Optimization Of Solar Energy Efficiency Using Neural Network Controllers With Direct Current Converters

Photovoltaic (PV) systems offer a renewable energy source by converting sunlight into electricity. This dissertation enhances PV system performance using advanced control mechanisms and DC-DC converters. PV systems, influenced by variables such as irradiance and temperature, require efficient Maximum Power Point Tracking (MPPT) for optimal energy conversion. Traditional MPPT methods like the Perturbation and Observation (P&O) algorithm often struggle with rapidly changing conditions. While Artificial Neural Networks (ANN) and Recurrent Neural Networks (RNN) have been explored for control purposes, this research applies Positive Output Super Lift Luo (P/O SLL), and Ultra Lift Luo (ULL) converters integrated with ANN and RNN controllers. These converters achieve higher output voltage increase compared to traditional converters like Boost, Cuk, and SEPIC by employing a super-lift technique. The study aims to design and implement these applications with AI-based controllers using MATLAB/Simulink. Research objectives include boosting DC voltage, minimizing power loss, optimizing voltage for varying conditions, and achieving optimized matching resistance. The optimization lies not only in integrating P/O SLL and ULL converters with ANN and RNN controllers but also in developing control algorithms that enhance adaptability and efficiency. Unlike existing approaches, the proposed system offers higher output voltage increase, reduced component stress, and improved efficiency. The AI controllers enable real-time adaptability to changing conditions, ensuring maximum energy extraction and enhanced MPPT performance. This research addresses static and dynamic learning rates in AI controllers, with static learning rates for steady-state conditions and dynamic learning rates for rapid adaptation. This dissertation provides a comprehensive solution for optimizing PV system performance, contributing to more efficient renewable energy systems and advancing PV system technology to support the global transition to sustainable energy. Index Terms—Artificial neural network, dynamic learning rate, dc-dc converters, maximum power point tracking, photovoltaic system, recurrent neural network, static learning rate

An Examination Of Risk Factors For Suicidality Among Adolescents In The United States

Suicide is considered a significant public health issue, identified as the second leading cause of early mortality in the United States among adolescents (CDC, 2023). The National Institute of Mental Health (2023) defined it as “death induced by self-directed destructive behavior with intent to die” (p. 4). For youth aged 10-14 suicide increased by 36% from 2000 to 2021 in the United States. In recent decades, suicide among adolescents has increased despite estimates of stable or dropping suicide rates in developed countries. Every year, 703,000 youth worldwide commit suicide, and many more attempt (WHO, 2022). This study used a nationally representative sample of adolescents from the 2021 High School Youth Risk Behavior surveys. Data were examined with a General Strain theoretical framework utilizing logistic regression, and linear regression to understand the impact of empirical risk factors, physical, dating, sexual victimization, bullying, and cyberbullying on youth mental health issues, physical well-being that includes exercises and workouts, and suicidality among high school students. During the early months of the COVID-19 pandemic (2020 into 2021), youth experiences of physical and sexual violence/victimization may have increased, given their isolation. While dating violence increased, it is not clear how this impacted suicides. Youth likely experienced more cyberbullying, given their increased interactions online. This study revealed significant relationships between various forms of victimization, that is physical, sexual, dating violence, bullying, and cyberbullying, and the mental health and physical well-being of high school students, which in turn influenced their risk of suicidality. The regression analyses highlighted that these forms of victimization were predictors of increased mental health issues, which were directly linked to higher suicidality rates among adolescents. The findings are consistent with the literature, as victimization indicators are expected to be related to mental health issues and physical wellness. Sexual victimization was more impactful than physical victimization and dating victimization on mental health and cyberbullying was more impactful than more traditional bullying on mental health. Relatedly mental health issues significantly affected high school students\u27 physical wellness. This study\u27s results offer empirical details that should be informative for policymakers in prioritizing their efforts to reduce youth health risk and victimization. Keywords: suicidality, victimization, mental health issues, physical wellness, adolescents

(R2073) Analysis of MMAP/PH(1), PH(2)/1 Preemptive Priority Queueing Model with Single Vacation, Repair and Impatient Customers

In this paper, we analyse a single server preemptive priority queue with phase-type vacation and repair, feedback, working breakdown, close-down and impatient customers. Customers arrive according to the Marked Markovian Arrival Process and their service time according to Phase-type distribution. If the High Priority customers need feedback, they lose their priority and join the Low Priority queue. At any instant, if the server is broken down, the server provide service with slow mode for that current customer and then the server will go into a repair process. When there are no customers present in both the queues, the server close-down the system and then goes on vacation. During the close-down and vacation period, high priority customers may balk. The Matrix Analytic Method is used to look into the number of consumers that are currently in the system. Analysis of the steady-state, the server active period, and the total cost are all discussed. Finally, some significant performance measures and numerical examples are given

(R2067) Solutions of Hyperbolic System of Time Fractional Partial Differential Equations for Heat Propagation

