of chemical reaction, called an oscillating Belousov-Zhabotinsky (or B-Z) reaction, which has a number of existing applications in biomedical engineering as well as the potential to be useful in future developments in other fields of science and engineering. Specifically, she uses experimental measurements in combination with computational analysis to investigate whether the reaction is cohesive – that is, whether the oscillations between chemical states will remain consistent or change over time as the reaction progresses. Her results indicate that the reaction is not cohesive, providing an important foundation for the development of future technologies using B-Z reactions.

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Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Dao et al. | Jun 27, 2021

Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Engineered bacteria that degrade oil are currently being considered as a safe option for the treatment of oil spills. For this approach to be successful, the bacteria must effectively express oil-degrading genes they uptake as part of an external genoming vehicle called a "plasmid". Using a computational approach, the authors investigate plasmid-bacterium compatibility to find pairs that ensure high levels of gene expression.

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Characterization of Drought Tolerance in Arabidopsis Mutant fry1-6

Kim et al. | Jan 07, 2019

Characterization of Drought Tolerance in Arabidopsis Mutant  fry1-6

In a world where water shortage is becoming an increasing concern, and where population increase seems inevitable, food shortage is an overwhelming concern for many. In this paper, the authors aim to characterize a drought-resistant strain of A. thaliana, investigating the cause for its water resistance. These and similar studies help us learn how plants could be engineered to improve their ability to flourish in a changing climate.

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Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution

Bhardwaj et al. | Dec 14, 2021

Artificial Intelligence-Based Smart Solution to Reduce Respiratory Problems Caused by Air Pollution

In this report, Bhardwaj and Sharma tested whether placing specific plants indoors can reduce levels of indoor air pollution that can lead to lung-related illnesses. Using machine learning, they show that plants improved overall indoor air quality and reduced levels of particulate matter. They suggest that plant-based interventions coupled with sensors may be a useful long-term solution to reducing and maintaining indoor air pollution.

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Effects of Wi-Fi EMF on Drosophila melanogaster

Anand et al. | Jan 29, 2020

Effects of Wi-Fi EMF on <em>Drosophila melanogaster</em>

While increased access to Wi-Fi has been a great advancement, we have a limited understanding if there are any health effects on animals. In this study, Anand and Anand exposed fruit flies (Drosophila melanogaster) to different concentrations of Wi-Fi electromagnetic fields, and observed effects on their reproduction and survivability.

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More Efficient Helicopter Blades Based on Whale Tubercles

Weitzman et al. | Dec 22, 2013

More Efficient Helicopter Blades Based on Whale Tubercles

Biomimicry is the practice of applying models and systems found in nature to improve the efficiency and usefulness of human technologies. In this study, the authors designed helicopter blades with tubercle structures similar to those found on the tails of humpback whales. The authors found that certain arrangements of these tubercle structures improved the windspeed and efficiency of a model helicopter.

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The Effect of Different Concentrations of Iron on the Growth of Egeria (Elodea) Densa

Hu et al. | Jan 08, 2015

The Effect of Different Concentrations of Iron on the Growth of <em>Egeria (Elodea) Densa</em>

Minerals such as iron are essential for life, but too much of a good thing can be poisonous. Here the authors investigate the effect of iron concentrations on the growth of an aquatic plant and find that supplementing small amounts of iron can help, but adding too much can be bad for the plant. These results should help inform decisions on allowable iron concentrations in the environment, aquatic farming, and even home aquariums.

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