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(R2081) Analysis of a Flexible Group Service MAP/PH/1 Queueing Model with Soft Failure and Reneging
Full text linkQueueing models where services are offered in groups (or blocks or batches) have shown to be very helpful in real-world applications and these queues have been well studied in the literature. In this paper we see one such group service queueing model with soft failure and reneging; here, by soft failure, we mean an emergency arrival. The arrival process is a Markovian arrival, whereas the emergency arrival follows an exponential distribution. Customers are served in groups ranging in size from 1 to a fixed constant, let’s say N. A batch’s service time is determined by the phase-type distribution that corresponds to each group size. The service time for a group is calculated as the highest of all the customers who make up the group. The emergency arrival can occur at any time and when the emergency arrival occurs the batch which is in the service station will be placed at the head of the queue. Service to the emergency arrival follows exponential distribution. The customers in the pool may renege when the server is busy with an emergency. The matrix geometric method was used to obtain the steady state probabilities and we generated few performance measures. We have studied the busy time and calculated the distribution of waiting times. Results are illustrated with some graphical representations
(R2113) A Numerical Method for Solving Linear First-Order Volterra Integro-Differential Equations with Integral Boundary Condition
Full text linkWe investigate an efficient numerical method for the linear first-order Volterra integro-differential equations with integral boundary condition. To solve this problem, boundaries are determined for its derivative and the solution. The numerical solutions of the problem are modeled over a uniform mesh using the composite right-side rectangle concept for the integral component and the implicit difference rules for the differential component. Next, the stability and convergence of the numerical approach are discussed. The numerical experiments are presented confirming the accuracy of the proposed scheme
Stability of Predator-Prey Model for Worm Attack in Wireless Sensor Networks
Full text linkIn this paper, we propose a predator-prey mathematical model for analyzing the dynamical behaviors of the system. This system is an epidemic model, and it is capable of ascertaining the worm\u27s spreading at the initial stage and improving the security of wireless sensor networks. We investigate different fixed points and examine the stability of the projected model
The Adultification Of African American Girls: Perceptions, Experiences, And Impact On Behavior
Full text linkAdultification occurs when adults treat children like they are more mature than they are. This is particularly likely to happen to African American children (Pope, 2022). Adultification in homes is the result of deficits in the adult figures; however, adultification outside of the family, cemented with implicit biases, has negative consequences for young African American children (Cooke & Halberstadt, 2021). These biases can negatively impact their self-concept. Furthermore, it may jeopardize their health, education, experiences with discipline, and likelihood of contact with the justice system (Koch & Kozhumam, 2022).
This qualitative descriptive study utilized focus groups of primarily young adults between 18 and 26 to understand their perceptions, experiences, attitudes, values, and opinions regarding young African American girls and their possible adultification. The data were collected from 13 focus groups. There were five groups of young African American girls, three groups of young African American boys, two groups of Non-African American girls, two groups of Non-African American boys, and one group of older African American women.
Data were analyzed with manual coding and with the aid of Atlas-ti qualitative data management program to identify emic codes, patterns, and themes in the responses. The preliminary code list, called etic codes, included concepts such as victimization, coping behaviors, use of physical violence in self-defense, and the likelihood of adultifying others. The findings indicated that adultification was a source of underlying trauma, which in turn triggered a resistance response as a form of resilience specific to African American girls. Several themes were identified: Familial Expectations, Differential Treatment, Independence, Proximity and Contrast to White Femininity, Perceived as “Loud” and “Rowdy,” Dichotomous Image – Mature Early yet Seen as Slow, A Need for Defensiveness, Coping and Resilience, and Intersection of Gender and Race. The results offer insights for re-educating parents, school, and justice system personnel toward improved trajectories and life outcomes for African American girls. The study adds to the literature on how to dismantle common misperceptions of African American girls because adultifying them has the potential of putting them into the “school-to-prison pipeline.”
