Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Computer Engineering (22)
- Physical Sciences and Mathematics (20)
- Materials Science and Engineering (11)
- Civil and Environmental Engineering (10)
- Digital Communications and Networking (10)
-
- Life Sciences (9)
- Mechanical Engineering (8)
- Oceanography and Atmospheric Sciences and Meteorology (6)
- Aerospace Engineering (5)
- Computer Sciences (5)
- Earth Sciences (4)
- Electrical and Computer Engineering (4)
- Soil Science (4)
- Chemical Engineering (3)
- Medicine and Health Sciences (3)
- Metallurgy (3)
- Plant Sciences (3)
- Power and Energy (3)
- Aeronautical Vehicles (2)
- Agriculture (2)
- Biomedical Engineering and Bioengineering (2)
- Bioresource and Agricultural Engineering (2)
- Environmental Sciences (2)
- Nanoscience and Nanotechnology (2)
- Social and Behavioral Sciences (2)
- Statistical Models (2)
- Statistics and Probability (2)
- Structures and Materials (2)
- Thermodynamics (2)
- Keyword
-
- Deep learning (3)
- Camber morphing (2)
- Circulation and wave coupled model (2)
- Convolutional Neural Network (2)
- Deep Learning (2)
-
- Inertial Measurement Unit (2)
- Key management (2)
- Lattice (2)
- Mobile sink (2)
- Optimization (2)
- Storm surge (2)
- Thermodynamics (2)
- Wing morphing (2)
- Wing skin (2)
- Wireless sensor networks (2)
- 36 MATERIALS SCIENCE (1)
- ADCIRC (1)
- AOP (1)
- Abstract (1)
- Accelerometer (1)
- Active Vibration Suppression (1)
- Adhesive/dentin interface (1)
- Aerial imaging (1)
- Air-sea interaction (1)
- Air-sea momentum flux (1)
- Alloys (1)
- Analysis (1)
- Anharmonic potential (1)
- Attitude Control System (1)
- Automatic control (1)
- Publication Year
Articles 1 - 30 of 71
Full-Text Articles in Engineering
Understanding The Effects Of Wind Intensity, Forward Speed, And Wave On The Propagation Of Hurricane Harvey Surges, Madinah Shamsu, Muhammad Akbar
Understanding The Effects Of Wind Intensity, Forward Speed, And Wave On The Propagation Of Hurricane Harvey Surges, Madinah Shamsu, Muhammad Akbar
Mechanical and Manufacturing Engineering Faculty Research
Hurricane storm surges are influenced by wind intensity, forward speed, width and slope of the ocean bottom, central pressure, angle of approach, shape of coastal lines, local features, and storm size. A numerical experiment is conducted using the Advanced Circulation + Simulation and Simulating Waves Nearshore (ADCIRC + SWAN) coupled model for understanding the effects of wind intensity, forward speed, and wave on the storm surges caused by Hurricane Harvey. The ADCIRC + SWAN is used to simulate hurricane storm surges and waves. The wind fields of Hurricane Harvey were reconstructed from observed data, aided by a variety of methodologies …
Freeze-Thaw Damage Assessment Of Engineered Cementitious Composites Using The Electrochemical Impedance Spectroscopy Method, Ru Bai, Shuguang Liu, Changwang Yan, Ji Zhou, Lihe Lu, Lin Li
Freeze-Thaw Damage Assessment Of Engineered Cementitious Composites Using The Electrochemical Impedance Spectroscopy Method, Ru Bai, Shuguang Liu, Changwang Yan, Ji Zhou, Lihe Lu, Lin Li
Civil and Architectural Engineering Faculty Research
The mechanical properties of engineered cementitious composites (ECC) in service in cold regions can be significantly degraded by periodic freezing and thawing. In this work, the damage degree of freeze–thaw of ECC was systematically assessed by using the electrochemical impedance spectroscopy (EIS) technique. In addition, Nuclear Magnetic Resonance (NMR) Relaxometry measurements were also performed to obtain pore structure parameters, and the uniaxial tensile tests were also carried out to analyse the tensile performance after freeze–thaw cycles. From the acquired results, it was demonstrated that the EIS behaviour of ECC varied with the freeze–thaw cycles. The diameter of the Nyquist curve …
Mathematical And Machine Learning Approaches For Classification Of Protein Secondary Structure Elements From Cα Coordinates, Ali Sekmen, Kamal Al Nasr, Bahadir Bilgin, Ahmet Bugra Koku, Christopher Jones
Mathematical And Machine Learning Approaches For Classification Of Protein Secondary Structure Elements From Cα Coordinates, Ali Sekmen, Kamal Al Nasr, Bahadir Bilgin, Ahmet Bugra Koku, Christopher Jones
Computer Science Faculty Research
Determining Secondary Structure Elements (SSEs) for any protein is crucial as an intermediate step for experimental tertiary structure determination. SSEs are identified using popular tools such as DSSP and STRIDE. These tools use atomic information to locate hydrogen bonds to identify SSEs. When some spatial atomic details are missing, locating SSEs becomes a hinder. To address the problem, when some atomic information is missing, three approaches for classifying SSE types using Ca atoms in protein chains were developed: (1) a mathematical approach, (2) a deep learning approach, and (3) an ensemble of five machine learning models. The proposed methods were …
Editorial: Special Issue “Protein Modeling And Simulation: Selected Articles From The Computational Structural Bioinformatics Workshop 2021”, Negin Forouzesh, Kamal Ai Nasr
Editorial: Special Issue “Protein Modeling And Simulation: Selected Articles From The Computational Structural Bioinformatics Workshop 2021”, Negin Forouzesh, Kamal Ai Nasr
Computer Science Faculty Research
No abstract provided.
