28360 research outputs found
Sort by
Design and Development of an Automatic Steering System for Agricultural Towed Implements
Get PDFWhile an auto steered tractor can improve the overall accuracy and efficiency of an operation, for operations that involve towing an implement, a significant portion of the efficiency reduction comes from uncontrolled motions of the towed implement. Therefore, there is a crucial need to study auto steering system for towed implement as well. In this study different requirements of an auto steering system for a towed implement were developed and studied. In this study the guiding performance of two local positioning sensors (Tactile and Ultrasonic sensors) under similar conditions were studied for reading different trajectories at different traveling speed. Furthermore, a fuzzy logic control algorithm was developed to continually generate correction steering signals and keep the tractor and towed implement within a certain boundary of the reference trajectory. Finally, the designed controller was implemented in a hardware-in-loop (HIL) system to analyze the performance of the controller in real world conditions.
The result of this study showed that although the local guidance sensors could locate the tractor or towed implement positions with respect to plant rows accurately, limitations to the performance of sensors were also observed in certain conditions. Sensors were prone to various noises and digital filters were required to apply to collected data. Data analysis showed that at lower speeds (less than 1.79 m/s) the accuracy of sensors was ?2 cm or better. The fuzzy logic controller improved the trajectory tracking accuracy at slow speeds (1-5 m/s) for following non-complex trajectories while no major improvements were achieved for complex trajectories at these speeds. Therefore, the controller had an acceptable accuracy following straight trajectory with negligible deviations at slow speeds. Moreover, experimental results showed that the hydraulic cylinder followed the controller signals with sufficient accuracy. During the experiment the angular displacements remained in the range of ?10? and never hit the constraint of maximum achievable angle, which was ?30?. The satisfactory results showed that the designed automatic steering control system has a good tracking performance with a fast response, thus meeting the navigation control requirement of agricultural equipment to a certain extent
Pattern Recognition and Quantifying Associations Within Entities of Data Driven Systems for Improving Model Interpretability
Get PDFDiscovering associations among entities of a system plays an important role in data science. The majority of the data science related problems have become heavily dependent on Machine Learning (ML) since the rise of computation power. However, the majority of the machine learning approaches rely on improving the performance of the algorithm by optimizing an objective function, at the cost of compromising the interpretability of the models. A new branch of machine learning focuses on model interpretability by explaining the models in various ways. The foundation of model interpretability is built on extracting patterns from the behavior of the models and the related entities. Gradually, Machine learning has spread its wing to almost every industry. This dissertation focuses on the data science application to three such domains. Firstly, assisting environmental sustainability by identifying patterns within its components. Machine learning techniques play an important role here in many ways. Discovering associations between environmental components and agriculture is one such topic. Secondly, improving the robustness of Artificial Intelligence applications on embedded systems. AI has reached our day-to-day life through embedded systems. The technical advancement of embedded systems made it possible to accommodate ML. However, embedded systems are susceptible to various types of errors, hence there is a huge scope of recovery systems for ML models deployed on embedded systems. Third, bringing the user communities of the entertainment systems across the globe together. Online streaming of entertainment has already leveraged ML to provide educated recommendations to its users. However, entertainment content can sometimes be isolated due to demographic barriers. ML can identify the hidden aspects of these contents which would not be possible otherwise. In subsequent paragraphs, various challenges concerning these topics will be introduced and corresponding solutions will be followed that can address those challenges
Tracking Body Dissatisfaction and Body Ideals of Ethnically Diverse College Women
Get PDFGlobally, women are exposed to society-created, unachievable body ideals, which change over time and are subject to influence by other, typically Western, societies. Socializing agents such as family members, peers, and media often reinforce these ideals through pressure, which can then lead to body dissatisfaction. Research on body ideals and body dissatisfaction disproportionately focuses on White women within the United States. While this group is important to continue to examine, there is a need to include women from outside of the United States and from Non-Western societies. Thus, this study examined college women?s perceptions of body ideals within and outside of the United States, where they learned these ideals, changes in body dissatisfaction over time, and how pressure to be thin from socializing agents was associated with body dissatisfaction in women from both Western and Non-Western societies. College women born and raised within the United States (domestic) and women from outside of the United States but now living in the United States to attend college (international) completed a series of online surveys. First, open-ended questions were used to gather participant perceptions of body ideals. Results indicated that three main body ideals existed within and outside of the United States, with a thin, with accentuated features ideal being the most prominent within the United States, and a thin-ideal being