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Full-Text Articles in Engineering
Efficiency Study Of A Hybrid Ac/Dc House, Eunice Dominique Solomon Santiago
Efficiency Study Of A Hybrid Ac/Dc House, Eunice Dominique Solomon Santiago
Master's Theses
With the proliferation of residential-scale renewable energy sources and DC loads, it has become attractive to use residential DC electrical system that could offer benefits over the legacy residential AC electrical system. The Hybrid AC/DC house provides a sustainable alternative to preexisting residential electrical system by having both AC and DC buses. The DC bus facilitates the connection from DC sources to DC loads, whereas the AC bus interfaces AC sources to AC loads. The study develops the equations to calculate losses based on a model consisting of four main components: Multiple-Input Single-Output (MISO) converter, AC-DC converter, inverter, and DC-DC …
Investigation Of Degradation Of Solar Photovoltaics: A Review Of Aging Factors, Impacts, And Future Directions Toward Sustainable Energy Management, Eklas Hossain
Electrical and Computer Engineering Faculty Publications and Presentations
The degradation of solar photovoltaic (PV) modules is caused by a number of factors that have an impact on their effectiveness, performance, and lifetime. One of the reasons contributing to the decline in solar PV performance is the aging issue. This study comprehensively examines the effects and difficulties associated with aging and degradation in solar PV applications. In light of this, this article examines and analyzes many aging factors, including temperature, humidity, dust, discoloration, cracks, and delamination. Additionally, the effects of aging factors on solar PV performance, including the lifetime, efficiency, material degradation, overheating, and mismatching, are critically investigated. Furthermore, …
Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney
Lightnet: A Novel Lightweight Convolutional Network For Brain Tumor Segmentation In Healthcare, Dongyuan Wu, Junyi Tao, Zhen Qin, Rao Asad Mumtaz, Jin Qin, Linfang Yu, Jane Courtney
Articles
Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model. This work proposes a simple and effective feed-forward CNN, LightNet (Light Network). Based on multi-path and multi-level, it replaces traditional convolutional methods with light operations, which reduces network parameters and redundant feature maps. In the …