Texas A&M University-Kingsville: AKM Digital Repository
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Mental health, cultural conformity, and stigma toward seeking psychological help among Latinx individuals
No full textStigma towards seeking psychological help has been a long-standing issue in the Latinx community. Previous research indicates that stigma towards seeking psychological help can be the result of one’s cultural values. The current study expands on previous research concerning cultural identity/conformity and stigma towards seeking psychological help. Participants (N = 225) were asked to complete an online survey which measured cultural values by the Latino Value Scale (LVS) (Kim et al., 2009), mental health distress by the Outcome Questionnaire (OQ-45.2) (Lambert et al., 1996), and self-stigma by the Self-Stigma of Seeking Help Scale (SSOSH) (Vogel et al., 2006). The first hypothesis that states those who exhibit high Latinx cultural values will also experience high self-stigma towards seeking psychological help was not supported. The second hypothesis that states those who uphold high Latinx cultural values will experience high psychological distress was not supported
Solar tracking using linear actuator
No full textThe function of solar trackers is to make solar panels perpendicular to solar ray in order to enhance solar power reaping. The relative motion between Sun and Earth has two degrees of freedom. Sun travels from east to west during daytime and also moves north and south due to Earth's tilt. However, Sun’s daily north-south move is much smaller than its east-west move. Sensor-based solar trackers make solar panels perpendicular to the solar ray based on sensor information. Although the existing sensor-based solar trackers increase solar power generation from solar panels significantly, they also consume considerable power by driving solar trackers. Sensorless solar trackers make solar panels perpendicular to solar ray based on calculated solar location. The performance of sensorless solar trackers is not affected by bad weather. This research is on sensorless solar trackers. Single-axis solar trackers have one degree of freedom solar tracking motion. They can catch Sun’s daily east-west movement effectively. The Sun’s small north-south movement can be covered for single-axis solar trackers by monthly or seasonal adjustment of their orientations. This research is focused on single-axis sensorless solar trackers that are driven by linear actuators. The advantages of linear actuator driven solar trackers are their self-locking function and high load carrying capacity. Their challenges include limited solar panel motion range, potential interference between an oscillating solar panel and its fixed supporting ground link, and motor power consumption for solar tracking. The research of this thesis is motivated by surmounting the challenges facing single-axis sensorless linear actuator driven solar trackers. In this research, linear actuator driven solar trackers will be designed and analyzed. The models of the designed solar trackers will be developed. The kinematic and dynamic performances of the modeled solar trackers will be simulated and analyzed. The results of this research will provide some guidelines for developing linear actuator driven solar trackers
Geomechanical analysis of rock in the near-wellbore region during drilling
No full textThe geomechanical properties of a formation greatly impact the stability of a wellbore; when not properly identified and managed, drilling and completion processes, the presence of a wellbore, and the in-situ formation stresses may lead to problems such as stuck pipe, formation failure, packing off, the inability to log the well, and poor cementations because of excessive washouts. The consequences of wellbore instability are not only immediate, but also build up over time. According to the theory of the plane of weakness, the transitional interface between different bedding layers in a heterogeneous formation is more susceptible to failure due to the fact the layers have different geomechanical properties and those bedding planes are not subject to the same stress conditions. There are several relevant parameters that contribute to identifying the plane of weakness such as Poisson’s ratio, Biot’s coefficient, the friction angle of bedding planes, and the strength parameters of rock beddings. Review of literature on the subject indicates that previous studies have worked with models that assume a homogenous formation where the anisotropic properties of the formation have not been taken into consideration. This study aims to analyze geomechanical behavior in heterogeneous formations using the constitutive model of poroelasticity and the theory of the plane of weakness. Commercial specialized finite element software is utilized for numerical simulation. More specifically, this study aims to analyze the geomechanical behavior of an open-hole drilled well and heterogeneous formation where the plane of weakness plays an important role. The cases that are covered are a vertically drilled well, and deviated wells with wellbore inclination angles between that of the vertically drilled and horizontal well. Additionally, all three cases are analyzed at various wellbore azimuth angles.
