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An Investigative Analysis of Climate Change Using Historical and Modern Weather Data

Han et al. | Dec 02, 2013

An Investigative Analysis of Climate Change Using Historical and Modern Weather Data

Climate change is an important and contentious issue that has far-reaching implications for our future. The authors here compare primary temperature and precipitation data from almost 200 years ago against the present day. They find that the average annual temperature in Brooklyn, NY has risen significantly over this time, as has the frequency of precipitation, though not the amount of precipitation. These data stress the need for more ecologically-conscious choices in our daily lives.

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The Effect of Music on Heart Rate

Agrawal et al. | Apr 25, 2013

The Effect of Music on Heart Rate

Different songs can seem to evoke different emotions. Here the authors demonstrate that different songs can have a significant effect on the heart rate of listeners. A slower song slows heart rate, and a faster song increases it.

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Vineyard vigilance: Harnessing deep learning for grapevine disease detection

Mandal et al. | Aug 21, 2024

Vineyard vigilance: Harnessing deep learning for grapevine disease detection

Globally, the cultivation of 77.8 million tons of grapes each year underscores their significance in both diets and agriculture. However, grapevines face mounting threats from diseases such as black rot, Esca, and leaf blight. Traditional detection methods often lag, leading to reduced yields and poor fruit quality. To address this, authors used machine learning, specifically deep learning with Convolutional Neural Networks (CNNs), to enhance disease detection.

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The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer

Ip et al. | Jul 28, 2024

The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer

Here, in an effort to identify alternatives to oil-based plastic, the authors sought to investigate the effects of plasticizers on the mechanical properties and chemical composition of gelatin bioplastic matrices. Through measurements of their tensile strength and elongation at break, along with FTIR spectroscopy, they identified 3% w/v polyethylene glycol film as having the best performance in their study..

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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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