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Angelo’s Pizza and Pasta Thanks for Continued Support of the Friends Annual Spaghetti Dinner
No full textText on plaque reads "Angelo's Pizza & Pasta Thank You For Your Continued Support Of The Friends Annual Spaghetti Dinner 2007". Sticker on back of plaque reads, "CROWN TROPHY 2168 Bayport Blvd. Seabrook, TX 77586 281-291-9977"
Kinematic Redundancy Resolution for the Baxter Research Robot
No full textRobotics is a brand of science and engineering which involves many other fields such as mechanical engineering, electrical engineering, and bioengineering. Robotic engineers and scientists develop machines that can substitute for humans in various situations. Nowadays, robots are used in hazardous and dangerous environments, factories or where humans cannot survive (outer space, deep sea, etc.). A lot of tasks can be done from something simple such as object lifting and carrying to something complicated such as bomb deactivation, sample collecting, etc. In order to do such tasks, kinematic redundancy plays an important part, especially in the class of humanoid robots.
A robot manipulator arm is said to be kinematically redundant when it has more degrees of freedom than it is required for a specific task. The redundancy can be used to achieve additional goals which is importance in robot design and planning. In this thesis, kinematic redundancy resolution will be investigated and applied to Baxter robot. This will include singularity avoidance, collision avoidance, as well as manipulability optimization. As a convenient tool for this research, a method of Baxter’s end-effectors manipulation, namely Cartesian velocity control, will also be developed
Highway 146 Drawbridge in Kemah TX with Paul Craig Pier 3 Store in Foreground
No full textPhotograph of the Highway 146 drawbridge in Kemah, Texas with Paul Craig Pier 3 store in foreground. Back of photo reads "K392114 POLAROID"
Kemah Views and Bridge Construction (1)
No full textBack of photo reads "1"One of ten photographs of Kemah views and bridge construction (front and back). Paper is manufactured by Kodak
Classification of Cocaine Addicted Patients Using 3D to 1D Hilbert Space-Filling Curve Ordering of fMRI Activation Maps
No full textIn analysis of functional magnetic resonance imaging (fMRI), transformation of the 3D brain imaging data to 1D is required for further analyses, which often includes the classification of different groups of participants. The conventional transformation method is linear ordering, which results in a 1D vector that has a high amount of discontinuity which does not preserve the structure of the brain. A Hilbert space-filling curve can better preserve the structure of the brain after the transformation. Features obtained after a transformation based on Hilbert space-filling curve should lead to better classification performance.
In this work, we applied Hilbert curve transformation to completely de-identified brain fMRI activation maps from 59 cocaine-addicted and 25 age-matched control participants and classify them as controls vs. patients using machine learning algorithms. Classification based on features from Hilbert space-filling curve ordering resulted in higher classification accuracy of cocaine-addicted patients vs. controls than those of conventional linear ordering
The Interaction Between Salivary Cortisol and DHEA During Acute Psychosocial Stress in Sleep Deprived Individuals
Get PDFSleep deprivation can impair cognitive and emotional processes, especially those regulated by the prefrontal cortex and medial temporal lobe (i.e., hippocampus, amygdala). Stress and increased cortisol levels have been found to have similar detrimental effects. More recently, research has found that dehydroepiandroeterone (DHEA), an antagonist to cortisol, may counter the negative consequences of stress and even provide beneficial results to individuals under stress. However, very little is known regarding the relationship between DHEA and cortisol when individuals are both sleep deprived and stressed. The aim of the current study was to explore the relationship between DHEA and cortisol during an acute psychological stressor in sleep-deprived individuals. It was hypothesized that sleep deprivation would disrupt the protective effects of DHEA, as evidenced by a larger interaction between cortisol and DHEA in sleep deprived individuals after an acute stressor, as compared to controls. Specifically, high cortisol and low DHEA would be seen in sleep deprived participants compared to low cortisol and high DHEA in control participants. Additionally, it was hypothesized that if such a difference exists between groups, this difference would predict changes in affect. More specifically, individuals with low cortisol and high DHEA would have decreased negative affect, whereas individuals with high cortisol and low DHEA would have increased negative affect. Twenty-eight participants were split evenly between the sleep deprivation group and control group. Sleep deprivation was induced by wakefulness for 24 hours while controls slept for 8 hours. Stress was induced through the Trier Social Stress Test. Saliva samples and the Positive and Negative Affect Scale (PANAS) were collected at three time points—before, immediately after, and 20 minutes after the acute stressor. There was no significant difference observed in the cortisol to DHEA ratio between sleep deprived and non-sleep deprived individuals after an acute stressor. These findings suggested that the combined effects of sleep deprivation and stress did not disrupt the protective effects of DHEA on cortisol. Future research should be conducted to fully elucidate these relationships
Examining instructor and instructional effects on students' statistics attitudes
No full textA long-standing hypothesis in statistics education has posited that instructors could have a large impact on students’ attitudes toward statistics. This hypothesis remained untested over the years. Moreover, if instructors do have a large impact on students’ statistics attitudes, then there is a need to provide explanations as to what dimensions of teaching competencies account for this impact. Drawing on a rich data set collected from 1,924 students clustered within 23 instructors across 11 post-secondary institutions in the United States, the hypothesis concerning instructor effects on students’ statistics attitudes was tested in this study. Multilevel covariate adjustment models were employed to quantify the size of instructor effects. The analysis suggested that instructors varied considerably in their abilities to improve students’ statistics attitudes. Furthermore, instructors’ differential contributions to students’ attitudes were found to be positively associated with instructional practices most proximal to tasks involving data collection and analysis in proper contexts as well as with instructors’ attitudes toward teaching statistics classes. Lastly, results showed that instructors who improved students’ statistics attitudes were also effective at improving their expected course grades, a measure that strongly predicts student ratings of teaching. The teaching effectiveness measures explored in this study may be used to orient instructors on the development of new pedagogic skills centered on students’ statistics attitudes. Altogether, these findings necessitate the need of future studies to identify and validate additional instructional dimensions that hold promise for improving students’ statistics attitudes and also herald an exciting opportunity to expose students to a full range of instructional skills in the modern statistics classrooms
Teacher Awareness of STEM Education: Industry, Resources and Student Preparation for Success in College and Career
Get PDFThis study examined science teachers’ perceptions and determined their level of STEM awareness and support. Survey, interview, and demographic data were collected from a purposeful sample of 124 high school science teachers across eight high schools in a large suburban school district in southeast Texas. For purposes of this study, the school district was divided into three regions based on the school’s percentage of students identified as economically disadvantaged (ED). The STEM Awareness Community Survey (SACS), developed by Sondergeld and Johnson, was used to assess teachers STEM awareness and support. Quantitative data were analyzed using frequencies, percentages, and a one-way analysis of variance (ANOVA), while an inductive coding process was used to analyze the collected qualitative data. Quantitative analysis showed there was not a significant mean difference between school district regions and two of the subscales measured, Industry Engagement in STEM Education and STEM Awareness and Resources