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Correlation of Prominent Intelligence Type & Coworker Relations

Rasmus et al. | Mar 29, 2022

Correlation of Prominent Intelligence Type & Coworker Relations

Ashley Moulton & Joseph Rasmus investigate 9 controversial categories of intelligence as predicted by Multiple Intelligence Theory, originally proposed in the mid-1980s. By collecting data from 56 participants, they record that there may not actually be a correlation between these categorical types when it comes to workplace atmosphere and project efficiency.

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Does Gaming Improve Cognitive Skills?

Chakravarti et al. | Jan 26, 2015

Does Gaming Improve Cognitive Skills?

Playing video games may improve mental performance by encouraging practicing logical reasoning skills. Students who played video games in between two tests tended to perform better on the second test than those that did not play video games.

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A comparative analysis of machine learning approaches for prediction of breast cancer

Nag et al. | May 11, 2021

A comparative analysis of machine learning approaches for prediction of breast cancer

Machine learning and deep learning techniques can be used to predict the early onset of breast cancer. The main objective of this analysis was to determine whether machine learning algorithms can be used to predict the onset of breast cancer with more than 90% accuracy. Based on research with supervised machine learning algorithms, Gaussian Naïve Bayes, K Nearest Algorithm, Random Forest, and Logistic Regression were considered because they offer a wide variety of classification methods and also provide high accuracy and performance. We hypothesized that all these algorithms would provide accurate results, and Random Forest and Logistic Regression would provide better accuracy and performance than Naïve Bayes and K Nearest Neighbor.

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The study of technology and the use of individual cognitive effort

Neravetla et al. | Jan 24, 2023

The study of technology and the use of individual cognitive effort
Image credit: Glenn Carstens-Peters

A trial study was performed in 2021 to investigate the link between technology and transactive memory. Transactive memory is shared knowledge in which members share the responsibility to encode, store, and retrieve certain tasks or assignments, leading to a successful and collective performance. We hypothesize that a participants’ expected access to an external source affects the recall rate and retrieval of information.

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Artificial Intelligence Networks Towards Learning Without Forgetting

Kreiman et al. | Oct 26, 2018

Artificial Intelligence Networks Towards Learning Without Forgetting

In their paper, Kreiman et al. examined what it takes for an artificial neural network to be able to perform well on a new task without forgetting its previous knowledge. By comparing methods that stop task forgetting, they found that longer training times and maintenance of the most important connections in a particular task while training on a new one helped the neural network maintain its performance on both tasks. The authors hope that this proof-of-principle research will someday contribute to artificial intelligence that better mimics natural human intelligence.

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