Texas A&M University – Corpus Christi
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Jake Stephens Orchestra at Driscoll
No full textJake Stephens Orchestra at Driscoll smiling for a group pictur
Fine-Scale genotypic diversity in the seagrass Halodule wrightii from Oso Bay
No full textDepartment of Physical and Environmental SciencesSeagrasses are the only marine angiosperms in the world. They reproduce sexually and asexually through clonal growth. Seagrass beds are vital ecosystems that harbor the adult and larval stages of many marine animals, including fish, manatees, stingrays and many other vertebrates and invertebrates. Seagrass also play a vital role in carbon sequestration, protecting shorelines from wave energy, and maintaining the water quality of coastal bays. Seagrass beds around the world are declining at alarming rates, and conservation-related research is becoming increasingly important. Genetic variation in seagrass beds has been demonstrated to be positively correlated with productivity, resistance to, and recovery from environmental stress. While several studies have examined genetic diversity at fairly large (meter) scales, few have examined fine-scale (cm) genotypic diversity. Diversity at this scale could have important implications for biological and chemical processes such as pollination or toxin neutralization. This project focused on the seagrass Halodule wrightii, otherwise known as "shoal grass”, the most abundant species of seagrass on the Texas Gulf coast. Ninety six single rhizome fragments were collected from each of three, 60 x 90 cm quadrats placed in H. wrightii beds on the south side of Ward Island, Texas. Each sample was genotyped and genetic diversity estimates (genotypic richness, evenness, and architecture) were produced for each qaudrat. We found a fair amount of genotypic variation at this scale, that declined from east to west in the sampling region. We also found the presence of a very large clone that was present in all 3 quadrats. We conclude that H.wrightii has been present near Ward Island for at least a century, and that environmental and/or anthropogenic factors may be influencing H. wrightii reproduction in an, as yet, undetermined manner.Welch Foundation Award No. BT-004
Let's Talk About Sexes: Is There a Difference in Emotional Intelligence Between Men and Women?
Get PDFCollege of Liberal Arts, Psychology Department, Honors Program; Faculty Mentor: Dr. Lauren Denver-PotterEmotional intelligence (EI) has shown promising results when used to impact the health of one’s interpersonal relationships. Establishing research has focused primarily on the validity and effectiveness of emotional intelligence assessments. As the field of psychology expands its knowledge of EI operations, it also expands its scope. One of the branches of research expansion is investigating the relationship between EI and biological sex. The varying outcomes of this preliminary research have shown a need for further exploration. For this project, we looked at differences in EI between men and women on campus. We used the Emotional Skills Assessment Process (ESAP) to collect EI data from adult participants. Our goal for this study is to identify any trends between sexes. We hope that our data will serve as an addition to the current body of literature, so that we may develop more definitive and personalized mental healthcare interventions
Beatrice Galvan Bridesmaids
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SECURENN: Defeating adversarial neural network attacks with moving target defense and genetic algorithms
No full textA Thesis Submitted In Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE in Computer Science from Texas A&M University-Corpus Christi.Neural Networks (NNs) have become a critical part of Artificial Intelligence due to their reputation of producing highly accurate outputs with minimal human assistance. NNs are used in various diverse implementations from housing market predictors to medical imaging. Their swift increase in importance and incorporation into our lives have rendered them valuable targets to Adversarial Attacks. Adversarial Attacks are malicious actions aimed to undermine NN model performance, cause misbehavior, and acquire protected information. NNs are used to run many state-of-the-art image classification systems therefore, attacks could be dangerous to the property, health and safety of their users. The most common and successful attacks are gradient based attacks on Image Classification Neural Networks. The defense strategies in existence, such as Adversarial Training, fall short on their ability to protect models against more complex attacks due to their susceptibility to degrade generalization ability in models. This work proposes SecureNN, a defense framework for image classification NNs to increase overall robustness of the models against white-box untargeted Adversarial Attacks. Through the combination of the well- established cybersecurity and Machine Learning techniques of Moving Target Defense, Genetic Algorithm, and Ensemble Learning, SecureNN is able reduce the degraded generalization ability seen in most defense methods as well as minimize the advantages white-box attacks have without incurring in significant cost on the accuracy and speed of the model. SecureNN has been tested extensively on the following four NN architecture types: CNN, ResNet50, Inception, and Inception-ResNet and trained with three common datasets of MNIST, ImageNet and Cifar-10. Each model architecture and dataset were tested against the four highest error rate gradient-based attacks of Fast Gradient Sign Method, Basic Iterative Method, Projected Gradient Descent and Carlini Wagner. The average of 1.5% higher accuracy rates than Adversarial Training and 49.6% higher accuracy rates than Undefended Models exhibited through the experimental phase of our framework substantiates SecureNN’s potential as a defense mechanism effective in increasing NN robustness.Computer ScienceCollege of Engineerin
Topic 4.2: Access modifiers
No full textIn this module, you will learn about:
Access Modifiers,
Public Access,
Private Access,
Protected Access,
Default Acces
Meeting at the Lozano Café
No full textMeeting at the Lozano Café in the Café was Rafael , Juan Galvan, Vicente,Elvera Lozano , Valente Quintana,Jose Gonzales, Andres Delauna,Rosa Martinez, Chito Tamez, and Manuel Loranz
Civil Defense Members
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