Texas A&M University-Kingsville: AKM Digital Repository
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Improved sentence based image search deep learning method
No full textThe success of social networking websites has imposed a challenge to handle the amount of data that is poured in every day. Most of those data are either in the form of image or in the form of videos. In this thesis, we present a new way to handle such a huge amount of pixel based data with the help of Advanced Machine Learning Method. Unlike traditional way of image retrieval which is either of two, Tag Based Image Retrieval (TBIR) which leverages Meta- data and text associated near image or Context Based Image Retrieval (CBIR) which finds the difference between contexts of two images. The proposed method uses machine learning to categorize images based on its content at storage stage and give a way to retrieve those images by giving more emphasis on content matching with natural language query
The impact of imagine math on student progress in STAAR math
No full textThe issue that this study addressed is the evaluation of the impact of Imagine Math© upon the closure of learning gaps of English Learners and students of diverse racial backgrounds in mathematics and Algebra. Specifically, the intent of the research was to determine the impact of the adaptive learning program, Imagine Math©, upon student achievement on STAAR Math in grades 3-8 and Algebra (8th and/or 9th). This quantitative approach employed a correlational design, analyzing the impact of Imagine Math© on student achievement over a five-year period, in a South-Central Texas public school district. This research encompassed the analysis of student achievement levels on standardized testing in mathematics, comparing males to females, ethnic/race differences, and English Learners in comparison to non-English learners. Findings demonstrated the use of the Imagine Math© seemed to help close student achievement gaps in mathematics, in the linear regression. While no major statistically significant differences seemed evident when comparing males to females, some statistically significant differences seemed to emerge when comparing mathematics scale scores between English Learners to non-English learners. Similarly, some statistically significant differences between different ethnic/races seemed to emerge as well. Specifically, the emergence of these differences seemed to occur when comparing White students to Black and Hispanic students and when comparing Asian students to White students, nevertheless these differences were not always present nor consistent. When one considers the implications of the findings, it is evident that the choice of using Imagine Math© seems to be a viable one, if the intent to close student achievement gaps in mathematics is the goal. In a nutshell, these research findings can be used to help district and campus leaders make informed choices on the use of digital programs to support students. In addition, trained teachers can in turn use these programs to monitor progress and help students master mathematical concepts
Evaluation of alternative reductants for stimulating uranium reduction and immobilization
No full textIn this study, sodium dithionite (DI) and calcium polysulfide (CPS) were added to microcosms and continuous-flow columns, using groundwater and sediments from a mining site to stimulate uranium immobilization.
The microcosm study evaluated two factors on uranium and sulfate removal: reductant (none, DI, and CPS) and buffer (none, carbonate, and phosphate). DI and CPS were selected to compare weak and strong reductants, respectively. Carbonate and phosphate were selected to compare buffers that form soluble and insoluble complexes, respectively. The following results were observed:
• DI decreased soluble uranium (likely due to reduction from U(VI) to insoluble U(IV)), but not sulfate (likely because sulfate reduction coupled to DI oxidation is endergonic). Addition of DI increased sulfate (likely due to oxidation of DI coupled to iron reduction).
• CPS decreased soluble uranium, but – unlike DI – also decreased sulfate (likely because sulfate reduction coupled to sulfide oxidation is exergonic). Sulfate reduction was obscured by oxidation of sulfide to sulfate via iron reduction.
•Carbonate and phosphate increased and decreased, respectively, soluble uranium (likelydue to uranyl-carbonate and uranyl-phosphate complex formation, respectively).
In the column studies, groundwater was pumped through columns packed with post-leached aquifer sediments and amended with no reductant, DI or CPS, respectively, for 60 days. The following results were observed:
•The DI-amended column did not achieve uranium removal. Significant increases insoluble iron and sulfate, however, were observed (likely due to reduction of iron coupledto DI oxidation).
•The CPS-amended column achieved significant uranium removal (>99%). Significantsulfate removal (72-86%) was observed between the 2nd and 4th pore volumes, followedby 15-35% removal for 10 pore volumes.
•ORP in the CPS-amended column decreased significantly (-480 mV versus -200 mV inthe control), but not in the DI-amended column.
These results supported hypotheses that: 1) both DI and CPS could stimulate reduction and immobilization of uranium; 2) CPS could stimulate sulfate reduction, but DI could not; and 3)carbonate and phosphate could increase and decrease, respectively, uranium solubility. Thecolumn study results, however, suggested that dithionite may not be drive ORP low enough to stimulate uranium reduction under continuous flow conditions.
Finally, a one-dimensional transport model, implemented using the PHREEQC and PhreePlot software packages, was used to fit the column data by adjusting dispersivity, sorption and mineral phases present. The modeling results showed that selection of different oxidized iron mineral phases significantly affected the model fit with the experimental column data
Teaching Corpus Christi beginners through first grades to read with a critical analysis of objectives, materials, methods, and procedure in the light of modern theory and practice
No full textSince there has never been a detailed study made of the teaching of beginners how to read in the Corpus Christi Elementary Schools, the purpose of this thesis is to present the methods and procedure used by the teachers of these grades.
The author has written a preview of the procedure used in the Corpus Christi Elementary Schools for teaching beginners to read. Included in this paper are the reading objectives compared with some from outstanding authors on primary reading. In connection with this, the writer has given a critical analysis of the materials-used in the pre-primer Primer, and high first grade. The writer has made this study in order that she may better prepare herself to teach beginners to read
History of the Christian Church (Disciples) in twelve southern counties of Texas known as District Six
No full textThe purpose of this study has been to glean from such sources as are available the history of the Christian Church as it pertains to the territory from. Corpus Christi south and to preserve that information for those who might want such materials in the years that are to come. The author knows every church that he has written about. He knows the pastors on the fields at the time of this writing. He has served in two of the churches of this district during the last five years just prior to this study
Relationship of intensity of illumination to performance of a simple visual task
No full textProblems of illumination in the school room and in other situations where visual tasks, particularly those involving learning, are performed, have interested the author for some time. This interest has given rise to the investigation which is here reported. Though one study can make but small contribution to the fund of knowledge necessary to the establishment of principles of lighting science, yet only as 1llumination science is builded upon adequate factual bases will a time arrive when optimum lighting pre9crlptions for particular visual tasks can be made.