Designing Harvesting And Hauling Cost Models For Energy Cane Production For Biorefineries, Prabodh Illukpitiya, Firuz Yuldashev, Kabirat Nasiru
Designing Harvesting And Hauling Cost Models For Energy Cane Production For Biorefineries, Prabodh Illukpitiya, Firuz Yuldashev, Kabirat Nasiru
Agricultural and Environmental Sciences Faculty Research
The harvesting and hauling operations of bioenergy feedstock is an important area in biofuel production. Production costs can be minimized by maintaining optimal machinery units for these operations. The objective of this study is to design an optimal harvesting unit for bioenergy refinery and estimate harvesting and hauling costs of energy cane. A biorefinery with the annual capacity of processing twenty-five million imp. gallons of ethanol were considered. Given the efficiency of harvesting, a two-row soldier system was considered. Considering the year-round supply of energy cane to the refinery, the optimal machinery unit was designed, and the combined operation costs …
Electrospray Deposition Of Polyvinylidene Fluoride (Pvdf) Microparticles: Impact Of Solvents And Flow Rate, Akinwunmi Joaquim, Omari Paul, Michael Ibezim, Dewayne Johnson, April Falconer, Ying Wu, Frances Williams, Richard Mu
Electrospray Deposition Of Polyvinylidene Fluoride (Pvdf) Microparticles: Impact Of Solvents And Flow Rate, Akinwunmi Joaquim, Omari Paul, Michael Ibezim, Dewayne Johnson, April Falconer, Ying Wu, Frances Williams, Richard Mu
TIGER Institute Faculty Research
Polymeric microparticles have been shown to have great impacts in the area of drug delivery, biosensing, and tissue engineering. Electrospray technology, which provides a simple yet effective technique in the creation of microparticles, was utilized in this work. In addition, altering the electrospray experimental parameters such as applied voltage, flow rate, collector distance, solvents, and the polymer-solvent mixtures can result in differences in the size and morphology of the produced microparticles. The effects of the flow rate at (0.15, 0.3, 0.45, 0.6, 0.8, and 1 mL/h) and N, N-Dimethylformamide (DMF)/acetone solvent ratios (20:80, 40:60, 60:40, 80:20, 100:0 v/v) in the …
Influence Of Rainfall-Induced Erosion On The Stability Of Sandy Slopes Treated By Micp, Shihui Liu, Kang Du, Kejun Wen, Catherine Armwood-Gordon, Lin Li
Influence Of Rainfall-Induced Erosion On The Stability Of Sandy Slopes Treated By Micp, Shihui Liu, Kang Du, Kejun Wen, Catherine Armwood-Gordon, Lin Li
Civil and Architectural Engineering Faculty Research
As an environmentally friendly technology, microbially induced calcite precipitation (MICP) is widely used to improve the engineering properties of soil. The goal of this study was to investigate the effect of rainfall-induced erosion on the stability of sandy slopes which were treated by MICP technology. The observation of the erosion pattern of low concentration (0.25 M Ca) and high concentration (0.5 M Ca) of MICP-treated slopes, the mechanical behaviors of MICP-treated and cement-treated samples, and the effects of rainfall-induced erosion on the roughness of 0.5 M Ca MICP-treated and 10% cement-treated slope were studied through visual observation, unconfined compressive tests, …
Dynamics And Simulations Of Discretized Caputo-Conformable Fractional-Order Lotka–Volterra Models, Yousef Feras, Semmar Billel, Al Nasr Kamal
Dynamics And Simulations Of Discretized Caputo-Conformable Fractional-Order Lotka–Volterra Models, Yousef Feras, Semmar Billel, Al Nasr Kamal
Computer Science Faculty Research
In this article, a prey–predator system is considered in Caputo-conformable fractional-order derivatives. First, a discretization process, making use of the piecewise-constant approximation, is performed to secure discrete-time versions of the two fractional-order systems. Local dynamic behaviors of the two discretized fractional-order systems are investigated. Numerical simulations are executed to assert the outcome of the current work. Finally, a discussion is conducted to compare the impacts of the Caputo and conformable fractional derivatives on the discretized model.
