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Students from the College of Science and Engineering participate in posters in St. Paul

Poster Presentation in St. Paul

On March 1, a handful of SCSU students had the opportunity to present their undergraduate research at the 2023 Poster at St. Paul event, organized by the Undergraduate Research Center at Minnesota State University, Mankato. In total 33 poster presentations were submitted, of these 33 posters 14 were co-authored by SCSU students. Eight of the 14 SCSU posters were products of students from the Department of Biology. The judges evaluated each poster presentation and gave awards to the four best. Of these four best, two were from SCSU.

 

Kerri Beers (Biology: Biodiversity, Ecology, Evolution Major, Dept. of Biology) was one of the awardees whose presentation, “Spot the Difference in Salamanders: using museum specimens to examine pattern and shape”, examines whether the dorsal pattern, and aspects of body shape, differ between the sexes of Eastern Tiger Salamanders. Beers spoke to the application of her study, saying that “understanding dorsal patterns and body size in relation to sex could help with better understanding the species. Males and females could have different stress factors that might influence how their dorsal spots appear”. She said that the most difficult part of the study was photographing the salamanders. Beers originally wanted to photograph the museum specimen outside of their ethanol filled jars but, after realizing that the spots weren’t as vibrant outside of the ethanol, she had to pivot and take images of the specimen submerged in the ethanol.

Arteom Katkov (Electrical Engineering Major, Dept. of Electrical and Computer Engineering) was another one of the SCSU awardees. The presentation, “SmartMeshIP Wireless Sensor Network using LTE, Smartphone, and Cloud Computing”, highlights a new wireless sensor network of SmartMeshIP to be deployed in remote areas without Wi-Fi access. This technology that the group developed is brand new to the industry. Katkov was accompanied in his work by Zak Abid, Suhaib Abugdera, and Isaac Koop. Dr. Yi Zheng, the graduate director of the Electrical Engineering program, mentored the group and facilitated project sponsorship from Emmerson Co.

All posters submitted for the event can be viewed here.

Company owned by SCSU alumnus earns 2023 Small Business Exporter of the Year recognition

RaJ BHANDARI
Raj Bhandari ’08

St. Cloud State University alumnus Raj Bhandari ’08 had his company, Sciencix, recognized by the U.S. Small Business Administration as the 2023 Small Business Exporter of the Year in March. Bhandari, who earned a bachelor’s degree in Chemistry and a minor in Biology from SCSU in 2008, is the sole owner and president of Sciencix.

This prestigious award is given out once each year by the U.S. Small Business Administration to a small business that exemplifies an impressive increase in company exports. Specifically, with the use of “$24,000 in SBA State Trade Expansion Program (STEP) grant funding” Sciencix boosted exports to a point where they now account for one-third of Sciencix’s total sales, a 10% increase from their 2020 export amount.

After completing his undergraduate studies at SCSU, Bhandari went on to obtain his doctorate degree from South Dakota State University. Sciencix is a manufacturer of high-performance liquid chromatography and mass spectrometry parts. These parts are used in drug testing, contamination analysis, pesticide detection, and other applications.

 

 

COSE students have research article published in international journal

In early March, two St. Cloud State students from the College of Science and Engineering (COSE) had their research article published in an international, scientific, peer-reviewed journal.

Faizi Fifita
Faizi Fifita

Software Engineering student Faizi Fifita and Data Science and Mathematics student Jordan Smith had their research article titled “Machine Learning-Based Identifications of COVID-19 Fake News Using Biomedical Information Extraction”, published in Big Data and Cognitive Computing. This research article belongs to the journal’s collection: Machine Learning and Artificial Intelligence for Health Applications on Social Networks.

Fifita and Smith’s research article highlights the spread of fake news related to the COVID-19 pandemic, which was labeled as an “infodemic” by the World Health Organization (WHO). This fake news can be blamed for numerous hate crimes, vaccine hesitancy and psychological disorders. The method they worked on was computer-based detection models whose algorithms allow them to pick out fake news.

Typically, these models compare various news articles to a data set of accurate news articles to compare the tone, source, and writing style of the articles. This process helps weed out the fake from the true. Fifita and Smith built on this method by leveraging a data set “of 1,164 COVID-19-related news articles collected from various platforms such as Twitter, Facebook, The New York Times, Harvard Health Publishing, WHO, etc.”.

Jordan Smith
Jordan Smith

They applied natural language processing algorithms to extract biomedical information from news articles. They then constructed machine-understandable features based on this information. By adding these features to several machine learning models, they tested the accuracy of the models in detecting fake news. It was found that the addition of biomedical information led to an increase in the accuracy of the models in detecting fake news.

This represents the first study to incorporate biomedical information extraction with machine learning-based COVID-19 fake news detections. The results of Fifita and Smith’s research article provides a new angle for future fake news detection models. In a time where fake news is running rampant, the work of these students has the potential to help put news back on track.

This research was funded by the National Science Foundation under grant No. 1742517 and SCSU early career grant.

Faculty member Dr. Mengshi Zhou was the supervising mentor for the project.

View the full published journal article.

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