In this report the construction and use of six forms of a cancellation test are described, with suggestions for possible educational applications. Experimental study of the relationship of intensity of illumination to performance on the six forms of the cancellation test, using eighty-three subjects, is described, and results are reported
Understanding the mechanical behavior of polymers using molecular dynamics simulation
No full textAtomistic simulations, also known as molecular dynamics simulations, can give significant insights on the relationships between structure and properties, which can be used for the creation of new polymer-based materials. Molecular dynamics simulation is mainly used to analyze atomic and molecular movements within a system. This simulation mimics real life atomic and molecular interactions by assuming a given potential energy function. This energy function enables calculating the force experienced by any atom with respect to the position of other atoms. The trajectories of these atoms are determined using Newton’s equations of motion. The values obtained from the atomic force and motion can be used to estimate the mechanical properties of the system. In this study, mechanical responses of polymers under various loading scenarios were captured using molecular dynamics simulation for in-depth understanding of the structure properties relationships. A classical molecular dynamics simulation software, large-scale atomic/molecular massively parallel simulator (LAMMPS) was used for the modeling purpose. The MD simulation framework used in the study was validated using the experimental data obtained from the literature. According to the MD simulation findings, Young’s modulus and yield strength of polyethylene depend on the molecular weight. Furthermore, the simulation was able to capture the temperature- and pressure-dependent mechanical responses of polyethylene. The results show a general increase in Young’s modulus and yield strength with increase in molecular weight under various temperature- and pressure-dependent tensile loading scenarios
Design and analysis of tilt rotor unmanned aerial vehicle (UAV) for optimal flight endurance and payload lift capacity
No full textUnmanned Aerial Vehicles (UAVs) are used on a wide range of missions depending on the situation and requirement for that task that has to be completed. UAVs are nothing but aircraft which fly without the physical presence of the pilot. They can be controlled from the ground station and are capable to perform autonomous flights. Some key factors which affect the flights of the UAV are the take-off distance, total time of flight, payload lifting capacity thrust to weight ratio, aerodynamic and structural force effects, and others. Helicopters are used in the areas where the take-off space is less and places where there is a need to hover around a location. Mostly in the case of military applications during surveillance and rescue operations. Airplanes are used to cover large distances for commercial and cargo transportation. Combining the concept of vertical take-off from helicopters and the cruising ability of airplanes, tilt rotors are one of the best ways to satisfy both conditions. There is no doubt that it has one of the most complex stability parameters as it undergoes the transition state in between helicopter mode and airplane mode. Hence the present work concentrates on the design and analysis of tilt-rotor UAV which helps in changing the values of parameters for optimal flight endurance and try to increase the payload lifting capacity of tilt rotor.
Keywords – UAV, Design, Analysis, and Tiltrotor
Energy management under load shedding condition using concept of DC microgrid for residential load
No full textResidential power-cuts are common due to chronic shortage of electricity which affects the country's potential for economic growth. The proposed solution is to supply low voltage from the substation and to convert it into DC at customer premises for domestic usage which will provide homes with uninterrupted, but limited power sufficient to support limited number fans, lights, small appliances, and charging stations irrespective of power shortages. This technology offers to perform Brown-Outs (BO) by feeding 10% of the power to energize houses in DC forms, even during power shortages. A sample area of the distribution grid is taken, and the proposed system is simulated for load shedding conditions to compare its feasibility and economic viability with existing AC grid for long-term power consumption and savings. To extend the idea, grid to vehicle and vehicle to grid to manage demand and generation using battery storage system can be done with the use of renewable generation such as solar power
A cloud based system for prediction of heart disease using machine learning algorithms
No full textHeart disease is a major concern for every individual, especially millennials and the current generation who are seeing its forms at an early age because of improper nutrition and exercise. With the advent of new drugs and techniques to curb its effects, it is crucial to detect the possibility of a heart related disease in the earliest stage. This can be done with data mining to process clinical cardiac parameters measured from a patient. The health sector can take maximum advantage of this, leveraging algorithms to pool in patient data like age, medical history, heart rate, stress, and cholesterol levels while providing probability models for prediction of an illness. Heart disease is an umbrella term used for a variety of ailments which need to be defined meticulously to develop a computational model for analysis. This work presents a web-based application to predict the likelihood of a patient to have a heart disease. The raw data is fed to a decision tree that outputs primary clusters, which in turn are pipelined into a neural network to factor in possibilities of symptoms to calculate the probability of heart disease. The work aims to reduce the errors due to human negligence by factoring in the most detailed symptoms starting from the patient’s medical history to most recent test results for highest accuracy. The work aims to give better accuracy results for the prediction of Heart Disease. The algorithms that are used for analysis are tested on two datasets - one is the Cleveland Cardiac Center dataset and the other is the Switzerland dataset. Both the datasets give different accuracy results. The accuracy results for the Cleveland dataset are Decision Tree Algorithm: 89%, Multilayer Perceptron Algorithm: 89%, Stacking Classifier: 93%. The accuracy results for the Switzerland dataset is Decision Tree Algorithm: 89%, Multilayer Perceptron: 94% and Stacking Algorithm: 94%