Regenerating Agricultural Landscapes With Perennial Groundcover For Intensive Crop Production, 2019 Iowa State University
Regenerating Agricultural Landscapes With Perennial Groundcover For Intensive Crop Production, Kenneth J. Moore, Robert P. Anex, Amani E. Elobeid, Shuizhang Fei, Cornelia B. Flora, A. Susana Goggi, Keri L. Jacobs, Prashant Jha, Amy L. Kaleita, Douglas L. Karlen, David A. Laird, Andrew W. Lenssen, Thomas Lubberstedt, Marshall D. Mcdaniel, D. Raj Raman, Sharon L. Weyers
Amy L. Kaleita
The Midwestern U.S. landscape is one of the most highly altered and intensively managed ecosystems in the country. The predominant crops grown are maize (Zea mays L.) and soybean [Glycine max (L.) Merr]. They are typically grown as monocrops in a simple yearly rotation or with multiple years of maize (2 to 3) followed by a single year of soybean. This system is highly productive because the crops and management systems have been well adapted to the regional growing conditions through substantial public and private investment. Furthermore, markets and supporting infrastructure are highly developed for both crops. As maize ...
Polyball: A New Adsorbent For The Efficient Removal Of Endotoxin From Biopharmaceuticals, 2019 Missouri University of Science and Technology
Polyball: A New Adsorbent For The Efficient Removal Of Endotoxin From Biopharmaceuticals, Sidharth Razdan, Jee-Ching Wang, Sutapa Barua
The presence of endotoxin, also known as lipopolysaccharides (LPS), as a side product appears to be a major drawback for the production of certain biomolecules that are essential for research, pharmaceutical, and industrial applications. In the biotechnology industry, gram-negative bacteria (e.g., Escherichia coli ) are widely used to produce recombinant products such as proteins, plasmid DNAs and vaccines. These products are contaminated with LPS, which may cause side effects when administered to animals or humans. Purification of LPS often suffers from product loss. For this reason, special attention must be paid when purifying proteins aiming a product as free as ...
Advanced Measurement Techniques For Enabling Multiphase Reactors And Flow Systems For Sustainable And Cleaner Processes, 2019 Missouri University of Science and Technology
Advanced Measurement Techniques For Enabling Multiphase Reactors And Flow Systems For Sustainable And Cleaner Processes, Muthanna H. Al-Dahhan
Muthanna H. Al-Dahhan
No abstract provided.
Development Of An Electrical Interface For A Lateral Field Excited Sensor System, 2019 The University of Maine
Development Of An Electrical Interface For A Lateral Field Excited Sensor System, Thomas J. Leighton
Electronic Theses and Dissertations
Sensor systems are utilized to provide critical information to an end user which may range from a physician in a heath care facility to a soldier in a battle field environment. The "heart" of the sensor system is the sensing platform, examples of which include semiconductor, piezoelectric and optical devices. The responses of these sensors must be converted into a format that the user can read and interpret. This conversion is achieved through integrating the sensing platform with an electrical interface.
The focus of this thesis is the development of the first electrical interface for Quartz Crystal Microbalance (QCM) sensors ...
A Review Of Biochar Properties And Their Utilization In Crop Agriculture And Livestock Production, 2019 Wroclaw University of Environmental and Life Sciences
A Review Of Biochar Properties And Their Utilization In Crop Agriculture And Livestock Production, Kajetan Kalus, Jacek A. Koziel, Sebastian Opalinski
Agricultural and Biosystems Engineering Publications
When it comes to the use of biochar in agriculture, the majority of research conducted in the last decade has focused on its application as a soil amendment and for soil remediation. This treatment improves soil quality, increases crops yields, and sequestrates atmospheric carbon to the soil. Another widely studied aspect connecting biochar with agriculture is the composting processes of various agricultural waste with the addition of biochar. Obtaining the material via the pyrolysis of agricultural waste, including animal manure, has also been investigated. However, given the remarkable properties of biochar, its application potential could be utilized in other areas ...
Machine Learning In Support Of Electric Distribution Asset Failure Prediction, 2019 Southern Methodist University
Machine Learning In Support Of Electric Distribution Asset Failure Prediction, Robert D. Flamenbaum, Thomas Pompo, Christopher Havenstein, Jade Thiemsuwan
SMU Data Science Review
In this paper, we present novel approaches to predicting as- set failure in the electric distribution system. Failures in overhead power lines and their associated equipment in particular, pose significant finan- cial and environmental threats to electric utilities. Electric device failure furthermore poses a burden on customers and can pose serious risk to life and livelihood. Working with asset data acquired from an electric utility in Southern California, and incorporating environmental and geospatial data from around the region, we applied a Random Forest methodology to predict which overhead distribution lines are most vulnerable to fail- ure. Our results provide evidence ...