Magnetic Nanoparticles Enhanced Surface Plasmon Resonance Biosensor For Rapid Detection Of Salmonella Typhimurium In Romaine Lettuce, Devendra Bhandari, Fur-Chi Chen, Roger C. Bridgman
Magnetic Nanoparticles Enhanced Surface Plasmon Resonance Biosensor For Rapid Detection Of Salmonella Typhimurium In Romaine Lettuce, Devendra Bhandari, Fur-Chi Chen, Roger C. Bridgman
Human Sciences Faculty Research
Salmonella is one of the major foodborne pathogens responsible for many cases of illnesses, hospitalizations and deaths worldwide. Although different methods are available to timely detect Salmonella in foods, surface plasmon resonance (SPR) has the benefit of real-time detection with a high sensitivity and specificity. The purpose of this study was to develop an SPR method in conjunction with magnetic nanoparticles (MNPs) for the rapid detection of Salmonella Typhimurium. The assay utilizes a pair of well-characterized, flagellin-specific monoclonal antibodies; one is immobilized on the sensor surface and the other is coupled to the MNPs. Samples of romaine lettuce contaminated with …
Incommensurate Conformable-Type Three-Dimensional Lotka–Volterramodel: Discretization, Stability, And Bifurcation, Feras Yousef, Billel Semmar, Kamal Al Nasr
Incommensurate Conformable-Type Three-Dimensional Lotka–Volterramodel: Discretization, Stability, And Bifurcation, Feras Yousef, Billel Semmar, Kamal Al Nasr
Computer Science Faculty Research
The classic Lotka–Volterra model is a two-dimensional system of differential equations used to model population dynamics among two-species: a predator and its prey. In this article, we consider a modified three-dimensional fractional-order Lotka–Volterra system that models population dynamics among three-species: a predator, an omnivore and their mutual prey. Biologically speaking, population models with a discrete and continuous structure often provide richer dynamics than either discrete or continuous models, so we first discretize the model while keeping one time-continuous dependent variable in each equation. Then, we analyze the stability and bifurcation near the equilibria. The results demonstrated that the dynamic behaviors …
Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry
Ggnb: Graph-Based Gaussian Naive Bayes Intrusion Detection System For Can Bus, Riadul Islam, Maloy K. Devnath, Manar D. Samad, Syed Md Jaffrey Al Kadry
Computer Science Faculty Research
The national highway traffic safety administration (NHTSA) identified cybersecurity of the automobile systems are more critical than the security of other information systems. Researchers already demonstrated remote attacks on critical vehicular electronic control units (ECUs) using controller area network (CAN). Besides, existing intrusion detection systems (IDSs) often propose to tackle a specific type of attack, which may leave a system vulnerable to numerous other types of attacks. A generalizable IDS that can identify a wide range of attacks within the shortest possible time has more practical value than attack-specific IDSs, which is not a trivial task to accomplish. In this …
Robust Feature Space Separation For Deep Convolutional Neural Network Training, Ali Sekmen, Mustafa Parlaktuna, Ayad Abdul-Malek, Erdem Erdemir, Ahmet Bugra Koku
Robust Feature Space Separation For Deep Convolutional Neural Network Training, Ali Sekmen, Mustafa Parlaktuna, Ayad Abdul-Malek, Erdem Erdemir, Ahmet Bugra Koku
Computer Science Faculty Research
This paper introduces two deep convolutional neural network training techniques that lead to more robust feature subspace separation in comparison to traditional training. Assume that dataset has M labels. The first method creates M deep convolutional neural networks called {DCNNi}M i=1 . Each of the networks DCNNi is composed of a convolutional neural network ( CNNi ) and a fully connected neural network ( FCNNi ). In training, a set of projection matrices are created and adaptively updated as representations for feature subspaces {S i}M i=1 . A rejection value is computed for each training based on its projections on …
Automatic Identification And Monitoring Of Plant Diseases Using Unmanned Aerial Vehicles: A Review, Krishna Neupane, Fulya Baysal-Gurel
Automatic Identification And Monitoring Of Plant Diseases Using Unmanned Aerial Vehicles: A Review, Krishna Neupane, Fulya Baysal-Gurel
