Texas A&M University-Kingsville: AKM Digital Repository
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Ballistic impact analysis of the segmented sandwich composite armor system
No full textThe advancement in ballistic weapons has provoked the necessity for improvement of armors to resist impact from such weapons. New lightweight armors for impact resistance have become a subject of much current research on personnel, vehicular, and equipment protection armors. Owing to the excellent impact resistance, lightweight, and relatively higher stiffness attributes of the sandwich-type armors, extensive research is still being conducted globally. The uniform, continuous nature of these armors can cause the weakening of the entire armor system after every impact, causing the entire armor system to become obsolete after a few hits. Studies done on armors found in nature is influencing the consideration of a multiple layered armor, made up of cellular top layer units pieced together and having the advantage of removing and replacing the localized damaged part without affecting adjacent tiles. To improve the impact resistance of the individual tile units and ensure more excellent layer bonding between the front ceramic layer and the backing composite layer, the mid-core section is designed in a gradient form and as a mixture of ceramic and metal material. This research delves into the design, modeling, and finite element impact analysis of the segmented sandwich composite armor system subjected to impact loading, with the design considering different parameters such as materials to be used, armor height, and armor design configuration. Initial validation studies are performed to select the ideal model that provides the best impact resistance at the least weight and with minimal fabrication requirements. Subjects such as material type, thickness, and overall model configuration were defined during the initial validation period. Once the final design is defined, finite element analysis is performed using ABAQUS CAE to observe the performance of the model and to validate the efficiency of the chosen armor. Based on the results from the material selection and thickness validation, the optimal design with the best impact resistance was noted as a 1.2mm thick rectangular segmented silicon carbide tiles, serving as the top layer that covers the three-level gradient core composed of a titanium metal honeycomb frame filled with silicon carbide inserts and finally a 2mm thick glass epoxy composite layer made from four laminas in a 0/45/90/-45-degree configuration serving as the last layer of the armor
Stability control of quadcopter
No full textIn recent years, unmanned aerial vehicles (UAVs) have received much attention due to
their ability to perform dangerous tasks, save time, and be used in various fields. Among drones,
the quadcopter with four rotors in one plane for versatile handling, hovering, vertical take-off
and landing has emerged as the most popular design. Its simple mechanical design and ease of
manufacture make it suitable for a wide range of applications including search and rescue, data
collection, surveillance, border patrol, traffic monitoring, agriculture and military operations.
However, quadcopters present control challenges because the system is highly nonlinear and
unstable. In this study, we address these challenges by developing a controller for hover
stabilization and investigating the feasibility of implementing a real-time flight control system to
improve quadcopter performance. Simulations are performed using MATLAB/Simulink to
evaluate the effectiveness of the controller in achieving the desired response. The results show
that the DMRAC controller offers promising performance and robustness for quadcopter control,
with potential implications for academia and industry in advancing the development of more
reliable and efficient UAVs. This work lays a foundation for future research to refine and
improve adaptive control methods that will ultimately help improve quadcopters and their
diverse applications
Effect of organic and inorganic nutrient sources on growth and development of Anaheim pepper
No full textGlobally, Fertilizers are important agricultural inputs that add nutrients to improve plant growth, soil health and maintain soil fertility. These three factors directly contribute to yield production. To enhance the yield of Anaheim pepper, Capsicum annum ‘Anaheim’ soil amendments are used in this study. Anaheim pepper is a member of the Capsicum spp. It is a mild variety of chili pepper with versatile uses. Alfalfa mill is used as soil amendment with the NPK ratio of 3:1:2 but in three different proportions, whereas Miracle-Gro® was used as the inorganic fertilizer with the NPK ratio of 9:4:12. A randomized complete block design (RCBD) was followed to know the effects of these two different nutrient sources on Anaheim pepper. Growth and development due to these two plant nutrient sources was compared to the control plants grown without the nutrients. Total design comprised of Five treatments: Control (C), Inorganic fertilizer (Miracle-Gro®), and three concentrations of Organic fertilizer (SA1, SA2, SA3 with 9 g, 18 g and 27 g of milled alfalfa respectively). Growth and development parameters measured to ascertain the fertilizer effects on pepper were stomatal conductance, transpiration, chlorophyll content, biomass, height, yield, and water holding capacity of the growth medium. Results of the study indicate that Anaheim pepper grown with 27 g of the soil amendment performed best in all parameters and had the highest yield
Sociodemographic predictors of health during the COVID-pandemic : an exploratory study