Life Cycle Cost Evaluation Strategy For High Performance Control Systems Under Uncertainties, 2019 Iowa State University
Life Cycle Cost Evaluation Strategy For High Performance Control Systems Under Uncertainties, Laura Micheli, Ling Cao, Simon Laflamme, Alice Alipour
High-performance control systems (HPCSs), including active, hybrid, and semi-active control strategies, can perform over a wide excitation bandwidth and are therefore good candidates for multi-hazard mitigation. However, the number of HPCS applications in the field is very limited. This is likely due the perceived high costs of installation, maintenance, possible malfunction, and lack of tools to financially justify their implementation. Such financial justifications could be conducted through life cycle cost (LCC) analysis, but would result in a computationally demanding task due to the very large number of simulations required given the large number of uncertainties. In this paper, two sets ...
Computational Finite Element Analysis Of Adaptive Gas Turbine Stator-Rotor Flow Interactions For Future Vertical Lift Propulsion, Nikita Kozak, Luis Bravo, Muthuvel Murugan, Anindya Ghoshal, Yu Yu Khine, Yuri Bazilevs, Ming-Chen Hsu
The objective of this work is to computationally investigate the impact of an incident-tolerant rotor blade concept on gas-turbine engine performance under off-design conditions. Currently, gas-turbine engines are designed to operate at a single condition with nearly fixed rotor speeds. Operation at off-design conditions, such as during hover flight or during takeoff, causes the turbine blade flow to excessively separate introducing performance degradations, excessive noise, and critical loss of operability. To address these issues, the benefits of using an incidence-tolerant rotor blade concept is explored based on a novel concept that articulates the rotating turbine blade synchronously with the stator ...
Omnidirectional Thermal Anemometer For Low Airspeed And Multi-Point Measurement Applications, 2019 Iowa State University and Huazhong Agricultural University
Omnidirectional Thermal Anemometer For Low Airspeed And Multi-Point Measurement Applications, Yun Gao, Brett C. Ramirez, Steven J. Hoff
Current control strategies for livestock and poultry facilities need to improve their interpretation of the Thermal Environment (TE) that the animals are experiencing in order to provide an optimum TE that is uniformly distributed throughout the facility; hence, airspeed, a critical parameter influencing evaporative and convective heat exchange must be measured. An omnidirectional, constant temperature, Thermal Anemometer (TA) with ambient dry-bulb temperature (tdb) compensation was designed and developed for measuring airspeeds between 0 and 6.0 m s−1. An Arduino measured two analog voltages to determine the thermistor temperature and subsequently the power being dissipated from a near-spherical overheated ...
Principal Component Neural Networks For Modeling, Prediction, And Optimization Of Hot Mix Asphalt Dynamics Modulus, Parnian Ghasemi, Mohamad Aslani, Derrick K. Rollins, R. Christopher Williams
Derrick K Rollins, Sr.
The dynamic modulus of hot mix asphalt (HMA) is a fundamental material property that defines the stress-strain relationship based on viscoelastic principles and is a function of HMA properties, loading rate, and temperature. Because of the large number of efficacious predictors (factors) and their nonlinear interrelationships, developing predictive models for dynamic modulus can be a challenging task. In this research, results obtained from a series of laboratory tests including mixture dynamic modulus, aggregate gradation, dynamic shear rheometer (on asphalt binder), and mixture volumetric are used to create a database. The created database is used to develop a model for estimating ...
Optimizing Ensemble Weights And Hyperparameters Of Machine Learning Models For Regression Problems, 2019 Iowa State University
Optimizing Ensemble Weights And Hyperparameters Of Machine Learning Models For Regression Problems, Mohsen Shahhosseini, Guiping Hu, Hieu Pham
Aggregating multiple learners through an ensemble of models aims to make better predictions by capturing the underlying distribution more accurately. Different ensembling methods, such as bagging, boosting and stacking/blending, have been studied and adopted extensively in research and practice. While bagging and boosting intend to reduce variance and bias, respectively, blending approaches target both by finding the optimal way to combine base learners to find the best trade-off between bias and variance. In blending, ensembles are created from weighted averages of multiple base learners. In this study, a systematic approach is proposed to find the optimal weights to create ...
