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Evaluating machine learning algorithms to classify forest tree species through satellite imagery

Gupta et al. | Mar 18, 2023

Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Image credit: Sergei A

Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

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Interaction of light with water under clear and algal bloom conditions

Ramesh et al. | Feb 01, 2024

Interaction of light with water under clear and algal bloom conditions
Image credit: Liz Harrell

Here, recognizing the potential harmful effects of algal blooms, the authors used satellite images to detect algal blooms in water bodies in Wyoming based on their reflectance of near infrared light. They found that remote monitoring in this way may provide a useful tool in providing early warning and advisories to people who may live in close proximity.

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Suppress that algae: Mitigating the effects of harmful algal blooms through preemptive detection & suppression

Natarajan et al. | Jul 17, 2023

Suppress that algae: Mitigating the effects of harmful algal blooms through preemptive detection & suppression
Image credit: Sharanya Natarajan

A bottleneck in deleting algal blooms is that current data section is manual and is reactionary to an existing algal bloom. These authors made a custom-designed Seek and Destroy Algal Mitigation System (SDAMS) that detects harmful algal blooms at earlier time points with astonishing accuracy, and can instantaneously suppress the pre-bloom algal population.

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The comparative effect of remote instruction on students and teachers

Ng et al. | Jan 16, 2022

The comparative effect of remote instruction on students and teachers

In this study, high school students and teachers responded to a survey consisting of Likert-type scale, multiple-choice, and open-ended questions regarding various aspects of remote instruction. After analyzing the data collected, they found that remote learning impacted high school students academically and socially. Students took longer to complete assignments, and both students and teachers felt that students do not learn as much in remote learning compared to in-person instruction. However, most high school students demonstrated a comprehensive understanding of the topics, and an overall negative impact on students' grades was not detected.

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Impact of Kindles4Covid Virtual Reading Buddies Program on reading frequency and social connections

Pandey et al. | Jun 25, 2022

Impact of Kindles4Covid Virtual Reading Buddies Program on reading frequency and social connections

With the COVID-19 pandemic necessitating the transition to remote learning, disruption to daily school routine has impacted educational experiences on a global scale. As a result, it has potentially worsened reading achievement gaps typically exacerbated by long summer months. To address literacy skill retention and pandemic-induced social isolation, the non-profit organization ByKids4Kids has created a reading program, “Kindles4Covid Virtual Reading Buddies Program,” to instill a structure for youth to read together and connect with the convenience of Amazon Kindle devices. In this article, the authors determine the efficacy of their invaluable program by assessing changes in reading frequency and self-reported connectedness among program participants.

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Enhancing the quantum efficiency of a silicon solar cell using one dimensional thin film interferometry

Ahuja et al. | May 03, 2024

Enhancing the quantum efficiency of a silicon solar cell using one dimensional thin film interferometry
Image credit: American Public Power Association

Here, recognizing the need to improve the efficiency of the conversion of solar energy to electrical energy, the authors used MATLAB to mathematically simulate a multi-layered thin film with an without an antireflective coating. They found that the use of alternating ZnO-SiO2 multilayers enhanced the transmission of light into the solar cell, increasing its efficiency and reducing the reflectivity of the Si-Air interface.

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