Hyperbolic linear theory of heat propagation has been established in the framework of a Caputo time fractional order derivative. The solution of a system of integer and fractional order initial value problems is achieved by employing the Adomian decomposition approach. The obtained solution is in convergent infinite series form, demonstrating the method’s strengths in solving fractional differential equations. Moreover, the double Laplace transform method is employed to acquire the solution of a system of integer and fractional order boundary conditions in the Laplace domain. An inversion of double Laplace transforms has been achieved numerically by employing the Xiao algorithm in the space-time domain. Considering the non-Fourier effect of heat conduction, the finite speed of thermal wave propagation has been attained. The role of the fractional order parameter has been examined scientifically. The results obtained by considering the fractional order theory and the integer order theory perfectly coincide as a limiting case of fractional order parameter approaches one

Panther - November 2017

https://digitalcommons.pvamu.edu/pv-panther-newspapers2017/1002/thumbnail.jp

Barriers To Telemedicine: Factors Influencing The Adoption Of Telemedicine

Telemedicine is a rapidly evolving health treatment capability that offers an efficient and cost-effective alternative to conventional medical care. Providing access to alternative medical treatment may mitigate the population’s stress on the medical infrastructure in the upcoming decades. This study investigated the factors influencing patient adoption of telemedicine, including patient experiences and economic considerations. A quantitative survey explored patient population’s intention to utilize telemedicine, focusing on factors influencing the patients’ decision-making processes. Analyzing the survey results, the researcher focused on five main variables: exposure to telemedicine, age, loss of income, trust in doctors, and time lost. The research findings offer valuable insights into the potential consumption of telemedicine by the population, benefiting stakeholders in the healthcare industry, lawmakers, social workers, and community activists. Keywords: telemedicine, healthcare/health disparities, cost-effective, opportunity cost, trust in doctors, ag

Untold Stories: Exploring Queer And Genderqueer Students’ Perceptions Of Sense Of Belonging And Experiences At One Historically Black University

This study used a basic interpretative qualitative design, using a case study as the theoretical approach to examine the experiences of Black queer students, particularly as they foreground a sense of belonging on a historically Black college and university (HBCU) campus. Extant literature demonstrated that queer cohorts are likely to experience isolation and a sense of not belonging at HBCUs due to tradition (Davis, et al., 2020; Lenning, 2017; Mobley & Johnson, 2019). Queer students’ sense of belonging can influence behaviors such as persistence, engagement, academic achievement, and a sense of self (Garvey, 2020; Squire et al., 2018; Strayhorn, 2019). Consequently, constructing and cultivating a sense of belonging is crucial to their welfare and overall academic success. Although educational attainment is an important goal for Black queer students, research detailing strategies that cultivated foregrounding of a sense of belonging as a path to academic success among this population is needed to fill the gaps in the literature. The objectives of this study were to research queer students making meaning of their experiences as well as to discover how these students focused on creating an environment of belonging and succeeding in a conservative space. Research detailing the strategies toward college completion is necessary to inform educational leaders on policies and practices that encouragingly influence queer students. This study informs queer students on becoming agents of their own development and success in college. The conceptual framework guiding this study was extracted tenets from College Students’ Sense of Belonging, Queer Theory, and Quare Theory. Data collected through interviews, artifacts, observation, and field notes were analysis utilizing thematic analysis. Two semi-structured interviews were conducted with each participant. The interviews provided thick, rich descriptions and details that gleaned the lived experiences of the participants. Data analysis revealed two master themes: Contextualizing A Sense of Belonging: Navigating A Non-Culturally Responsive Classroom and Learning How to Just Do Me: Attaining Self-Actualization. The findings support the importance of educational leaders cultivating welcoming spaces and the importance of self-agency in foregrounding a sense of belonging. Keywords: queer, genderqueer, sense of belonging, academic success, historically Black colleges and universitie

Panther - April 2015 - Vol. XCV, Issue 6

https://digitalcommons.pvamu.edu/pv-panther-newspapers2015/1000/thumbnail.jp

School Shootings In The United States: An Analysis Of Micro And Macro Level Variables

In 2023, by November 2, there had been 45 school shootings resulting in fatalities and injuries (Matthews, 2023). There were 193 shooting incidents in preschools and K–12 schools during the previous school year, which is greater than an average of 49 incidents each school year since 2013 (Everytown Research & Policy, 2022). This predictive quantitative study offers a comprehensive analysis of various state-level, school-level, and individual-level variables, such as the laws related to guns, access to mental health services, economics, type of school shooting, socio-demographic indicators, school type, and timing of the incident toward informing effective preventative policies. It utilized information from five data sets: the K-12 School Shooting Data Base, Giffords Law Center, KFF Data Base, State of Mental Health in America Report, and the Washington Post School Shooting Database. The data were analyzed with t-tests and regression using a layered ecological contextual theoretical framework to understand what increases the possibility of school shootings with casualties. The findings revealed that school factors such as indoor locations, targeted victims, and the presence of School Resource Officers, and macro factors such as limited youth access to mental health services and a high percentage of youth in poverty are predictive of school shootings with casualties. Keywords: school shootings, gun violence, school violence, school fatalitie

PV Panther October 1968 Music and Fine Arts Pt.2

https://digitalcommons.pvamu.edu/dr-robert-alphonso-henry-professional/1038/thumbnail.jp