Agricultural and Environmental Sciences Faculty Research
Disease diagnosis is one of the major tasks for increasing food production in agriculture. Although precision agriculture (PA) takes less time and provides a more precise application of agricultural activities, the detection of disease using an Unmanned Aerial System (UAS) is a challenging task. Several Unmanned Aerial Vehicles (UAVs) and sensors have been used for this purpose. The UAVs’ platforms and their peripherals have their own limitations in accurately diagnosing plant diseases. Several types of image processing software are available for vignetting and orthorectification. The training and validation of datasets are important characteristics of data analysis. Currently, different algorithms and …
High-Throughput Design Of High-Performance Lightweight High-Entropy Alloys, Rui Feng, Chuan Zhang, Michael C. Gao, Zongrui Pei, Fan Zhang, Yan Chen, Dong Ma, Ke An, Jonathan D. Poplawsky, Lizhi Ouyang, Yang Ren, Jeffrey A. Hawk, Michael Widom, Peter K. Liaw
High-Throughput Design Of High-Performance Lightweight High-Entropy Alloys, Rui Feng, Chuan Zhang, Michael C. Gao, Zongrui Pei, Fan Zhang, Yan Chen, Dong Ma, Ke An, Jonathan D. Poplawsky, Lizhi Ouyang, Yang Ren, Jeffrey A. Hawk, Michael Widom, Peter K. Liaw
Mathematical Sciences Faculty Research
Developing affordable and light high-temperature materials alternative to Ni-base superalloys has significantly increased the efforts in designing advanced ferritic superalloys. However, currently developed ferritic superalloys still exhibit low high-temperature strengths, which limits their usage. Here we use a CALPHAD-based high-throughput computational method to design light, strong, and low-cost high-entropy alloys for elevated-temperature applications. Through the high-throughput screening, precipitation-strengthened lightweight high-entropy alloys are discovered from thousands of initial compositions, which exhibit enhanced strengths compared to other counterparts at room and elevated temperatures. The experimental and theoretical understanding of both successful and failed cases in their strengthening mechanisms and order-disorder transitions further …
Can Agricultural Management Induced Changes In Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?, Jonathan Sanderman, Kathleen Savage, Shree R.S. Dangal, Gabriel Duran, Charlotte Rivard, Michel A. Cavigelli, Hero T. Gollany, Virginia L. Jin, Mark A. Liebig, Emmanuel Chiwo Omondi, Yichao Rui, Catherine Stewart
Can Agricultural Management Induced Changes In Soil Organic Carbon Be Detected Using Mid-Infrared Spectroscopy?, Jonathan Sanderman, Kathleen Savage, Shree R.S. Dangal, Gabriel Duran, Charlotte Rivard, Michel A. Cavigelli, Hero T. Gollany, Virginia L. Jin, Mark A. Liebig, Emmanuel Chiwo Omondi, Yichao Rui, Catherine Stewart
Agricultural and Environmental Sciences Faculty Research
A major limitation to building credible soil carbon sequestration programs is the cost of measuring soil carbon change. Diffuse reflectance spectroscopy (DRS) is considered a viable low-cost alternative to traditional laboratory analysis of soil organic carbon (SOC). While numerous studies have shown that DRS can produce accurate and precise estimates of SOC across landscapes, whether DRS can detect subtle management induced changes in SOC at a given site has not been resolved. Here, we leverage archived soil samples from seven long-term research trials in the U.S. to test this question using mid infrared (MIR) spectroscopy coupled with the USDA-NRCS Kellogg …
Manganese Oxide Carbon-Based Nanocomposite In Energy Storage Applications, Mulugeta Wayu
Manganese Oxide Carbon-Based Nanocomposite In Energy Storage Applications, Mulugeta Wayu
Chemistry Faculty Research
Global increasing demand in the need of energy leads to the development of non-conventional, high power energy sources. Supercapacitors (SCs) are one of the typical non-conventional energy storage devices which are based on the principle of electrochemical energy conversion. SCs are promising energy storage devices for better future energy technology. Increasing progress has been made in the development of applied and fundamental aspects of SCs. Manganese oxide electrode materials have been well studied; however, their capacitive performance is still inadequate for practical applications. Recent research is mainly focused on enhancing manganese oxide capacitive performance through the incorporation of electrically conductive …