No full textThe emergence and transmission of COVID-19 caused a socio-economic crisis and uncontrollable consequences that led to an increase in individual psychological distress due to factors such as anxiety and depression related to the unique facets of COVID-19. With these complexities in mind, this study aims to analyze data from the Understanding America Study to explore psychological resilience and vulnerabilities across sociodemographic variables to create a detailed understanding of the mental health impacts of COVID-19. The results indicated that individuals such as women, those without employment, and African American were adversely affected at early and later stages of the pandemic. Results further showed that these negative impacts on the mental health of such individuals remained stable over time
Detecting deepfakes using convolutional neural networks
No full textA deepfake is a kind of computer-generated image or video content in which a person's image is digitally superimposed over an existing video or image. Artificial intelligence and machine learning algorithms are used to create deepfakes. Machine learning methods, especially deep learning algorithms, are used to alter the appearances of faces in images, videos and other forms of digital media. Deepfakes present a grave threat to human society. It is possible to generate fake videos and images that seem and feel so real that many viewers could believe them as real. Fake videos and images may be used to disseminate false information or even to defame famous individuals. It may also inflame the international community by means of fabricated videos and images involving sensitive political, religious, ethnic, or other international issues. Therefore, we must build a mechanism for identifying deepfakes and distinguishing them from authentic ones. In this study, we developed a convolutional neural network (CNN) model for detecting fake images and videos. The images or visual frames captured from the videos are passed into a convolutional neural network model. Then the model predicts whether the images or the frames are real or fake. We implemented the hidden layers of the CNN in such a way that it improves the detection accuracy and the training speed of the model. We tested our model on two existing datasets. Our model has a prediction accuracy of 89% on the first dataset and 92% on the second, whereas the accuracies in the previous work are 86% and 90%, respectively, on the same datasets
Stacking asynchronous Null Convention Logic (NCL) circuits for enhanced power efficiency
No full textThis thesis focuses on improving chip-level power efficiency by stacking asynchronous circuits to utilize higher supply voltages and reduce the number of voltage regulators on chip. The circuit stacking architecture places N digital circuits on top of one another, with the “ground” of each circuit serving as the “power” of the circuit below it and utilizes an overall supply voltage of N * VDD. By increasing the voltage level required for delivery, stacking N circuits results in significant power reductions via the substantially fewer number of voltage regulators required. However, there are major issues when applying this technique to synchronous circuits, as supply voltage fluctuates between stacked circuits, resulting in timing violations, which cause the circuits to malfunction. Hence, this thesis proposes to stack asynchronous NULL Convention Logic (NCL) circuits, which are highly robust to process, voltage, and temperature (PVT) variations, as they are correct-by-construction and do not rely on timing for functional correctness. Therefore, the proposed stacked NCL circuit architecture will not malfunction when the internal circuit supply voltages fluctuate, such that NCL circuit stacking will be a viable technique for significantly reducing a system’s power management unit design complexity and overall system power
Effect of conservation management on grain sorghum-cotton cropping systems in a semi arid region
No full textConservation agriculture, including no-tillage (NT) and cover cropping, has not been as widely adopted in semi-arid regions, such as South Texas, to the same extent as areas of the United States that receive greater amounts of annual precipitation. The limited research demonstrating the effects of these practices on cropping systems is one of the reasons for the low implementation of conservation practices. For the first study, two years of data was collected from a grain sorghum (Sorghum bicolor (L.) Moench)-cotton (Gossypium hirsutum L.) dryland rotation that had been under no-till management for over 30 years at the Texas A&M AgriLife Research and Extension Center at Corpus Christi. This split-split-split plot experiment had two tillage treatments (conventional tillage [CT] or no-tillage [NT]), three winter cover crop treatments (fallow, mix of three species, or mix of six species), and two sorghum residue treatments (residue after harvest shredded or left standing). Soil gravimetric water concentration, target crop yield, penetrometer resistance, cover crop canopy cover and herbage mass was evaluated. The second study was conducted at the Texas A&M AgriLife Research – Beeville Station from 2011-2018. There were four winter cover crop treatments under strip-tillage management (‘Armadillo’ burr medic [Medicago polymorpha L.], ‘Bee Black’ black medic [M. lupulina L.], ‘Devine’ little burr medic [M. minima L.], or ‘Hykon’ rose clover [Trifolium hirtum All.]) with one control treatment (winter fallow and conventional tillage). Sorghum and cotton yield, soil fertility and other parameters, cover crop herbage mass, penetrometer resistance, and water infiltration data was measured throughout the duration of the study. Although there were limited consistent statistical differences among treatments in both studies, conservation agriculture practices did not reduce row crop yields. There is clear promise in the practicality of implementing one or more conservation agricultural practices in South Texas
The Spanish and Mexican land grants of present day Cameron County
No full textFor many years the author has been interested in the history of the land of Cameron County, especially the territory surrounding Brownsville. This interest leads to the purpose of this research study, the Spanish and Mexican Land Grants of Cameron County.