Keywords: geomechanical behavior, Mohr-Coulomb, heterogenous, drilling, stresse
Vision based obstacle avoidance and navigation system for mobile robots
No full textThis thesis documents a simulation-based investigation into the use of vision for the navigation of mobile robots. We developed characteristics such as goal-seeking, obstacle, and collision avoidance with visual data. In this thesis, we address the ability of autonomous robots to avoid conflicting circumstances, thereby allowing the robot to attain independent and goaloriented navigation. Current robotics research and development are primarily based on making the robotic system more autonomous and versatile. Tracking the objects is an extremely critical issue in computer vision, so we use techniques such as Canny edge detection, perspective transform along with libraries like OpenCV and TensorFlow are used to process the image. The processed images are used by different algorithms to perform lane following and traffic sign detection. The issue of moving a robot through severe conditions has pulled into much consideration. A robot may encounter obstacles of all structures, which is needed to be avoided intelligently. Therefore, algorithms that consider absolute path length and security are created by using a well-known A* path planning approach. The robot uses the A* path planning to create a cost map to select the most efficient path with minimum distance and risk. To run the simulation to visualize the robot's path planning, lane following, and traffic light detection, we built an environment and mapped it using the SLAM (Simultaneous Localization and Mapping) technique. The data obtained by performing all the algorithms are stored in the ROS bag. These data are then plotted to understand the behavior of the robot under different condition
Design of a lower leg exoskeleton using microsoft kinect
No full textThis research is focused on gait rehabilitation of a subject who suffers from walking disability in the lower leg of the body that includes the knee and ankle. The idea behind this research is to help the person in their gait restoration by creating an Exoskeleton that could support the impaired limbs and give them the desired motion again. This research introduces the design of a two-degree freedom exoskeleton for the knee and ankle. An exoskeleton unit for walking is designed as a serial mechanism used for the entire leg or entire body, but this research presents a manipulator only for the knee and ankle. Working on the lower extremity of the body gives us an advantage of a much more workspace than any other part. The idea behind the exoskeleton is to target that group of individuals who have an external injury in the knee such as war veterans or people who suffered an accident causing the injury in the lower limb. The thesis is concerned with the movement in the knee so that the subject can walk as he used to before the injury since this is a two degree of freedom, so it is just concerned with the flexion and extension of the knee and ankle. Since this model is two degrees of freedom, so an RGB-D camera (Microsoft Kinect) is used to track the skeletal movements and derive the joints angles, based on the angle time series the torque for the individual joints is calculated. Then a motor is modeled in Simulink to provide the exoskeleton the desired motion. Then a SOLIDWORKS model is designed to provide a better understanding of the motion generated by the Exoskeleton
The diagnostic competencies: perceptions of educational diagnosticians, administrators, and classroom teachers
No full textThe role that educational diagnosticians play in the educational process can vary across settings. In Texas, the Texas Education Agency oversees the State Board of Educator Certification (SBEC). SBEC certification standards outline knowledge and skills that are required for educational diagnosticians to practice in Texas. The Texas required endorsement is acquired by passing a state mandated assessment covering the standards set by SBEC (TAC,§231.623). Given the evolving role of an educational diagnostician, this study examined the perceptions of educational diagnosticians, administrators, and classroom teachers of the competencies in regards to implementation, utilization, and importance. Furthermore, this study sought to determine if years of experience in education affects these perceptions. Results indicate that administrators and teachers perceive the utilization of competencies to occur at a lower rate than diagnosticians report utilizing them, and years of experience showed no statistically significant effect on perceptions. No statistically significant interactions were found among position, years of experience, and perceptions of the competencies
The history of Lamar Junior College
No full textThe junior college movement in Texas has been one of rapid development. In the past fifteen years junior colleges have been built in practically every leading city in the state. These junior colleges have rendered valuable services to the four year colleges and universities, in that they have tended to keep down overcrowded conditions in many of them. Also, many students have been able to get two years of college work at home in preparation for degrees from institutions of higher learning. Too, many students are able to round out their secondary education and thus prepare themselves for a business, or possibly a professional career
The influence of forage quantity and quality on the morphology of White-tailed deer (Odocoileus virginianus) in South Texas
