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Articles 1 - 10 of 10
Full-Text Articles in Engineering
An Efficient Deep-Learning-Based Detection And Classification System For Cyber-Attacks In Iot Communication Networks, Qasem Abu Al-Haija, Saleh Zein-Sabatto
An Efficient Deep-Learning-Based Detection And Classification System For Cyber-Attacks In Iot Communication Networks, Qasem Abu Al-Haija, Saleh Zein-Sabatto
Electrical and Computer Engineering Faculty Research
With the rapid expansion of intelligent resource-constrained devices and high-speed communication technologies, the Internet of Things (IoT) has earned wide recognition as the primary standard for low-power lossy networks (LLNs). Nevertheless, IoT infrastructures are vulnerable to cyber-attacks due to the constraints in computation, storage, and communication capacity of the endpoint devices. From one side, the majority of newly developed cyber-attacks are formed by slightly mutating formerly established cyber-attacks to produce a new attack that tends to be treated as normal traffic through the IoT network. From the other side, the influence of coupling the deep learning techniques with the cybersecurity …
Optimization Of Electron Beam-Deposited Silver Nanoparticles On Zinc Oxide For Maximally Surface Enhanced Raman Spectroscopy, Andrew L. Cook, Christopher P. Haycook, Andrea K. Locke, Richard R. Mu, Todd D. Giorgio
Optimization Of Electron Beam-Deposited Silver Nanoparticles On Zinc Oxide For Maximally Surface Enhanced Raman Spectroscopy, Andrew L. Cook, Christopher P. Haycook, Andrea K. Locke, Richard R. Mu, Todd D. Giorgio
TIGER Institute Faculty Research
Surface enhanced Raman spectroscopy enables robust, rapid analysis on highly dilute samples. To be useful, the technique needs sensing substrates that will enhance intrinsically weak Raman signals of trace analytes. In particular, three-dimensional substrates such as zinc oxide nanowires decorated with electron-beam deposited silver nanoparticles are easily fabricated and serve the dual need of structural stability and detection sensitivity. However, little has been done to optimize electron beam-deposited silver nanoparticles for maximal surface enhancement in the unique dielectric environment of the zinc oxide substrate. Herein, fabrication and anneal parameters of electron beam-deposited silver nanoparticles were examined for the purpose of …
Survey On Deep Neural Networks In Speech And Vision Systems, M. Alam, Manar D. Samad, Lasitha Vidyaratne, Alexander Glandon, Khan M. Iftekharuddin
Survey On Deep Neural Networks In Speech And Vision Systems, M. Alam, Manar D. Samad, Lasitha Vidyaratne, Alexander Glandon, Khan M. Iftekharuddin
Computer Science Faculty Research
This survey presents a review of state-of-the-art deep neural network architectures, algorithms, and systems in speech and vision applications. Recent advances in deep artificial neural network algorithms and architectures have spurred rapid innovation and development of intelligent speech and vision systems. With availability of vast amounts of sensor data and cloud computing for processing and training of deep neural networks, and with increased sophistication in mobile and embedded technology, the next-generation intelligent systems are poised to revolutionize personal and commercial computing. This survey begins by providing background and evolution of some of the most successful deep learning models for intelligent …
Potential Of Hemp (Cannabis Sativa L.) For Paired Phytoremediation And Bioenergy Production, Hanah T. Rheay, Emmanuel C. Omondi, Catherine E. Brewer
Potential Of Hemp (Cannabis Sativa L.) For Paired Phytoremediation And Bioenergy Production, Hanah T. Rheay, Emmanuel C. Omondi, Catherine E. Brewer
Agricultural and Environmental Sciences Faculty Research
Hemp (Cannabis sativa L.) is a multi-use crop that has been investigated for its potential use in phytoremediation of heavy metals, radionuclides, and organic contaminants, and as a feedstock for bioenergy production. A review of research literature indicates that hemp is a suitable crop for phytoremediation, and a competitive option for bioenergy. Coupling phytoremediation and bioenergy production from a single hemp crop is a potential solution to overcoming the economic constraints of phytoremediation projects. The current challenge is ensuring that the extracted contaminants are not introduced into the consumer marketplace. After several decades of limited research on hemp in the …
Design And Experiment Of A Sun-Powered Smart Building Envelope With Automatic Control, Qiliang Lin, Yanchu Zhang, Arnaud Van Mieghem, Yi-Chung Chen, Nanfang Yu, Yuan Yang, Huiming Yin
Design And Experiment Of A Sun-Powered Smart Building Envelope With Automatic Control, Qiliang Lin, Yanchu Zhang, Arnaud Van Mieghem, Yi-Chung Chen, Nanfang Yu, Yuan Yang, Huiming Yin
Electrical and Computer Engineering Faculty Research
A novel sun-powered smart window blind (SPSWB) system has been designed and developed for the smart control of building envelopes to achieve the optimal internal comfort with minimum energy expenditure. Its self-powered sensing, controlling, and actuation significantly simplify the installation and maintenance of the system. The energy is harvested by the attached thin-film photovoltaic cells, after which it is voltage-regulated for the permanent storage into a rechargeable battery with 55% energy efficiency. The excessive heat absorbed by the solar cells is dissipated by a PVdF-HFP porous coating with more than 9% temperature reduction. The smart control of the energy harvesting …