Keywords: African American girls, experiences, expectations, schools, white femininity, qualitativ
School Shootings In The United States: An Analysis Of Micro And Macro Level Variables
Full text linkIn 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
Faculty perspectives on research mentoring across a multi-level statewide LSAMP Alliance
Full text linkIn this, mixed-method exploratory sequential design study, we examined a multi-level state-wide mentoring program for underrepresented students in science, technology, engineering, and mathematics (STEM). This study examined faculty perspectives on the factors involved in, and the impact of, mentoring minoritized students at the critical retention-to-graduation stage. Between 2020 and 2022, an online survey and two rounds of focus group interviews were conducted with faculty members at participating institutions. Data were analyzed using an iterative, thematic coding method. Analysis of the comments from faculty focus groups and a faculty survey revealed eleven themes that codified the faculty member’s perspectives on mentoring. Specifically, to support underrepresented STEM students during the critical retention-to-graduation stage from community college to doctoral degree achievement. This manuscript focuses on the faculty research question and examines the themes that emerged and the perspectives of the faculty mentors on mentoring
Sustainable Energy-Generating Pads As Future Alternative Energy Source For Road Infrastructure
Full text linkThe world is experiencing a significant environmental crisis due to its dependence on fossil fuels for energy and transportation, which is leading to global warming and climate change. The global climate crisis demonstrates the urgent need to transition to renewable energy sources, making research on sustainable energy-generating systems increasingly important. PZT cells present an alternative energy-generating source but face challenges such as brittleness, low-frequency operation, and high-temperature sensitivity, which cause performance degradation. Additionally, issues like impedance matching and fluctuations in PZT-based energy systems contribute to significant energy generation losses. Research into composite materials, design optimizations, temperature-stabilized materials, fabrication techniques, and advanced power electronics is essential to enhance system efficiency. This research focuses on the sustainable energy-generating pad (SEGP), which harnesses energy for lightweight vehicles like bicycles and electric bikes. The SEGP consists of multiple layers of thin-film PZT cells, energy collector circuits, and multi-composite material, effectively converting mechanical vibrations and kinetic energy into
clean electricity. Software simulations show that the first-generation SEGP (SEGP1X) generates 0.59–1.35 W/ride/0.34Sec with up to 450 lbs of force applied, while the second-generation SEGP (SEGP2X) produces 1.42–3.42 W/ride/0.34Sec. However, in prototype testing, SEGP1X generates 0.33–0.41 W per ride, and SEGP2X generates 0.54–0.67 W per ride, based on a rider and bicycle weight of approximately 160 lbs, demonstrating the potential of this technology. Effective energy storage and collection systems are fundamental requirements for the success of any renewable energy source. To ensure stable operation and maximize energy storage, a smart dual-stage charging system (DSCS) with a round-trip efficiency of around 95% has been developed, particularly for non-sinusoidal and fluctuating energy systems. The SEGP system is integrated with existing PV technology and connected to a grid, forming a grid-tied hybrid energy microgrid system. This setup serves as a test case to evaluate the SEGP\u27s efficiency, feasibility, and potential for real-world implementation. The generated energy can be used for water purification and e-charging, with any surplus energy sold to a utility company. A techno-economic analysis reveals a seven-year return on investment for a ten-year project, highlighting the economic viability of SEGP technology.
Index Terms – SEGP, Thin-film PZT, DSCS, Techno-economi
Comparative Analysis Of Inference Performance Of Pretrained Deep Learning Models In Analog Accelerators
Full text linkResistive crossbars using non-volatile memory devices have become promising components for implementing Deep Neural Network (DNN) in hardware. However, crossbar-based computations encounter a notable challenge due to device and circuit-level non-idealities. In this study, we explored three recent crossbar simulation tools, namely, AIHWKIT, CrossSim, and MemTorch, and evaluated four pre-trained DNNs for image classification on CIFAR-100 dataset using these tools. All three tools had strong analog simulation functionalities that effectively mimicked the actual hardware environment. To the best of our knowledge, this is the first study using all three simulation tools of analog accelerators, representing three distinctive hardware settings, to evaluate DNN robustness under analog noise and nonlinearities. We first tested the robustness of four DNNs (VGG19, InceptionV3, ResNet50, & MobilenetV2) using different levels of white Gaussian noise as baselines. Then we evaluated their inference performance on the three tools to determine their resilience to analog noise and nonlinearities in hardware environment. Results showed that using CIFAR-100 while all DNNs suffered performance degradation as expected. ResNet50 outperforms outperformed others in two out of three simulators despite real-world hardware
imperfections due to its deep structure. Specifically, the ResNet50 model showed a mere 3% performance drop in CrossSim and, interestingly, a two percent improvement in AIHWKIT. At the same time, InceptionV3 exhibits only a three percent drop from its baseline, while the performance of three other models declined by 12-19% in MemTorch underscoring InceptionV3’s resilience in MemTorch environment. Later, we extended our analysis of the analog DNNs to MNIST and SVHN datasets, finding that ResNet50 and InceptionV3 outperform their digital counterparts on both datasets. This indicated that model design of DNNs played an important role in their resilience to analog noise and nonlinearities, and their inference performance also depends on specific hardware implementation.
Index Terms − Deep Neural Networks, CrossSim, AIHWKIT, MemTorch, Crossbar Simulatio
(R2082) Two New Operations and Extended Modal Operators on Bipolar Pythagorean Fuzzy Matrices
Full text linkIn this paper, two novel binary operations concerning bipolar Pythagorean fuzzy matrices are delineated. Several algebraic properties, such as commutativity and associativity, are explored. Additionally, extended modal operators for Bipolar Pythagorean fuzzy matrices are introduced. Subsequently, these methodologies are applied to a decision-making scenario wherein a scoring matrix is formulated and alternatives are ranked according to their cumulative score values