
In this experiment, the authors modify the heat equation to account for imperfect insulation during heat transfer and compare it to experimental data to determine which is more accurate.
Read More...Heat conduction: Mathematical modeling and experimental data
In this experiment, the authors modify the heat equation to account for imperfect insulation during heat transfer and compare it to experimental data to determine which is more accurate.
Read More...The effects of container materials on food microwave heat times
The authors analyzed the heat transfer of different containers in the microwave aiming to identify the most optimal material of container to reduce heating time.
Read More...Transfer learning and data augmentation in osteosarcoma cancer detection
Osteosarcoma is a type of bone cancer that affects young adults and children. Early diagnosis of osteosarcoma is crucial to successful treatment. The current methods of diagnosis, which include imaging tests and biopsy, are time consuming and prone to human error. Hence, we used deep learning to extract patterns and detect osteosarcoma from histological images. We hypothesized that the combination of two different technologies (transfer learning and data augmentation) would improve the efficacy of osteosarcoma detection in histological images. The dataset used for the study consisted of histological images for osteosarcoma and was quite imbalanced as it contained very few images with tumors. Since transfer learning uses existing knowledge for the purpose of classification and detection, we hypothesized it would be proficient on such an imbalanced dataset. To further improve our learning, we used data augmentation to include variations in the dataset. We further evaluated the efficacy of different convolutional neural network models on this task. We obtained an accuracy of 91.18% using the transfer learning model MobileNetV2 as the base model with various geometric transformations, outperforming the state-of-the-art convolutional neural network based approach.
Read More...Variations in Heat Absorption and Release of Earth Surfaces During Fall in Laramie, Wyoming
Here the authors investigate the contributions of man-made surfaces in Laramie, Wyoming to the Urban Heat Island (UHI) effect. Heat absorption and release by five surfaces were measured in the autumn of 2018. By recording temperatures of man-made and natural surfaces at early morning, mid-afternoon, and evening using an infrared thermometer, the authors determined that man-made surfaces retained more heat in fall than natural surfaces.
Read More...Examining Heat Recovery from Electric Light Bulbs Using Thermoelectric Generators
Here the author investigates how much heat energy is output and recovered from a conventional electric light bulb.
Read More...Heat impact to food’s shelf life - An example of milk
Food spoilage happens when food is not kept in a good storage condition. Qualitatively estimating the shortened shelf life of food could reduce food waste. In this study, we tested the impact of heat on milk shelf life. Our results showed that an exposure at room temperature (25°C) for 3.2 hours will decrease the shelf life of milk by one day.
Read More...Astragalus membranaceus Root Concentration and Exposure Time: Role in Heat Stress Diminution in C. elegans
In this study, the authors investigated the biological mechanism underlying the actions of a traditional medicinal plant, Astragalus membranaceus. Using C. elegans as an experimental model, they tested the effects of AM root on heat stress responses. Their results suggest that AM root extract may enhance the activity of endogenous pathways that mediate cellular responses to heat stress.
Read More...Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance
In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.
Read More...Machine learning for the diagnosis of malaria: a pilot study of transfer learning techniques
The diagnosis of malaria remains one of the major hurdles to eradicating the disease, especially among poorer populations. Here, the authors use machine learning to improve the accuracy of deep learning algorithms that automate the diagnosis of malaria using images of blood smears from patients, which could make diagnosis easier and faster for many.
Read More...Analysis of the effects of positive ions and boundary layer temperature at various hypersonic speeds on boundary layer density
This study's goal was to identify the Mach numbers for which electrostatic drag and heat transfer manipulation would be most applicable inside the stratosphere. The experiments were conducted using computational fluid dynamics software. The study demonstrated that, on average, higher Mach speeds resulted in a considerably higher potential decrease in density. The study highlights that further research on the surface charge method is warranted to explore higher hypersonic speeds within the stratosphere.
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