Environmental Investigation Of Bio-Modification Of Steel Slag Through Microbially Induced Carbonate Precipitation, Junke Zhang, Peidong Su, Yadong Li, Lin Li
Environmental Investigation Of Bio-Modification Of Steel Slag Through Microbially Induced Carbonate Precipitation, Junke Zhang, Peidong Su, Yadong Li, Lin Li
Civil and Architectural Engineering Faculty Research
Steel slag (SS) is one of byproduct of steel manufacture industry. The environmental concerns of SS may limit their re-use in different applications. The goal of this study was to investigate the leaching behavior of metals from SS before and after treated by microbially induced carbonate precipitation (MICP). Toxicity characteristic leaching procedure, synthetic precipitation leaching procedure and water leaching tests were performed to evaluate the leaching behavior of major elements (Fe, Mg and Ca) and trace elements (Ba, Cu and Mn) in three scenarios. The concentrations of leaching metals increased with the content of SS. After it reached the peak …
Constitutive Model Of Lateral Unloading Creep Of Soft Soil Under Excess Pore Water Pressure, Wei Huang, Kejun Wen, Xiaojia Deng, Junjie Li, Zhijian Jiang, Yang Li, Lin Li, Farshad Amini
Constitutive Model Of Lateral Unloading Creep Of Soft Soil Under Excess Pore Water Pressure, Wei Huang, Kejun Wen, Xiaojia Deng, Junjie Li, Zhijian Jiang, Yang Li, Lin Li, Farshad Amini
Civil and Architectural Engineering Faculty Research
Presented in this paper is a study on the lateral unloading creep tests under different excess pore water pressures. The marine sedimentary soft soil in Shenzhen, China, was selected in this study. The results show that the excess pore water pressure plays a significant role in enhancing the unloading creep of soft soil. Higher excess pore water pressure brings more obvious creep deformation of soft soil and lower ultimate failure load. Meanwhile, the viscoelastic and the viscoplastic modulus of soft soil were found to exponentially decline with creep time. A modified merchant model and a combined model of the modified …
Geometric Optimization Of Plasmonic Nanostructure Arrays On Mwir Hgcdte (Mct), Nagendrababu Vanamala, Kevin C. Santiago, Naresh C. Das, Samuel Keith Hargrove
Geometric Optimization Of Plasmonic Nanostructure Arrays On Mwir Hgcdte (Mct), Nagendrababu Vanamala, Kevin C. Santiago, Naresh C. Das, Samuel Keith Hargrove
Mechanical and Manufacturing Engineering Faculty Research
Mercury Cadmium Telluride (MCT) is a primary absorber material used in most infrared (IR) detection technologies. Our previous studies show that the optical absorbance profile of MCT in the mid-infrared region can be enhanced by 13% under ambient conditions via integrating periodic Indium Tin Oxide (ITO) nanostructures. Here, we focus on the geometrical parameterization and optimization of ITO nanostructure arrays. We simulate several types of geometries, their corresponding effective absorption profiles, E-field distribution, and optimal geometric parameters. This work may lead to improved light collection and absorption edge engineering, as MCT continues to be the material of choice in IR …
Optimization Of Window Positions For Wind-Driven Natural Ventilation Performance, Nari Yoon, Mary Ann Piette, Jung Min Han, Wentao Wu, Ali Malkawi
Optimization Of Window Positions For Wind-Driven Natural Ventilation Performance, Nari Yoon, Mary Ann Piette, Jung Min Han, Wentao Wu, Ali Malkawi
Civil and Architectural Engineering Faculty Research
This paper optimizes opening positions on building facades to maximize the natural ventilation’s potential for ventilation and cooling purposes. The paper demonstrates how to apply computational fluid dynamics (CFD) simulation results to architectural design processes, and how the CFD-driven decisions impact ventilation and cooling: (1) background: A CFD helps predict the natural ventilation’s potential, the integration of CFD results into design decision-making has not been actively practiced; (2) methods: Pressure data on building facades were obtained from CFD simulations and mapped into the 3D modeling environment, which were then used to identify optimal positions of two openings of a zone. …
Ahead: Automatic Holistic Energy-Aware Design Methodology For Mlp Neural Network Hardware Generation In Proactive Bmi Edge Devices, Nan-Sheng Huang, Yi-Chung Chen, Jørgen Christian Larsen, Poramate Manoonpong
Ahead: Automatic Holistic Energy-Aware Design Methodology For Mlp Neural Network Hardware Generation In Proactive Bmi Edge Devices, Nan-Sheng Huang, Yi-Chung Chen, Jørgen Christian Larsen, Poramate Manoonpong
Electrical and Computer Engineering Faculty Research
The prediction of a high-level cognitive function based on a proactive brain–machine interface (BMI) control edge device is an emerging technology for improving the quality of life for disabled people. However, maintaining the stability of multiunit neural recordings is made difficult by the nonstationary nature of neurons and can affect the overall performance of proactive BMI control. Thus, it requires regular recalibration to retrain a neural network decoder for proactive control. However, retraining may lead to changes in the network parameters, such as the network topology. In terms of the hardware implementation of the neural decoder for real-time and low-power …