The author wanted to make a detail study of each grant but realized that such a study was impossible within the limits of this thesis. A brief history of the land grants is given up to the time of the main partitioning of each grant. These main partitions occur at different times, ranging from 1856 to 1934. After the time of the main partitions, the titles became too complicated to trace with any appreciable degree of accuracy or clarity because of the lack of uniformity in the use of the Christian names and surnames; lack of official recordings of transfers of title to the lands by the heirs of the grantees presents another problem. Two Spanish land grants, the Brazos Island grant and the Padre Island grant, are not mentioned in this thesis due to the complexity of their titles.
The author would like to repeat that this thesis is not a thorough study of the Spanish and Mexican land grants on the mainland of present day Cameron County as this would be a full-time task taking many years to complete, but with this brief sketch, maybe a better understanding can be had of the history of the land in Cameron County
The impact of multiplication fluency math intervention and attendance on mathematics course performance
No full textMultiplication fluency math interventions are utilized in elementary schools, but a dearth in scholarship exists on the effects of these interventions on fifth grade math students’ performance and final grades. This scholarship gap may have an adverse effect on informing administrators and educators on best practices in helping fifth grade math students develop the mathematical skills needed to succeed in the classroom, and developing the necessary competence to translate that success, for employment and income management. My quantitative study examined factors that determine if multiplication fluency math intervention may impact fifth graders on mathematics course performance and end of semester grades. Specifically, this study observed for any statistically significant differences in relationships between attendance and final grades. Bandura’s Self-Efficacy Theory served as the theoretical framework for this study focusing on student academic assistance such as math intervention program. An archival causal-comparative, between-subjects design is appropriate for this study as observation of probable relationships between groups were observed. Archived data from a school district was utilized for this study. To obtain an adequate sample size, data across four semesters (fall 2017, spring 2018, fall 2018, spring 2019), prior to COVID-19, was aggregated for each group. A stratified randomized matching procedure was utilized to assure the treatment and control groups had equal representation. A Mann-Whitney U test was run to match mean mathematics grades between groups. Spearman’s Rho correlation analysis was used for the second research question of this study, which examined the relationship between two variables, attendance, and end of semester grades. The findings indicated that there was no evidence of a consequential relationship. The treatment group utilizing the intervention did not significantly outperform the control group. A recommendation opportunity for future studies is to track targeted intervention for increased student performance along with examining group intervention versus one-on-one intervention. Implications and recommendations for developmental education and learning assistance researchers and practitioners were discussed
Investigation of RFID-based plant growth and inventory system
No full textRadio frequency identification device technology has been in use since World War II and has developed significantly since then, with the range of applications continuously increasing each year. Only recently has the use of RFID tags and readers been tested in the field of agriculture. These tests include being used as a management aid for animal husbandry, monitoring the surrounding environment of crops, and studying wild animal behaviors.
This research work will focus on designing and building a RFID management system. This RFID system aims to monitor the growth of individual plants as well as keep the inventory of the crops using data continuously collected from sensors about their surrounding environment. The unmanned aerial vehicle or a mobile robot will be used as a data collecting tool, downloading the stored data of the RFID tags and uploading the information to the main database. Implementation of the RFID tags can be done with the UAV or mobile robot in two ways. The first option is to place the RFID tags in predetermined locations around a greenhouse or similar indoor environment and use the drone or robot to collect information. The second option is to place RFID tags in strategic locations throughout a farm field or similar outdoor environment. randomly over the area to be covered, in which case data collection will be non-uniform