the most common among Non-Western women. Further, nearly all participants stated that the media was responsible for teaching them about body ideals. Second, validated measures were used to collect data about pressure from socializing agents and body dissatisfaction among Western and Non-Western (specifically Asian) women. Body dissatisfaction at baseline and trajectory of body dissatisfaction did not significantly differ between the two groups. However, while greater pressure all socializing agents were associated with higher body dissatisfaction in the predominantly White Western group, for the Asian group, only pressure from family members was significantly associated with increased body dissatisfaction. The results of this study can be used to inform and create broader, culturally appropriate educational body image programming with the goal of preventing or intervening to reduce body dissatisfaction in college women
Characterization of North Dakota Hard Red Spring Wheat for Stem and Stripe Rust Resistance
Get PDFPuccinia graminis f. sp. tritici (Pgt) and Puccinia striiformis f. sp. tritici (Pst) are causal agents of devastating wheat stem and stripe rust diseases, respectively. Both diseases sporadically occur in North Dakota (ND), and stripe rust incidence has been increasing in the Midwest of United States over the last decade. Complete information of rust resistance in ND hard red spring wheat (HRSW) germplasm is not well-established. This study focused on the phenotypic characterization of ND HRSW germplasm for stripe and stem rust resistance and the identification of existing and novel rust resistance genomic loci in this population through genome-wide association study (GWAS). The GWAS has identified several marker-trait associations (MTAs) for both all-stage and adult plant resistance for each rust disease. This information will support the deployment of these resistant loci in wheat varieties by the NDSU HRSW breeding program
The Effects of Humeral Retroversion on Range of Motion in the Throwing Athlete
Get PDFThe purpose of this study was to examine the relationship between shoulder rotational range of motion once accounting for humeral retroversion (HR) and the Functional Arm Scale for Throwers (FAST). The following research questions guided the study: Is there a correlation between shoulder rotational range of motion (ROM) after HR is accounted for, and the total FAST pitcher?s subscale score? What specific questions on the FAST pitcher?s subscale can help sports medicine professionals predict the chance of rotational deficiencies in the throwing shoulder? Are pitchers with more years of college baseball more likely to see changes in total rotational ROM than pitchers with less years of college baseball? No relationship was found between rotational ROM and the FAST score or rotational ROM and total number of years playing college baseball. The findings suggest further research that needs to be performed on patient reported outcomes specific to changes in rotational ROM
Recovery of Physical and Biological Soil Properties and Vegetation on Reclaimed Oil Well Pads in Western North Dakota
Get PDFSince 2000, the oil industry in North Dakota has grown to become the fifth largest oil producing and the second largest oil production and reserve state in the country. This increase in growth and activity has contributed to large amounts of ecological disturbance and degradation in western North Dakota. Oil companies are required to complete reclamations on disturbed and degraded lands once well pad activity ceases at a site. It is unclear how successful these reclamations are though as studies have found that significant ecological recovery can take multiple decades. This study assessed the recovery of soil properties and vegetation establishment on reclamations varying in age up to 37 years. It was determined that, at least in western North Dakota, soil microbes in reclaimed areas reflect those of undisturbed areas more over time and that time does not appear to have much effect on vegetation presence in reclaimed areas
Comparison and Standardization of Wheat Pre-Harvest Sprouting Screening Methods, Preliminary Screening of Genomic Panel Lines
Get PDFPreharvest sprouting (PHS) in spring wheat (Triticum aestivum, L.) is a significant problem in the United States, with many ways to evaluate it. When unharvested wheat begins to sprout, the grain begins to germinate reducing functional quality. Screening methods for PHS can range from in-situ spike misting to seed wetting. Each method has multiple published protocols, each with differing results. This experiment sought to compare two common screening methods, in-situ spike misting and seed wetting, from both field grown, and greenhouse grown seed sources. The experiment was comprised of 528 wheat lines in 2020 and a 50-genotype subset in 2021. Results from the correlation of methods analysis yielded a high correlation (r=0.74). Results from the correlation of sourced material analysis yielded a high correlation also (r=0.87). A preliminary genome wide association study identified a significant QTL present on chromosome 4A. This work will serve as a foundation for future studies
Data-Science-Driven Refinements of Stochastic Models With Applications in Oil Data, Short Maturity Asian Options, and Yield Prediction
Get PDFIn this dissertation, at first, we present a refined Barndorff-Nielsen and Shephard (BN-S) model which is implemented to find an optimal hedging strategy for commodity markets. The refinement of the BN-S model is obtained with various machine and deep learning algorithms. The refinement leads to the extraction of a deterministic parameter from the empirical data set. The problem is transformed to an appropriate classification problem with a couple of different approaches- the volatility approach and the duration approach. The analysis is implemented to the Bakken crude oil data and the aforementioned deterministic parameter is obtained for a wide range of data sets. With the implementation of this parameter in the refined model, the resulting model performs much better than the classical BN-S model.