No full textHistorically, many ungulate sub-species boundaries were based on minor morphological differences. With the advent of molecular tools it has become apparent that most of these sub-species designations do not reflect the distribution of genetic lineages. A growing body of work has revealed that differences in body size of ungulates do follow ecoregion and soil boundaries and that these size differences are nutritionally influenced. Currently, it is unclear if these patterns of body size are a result of differences in the quantity of high-quality forage produced or from differences in nutritive value of the same plant species. I quantified differences in white-tailed deer (Odocoileus virginianus) body mass and antler size at 4 spatially segregated sites in South Texas, USA, using data from captured deer. I sampled forage items to determine if differences in body and antler size were best explained by forage quantity or quality. Long-term trend data, collected from 2011–2019, indicated female body mass was 9% smaller for deer captured on the eastern edge of the Coastal Sand Plain ecoregion as compared to those from the western transition zone of the Coastal Sand Plain and Tamaulipan Thornscrub ecoregions. Similarly, male body mass and antler size were 20% and 8% smaller respectively, in coastal habitats compared to more interior sites. The amount of digestible energy in browse and mast species was ~60 kcal/kg lower at sites with smaller deer body mass and antler sizes, which was about a 2% reduction in digestible energy (χ32 = 7.40, P = 0.06). Additionally, I found that the proportion of deer that had deficient levels of serum copper was greater at the site with smaller deer body mass and antler sizes (100% versus 21%, P < 0.001, Fisher’s exact test). Overall, my research suggests that regional differences in nutritive value of primary productivity drives regional size differences in ungulate morphology
Melanoma detection in dermoscopy images using a cloud based machine learning application
No full textDue to various skin diseases and the similarity in their appearances, dermatologists find it a challenging task to automatically diagnose dermoscopic skin lesions of skin cancer. Recent advancements in the areas of Dermoscopy, Machine Learning, and Image Processing have made it possible to automatically detect and distinguish a melanoma in its early stage without requiring a biopsy. This work presents a cloud-based Machine Learning application for Melanoma detection in Dermoscopy images. First, we discuss the discriminating properties for the melanoma skin lesions. Then we provide a brief overview of the isolated qualities which then are fed to the Machine Learning classifier to categorize melanoma in dermoscopy pictures. A study of various Machine Learning classifiers is done pertaining to Melanoma detection and each of them is trained with the melanoma images. We test the application on a publicly available PH2 dataset and ISIC Archive for various physical and texture features. The implementation of the application includes a dual cloud-based architecture where two clouds are used for training the algorithms and web application respectively. The physical and texture features are then extracted using Haralick’s, Tamura’s, King’s texture feature and Gabor’s physical features algorithms, to form a feature vector. We then assign labels to this feature vector and use the RFC (Random Forest Classifier) classifier to classify the image as melanoma, non-melanoma or negative. Implementation and Analysis of various Machine Learning Classifiers including Decision Tree Classifier, Support Vector Machine Classifier, and Random Forest Classifier gave an accuracy of 58.33 percent, 75.00 percent and 91.66 percent respectively. The proposed machine-learning based melanoma detection from the dermoscopy images through a cloud-based application proves to be a non-invasive method, increases the accessibility of the melanoma detection for patients and hospitals, and also improves the accuracy, speed, and reliability of the melanoma detection from dermoscopy images
Pedestrian detection using deep learning through a dashcam
No full textDeep learning based strategies have shown exceptionally huge advancements in accuracy and quick decision making for applications in intelligent or autonomous driving vehicles. Pedestrian recognition, having applications in autonomous or intelligent vehicles, is one of the vital applications of object detection, an area of basic ongoing research in computer vision. From the last couple of decades, pedestrian recognition has played a vital role in numerous real time applications such as collision avoidance systems for smart or intelligent vehicles, intelligent observation cameras, and domestic security frameworks. The proposed methodology of this work suggests utilizing a dash camera to support a model that identifies all humans that might come in the way of a moving autonomous or driven vehicle from images captured with the dash camera. This algorithm proposed model is based on TensorFlow Human Detection API and is compared to the Histograms of Oriented Gradients (HOG) for human detection. Based on the research, the accuracy and efficiency of the proposed model to detect human was much better than to the other models. The defined method in this paper had an accuracy of around 98% as compared to 84% for the Histograms of Oriented Gradients detection model. The proposed model was faster on average as compared to the Histograms of Oriented Gradients detection model for any given picture on the same framework for training to testing because the proposed model took 11 seconds on average for processing one picture whereas the HOG method took more than 40 seconds on average. The proposed model gives “boxes” as outputs around the humans detected in the images and the result of this model is that it is accurately able to recognize pedestrians with the high accuracy of 98%. The samples on which the algorithm was tested are low-quality pictures taken from low-cost cameras, needing exceptionally less computing power, obviating need for expensive components. This low-cost proposed system will thus permit a dash-cam based system fitted with pedestrian detection technology in vehicles to be implemented for automatic vehicle and self-driving vehicle applications