Texas A&M University-Kingsville: AKM Digital Repository
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Spanish-culture withdrawals, sixth grade level, Premont Public Schools, Premont, Texas
No full textThe purpose of this research is to present an unbiased study of withdrawals among Spanish-Culture students at the sixth grade level, Premont Public Schools. This level is chosen because observations seem to indicate that pupils who advance beyond this level are more apt to remain in school. An accurate record of the withdrawals below the :3ixth·grade level would be more difficult to obtain, since so<many frequently withdraw and re-enter the primary grades of the Premont Elementary School.
Due to the fact that there are only a few of the older Spanish-Culture scholastics who attend high school, the author can not but feel some responsibility, as a teacher, for the educational status of the children in the Premont School District. Less than fifty per cent of the Spanish-Culture enrollment receive any schooling above the sixth grade, as revealed by past records of the school district. During the past four years, 1935-1939, ninety-four Spanish-Culture students have enrolled in the sixth grade. Forty-nine of the ninety-four withdrew either during the year or at the close of the school. A knowledge of the number of withdrawals among Spanish-Culture pupils has led the author to make this study on the possible causes of withdrawal
Microbiology of the Kingsville sewage lake
No full textThis series of experiments was performed for the purpose of showing the types and numbers of micro-organisms found in the sewage lake of Kingsville, Texas. The determination of the types of micro organisms was to show the sanitary aspect as evidenced by the presence of the intestinal bacteria, Escherichia coli, (E. coli). Periodic tests were made to determine the presence of other Bacteria, Protozoa and Algae in the water. The presence of E. coli indicates the presence of intestinal bacteria, either pathogenic or non-pathogenic. The test for E. coli as performed in this series is the standard test for fecal contamination
Design and performance evaluation of 8T SRAM cell using FinFET and CMOS at 16nm technology
No full textCache memories on the processor are the crucial blocks in VLSI system design. Careful inspection of the performance, power, and area of memories is necessary before fabricating the system. In digital processors, SRAM cells are used in the memory cache for better performance and low power consumption. The performance of conventional CMOS devices is affected by the submicron scaling of CMOS devices. Short channel effects and variations in process parameters affect the circuit reliability and performance by making CMOS devices smaller in size. FinFET will be the perfect replacement for CMOS when the device's size is below 32nm. FinFETs fabrication and the circuit design result in efficient performance and reliability. The double-gate transistor architecture of FinFET allows for greater scaling than planar devices. A compromise is needed for either read or write stabilities of SRAM cell due to the sizing issue of pass transistors in the 6T SRAM cell design. 8T SRAM will overcome the access transistor sizing conflict faced in 6T SRAM. In this thesis, the 8T SRAM cell is designed with CMOS and FinFET technologies. Performance evaluation is done for FinFET and CMOS in 16nm technology. The Predictive Technology Model (PTM) of the Arizona State University tentative model is used to simulate CMOS and FinFET based SRAM cells with Synopsys HSPICE. Average power consumption, delay, and SNM are analyzed and compared for both CMOS and FinFET
Sustainbility assessment of selected additive manufacturing processes
No full textSustainable manufacturing has risen to a peek of interest for organizations who are seeking out methods of producing their material with minimal environmental impacts for an eco-friendlier product. Users of additive manufacturing technologies are faced with lack of centralized source of material information or process information which will be useful for sustainability assessment. A material information model (MIM) which is modified to capture several information about the build material selected and the role it plays across the product life phases is proposed. In this model, a clarification on ways to utilize elemental data (characteristics – based) to gauge the impact of the materials is discussed. Secondly, a method for analyzing the social performance of an additive manufacturing process is presented. In this method, various indicators are identified and grouped into a scale of points, to evaluate the social performance. Lastly, a model for the sustainability assessment performance of additive manufacturing process is developed. The three aspects captured are grouped into the three pillars of sustainability (social, economic, and environmental) and integrated to evaluate the sustainability assessment performance model.