Effect Of Varying Wind Intensity, Forward Speed, And Surface Pressure On Storm Surges Of Hurricane Ritaeffect Of Varying Wind Intensity, Forward Speed, And Surface Pressure On Storm Surges Of Hurricane Rita, Abram Musinguzi, Muhammad K. Akbar
Effect Of Varying Wind Intensity, Forward Speed, And Surface Pressure On Storm Surges Of Hurricane Ritaeffect Of Varying Wind Intensity, Forward Speed, And Surface Pressure On Storm Surges Of Hurricane Rita, Abram Musinguzi, Muhammad K. Akbar
Mechanical and Manufacturing Engineering Faculty Research
Hurricane storm surges are influenced by several factors, including wind intensity, surface pressure, forward speed, size, angle of approach, ocean bottom depth and slope, shape and geographical features of the coastline. The relative influence of each factor may be amplified or abated by other factors that are acting at the time of the hurricane’s approach to the land. To understand the individual and combined influence of wind intensity, surface pressure and forward speed, a numerical experiment is conducted using Advanced CIRCulation + Simulating Waves Nearshore (ADCIRC + SWAN) by performing hindcasts of Hurricane Rita storm surges. The wind field generated …
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 …
A Deep Learning Approach For Final Grasping State Determination From Motion Trajectory Of A Prosthetic Hand, Cihan Uyanik, Syed F. Hussaini, Erdem Erdemir, Erkan Kaplanoglu, Ali Sekmen
A Deep Learning Approach For Final Grasping State Determination From Motion Trajectory Of A Prosthetic Hand, Cihan Uyanik, Syed F. Hussaini, Erdem Erdemir, Erkan Kaplanoglu, Ali Sekmen
Computer Science Faculty Research
Deep Learning has been gaining popularity due to its numerous implementations and continuous growing capabilities, including the prosthetics industry which has trend of evaluation towards the smart operational decision. The aim of this study is to develop a reliable decision-making system for prosthetic hands which is responsible to grasp or point an object located in the interaction area. In order to achieve this goal, we have exploited the measurements taken from a low-cost inertial measurement unit (IMU) and proposed a convolutional neural network-based decision-making system, which utilizes 9 distinct measurement variables as input, 3 axis accelerometer, 3 axis gyroscope and …
A Deep Learning Approach For Motion Segment Estimation For Pipe Leak Detection Robot, Cihan Uyanik, Erdem Erdemir, Erkan Kaplanoglu, Ali Sekmen
A Deep Learning Approach For Motion Segment Estimation For Pipe Leak Detection Robot, Cihan Uyanik, Erdem Erdemir, Erkan Kaplanoglu, Ali Sekmen
Computer Science Faculty Research
The trajectory motion of a robot can be a valuable information to estimate the localization of an autonomous robotic system, especially in a very dynamic but structurally-known environments like water pipes where the sensor readings are not reliable. The main focus of this research is to estimate the location of meso-scale robots using a deep-learning-based motion trajectory segment detection system from recorded sensory measurements while the robot travels through a pipe system. The idea is based on the classification of the motion measurements, acquired by inertial measurement unit (IMU), by exploiting the deep learning approach. Proposed idea and utilized methodology …
Unmanned Aircraft System (Uas) Technology And Applications In Agriculture, Samuel C. Hassler, Fulya Baysal-Gurel
Unmanned Aircraft System (Uas) Technology And Applications In Agriculture, Samuel C. Hassler, Fulya Baysal-Gurel
Agricultural and Environmental Sciences Faculty Research
Numerous sensors have been developed over time for precision agriculture; though, only recently have these sensors been incorporated into the new realm of unmanned aircraft systems (UAS). This UAS technology has allowed for a more integrated and optimized approach to various farming tasks such as field mapping, plant stress detection, biomass estimation, weed management, inventory counting, and chemical spraying, among others. These systems can be highly specialized depending on the particular goals of the researcher or farmer, yet many aspects of UAS are similar. All systems require an underlying platform—or unmanned aerial vehicle (UAV)—and one or more peripherals and sensing …