After that, in this dissertation we propose a general mathematical model for analyzing yield data. The data analyzed in this dissertation come from a characteristic corn field in the upper midwestern United States. We derive expressions for statistical moments from the underlying stochastic model. Consequently, we illustrate how a particular feature variable contributes to the statistical moments (and in effect, the characteristic function) of the target variable (i.e., yield). We also analyze the data with neural network techniques and provide two methods of data analysis. This mathematical model and neural network-based data analysis allow for better understanding of the variability within the data set, which is useful to farm managers attempting to make current and future decisions using the yield data. Lenders and risk management consultants may benefit from the insights of this mathematical model and neural network-based data analysis regarding yield expectations.
In the last segment of this dissertation, we provide important mathematical results obtained from the study of short maturity asymptotics for Asian options with continuous time averaging. We assume that the underlying asset follows a local volatility model associated with a L?vy subordinator. In our work, the asymptotics for out-of-the-money, in-the-money, and at-the-money cases are derived for fixed strike Asian options
Understanding the Role of Rage in Cell Adhesion
Get PDFThe Receptor for Advanced Glycation Endproducts (RAGE) is a mammalian specific cell surface receptor. RAGE consists of three extracellular domains (V, C1, and C2), a transmembrane domain, and an intracellular cytoplasmic tail. RAGE has a significant role in human pathogenesis, including neurodegenerative diseases, diabetic complications, and certain cancers. Deregulation of cell adhesion is one of the contributing cellular events common in many of the above listed human pathologies and might be mediated via RAGE signaling. In our study, we aimed to understand the role of RAGE in cell adhesion and to define the importance of the different domains of RAGE in mediating this phenomenon.
For this study, a protein engineering approach was used to express full-length RAGE (FL-RAGE) and a panel of domain deletion constructs ((?V-, ?C1-, ?C2-, DN-, TmCyto-) RAGE) of the receptor. The necessary expression constructs were assembled in the pcDNA3 vector, and the RAGE variants were expressed in HEK293 cells. The expression and cellular localization of RAGE in HEK 293 cells were analyzed using Western blot, immunofluorescence microscopy, and flow cytometry techniques. Our results show that the cytoplasmic domain of RAGE was sufficient to contribute to cell adhesion to the extracellular matrix to a level comparable to that of the FL-RAGE expressing cells.
The current mechanistic model suggests that RAGE signaling is initiated by ligand binding to the extracellular region, followed by conformational changes in the intracellular domain. Subsequently, this conformation change leads to the recruitment of RAGE-interacting proteins on the intracellular side of the plasma membrane. However, in this thesis, we present evidence of an alternative mechanism of RAGE signaling possibly involving the translocation of RAGE into the nucleus. The results from our study suggest an alternative model for RAGE signaling and will help to better understand RAGE signaling in pathophysiological conditions. Our results could contribute to the development of new small molecule drugs targeting intracellular RAGE or the intracellular RAGE domain as a novel approach for inhibiting RAGE signaling.
Using UAS Imagery and Computer Vision to Support Site-Specific Weed Control in Corn
Get PDFCurrently, a blanket application of herbicides across the field without considering the spatial distribution of weeds is the most used method to control weeds in corn. Unmanned aerial systems (UASs) can provide high spatial resolution imagery, which can be used to map weeds across a field with a high spatial and temporal resolution during early growing season to support site-specific weed control (SSWC). The proposed approach assumes that plants growing outside the corn rows are weeds that need to be controlled. For that, we are proposing the use of ?Pixel Intensity Projection? (PIP) algorithm for the detection of corn rows on UAS imagery. After being identified, corn rows were then removed from the imagery and the remaining vegetation fraction was assumed to be weeds. A weed prescription map based on the remaining vegetation fraction was created and implemented through a commercial sprayer field weed control