Multi-Objective Evolutionary Neural Network To Predict Graduation Success At The United States Military Academy, 2019 Missouri University of Science and Technology
Multi-Objective Evolutionary Neural Network To Predict Graduation Success At The United States Military Academy, Gene Lesinski, Steven Corns
This paper presents an evolutionary neural network approach to classify student graduation status based upon selected academic, demographic, and other indicators. A pareto-based, multi-objective evolutionary algorithm utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) fitness evaluation scheme simultaneously evolves connection weights and identifies the neural network topology using network complexity and classification accuracy as objective functions. A combined vector-matrix representation scheme and differential evolution recombination operators are employed. The model is trained, tested, and validated using 5100 student samples with data compiled from admissions records and institutional research databases. The inputs to the evolutionary neural network model are used to classify ...
Densenet For Anatomical Brain Segmentation, 2019 Missouri University of Science and Technology
Densenet For Anatomical Brain Segmentation, Ram Deepak Gottapu, Cihan H. Dagli
Cihan H. Dagli
Automated segmentation in brain magnetic resonance image (MRI) plays an important role in the analysis of many diseases and conditions. In this paper, we present a new architecture to perform MR image brain segmentation (MRI) into a number of classes based on type of tissue. Recent work has shown that convolutional neural networks (DenseNet) can be substantially more accurate with less number of parameters if each layer in the network is connected with every other layer in a feed forward fashion. We embrace this idea and generate new architecture that can assign each pixel/voxel in an MR image of ...
Analysis Of Parkinson's Disease Data, 2019 Missouri University of Science and Technology
Analysis Of Parkinson's Disease Data, Ram Deepak Gottapu, Cihan H. Dagli
Cihan H. Dagli
In this paper, we investigate the diagnostic data from patients suffering with Parkinson's disease (PD) and design classification/prediction model to simplify the diagnosis. The main aim of this research is to open possibilities to be able to apply deep learning algorithms to help better understand and diagnose the disease. To our knowledge, the capabilities of deep learning algorithms have not yet been completely utilized in the field of Parkinson's research and we believe that by having an in-depth understanding of data, we can create a platform to apply different algorithms to automate the Parkinson's Disease diagnosis ...
Deformation Of Multifunctional Materials At Various Time And Length Scales: A Dic-Based Study, 2019 University of South Carolina
Deformation Of Multifunctional Materials At Various Time And Length Scales: A Dic-Based Study, Behrad Koohbor
The focus in the present work is to explore and characterize the underlying deformation and failure mechanisms in multifunctional materials including woven composites and polymeric foams, using full-field measurements. Attention has been especially drawn towards the challenges associated with characterizing these materials at extreme length and time scales, and investigating the advantages of full-field measurements to resolve the existing limitations. Accordingly, the current limitations in the study of dynamic deformation response of low-impedance materials are identified. An approach based on the general stress equilibrium is presented and successfully implemented to include the concurrent effects of inertia and material compressibility into ...
Our Envirome, Spring/Summer 2019, Issue 40, 2019 University of Louisville
Our Envirome, Spring/Summer 2019, Issue 40
No abstract provided.
Plastic Pollution, Fall/Winter 2019, Issue 39.3, 2019 University of Louisville
Plastic Pollution, Fall/Winter 2019, Issue 39.3
No abstract provided.
Plastic Pollution, Fall/Winter 2019, Issue 39.2, 2019 University of Louisville
Plastic Pollution, Fall/Winter 2019, Issue 39.2
No abstract provided.
Plastic Pollution, Fall/Winter 2019, Issue 39, 2019 University of Louisville
Plastic Pollution, Fall/Winter 2019, Issue 39
No abstract provided.
Effects Of Building Scale Parameters On Pressure Equalization Capacity Of Roof Paver Systems, 2019 The University of Western Ontario
Effects Of Building Scale Parameters On Pressure Equalization Capacity Of Roof Paver Systems, Matthew Sparks
Electronic Thesis and Dissertation Repository
Roof pavers are commonly installed with a cavity beneath the paver that develops an internal suction pressure. These cavity pressures reduce the net pressure felt by a roof paver subject to uplift. Paver-scale parameter effects are well-understood, in this study, the effects of changing building-scale parameters such as height, aspect ratio, afterbody length, small and large scale roof obstructions, and paver to roof size ratio on cavity pressures are investigated. To do so pressure measurements were taken at the University of Western Ontario’s Boundary Layer Wind Tunnel Laboratory on a modular flat roof building model at four different heights ...