Browse Articles

Augmented Reality Chess Analyzer (ARChessAnalyzer): In-Device Inference of Physical Chess Game Positions through Board Segmentation and Piece Recognition using Convolutional Neural Networks

Mehta et al. | Jul 17, 2020

Augmented Reality Chess Analyzer (ARChessAnalyzer): In-Device Inference of Physical Chess Game Positions through Board Segmentation and Piece Recognition using Convolutional Neural Networks

In this study the authors develop an app for faster chess game entry method to help chess learners improve their game. This culminated in the Augmented Reality Chess Analyzer (ARChessAnalyzer) which uses traditional image and vision techniques for chess board recognition and Convolutional Neural Networks (CNN) for chess piece recognition.

Read More...

Methanotrophic bioremediation for the degradation of oceanic methane and chlorinated hydrocarbons

Lee et al. | Oct 08, 2021

Methanotrophic bioremediation for the degradation of oceanic methane and chlorinated hydrocarbons

Seeking an approach to address the increasing levels of methane and chlorinated hydrocarbons that threaten the environment, the authors worked to develop a novel, low-cost biotrickling filter for use as an ex situ method tailored to marine environments. By using methanotrophic bacteria in the filter, they observed methane degradation, suggesting the feasibility of chlorinated hydrocarbon degradation.

Read More...

Assessing grass water use efficiency through smartphone imaging and ImageJ analysis

Shen et al. | Jul 27, 2022

Assessing grass water use efficiency through smartphone imaging and ImageJ analysis

Overwatering and underwatering grass are widespread issues with environmental and financial consequences. This study developed an accessible method to assess grass water use efficiency (WUE) combining smartphone imaging with open access color unmixing analysis. The method can be applied in automated irrigation systems or apps, providing grass WUE assessment for regular consumer use.

Read More...

A machine learning approach for abstraction and reasoning problems without large amounts of data

Isik et al. | Jun 25, 2022

A machine learning approach for abstraction and reasoning problems without large amounts of data

While remarkable in its ability to mirror human cognition, machine learning and its associated algorithms often require extensive data to prove effective in completing tasks. However, data is not always plentiful, with unpredictable events occurring throughout our daily lives that require flexibility by artificial intelligence utilized in technology such as personal assistants and self-driving vehicles. Driven by the need for AI to complete tasks without extensive training, the researchers in this article use fluid intelligence assessments to develop an algorithm capable of generalization and abstraction. By forgoing prioritization on skill-based training, this article demonstrates the potential of focusing on a more generalized cognitive ability for artificial intelligence, proving more flexible and thus human-like in solving unique tasks than skill-focused algorithms.

Read More...

Assessing the Efficacy of NOX Enzyme Inhibitors as Potential Treatments for Ischemic Stroke in silico

Vinay et al. | Sep 18, 2020

Assessing the Efficacy of NOX Enzyme Inhibitors as Potential Treatments for Ischemic Stroke <i>in silico</i>

Ischemic stroke occurs when blood flow to the brain is interrupted, causing brain damage. This study investigated the effectiveness of different NOX inhibitors as treatments for ischemic stroke in silico. The results help corroborate previous in vivo and in vitro studies in an in silico format, and can be used towards developing drugs to treat ischemic stroke.

Read More...

Physical Appearance and Its Effect on Trust

Ledesma et al. | Nov 09, 2020

Physical Appearance and Its Effect on Trust

Do different physical traits affect teenagers’ initial trust of an unknown person? Would they give greater trust to women and people of similar ethnicity? To test these hypotheses, the authors developed a survey to determine the sets of physical characteristics that affect a person's trustworthiness. They found that gender and expression were the main physical traits associated with how trustworthy an individual looks, while ethnicity was also important.

Read More...

Bacteroides thetaiotaomicron Growth Numbers Are Unchanged in the Presence of Yogurt

Phan et al. | Dec 29, 2016

<i>Bacteroides thetaiotaomicron</i> Growth Numbers Are Unchanged in the Presence of Yogurt

Disruptions to the microbiome, specifically the imbalance in the two major phyla, the Firmicutes and the Bacteroidetes, have been linked to the development of obesity. This study explored whether or not Fage plain total 0% Greek yogurt, which contains live and active bacterial cultures belonging to the Firmicute phylum, could decrease the numbers of Bacteroides thetaiotaomicron, an organism found in the human gut that belongs to the Bacteroidetes phylum.

Read More...

A Cloud-Enabled Communication Strategy for Wildfire Alerts

Vinaithirthan et al. | Jul 19, 2020

A Cloud-Enabled Communication Strategy for Wildfire Alerts

The traditional alert system in California consists of Wireless Emergency Alerts (WEAs), which lack location specificity, and sign-up-based technology which is limited by the number of sign ups. Those who do not have phones or have a silence option on their devices are most at risk from the current alert system. Here the authors developed cloud-enabled crisis connection for disaster alerts (CRISIS-CONNECT) to mitigate problems associated with the current alert system.

Read More...

Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Patel et al. | Mar 14, 2022

Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe2) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.

Read More...

DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection

Wang et al. | Jun 05, 2018

DyGS: A Dynamic Gene Searching Algorithm for Cancer Detection

Wang and Gong developed a novel dynamic gene-searching algorithm called Dynamic Gene Search (DyGS) to create a gene panel for each of the 12 cancers with the highest annual incidence and death rate. The 12 gene panels the DyGS algorithm selected used only 3.5% of the original gene mutation pool, while covering every patient sample. About 40% of each gene panel is druggable, which indicates that the DyGS-generated gene panels can be used for early cancer detection as well as therapeutic targets in treatment methods.

Read More...

Search Articles

Search articles by title, author name, or tags

Clear all filters

Popular Tags

Browse by school level