The authors looked at how students performed on standardized tests when they were taught material via memorization vs. conceptual based approaches.
Read More...The impact of conceptual versus memorization-based teaching methods on student performance
The authors looked at how students performed on standardized tests when they were taught material via memorization vs. conceptual based approaches.
Read More...An assessment of controllable etiological factors involved in neonatal seizure using a Monte Carlo model
The authors used Monte Carlo simulations to assess the impacts of various factors on neonatal seizure risk.
Read More...Redefining and advancing tree disease diagnosis through VOC emission measurements
Here the authors investigated the use of an affordable gas sensor to detect volatile organic compound (VOC) emissions as an early indicator of tree disease, finding statistically significant differences in VOCs between diseased and non-diseased ash, beech, and maple trees. They suggest this sensor has potential for widespread early disease detection, but call for further research with larger sample sizes and diverse locations.
Read More...Convolutional neural network-based analysis of pediatric chest X-ray images for pneumonia detection
The authors test various machine learning models to improve the accuracy and efficiency of pneumonia diagnosis from X-ray images.
Read More...Quantitative analysis and development of alopecia areata classification frameworks
This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.
Read More...Enhancing the quantum efficiency of a silicon solar cell using one dimensional thin film interferometry
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.
Read More...Genetic algorithm based features selection for predicting the unemployment rate of India
The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.
Read More...Analyzing the effect of mycorrhizal fungi on plant communication of nutrients
The authors looked at the ability of plants to transfer phosphate between each other through mycorrhizal fungi. Specifically, they looked at whether plants with excess phosphate would transfer this nutrient to other plants that had depleted levels of phosphate.
Read More...Floor level estimation using MEMS pressure sensors
The authors propose a method to help first responders find the location of a person within a high-rise building in densely populated areas.
Read More...Pruning replay buffer for efficient training of deep reinforcement learning
Reinforcement learning (RL) is a form of machine learning that can be harnessed to develop artificial intelligence by exposing the intelligence to multiple generations of data. The study demonstrates how reply buffer reward mechanics can inform the creation of new pruning methods to improve RL efficiency.
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