Keywords: Sustainability; Sustainability Assessment; Additive Manufacturin
Studies on the mechanisms of DNA damage repair in human neurons
No full textMany studies suggest that DNA lesions are increased in aging cells. Although repairing the lesion in DNA is critical for proper cellular function, it has not been fully understood how neurons cope with various DNA lesions, especially in aging brain. In particular, most of neurons in the brain are irreplaceable with new cells unlike majority of cells in other tissues and organs and the failure of DNA repair in neurons may lead to neurodegenerative diseases including Alzheimer’s disease. To investigate DNA repair activities in neurons, the expression of various DNA repair genes in aging neurons other cell types was assessed. Gene expression data from Genotype-Tissue Expression (GTEx) consortium were analyzed to find genes involved in mismatch repair and homologous repair pathways those expressions are positively or negatively correlated to the age. To investigate the effect of altered expression of these genes
in DNA repair and neuronal function, the development of a new model system using induced pluripotent stem cells has been initiated
Topology control protocols in wireless sensor networks
No full textTopology control is a crucial strategy to extend the lifetime of the energy constrained Wireless Sensor Networks (WSNs). It is a well-known strategy to build a reduced topology without sacrificing the coverage and connectivity of the network and thus save the total energy of the network and individual energy of the nodes. As energy efficiency is one of the most critical issues in Wireless Sensor Networks (WSNs), it is imperative to employ energy aware and load balanced topology control (TC) algorithms in WSNs without sacrificing the connectivity and coverage. The total topology control mechanism can be divided into two processes: topology construction and topology maintenance. It is topology construction which has the responsibility to create a reduced topology. Topology maintenance is the process to recreate or change the reduced topology when the network is not energy optimal anymore. This thesis paper concentrates on the Minimal Spanning Tree (MST), which is a frequently encountered problem while designing the topology construction protocol for WSNs. As the amount of running time and messages exchanged is an important benchmark to measure the efficiency of the distributed algorithms, a lot of research has been conducted to develop simple, local and energy efficient algorithms for WSNs which aim to create sub optimal MSTs. This thesis discusses two popular approaches to build a Spanning Tree in the WSNs- Random Nearest Neighbor Tree (Random NNT) and Euclidian Minimal Spanning Tree (Euclidian MST) along with the Simple Tree (ST) algorithm. Then, two novel load balanced TC protocols for connectivity – SWST (Simple Weighted Spanning Tree) and EAST (Energy Aware Spanning Tree) is presented. SWST aims to balance the load of the network evenly among the children and parent nodes and increase the number of successful delivery of the messages to the sink. The aim of the EAST protocol is to reduce the energy consumption in the weak nodes as well as weak branches and thus to balance the load. The proposed TC methods are based on the Minimal Spanning Tree construction method which creates a Connected Dominating Set (CDS). In the proposed TC protocols, the strategy is to make any node active depending on the weight or energy metric and put as much nodes to sleep as possible. To simplify the performance evaluation, Dynamic Global Topology Recreation (DGTRec) was employed as the topology maintenance protocol which repetitively recreates the virtual communication backbone after a predefined amount of time. The new algorithms were tested and compared with Simple Tree, Random Nearest Neighbor Tree (Random NNT) and Euclidian Minimal Spanning Tree (Euclidian MST). The Matlab simulation results show significant improvement in load balancing and event covering after the implementation of the new algorithms
Ergonomic assessment of work-related musculoskeletal disorders among limited service restaurants
No full textMusculoskeletal disorder is one of the most common work-related recordable disorders across all industries. This thesis examines work related musculoskeletal disorders present in limited service restaurants using Texas A&M University Kingsville as a case study. This research provides highlights into the most common musculoskeletal disorder amongst servers, how they can be identified and determining its impact on employees. The outcome indicates a significant relationship between the work demand/work posture and the occupational disorder experienced amongst limited service restaurant employees. Employing various tables, charts, and ordinary least square regression model, with the aid of IBM Statistical Package for Social Sciences (SPSS), this research shows that there is a common musculoskeletal disorder associated with all the five limited service restaurants examined in this case study and shows its effect on employee productivity
