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Full-Text Articles in Other Engineering
Furthering Development Of Smart Fabrics To Improve The Accessibility Of Music Therapy, Ellie Nguyen, Daisy Z. Fernandez-Reyes, Franceli L. Cibrian
Furthering Development Of Smart Fabrics To Improve The Accessibility Of Music Therapy, Ellie Nguyen, Daisy Z. Fernandez-Reyes, Franceli L. Cibrian
Engineering Faculty Articles and Research
In this paper, we present the design and development of HarmonicThreads, a smart, cost-effective fabric augmented by generative machine learning algorithms to create music in real time according to the user's interaction. In this manner, we hypothesize that individuals with sensory differences could take advantage of the fabric's flexibility, the music will adapt according to users' interaction, and the affordable hardware we propose will make it more accessible. We follow a design thinking methodology using data from a multidisciplinary team in Mexico and the United States. Then we will close this paper by discussing challenges in developing accessible smart fabrics …
Self-Dual Systems For Backscattering Cancellation, Nasim Mohammadi Estrakhri
Self-Dual Systems For Backscattering Cancellation, Nasim Mohammadi Estrakhri
Engineering Faculty Articles and Research
Using carefully arranged electric and magnetic components, we have recently demonstrated that backscattering from otherwise arbitrarily shaped two- and three-dimensional structures can be fully eliminated. Here, first we investigate the possibility of creating self-dual microwave absorbers that may provide advantages compared to typical commercial magnetoelectric absorbers. Next, we demonstrate that the self-duality condition is not limited to homogenous structures and may be extended to effective material properties, opening the door to realistic implementation of these structures at microwave and optical frequencies.
Weakly-Supervised Learning Method For The Recognition Of Potato Leaf Diseases, Junde Chen, Xiaofang Deng, Yuxin Wen, Weirong Chen, Adnan Zeb, Defu Zhang
Weakly-Supervised Learning Method For The Recognition Of Potato Leaf Diseases, Junde Chen, Xiaofang Deng, Yuxin Wen, Weirong Chen, Adnan Zeb, Defu Zhang
Engineering Faculty Articles and Research
As a crucial food crop, potatoes are highly consumed worldwide, while they are also susceptible to being infected by diverse diseases. Early detection and diagnosis can prevent the epidemic of plant diseases and raise crop yields. To this end, this study proposed a weakly-supervised learning approach for the identification of potato plant diseases. The foundation network was applied with the lightweight MobileNet V2, and to enhance the learning ability for minute lesion features, we modified the existing MobileNet-V2 architecture using the fine-tuning approach conducted by transfer learning. Then, the atrous convolution along with the SPP module was embedded into the …
A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin
A Deep Learning-Based Approach To Extraction Of Filler Morphology In Sem Images With The Application Of Automated Quality Inspection, Md. Fashiar Rahman, Tzu-Liang Bill Tseng, Jianguo Wu, Yuxin Wen, Yirong Lin
Engineering Faculty Articles and Research
Automatic extraction of filler morphology (size, orientation, and spatial distribution) in Scanning Electron Microscopic (SEM) images is essential in many applications such as automatic quality inspection in composite manufacturing. Extraction of filler morphology greatly depends on accurate segmentation of fillers (fibers and particles), which is a challenging task due to the overlap of fibers and particles and their obscure presence in SEM images. Convolution Neural Networks (CNNs) have been shown to be very effective at object recognition in digital images. This paper proposes an automatic filler detection system in SEM images, utilizing a Mask Region-based CNN architecture. The proposed system …