A cloud based system for breast cancer detection using machine learning algorithms
No full textCancer is an abnormal growth of cells which tend to proliferate in an uncontrolled way and, in some cases, to metastasize. Cancer is not one disease. It is a group of more than 100 different and distinctive diseases. Cancer can involve any tissue of the body and have many different forms in each body area. Breast Cancer is the most common cancer among American women. Prediction of Breast Cancer occurrence is necessarily required to increase the survival rate of patients suffering from Breast Cancer. The diagnosis of cancer and detecting the accuracy of prognosis of the cancer has improved due to technological advancements, Machine Learning techniques, and statistical methods. This work implements a web application that will display the cancer prediction results thus made accessible to medical staff. This research depends on the concepts of cloud computing, Machine Learning techniques, and web services. The data set used in this work is accessible on the cloud that will be processed by expert Machine Learning techniques and circulated to the hospital employees. The Breast Cancer Wisconsin Dataset used is preprocessed. The Machine Learning techniques: Decision Tree, Multiplayer Perceptron, and Support Vector Machine algorithms are implemented in this work and is applied to the dataset to get better accuracy results for the prediction of Breast Cancer. The accuracy obtained for these algorithms was Decision Tree - 94.74%, Support Vector Machine - 63.55%, and Multilayer Perceptron - 58.31%. Thus, the Decision Tree algorithm had the best accuracy for this dataset and thus has been used for prediction of Breast Cancer type (benign or malignant) for new patients
Development of daily, 3-day and 7-day ahead statistical streamflow forecasts
No full textClimate variability plays an important role in effecting water availability, which could threaten reliability of water resources management in various river basins. In particular, frequency and magnitude of extreme events (e.g. hurricanes) have increased in Texas during recent decades, resulting in significant damages due to flooding. In order to improve decision making for flood preparedness and planning as well as managing daily reservoir operations and hydropower generation, forecasting of daily to weekly streamflow could play an important role. Thus, the primary objective of this study is to develop statistical forecasts for 1, 3 and 7 days’ lead time for multiple sites across different watersheds in Texas. To address this objective, two different statistical models (ARIMA and semi-parametric) were developed for three dam sites. In order to forecast daily to weekly streamflow during 1978 - 2018, only the antecedent streamflow was used as a predictor in the ARIMA modeling. In the semi-parametric method, besides antecedent streamflow, the forecasted precipitation was also used as the predictor to forecasts streamflow from 2011 – 2018. Our results indicated that ARIMA model outperformed semi-parametric approach in forecasting daily to weekly streamflow for all the three sites chosen in this study. The forecasting skill for 7-day and 3-day ahead forecasts were better than 1-day ahead forecasts for all the sites. Such simple statistical models could be used for decision making on 3-day to weekly time scales to better manage hydropower generation and minimize effects of multiday flooding event
Prediction of remaining useful life of a wing of an aircraft using the twice yield method
No full textDue to the increasing cost in aircraft maintenance, the aircrafts are required to operate beyond their design life. But using the aircraft beyond design values could risk the operation of the aircraft. Failure of the aircraft structure may lead to dangerous consequences, among them the most serious damage is the loss of the life. Hence to create a balance between safety and the cost, the prediction of Remaining Useful Life (RUL) plays a very important rule. Different models had been proposed to predict the Remaining Useful Life (RUL).
In this research, the Twice Yield Method was used. Twice Yield Method was introduced by Kalnins [1]. This method only requires a single loading step and is performed like a monotonic analysis, as opposed to cycle by cyclic analysis of loading and unloading. It was used with the analysis program, a finite element software- Abaqus. An aircraft semi-wing of A310-300 was considered. The wing was modeled in SolidWorks and then was imported to the Abaqus to run the analysis because the stresses due to the loading of the aircraft are necessary to evaluate the Remaining Useful Life of the aircraft (RUL). Using the Alternating Stress (found from Abaqus) into the Paris equation, Fatigue Life (Nf) values at different point of interests are found and the least value (1.36 x 105) gives the Fatigue Life (Nf) or Remaining Useful Life (RUL). The predicted Fatigue Life (Nf) was compared with the experimental value and a good agreement was found